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Sample records for homeostasis predicts dynamics

  1. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

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    Giovanni Dalmasso

    Full Text Available Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis and the removal of damaged mitochondria by selective autophagy (mitophagy. While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1 mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2 restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3 maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4 our model suggests sources of, and stress conditions

  2. Dynamic thiol/disulphide homeostasis in patients with basal cell carcinoma.

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    Demirseren, Duriye Deniz; Cicek, Cagla; Alisik, Murat; Demirseren, Mustafa Erol; Aktaş, Akın; Erel, Ozcan

    2017-09-01

    The aim of this study is to measure and compare the dynamic thiol/disulphide homeostasis of patients with basal cell carcinoma and healthy subjects with a newly developed and original method. Thirty four patients attending our outpatient clinic and clinically and histopathologically diagnosed as nodular basal cell carcinoma, and age and gender matched 30 healthy individuals have been involved in the study. Thiol/disulphide homeostasis tests have been measured with a novel automatic spectrophotometric method developed and the results have been compared statistically. Serum native thiol and disulphide levels in the patient and control group show a considerable variance statistically (p = 0.028, 0.039, respectively). Total thiol levels do not reveal a considerable variation (p = 0.094). Disulphide/native thiol ratios and native thiol/total thiol ratios also show a considerable variance statistically (p = 0.012, 0.013, 0.010, respectively). Thiol disulphide homeostasis in patients with basal cell carcinoma alters in the way that disulphide gets lower and thiols get higher. Thiol/disulphide level is likely to have a role in basal cell carcinoma pathogenesis.

  3. Utility of Childhood Glucose Homeostasis Variables in Predicting Adult Diabetes and Related Cardiometabolic Risk Factors

    OpenAIRE

    Nguyen, Quoc Manh; Srinivasan, Sathanur R.; Xu, Ji-Hua; Chen, Wei; Kieltyka, Lyn; Berenson, Gerald S.

    2009-01-01

    OBJECTIVE This study examines the usefulness of childhood glucose homeostasis variables (glucose, insulin, and insulin resistance index [homeostasis model assessment of insulin resistance {HOMA-IR}]) in predicting pre-diabetes and type 2 diabetes and related cardiometabolic risk factors in adulthood. RESEARCH DESIGN AND METHODS This retrospective cohort study consisted of normoglycemic (n = 1,058), pre-diabetic (n = 37), and type 2 diabetic (n = 25) adults aged 19–39 years who were followed o...

  4. Bistable dynamics underlying excitability of ion homeostasis in neuron models.

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    Niklas Hübel

    2014-05-01

    Full Text Available When neurons fire action potentials, dissipation of free energy is usually not directly considered, because the change in free energy is often negligible compared to the immense reservoir stored in neural transmembrane ion gradients and the long-term energy requirements are met through chemical energy, i.e., metabolism. However, these gradients can temporarily nearly vanish in neurological diseases, such as migraine and stroke, and in traumatic brain injury from concussions to severe injuries. We study biophysical neuron models based on the Hodgkin-Huxley (HH formalism extended to include time-dependent ion concentrations inside and outside the cell and metabolic energy-driven pumps. We reveal the basic mechanism of a state of free energy-starvation (FES with bifurcation analyses showing that ion dynamics is for a large range of pump rates bistable without contact to an ion bath. This is interpreted as a threshold reduction of a new fundamental mechanism of ionic excitability that causes a long-lasting but transient FES as observed in pathological states. We can in particular conclude that a coupling of extracellular ion concentrations to a large glial-vascular bath can take a role as an inhibitory mechanism crucial in ion homeostasis, while the Na⁺/K⁺ pumps alone are insufficient to recover from FES. Our results provide the missing link between the HH formalism and activator-inhibitor models that have been successfully used for modeling migraine phenotypes, and therefore will allow us to validate the hypothesis that migraine symptoms are explained by disturbed function in ion channel subunits, Na⁺/K⁺ pumps, and other proteins that regulate ion homeostasis.

  5. Linking stoichiometric homeostasis of microorganisms with soil phosphorus dynamics in wetlands subjected to microcosm warming.

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    Hang Wang

    Full Text Available Soil biogeochemical processes and the ecological stability of wetland ecosystems under global warming scenarios have gained increasing attention worldwide. Changes in the capacity of microorganisms to maintain stoichiometric homeostasis, or relatively stable internal concentrations of elements, may serve as an indicator of alterations to soil biogeochemical processes and their associated ecological feedbacks. In this study, an outdoor computerized microcosm was set up to simulate a warmed (+5°C climate scenario, using novel, minute-scale temperature manipulation technology. The principle of stoichiometric homeostasis was adopted to illustrate phosphorus (P biogeochemical cycling coupled with carbon (C dynamics within the soil-microorganism complex. We hypothesized that enhancing the flux of P from soil to water under warming scenarios is tightly coupled with a decrease in homeostatic regulation ability in wetland ecosystems. Results indicate that experimental warming impaired the ability of stoichiometric homeostasis (H to regulate biogeochemical processes, enhancing the ecological role of wetland soil as an ecological source for both P and C. The potential P flux from soil to water ranged from 0.11 to 34.51 mg m(-2 d(-1 in the control and 0.07 to 61.26 mg m(-2 d(-1 in the warmed treatment. The synergistic function of C-P acquisition is an important mechanism underlying C∶P stoichiometric balance for soil microorganisms under warming. For both treatment groups, strongly significant (p<0.001 relationships fitting a negative allometric power model with a fractional exponent were found between n-HC∶P (the specialized homeostatic regulation ability as a ratio of soil highly labile organic carbon to dissolved reactive phosphorus in porewater and potential P flux. Although many factors may affect soil P dynamics, the n-HC∶P term fundamentally reflects the stoichiometric balance or interactions between the energy landscape (i.e., C and flow of

  6. The homeostasis solution – Mechanical homeostasis in architecturally homeostatic buildings

    International Nuclear Information System (INIS)

    Wang, Lin-Shu; Ma, Peizheng

    2016-01-01

    Highlights: • Architectural homeostatic buildings (AHBs) make sense because of the laws of physics. • However, high efficiency can be obtained only with AHBs and equipment considered as systems. • Mechanical homeostasis facilitates AHB-equipment system synergy with heat extraction. • Entropically speaking a building needs neither energy nor a fixed amount of heat, but its homeostatic existence. • Homeostatic buildings can reduce building energy consumption from 80% to 90%. - Abstract: We already know, for energy-saving potential, the necessary architectural features in well-designed buildings: high performance building envelope, sufficient interior thermal mass, and hydronic-network activated radiant surfaces for cooling and heating. Buildings with these features may be referred to as architecturally homeostatic buildings (AHBs); such a building-system is thermally semi-autonomous in the sense that its temperature variation stays within a certain range even without conditioning equipment, and, with conditioning equipment in operation, its thermal regulation is handled by its hydronic heat-distribution-network for controlling the temperature level of the building. At the present time conventional HVAC equipment is used for maintaining the heat-distribution-network: this arrangement, however, has resulted in great energy saving only for AHBs with accessible natural water bodies. In operation of general AHBs, a case is made here for a new kind of mechanical equipment having the attribute of mechanical homeostasis (MH). MH is a new energy transformation concept in a triadic framework. Superlative energy efficiency is predicted as a result of combined improvements in higher triadCOPs and lower total (inducted + removed) heat rates—evincing existence of synergy in architectural and mechanical homeostasis, which together will be referred to as the homeostasis solution.

  7. The S-Lagrangian and a theory of homeostasis in living systems

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    Sandler, U.; Tsitolovsky, L.

    2017-04-01

    A major paradox of living things is their ability to actively counteract degradation in a continuously changing environment or being injured through homeostatic protection. In this study, we propose a dynamic theory of homeostasis based on a generalized Lagrangian approach (S-Lagrangian), which can be equally applied to physical and nonphysical systems. Following discoverer of homeostasis Cannon (1935), we assume that homeostasis results from tendency of the organisms to decrease of the stress and avoid of death. We show that the universality of homeostasis is a consequence of analytical properties of the S-Lagrangian, while peculiarities of the biochemical and physiological mechanisms of homeostasis determine phenomenological parameters of the S-Lagrangian. Additionally, we reveal that plausible assumptions about S-Lagrangian features lead to good agreement between theoretical descriptions and observed homeostatic behavior. Here, we have focused on homeostasis of living systems, however, the proposed theory is also capable of being extended to social systems.

  8. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  9. Dynamical Predictability of Monthly Means.

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    Shukla, J.

    1981-12-01

    We have attempted to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. We have extended the concept of `classical' predictability, which primarily refers to the lack of predictability due mainly to the instabilities of synoptic-scale disturbances, to the predictability of time averages, which are determined by the predictability of low-frequency planetary waves. We have carded out 60-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperature, snow, sea ice and soil moisture. Three of these initial conditions are the observed atmospheric conditions on 1 January of 1975, 1976 and 1977. The other six initial conditions are obtained by superimposing over the observed initial conditions a random perturbation comparable to the errors of observation. The root-mean-square (rms) error of random perturbations at all the grid points and all the model levels is 3 m s1 in u and v components of wind. The rms vector wind error between the observed initial conditions is >15 m s1.It is hypothesized that for a given averaging period, if the rms error among the time averages predicted from largely different initial conditions becomes comparable to the rms error among the time averages predicted from randomly perturbed initial conditions, the time averages are dynamically unpredictable. We have carried out the analysis of variance to compare the variability, among the three groups, due to largely different initial conditions, and within each group due to random perturbations.It is found that the variances among the first 30-day means, predicted from largely different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, whereas the variances among 30-day means for days 31-60 are not distinguishable from the variances due to random initial

  10. Dynamic thiol/disulfide homeostasis and effects of smoking on homeostasis parameters in patients with psoriasis.

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    Emre, Selma; Demirseren, Duriye Deniz; Alisik, Murat; Aktas, Akin; Neselioglu, Salim; Erel, Ozcan

    2017-12-01

    Recently, increased reactive oxygen species (ROS), reduced antioxidant capacity, and oxidative stress have been suggested in the pathogenesis of psoriasis. The aim of this study to evaluate the thiol/disulfide homeostasis in patients with psoriasis. Ninety patients with psoriasis who did not receive any systemic treatment in the last six  months were included in the study. Seventy-six age and gender-matched healthy volunteers served as control group. Thiol/disulfide homeostasis was measured in venous blood samples obtained from patient and control groups. Native thiol and total thiol levels were significantly higher in patients than in control group. When thiol/disulfide hemostasis parameters and clinical and demographic characteristics were compared, a negative correlation was detected between native thiol and total thiol with age. The levels of total thiols had also negative correlation with PASI and duration of the disease. When we divided the patients into smokers and non-smokers, native thiol and total thiol levels were significantly higher in smokers than in controls, whereas native thiol and total thiol levels were comparable in non-smoker patients and controls. Thiol/disulfide balance shifted towards thiol in psoriasis patients and this may be responsible for increased keratinocyte proliferation in the pathogenesis of psoriasis.

  11. pH and Ion Homeostasis on Plant Endomembrane Dynamics: Insights from structural models and mutants of K+/H+ antiporters.

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    Sze, Heven; Chanroj, Salil

    2018-04-24

    Plants remodel their cells through the dynamic endomembrane system. Intracellular pH is important for membrane trafficking, but the determinants of pH homeostasis are poorly defined in plants. Electrogenic proton (H+) pumps depend on counter-ion fluxes to establish transmembrane pH gradients at the plasma membrane and endomembranes. Vacuolar-type H+-ATPase-mediated acidification of the trans-Golgi network (TGN) is crucial for secretion and membrane recycling. Pump and counter-ion fluxes are unlikely to fine-tune pH; rather, alkali cation/H+ antiporters, which can alter pH and/or cation homeostasis locally and transiently, are prime candidates. Plants have a large family of predicted cation/H+ exchangers (CHX) of obscure function, in addition to the well-studied K+(Na+)/H+ exchangers (NHX). Here, we review the regulation of cytosolic and vacuolar pH, highlighting the similarities and distinctions of NHX and CHX members. In planta, alkalinization of the TGN or vacuole by NHXs promotes membrane trafficking, endocytosis, cell expansion, and growth. CHXs localize to endomembranes and/or the plasma membrane, contribute to male fertility, pollen tube guidance, pollen wall construction, stomatal opening, and in soybean (Glycine max), tolerance to salt stress. Three-dimensional structural models and mutagenesis of Arabidopsis thaliana genes have allowed us to infer that AtCHX17 and AtNHX1 share a global architecture and a translocation core like bacterial Na+/H+ antiporters. Yet the presence of distinct residues suggests some CHXs differ from NHXs in pH sensing and electrogenicity. How H+ pumps, counter-ion fluxes, and cation/H+ antiporters are linked with signaling and membrane trafficking to remodel membranes and cell walls awaits further investigation. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.

  12. Evaluation of Dynamic Disulphide/Thiol Homeostasis in Silica Exposed Workers

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    Meşide Gündüzöz

    2017-04-01

    Full Text Available Background: Oxidative stress is implicated as one of the main molecular mechanism underlying silicosis. Aims: In this study, our aim was to asses the redox status in occupationally silica-exposed workers, by evaluating the dynamic thiol-disulphide homeostasis. Study Design: Case-control study. Methods: Thirty-six male workers occupationally exposed to silica particles and 30 healthy volunteers, working as office workers were included to the study. Posteroanterior chest radiographs and pulmonary function tests of both groups were evaluated. Also serum thiol disulphide levels were measured using the spectrophotometric method described by Erel and Neşelioğlu. Results: Among the 36 workers that underwent pulmonary function tests 6 (17% had obstructive, 7 (19% had restrictive, 6 (17% had obstructive and restrictive signs whereas 17 (47% had no signs. The mean PFTs results of silica-exposed workers were significantly lower than control subjects. The serum disulphide levels of silica-exposed workers were significantly higher than control subjects (23.84±5.89 μmol/L and 21.18±3.44 μmol/L, respectively p=0.02. Conclusion: The serum disulphide levels, a biomarker of oxidative stress, are found to be higher in silica-exposed workers

  13. Predictable nonlinear dynamics: Advances and limitations

    International Nuclear Information System (INIS)

    Anosov, L.A.; Butkovskii, O.Y.; Kravtsov, Y.A.; Surovyatkina, E.D.

    1996-01-01

    Methods for reconstruction chaotic dynamical system structure directly from experimental time series are described. Effectiveness of general methods is illustrated with the results of numerical simulation. It is of common interest that from the single time series it is possible to reconstruct a set of interconnected variables. Predictive power of dynamical models, provided by the nonlinear dynamics inverse problem solution, is limited firstly by the noise level in the system under study and is characterized by the horizon of predictability. New physical results are presented, concerning nonstationary and bifurcation nonlinear systems: (1) algorithms for revealing of nonstationarity in random-like chaotic time-series are suggested based on discriminant analysis with nonlinear discriminant function; (2) an opportunity is established to predict the final state in bifurcation system with quickly varying control parameters; (3) hysteresis is founded out in bifurcation system with quickly varying parameters; (4) delayed correlation left-angle noise-prediction error right-angle in chaotic systems is revealed. copyright 1996 American Institute of Physics

  14. Transcranial electrical stimulation accelerates human sleep homeostasis.

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    Davide Reato

    Full Text Available The sleeping brain exhibits characteristic slow-wave activity which decays over the course of the night. This decay is thought to result from homeostatic synaptic downscaling. Transcranial electrical stimulation can entrain slow-wave oscillations (SWO in the human electro-encephalogram (EEG. A computational model of the underlying mechanism predicts that firing rates are predominantly increased during stimulation. Assuming that synaptic homeostasis is driven by average firing rates, we expected an acceleration of synaptic downscaling during stimulation, which is compensated by a reduced drive after stimulation. We show that 25 minutes of transcranial electrical stimulation, as predicted, reduced the decay of SWO in the remainder of the night. Anatomically accurate simulations of the field intensities on human cortex precisely matched the effect size in different EEG electrodes. Together these results suggest a mechanistic link between electrical stimulation and accelerated synaptic homeostasis in human sleep.

  15. State-dependent intrinsic predictability of cortical network dynamics.

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    Leila Fakhraei

    Full Text Available The information encoded in cortical circuit dynamics is fleeting, changing from moment to moment as new input arrives and ongoing intracortical interactions progress. A combination of deterministic and stochastic biophysical mechanisms governs how cortical dynamics at one moment evolve from cortical dynamics in recently preceding moments. Such temporal continuity of cortical dynamics is fundamental to many aspects of cortex function but is not well understood. Here we study temporal continuity by attempting to predict cortical population dynamics (multisite local field potential based on its own recent history in somatosensory cortex of anesthetized rats and in a computational network-level model. We found that the intrinsic predictability of cortical dynamics was dependent on multiple factors including cortical state, synaptic inhibition, and how far into the future the prediction extends. By pharmacologically tuning synaptic inhibition, we obtained a continuum of cortical states with asynchronous population activity at one extreme and stronger, spatially extended synchrony at the other extreme. Intermediate between these extremes we observed evidence for a special regime of population dynamics called criticality. Predictability of the near future (10-100 ms increased as the cortical state was tuned from asynchronous to synchronous. Predictability of the more distant future (>1 s was generally poor, but, surprisingly, was higher for asynchronous states compared to synchronous states. These experimental results were confirmed in a computational network model of spiking excitatory and inhibitory neurons. Our findings demonstrate that determinism and predictability of network dynamics depend on cortical state and the time-scale of the dynamics.

  16. Homeostasis as the Mechanism of Evolution

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    John S. Torday

    2015-09-01

    Full Text Available Homeostasis is conventionally thought of merely as a synchronic (same time servo-mechanism that maintains the status quo for organismal physiology. However, when seen from the perspective of developmental physiology, homeostasis is a robust, dynamic, intergenerational, diachronic (across-time mechanism for the maintenance, perpetuation and modification of physiologic structure and function. The integral relationships generated by cell-cell signaling for the mechanisms of embryogenesis, physiology and repair provide the needed insight to the scale-free universality of the homeostatic principle, offering a novel opportunity for a Systems approach to Biology. Starting with the inception of life itself, with the advent of reproduction during meiosis and mitosis, moving forward both ontogenetically and phylogenetically through the evolutionary steps involved in adaptation to an ever-changing environment, Biology and Evolution Theory need no longer default to teleology.

  17. Dynamic optimal control of homeostasis: an integrative system approach for modeling of the central nitrogen metabolism in Saccharomyces cerevisiae.

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    van Riel, N A; Giuseppin, M L; Verrips, C T

    2000-01-01

    The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the source of the cellular amino acids and proteins, including flavors and potentially valuable biomolecules; therefore, it is also of industrial interest. In the DOMC approach the cell is regarded as an optimally controlled system. Given the metabolic genotype, the cell faces a control problem to maintain an optimal flux distribution in a changing environment. The regulation is based on strategies and balances feedback control of homeostasis and feedforward regulation for adaptation. The DOMC approach is an integrative, holistic approach, not based on mechanistic descriptions and (therefore) not biased by the variation present in biochemical and molecular biological data. It is an effective tool to structure the rapidly increasing amount of data on the function of genes and pathways. The DOMC model is used successfully to predict the responses of pulses of ammonia and glutamine to nitrogen-limited continuous cultures of a wild-type strain and a glutamine synthetase-negative mutant. The simulation results are validated with experimental data.

  18. Descriptive Modeling of the Dynamical Systems and Determination of Feedback Homeostasis at Different Levels of Life Organization.

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    Zholtkevych, G N; Nosov, K V; Bespalov, Yu G; Rak, L I; Abhishek, M; Vysotskaya, E V

    2018-05-24

    The state-of-art research in the field of life's organization confronts the need to investigate a number of interacting components, their properties and conditions of sustainable behaviour within a natural system. In biology, ecology and life sciences, the performance of such stable system is usually related to homeostasis, a property of the system to actively regulate its state within a certain allowable limits. In our previous work, we proposed a deterministic model for systems' homeostasis. The model was based on dynamical system's theory and pairwise relationships of competition, amensalism and antagonism taken from theoretical biology and ecology. However, the present paper proposes a different dimension to our previous results based on the same model. In this paper, we introduce the influence of inter-component relationships in a system, wherein the impact is characterized by direction (neutral, positive, or negative) as well as its (absolute) value, or strength. This makes the model stochastic which, in our opinion, is more consistent with real-world elements affected by various random factors. The case study includes two examples from areas of hydrobiology and medicine. The models acquired for these cases enabled us to propose a convincing explanation for corresponding phenomena identified by different types of natural systems.

  19. Evaluation of dynamic serum thiol/disulfide homeostasis in locally advanced and metastatic gastric cancer

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    Mutlu Hizal

    2018-04-01

    Full Text Available Background: Gastric cancer is one the most diagnosed cancer and the third leading cause of death from cancer worldwide. As an indicator of antioxidant capacity thiol/disulfide homeostasis regulates detoxification, cell signal mechanisms, apoptosis, transcription and antioxidant defense mechanisms. Disregulation of thiol/disulfide homeostasis identified in other cancer types by recent data. In this study, we aimed to evaluate the thiol/disulfide homeostasis in advanced gastric cancer patients. Methods: The patients who diagnosed with gastric cancer and healthy control subjects were included to study. Serum samples for the thiol-disulphide test were obtained at the time of diagnosis. Thiol-disulphide homeostasis tests were measured by the automated spectrophotometric method. Thiol-disulphide homeostasis was also measured according to clinical and laboratory features. Results: Thirty newly diagnosed advanced gastric adenocarcinoma patients and 28 healthy controls were enrolled in the study. The native thiol (NT and total thiol (TT levels of patients' group were significantly lower compared with controls (p = 0.001 and p < 0.001. In the CEA high (≥5.4 ng/ml group, DS/NT ratio were higher compared with CEA low (<5.4 ng/ml group (p = 0.024. In CA.19-9 high (≥28.3 kU/L group, both DS and DS/NT ratio were significantly higher compared with a CA19-9 low(<28.3 kU/L group (p < 0.05 both. The correlation between CEA and DS levels was also significant (p = 0.02. There was also a positive correlation between CEA levels and DS/NT ratio (p = 0.01. Conclusion: Derangements of thiol/disulfide homeostasis may have a role in gastric cancer pathogenesis and the higher level of oxidative stress may relate to extensive and aggressiveness of the advanced disease. The diagnostic and prognostic values of thiol/disulfide products need to identify with further studies. Keywords: Thiol, Disulfide, Oxidative stress, Gastric cancer, Metastatic

  20. A new theoretical approach to the functional meaning of sleep and dreaming in humans based on the maintenance of 'predictive psychic homeostasis'.

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    Agnati, Luigi F; Barlow, Peter W; Baluška, František; Tonin, Paolo; Guescini, Michele; Leo, Giuseppina; Fuxe, Kjell

    2011-11-01

    Different theories have been put forward during the last decade to explain the functional meaning of sleep and dreaming in humans. In the present paper, a new theory is presented which, while taking advantage of these earlier theories, introduces the following new and original aspects:   • Circadian rhythms relevant to various organs of the body affect the reciprocal interactions which operate to maintain constancy of the internal milieu and thereby also affect the sleep/wakefulness cycle. Particular attention is given to the constancy of natraemia and osmolarity and to the permissive role that the evolution of renal function has had for the evolution of the central nervous system and its integrative actions. • The resetting of neuro-endocrine controls at the onset of wakefulness leads to the acquisition of new information and its integration within previously stored memories. This point is dealt with in relation to Moore-Ede's proposal for the existence of a 'predictive homeostasis'. • The concept of 'psychic homeostasis' is introduced and is considered as one of the most important states since it is aimed at the well-being, or eudemonia, of the human psyche. Sleep and dreaming in humans are discussed as important functions for the maintenance of a newly proposed composite state: that of 'predictive psychic homeostasis'. On the basis of these assumptions, and in accordance with the available neurobiological data, the present paper puts forward the novel hypothesis that sleep and dreaming play important functions in humans by compensating for psychic allostatic overloads. Hence, both consolatory dreams and disturbing nightmares can be part of the vis medicatrix naturae, the natural healing power, in this case, the state of eudemonia.

  1. Analysis of vegetative homeostasis state of elite handball players

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    Y.N. Prystupa

    2015-12-01

    Full Text Available Purpose: to study characteristics and dynamic of elite handball players’ physiological indicators. Material: In experiment elite handball players (n=112, age 18-35 years participated. For determination of vegetative homeostasis state we analyzed variability of heart rhythm. The researches were conducted in laboratory conditions in rest state, in lying position during 5 minutes. Results: it was found that organism’s adaptation reactions to training loads go with different tension of regulation systems. At the end of competition period there appears hyper-kinetic syndrome. It witnessed insufficiency of means, which permit to maintain optimal regulation of cardio-vascular system and increase its functional potentials. Conclusions: indicators of cardio-vascular system and their dynamic w3itnessed maintaining of high level of handball players’ organism hemodynamic provisioning. High level of vegetative homeostasis pointed at certain degree of sportsmen’s fitness. Such state is sufficient for preservation of high potential of sympathetic -adrenaline system and overcoming of fatigue processes.

  2. Role of Snf3 in glucose homeostasis of Saccharomyces cerevisiae (review)

    DEFF Research Database (Denmark)

    Kielland-Brandt, Morten

    signal pathways in directions opposite to those caused by extracellular nutrients (6,7), a phenomenon predicted to contribute to intracellular nutrient homeostasis. Although significant, the influence of intracellular leucine on signaling from Ssy1 is relatively modest (6), whereas the conditions...... with enhanced intracellular glucose concentrations (7) caused a strong decrease in signaling from Snf3, suggesting an important role of Snf3 in intracellular glucose homeostasis. Strategies for studies of this role will be discussed....

  3. Lifespan extension by preserving proliferative homeostasis in Drosophila.

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    Benoît Biteau

    2010-10-01

    Full Text Available Regenerative processes are critical to maintain tissue homeostasis in high-turnover tissues. At the same time, proliferation of stem and progenitor cells has to be carefully controlled to prevent hyper-proliferative diseases. Mechanisms that ensure this balance, thus promoting proliferative homeostasis, are expected to be critical for longevity in metazoans. The intestinal epithelium of Drosophila provides an accessible model in which to test this prediction. In aging flies, the intestinal epithelium degenerates due to over-proliferation of intestinal stem cells (ISCs and mis-differentiation of ISC daughter cells, resulting in intestinal dysplasia. Here we show that conditions that impair tissue renewal lead to lifespan shortening, whereas genetic manipulations that improve proliferative homeostasis extend lifespan. These include reduced Insulin/IGF or Jun-N-terminal Kinase (JNK signaling activities, as well as over-expression of stress-protective genes in somatic stem cell lineages. Interestingly, proliferative activity in aging intestinal epithelia correlates with longevity over a range of genotypes, with maximal lifespan when intestinal proliferation is reduced but not completely inhibited. Our results highlight the importance of the balance between regenerative processes and strategies to prevent hyperproliferative disorders and demonstrate that promoting proliferative homeostasis in aging metazoans is a viable strategy to extend lifespan.

  4. Hedgehog Signaling and Maintenance of Homeostasis in the Intestinal Epithelium

    NARCIS (Netherlands)

    Büller, Nikè V. J. A.; Rosekrans, Sanne L.; Westerlund, Jessica; van den Brink, Gijs R.

    2012-01-01

    Homeostasis of the rapidly renewing intestinal epithelium depends on a balance between cell proliferation and loss. Indian hedgehog (Ihh) acts as a negative feedback signal in this dynamic equilibrium. We discuss recent evidence that Ihh may be one of the key epithelial signals that indicates

  5. Thiol/disulphide homeostasis in celiac disease

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    Kaplan, Mustafa; Ates, Ihsan; Yuksel, Mahmut; Ozderin Ozin, Yasemin; Alisik, Murat; Erel, Ozcan; Kayacetin, Ertugrul

    2017-01-01

    AIM To determine dynamic thiol/disulphide homeostasis in celiac disease and to examine the associate with celiac autoantibodies and gluten-free diet. METHODS Seventy three patients with celiac disease and 73 healthy volunteers were enrolled in the study. In both groups, thiol/disulphide homeostasis was examined with a new colorimetric method recently developed by Erel and Neselioglu. RESULTS In patients with celiac disease, native thiol (P = 0.027) and total thiol (P = 0.031) levels were lower, while disulphide (P < 0.001) level, disulphide/native thiol (P < 0.001) and disulphide/total thiol (P < 0.001) ratios were higher compared to the control group. In patients who do not comply with a gluten-free diet, disulphide/native thiol ratio was found higher compared to the patients who comply with the diet (P < 0.001). In patients with any autoantibody-positive, disulphide/native thiol ratio was observed higher compared to the patients with autoantibody-negative (P < 0.05). It is found that there is a negative correlation between celiac autoantibodies, and native thiol, total thiol levels and native thiol/total thiol ratio, while a positive correlation is observed between disulphide, disulphide/native thiol and disulphide/total thiol levels. CONCLUSION This study is first in the literature which found that the patients with celiac disease the dynamic thiol/disulphide balance shifts through disulphide form compared to the control group. PMID:28533921

  6. Dynamic Algorithm for LQGPC Predictive Control

    DEFF Research Database (Denmark)

    Hangstrup, M.; Ordys, A.W.; Grimble, M.J.

    1998-01-01

    In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated into the control......In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated...... into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive, e.g. GPS is that LQGPC enables...

  7. Chemistry Misconceptions Associated with Understanding Calcium and Phosphate Homeostasis

    Science.gov (United States)

    Cliff, William H.

    2009-01-01

    Successful learning of many aspects in physiology depends on a meaningful understanding of fundamental chemistry concepts. Two conceptual diagnostic questions measured student understanding of the chemical equilibrium underlying calcium and phosphate homeostasis. One question assessed the ability to predict the change in phosphate concentration…

  8. Predictability in community dynamics.

    Science.gov (United States)

    Blonder, Benjamin; Moulton, Derek E; Blois, Jessica; Enquist, Brian J; Graae, Bente J; Macias-Fauria, Marc; McGill, Brian; Nogué, Sandra; Ordonez, Alejandro; Sandel, Brody; Svenning, Jens-Christian

    2017-03-01

    The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no-lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay. However, more complex dynamics are possible and may lead to memory effects and alternate unstable states. We develop graphical and analytic methods for assessing these scenarios and show that these dynamics can appear in even simple models. The overall implications are that (1) complex community dynamics may be common and (2) detailed knowledge of past climate change and community states will often be necessary yet sometimes insufficient to make predictions of a community's future state. © 2017 John Wiley & Sons Ltd/CNRS.

  9. Prediction of a required dynamic torque for motor-operated butterfly valves

    International Nuclear Information System (INIS)

    Bae, J. H.; Lee, K. N.; Jeong, W. K.

    2002-01-01

    This study describes the methodology for predicting a required dynamic torque in motor-operated butterfly valves. The results of this methodology have been compared with test data for motor-operated butterfly valves in nuclear power plant. With the close review of test data and torque prediction, it is concluded that the prediction methodology is conservative to predict a required dynamic torque of motor-operated butterfly valves. In addition, the information of correct differential pressure is vital to predict a required dynamic torque of motor-operated butterfly valves

  10. Complement: a key system for immune surveillance and homeostasis.

    Science.gov (United States)

    Ricklin, Daniel; Hajishengallis, George; Yang, Kun; Lambris, John D

    2010-09-01

    Nearly a century after the significance of the human complement system was recognized, we have come to realize that its functions extend far beyond the elimination of microbes. Complement acts as a rapid and efficient immune surveillance system that has distinct effects on healthy and altered host cells and foreign intruders. By eliminating cellular debris and infectious microbes, orchestrating immune responses and sending 'danger' signals, complement contributes substantially to homeostasis, but it can also take action against healthy cells if not properly controlled. This review describes our updated view of the function, structure and dynamics of the complement network, highlights its interconnection with immunity at large and with other endogenous pathways, and illustrates its multiple roles in homeostasis and disease.

  11. A mathematical model of brain glucose homeostasis

    Directory of Open Access Journals (Sweden)

    Kimura Hidenori

    2009-11-01

    Full Text Available Abstract Background The physiological fact that a stable level of brain glucose is more important than that of blood glucose suggests that the ultimate goal of the glucose-insulin-glucagon (GIG regulatory system may be homeostasis of glucose concentration in the brain rather than in the circulation. Methods In order to demonstrate the relationship between brain glucose homeostasis and blood hyperglycemia in diabetes, a brain-oriented mathematical model was developed by considering the brain as the controlled object while the remaining body as the actuator. After approximating the body compartmentally, the concentration dynamics of glucose, as well as those of insulin and glucagon, are described in each compartment. The brain-endocrine crosstalk, which regulates blood glucose level for brain glucose homeostasis together with the peripheral interactions among glucose, insulin and glucagon, is modeled as a proportional feedback control of brain glucose. Correlated to the brain, long-term effects of psychological stress and effects of blood-brain-barrier (BBB adaptation to dysglycemia on the generation of hyperglycemia are also taken into account in the model. Results It is shown that simulation profiles obtained from the model are qualitatively or partially quantitatively consistent with clinical data, concerning the GIG regulatory system responses to bolus glucose, stepwise and continuous glucose infusion. Simulations also revealed that both stress and BBB adaptation contribute to the generation of hyperglycemia. Conclusion Simulations of the model of a healthy person under long-term severe stress demonstrated that feedback control of brain glucose concentration results in elevation of blood glucose level. In this paper, we try to suggest that hyperglycemia in diabetes may be a normal outcome of brain glucose homeostasis.

  12. A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

    Science.gov (United States)

    Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

    2018-01-15

    Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.

  13. Assessing predictability of a hydrological stochastic-dynamical system

    Science.gov (United States)

    Gelfan, Alexander

    2014-05-01

    The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar

  14. Cell-size distribution in epithelial tissue formation and homeostasis.

    Science.gov (United States)

    Puliafito, Alberto; Primo, Luca; Celani, Antonio

    2017-03-01

    How cell growth and proliferation are orchestrated in living tissues to achieve a given biological function is a central problem in biology. During development, tissue regeneration and homeostasis, cell proliferation must be coordinated by spatial cues in order for cells to attain the correct size and shape. Biological tissues also feature a notable homogeneity of cell size, which, in specific cases, represents a physiological need. Here, we study the temporal evolution of the cell-size distribution by applying the theory of kinetic fragmentation to tissue development and homeostasis. Our theory predicts self-similar probability density function (PDF) of cell size and explains how division times and redistribution ensure cell size homogeneity across the tissue. Theoretical predictions and numerical simulations of confluent non-homeostatic tissue cultures show that cell size distribution is self-similar. Our experimental data confirm predictions and reveal that, as assumed in the theory, cell division times scale like a power-law of the cell size. We find that in homeostatic conditions there is a stationary distribution with lognormal tails, consistently with our experimental data. Our theoretical predictions and numerical simulations show that the shape of the PDF depends on how the space inherited by apoptotic cells is redistributed and that apoptotic cell rates might also depend on size. © 2017 The Author(s).

  15. Innate immune signalling at the intestinal epithelium in homeostasis and disease

    Science.gov (United States)

    Pott, Johanna; Hornef, Mathias

    2012-01-01

    The intestinal epithelium—which constitutes the interface between the enteric microbiota and host tissues—actively contributes to the maintenance of mucosal homeostasis and defends against pathogenic microbes. The recognition of conserved microbial products by cytosolic or transmembrane pattern recognition receptors in epithelial cells initiates signal transduction and influences effector cell function. However, the signalling pathways, effector molecules and regulatory mechanisms involved are not yet fully understood, and the functional outcome is poorly defined. This review analyses the complex and dynamic role of intestinal epithelial innate immune recognition and signalling, on the basis of results in intestinal epithelial cell-specific transgene or gene-deficient animals. This approach identifies specific epithelial cell functions within the diverse cellular composition of the mucosal tissue, in the presence of the complex and dynamic gut microbiota. These insights have thus provided a more comprehensive understanding of the role of the intestinal epithelium in innate immunity during homeostasis and disease. PMID:22801555

  16. Osteoclasts and CD8 T cells form a negative feedback loop that contributes to homeostasis of both the skeletal and immune systems.

    Science.gov (United States)

    Buchwald, Zachary S; Aurora, Rajeev

    2013-01-01

    There are a number of dynamic regulatory loops that maintain homeostasis of the immune and skeletal systems. In this review, we highlight a number of these regulatory interactions that contribute to maintaining homeostasis. In addition, we review data on a negative regulatory feedback loop between osteoclasts and CD8 T cells that contributes to homeostasis of both the skeletal and immune systems.

  17. Prediction-based dynamic load-sharing heuristics

    Science.gov (United States)

    Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

    1993-01-01

    The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

  18. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  19. Lipid Raft, Regulator of Plasmodesmal Callose Homeostasis

    Directory of Open Access Journals (Sweden)

    Arya Bagus Boedi Iswanto

    2017-04-01

    Full Text Available Abstract: The specialized plasma membrane microdomains known as lipid rafts are enriched by sterols and sphingolipids. Lipid rafts facilitate cellular signal transduction by controlling the assembly of signaling molecules and membrane protein trafficking. Another specialized compartment of plant cells, the plasmodesmata (PD, which regulates the symplasmic intercellular movement of certain molecules between adjacent cells, also contains a phospholipid bilayer membrane. The dynamic permeability of plasmodesmata (PDs is highly controlled by plasmodesmata callose (PDC, which is synthesized by callose synthases (CalS and degraded by β-1,3-glucanases (BGs. In recent studies, remarkable observations regarding the correlation between lipid raft formation and symplasmic intracellular trafficking have been reported, and the PDC has been suggested to be the regulator of the size exclusion limit of PDs. It has been suggested that the alteration of lipid raft substances impairs PDC homeostasis, subsequently affecting PD functions. In this review, we discuss the substantial role of membrane lipid rafts in PDC homeostasis and provide avenues for understanding the fundamental behavior of the lipid raft–processed PDC.

  20. Lipid Raft, Regulator of Plasmodesmal Callose Homeostasis.

    Science.gov (United States)

    Iswanto, Arya Bagus Boedi; Kim, Jae-Yean

    2017-04-03

    A bstract: The specialized plasma membrane microdomains known as lipid rafts are enriched by sterols and sphingolipids. Lipid rafts facilitate cellular signal transduction by controlling the assembly of signaling molecules and membrane protein trafficking. Another specialized compartment of plant cells, the plasmodesmata (PD), which regulates the symplasmic intercellular movement of certain molecules between adjacent cells, also contains a phospholipid bilayer membrane. The dynamic permeability of plasmodesmata (PDs) is highly controlled by plasmodesmata callose (PDC), which is synthesized by callose synthases (CalS) and degraded by β-1,3-glucanases (BGs). In recent studies, remarkable observations regarding the correlation between lipid raft formation and symplasmic intracellular trafficking have been reported, and the PDC has been suggested to be the regulator of the size exclusion limit of PDs. It has been suggested that the alteration of lipid raft substances impairs PDC homeostasis, subsequently affecting PD functions. In this review, we discuss the substantial role of membrane lipid rafts in PDC homeostasis and provide avenues for understanding the fundamental behavior of the lipid raft-processed PDC.

  1. Long-time predictions in nonlinear dynamics

    Science.gov (United States)

    Szebehely, V.

    1980-01-01

    It is known that nonintegrable dynamical systems do not allow precise predictions concerning their behavior for arbitrary long times. The available series solutions are not uniformly convergent according to Poincare's theorem and numerical integrations lose their meaningfulness after the elapse of arbitrary long times. Two approaches are the use of existing global integrals and statistical methods. This paper presents a generalized method along the first approach. As examples long-time predictions in the classical gravitational satellite and planetary problems are treated.

  2. Fluid mechanics of dynamic stall. II - Prediction of full scale characteristics

    Science.gov (United States)

    Ericsson, L. E.; Reding, J. P.

    1988-01-01

    Analytical extrapolations are made from experimental subscale dynamics to predict full scale characteristics of dynamic stall. The method proceeds by establishing analytic relationships between dynamic and static aerodynamic characteristics induced by viscous flow effects. The method is then validated by predicting dynamic test results on the basis of corresponding static test data obtained at the same subscale flow conditions, and the effect of Reynolds number on the static aerodynamic characteristics are determined from subscale to full scale flow conditions.

  3. ER network homeostasis is critical for plant endosome streaming and endocytosis

    Science.gov (United States)

    Stefano, Giovanni; Renna, Luciana; Lai, YaShiuan; Slabaugh, Erin; Mannino, Nicole; Buono, Rafael A; Otegui, Marisa S; Brandizzi, Federica

    2015-01-01

    Eukaryotic cells internalize cargo at the plasma membrane via endocytosis, a vital process that is accomplished through a complex network of endosomal organelles. In mammalian cells, the ER is in close association with endosomes and regulates their fission. Nonetheless, the physiological role of such interaction on endocytosis is yet unexplored. Here, we probed the existence of ER–endosome association in plant cells and assayed its physiological role in endocytosis. Through live-cell imaging and electron microscopy studies, we established that endosomes are extensively associated with the plant ER, supporting conservation of interaction between heterotypic organelles in evolutionarily distant kingdoms. Furthermore, by analyzing ER–endosome dynamics in genetic backgrounds with defects in ER structure and movement, we also established that the ER network integrity is necessary for homeostasis of the distribution and streaming of various endosome populations as well as for efficient endocytosis. These results support a novel model that endocytosis homeostasis depends on a spatiotemporal control of the endosome dynamics dictated by the ER membrane network. PMID:27462431

  4. Ergothioneine Maintains Redox and Bioenergetic Homeostasis Essential for Drug Susceptibility and Virulence of Mycobacterium tuberculosis

    Directory of Open Access Journals (Sweden)

    Vikram Saini

    2016-01-01

    Full Text Available The mechanisms by which Mycobacterium tuberculosis (Mtb maintains metabolic equilibrium to survive during infection and upon exposure to antimycobacterial drugs are poorly characterized. Ergothioneine (EGT and mycothiol (MSH are the major redox buffers present in Mtb, but the contribution of EGT to Mtb redox homeostasis and virulence remains unknown. We report that Mtb WhiB3, a 4Fe-4S redox sensor protein, regulates EGT production and maintains bioenergetic homeostasis. We show that central carbon metabolism and lipid precursors regulate EGT production and that EGT modulates drug sensitivity. Notably, EGT and MSH are both essential for redox and bioenergetic homeostasis. Transcriptomic analyses of EGT and MSH mutants indicate overlapping but distinct functions of EGT and MSH. Last, we show that EGT is critical for Mtb survival in both macrophages and mice. This study has uncovered a dynamic balance between Mtb redox and bioenergetic homeostasis, which critically influences Mtb drug susceptibility and pathogenicity.

  5. Evolving a Dynamic Predictive Coding Mechanism for Novelty Detection

    OpenAIRE

    Haggett, Simon J.; Chu, Dominique; Marshall, Ian W.

    2007-01-01

    Novelty detection is a machine learning technique which identifies new or unknown information in data sets. We present our current work on the construction of a new novelty detector based on a dynamical version of predictive coding. We compare three evolutionary algorithms, a simple genetic algorithm, NEAT and FS-NEAT, for the task of optimising the structure of an illustrative dynamic predictive coding neural network to improve its performance over stimuli from a number of artificially gener...

  6. Prediction-based Dynamic Energy Management in Wireless Sensor Networks

    Science.gov (United States)

    Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

    2007-01-01

    Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

  7. Prediction-based Dynamic Energy Management in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dao-Wei Bi

    2007-03-01

    Full Text Available Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

  8. Dynamics and predictions in the co-event interpretation

    International Nuclear Information System (INIS)

    Ghazi-Tabatabai, Yousef; Wallden, Petros

    2009-01-01

    Sorkin has introduced a new, observer independent, interpretation of quantum mechanics that can give a successful realist account of the 'quantum micro-world' as well as explaining how classicality emerges at the level of observable events for a range of systems including single time 'Copenhagen measurements'. This 'co-event interpretation' presents us with a new ontology, in which a single 'co-event' is real. A new ontology necessitates a review of the dynamical and predictive mechanism of a theory, and in this paper we begin the process by exploring means of expressing the dynamical and predictive content of histories theories in terms of co-events

  9. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Clinical time series prediction: towards a hierarchical dynamical system framework

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  11. Human motion simulation predictive dynamics

    CERN Document Server

    Abdel-Malek, Karim

    2013-01-01

    Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures, such as speed and energy, which act as objective functions to be optimized. Constraints on joint torques and angles are imposed quite easily. Predicting motion in this way allows one to use avatars to study how and why humans move the way they do, given specific scenarios. It also enables avatars to react to infinitely many scenarios with substantial autonomy. With this approach it is possible to predict dynamic motion without having to integrate equations of motion -- rather than solving equations of motion, this approach solves for a continuous time-dependent curve characterizing joint variables (also called joint profiles) for every degree of freedom. Introduces rigorous mathematical methods for digital human modelling and simulation Focuses on understanding and representing spatial relationships (3D) of biomechanics Develops an i...

  12. The dynamic interplay of microbiota and mucosa drives establishment of homeostasis in conventionalized mice

    NARCIS (Netherlands)

    Aidy, El S.F.

    2012-01-01

    The intimate interplay between gut microbiota, host, and nutrient flow is crucial in defining the health status of the host. During microbial conventionalization of germfree mice, tightly regulated molecular responses assure the establishment of homeostasis and immune tolerance towards the

  13. Tissues Use Resident Dendritic Cells and Macrophages to Maintain Homeostasis and to Regain Homeostasis upon Tissue Injury: The Immunoregulatory Role of Changing Tissue Environments

    Science.gov (United States)

    Lech, Maciej; Gröbmayr, Regina; Weidenbusch, Marc; Anders, Hans-Joachim

    2012-01-01

    Most tissues harbor resident mononuclear phagocytes, that is, dendritic cells and macrophages. A classification that sufficiently covers their phenotypic heterogeneity and plasticity during homeostasis and disease does not yet exist because cell culture-based phenotypes often do not match those found in vivo. The plasticity of mononuclear phagocytes becomes obvious during dynamic or complex disease processes. Different data interpretation also originates from different conceptual perspectives. An immune-centric view assumes that a particular priming of phagocytes then causes a particular type of pathology in target tissues, conceptually similar to antigen-specific T-cell priming. A tissue-centric view assumes that changing tissue microenvironments shape the phenotypes of their resident and infiltrating mononuclear phagocytes to fulfill the tissue's need to maintain or regain homeostasis. Here we discuss the latter concept, for example, why different organs host different types of mononuclear phagocytes during homeostasis. We further discuss how injuries alter tissue environments and how this primes mononuclear phagocytes to enforce this particular environment, for example, to support host defense and pathogen clearance, to support the resolution of inflammation, to support epithelial and mesenchymal healing, and to support the resolution of fibrosis to the smallest possible scar. Thus, organ- and disease phase-specific microenvironments determine macrophage and dendritic cell heterogeneity in a temporal and spatial manner, which assures their support to maintain and regain homeostasis in whatever condition. Mononuclear phagocytes contributions to tissue pathologies relate to their central roles in orchestrating all stages of host defense and wound healing, which often become maladaptive processes, especially in sterile and/or diffuse tissue injuries. PMID:23251037

  14. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

    Science.gov (United States)

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

  15. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

    Science.gov (United States)

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

  16. Adaptive mechanisms of homeostasis disorders

    Directory of Open Access Journals (Sweden)

    Anna Maria Dobosiewicz

    2017-08-01

    Full Text Available The ability to preserve a permanent level of internal environment in a human organism, against internal and external factors, which could breach the consistency, can be define as homeostasis. Scientific proven influence on the homeostasis has the periodicity of biological processes, which is also called circadian rhythm. The effect of circadian rhythm is also to see in the functioning of autonomic nervous system and cardiovascular system. Sleep deprivation is an example of how the disorders in circadian rhythm could have the influence on the homeostasis.

  17. Dynamics and predictions in the co-event interpretation

    Energy Technology Data Exchange (ETDEWEB)

    Ghazi-Tabatabai, Yousef [Blackett Laboratory, Imperial College, London, SW7 2AZ (United Kingdom); Wallden, Petros [Raman Research Institute, Bangalore 560 080 (India)

    2009-06-12

    Sorkin has introduced a new, observer independent, interpretation of quantum mechanics that can give a successful realist account of the 'quantum micro-world' as well as explaining how classicality emerges at the level of observable events for a range of systems including single time 'Copenhagen measurements'. This 'co-event interpretation' presents us with a new ontology, in which a single 'co-event' is real. A new ontology necessitates a review of the dynamical and predictive mechanism of a theory, and in this paper we begin the process by exploring means of expressing the dynamical and predictive content of histories theories in terms of co-events.

  18. Linear and nonlinear dynamic systems in financial time series prediction

    Directory of Open Access Journals (Sweden)

    Salim Lahmiri

    2012-10-01

    Full Text Available Autoregressive moving average (ARMA process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX are compared by evaluating their ability to predict financial time series; for instance the S&P500 returns. Two classes of ARMA are considered. The first one is the standard ARMA model which is a linear static system. The second one uses Kalman filter (KF to estimate and predict ARMA coefficients. This model is a linear dynamic system. The forecasting ability of each system is evaluated by means of mean absolute error (MAE and mean absolute deviation (MAD statistics. Simulation results indicate that the ARMA-KF system performs better than the standard ARMA alone. Thus, introducing dynamics into the ARMA process improves the forecasting accuracy. In addition, the ARMA-KF outperformed the NARX. This result may suggest that the linear component found in the S&P500 return series is more dominant than the nonlinear part. In sum, we conclude that introducing dynamics into the ARMA process provides an effective system for S&P500 time series prediction.

  19. Maintenance of Gastrointestinal Glucose Homeostasis by the Gut-Brain Axis.

    Science.gov (United States)

    Chen, Xiyue; Eslamfam, Shabnam; Fang, Luoyun; Qiao, Shiyan; Ma, Xi

    2017-01-01

    Gastrointestinal homeostasis is a dynamic balance under the interaction between the host, GI tract, nutrition and energy metabolism. Glucose is the main energy source in living cells. Thus, glucose metabolic disorders can impair normal cellular function and endanger organisms' health. Diseases that are associated with glucose metabolic disorders such as obesity, diabetes, hypertension, and other metabolic syndromes are in fact life threatening. Digestive system is responsible for food digestion and nutrient absorption. It is also involved in neuronal, immune, and endocrine pathways. In addition, the gut microbiota plays an essential role in initiating signal transduction, and communication between the enteric and central nervous system. Gut-brain axis is composed of enteric neural system, central neural system, and all the efferent and afferent neurons that are involved in signal transduction between the brain and gut-brain. Gut-brain axis is influenced by the gut-microbiota as well as numerous neurotransmitters. Properly regulated gut-brain axis ensures normal digestion, absorption, energy production, and subsequently maintenance of glucose homeostasis. Understanding the underlying regulatory mechanisms of gut-brain axis involved in gluose homeostasis would enable us develop more efficient means of prevention and management of metabolic disease such as diabetic, obesity, and hypertension. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

  1. MicroRNA-orchestrated pathophysiologic control in gut homeostasis and inflammation.

    Science.gov (United States)

    Lee, Juneyoung; Park, Eun Jeong; Kiyono, Hiroshi

    2016-05-01

    The intestine represents the largest and most elaborate immune system organ, in which dynamic and reciprocal interplay among numerous immune and epithelial cells, commensal microbiota, and external antigens contributes to establishing both homeostatic and pathologic conditions. The mechanisms that sustain gut homeostasis are pivotal in maintaining gut health in the harsh environment of the gut lumen. Intestinal epithelial cells are critical players in creating the mucosal platform for interplay between host immune cells and luminal stress inducers. Thus, knowledge of the epithelial interface between immune cells and the luminal environment is a prerequisite for a better understanding of gut homeostasis and pathophysiologies such as inflammation. In this review, we explore the importance of the epithelium in limiting or promoting gut inflammation (e.g., inflammatory bowel disease). We also introduce recent findings on how small RNAs such as microRNAs orchestrate pathophysiologic gene regulation. [BMB Reports 2016; 49(5): 263-269].

  2. Nonlinear dynamics and predictability in the atmospheric sciences

    Science.gov (United States)

    Ghil, M.; Kimoto, M.; Neelin, J. D.

    1991-01-01

    Systematic applications of nonlinear dynamics to studies of the atmosphere and climate are reviewed for the period 1987-1990. Problems discussed include paleoclimatic applications, low-frequency atmospheric variability, and interannual variability of the ocean-atmosphere system. Emphasis is placed on applications of the successive bifurcation approach and the ergodic theory of dynamical systems to understanding and prediction of intraseasonal, interannual, and Quaternary climate changes.

  3. Summer drought predictability over Europe: empirical versus dynamical forecasts

    Science.gov (United States)

    Turco, Marco; Ceglar, Andrej; Prodhomme, Chloé; Soret, Albert; Toreti, Andrea; Doblas-Reyes Francisco, J.

    2017-08-01

    Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

  4. A Physiologist's View of Homeostasis

    Science.gov (United States)

    Modell, Harold; Cliff, William; Michael, Joel; McFarland, Jenny; Wenderoth, Mary Pat; Wright, Ann

    2015-01-01

    Homeostasis is a core concept necessary for understanding the many regulatory mechanisms in physiology. Claude Bernard originally proposed the concept of the constancy of the "milieu interieur," but his discussion was rather abstract. Walter Cannon introduced the term "homeostasis" and expanded Bernard's notion of…

  5. Reactive Oxygen Species and Mitochondrial Homeostasis as Regulators of Stem Cell Fate and Function.

    Science.gov (United States)

    Tan, Darren Q; Suda, Toshio

    2018-07-10

    The precise role and impact of reactive oxygen species (ROS) in stem cells, which are essential for lifelong tissue homeostasis and regeneration, remain of significant interest to the field. The long-term regenerative potential of a stem cell compartment is determined by the delicate balance between quiescence, self-renewal, and differentiation, all of which can be influenced by ROS levels. Recent Advances: The past decade has seen a growing appreciation for the importance of ROS and redox homeostasis in various stem cell compartments, particularly those of hematopoietic, neural, and muscle tissues. In recent years, the importance of proteostasis and mitochondria in relation to stem cell biology and redox homeostasis has garnered considerable interest. Here, we explore the reciprocal relationship between ROS and stem cells, with significant emphasis on mitochondria as a core component of redox homeostasis. We discuss how redox signaling, involving cell-fate determining protein kinases and transcription factors, can control stem cell function and fate. We also address the impact of oxidative stress on stem cells, especially oxidative damage of lipids, proteins, and nucleic acids. We further discuss ROS management in stem cells, and present recent evidence supporting the importance of mitochondrial activity and its modulation (via mitochondrial clearance, biogenesis, dynamics, and distribution [i.e., segregation and transfer]) in stem cell redox homeostasis. Therefore, elucidating the intricate links between mitochondria, cellular metabolism, and redox homeostasis is envisioned to be critical for our understanding of ROS in stem cell biology and its therapeutic relevance in regenerative medicine. Antioxid. Redox Signal. 00, 000-000.

  6. Dynamic Simulation of Human Gait Model With Predictive Capability.

    Science.gov (United States)

    Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

    2018-03-01

    In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

  7. A dynamic predictive maintenance policy for complex multi-component systems

    International Nuclear Information System (INIS)

    Van Horenbeek, Adriaan; Pintelon, Liliane

    2013-01-01

    The use of prognostic methods in maintenance in order to predict remaining useful life is receiving more attention over the past years. The use of these techniques in maintenance decision making and optimization in multi-component systems is however a still underexplored area. The objective of this paper is to optimally plan maintenance for a multi-component system based on prognostic/predictive information while considering different component dependencies (i.e. economic, structural and stochastic dependence). Consequently, this paper presents a dynamic predictive maintenance policy for multi-component systems that minimizes the long-term mean maintenance cost per unit time. The proposed maintenance policy is a dynamic method as the maintenance schedule is updated when new information on the degradation and remaining useful life of components becomes available. The performance, regarding the objective of minimal long-term mean cost per unit time, of the developed dynamic predictive maintenance policy is compared to five other conventional maintenance policies, these are: block-based maintenance, age-based maintenance, age-based maintenance with grouping, inspection condition-based maintenance and continuous condition-based maintenance. The ability of the predictive maintenance policy to react to changing component deterioration and dependencies within a multi-component system is quantified and the results show significant cost savings

  8. Correlation of chemical shifts predicted by molecular dynamics simulations for partially disordered proteins

    Energy Technology Data Exchange (ETDEWEB)

    Karp, Jerome M.; Erylimaz, Ertan; Cowburn, David, E-mail: cowburn@cowburnlab.org, E-mail: David.cowburn@einstein.yu.edu [Albert Einstein College of Medicine of Yeshiva University, Department of Biochemistry (United States)

    2015-01-15

    There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.

  9. The Role of Follicular Fluid Thiol/Disulphide Homeostasis in Polycystic Ovary Syndrome.

    Science.gov (United States)

    Tola, Esra Nur; Köroğlu, Nadiye; Ergin, Merve; Oral, Hilmi Baha; Turgut, Abdülkadir; Erel, Özcan

    2018-04-04

    Oxidative stress is suggested as a potential triggering factor in the etiopathogenesis of Polycystic ovary syndrome related infertility. Thiol/disulphide homeostasis, a recently oxidative stress marker, is one of the antioxidant mechanism in human which have critical roles in folliculogenesis and ovulation. The aim of our study is to investigate follicular fluid thiol/disulphide homeostasis in the etiopathogenesis of Polycystic ovary syndrome and to determine its' association with in vitro fertilization outcome. The study procedures were approved by local ethic committee. Cross sectional design Methods: Follicular fluid of twenty-two Polycystic ovary syndrome women and twenty ovulatory controls undergoing in vitro fertilization treatment were recruited. Thiol/disulphide homeostasis was analyzed via a novel spectrophotometric method. Follicular native thiol levels were found to be lower in Polycystic ovary syndrome group than non- Polycystic ovary syndrome group (p=0.041) as well as native thiol/total thiol ratio (pPolycystic ovary syndrome group (pPolycystic ovary syndrome patients was found. A positive predictive effect of native thiol on fertilization rate among Polycystic ovary syndrome group was also found (p=0.03, β=0.45, 95% CI=0.031-0.643). Deterioration in thiol/disulphide homeostasis, especially elevated disulphide levels could be one of the etiopathogenetic mechanism in Polycystic ovary syndrome. Increased native thiol levels is related to fertilization rate among Polycystic ovary syndrome patients and also positive predictor marker of fertilization rate among Polycystic ovary syndrome patients. Improvement of thiol/disulphide homeostasis could be of importance in the treatment of Polycystic ovary syndrome to increase in vitro fertilization success in Polycystic ovary syndrome.

  10. Dynamic prediction of cumulative incidence functions by direct binomial regression.

    Science.gov (United States)

    Grand, Mia K; de Witte, Theo J M; Putter, Hein

    2018-03-25

    In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights. We extend the approach by combining it with landmarking to enable dynamic prediction of the cumulative incidence function. The proposed models are very flexible, as they allow the covariates to have complex time-varying effects, and we illustrate how to investigate possible time-varying structures using Wald tests. The models are fitted using generalized estimating equations. The method is applied to bone marrow transplant data and the performance is investigated in a simulation study. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Lipidomics in research on yeast membrane lipid homeostasis.

    Science.gov (United States)

    de Kroon, Anton I P M

    2017-08-01

    Mass spectrometry is increasingly used in research on membrane lipid homeostasis, both in analyses of the steady state lipidome at the level of molecular lipid species, and in pulse-chase approaches employing stable isotope-labeled lipid precursors addressing the dynamics of lipid metabolism. Here my experience with, and view on mass spectrometry-based lipid analysis is presented, with emphasis on aspects of quantification of membrane lipid composition of the yeast Saccharomyces cerevisiae. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Cooperation between brain and islet in glucose homeostasis and diabetes

    Science.gov (United States)

    Schwartz, Michael W.; Seeley, Randy J.; Tschöp, Matthias H.; Woods, Stephen C.; Morton, Gregory J.; Myers, Martin G.; D'Alessio, David

    2014-01-01

    Although a prominent role for the brain in glucose homeostasis was proposed by scientists in the nineteenth century, research throughout most of the twentieth century focused on evidence that the function of pancreatic islets is both necessary and sufficient to explain glucose homeostasis, and that diabetes results from defects of insulin secretion, action or both. However, insulin-independent mechanisms, referred to as ‘glucose effectiveness’, account for roughly 50% of overall glucose disposal, and reduced glucose effectiveness also contributes importantly to diabetes pathogenesis. Although mechanisms underlying glucose effectiveness are poorly understood, growing evidence suggests that the brain can dynamically regulate this process in ways that improve or even normalize glycaemia in rodent models of diabetes. Here we present evidence of a brain-centred glucoregulatory system (BCGS) that can lower blood glucose levels via both insulin-dependent and -independent mechanisms, and propose a model in which complex and highly coordinated interactions between the BCGS and pancreatic islets promote normal glucose homeostasis. Because activation of either regulatory system can compensate for failure of the other, defects in both may be required for diabetes to develop. Consequently, therapies that target the BCGS in addition to conventional approaches based on enhancing insulin effects may have the potential to induce diabetes remission, whereas targeting just one typically does not. PMID:24201279

  13. Cellular copper homeostasis: current concepts on its interplay with glutathione homeostasis and its implication in physiology and human diseases.

    Science.gov (United States)

    Bhattacharjee, Ashima; Chakraborty, Kaustav; Shukla, Aditya

    2017-10-18

    Copper is a trace element essential for almost all living organisms. But the level of intracellular copper needs to be tightly regulated. Dysregulation of cellular copper homeostasis leading to various diseases demonstrates the importance of this tight regulation. Copper homeostasis is regulated not only within the cell but also within individual intracellular compartments. Inactivation of export machinery results in excess copper being redistributed into various intracellular organelles. Recent evidence suggests the involvement of glutathione in playing an important role in regulating copper entry and intracellular copper homeostasis. Therefore interplay of both homeostases might play an important role within the cell. Similar to copper, glutathione balance is tightly regulated within individual cellular compartments. This review explores the existing literature on the role of glutathione in regulating cellular copper homeostasis. On the one hand, interplay of glutathione and copper homeostasis performs an important role in normal physiological processes, for example neuronal differentiation. On the other hand, perturbation of the interplay might play a key role in the pathogenesis of copper homeostasis disorders.

  14. Targeting Cellular Calcium Homeostasis to Prevent Cytokine-Mediated Beta Cell Death.

    Science.gov (United States)

    Clark, Amy L; Kanekura, Kohsuke; Lavagnino, Zeno; Spears, Larry D; Abreu, Damien; Mahadevan, Jana; Yagi, Takuya; Semenkovich, Clay F; Piston, David W; Urano, Fumihiko

    2017-07-17

    Pro-inflammatory cytokines are important mediators of islet inflammation, leading to beta cell death in type 1 diabetes. Although alterations in both endoplasmic reticulum (ER) and cytosolic free calcium levels are known to play a role in cytokine-mediated beta cell death, there are currently no treatments targeting cellular calcium homeostasis to combat type 1 diabetes. Here we show that modulation of cellular calcium homeostasis can mitigate cytokine- and ER stress-mediated beta cell death. The calcium modulating compounds, dantrolene and sitagliptin, both prevent cytokine and ER stress-induced activation of the pro-apoptotic calcium-dependent enzyme, calpain, and partly suppress beta cell death in INS1E cells and human primary islets. These agents are also able to restore cytokine-mediated suppression of functional ER calcium release. In addition, sitagliptin preserves function of the ER calcium pump, sarco-endoplasmic reticulum Ca 2+ -ATPase (SERCA), and decreases levels of the pro-apoptotic protein thioredoxin-interacting protein (TXNIP). Supporting the role of TXNIP in cytokine-mediated cell death, knock down of TXNIP in INS1-E cells prevents cytokine-mediated beta cell death. Our findings demonstrate that modulation of dynamic cellular calcium homeostasis and TXNIP suppression present viable pharmacologic targets to prevent cytokine-mediated beta cell loss in diabetes.

  15. An Artificial Neural Network Based Short-term Dynamic Prediction of Algae Bloom

    Directory of Open Access Journals (Sweden)

    Yao Junyang

    2014-06-01

    Full Text Available This paper proposes a method of short-term prediction of algae bloom based on artificial neural network. Firstly, principal component analysis is applied to water environmental factors in algae bloom raceway ponds to get main factors that influence the formation of algae blooms. Then, a model of short-term dynamic prediction based on neural network is built with the current chlorophyll_a values as input and the chlorophyll_a values in the next moment as output to realize short-term dynamic prediction of algae bloom. Simulation results show that the model can realize short-term prediction of algae bloom effectively.

  16. Predictive assessment of models for dynamic functional connectivity

    DEFF Research Database (Denmark)

    Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

    2018-01-01

    represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

  17. The role of glutamate in neuronal ion homeostasis: A case study of spreading depolarization.

    Directory of Open Access Journals (Sweden)

    Niklas Hübel

    2017-10-01

    Full Text Available Simultaneous changes in ion concentrations, glutamate, and cell volume together with exchange of matter between cell network and vasculature are ubiquitous in numerous brain pathologies. A complete understanding of pathological conditions as well as normal brain function, therefore, hinges on elucidating the molecular and cellular pathways involved in these mostly interdependent variations. In this paper, we develop the first computational framework that combines the Hodgkin-Huxley type spiking dynamics, dynamic ion concentrations and glutamate homeostasis, neuronal and astroglial volume changes, and ion exchange with vasculature into a comprehensive model to elucidate the role of glutamate uptake in the dynamics of spreading depolarization (SD-the electrophysiological event underlying numerous pathologies including migraine, ischemic stroke, aneurysmal subarachnoid hemorrhage, intracerebral hematoma, and trauma. We are particularly interested in investigating the role of glutamate in the duration and termination of SD caused by K+ perfusion and oxygen-glucose deprivation. Our results demonstrate that glutamate signaling plays a key role in the dynamics of SD, and that impaired glutamate uptake leads to recovery failure of neurons from SD. We confirm predictions from our model experimentally by showing that inhibiting astrocytic glutamate uptake using TFB-TBOA nearly quadruples the duration of SD in layers 2-3 of visual cortical slices from juvenile rats. The model equations are either derived purely from first physical principles of electroneutrality, osmosis, and conservation of particles or a combination of these principles and known physiological facts. Accordingly, we claim that our approach can be used as a future guide to investigate the role of glutamate, ion concentrations, and dynamics cell volume in other brain pathologies and normal brain function.

  18. The role of glutamate in neuronal ion homeostasis: A case study of spreading depolarization.

    Science.gov (United States)

    Hübel, Niklas; Hosseini-Zare, Mahshid S; Žiburkus, Jokūbas; Ullah, Ghanim

    2017-10-01

    Simultaneous changes in ion concentrations, glutamate, and cell volume together with exchange of matter between cell network and vasculature are ubiquitous in numerous brain pathologies. A complete understanding of pathological conditions as well as normal brain function, therefore, hinges on elucidating the molecular and cellular pathways involved in these mostly interdependent variations. In this paper, we develop the first computational framework that combines the Hodgkin-Huxley type spiking dynamics, dynamic ion concentrations and glutamate homeostasis, neuronal and astroglial volume changes, and ion exchange with vasculature into a comprehensive model to elucidate the role of glutamate uptake in the dynamics of spreading depolarization (SD)-the electrophysiological event underlying numerous pathologies including migraine, ischemic stroke, aneurysmal subarachnoid hemorrhage, intracerebral hematoma, and trauma. We are particularly interested in investigating the role of glutamate in the duration and termination of SD caused by K+ perfusion and oxygen-glucose deprivation. Our results demonstrate that glutamate signaling plays a key role in the dynamics of SD, and that impaired glutamate uptake leads to recovery failure of neurons from SD. We confirm predictions from our model experimentally by showing that inhibiting astrocytic glutamate uptake using TFB-TBOA nearly quadruples the duration of SD in layers 2-3 of visual cortical slices from juvenile rats. The model equations are either derived purely from first physical principles of electroneutrality, osmosis, and conservation of particles or a combination of these principles and known physiological facts. Accordingly, we claim that our approach can be used as a future guide to investigate the role of glutamate, ion concentrations, and dynamics cell volume in other brain pathologies and normal brain function.

  19. Comparison of the Usefulness of the Updated Homeostasis Model Assessment (HOMA2) with the Original HOMA1 in the Prediction of Type 2 Diabetes Mellitus in Koreans

    OpenAIRE

    Song, Young Seok; Hwang, You-Cheol; Ahn, Hong-Yup; Park, Cheol-Young

    2016-01-01

    Background The original homeostasis model assessment (HOMA1) and the updated HOMA model (HOMA2) have been used to evaluate insulin resistance (IR) and ?-cell function, but little is known about the usefulness of HOMA2 for the prediction of diabetes in Koreans. The aim of this study was to demonstrate the usefulness of HOMA2 as a predictor of type 2 diabetes mellitus in Koreans without diabetes. Methods The study population consisted of 104,694 Koreans enrolled at a health checkup program and ...

  20. Comparison of the Usefulness of the Updated Homeostasis Model Assessment (HOMA2) with the Original HOMA1 in the Prediction of Type 2 Diabetes Mellitus in Koreans

    OpenAIRE

    Young Seok Song; You-Cheol Hwang; Hong-Yup Ahn; Cheol-Young Park

    2016-01-01

    BackgroundThe original homeostasis model assessment (HOMA1) and the updated HOMA model (HOMA2) have been used to evaluate insulin resistance (IR) and β-cell function, but little is known about the usefulness of HOMA2 for the prediction of diabetes in Koreans. The aim of this study was to demonstrate the usefulness of HOMA2 as a predictor of type 2 diabetes mellitus in Koreans without diabetes.MethodsThe study population consisted of 104,694 Koreans enrolled at a health checkup program and fol...

  1. A conceptual framework for homeostasis: development and validation

    Science.gov (United States)

    Wenderoth, Mary Pat; Michael, Joel; Cliff, William; Wright, Ann; Modell, Harold

    2016-01-01

    We have developed and validated a conceptual framework for understanding and teaching organismal homeostasis at the undergraduate level. The resulting homeostasis conceptual framework details critical components and constituent ideas underlying the concept of homeostasis. It has been validated by a broad range of physiology faculty members from community colleges, primarily undergraduate institutions, research universities, and medical schools. In online surveys, faculty members confirmed the relevance of each item in the framework for undergraduate physiology and rated the importance and difficulty of each. The homeostasis conceptual framework was constructed as a guide for teaching and learning of this critical core concept in physiology, and it also paves the way for the development of a concept inventory for homeostasis. PMID:27105740

  2. Gut Homeostasis, Microbial Dysbiosis, and Opioids.

    Science.gov (United States)

    Wang, Fuyuan; Roy, Sabita

    2017-01-01

    Gut homeostasis plays an important role in maintaining animal and human health. The disruption of gut homeostasis has been shown to be associated with multiple diseases. The mutually beneficial relationship between the gut microbiota and the host has been demonstrated to maintain homeostasis of the mucosal immunity and preserve the integrity of the gut epithelial barrier. Currently, rapid progress in the understanding of the host-microbial interaction has redefined toxicological pathology of opioids and their pharmacokinetics. However, it is unclear how opioids modulate the gut microbiome and metabolome. Our study, showing opioid modulation of gut homeostasis in mice, suggests that medical interventions to ameliorate the consequences of drug use/abuse will provide potential therapeutic and diagnostic strategies for opioid-modulated intestinal infections. The study of morphine's modulation of the gut microbiome and metabolome will shed light on the toxicological pathology of opioids and its role in the susceptibility to infectious diseases.

  3. Testing for the 'predictability' of dynamically triggered earthquakes in The Geysers geothermal field

    Science.gov (United States)

    Aiken, Chastity; Meng, Xiaofeng; Hardebeck, Jeanne

    2018-03-01

    The Geysers geothermal field is well known for being susceptible to dynamic triggering of earthquakes by large distant earthquakes, owing to the introduction of fluids for energy production. Yet, it is unknown if dynamic triggering of earthquakes is 'predictable' or whether dynamic triggering could lead to a potential hazard for energy production. In this paper, our goal is to investigate the characteristics of triggering and the physical conditions that promote triggering to determine whether or not triggering is in anyway foreseeable. We find that, at present, triggering in The Geysers is not easily 'predictable' in terms of when and where based on observable physical conditions. However, triggered earthquake magnitude positively correlates with peak imparted dynamic stress, and larger dynamic stresses tend to trigger sequences similar to mainshock-aftershock sequences. Thus, we may be able to 'predict' what size earthquakes to expect at The Geysers following a large distant earthquake.

  4. Organelle communication: signaling crossroads between homeostasis and disease.

    Science.gov (United States)

    Bravo-Sagua, Roberto; Torrealba, Natalia; Paredes, Felipe; Morales, Pablo E; Pennanen, Christian; López-Crisosto, Camila; Troncoso, Rodrigo; Criollo, Alfredo; Chiong, Mario; Hill, Joseph A; Simmen, Thomas; Quest, Andrew F; Lavandero, Sergio

    2014-05-01

    Cellular organelles do not function as isolated or static units, but rather form dynamic contacts between one another that can be modulated according to cellular needs. The physical interfaces between organelles are important for Ca2+ and lipid homeostasis, and serve as platforms for the control of many essential functions including metabolism, signaling, organelle integrity and execution of the apoptotic program. Emerging evidence also highlights the importance of organelle communication in disorders such as Alzheimer's disease, pulmonary arterial hypertension, cancer, skeletal and cardiac muscle dysfunction. Here, we provide an overview of the current literature on organelle communication and the link to human pathologies. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. A conceptual framework for homeostasis: development and validation.

    Science.gov (United States)

    McFarland, Jenny; Wenderoth, Mary Pat; Michael, Joel; Cliff, William; Wright, Ann; Modell, Harold

    2016-06-01

    We have developed and validated a conceptual framework for understanding and teaching organismal homeostasis at the undergraduate level. The resulting homeostasis conceptual framework details critical components and constituent ideas underlying the concept of homeostasis. It has been validated by a broad range of physiology faculty members from community colleges, primarily undergraduate institutions, research universities, and medical schools. In online surveys, faculty members confirmed the relevance of each item in the framework for undergraduate physiology and rated the importance and difficulty of each. The homeostasis conceptual framework was constructed as a guide for teaching and learning of this critical core concept in physiology, and it also paves the way for the development of a concept inventory for homeostasis. Copyright © 2016 The American Physiological Society.

  6. Predicting dynamic behavior via anticipating synchronization in coupled pendulum-like systems

    International Nuclear Information System (INIS)

    Xu Shiyun; Yang Ying

    2009-01-01

    In this paper, the regime of anticipating synchronization (sometimes called predicted synchronization) in a class of nonlinear dynamical systems is investigated by testing the global asymptotical stability of time-delayed error dynamics. Sufficient conditions in terms of linear matrix inequalities are established for anticipating synchronization between such systems with and without state time delay. These results allow one to predict the dynamic behavior of the systems by using a copy of the same system that performs as a slave. Moreover, the cascaded anticipating synchronization is concerned such that several slave systems could anticipate the same master system with different delays. Concrete applications to phase-locked loops demonstrate the applicability and validity of the proposed results.

  7. The homeostasis of Plasmodium falciparum-infected red blood cells.

    Directory of Open Access Journals (Sweden)

    Jakob M A Mauritz

    2009-04-01

    Full Text Available The asexual reproduction cycle of Plasmodium falciparum, the parasite responsible for severe malaria, occurs within red blood cells. A merozoite invades a red cell in the circulation, develops and multiplies, and after about 48 hours ruptures the host cell, releasing 15-32 merozoites ready to invade new red blood cells. During this cycle, the parasite increases the host cell permeability so much that when similar permeabilization was simulated on uninfected red cells, lysis occurred before approximately 48 h. So how could infected cells, with a growing parasite inside, prevent lysis before the parasite has completed its developmental cycle? A mathematical model of the homeostasis of infected red cells suggested that it is the wasteful consumption of host cell hemoglobin that prevents early lysis by the progressive reduction in the colloid-osmotic pressure within the host (the colloid-osmotic hypothesis. However, two critical model predictions, that infected cells would swell to near prelytic sphericity and that the hemoglobin concentration would become progressively reduced, remained controversial. In this paper, we are able for the first time to correlate model predictions with recent experimental data in the literature and explore the fine details of the homeostasis of infected red blood cells during five model-defined periods of parasite development. The conclusions suggest that infected red cells do reach proximity to lytic rupture regardless of their actual volume, thus requiring a progressive reduction in their hemoglobin concentration to prevent premature lysis.

  8. NOD-Like Receptors in Intestinal Homeostasis and Epithelial Tissue Repair

    Science.gov (United States)

    Parlato, Marianna; Yeretssian, Garabet

    2014-01-01

    The intestinal epithelium constitutes a dynamic physical barrier segregating the luminal content from the underlying mucosal tissue. Following injury, the epithelial integrity is restored by rapid migration of intestinal epithelial cells (IECs) across the denuded area in a process known as wound healing. Hence, through a sequence of events involving restitution, proliferation and differentiation of IECs the gap is resealed and homeostasis reestablished. Relapsing damage followed by healing of the inflamed mucosa is a hallmark of several intestinal disorders including inflammatory bowel diseases (IBD). While several regulatory peptides, growth factors and cytokines stimulate restitution of the epithelial layer after injury, recent evidence in the field underscores the contribution of innate immunity in controlling this process. In particular, nucleotide-binding and oligomerization domain-like receptors (NLRs) play critical roles in sensing the commensal microbiota, maintaining homeostasis, and regulating intestinal inflammation. Here, we review the process of intestinal epithelial tissue repair and we specifically focus on the impact of NLR-mediated signaling mechanisms involved in governing epithelial wound healing during disease. PMID:24886810

  9. The plasticity of extracellular fluid homeostasis in insects.

    Science.gov (United States)

    Beyenbach, Klaus W

    2016-09-01

    In chemistry, the ratio of all dissolved solutes to the solution's volume yields the osmotic concentration. The present Review uses this chemical perspective to examine how insects deal with challenges to extracellular fluid (ECF) volume, solute content and osmotic concentration (pressure). Solute/volume plots of the ECF (hemolymph) reveal that insects tolerate large changes in all three of these ECF variables. Challenges beyond those tolerances may be 'corrected' or 'compensated'. While a correction simply reverses the challenge, compensation accommodates the challenge with changes in the other two variables. Most insects osmoregulate by keeping ECF volume and osmotic concentration within a wide range of tolerance. Other insects osmoconform, allowing the ECF osmotic concentration to match the ambient osmotic concentration. Aphids are unique in handling solute and volume loads largely outside the ECF, in the lumen of the gut. This strategy may be related to the apparent absence of Malpighian tubules in aphids. Other insects can suspend ECF homeostasis altogether in order to survive extreme temperatures. Thus, ECF homeostasis in insects is highly dynamic and plastic, which may partly explain why insects remain the most successful class of animals in terms of both species number and biomass. © 2016. Published by The Company of Biologists Ltd.

  10. Navier-Stokes Predictions of Dynamic Stability Derivatives: Evaluation of Steady-State Methods

    National Research Council Canada - National Science Library

    DeSpirito, James; Silton, Sidra I; Weinacht, Paul

    2008-01-01

    The prediction of the dynamic stability derivatives-roll-damping, Magnus, and pitch-damping moments-were evaluated for three spin-stabilized projectiles using steady-state computational fluid dynamic (CFD) calculations...

  11. Dynamic Trading with Predictable Returns and Transaction Costs

    DEFF Research Database (Denmark)

    Gârleanu, Nicolae; Heje Pedersen, Lasse

    2013-01-01

    We derive a closed-form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean-reversion speeds. The optimal strategy is characterized by two principles: (1) aim in front of the target, and (2) trade partially toward the current...

  12. Metal ion transporters and homeostasis.

    OpenAIRE

    Nelson, N

    1999-01-01

    Transition metals are essential for many metabolic processes and their homeostasis is crucial for life. Aberrations in the cellular metal ion concentrations may lead to cell death and severe diseases. Metal ion transporters play a major role in maintaining the correct concentrations of the various metal ions in the different cellular compartments. Recent studies of yeast mutants revealed key elements in metal ion homeostasis, including novel transport systems. Several of the proteins discover...

  13. Construction Worker Fatigue Prediction Model Based on System Dynamic

    OpenAIRE

    Wahyu Adi Tri Joko; Ayu Ratnawinanda Lila

    2017-01-01

    Construction accident can be caused by internal and external factors such as worker fatigue and unsafe project environment. Tight schedule of construction project forcing construction worker to work overtime in long period. This situation leads to worker fatigue. This paper proposes a model to predict construction worker fatigue based on system dynamic (SD). System dynamic is used to represent correlation among internal and external factors and to simulate level of worker fatigue. To validate...

  14. Dynamic Trading with Predictable Returns and Transaction Costs

    DEFF Research Database (Denmark)

    Garleanu, Nicolae; Heje Pedersen, Lasse

    We derive a closed-form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with dierent mean-reversion speeds.The optimal strategy is characterized by two principles: 1) aim in front of the target and 2) trade partially towards the current aim...

  15. Neuronal regulation of homeostasis by nutrient sensing.

    Science.gov (United States)

    Lam, Tony K T

    2010-04-01

    In type 2 diabetes and obesity, the homeostatic control of glucose and energy balance is impaired, leading to hyperglycemia and hyperphagia. Recent studies indicate that nutrient-sensing mechanisms in the body activate negative-feedback systems to regulate energy and glucose homeostasis through a neuronal network. Direct metabolic signaling within the intestine activates gut-brain and gut-brain-liver axes to regulate energy and glucose homeostasis, respectively. In parallel, direct metabolism of nutrients within the hypothalamus regulates food intake and blood glucose levels. These findings highlight the importance of the central nervous system in mediating the ability of nutrient sensing to maintain homeostasis. Futhermore, they provide a physiological and neuronal framework by which enhancing or restoring nutrient sensing in the intestine and the brain could normalize energy and glucose homeostasis in diabetes and obesity.

  16. Dynamical seasonal prediction of Southern African summer precipitation

    CSIR Research Space (South Africa)

    Yuan, C

    2014-01-01

    Full Text Available Pacific as predictors. More recently, they were replaced by two- and one-tiered dynamical 75 forecast systems, but raw model outputs, such as geopotential height at 850 hPa, are often 76 statistically downscaled to achieve better prediction skills... above-normal years, all have a distinct La Niña signal in the tropical Pacific, and 315 among six successfully predicted below-normal years, all but the 2000/2001 austral summer 316 have a distinct El Niño signal. As a result, composites of SST...

  17. Learning predictive statistics from temporal sequences: Dynamics and strategies.

    Science.gov (United States)

    Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

    2017-10-01

    Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

  18. Predicting individual brain maturity using dynamic functional connectivity

    Directory of Open Access Journals (Sweden)

    Jian eQin

    2015-07-01

    Full Text Available Neuroimaging-based functional connectivity (FC analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI (n=183, ages 7-30 and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains.

  19. Pharmacological modulation of mitochondrial calcium homeostasis.

    Science.gov (United States)

    Arduino, Daniela M; Perocchi, Fabiana

    2018-01-10

    Mitochondria are pivotal organelles in calcium (Ca 2+ ) handling and signalling, constituting intracellular checkpoints for numerous processes that are vital for cell life. Alterations in mitochondrial Ca 2+ homeostasis have been linked to a variety of pathological conditions and are critical in the aetiology of several human diseases. Efforts have been taken to harness mitochondrial Ca 2+ transport mechanisms for therapeutic intervention, but pharmacological compounds that direct and selectively modulate mitochondrial Ca 2+ homeostasis are currently lacking. New avenues have, however, emerged with the breakthrough discoveries on the genetic identification of the main players involved in mitochondrial Ca 2+ influx and efflux pathways and with recent hints towards a deep understanding of the function of these molecular systems. Here, we review the current advances in the understanding of the mechanisms and regulation of mitochondrial Ca 2+ homeostasis and its contribution to physiology and human disease. We also introduce and comment on the recent progress towards a systems-level pharmacological targeting of mitochondrial Ca 2+ homeostasis. © 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.

  20. Research on dynamic creep strain and settlement prediction under the subway vibration loading.

    Science.gov (United States)

    Luo, Junhui; Miao, Linchang

    2016-01-01

    This research aims to explore the dynamic characteristics and settlement prediction of soft soil. Accordingly, the dynamic shear modulus formula considering the vibration frequency was utilized and the dynamic triaxial test conducted to verify the validity of the formula. Subsequently, the formula was applied to the dynamic creep strain function, with the factors influencing the improved dynamic creep strain curve of soft soil being analyzed. Meanwhile, the variation law of dynamic stress with sampling depth was obtained through the finite element simulation of subway foundation. Furthermore, the improved dynamic creep strain curve of soil layer was determined based on the dynamic stress. Thereafter, it could to estimate the long-term settlement under subway vibration loading by norms. The results revealed that the dynamic shear modulus formula is straightforward and practical in terms of its application to the vibration frequency. The values predicted using the improved dynamic creep strain formula closed to the experimental values, whilst the estimating settlement closed to the measured values obtained in the field test.

  1. Predicting Mood Changes in Bipolar Disorder through Heartbeat Nonlinear Dynamics.

    Science.gov (United States)

    Valenza, Gaetano; Nardelli, Mimma; Lanata', Antonio; Gentili, Claudio; Bertschy, Gilles; Kosel, Markus; Scilingo, Enzo Pasquale

    2016-04-20

    Bipolar Disorder (BD) is characterized by an alternation of mood states from depression to (hypo)mania. Mixed states, i.e., a combination of depression and mania symptoms at the same time, can also be present. The diagnosis of this disorder in the current clinical practice is based only on subjective interviews and questionnaires, while no reliable objective psychophysiological markers are available. Furthermore, there are no biological markers predicting BD outcomes, or providing information about the future clinical course of the phenomenon. To overcome this limitation, here we propose a methodology predicting mood changes in BD using heartbeat nonlinear dynamics exclusively, derived from the ECG. Mood changes are here intended as transitioning between two mental states: euthymic state (EUT), i.e., the good affective balance, and non-euthymic (non-EUT) states. Heart Rate Variability (HRV) series from 14 bipolar spectrum patients (age: 33.439.76, age range: 23-54; 6 females) involved in the European project PSYCHE, undergoing whole night ECG monitoring were analyzed. Data were gathered from a wearable system comprised of a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire ECGs. Each patient was monitored twice a week, for 14 weeks, being able to perform normal (unstructured) activities. From each acquisition, the longest artifact-free segment of heartbeat dynamics was selected for further analyses. Sub-segments of 5 minutes of this segment were used to estimate trends of HRV linear and nonlinear dynamics. Considering data from a current observation at day t0, and past observations at days (t1, t2,...,), personalized prediction accuracies in forecasting a mood state (EUT/non-EUT) at day t+1 were 69% on average, reaching values as high as 83.3%. This approach opens to the possibility of predicting mood states in bipolar patients through heartbeat nonlinear dynamics exclusively.

  2. Does a dynamic test of phonological awareness predict early reading difficulties?

    DEFF Research Database (Denmark)

    Gellert, Anna Steenberg; Elbro, Carsten

    2017-01-01

    A few studies have indicated that dynamic measures of phonological awareness may contribute uniquely to the prediction of early reading development. However, standard control measures have been few and limited by floor effects, thus limiting their predictive value. The purpose of the present stud...

  3. Tongue and Taste Organ Biology and Function: Homeostasis Maintained by Hedgehog Signaling.

    Science.gov (United States)

    Mistretta, Charlotte M; Kumari, Archana

    2017-02-10

    The tongue is an elaborate complex of heterogeneous tissues with taste organs of diverse embryonic origins. The lingual taste organs are papillae, composed of an epithelium that includes specialized taste buds, the basal lamina, and a lamina propria core with matrix molecules, fibroblasts, nerves, and vessels. Because taste organs are dynamic in cell biology and sensory function, homeostasis requires tight regulation in specific compartments or niches. Recently, the Hedgehog (Hh) pathway has emerged as an essential regulator that maintains lingual taste papillae, taste bud and progenitor cell proliferation and differentiation, and neurophysiological function. Activating or suppressing Hh signaling, with genetic models or pharmacological agents used in cancer treatments, disrupts taste papilla and taste bud integrity and can eliminate responses from taste nerves to chemical stimuli but not to touch or temperature. Understanding Hh regulation of taste organ homeostasis contributes knowledge about the basic biology underlying taste disruptions in patients treated with Hh pathway inhibitors.

  4. Stochastic Ocean Predictions with Dynamically-Orthogonal Primitive Equations

    Science.gov (United States)

    Subramani, D. N.; Haley, P., Jr.; Lermusiaux, P. F. J.

    2017-12-01

    The coastal ocean is a prime example of multiscale nonlinear fluid dynamics. Ocean fields in such regions are complex and intermittent with unstationary heterogeneous statistics. Due to the limited measurements, there are multiple sources of uncertainties, including the initial conditions, boundary conditions, forcing, parameters, and even the model parameterizations and equations themselves. For efficient and rigorous quantification and prediction of these uncertainities, the stochastic Dynamically Orthogonal (DO) PDEs for a primitive equation ocean modeling system with a nonlinear free-surface are derived and numerical schemes for their space-time integration are obtained. Detailed numerical studies with idealized-to-realistic regional ocean dynamics are completed. These include consistency checks for the numerical schemes and comparisons with ensemble realizations. As an illustrative example, we simulate the 4-d multiscale uncertainty in the Middle Atlantic/New York Bight region during the months of Jan to Mar 2017. To provide intitial conditions for the uncertainty subspace, uncertainties in the region were objectively analyzed using historical data. The DO primitive equations were subsequently integrated in space and time. The probability distribution function (pdf) of the ocean fields is compared to in-situ, remote sensing, and opportunity data collected during the coincident POSYDON experiment. Results show that our probabilistic predictions had skill and are 3- to 4- orders of magnitude faster than classic ensemble schemes.

  5. A multi-scale model of hepcidin promoter regulation reveals factors controlling systemic iron homeostasis.

    Directory of Open Access Journals (Sweden)

    Guillem Casanovas

    2014-01-01

    Full Text Available Systemic iron homeostasis involves a negative feedback circuit in which the expression level of the peptide hormone hepcidin depends on and controls the iron blood levels. Hepcidin expression is regulated by the BMP6/SMAD and IL6/STAT signaling cascades. Deregulation of either pathway causes iron-related diseases such as hemochromatosis or anemia of inflammation. We quantitatively analyzed how BMP6 and IL6 control hepcidin expression. Transcription factor (TF phosphorylation and reporter gene expression were measured under co-stimulation conditions, and the promoter was perturbed by mutagenesis. Using mathematical modeling, we systematically analyzed potential mechanisms of cooperative and competitive promoter regulation by the transcription factors, and experimentally validated the model predictions. Our results reveal that hepcidin cross-regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signaling crosstalk is insignificant. We find that the presence of two BMP-responsive elements enhances the steepness of the promoter response towards the iron-sensing BMP signaling axis, which promotes iron homeostasis in vivo. IL6 co-stimulation reduces the promoter sensitivity towards the BMP signal, because the SMAD and STAT transcription factors compete for recruiting RNA polymerase to the transcription start site. This may explain why inflammatory signals disturb iron homeostasis in anemia of inflammation. Taken together, our results reveal why the iron homeostasis circuit is sensitive to perturbations implicated in disease.

  6. Molecular aspects of glucose homeostasis in skeletal muscle--A focus on the molecular mechanisms of insulin resistance.

    Science.gov (United States)

    Carnagarin, Revathy; Dharmarajan, Arun M; Dass, Crispin R

    2015-12-05

    Among all the varied actions of insulin, regulation of glucose homeostasis is the most critical and intensively studied. With the availability of glucose from nutrient metabolism, insulin action in muscle results in increased glucose disposal via uptake from the circulation and storage of excess, thereby maintaining euglycemia. This major action of insulin is executed by redistribution of the glucose transporter protein, GLUT4 from intracellular storage sites to the plasma membrane and storage of glucose in the form of glycogen which also involves modulation of actin dynamics that govern trafficking of all the signal proteins of insulin signal transduction. The cellular mechanisms responsible for these trafficking events and the defects associated with insulin resistance are largely enigmatic, and this review provides a consolidated overview of the various molecular mechanisms involved in insulin-dependent glucose homeostasis in skeletal muscle, as insulin resistance at this major peripheral site impacts whole body glucose homeostasis. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. Redox homeostasis: The Golden Mean of healthy living

    Directory of Open Access Journals (Sweden)

    Fulvio Ursini

    2016-08-01

    Full Text Available The notion that electrophiles serve as messengers in cell signaling is now widely accepted. Nonetheless, major issues restrain acceptance of redox homeostasis and redox signaling as components of maintenance of a normal physiological steady state. The first is that redox signaling requires sudden switching on of oxidant production and bypassing of antioxidant mechanisms rather than a continuous process that, like other signaling mechanisms, can be smoothly turned up or down. The second is the misperception that reactions in redox signaling involve “reactive oxygen species” rather than reaction of specific electrophiles with specific protein thiolates. The third is that hormesis provides protection against oxidants by increasing cellular defense or repair mechanisms rather than by specifically addressing the offset of redox homeostasis. Instead, we propose that both oxidant and antioxidant signaling are main features of redox homeostasis. As the redox shift is rapidly reversed by feedback reactions, homeostasis is maintained by continuous signaling for production and elimination of electrophiles and nucleophiles. Redox homeostasis, which is the maintenance of nucleophilic tone, accounts for a healthy physiological steady state. Electrophiles and nucleophiles are not intrinsically harmful or protective, and redox homeostasis is an essential feature of both the response to challenges and subsequent feedback. While the balance between oxidants and nucleophiles is preserved in redox homeostasis, oxidative stress provokes the establishment of a new radically altered redox steady state. The popular belief that scavenging free radicals by antioxidants has a beneficial effect is wishful thinking. We propose, instead, that continuous feedback preserves nucleophilic tone and that this is supported by redox active nutritional phytochemicals. These nonessential compounds, by activating Nrf2, mimic the effect of endogenously produced electrophiles

  8. A consensus approach for estimating the predictive accuracy of dynamic models in biology.

    Science.gov (United States)

    Villaverde, Alejandro F; Bongard, Sophia; Mauch, Klaus; Müller, Dirk; Balsa-Canto, Eva; Schmid, Joachim; Banga, Julio R

    2015-04-01

    Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  9. Comparison of RF spectrum prediction methods for dynamic spectrum access

    Science.gov (United States)

    Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

    2017-05-01

    Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

  10. Power system dynamic state estimation using prediction based evolutionary technique

    International Nuclear Information System (INIS)

    Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

    2016-01-01

    In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

  11. Predicting responsiveness to intervention in dyslexia using dynamic assessment

    NARCIS (Netherlands)

    Aravena, S.; Tijms, J.; Snellings, P.; van der Molen, M.W.

    In the current study we examined the value of a dynamic test for predicting responsiveness to reading intervention for children diagnosedwith dyslexia. The test consisted of a 20-minute training aimed at learning eight basic letter–speech sound correspondences within an artificial orthography,

  12. Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2017-10-01

    Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

  13. A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

    Directory of Open Access Journals (Sweden)

    Meng Fan-Bo

    2016-01-01

    Full Text Available Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.

  14. In Silico Identification of Potent PPAR-γ Agonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study

    Directory of Open Access Journals (Sweden)

    Kuan-Chung Chen

    2014-01-01

    Full Text Available The peroxisome proliferator-activated receptors (PPARs related to regulation of lipid metabolism, inflammation, cell proliferation, differentiation, and glucose homeostasis by controlling the related ligand-dependent transcription of networks of genes. They are used to be served as therapeutic targets against metabolic disorder, such as obesity, dyslipidemia, and diabetes; especially, PPAR-γ is the most extensively investigated isoform for the treatment of dyslipidemic type 2 diabetes. In this study, we filter compounds of traditional Chinese medicine (TCM using bioactivities predicted by three distinct prediction models before the virtual screening. For the top candidates, the molecular dynamics (MD simulations were also utilized to investigate the stability of interactions between ligand and PPAR-γ protein. The top two TCM candidates, 5-hydroxy-L-tryptophan and abrine, have an indole ring and carboxyl group to form the H-bonds with the key residues of PPAR-γ protein, such as residues Ser289 and Lys367. The secondary amine group of abrine also stabilized an H-bond with residue Ser289. From the figures of root mean square fluctuations (RMSFs, the key residues were stabilized in protein complexes with 5-Hydroxy-L-tryptophan and abrine as control. Hence, we propose 5-hydroxy-L-tryptophan and abrine as potential lead compounds for further study in drug development process with the PPAR-γ protein.

  15. Prediction of methyl-side Chain Dynamics in Proteins

    International Nuclear Information System (INIS)

    Ming Dengming; Brueschweiler, Rafael

    2004-01-01

    A simple analytical model is presented for the prediction of methyl-side chain dynamics in comparison with S 2 order parameters obtained by NMR relaxation spectroscopy. The model, which is an extension of the local contact model for backbone order parameter prediction, uses a static 3D protein structure as input. It expresses the methyl-group S 2 order parameters as a function of local contacts of the methyl carbon with respect to the neighboring atoms in combination with the number of consecutive mobile dihedral angles between the methyl group and the protein backbone. For six out of seven proteins the prediction results are good when compared with experimentally determined methyl-group S 2 values with an average correlation coefficient r-bar=0.65±0.14. For the unusually rigid cytochrome c 2 no significant correlation between prediction and experiment is found. The presented model provides independent support for the reliability of current side-chain relaxation methods along with their interpretation by the model-free formalism

  16. Modeling proteasome dynamics in Parkinson's disease

    International Nuclear Information System (INIS)

    Sneppen, Kim; Lizana, Ludvig; Jensen, Mogens H; Pigolotti, Simone; Otzen, Daniel

    2009-01-01

    In Parkinson's disease (PD), there is evidence that α-synuclein (αSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin–proteasome system. Here, we develop a simple dynamical model for the on-going conflict between αSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature αSN fibrils and their protofilament precursors. In the presence of excess proteasomes the cell easily maintains homeostasis. However, when the ratio between the available proteasome and the αSN protofilaments is reduced below a threshold level, we predict a collapse of homeostasis and onset of oscillations in the proteasome concentration. Depleted proteasome opens for accumulation of oligomers. Our analysis suggests that the onset of PD is associated with a proteasome population that becomes occupied in periodic degradation of aggregates. This behavior is found to be the general state of a proteasome/chaperone system under pressure, and suggests new interpretations of other diseases where protein aggregation could stress elements of the protein quality control system

  17. Nature versus nurture: Predictability in low-temperature Ising dynamics

    Science.gov (United States)

    Ye, J.; Machta, J.; Newman, C. M.; Stein, D. L.

    2013-10-01

    Consider a dynamical many-body system with a random initial state subsequently evolving through stochastic dynamics. What is the relative importance of the initial state (“nature”) versus the realization of the stochastic dynamics (“nurture”) in predicting the final state? We examined this question for the two-dimensional Ising ferromagnet following an initial deep quench from T=∞ to T=0. We performed Monte Carlo studies on the overlap between “identical twins” raised in independent dynamical environments, up to size L=500. Our results suggest an overlap decaying with time as t-θh with θh=0.22±0.02; the same exponent holds for a quench to low but nonzero temperature. This “heritability exponent” may equal the persistence exponent for the two-dimensional Ising ferromagnet, but the two differ more generally.

  18. Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.

    Science.gov (United States)

    Suresh, Krithika; Taylor, Jeremy M G; Spratt, Daniel E; Daignault, Stephanie; Tsodikov, Alexander

    2017-11-01

    Dynamic prediction incorporates time-dependent marker information accrued during follow-up to improve personalized survival prediction probabilities. At any follow-up, or "landmark", time, the residual time distribution for an individual, conditional on their updated marker values, can be used to produce a dynamic prediction. To satisfy a consistency condition that links dynamic predictions at different time points, the residual time distribution must follow from a prediction function that models the joint distribution of the marker process and time to failure, such as a joint model. To circumvent the assumptions and computational burden associated with a joint model, approximate methods for dynamic prediction have been proposed. One such method is landmarking, which fits a Cox model at a sequence of landmark times, and thus is not a comprehensive probability model of the marker process and the event time. Considering an illness-death model, we derive the residual time distribution and demonstrate that the structure of the Cox model baseline hazard and covariate effects under the landmarking approach do not have simple form. We suggest some extensions of the landmark Cox model that should provide a better approximation. We compare the performance of the landmark models with joint models using simulation studies and cognitive aging data from the PAQUID study. We examine the predicted probabilities produced under both methods using data from a prostate cancer study, where metastatic clinical failure is a time-dependent covariate for predicting death following radiation therapy. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Energy homeostasis and running wheel activity during pregnancy in the mouse.

    Science.gov (United States)

    Ladyman, S R; Carter, K M; Grattan, D R

    2018-05-05

    Pregnancy and lactation are metabolically challenging states, where the mother must supply all the energy requirements for the developing fetus and growing pups respectively. The aim of the current study was to characterize many aspects of energy homeostasis before and during pregnancy in the mouse, and to examine the role of voluntary activity on changes in energy expenditure during pregnancy. In a secondary aim, we evaluate measures of energy homeostasis during pregnancy in mice that successfully reared their litter or in mice that went on to abandon their litter, to determine if an impairment in pregnancy-induced adaptation of energy homeostasis might underlie the abandonment of pups soon after birth. During pregnancy, food intake was increased, characterized by increased meal size and duration but not number of meals per day. The duration of time spent inactive, predicted to indicate sleep behaviour, was increased both early and late in pregnancy compared to pre-pregnancy levels. Increased x + y beam breaks, as a measure of activity increased during pregnancy and this reflected an increase in ambulatory behaviour in mid pregnancy and an increase in non-ambulatory movement in late pregnancy. Energy expenditure, as measured by indirect calorimetry, increased across pregnancy, likely due to the growth and development of fetal tissue. There was also a dramatic reduction in voluntary wheel running as soon as the mice became pregnant. Compared with successful pregnancies and lactations, pregnancies where pups were abandoned soon after birth were associated with reduced body weight gain and an increase in running wheel activity at the end of pregnancy, but no difference in food intake or energy expenditure. Overall, during pregnancy there are multiple adaptations to change energy homeostasis, resulting in partitioning of provisions of energy to the developing fetus and storing energy for future metabolic demands. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Acute loss of the hepatic endo-lysosomal system in vivo causes compensatory changes in iron homeostasis.

    Science.gov (United States)

    Metzendorf, Christoph; Zeigerer, Anja; Seifert, Sarah; Sparla, Richard; Najafi, Bahar; Canonne-Hergaux, François; Zerial, Marino; Muckenthaler, Martina U

    2017-06-22

    Liver cells communicate with the extracellular environment to take up nutrients via endocytosis. Iron uptake is essential for metabolic activities and cell homeostasis. Here, we investigated the role of the endocytic system for maintaining iron homeostasis. We specifically depleted the small GTPase Rab5 in the mouse liver, causing a transient loss of the entire endo-lysosomal system. Strikingly, endosome depletion led to a fast reduction of hepatic iron levels, which was preceded by an increased abundance of the iron exporter ferroportin. Compensatory changes in livers of Rab5-depleted mice include increased expression of transferrin receptor 1 as well as reduced expression of the iron-regulatory hormone hepcidin. Serum iron indices (serum iron, free iron binding capacity and total iron binding capacity) in Rab5-KD mice were increased, consistent with an elevated splenic and hepatic iron export. Our data emphasize the critical importance of the endosomal compartments in hepatocytes to maintain hepatic and systemic iron homeostasis in vivo. The short time period (between day four and five) upon which these changes occur underscore the fast dynamics of the liver iron pool.

  1. INTRACELLULAR Ca2+ HOMEOSTASIS

    Directory of Open Access Journals (Sweden)

    Shahdevi Nandar Kurniawan

    2015-01-01

    Full Text Available Ca2+ signaling functions to regulate many cellular processes. Dynamics of Ca2+ signaling or homeostasis is regulated by the interaction between ON and OFF reactions that control Ca2+ flux in both the plasma membrane and internal organelles such as the endoplasmic reticulum (ER and mitochondria. External stimuli activate the ON reactions, which include Ca2+ into the cytoplasm either through channels in the plasma membrane or from internal storage like in ER. Most of the cells utilize both channels/sources, butthere area few cells using an external or internal source to control certain processes. Most of the Ca2+ entering the cytoplasm adsorbed to the buffer, while a smaller part activate effect or to stimulate cellular processes. Reaction OFF is pumping of cytoplasmic Ca2+ using a combination mechanism of mitochondrial and others. Changes in Ca2+ signal has been detected in various tissues isolated from animals induced into diabetes as well as patients with diabetes. Ca2+ signal interference is also found in sensory neurons of experimental animals with diabetes. Ca2+ signaling is one of the main signaling systems in the cell.

  2. Maintaining homeostasis by decision-making.

    Directory of Open Access Journals (Sweden)

    Christoph W Korn

    2015-05-01

    Full Text Available Living organisms need to maintain energetic homeostasis. For many species, this implies taking actions with delayed consequences. For example, humans may have to decide between foraging for high-calorie but hard-to-get, and low-calorie but easy-to-get food, under threat of starvation. Homeostatic principles prescribe decisions that maximize the probability of sustaining appropriate energy levels across the entire foraging trajectory. Here, predictions from biological principles contrast with predictions from economic decision-making models based on maximizing the utility of the endpoint outcome of a choice. To empirically arbitrate between the predictions of biological and economic models for individual human decision-making, we devised a virtual foraging task in which players chose repeatedly between two foraging environments, lost energy by the passage of time, and gained energy probabilistically according to the statistics of the environment they chose. Reaching zero energy was framed as starvation. We used the mathematics of random walks to derive endpoint outcome distributions of the choices. This also furnished equivalent lotteries, presented in a purely economic, casino-like frame, in which starvation corresponded to winning nothing. Bayesian model comparison showed that--in both the foraging and the casino frames--participants' choices depended jointly on the probability of starvation and the expected endpoint value of the outcome, but could not be explained by economic models based on combinations of statistical moments or on rank-dependent utility. This implies that under precisely defined constraints biological principles are better suited to explain human decision-making than economic models based on endpoint utility maximization.

  3. Do resting brain dynamics predict oddball evoked-potential?

    Directory of Open Access Journals (Sweden)

    Lee Tien-Wen

    2011-11-01

    Full Text Available Abstract Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP is still not clear. This study explored the relationship between resting electroencephalography (EEG and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection.

  4. Osmotic homeostasis and NKLy lymphoma cells radiosensitivity

    International Nuclear Information System (INIS)

    Tishchenko, V.V.; Magda, I.N.

    1992-01-01

    In experiments with cells of ascites NKLy lymphoma differing in ploidy and position in the cell cycle, a study was made of the radiosensitivity, osmotic homeostasis peculiarities and thermoradiation changes in potassium content. It was shown that the resistance of osmotic homeostasis of NKLy cells to thermoradiation correlated with their radioresistance

  5. Redox homeostasis: The Golden Mean of healthy living.

    Science.gov (United States)

    Ursini, Fulvio; Maiorino, Matilde; Forman, Henry Jay

    2016-08-01

    The notion that electrophiles serve as messengers in cell signaling is now widely accepted. Nonetheless, major issues restrain acceptance of redox homeostasis and redox signaling as components of maintenance of a normal physiological steady state. The first is that redox signaling requires sudden switching on of oxidant production and bypassing of antioxidant mechanisms rather than a continuous process that, like other signaling mechanisms, can be smoothly turned up or down. The second is the misperception that reactions in redox signaling involve "reactive oxygen species" rather than reaction of specific electrophiles with specific protein thiolates. The third is that hormesis provides protection against oxidants by increasing cellular defense or repair mechanisms rather than by specifically addressing the offset of redox homeostasis. Instead, we propose that both oxidant and antioxidant signaling are main features of redox homeostasis. As the redox shift is rapidly reversed by feedback reactions, homeostasis is maintained by continuous signaling for production and elimination of electrophiles and nucleophiles. Redox homeostasis, which is the maintenance of nucleophilic tone, accounts for a healthy physiological steady state. Electrophiles and nucleophiles are not intrinsically harmful or protective, and redox homeostasis is an essential feature of both the response to challenges and subsequent feedback. While the balance between oxidants and nucleophiles is preserved in redox homeostasis, oxidative stress provokes the establishment of a new radically altered redox steady state. The popular belief that scavenging free radicals by antioxidants has a beneficial effect is wishful thinking. We propose, instead, that continuous feedback preserves nucleophilic tone and that this is supported by redox active nutritional phytochemicals. These nonessential compounds, by activating Nrf2, mimic the effect of endogenously produced electrophiles (parahormesis). In summary

  6. Contribution of Dynamic Vegetation Phenology to Decadal Climate Predictability

    NARCIS (Netherlands)

    Weiss, M.; Miller, P.A.; Hurk, van den B.J.J.M.; Noije, van T.; Stefanescu, S.; Haarsma, R.; Ulft, van L.H.; Hazeleger, W.; Sager, Le P.; Smith, B.; Schurgers, G.

    2014-01-01

    In this study, the impact of coupling and initializing the leaf area index from the dynamic vegetation model Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) is analyzed on skill of decadal predictions in the fully coupled atmosphere-land-ocean-sea ice model, the European Consortium Earth

  7. A dynamic particle filter-support vector regression method for reliability prediction

    International Nuclear Information System (INIS)

    Wei, Zhao; Tao, Tao; ZhuoShu, Ding; Zio, Enrico

    2013-01-01

    Support vector regression (SVR) has been applied to time series prediction and some works have demonstrated the feasibility of its use to forecast system reliability. For accuracy of reliability forecasting, the selection of SVR's parameters is important. The existing research works on SVR's parameters selection divide the example dataset into training and test subsets, and tune the parameters on the training data. However, these fixed parameters can lead to poor prediction capabilities if the data of the test subset differ significantly from those of training. Differently, the novel method proposed in this paper uses particle filtering to estimate the SVR model parameters according to the whole measurement sequence up to the last observation instance. By treating the SVR training model as the observation equation of a particle filter, our method allows updating the SVR model parameters dynamically when a new observation comes. Because of the adaptability of the parameters to dynamic data pattern, the new PF–SVR method has superior prediction performance over that of standard SVR. Four application results show that PF–SVR is more robust than SVR to the decrease of the number of training data and the change of initial SVR parameter values. Also, even if there are trends in the test data different from those in the training data, the method can capture the changes, correct the SVR parameters and obtain good predictions. -- Highlights: •A dynamic PF–SVR method is proposed to predict the system reliability. •The method can adjust the SVR parameters according to the change of data. •The method is robust to the size of training data and initial parameter values. •Some cases based on both artificial and real data are studied. •PF–SVR shows superior prediction performance over standard SVR

  8. Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

    Science.gov (United States)

    Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

    2014-11-26

    Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

  9. Construction Worker Fatigue Prediction Model Based on System Dynamic

    Directory of Open Access Journals (Sweden)

    Wahyu Adi Tri Joko

    2017-01-01

    Full Text Available Construction accident can be caused by internal and external factors such as worker fatigue and unsafe project environment. Tight schedule of construction project forcing construction worker to work overtime in long period. This situation leads to worker fatigue. This paper proposes a model to predict construction worker fatigue based on system dynamic (SD. System dynamic is used to represent correlation among internal and external factors and to simulate level of worker fatigue. To validate the model, 93 construction workers whom worked in a high rise building construction projects, were used as case study. The result shows that excessive workload, working elevation and age, are the main factors lead to construction worker fatigue. Simulation result also shows that these factors can increase worker fatigue level to 21.2% times compared to normal condition. Beside predicting worker fatigue level this model can also be used as early warning system to prevent construction worker accident

  10. Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

    Science.gov (United States)

    Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

    2018-03-01

    In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

  11. Bridge Deterioration Prediction Model Based On Hybrid Markov-System Dynamic

    Directory of Open Access Journals (Sweden)

    Widodo Soetjipto Jojok

    2017-01-01

    Full Text Available Instantaneous bridge failure tends to increase in Indonesia. To mitigate this condition, Indonesia’s Bridge Management System (I-BMS has been applied to continuously monitor the condition of bridges. However, I-BMS only implements visual inspection for maintenance priority of the bridge structure component instead of bridge structure system. This paper proposes a new bridge failure prediction model based on hybrid Markov-System Dynamic (MSD. System dynamic is used to represent the correlation among bridge structure components while Markov chain is used to calculate temporal probability of the bridge failure. Around 235 data of bridges in Indonesia were collected from Directorate of Bridge the Ministry of Public Works and Housing for calculating transition probability of the model. To validate the model, a medium span concrete bridge was used as a case study. The result shows that the proposed model can accurately predict the bridge condition. Besides predicting the probability of the bridge failure, this model can also be used as an early warning system for bridge monitoring activity.

  12. Transcriptome dynamics-based operon prediction in prokaryotes.

    Science.gov (United States)

    Fortino, Vittorio; Smolander, Olli-Pekka; Auvinen, Petri; Tagliaferri, Roberto; Greco, Dario

    2014-05-16

    Inferring operon maps is crucial to understanding the regulatory networks of prokaryotic genomes. Recently, RNA-seq based transcriptome studies revealed that in many bacterial species the operon structure vary with the change of environmental conditions. Therefore, new computational solutions that use both static and dynamic data are necessary to create condition specific operon predictions. In this work, we propose a novel classification method that integrates RNA-seq based transcriptome profiles with genomic sequence features to accurately identify the operons that are expressed under a measured condition. The classifiers are trained on a small set of confirmed operons and then used to classify the remaining gene pairs of the organism studied. Finally, by linking consecutive gene pairs classified as operons, our computational approach produces condition-dependent operon maps. We evaluated our approach on various RNA-seq expression profiles of the bacteria Haemophilus somni, Porphyromonas gingivalis, Escherichia coli and Salmonella enterica. Our results demonstrate that, using features depending on both transcriptome dynamics and genome sequence characteristics, we can identify operon pairs with high accuracy. Moreover, the combination of DNA sequence and expression data results in more accurate predictions than each one alone. We present a computational strategy for the comprehensive analysis of condition-dependent operon maps in prokaryotes. Our method can be used to generate condition specific operon maps of many bacterial organisms for which high-resolution transcriptome data is available.

  13. TSH and Thyrotropic Agonists: Key Actors in Thyroid Homeostasis

    Science.gov (United States)

    Dietrich, Johannes W.; Landgrafe, Gabi; Fotiadou, Elisavet H.

    2012-01-01

    This paper provides the reader with an overview of our current knowledge of hypothalamic-pituitary-thyroid feedback from a cybernetic standpoint. Over the past decades we have gained a plethora of information from biochemical, clinical, and epidemiological investigation, especially on the role of TSH and other thyrotropic agonists as critical components of this complex relationship. Integrating these data into a systems perspective delivers new insights into static and dynamic behaviour of thyroid homeostasis. Explicit usage of this information with mathematical methods promises to deliver a better understanding of thyrotropic feedback control and new options for personalised diagnosis of thyroid dysfunction and targeted therapy, also by permitting a new perspective on the conundrum of the TSH reference range. PMID:23365787

  14. Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

    Science.gov (United States)

    Reagan, Andrew J; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M

    2016-01-01

    A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

  15. Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

    Directory of Open Access Journals (Sweden)

    Andrew J Reagan

    Full Text Available A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

  16. Telomere dynamics and homeostasis in a transmissible cancer.

    Science.gov (United States)

    Ujvari, Beata; Pearse, Anne-Maree; Taylor, Robyn; Pyecroft, Stephen; Flanagan, Cassandra; Gombert, Sara; Papenfuss, Anthony T; Madsen, Thomas; Belov, Katherine

    2012-01-01

    Devil Facial Tumour Disease (DFTD) is a unique clonal cancer that threatens the world's largest carnivorous marsupial, the Tasmanian devil (Sarcophilus harrisii) with extinction. This transmissible cancer is passed between individual devils by cell implantation during social interactions. The tumour arose in a Schwann cell of a single devil over 15 years ago and since then has expanded clonally, without showing signs of replicative senescence; in stark contrast to a somatic cell that displays a finite capacity for replication, known as the "Hayflick limit". In the present study we investigate the role of telomere length, measured as Telomere Copy Number (TCN), and telomerase and shelterin gene expression, as well as telomerase activity in maintaining hyperproliferation of Devil Facial Tumour (DFT) cells. Our results show that DFT cells have short telomeres. DFTD TCN does not differ between geographic regions or between strains. However, TCN has increased over time. Unlimited cell proliferation is likely to have been achieved through the observed up-regulation of the catalytic subunit of telomerase (TERT) and concomitant activation of telomerase. Up-regulation of the central component of shelterin, the TRF1-intercating nuclear factor 2 (TINF2) provides DFT a mechanism for telomere length homeostasis. The higher expression of both TERT and TINF2 may also protect DFT cells from genomic instability and enhance tumour proliferation. DFT cells appear to monitor and regulate the length of individual telomeres: i.e. shorter telomeres are elongated by up-regulation of telomerase-related genes; longer telomeres are protected from further elongation by members of the shelterin complex, which may explain the lack of spatial and strain variation in DFT telomere copy number. The observed longitudinal increase in gene expression in DFT tissue samples and telomerase activity in DFT cell lines might indicate a selection for more stable tumours with higher proliferative potential.

  17. Telomere dynamics and homeostasis in a transmissible cancer.

    Directory of Open Access Journals (Sweden)

    Beata Ujvari

    Full Text Available Devil Facial Tumour Disease (DFTD is a unique clonal cancer that threatens the world's largest carnivorous marsupial, the Tasmanian devil (Sarcophilus harrisii with extinction. This transmissible cancer is passed between individual devils by cell implantation during social interactions. The tumour arose in a Schwann cell of a single devil over 15 years ago and since then has expanded clonally, without showing signs of replicative senescence; in stark contrast to a somatic cell that displays a finite capacity for replication, known as the "Hayflick limit".In the present study we investigate the role of telomere length, measured as Telomere Copy Number (TCN, and telomerase and shelterin gene expression, as well as telomerase activity in maintaining hyperproliferation of Devil Facial Tumour (DFT cells. Our results show that DFT cells have short telomeres. DFTD TCN does not differ between geographic regions or between strains. However, TCN has increased over time. Unlimited cell proliferation is likely to have been achieved through the observed up-regulation of the catalytic subunit of telomerase (TERT and concomitant activation of telomerase. Up-regulation of the central component of shelterin, the TRF1-intercating nuclear factor 2 (TINF2 provides DFT a mechanism for telomere length homeostasis. The higher expression of both TERT and TINF2 may also protect DFT cells from genomic instability and enhance tumour proliferation.DFT cells appear to monitor and regulate the length of individual telomeres: i.e. shorter telomeres are elongated by up-regulation of telomerase-related genes; longer telomeres are protected from further elongation by members of the shelterin complex, which may explain the lack of spatial and strain variation in DFT telomere copy number. The observed longitudinal increase in gene expression in DFT tissue samples and telomerase activity in DFT cell lines might indicate a selection for more stable tumours with higher proliferative

  18. Adipose Type One Innate Lymphoid Cells Regulate Macrophage Homeostasis through Targeted Cytotoxicity.

    Science.gov (United States)

    Boulenouar, Selma; Michelet, Xavier; Duquette, Danielle; Alvarez, David; Hogan, Andrew E; Dold, Christina; O'Connor, Donal; Stutte, Suzanne; Tavakkoli, Ali; Winters, Desmond; Exley, Mark A; O'Shea, Donal; Brenner, Michael B; von Andrian, Ulrich; Lynch, Lydia

    2017-02-21

    Adipose tissue has a dynamic immune system that adapts to changes in diet and maintains homeostatic tissue remodeling. Adipose type 1 innate lymphoid cells (AT1-ILCs) promote pro-inflammatory macrophages in obesity, but little is known about their functions at steady state. Here we found that human and murine adipose tissue harbor heterogeneous populations of AT1-ILCs. Experiments using parabiotic mice fed a high-fat diet (HFD) showed differential trafficking of AT1-ILCs, particularly in response to short- and long-term HFD and diet restriction. At steady state, AT1-ILCs displayed cytotoxic activity toward adipose tissue macrophages (ATMs). Depletion of AT1-ILCs and perforin deficiency resulted in alterations in the ratio of inflammatory to anti-inflammatory ATMs, and adoptive transfer of AT1-ILCs exacerbated metabolic disorder. Diet-induced obesity impaired AT1-ILC killing ability. Our findings reveal a role for AT1-ILCs in regulating ATM homeostasis through cytotoxicity and suggest that this function is relevant in both homeostasis and metabolic disease. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2015-01-01

    Full Text Available To tackle the sensitivity to outliers in system identification, a new robust dynamic partial least squares (PLS model based on an outliers detection method is proposed in this paper. An improved radial basis function network (RBFN is adopted to construct the predictive model from inputs and outputs dataset, and a hidden Markov model (HMM is applied to detect the outliers. After outliers are removed away, a more robust dynamic PLS model is obtained. In addition, an improved generalized predictive control (GPC with the tuning weights under dynamic PLS framework is proposed to deal with the interaction which is caused by the model mismatch. The results of two simulations demonstrate the effectiveness of proposed method.

  20. Dynamical prediction and pattern mapping in short-term load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Aguirre, Luis Antonio; Rodrigues, Daniela D.; Lima, Silvio T. [Departamento de Engenharia Eletronica, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil); Martinez, Carlos Barreira [Departamento de Engenharia Hidraulica e Recursos Hidricos, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil)

    2008-01-15

    This work will not put forward yet another scheme for short-term load forecasting but rather will provide evidences that may improve our understanding about fundamental issues which underlay load forecasting problems. In particular, load forecasting will be decomposed into two main problems, namely dynamical prediction and pattern mapping. It is argued that whereas the latter is essentially static and becomes nonlinear when weekly features in the data are taken into account, the former might not be deterministic at all. In such cases there is no determinism (serial correlations) in the data apart from the average cycle and the best a model can do is to perform pattern mapping. Moreover, when there is determinism in addition to the average cycle, the underlying dynamics are sometimes linear, in which case there is no need to resort to nonlinear models to perform dynamical prediction. Such conclusions were confirmed using real load data and surrogate data analysis. In a sense, the paper details and organizes some general beliefs found in the literature on load forecasting. This sheds some light on real model-building and forecasting problems and helps understand some apparently conflicting results reported in the literature. (author)

  1. Application of artificial neural networks for predicting the impact of rolling dynamic compaction using dynamic cone penetrometer test results

    Directory of Open Access Journals (Sweden)

    R.A.T.M. Ranasinghe

    2017-04-01

    Full Text Available Rolling dynamic compaction (RDC, which involves the towing of a noncircular module, is now widespread and accepted among many other soil compaction methods. However, to date, there is no accurate method for reliable prediction of the densification of soil and the extent of ground improvement by means of RDC. This study presents the application of artificial neural networks (ANNs for a priori prediction of the effectiveness of RDC. The models are trained with in situ dynamic cone penetration (DCP test data obtained from previous civil projects associated with the 4-sided impact roller. The predictions from the ANN models are in good agreement with the measured field data, as indicated by the model correlation coefficient of approximately 0.8. It is concluded that the ANN models developed in this study can be successfully employed to provide more accurate prediction of the performance of the RDC on a range of soil types.

  2. Prediction of heat-illness symptoms with the prediction of human vascular response in hot environment under resting condition.

    Science.gov (United States)

    Aggarwal, Yogender; Karan, Bhuwan Mohan; Das, Barsa Nand; Sinha, Rakesh Kumar

    2008-04-01

    The thermoregulatory control of human skin blood flow is vital to maintain the body heat storage during challenges of thermal homeostasis under heat stress. Whenever thermal homeostasis disturbed, the heat load exceeds heat dissipation capacity, which alters the cutaneous vascular responses along with other body physiological variables. Whole body skin blood flow has been calculated from the forearm blood flow. Present model has been designed using electronics circuit simulator (Multisim 8.0, National Instruments, USA), is to execute a series of predictive equations for early prediction of physiological parameters of young nude subjects during resting condition at various level of dry heat stress under almost still air to avoid causalities associated with hot environmental. The users can execute the model by changing the environmental temperature in degrees C and exposure time in minutes. The model would be able to predict and detect the changes in human vascular responses along with other physiological parameters and from this predicted values heat related-illness symptoms can be inferred.

  3. Three-component homeostasis control

    Science.gov (United States)

    Xu, Jin; Hong, Hyunsuk; Jo, Junghyo

    2014-03-01

    Two reciprocal components seem to be sufficient to maintain a control variable constant. However, pancreatic islets adapt three components to control glucose homeostasis. They are α (secreting glucagon), β (insulin), and δ (somatostatin) cells. Glucagon and insulin are the reciprocal hormones for increasing and decreasing blood glucose levels, while the role of somatostatin is unknown. However, it has been known how each hormone affects other cell types. Based on the pulsatile hormone secretion and the cellular interactions, this system can be described as coupled oscillators. In particular, we used the Landau-Stuart model to consider both amplitudes and phases of hormone oscillations. We found that the presence of the third component, δ cell, was effective to resist under glucose perturbations, and to quickly return to the normal glucose level once perturbed. Our analysis suggested that three components are necessary for advanced homeostasis control.

  4. PREDICTION OF DENGUE FEVER EPIDEMIC SPREADING USING DYNAMICS TRANSMISSION VECTOR MODEL

    Directory of Open Access Journals (Sweden)

    Retno Widyaningrum

    2014-05-01

    Full Text Available Increasing number of dengue cases in Surabaya shows that its city has high potential of dengue fever epidemic. Although some policies were designed by Surabaya Health Department, such as fogging and mosquito’s nest eradication, but these efforts still out of target because of inaccurate predictions. Ineffectiveness eradication of dengue fever epidemic is caused by lack of information and knowledge on environmental conditions in Surabaya. Developing spread and prediction system to minimize dengue fever epidemic is necessary to be conducted immediately. Spread and prediction system can improve eradication and prevention accuracy. The transmission dynamics vector simulation will be used as an approach to draw a complex system ofmosquito life cycle in which involve a lot offactors. Dynamics transmission model used to build model in mosquito model (oviposition rate and pre adult mosquito, infected and death cases in dengue fever. The model of mosquito and infected population can represent system. The output of this research is website of spread and prediction system of dengue fever epidemics to predict growth rate of Aedes Aegypti mosquito, infected, and death population because of dengue fever epidemics. The deviation of infected population is 0,519. The model of death cases in dengue fever is less precision with the deviation 1,229. Death cases model need improvement by adding some variables that influence to dengue fever death cases. Spread ofdengue fever prediction will help the government, health department to decide the best policies in minimizing the spread ofdengue fever epidemics.

  5. Challenges in microbial ecology: Building predictive understanding of community function and dynamics

    DEFF Research Database (Denmark)

    Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

    2016-01-01

    The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...... is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved....

  6. Dynamic Model of Centrifugal Compressor for Prediction of Surge Evolution and Performance Variations

    International Nuclear Information System (INIS)

    Jung, Mooncheong; Han, Jaeyoung; Yu, Sangseok

    2016-01-01

    When a control algorithm is developed to protect automotive compressor surges, the simulation model typically selects an empirically determined look-up table. However, it is difficult for a control oriented empirical model to show surge characteristics of the super charger. In this study, a dynamic supercharger model is developed to predict the performance of a centrifugal compressor under dynamic load follow-up. The model is developed using Simulink® environment, and is composed of a compressor, throttle body, valves, and chamber. Greitzer’s compressor model is used, and the geometric parameters are achieved by the actual supercharger. The simulation model is validated with experimental data. It is shown that compressor surge is effectively predicted by this dynamic compressor model under various operating conditions.

  7. Dynamic Model of Centrifugal Compressor for Prediction of Surge Evolution and Performance Variations

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Mooncheong; Han, Jaeyoung; Yu, Sangseok [Chungnam National Univ., Daejeon (Korea, Republic of)

    2016-05-15

    When a control algorithm is developed to protect automotive compressor surges, the simulation model typically selects an empirically determined look-up table. However, it is difficult for a control oriented empirical model to show surge characteristics of the super charger. In this study, a dynamic supercharger model is developed to predict the performance of a centrifugal compressor under dynamic load follow-up. The model is developed using Simulink® environment, and is composed of a compressor, throttle body, valves, and chamber. Greitzer’s compressor model is used, and the geometric parameters are achieved by the actual supercharger. The simulation model is validated with experimental data. It is shown that compressor surge is effectively predicted by this dynamic compressor model under various operating conditions.

  8. Dynamic regulation of auxin oxidase and conjugating enzymes AtDAO1 and GH3 modulates auxin homeostasis.

    Science.gov (United States)

    Mellor, Nathan; Band, Leah R; Pěnčík, Aleš; Novák, Ondřej; Rashed, Afaf; Holman, Tara; Wilson, Michael H; Voß, Ute; Bishopp, Anthony; King, John R; Ljung, Karin; Bennett, Malcolm J; Owen, Markus R

    2016-09-27

    The hormone auxin is a key regulator of plant growth and development, and great progress has been made understanding auxin transport and signaling. Here, we show that auxin metabolism and homeostasis are also regulated in a complex manner. The principal auxin degradation pathways in Arabidopsis include oxidation by Arabidopsis thaliana gene DIOXYGENASE FOR AUXIN OXIDATION 1/2 (AtDAO1/2) and conjugation by Gretchen Hagen3s (GH3s). Metabolic profiling of dao1-1 root tissues revealed a 50% decrease in the oxidation product 2-oxoindole-3-acetic acid (oxIAA) and increases in the conjugated forms indole-3-acetic acid aspartic acid (IAA-Asp) and indole-3-acetic acid glutamic acid (IAA-Glu) of 438- and 240-fold, respectively, whereas auxin remains close to the WT. By fitting parameter values to a mathematical model of these metabolic pathways, we show that, in addition to reduced oxidation, both auxin biosynthesis and conjugation are increased in dao1-1 Transcripts of AtDAO1 and GH3 genes increase in response to auxin over different timescales and concentration ranges. Including this regulation of AtDAO1 and GH3 in an extended model reveals that auxin oxidation is more important for auxin homoeostasis at lower hormone concentrations, whereas auxin conjugation is most significant at high auxin levels. Finally, embedding our homeostasis model in a multicellular simulation to assess the spatial effect of the dao1-1 mutant shows that auxin increases in outer root tissues in agreement with the dao1-1 mutant root hair phenotype. We conclude that auxin homeostasis is dependent on AtDAO1, acting in concert with GH3, to maintain auxin at optimal levels for plant growth and development.

  9. MicroRNAs and Periodontal Homeostasis.

    Science.gov (United States)

    Luan, X; Zhou, X; Trombetta-eSilva, J; Francis, M; Gaharwar, A K; Atsawasuwan, P; Diekwisch, T G H

    2017-05-01

    MicroRNAs (miRNAs) are a group of small RNAs that control gene expression in all aspects of eukaryotic life, primarily through RNA silencing mechanisms. The purpose of the present review is to introduce key miRNAs involved in periodontal homeostasis, summarize the mechanisms by which they affect downstream genes and tissues, and provide an introduction into the therapeutic potential of periodontal miRNAs. In general, miRNAs function synergistically to fine-tune the regulation of biological processes and to remove expression noise rather than by causing drastic changes in expression levels. In the periodontium, miRNAs play key roles in development and periodontal homeostasis and during the loss of periodontal tissue integrity as a result of periodontal disease. As part of the anabolic phase of periodontal homeostasis and periodontal development, miRNAs direct periodontal fibroblasts toward alveolar bone lineage differentiation and new bone formation through WNT, bone morphogenetic protein, and Notch signaling pathways. miRNAs contribute equally to the catabolic aspect of periodontal homeostasis as they affect osteoclastogenesis and osteoclast function, either by directly promoting osteoclast activity or by inhibiting osteoclast signaling intermediaries or through negative feedback loops. Their small size and ability to target multiple regulatory networks of related sets of genes have predisposed miRNAs to become ideal candidates for drug delivery and tissue regeneration. To address the immense therapeutic potential of miRNAs and their antagomirs, an ever growing number of delivery approaches toward clinical applications have been developed, including nanoparticle carriers and secondary structure interference inhibitor systems. However, only a fraction of the miRNAs involved in periodontal health and disease are known today. It is anticipated that continued research will lead to a more comprehensive understanding of the periodontal miRNA world, and a systematic

  10. Development and Validation of the Homeostasis Concept Inventory

    Science.gov (United States)

    McFarland, Jenny L.; Price, Rebecca M.; Wenderoth, Mary Pat; Martinková, Patrícia; Cliff, William; Michael, Joel; Modell, Harold; Wright, Ann

    2017-01-01

    We present the Homeostasis Concept Inventory (HCI), a 20-item multiple-choice instrument that assesses how well undergraduates understand this critical physiological concept. We used an iterative process to develop a set of questions based on elements in the Homeostasis Concept Framework. This process involved faculty experts and undergraduate…

  11. TSH and Thyrotropic Agonists: Key Actors in Thyroid Homeostasis

    Directory of Open Access Journals (Sweden)

    Johannes W. Dietrich

    2012-01-01

    Full Text Available This paper provides the reader with an overview of our current knowledge of hypothalamic-pituitary-thyroid feedback from a cybernetic standpoint. Over the past decades we have gained a plethora of information from biochemical, clinical, and epidemiological investigation, especially on the role of TSH and other thyrotropic agonists as critical components of this complex relationship. Integrating these data into a systems perspective delivers new insights into static and dynamic behaviour of thyroid homeostasis. Explicit usage of this information with mathematical methods promises to deliver a better understanding of thyrotropic feedback control and new options for personalised diagnosis of thyroid dysfunction and targeted therapy, also by permitting a new perspective on the conundrum of the TSH reference range.

  12. A Conserved Splicing Silencer Dynamically Regulates O-GlcNAc Transferase Intron Retention and O-GlcNAc Homeostasis

    Directory of Open Access Journals (Sweden)

    Sung-Kyun Park

    2017-08-01

    Full Text Available Modification of nucleocytoplasmic proteins with O-GlcNAc regulates a wide variety of cellular processes and has been linked to human diseases. The enzymes O-GlcNAc transferase (OGT and O-GlcNAcase (OGA add and remove O-GlcNAc, but the mechanisms regulating their expression remain unclear. Here, we demonstrate that retention of the fourth intron of OGT is regulated in response to O-GlcNAc levels. We further define a conserved intronic splicing silencer (ISS that is necessary for OGT intron retention. Deletion of the ISS in colon cancer cells leads to increases in OGT, but O-GlcNAc homeostasis is maintained by concomitant increases in OGA protein. However, the ISS-deleted cells are hypersensitive to OGA inhibition in culture and in soft agar. Moreover, growth of xenograft tumors from ISS-deleted cells is compromised in mice treated with an OGA inhibitor. Thus, ISS-mediated regulation of OGT intron retention is a key component in OGT expression and maintaining O-GlcNAc homeostasis.

  13. Childhood cardiorespiratory fitness, muscular fitness and adult measures of glucose homeostasis.

    Science.gov (United States)

    Fraser, Brooklyn J; Blizzard, Leigh; Schmidt, Michael D; Juonala, Markus; Dwyer, Terence; Venn, Alison J; Magnussen, Costan G

    2018-02-14

    To assess whether childhood cardiorespiratory fitness (CRF) and muscular fitness phenotypes (strength, power, endurance) predict adult glucose homeostasis measures. Prospective longitudinal study. Study examining participants who had physical fitness measured in childhood (aged 7-15 years) and who attended follow-up clinics approximately 20 years later and provided a fasting blood sample which was tested for glucose and insulin. Physical fitness measurements included muscular strength (right and left grip, shoulder flexion, shoulder and leg extension), power (standing long jump distance) and endurance (number of push-ups in 30s), and CRF (1.6km run duration). In adulthood, fasting glucose and insulin levels were used to derive glucose homeostasis measures of insulin resistance (HOMA2-IR) and beta cell function (HOMA2-β). A standard deviation increase in childhood CRF or muscular strength (males) was associated with fasting glucose (CRF: β=-0.06mmol/L), fasting insulin (CRF: β=-0.73mU/L; strength: β=-0.40mU/L), HOMA2-IR (CRF: β=-0.06; strength: β=-0.05) and HOMA2-β (CRF: β=-3.06%; strength: β=-2.62%) in adulthood, independent of the alternative fitness phenotype (all p0.06). CRF and muscular fitness in childhood were inversely associated with measures of fasting insulin, insulin resistance and beta cell function in adulthood. Childhood CRF and muscular fitness could both be potential independent targets for strategies to help reduce the development of adverse glucose homeostasis. Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  14. Age-dependent transition from cell-level to population-level control in murine intestinal homeostasis revealed by coalescence analysis.

    Directory of Open Access Journals (Sweden)

    Zheng Hu

    Full Text Available In multi-cellular organisms, tissue homeostasis is maintained by an exquisite balance between stem cell proliferation and differentiation. This equilibrium can be achieved either at the single cell level (a.k.a. cell asymmetry, where stem cells follow strict asymmetric divisions, or the population level (a.k.a. population asymmetry, where gains and losses in individual stem cell lineages are randomly distributed, but the net effect is homeostasis. In the mature mouse intestinal crypt, previous evidence has revealed a pattern of population asymmetry through predominantly symmetric divisions of stem cells. In this work, using population genetic theory together with previously published crypt single-cell data obtained at different mouse life stages, we reveal a strikingly dynamic pattern of stem cell homeostatic control. We find that single-cell asymmetric divisions are gradually replaced by stochastic population-level asymmetry as the mouse matures to adulthood. This lifelong process has important developmental and evolutionary implications in understanding how adult tissues maintain their homeostasis integrating the trade-off between intrinsic and extrinsic regulations.

  15. Mathematical model reveals role of nucleotide signaling in airway surface liquid homeostasis and its dysregulation in cystic fibrosis.

    Science.gov (United States)

    Sandefur, Conner I; Boucher, Richard C; Elston, Timothy C

    2017-08-29

    Mucociliary clearance is composed of three components (i.e., mucin secretion, airway surface hydration, and ciliary-activity) which function coordinately to clear inhaled microbes and other foreign particles from airway surfaces. Airway surface hydration is maintained by water fluxes driven predominantly by active chloride and sodium ion transport. The ion channels that mediate electrogenic ion transport are regulated by extracellular purinergic signals that signal through G protein-coupled receptors. These purinoreceptors and the signaling pathways they activate have been identified as possible therapeutic targets for treating lung disease. A systems-level description of airway surface liquid (ASL) homeostasis could accelerate development of such therapies. Accordingly, we developed a mathematical model to describe the dynamic coupling of ion and water transport to extracellular purinergic signaling. We trained our model from steady-state and time-dependent experimental measurements made using normal and cystic fibrosis (CF) cultured human airway epithelium. To reproduce CF conditions, reduced chloride secretion, increased potassium secretion, and increased sodium absorption were required. The model accurately predicted ASL height under basal normal and CF conditions and the collapse of surface hydration due to the accelerated nucleotide metabolism associated with CF exacerbations. Finally, the model predicted a therapeutic strategy to deliver nucleotide receptor agonists to effectively rehydrate the ASL of CF airways.

  16. Predictive Modeling of Mechanical Properties of Welded Joints Based on Dynamic Fuzzy RBF Neural Network

    Directory of Open Access Journals (Sweden)

    ZHANG Yongzhi

    2016-10-01

    Full Text Available A dynamic fuzzy RBF neural network model was built to predict the mechanical properties of welded joints, and the purpose of the model was to overcome the shortcomings of static neural networks including structural identification, dynamic sample training and learning algorithm. The structure and parameters of the model are no longer head of default, dynamic adaptive adjustment in the training, suitable for dynamic sample data for learning, learning algorithm introduces hierarchical learning and fuzzy rule pruning strategy, to accelerate the training speed of model and make the model more compact. Simulation of the model was carried out by using three kinds of thickness and different process TC4 titanium alloy TIG welding test data. The results show that the model has higher prediction accuracy, which is suitable for predicting the mechanical properties of welded joints, and has opened up a new way for the on-line control of the welding process.

  17. Predicted Bacterial Interactions Affect in Vivo Microbial Colonization Dynamics in Nematostella

    Science.gov (United States)

    Domin, Hanna; Zurita-Gutiérrez, Yazmín H.; Scotti, Marco; Buttlar, Jann; Hentschel Humeida, Ute; Fraune, Sebastian

    2018-01-01

    The maintenance and resilience of host-associated microbiota during development is a fundamental process influencing the fitness of many organisms. Several host properties were identified as influencing factors on bacterial colonization, including the innate immune system, mucus composition, and diet. In contrast, the importance of bacteria–bacteria interactions on host colonization is less understood. Here, we use bacterial abundance data of the marine model organism Nematostella vectensis to reconstruct potential bacteria–bacteria interactions through co-occurrence networks. The analysis indicates that bacteria–bacteria interactions are dynamic during host colonization and change according to the host’s developmental stage. To assess the predictive power of inferred interactions, we tested bacterial isolates with predicted cooperative or competitive behavior for their ability to influence bacterial recolonization dynamics. Within 3 days of recolonization, all tested bacterial isolates affected bacterial community structure, while only competitive bacteria increased bacterial diversity. Only 1 week after recolonization, almost no differences in bacterial community structure could be observed between control and treatments. These results show that predicted competitive bacteria can influence community structure for a short period of time, verifying the in silico predictions. However, within 1 week, the effects of the bacterial isolates are neutralized, indicating a high degree of resilience of the bacterial community. PMID:29740401

  18. Predicted Bacterial Interactions Affect in Vivo Microbial Colonization Dynamics in Nematostella

    Directory of Open Access Journals (Sweden)

    Hanna Domin

    2018-04-01

    Full Text Available The maintenance and resilience of host-associated microbiota during development is a fundamental process influencing the fitness of many organisms. Several host properties were identified as influencing factors on bacterial colonization, including the innate immune system, mucus composition, and diet. In contrast, the importance of bacteria–bacteria interactions on host colonization is less understood. Here, we use bacterial abundance data of the marine model organism Nematostella vectensis to reconstruct potential bacteria–bacteria interactions through co-occurrence networks. The analysis indicates that bacteria–bacteria interactions are dynamic during host colonization and change according to the host’s developmental stage. To assess the predictive power of inferred interactions, we tested bacterial isolates with predicted cooperative or competitive behavior for their ability to influence bacterial recolonization dynamics. Within 3 days of recolonization, all tested bacterial isolates affected bacterial community structure, while only competitive bacteria increased bacterial diversity. Only 1 week after recolonization, almost no differences in bacterial community structure could be observed between control and treatments. These results show that predicted competitive bacteria can influence community structure for a short period of time, verifying the in silico predictions. However, within 1 week, the effects of the bacterial isolates are neutralized, indicating a high degree of resilience of the bacterial community.

  19. Temporal dynamics of stomatal conductance of plants under water deficit: can homeostasis be improved by more complex dynamics?

    Directory of Open Access Journals (Sweden)

    Gustavo Maia Souza

    2004-07-01

    Full Text Available In this study we hypothesized that chaotic or complex behavior of stomatal conductance could improve plant homeostasis after water deficit. Stomatal conductance of sunflower and sugar beet leaves was measured in plants grown either daily irrigation or under water deficit using an infrared gas analyzer. All measurements were performed under controlled environmental conditions. In order to measure a consistent time series, data were scored with time intervals of 20s during 6h. Lyapunov exponents, fractal dimensions, KS entropy and relative LZ complexity were calculated. Stomatal conductance in both irrigated and non-irrigated plants was chaotic-like. Plants under water deficit showed a trend to a more complex behaviour, mainly in sunflower that showed better homeostasis than in sugar beet. Some biological implications are discussed.Este estudo testou a hipótese de que a condutância estomática de uma população de estômatos em uma folha poderia apresentar um comportamento caótico ou complexo sob diferentes condições hídricas, o que poderia favorecer a capacidade homeostática das plantas. A condutância estomática em folhas de girassol e de beterraba cultivadas com irrigação diária e sob deficiência hídrica foi medida com um analisador de gás por infra-vermelho em condições controladas. Os dados foram registrados a cada 20s durante 6h. As séries temporais obtidas foram analisadas por meio dos coeficientes de Lyapunov, dimensão fractal, entropia KS e complexidade LZ relativa. A condutância estomática nas plantas cultivadas com e sem deficiência hídrica exibiu um comportamento provavelmente caótico. As plantas sob estresse hídrico mostraram uma tendência para um comportamento mais complexo, principalmente as plantas de girassol cuja capacidade homeostática foi superior. Algumas implicações biológicas destes comportamentos são discutidas no texto.

  20. A predictability study of Lorenz's 28-variable model as a dynamical system

    Science.gov (United States)

    Krishnamurthy, V.

    1993-01-01

    The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

  1. Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

    Science.gov (United States)

    Ma, Xiaoke; Sun, Penggang; Wang, Yu

    2018-04-01

    Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

  2. Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.

    Science.gov (United States)

    Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias

    2016-10-01

    The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Gut TFH and IgA: key players for regulation of bacterial communities and immune homeostasis.

    Science.gov (United States)

    Kato, Lucia M; Kawamoto, Shimpei; Maruya, Mikako; Fagarasan, Sidonia

    2014-01-01

    The main function of the immune system is to protect the host against pathogens. However, unlike the systemic immune system, the gut immune system does not eliminate, but instead nourishes complex bacterial communities and establishes advanced symbiotic relationships. Immunoglobulin A (IgA) is the most abundant antibody isotype in mammals, produced mainly in the gut. The primary function of IgA is to maintain homeostasis at mucosal surfaces, and studies in mice have demonstrated that IgA diversification has an essential role in the regulation of gut microbiota. Dynamic diversification and constant adaptation of IgA responses to local microbiota require expression of activation-induced cytidine deaminase by B cells and control from T follicular helper and Foxp3(+) T cells in germinal centers (GCs). We discuss the finely tuned regulatory mechanisms for IgA synthesis in GCs of Peyer's patches and emphasize the roles of CD4(+) T cells for IgA selection and the maintenance of appropriate gut microbial communities required for immune homeostasis.

  4. Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2016-01-01

    Full Text Available We investigate the problem of fuzzy constrained predictive optimal control of high speed train considering the effect of actuator dynamics. The dynamics feature of the high speed train is modeled as a cascade of cars connected by flexible couplers, and the formulation is mathematically transformed into a Takagi-Sugeno (T-S fuzzy model. The goal of this study is to design a state feedback control law at each decision step to enhance safety, comfort, and energy efficiency of high speed train subject to safety constraints on the control input. Based on Lyapunov stability theory, the problem of optimizing an upper bound on the cruise control cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities (LMIs. Furthermore, we analyze the influences of second-order actuator dynamics on the fuzzy constrained predictive controller, which shows risk of potentially deteriorating the overall system. Employing backstepping method, an actuator compensator is proposed to accommodate for the influence of the actuator dynamics. The experimental results show that with the proposed approach high speed train can track the desired speed, the relative coupler displacement between the neighbouring cars is stable at the equilibrium state, and the influence of actuator dynamics is reduced, which demonstrate the validity and effectiveness of the proposed approaches.

  5. Partial restoration of mutant enzyme homeostasis in three distinct lysosomal storage disease cell lines by altering calcium homeostasis.

    Directory of Open Access Journals (Sweden)

    Ting-Wei Mu

    2008-02-01

    Full Text Available A lysosomal storage disease (LSD results from deficient lysosomal enzyme activity, thus the substrate of the mutant enzyme accumulates in the lysosome, leading to pathology. In many but not all LSDs, the clinically most important mutations compromise the cellular folding of the enzyme, subjecting it to endoplasmic reticulum-associated degradation instead of proper folding and lysosomal trafficking. A small molecule that restores partial mutant enzyme folding, trafficking, and activity would be highly desirable, particularly if one molecule could ameliorate multiple distinct LSDs by virtue of its mechanism of action. Inhibition of L-type Ca2+ channels, using either diltiazem or verapamil-both US Food and Drug Administration-approved hypertension drugs-partially restores N370S and L444P glucocerebrosidase homeostasis in Gaucher patient-derived fibroblasts; the latter mutation is associated with refractory neuropathic disease. Diltiazem structure-activity studies suggest that it is its Ca2+ channel blocker activity that enhances the capacity of the endoplasmic reticulum to fold misfolding-prone proteins, likely by modest up-regulation of a subset of molecular chaperones, including BiP and Hsp40. Importantly, diltiazem and verapamil also partially restore mutant enzyme homeostasis in two other distinct LSDs involving enzymes essential for glycoprotein and heparan sulfate degradation, namely alpha-mannosidosis and type IIIA mucopolysaccharidosis, respectively. Manipulation of calcium homeostasis may represent a general strategy to restore protein homeostasis in multiple LSDs. However, further efforts are required to demonstrate clinical utility and safety.

  6. A Formal Explication of the Concept of Family Homeostasis.

    Science.gov (United States)

    Ariel, Shlomo; And Others

    1984-01-01

    Presents three articles discussing the concept of family homeostasis and the related concepts of family rules and family feedback. Includes a reply by Paul Dell citing the need for family therapy to go beyond homeostasis and further comments by Ariel, Carel, and Tyano. (JAC)

  7. Regulation of intestinal homeostasis and immunity with probiotic lactobacilli

    NARCIS (Netherlands)

    Baarlen, van P.; Wells, J.; Kleerebezem, M.

    2013-01-01

    The gut microbiota provide important stimuli to the human innate and adaptive immune system and co-mediate metabolic and immune homeostasis. Probiotic bacteria can be regarded as part of the natural human microbiota, and have been associated with improving homeostasis, albeit with different levels

  8. Thiol/disulfide homeostasis in pregnant women with obstructive sleep apnea syndrome.

    Science.gov (United States)

    Üstündağ, Yasemin; Demirci, Hakan; Balık, Rifat; Erel, Ozcan; Özaydın, Fahri; Kücük, Bilgen; Ertaş, Dilber; Ustunyurt, Emin

    2017-11-27

    Repetitive episodes of hypoxia and reoxygenation during sleep in patients with obstructive sleep apnea syndrome (OSAS) resemble an ischemia-reperfusion injury. We aimed to test the hypothesis that oxidative stress occurs in pregnant women with OSAS. We also aimed to compare thiol/disulfide homeostasis with ischemia-modified albumin (IMA) and total antioxidant capacity (TAC) as markers of ischemia-reperfusion injury in pregnant women with and without OSAS and healthy control. This study included 29 pregnant women with OSAS, 30 women without OSAS in the third trimester applying for periodic examinations, and 30 healthy women. Serum IMA and TAC (using the ferric reducing power of plasma method) were measured. Serum thiol/disulfide homeostasis was determined by a novel automated method. The mean age of the pregnant women with OSAS was 31.0 ± 4.7 years with a mean gestational age of 36.5 ± 3.0 weeks. The mean age of pregnant women without OSAS was 29.8 ± 4.9 years with a mean gestational age of 36.9 ± 2.7 weeks. The mean age of the nonpregnant control group was 29.7 ± 6.4 years. Both native thiol (291 ± 29 μmol/L versus 314 ± 30 μmol/L; p = .018) and total thiol (325 ± 32 versus 350 ± 32, p = .025) levels were lower in pregnant women with OSAS compared to pregnant women without OSAS, respectively (p total thiol levels were lower in pregnant women with OSAS compared to those without OSAS. However, dynamic thiol/disulfide homeostasis parameters cannot provide valuable information to discriminate OSAS in pregnant women.

  9. Persistent hepatitis virus infection and immune homeostasis

    OpenAIRE

    ZHOU Yun

    2014-01-01

    Homeostasis between the host and viruses is naturally maintained. On the one hand, the immune system activates the immune response to kill or eliminate viruses; on the other hand, the immune system controls the immune response to maintain immune homeostasis. The cause of persistent infections with hepatitis viruses such as HBV and HCV is that viral molecules damage the immune system of the host and their variants escape immune clearance. Long-term coexistence of the host and viruses is the pr...

  10. Neuroimmune regulation during intestinal development and homeostasis.

    Science.gov (United States)

    Veiga-Fernandes, Henrique; Pachnis, Vassilis

    2017-02-01

    Interactions between the nervous system and immune system are required for organ function and homeostasis. Evidence suggests that enteric neurons and intestinal immune cells share common regulatory mechanisms and can coordinate their responses to developmental challenges and environmental aggressions. These discoveries shed light on the physiology of system interactions and open novel perspectives for therapy designs that target underappreciated neurological-immunological commonalities. Here we highlight findings that address the importance of neuroimmune cell units (NICUs) in intestinal development, homeostasis and disease.

  11. Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

    International Nuclear Information System (INIS)

    Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

    2015-01-01

    Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

  12. Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

    Science.gov (United States)

    Kwasniok, Frank

    2013-11-01

    A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

  13. Hypothalamic carnitine metabolism integrates nutrient and hormonal feedback to regulate energy homeostasis.

    Science.gov (United States)

    Stark, Romana; Reichenbach, Alex; Andrews, Zane B

    2015-12-15

    The maintenance of energy homeostasis requires the hypothalamic integration of nutrient feedback cues, such as glucose, fatty acids, amino acids, and metabolic hormones such as insulin, leptin and ghrelin. Although hypothalamic neurons are critical to maintain energy homeostasis research efforts have focused on feedback mechanisms in isolation, such as glucose alone, fatty acids alone or single hormones. However this seems rather too simplistic considering the range of nutrient and endocrine changes associated with different metabolic states, such as starvation (negative energy balance) or diet-induced obesity (positive energy balance). In order to understand how neurons integrate multiple nutrient or hormonal signals, we need to identify and examine potential intracellular convergence points or common molecular targets that have the ability to sense glucose, fatty acids, amino acids and hormones. In this review, we focus on the role of carnitine metabolism in neurons regulating energy homeostasis. Hypothalamic carnitine metabolism represents a novel means for neurons to facilitate and control both nutrient and hormonal feedback. In terms of nutrient regulation, carnitine metabolism regulates hypothalamic fatty acid sensing through the actions of CPT1 and has an underappreciated role in glucose sensing since carnitine metabolism also buffers mitochondrial matrix levels of acetyl-CoA, an allosteric inhibitor of pyruvate dehydrogenase and hence glucose metabolism. Studies also show that hypothalamic CPT1 activity also controls hormonal feedback. We hypothesis that hypothalamic carnitine metabolism represents a key molecular target that can concurrently integrate nutrient and hormonal information, which is critical to maintain energy homeostasis. We also suggest this is relevant to broader neuroendocrine research as it predicts that hormonal signaling in the brain varies depending on current nutrient status. Indeed, the metabolic action of ghrelin, leptin or insulin

  14. Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

    Science.gov (United States)

    Hong, S-M; Jung, B-H; Ruan, D

    2011-03-21

    Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

  15. Pseudomonas aeruginosa Trent and zinc homeostasis.

    Science.gov (United States)

    Davies, Corey B; Harrison, Mark D; Huygens, Flavia

    2017-09-01

    Pseudomonas aeruginosa is a Gram-negative pathogen and the major cause of mortality in patients with cystic fibrosis. The mechanisms that P. aeruginosa strains use to regulate intracellular zinc have an effect on infection, antibiotic resistance and the propensity to form biofilms. However, zinc homeostasis in P. aeruginosa strains of variable infectivity has not been compared. In this study, zinc homeostasis in P. aeruginosa Trent, a highly infectious clinical strain, was compared to that of a laboratory P. aeruginosa strain, ATCC27853. Trent was able to tolerate higher concentrations of additional zinc in rich media than ATCC27853. Further, pre-adaptation to additional zinc enhanced the growth of Trent at non-inhibitory concentrations but the impact of pre-adaption on the growth of ATCC27853 under the same conditions was minimal. The results establish clear differences in zinc-induced responses in Trent and ATCC27853, and how zinc homeostasis can be a promising target for the development of novel antimicrobial strategies for P. aeruginosa infection in cystic fibrosis patients. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. An Emergency Georeferencing Framework for GF-4 Imagery Based on GCP Prediction and Dynamic RPC Refinement

    Directory of Open Access Journals (Sweden)

    Pengfei Li

    2017-10-01

    Full Text Available GaoFen-4 (GF-4 imagery has very potential in terms of emergency response due to its gazing mode. However, only poor geometric accuracy can be obtained using the rational polynomial coefficient (RPC parameters provided, making ground control points (GCPs necessary for emergency response. However, selecting GCPs is traditionally time-consuming, labor-intensive, and not fully reliable. This is mainly due to the facts that (1 manual GCP selection is time-consuming and cumbersome because of too many human interventions, especially for the first few GCPs; (2 typically, GF-4 gives planar array imagery acquired at rather large tilt angles, and the distortion introduces problems in image matching; (3 reference data will not always be available, especially under emergency circumstances. This paper provides a novel emergency georeferencing framework for GF-4 Level 1 imagery. The key feature is GCP prediction based on dynamic RPC refinement, which is able to predict even the first GCP and the prediction will be dynamically refined as the selection goes on. This is done by two techniques: (1 GCP prediction using RPC parameters and (2 dynamic RPC refinement using as few as only one GCP. Besides, online map services are also adopted to automatically provide reference data. Experimental results show that (1 GCP predictions improve using dynamic RPC refinement; (2 GCP selection becomes more efficient with GCP prediction; (3 the integration of online map services constitutes a good example for emergency response.

  17. Preface: Current perspectives in modelling, monitoring, and predicting geophysical fluid dynamics

    Science.gov (United States)

    Mancho, Ana M.; Hernández-García, Emilio; López, Cristóbal; Turiel, Antonio; Wiggins, Stephen; Pérez-Muñuzuri, Vicente

    2018-02-01

    The third edition of the international workshop Nonlinear Processes in Oceanic and Atmospheric Flows was held at the Institute of Mathematical Sciences (ICMAT) in Madrid from 6 to 8 July 2016. The event gathered oceanographers, atmospheric scientists, physicists, and applied mathematicians sharing a common interest in the nonlinear dynamics of geophysical fluid flows. The philosophy of this meeting was to bring together researchers from a variety of backgrounds into an environment that favoured a vigorous discussion of concepts across different disciplines. The present Special Issue on Current perspectives in modelling, monitoring, and predicting geophysical fluid dynamics contains selected contributions, mainly from attendants of the workshop, providing an updated perspective on modelling aspects of geophysical flows as well as issues on prediction and assimilation of observational data and novel tools for describing transport and mixing processes in these contexts. More details on these aspects are discussed in this preface.

  18. Predictive display design for the vehicles with time delay in dynamic response

    Science.gov (United States)

    Efremov, A. V.; Tiaglik, M. S.; Irgaleev, I. H.; Efremov, E. V.

    2018-02-01

    The two ways for the improvement of flying qualities are considered: the predictive display (PD) and the predictive display integrated with the flight control system (FCS). The both ways allow to transforming the controlled element dynamics in the crossover frequency range, to improve the accuracy of tracking and to suppress the effect of time delay in the vehicle response too. The technique for optimization of the predictive law is applied to the landing task. The results of the mathematical modeling and experimental investigations carried out for this task are considered in the paper.

  19. Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

    Science.gov (United States)

    Krylova, Olga; Earn, David J D

    2013-07-06

    The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

  20. Copper Homeostasis in Escherichia coli and Other Enterobacteriaceae.

    Science.gov (United States)

    Rensing, Christopher; Franke, Sylvia

    2007-04-01

    An interesting model for studying environmental influences shaping microbial evolution is provided by a multitude of copper resistance and copper homeostasis determinants in enteric bacteria. This review describes these determinants and tries to relate their presence to the habitat of the respective organism, as a current hypothesis predicts that the environment should determine an organism's genetic makeup. In Escherichia coli there are four regulons that are induced in the presence of copper. Two, the CueR and the CusR regulons, are described in detail. A central component regulating intracellular copper levels, present in all free-living enteric bacteria whose genomes have so far been sequenced, is a Cu(I)translocating P-type ATPase. The P-type ATPase superfamily is a ubiquitous group of proteins involved in the transport of charged substrates across biological membranes. Whereas some components involved in copper homeostasis can be found in both anaerobes and aerobes, multi-copper oxidases (MCOs) implicated in copper tolerance in E. coli, such as CueO and the plasmid-based PcoA, can be found only in aerobic organisms. Several features indicate that CueO, PcoA, and other related MCOs are specifically adapted to combat copper-mediated oxidative damage. In addition to these well-characterized resistance operons, there are numerous other genes that appear to be involved in copper binding and trafficking that have not been studied in great detail. SilE and its homologue PcoE, for example, are thought to effect the periplasmic binding and sequestration of silver and copper, respectively.

  1. Prediction of velocity and attitude of a yacht sailing upwind by computational fluid dynamics

    OpenAIRE

    Lee, Heebum; Park, Mi Yeon; Park, Sunho; Rhee, Shin Hyung

    2016-01-01

    One of the most important factors in sailing yacht design is accurate velocity prediction. Velocity prediction programs (VPP's) are widely used to predict velocity of sailing yachts. VPP's, which are primarily based on experimental data and experience of long years, however suffer limitations when applied in realistic conditions. Thus, in the present study, a high fidelity velocity prediction method using computational fluid dynamics (CFD) was proposed. Using the developed method, velocity an...

  2. Predictability of chaotic dynamics a finite-time Lyapunov exponents approach

    CERN Document Server

    Vallejo, Juan C

    2017-01-01

    This book is primarily concerned with the computational aspects of predictability of dynamical systems – in particular those where observation, modeling and computation are strongly interdependent. Unlike with physical systems under control in laboratories, for instance in celestial mechanics, one is confronted with the observation and modeling of systems without the possibility of altering the key parameters of the objects studied. Therefore, the numerical simulations offer an essential tool for analyzing these systems. With the widespread use of computer simulations to solve complex dynamical systems, the reliability of the numerical calculations is of ever-increasing interest and importance. This reliability is directly related to the regularity and instability properties of the modeled flow. In this interdisciplinary scenario, the underlying physics provide the simulated models, nonlinear dynamics provides their chaoticity and instability properties, and the computer sciences provide the actual numerica...

  3. Regulation of intestinal homeostasis and immunity with probiotic lactobacilli.

    Science.gov (United States)

    van Baarlen, Peter; Wells, Jerry M; Kleerebezem, Michiel

    2013-05-01

    The gut microbiota provide important stimuli to the human innate and adaptive immune system and co-mediate metabolic and immune homeostasis. Probiotic bacteria can be regarded as part of the natural human microbiota, and have been associated with improving homeostasis, albeit with different levels of success. Composition of microbiota, probiotic strain identity, and host genetic differences may account for differential modulation of immune responses by probiotics. Here, we review the mechanisms of immunomodulating capacities of specific probiotic strains, the responses they can induce in the host, and how microbiota and genetic differences between individuals may co-influence host responses and immune homeostasis. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Diminished stress resistance and defective adaptive homeostasis in age-related diseases.

    Science.gov (United States)

    Lomeli, Naomi; Bota, Daniela A; Davies, Kelvin J A

    2017-11-01

    Adaptive homeostasis is defined as the transient expansion or contraction of the homeostatic range following exposure to subtoxic, non-damaging, signaling molecules or events, or the removal or cessation of such molecules or events ( Mol. Aspects Med. (2016) 49, 1-7 ). Adaptive homeostasis allows us to transiently adapt (and then de-adapt) to fluctuating levels of internal and external stressors. The ability to cope with transient changes in internal and external environmental stress, however, diminishes with age. Declining adaptive homeostasis may make older people more susceptible to many diseases. Chronic oxidative stress and defective protein homeostasis (proteostasis) are two major factors associated with the etiology of age-related disorders. In the present paper, we review the contribution of impaired responses to oxidative stress and defective adaptive homeostasis in the development of age-associated diseases. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  5. Dynamic Universe Model Predicts the Trajectory of New Horizons Satellite Going to Pluto.......

    Science.gov (United States)

    Naga Parameswara Gupta, Satyavarapu

    2012-07-01

    New Horizons is NASA's artificial satellite now going towards to the dwarf planet Pluto. It has crossed Jupiter. It is expected to be the rst spacecraft to go near and study Pluto and its moons, Charon, Nix, and Hydra. These are the predictions for New Horizons (NH) space craft as on A.D. 2009-Aug-09 00:00:00.0000 hrs. The behavior of NH is similar to Pioneer Space craft as NH traveling is alike to Pioneer. NH is supposed to reach Pluto in 2015 AD. There was a gravity assist taken at Jupiter about a year back. As Dynamic universe model explains Pioneer anomaly and the higher gravitational attraction forces experienced towards SUN, It can explain NH also in a similar fashion. I am giving the predictions for NH by Dynamic Universe Model in the following Table 4. Here first two rows give Dynamic Universe Model predictions based on 02-01-2009 00:00 hrs data with Daily time step and hourly time step. Third row gives Ephemeris from Jet propulsion lab.Dynamic Universe Model can predict further to 9-Aug-2009. These Ephemeris data is from their web as on 28th June 2009 Any new data can be calculated..... For finding trajectories of Pioneer satellite (Anomaly), New Horizons satellite going to Pluto, the Calculations of Dynamic Universe model can be successfully applied. No dark matter is assumed within solar system radius. The effect on the masses around SUN shows as though there is extra gravitation pull toward SUN. It solves the Dynamics of Extra-solar planets like Planet X, satellite like Pioneer and NH for 3-Position, 3-velocity 3-acceleration for their masses,considering the complex situation of Multiple planets, Stars, Galaxy parts and Galaxy center and other Galaxies Using simple Newtonian Physics. It already solved problems Missing mass in Galaxies observed by galaxy circular velocity curves successfully. `SITA Simulations' software was developed about 18 years back for Dynamic Universe Model of Cosmology. It is based on Newtonian physics. It is Classical singularity

  6. Temporal anomaly detection: an artificial immune approach based on T cell activation, clonal size regulation and homeostasis.

    Science.gov (United States)

    Antunes, Mário J; Correia, Manuel E

    2010-01-01

    This paper presents an artificial immune system (AIS) based on Grossman's tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous. We conclude by discussing results obtained thus far with artificially generated data sets.

  7. Cellular Links between Neuronal Activity and Energy Homeostasis

    OpenAIRE

    Shetty, Pavan K.; Galeffi, Francesca; Turner, Dennis A.

    2012-01-01

    Neuronal activity, astrocytic responses to this activity, and energy homeostasis are linked together during baseline, conscious conditions, and short-term rapid activation (as occurs with sensory or motor function). Nervous system energy homeostasis also varies during long-term physiological conditions (i.e., development and aging) and with adaptation to pathological conditions, such as ischemia or low glucose. Neuronal activation requires increased metabolism (i.e., ATP generation) which lea...

  8. Predictive control and identification: Applications to steering dynamics

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela

    1996-01-01

    and of the loss function, which defines the optimality of the control. Some guidelines on how to choose the design parameters, depending on the type of process to be controlled and on the required control performance, are presented. A predictive track keeping system for a Mariner Class Vessel is formulated based...... the under- standing of the connection between identification and control, analysed in Chapter 7. Chapter 7 focuses on how to make the on-line identification for predictive control more robust towards unmodelled dynamics. The theory is verified via simulation studies on a Mariner Class Vessel. The effects...... and the need of a prefilter in the estimation are analysed and illustrated. Based on the idea that the control criterion must be dual to the estimation criterion, an iterative optimal prefilter is designed. This seems to be an appealing way to tune the model towards the objective for which the model...

  9. Telomere Homeostasis: Interplay with Magnesium

    Directory of Open Access Journals (Sweden)

    Donogh Maguire

    2018-01-01

    Full Text Available Telomere biology, a key component of the hallmarks of ageing, offers insight into dysregulation of normative ageing processes that accompany age-related diseases such as cancer. Telomere homeostasis is tightly linked to cellular metabolism, and in particular with mitochondrial physiology, which is also diminished during cellular senescence and normative physiological ageing. Inherent in the biochemistry of these processes is the role of magnesium, one of the main cellular ions and an essential cofactor in all reactions that use ATP. Magnesium plays an important role in many of the processes involved in regulating telomere structure, integrity and function. This review explores the mechanisms that maintain telomere structure and function, their influence on circadian rhythms and their impact on health and age-related disease. The pervasive role of magnesium in telomere homeostasis is also highlighted.

  10. Predictable Internal Brain Dynamics in EEG and Its Relation to Conscious States

    Directory of Open Access Journals (Sweden)

    Jaewook eYoo

    2014-06-01

    Full Text Available Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory, protention (anticipation, and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG data. Our results show that EEG signals from awake or rapid eye movement (REM sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS. Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

  11. Ageing and water homeostasis

    Science.gov (United States)

    Robertson, David; Jordan, Jens; Jacob, Giris; Ketch, Terry; Shannon, John R.; Biaggioni, Italo

    2002-01-01

    This review outlines current knowledge concerning fluid intake and volume homeostasis in ageing. The physiology of vasopressin is summarized. Studies have been carried out to determine orthostatic changes in plasma volume and to assess the effect of water ingestion in normal subjects, elderly subjects, and patients with dysautonomias. About 14% of plasma volume shifts out of the vasculature within 30 minutes of upright posture. Oral ingestion of water raises blood pressure in individuals with impaired autonomic reflexes and is an important source of noise in blood pressure trials in the elderly. On the average, oral ingestion of 16 ounces (473ml) of water raises blood pressure 11 mmHg in elderly normal subjects. In patients with autonomic impairment, such as multiple system atrophy, strikingly exaggerated pressor effects of water have been seen with blood pressure elevations greater than 75 mmHg not at all uncommon. Ingestion of water is a major determinant of blood pressure in the elderly population. Volume homeostasis is importantly affected by posture and large changes in plasma volume may occur within 30 minutes when upright posture is assumed.

  12. Amyloid and immune homeostasis.

    Science.gov (United States)

    Wang, Ying-Hui; Zhang, Yu-Gen

    2018-03-01

    Extracellular amyloid deposition defines a range of amyloidosis and amyloid-related disease. Addition to primary and secondary amyloidosis, amyloid-related disease can be observed in different tissue/organ that sharing the common pathogenesis based on the formation of amyloid deposition. Currently, both Alzheimer's disease and type 2 diabetes can be diagnosed with certainly only based on the autopsy results, by which amyloidosis of the associative tissue/organ is observed. Intriguingly, since it demonstrated that amyloid deposits trigger inflammatory reaction through the activation of cascaded immune response, wherein several lines of evidence implies a protective role of amyloid in preventing autoimmunity. Furthermore, attempts for preventing amyloid formation and/or removing amyloid deposits from the brain have caused meningoencephalitis and consequent deaths among the subjects. Hence, it is important to note that amyloid positively participates in maintaining immune homeostasis and contributes to irreversible inflammatory response. In this review, we will focus on the interactive relationship between amyloid and the immune system, discussing the potential functional roles of amyloid in immune tolerance and homeostasis. Copyright © 2017 Elsevier GmbH. All rights reserved.

  13. Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date in South Korea using Dynamical Downscaling

    Science.gov (United States)

    Ahn, J. B.; Hur, J.

    2015-12-01

    The seasonal prediction of both the surface air temperature and the first-flowering date (FFD) over South Korea are produced using dynamical downscaling (Hur and Ahn, 2015). Dynamical downscaling is performed using Weather Research and Forecast (WRF) v3.0 with the lateral forcing from hourly outputs of Pusan National University (PNU) coupled general circulation model (CGCM) v1.1. Gridded surface air temperature data with high spatial (3km) and temporal (daily) resolution are obtained using the physically-based dynamical models. To reduce systematic bias, simple statistical correction method is then applied to the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999-2008 by applying the corrected daily temperature predictions to the phenological thermal-time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) well represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predict the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. The approach used in the study may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically-based atmospheric dynamics, although the seasonal predictability of flowering phenology is not high enough. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953 and

  14. Homeostasis and function of regulatory T cells (Tregs) in vivo: lessons from TCR-transgenic Tregs

    Science.gov (United States)

    Attridge, Kesley; Walker, Lucy S K

    2014-01-01

    The identification of CD25 and subsequently Forkhead box protein 3 (Foxp3) as markers for regulatory T cells (Tregs) has revolutionized our ability to explore this population experimentally. In a similar vein, our understanding of antigen-specific Treg responses in vivo owes much to the fortuitous generation of T-cell receptor (TCR)-transgenic Tregs. This has permitted tracking of Tregs with a defined specificity in vivo, facilitating analysis of how encounter with cognate antigen shapes Treg homeostasis and function. Here, we review the key lessons learned from a decade of analysis of TCR-transgenic Tregs and set this in the broader context of general progress in the field. Use of TCR-transgenic Tregs has led to an appreciation that Tregs are a highly dynamic proliferative population in vivo, rather than an anergic population as they were initially portrayed. It is now clear that Treg homeostasis is positively regulated by encounter with self-antigen expressed on peripheral tissues, which is likely to be relevant to the phenomenon of peripheral repertoire reshaping that has been described for Tregs and the observation that the Treg TCR specificities vary by anatomical location. Substantial evidence has also accumulated to support the role of CD28 costimulation and interleukin-2 in Treg homeostasis. The availability of TCR-transgenic Tregs has enabled analysis of Treg populations that are sufficient or deficient in particular genes, without the comparison being confounded by repertoire alterations. This approach has yielded insights into genes required for Treg function in vivo, with particular progress being made on the role of ctla-4 in this context. As the prospect of manipulating Treg populations in the clinic becomes reality, a full appreciation of the rules governing their homeostasis will prove increasingly important. PMID:24712457

  15. Dynamic state estimation and prediction for real-time control and operation

    NARCIS (Netherlands)

    Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.

    2013-01-01

    Real-time control and operation are crucial to deal with increasing complexity of modern power systems. To effectively enable those functions, it is required a Dynamic State Estimation (DSE) function to provide accurate network state variables at the right moment and predict their trends ahead. This

  16. Dynamics and control of quadcopter using linear model predictive control approach

    Science.gov (United States)

    Islam, M.; Okasha, M.; Idres, M. M.

    2017-12-01

    This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

  17. An excitable cortex and memory model successfully predicts new pseudopod dynamics.

    Directory of Open Access Journals (Sweden)

    Robert M Cooper

    Full Text Available Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable--thus creating a memory of previous pseudopod locations--the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence.

  18. The Interplay between Feedback and Buffering in Cellular Homeostasis.

    Science.gov (United States)

    Hancock, Edward J; Ang, Jordan; Papachristodoulou, Antonis; Stan, Guy-Bart

    2017-11-22

    Buffering, the use of reservoirs of molecules to maintain concentrations of key molecular species, and negative feedback are the primary known mechanisms for robust homeostatic regulation. To our knowledge, however, the fundamental principles behind their combined effect have not been elucidated. Here, we study the interplay between buffering and negative feedback in the context of cellular homeostasis. We show that negative feedback counteracts slow-changing disturbances, whereas buffering counteracts fast-changing disturbances. Furthermore, feedback and buffering have limitations that create trade-offs for regulation: instability in the case of feedback and molecular noise in the case of buffering. However, because buffering stabilizes feedback and feedback attenuates noise from slower-acting buffering, their combined effect on homeostasis can be synergistic. These effects can be explained within a traditional control theory framework and are consistent with experimental observations of both ATP homeostasis and pH regulation in vivo. These principles are critical for studying robustness and homeostasis in biology and biotechnology. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

    KAUST Repository

    Panos, C.

    2010-09-01

    We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.

  20. Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

    KAUST Repository

    Panos, C.; Kouramas, K.I.; Georgiadis, M.C.; Pistikopoulos, E.N.

    2010-01-01

    We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.

  1. Forecast for Artificial Muscle Tremor Behavior Based on Dynamic Additional Grey Catastrophe Prediction

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    Yu Fu

    2018-02-01

    Full Text Available Recently, bio-inspired artificial muscles based on ionic polymers have shown a bright perspective in engineering and medical research, but the inherent tremor behavior can cause instability of output response. In this paper, dynamic additional grey catastrophe prediction (DAGCP is proposed to forecast the occurrence time of tremor behavior, providing adequate preparation time for the suppression of the chitosan-based artificial muscles. DAGCP constructs various dimensions of time subsequence models under different starting points based on the threshold of tremor occurrence times and peak-to-peak values in unit time. Next, the appropriate subsequence is selected according to grey correlation degree and prediction accuracy, then it is updated with the newly generated values to achieve a real-time forecast of forthcoming tremor time. Compared with conventional grey catastrophe prediction (GCP, the proposed method has the following advantages: (1 the degradation of prediction accuracy caused by the immobilization of original parameters is prevented; (2 the dynamic input, real-time update and gradual forecast of time sequence are incorporated into the model. The experiment results show that the novel DAGCP can predict forthcoming tremor time earlier and more accurately than the conventional GCP. The generation mechanism of tremor behavior is illustrated as well.

  2. Mechanism for maintaining homeostasis in the immune system of the intestine.

    Science.gov (United States)

    Taniguchi, Yoshie; Yoshioka, Noriko; Nakata, Kazue; Nishizawa, Takashi; Inagawa, Hiroyuki; Kohchi, Chie; Soma, Gen-Ichiro

    2009-11-01

    Every organism possesses a mechanism for maintaining homeostasis. We have focused on the immune system as a system that helps maintain homeostasis of the body, and particularly on the intestine as the largest organ of immunity in the body. We have also focused our research on the mechanism that responds to foreign substances in the intestine, especially the toll-like receptors (TLR). The activation of myeloid differentiation primary response gene 88 (MyD88) signal transduction as a response to TLR in the intestine is believed to contribute to the maintenance of homeostasis of the body through the homeostasis of the intestine. Furthermore, significant findings were reported in which signal transduction from TLR4 was essential for the maintenance and regulation of the intestine. These results strongly suggest the possibility that homeostasis in the intestine is maintained by TLR4, and signaling by TLR4 after exposure to lipopolysaccharide (LPS) probably has a role in regulating homeostasis. It is expected that the prevention and treatment of various diseases using TLR4 will continue to develop. As LPS is a substance that enhances the activity of TLR4, it will also attract attention as a valuable substance in its own right.

  3. Impact of intermittent fasting on glucose homeostasis.

    Science.gov (United States)

    Varady, Krista A

    2016-07-01

    This article provides an overview of the most recent human trials that have examined the impact of intermittent fasting on glucose homeostasis. Our literature search retrieved one human trial of alternate day fasting, and three trials of Ramadan fasting published in the past 12 months. Current evidence suggests that 8 weeks of alternate day fasting that produces mild weight loss (4% from baseline) has no effect on glucose homeostasis. As for Ramadan fasting, decreases in fasting glucose, insulin, and insulin resistance have been noted after 4 weeks in healthy normal weight individuals with mild weight loss (1-2% from baseline). However, Ramadan fasting may have little impact on glucoregulatory parameters in women with polycystic ovarian syndrome who failed to observe weight loss. Whether intermittent fasting is an effective means of regulating glucose homeostasis remains unclear because of the scarcity of studies in this area. Large-scale, longer-term randomized controlled trials will be required before the use of fasting can be recommended for the prevention and treatment of metabolic diseases.

  4. The role of the BH3-only protein Noxa in bone homeostasis.

    Science.gov (United States)

    Idrus, Erik; Nakashima, Tomoki; Wang, Ling; Hayashi, Mikihito; Okamoto, Kazuo; Kodama, Tatsuhiko; Tanaka, Nobuyuki; Taniguchi, Tadatsugu; Takayanagi, Hiroshi

    2011-07-08

    Bone homeostasis is maintained by a dynamic balance between bone resorption by osteoclasts and bone formation by osteoblasts. Since excessive osteoclast activity is implicated in pathological bone resorption, understanding the mechanism underlying osteoclast differentiation, function and survival is of both scientific and clinical importance. Osteoclasts are monocyte/macrophage lineage cells with a short life span that undergo rapid apoptosis, the rate of which critically determines the level of bone resorption in vivo. However, the molecular basis of rapid osteoclast apoptosis remains obscure. Here we report the role of a BH3-only protein, Noxa (encoded by the Pmaip1 gene), in bone homeostasis using Noxa-deficient mice. Among the Bcl-2 family members, Noxa was selectively induced during osteoclastogenesis. Mice lacking Noxa exhibit a severe osteoporotic phenotype due to an increased number of osteoclasts. Noxa deficiency did not have any effect on the number of osteoclast precursor cells or the expression of osteoclast-specific genes, but led to a prolonged survival of osteoclasts. Furthermore, adenovirus-mediated Noxa overexpression remarkably reduced bone loss in a model of inflammation-induced bone destruction. This study reveals Noxa to be a crucial regulator of osteoclast apoptosis, and may provide a molecular basis for a new therapeutic approach to bone diseases. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. Arginine Improves pH Homeostasis via Metabolism and Microbiome Modulation.

    Science.gov (United States)

    Agnello, M; Cen, L; Tran, N C; Shi, W; McLean, J S; He, X

    2017-07-01

    Dental caries can be described as a dysbiosis of the oral microbial community, in which acidogenic, aciduric, and acid-adapted bacterial species promote a pathogenic environment, leading to demineralization. Alkali generation by oral microbes, specifically via arginine catabolic pathways, is an essential factor in maintaining plaque pH homeostasis. There is evidence that the use of arginine in dentifrices helps protect against caries. The aim of the current study was to investigate the mechanistic and ecological effect of arginine treatment on the oral microbiome and its regulation of pH dynamics, using an in vitro multispecies oral biofilm model that was previously shown to be highly reflective of the in vivo oral microbiome. Pooled saliva from 6 healthy subjects was used to generate overnight biofilms, reflecting early stages of biofilm maturation. First, we investigated the uptake of arginine by the cells of the biofilm as well as the metabolites generated. We next explored the effect of arginine on pH dynamics by pretreating biofilms with 75 mM arginine, followed by the addition of sucrose (15 mM) after 0, 6, 20, or 48 h. pH was measured at each time point and biofilms were collected for 16S sequencing and targeted arginine quantification, and supernatants were prepared for metabolomic analysis. Treatment with only sucrose led to a sustained pH drop from 7 to 4.5, while biofilms treated with sucrose after 6, 20, or 48 h of preincubation with arginine exhibited a recovery to higher pH. Arginine was detected within the cells of the biofilms, indicating active uptake, and arginine catabolites citrulline, ornithine, and putrescine were detected in supernatants, indicating active metabolism. Sequencing analysis revealed a shift in the microbial community structure in arginine-treated biofilms as well as increased species diversity. Overall, we show that arginine improved pH homeostasis through a remodeling of the oral microbial community.

  6. Predicting Earth orientation changes from global forecasts of atmosphere-hydrosphere dynamics

    Science.gov (United States)

    Dobslaw, Henryk; Dill, Robert

    2018-02-01

    Effective Angular Momentum (EAM) functions obtained from global numerical simulations of atmosphere, ocean, and land surface dynamics are routinely processed by the Earth System Modelling group at Deutsches GeoForschungsZentrum. EAM functions are available since January 1976 with up to 3 h temporal resolution. Additionally, 6 days-long EAM forecasts are routinely published every day. Based on hindcast experiments with 305 individual predictions distributed over 15 months, we demonstrate that EAM forecasts improve the prediction accuracy of the Earth Orientation Parameters at all forecast horizons between 1 and 6 days. At day 6, prediction accuracy improves down to 1.76 mas for the terrestrial pole offset, and 2.6 mas for Δ UT1, which correspond to an accuracy increase of about 41% over predictions published in Bulletin A by the International Earth Rotation and Reference System Service.

  7. Dysregulated homeostasis of target tissues or autoantigens - A novel principle in autoimmunity.

    Science.gov (United States)

    Petersen, Frank; Yue, Xiaoyang; Riemekasten, Gabriela; Yu, Xinhua

    2017-06-01

    Monogenic autoimmune disorders provide a powerful tool for our understanding of the principles of autoimmunity due to the obvious impact of a single gene on the disease. So far, approximately 100 single gene defects causing murine monogenic autoimmune disorders have been reported and the functional characterization of these genes will provide significant progress in understanding the nature of autoimmunity. According to their function, genes leading to monogenic autoimmune disorders can be categorized into two groups. An expectable first group contains genes involved in the homeostasis of the immune system, including homeostasis of immune organs and immune cells. Intriguingly, the second group consists of genes functionally involved in the homeostasis of target tissues or autoantigens. According to our novel hypothesis, we propose that autoimmunity represents a consequence of a dysregulated homeostasis of the immune system and/or its targets including autoantigens and target tissues. In this review we refer to both aspects of homeostasis in autoimmunity with a highlight on the role of the homeostasis of target tissues and autoantigens. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Regulation of body fluid and salt homeostasis--from observations in space to new concepts on Earth.

    Science.gov (United States)

    Gerzer, R; Heer, M

    2005-08-01

    The present manuscript summarizes recent discoveries that were made by studying salt and fluid homeostasis in weightlessness. These data indicate that 1. atrial natriuretic peptide appears not to play an important role in natriuresis in physiology, 2. the distribution of body fluids appears to be tightly coupled with hunger and thirst regulation, 3. intrathoracic pressure may be an important co-regulator of body fluid homeostasis, 4. a so far unknown low-affinity, high capacity osmotically inactive sodium storage mechanism appears to be present in humans that is acting through sodium/hydrogen exchange on glycosaminoglycans and might explain the pathophysiology, e.g., of salt sensitive hypertension. The surprising and unexpected data underline that weightlessness is an excellent tool to investigate the physiology of our human body: If we knew it, we should be able to predict changes that occur when gravity is absent. But, as data from space demonstrate, we do not.

  9. THE WORLD VIEW, IDENTITY AND SOCIOCULTUR HOMEOSTASIS

    Directory of Open Access Journals (Sweden)

    Marina Yur’evna Neronova

    2016-02-01

    Full Text Available The paper presents the relationship between the phenomenon of world view and sociocultural identity both individuals and the community as a whole. The research is being carried out in the context of current crisis of world view accepted in so-called art Nouveau era. This paper also presents the identity crisis typical for modern civilized societies. A new notion of sociocultural homeostasis is introduced in connection with analyzable phenomena and their mutual relations.Purpose. Study of the relationship between the phenomenon of the world view and sociocultural identity as a structural and functional mechanism.Methodology. Phenomenological and systematic methods with the elements of historical method were employed. Cultural analysis is based on using both axiological and phenomenological approach, and also the elements of semiotic approach.Results. The dependence of identity on the world view is revealed (or is being revealed?, the phenomenon of sociocultural homeostasis is singled out (or is being singled out in the capacity of the mechanism setting up the correspondence in the contradictory unity between the world view as a subjective image and concrete reality as an objective part of this contradictory. The analysis of sociocultural homeostasis is carried out (or is being carried out and the conclusion is being drown that instability of the latter leads to serious problems in the identification of both individuals and communities as a whole. Besides, (moreover the relationship between the legitimacy level of the world view and stability of sociocultural homeostasis is established. (is being established.Practical implications: the system of education.

  10. Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

    Directory of Open Access Journals (Sweden)

    Jill X O'Reilly

    2013-09-01

    Full Text Available A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI we showed that activity in two brain systems (typically associated with reward learning and motor control could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

  11. Cooperative Multiagent System for Parking Availability Prediction Based on Time Varying Dynamic Markov Chains

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    Surafel Luleseged Tilahun

    2017-01-01

    Full Text Available Traffic congestion is one of the main issues in the study of transportation planning and management. It creates different problems including environmental pollution and health problem and incurs a cost which is increasing through years. One-third of this congestion is created by cars searching for parking places. Drivers may be aware that parking places are fully occupied but will drive around hoping that a parking place may become vacant. Opportunistic services, involving learning, predicting, and exploiting Internet of Things scenarios, are able to adapt to dynamic unforeseen situations and have the potential to ease parking search issues. Hence, in this paper, a cooperative dynamic prediction mechanism between multiple agents for parking space availability in the neighborhood, integrating foreseen and unforeseen events and adapting for long-term changes, is proposed. An agent in each parking place will use a dynamic and time varying Markov chain to predict the parking availability and these agents will communicate to produce the parking availability prediction in the whole neighborhood. Furthermore, a learning approach is proposed where the system can adapt to different changes in the parking demand including long-term changes. Simulation results, using synthesized data based on an actual parking lot data from a shopping mall in Geneva, show that the proposed model is promising based on the learning accuracy with service adaptation and performance in different cases.

  12. Oxidative stress homeostasis in grapevine (Vitis vinifera L.

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    Luisa C Carvalho

    2015-03-01

    Full Text Available Plants can maintain growth and reproductive success by sensing changes in the environment and reacting through mechanisms at molecular, cellular, physiological and developmental levels. Each stress condition prompts a unique response although some overlap between the reactions to abiotic stress (drought, heat, cold, salt or high light and to biotic stress (pathogens does occur. A common feature in the response to all stresses is the onset of oxidative stress, through the production of reactive oxygen species (ROS. As hydrogen peroxide and superoxide are involved in stress signaling, a tight control in ROS homeostasis requires a delicate balance of systems involved in their generation and degradation. If the plant lacks the capacity to generate scavenging potential, this can ultimately lead to death. In grapevine, antioxidant homeostasis can be considered at whole plant levels and during the development cycle. The most striking example lies in berries and their derivatives, such as wine, with nutraceutical properties associated with their antioxidant capacity. Antioxidant homeostasis is tightly regulated in leaves, assuring a positive balance between photosynthesis and respiration, explaining the tolerance of many grapevine varieties to extreme environments.In this review we will focus on antioxidant metabolites, antioxidant enzymes, transcriptional regulation and cross-talk with hormones prompted by abiotic stress conditions. We will also discuss three situations that require specific homeostasis balance: biotic stress, the oxidative burst in berries at veraison and in vitro systems. The genetic plasticity of the antioxidant homeostasis response put in evidence by the different levels of tolerance to stress presented by grapevine varieties will be addressed. The gathered information is relevant to foster varietal adaptation to impending climate changes, to assist breeders in choosing the more adapted varieties and to suitable viticulture

  13. Dynamic preload indicators fail to predict fluid responsiveness in open-chest conditions

    NARCIS (Netherlands)

    de Waal, Eric E. C.; Rex, Steffen; Kruitwagen, Cas L. J. J.; Kalkman, Cor J.; Buhre, Wolfgang F.

    Objective: Dynamic preload indicators like pulse pressure variation (PPV) and stroke volume variation (SVV) are increasingly being used for optimizing cardiac preload since they have been demonstrated to predict fluid responsiveness in a variety of perioperative settings. However, in open-chest

  14. FOREST ECOSYSTEM DYNAMICS ASSESSMENT AND PREDICTIVE MODELLING IN EASTERN HIMALAYA

    Directory of Open Access Journals (Sweden)

    S. P. S. Kushwaha

    2012-09-01

    Full Text Available This study focused on the forest ecosystem dynamics assessment and predictive modelling deforestation and forest cover prediction in a part of north-eastern India i.e. forest areas along West Bengal, Bhutan, Arunachal Pradesh and Assam border in Eastern Himalaya using temporal satellite imagery of 1975, 1990 and 2009 and predicted forest cover for the period 2028 using Cellular Automata Markov Modedel (CAMM. The exercise highlighted large-scale deforestation in the study area during 1975–1990 as well as 1990–2009 forest cover vectors. A net loss of 2,334.28 km2 forest cover was noticed between 1975 and 2009, and with current rate of deforestation, a forest area of 4,563.34 km2 will be lost by 2028. The annual rate of deforestation worked out to be 0.35 and 0.78% during 1975–1990 and 1990–2009 respectively. Bamboo forest increased by 24.98% between 1975 and 2009 due to opening up of the forests. Forests in Kokrajhar, Barpeta, Darrang, Sonitpur, and Dhemaji districts in Assam were noticed to be worst-affected while Lower Subansiri, West and East Siang, Dibang Valley, Lohit and Changlang in Arunachal Pradesh were severely affected. Among different forest types, the maximum loss was seen in case of sal forest (37.97% between 1975 and 2009 and is expected to deplete further to 60.39% by 2028. The tropical moist deciduous forest was the next category, which decreased from 5,208.11 km2 to 3,447.28 (33.81% during same period with further chances of depletion to 2,288.81 km2 (56.05% by 2028. It noted progressive loss of forests in the study area between 1975 and 2009 through 1990 and predicted that, unless checked, the area is in for further depletion of the invaluable climax forests in the region, especially sal and moist deciduous forests. The exercise demonstrated high potential of remote sensing and geographic information system for forest ecosystem dynamics assessment and the efficacy of CAMM to predict the forest cover change.

  15. Forest Ecosystem Dynamics Assessment and Predictive Modelling in Eastern Himalaya

    Science.gov (United States)

    Kushwaha, S. P. S.; Nandy, S.; Ahmad, M.; Agarwal, R.

    2011-09-01

    This study focused on the forest ecosystem dynamics assessment and predictive modelling deforestation and forest cover prediction in a part of north-eastern India i.e. forest areas along West Bengal, Bhutan, Arunachal Pradesh and Assam border in Eastern Himalaya using temporal satellite imagery of 1975, 1990 and 2009 and predicted forest cover for the period 2028 using Cellular Automata Markov Modedel (CAMM). The exercise highlighted large-scale deforestation in the study area during 1975-1990 as well as 1990-2009 forest cover vectors. A net loss of 2,334.28 km2 forest cover was noticed between 1975 and 2009, and with current rate of deforestation, a forest area of 4,563.34 km2 will be lost by 2028. The annual rate of deforestation worked out to be 0.35 and 0.78% during 1975-1990 and 1990-2009 respectively. Bamboo forest increased by 24.98% between 1975 and 2009 due to opening up of the forests. Forests in Kokrajhar, Barpeta, Darrang, Sonitpur, and Dhemaji districts in Assam were noticed to be worst-affected while Lower Subansiri, West and East Siang, Dibang Valley, Lohit and Changlang in Arunachal Pradesh were severely affected. Among different forest types, the maximum loss was seen in case of sal forest (37.97%) between 1975 and 2009 and is expected to deplete further to 60.39% by 2028. The tropical moist deciduous forest was the next category, which decreased from 5,208.11 km2 to 3,447.28 (33.81%) during same period with further chances of depletion to 2,288.81 km2 (56.05%) by 2028. It noted progressive loss of forests in the study area between 1975 and 2009 through 1990 and predicted that, unless checked, the area is in for further depletion of the invaluable climax forests in the region, especially sal and moist deciduous forests. The exercise demonstrated high potential of remote sensing and geographic information system for forest ecosystem dynamics assessment and the efficacy of CAMM to predict the forest cover change.

  16. Neutrophils in Homeostasis, Immunity, and Cancer.

    Science.gov (United States)

    Nicolás-Ávila, José Ángel; Adrover, José M; Hidalgo, Andrés

    2017-01-17

    Neutrophils were among the first leukocytes described and visualized by early immunologists. Prominent effector functions during infection and sterile inflammation classically placed them low in the immune tree as rapid, mindless aggressors with poor regulatory functions. This view is currently under reassessment as we uncover new aspects of their life cycle and identify transcriptional and phenotypic diversity that endows them with regulatory properties that extend beyond their lifetime in the circulation. These properties are revealing unanticipated roles for neutrophils in supporting homeostasis, as well as complex disease states such as cancer. We focus this review on these emerging functions in order to define the true roles of neutrophils in homeostasis, immunity, and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. microRNA Regulation of Peritoneal Cavity Homeostasis in Peritoneal Dialysis

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    Melisa Lopez-Anton

    2015-01-01

    Full Text Available Preservation of peritoneal cavity homeostasis and peritoneal membrane function is critical for long-term peritoneal dialysis (PD treatment. Several microRNAs (miRNAs have been implicated in the regulation of key molecular pathways driving peritoneal membrane alterations leading to PD failure. miRNAs regulate the expression of the majority of protein coding genes in the human genome, thereby affecting most biochemical pathways implicated in cellular homeostasis. In this review, we report published findings on miRNAs and PD therapy, with emphasis on evidence for changes in peritoneal miRNA expression during long-term PD treatment. Recent work indicates that PD effluent- (PDE- derived cells change their miRNA expression throughout the course of PD therapy, contributing to the loss of peritoneal cavity homeostasis and peritoneal membrane function. Changes in miRNA expression profiles will alter regulation of key molecular pathways, with the potential to cause profound effects on peritoneal cavity homeostasis during PD treatment. However, research to date has mainly adopted a literature-based miRNA-candidate methodology drawing conclusions from modest numbers of patient-derived samples. Therefore, the study of miRNA expression during PD therapy remains a promising field of research to understand the mechanisms involved in basic peritoneal cell homeostasis and PD failure.

  18. Sleep duration and sleep quality are associated differently with alterations of glucose homeostasis.

    Science.gov (United States)

    Byberg, S; Hansen, A-L S; Christensen, D L; Vistisen, D; Aadahl, M; Linneberg, A; Witte, D R

    2012-09-01

    Studies suggest that inadequate sleep duration and poor sleep quality increase the risk of impaired glucose regulation and diabetes. However, associations with specific markers of glucose homeostasis are less well explained. The objective of this study was to explore possible associations of sleep duration and sleep quality with markers of glucose homeostasis and glucose tolerance status in a healthy population-based study sample. The study comprised 771 participants from the Danish, population-based cross-sectional 'Health2008' study. Sleep duration and sleep quality were measured by self-report. Markers of glucose homeostasis were derived from a 3-point oral glucose tolerance test and included fasting plasma glucose, 2-h plasma glucose, HbA(1c), two measures of insulin sensitivity (the insulin sensitivity index(0,120) and homeostasis model assessment of insulin sensitivity), the homeostasis model assessment of β-cell function and glucose tolerance status. Associations of sleep duration and sleep quality with markers of glucose homeostasis and tolerance were analysed by multiple linear and logistic regression. A 1-h increment in sleep duration was associated with a 0.3 mmol/mol (0.3%) decrement in HbA(1c) and a 25% reduction in the risk of having impaired glucose regulation. Further, a 1-point increment in sleep quality was associated with a 2% increase in both the insulin sensitivity index(0,120) and homeostasis model assessment of insulin sensitivity, as well as a 1% decrease in homeostasis model assessment of β-cell function. In the present study, shorter sleep duration was mainly associated with later alterations in glucose homeostasis, whereas poorer sleep quality was mainly associated with earlier alterations in glucose homeostasis. Thus, adopting healthy sleep habits may benefit glucose metabolism in healthy populations. © 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK.

  19. Dynamic measures of RSA predict distress and regulation in toddlers.

    Science.gov (United States)

    Brooker, Rebecca J; Buss, Kristin A

    2010-05-01

    In this study, we examined a new method for quantifying individual variability using dynamic measures of respiratory sinus arrhythmia (RSA). This method incorporated temporal variation into the measurement of RSA and provided information beyond that offered by more traditional quantifications such as difference scores. Dynamic and static measures of change in RSA were tested in relation to displays of emotion and affective behaviors during a fear-eliciting episode in a sample of 88 typically developing and high-fear toddlers during a laboratory visit at age 24 months. Dynamic measures of RSA contributed information that was unique from traditionally employed, static change scores in predicting high-fear toddlers' displays of shyness during a fear-eliciting episode. In contrast, RSA change scores offered information related to boldness in nonhigh-fear children. In addition, several associations included estimates of nonlinear change in RSA. Implications for the study of individual differences in RSA and relations with emotion and emotion regulation are discussed.

  20. Predicting physical time series using dynamic ridge polynomial neural networks.

    Directory of Open Access Journals (Sweden)

    Dhiya Al-Jumeily

    Full Text Available Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

  1. Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

    Science.gov (United States)

    Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

    2018-01-01

    When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley

  2. Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model.

    Science.gov (United States)

    Hardiansyah, Deni; Attarwala, Ali Asgar; Kletting, Peter; Mottaghy, Felix M; Glatting, Gerhard

    2017-10-01

    To investigate the accuracy of predicted time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using simulated dynamic PET data and a physiologically based pharmacokinetic (PBPK) model. PBPK parameters were estimated using biokinetic data of 15 patients after injection of (152±15)MBq of 111 In-DTPAOC (total peptide amount (5.78±0.25)nmol). True mathematical phantoms of patients (MPPs) were the PBPK model with the estimated parameters. Dynamic PET measurements were simulated as being done after bolus injection of 150MBq 68 Ga-DOTATATE using the true MPPs. Dynamic PET scans around 35min p.i. (P 1 ), 4h p.i. (P 2 ) and the combination of P 1 and P 2 (P 3 ) were simulated. Each measurement was simulated with four frames of 5min each and 2 bed positions. PBPK parameters were fitted to the PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 5.1GBq of 90 Y-DOTATATE over 30min in both true and PET-predicted MPPs. TIACs of simulated therapy were calculated, true MPPs (true TIACs) and predicted MPPs (predicted TIACs) followed by the calculation of variabilities v. For P 1 and P 2 the population variabilities of kidneys, liver and spleen were acceptable (v10%). Treatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  3. Breast Milk Hormones and Regulation of Glucose Homeostasis

    Directory of Open Access Journals (Sweden)

    Francesco Savino

    2011-01-01

    Full Text Available Growing evidence suggests that a complex relationship exists between the central nervous system and peripheral organs involved in energy homeostasis. It consists in the balance between food intake and energy expenditure and includes the regulation of nutrient levels in storage organs, as well as in blood, in particular blood glucose. Therefore, food intake, energy expenditure, and glucose homeostasis are strictly connected to each other. Several hormones, such as leptin, adiponectin, resistin, and ghrelin, are involved in this complex regulation. These hormones play a role in the regulation of glucose metabolism and are involved in the development of obesity, diabetes, and metabolic syndrome. Recently, their presence in breast milk has been detected, suggesting that they may be involved in the regulation of growth in early infancy and could influence the programming of energy balance later in life. This paper focuses on hormones present in breast milk and their role in glucose homeostasis.

  4. MicroRNAs at the epicenter of intestinal homeostasis.

    Science.gov (United States)

    Belcheva, Antoaneta

    2017-03-01

    Maintaining intestinal homeostasis is a key prerequisite for a healthy gut. Recent evidence points out that microRNAs (miRNAs) act at the epicenter of the signaling networks regulating this process. The fine balance in the interaction between gut microbiota, intestinal epithelial cells, and the host immune system is achieved by constant transmission of signals and their precise regulation. Gut microbes extensively communicate with the host immune system and modulate host gene expression. On the other hand, sensing of gut microbiota by the immune cells provides appropriate tolerant responses that facilitate the symbiotic relationships. While the role of many regulatory proteins, receptors and their signaling pathways in the regulation of the intestinal homeostasis is well documented, the involvement of non-coding RNA molecules in this process has just emerged. This review discusses the most recent knowledge about the contribution of miRNAs in the regulation of the intestinal homeostasis. © 2017 WILEY Periodicals, Inc.

  5. PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Aboul-Magd Mohammed O

    2009-07-01

    Full Text Available Abstract Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures from primary sequence data which makes use of Parallel Cascade Identification (PCI, a powerful technique from the field of nonlinear system identification. Results Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at http://bioinf.sce.carleton.ca/PCISS. In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input

  6. Regulation of energy homeostasis via GPR120

    Directory of Open Access Journals (Sweden)

    Atsuhiko eIchimura

    2014-07-01

    Full Text Available Free fatty acids (FFAs are fundamental units of key nutrients. FFAs exert various biological functions, depending on the chain length and degree of desaturation. Recent studies have shown that several FFAs act as ligands of G-protein-coupled receptors (GPCRs, activate intracellular signaling and exert physiological functions via these GPCRs. GPR120 (also known as free fatty acid receptor 4, FFAR4 is activated by unsaturated medium- to long-chain FFAs and has a critical role in various physiological homeostasis mechanisms such as incretin hormone secretion, food preference, anti-inflammation and adipogenesis. Recent studies showed that a lipid sensor GPR120 has a key role in sensing dietary fat in white adipose tissue and regulates the whole body energy homeostasis in both humans and rodents. Genetic study in human identified the loss-of-functional mutation of GPR120 associated with obesity and insulin resistance. In addition, dysfunction of GPR120 has been linked as a novel risk factor for diet-induced obesity. This review aims to provide evidence from the recent development in physiological function of GPR120 and discusses its functional roles in regulation of energy homeostasis and its potential as drug targets.

  7. A novel method for prediction of dynamic smiling expressions after orthodontic treatment: a case report.

    Science.gov (United States)

    Dai, Fanfan; Li, Yangjing; Chen, Gui; Chen, Si; Xu, Tianmin

    2016-02-01

    Smile esthetics has become increasingly important for orthodontic patients, thus prediction of post-treatment smile is necessary for a perfect treatment plan. In this study, with a combination of three-dimensional craniofacial data from the cone beam computed tomography and color-encoded structured light system, a novel method for smile prediction was proposed based on facial expression transfer, in which dynamic facial expression was interpreted as a matrix of facial depth changes. Data extracted from the pre-treatment smile expression record were applied to the post-treatment static model to realize expression transfer. Therefore smile esthetics of the patient after treatment could be evaluated in pre-treatment planning procedure. The positive and negative mean values of error for prediction accuracy were 0.9 and - 1.1 mm respectively, with the standard deviation of ± 1.5 mm, which is clinically acceptable. Further studies would be conducted to reduce the prediction error from both the static and dynamic sides as well as to explore automatically combined prediction from the two sides.

  8. The role of CDX2 in intestinal homeostasis and inflammation

    DEFF Research Database (Denmark)

    Coskun, Mehmet; Troelsen, Jesper Thorvald; Nielsen, Ole Haagen

    2011-01-01

    a causal role in a large number of diseases and developmental disorders. Inflammatory bowel disease (IBD) is characterized by a chronically inflamed mucosa caused by dysregulation of the intestinal immune homeostasis. The aetiology of IBD is thought to be a combination of genetic and environmental factors......, including luminal bacteria. The Caudal-related homeobox transcription factor 2 (CDX2) is critical in early intestinal differentiation and has been implicated as a master regulator of the intestinal homeostasis and permeability in adults. When expressed, CDX2 modulates a diverse set of processes including...... of the intestinal homeostasis and further to reveal its potential role in inflammation....

  9. Degradation Prediction Model Based on a Neural Network with Dynamic Windows

    Science.gov (United States)

    Zhang, Xinghui; Xiao, Lei; Kang, Jianshe

    2015-01-01

    Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but for some high reliability components, it is very difficult to collect run-to-failure condition monitoring data, i.e., from normal to failure. Only a certain number of condition indicators in certain period can be used to estimate RUL. In addition, some existing prediction methods have problems which block RUL estimation due to poor extrapolability. The predicted value converges to a certain constant or fluctuates in certain range. Moreover, the fluctuant condition features also have bad effects on prediction. In order to solve these dilemmas, this paper proposes a RUL prediction model based on neural network with dynamic windows. This model mainly consists of three steps: window size determination by increasing rate, change point detection and rolling prediction. The proposed method has two dominant strengths. One is that the proposed approach does not need to assume the degradation trajectory is subject to a certain distribution. The other is it can adapt to variation of degradation indicators which greatly benefits RUL prediction. Finally, the performance of the proposed RUL prediction model is validated by real field data and simulation data. PMID:25806873

  10. Neuronal and molecular mechanisms of sleep homeostasis.

    Science.gov (United States)

    Donlea, Jeffrey M

    2017-12-01

    Sleep is necessary for survival, and prolonged waking causes a homeostatic increase in the need for recovery sleep. Homeostasis is a core component of sleep regulation and has been tightly conserved across evolution from invertebrates to man. Homeostatic sleep regulation was first identified among insects in cockroaches several decades ago, but the characterization of sleep rebound in Drosophila melanogaster opened the use of insect model species to understand homeostatic functions and regulation of sleep. This review describes circuits in two neuropil structures, the central complex and mushroom bodies, that influence sleep homeostasis and neuromodulatory systems that influence the accrual of homeostatic sleep need. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Affective Value in the Predictive Mind

    OpenAIRE

    Van de Cruys, Sander

    2017-01-01

    Although affective value is fundamental in explanations of behavior, it is still a somewhat alien concept in cognitive science. It implies a normativity or directionality that mere information processing models cannot seem to provide. In this paper we trace how affective value can emerge from information processing in the brain, as described by predictive processing. We explain the grounding of predictive processing in homeostasis, and articulate the implications this has for the concept of r...

  12. Protein-DNA binding dynamics predict transcriptional response to nutrients in archaea.

    Science.gov (United States)

    Todor, Horia; Sharma, Kriti; Pittman, Adrianne M C; Schmid, Amy K

    2013-10-01

    Organisms across all three domains of life use gene regulatory networks (GRNs) to integrate varied stimuli into coherent transcriptional responses to environmental pressures. However, inferring GRN topology and regulatory causality remains a central challenge in systems biology. Previous work characterized TrmB as a global metabolic transcription factor in archaeal extremophiles. However, it remains unclear how TrmB dynamically regulates its ∼100 metabolic enzyme-coding gene targets. Using a dynamic perturbation approach, we elucidate the topology of the TrmB metabolic GRN in the model archaeon Halobacterium salinarum. Clustering of dynamic gene expression patterns reveals that TrmB functions alone to regulate central metabolic enzyme-coding genes but cooperates with various regulators to control peripheral metabolic pathways. Using a dynamical model, we predict gene expression patterns for some TrmB-dependent promoters and infer secondary regulators for others. Our data suggest feed-forward gene regulatory topology for cobalamin biosynthesis. In contrast, purine biosynthesis appears to require TrmB-independent regulators. We conclude that TrmB is an important component for mediating metabolic modularity, integrating nutrient status and regulating gene expression dynamics alone and in concert with secondary regulators.

  13. Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

    Science.gov (United States)

    Darmon, David

    2018-03-01

    In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

  14. Prediction of velocity and attitude of a yacht sailing upwind by computational fluid dynamics

    Directory of Open Access Journals (Sweden)

    Heebum Lee

    2016-01-01

    Full Text Available One of the most important factors in sailing yacht design is accurate velocity prediction. Velocity prediction programs (VPP's are widely used to predict velocity of sailing yachts. VPP's, which are primarily based on experimental data and experience of long years, however suffer limitations when applied in realistic conditions. Thus, in the present study, a high fidelity velocity prediction method using computational fluid dynamics (CFD was proposed. Using the developed method, velocity and attitude of a 30 feet sloop yacht, which was developed by Korea Research Institute of Ship and Ocean (KRISO and termed KORDY30, were predicted in upwind sailing condition.

  15. Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics.

    Science.gov (United States)

    Zhang, Liping; Wang, Li; Zheng, Yanling; Wang, Kai; Zhang, Xueliang; Zheng, Yujian

    2017-03-04

    Echinococcosis, which can seriously harm human health and animal husbandry production, has become an endemic in the Xinjiang Uygur Autonomous Region of China. In order to explore an effective human Echinococcosis forecasting model in Xinjiang, three grey models, namely, the traditional grey GM(1,1) model, the Grey-Periodic Extensional Combinatorial Model (PECGM(1,1)), and the Modified Grey Model using Fourier Series (FGM(1,1)), in addition to a multiplicative seasonal ARIMA(1,0,1)(1,1,0)₄ model, are applied in this study for short-term predictions. The accuracy of the different grey models is also investigated. The simulation results show that the FGM(1,1) model has a higher performance ability, not only for model fitting, but also for forecasting. Furthermore, considering the stability and the modeling precision in the long run, a dynamic epidemic prediction model based on the transmission mechanism of Echinococcosis is also established for long-term predictions. Results demonstrate that the dynamic epidemic prediction model is capable of identifying the future tendency. The number of human Echinococcosis cases will increase steadily over the next 25 years, reaching a peak of about 1250 cases, before eventually witnessing a slow decline, until it finally ends.

  16. Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics

    Directory of Open Access Journals (Sweden)

    Liping Zhang

    2017-03-01

    Full Text Available Echinococcosis, which can seriously harm human health and animal husbandry production, has become an endemic in the Xinjiang Uygur Autonomous Region of China. In order to explore an effective human Echinococcosis forecasting model in Xinjiang, three grey models, namely, the traditional grey GM(1,1 model, the Grey-Periodic Extensional Combinatorial Model (PECGM(1,1, and the Modified Grey Model using Fourier Series (FGM(1,1, in addition to a multiplicative seasonal ARIMA(1,0,1(1,1,04 model, are applied in this study for short-term predictions. The accuracy of the different grey models is also investigated. The simulation results show that the FGM(1,1 model has a higher performance ability, not only for model fitting, but also for forecasting. Furthermore, considering the stability and the modeling precision in the long run, a dynamic epidemic prediction model based on the transmission mechanism of Echinococcosis is also established for long-term predictions. Results demonstrate that the dynamic epidemic prediction model is capable of identifying the future tendency. The number of human Echinococcosis cases will increase steadily over the next 25 years, reaching a peak of about 1250 cases, before eventually witnessing a slow decline, until it finally ends.

  17. Role of Mitochondrial Dynamics in Neuronal Development: Mechanism for Wolfram Syndrome.

    Science.gov (United States)

    Cagalinec, Michal; Liiv, Mailis; Hodurova, Zuzana; Hickey, Miriam Ann; Vaarmann, Annika; Mandel, Merle; Zeb, Akbar; Choubey, Vinay; Kuum, Malle; Safiulina, Dzhamilja; Vasar, Eero; Veksler, Vladimir; Kaasik, Allen

    2016-07-01

    Deficiency of the protein Wolfram syndrome 1 (WFS1) is associated with multiple neurological and psychiatric abnormalities similar to those observed in pathologies showing alterations in mitochondrial dynamics. The aim of this study was to examine the hypothesis that WFS1 deficiency affects neuronal function via mitochondrial abnormalities. We show that down-regulation of WFS1 in neurons leads to dramatic changes in mitochondrial dynamics (inhibited mitochondrial fusion, altered mitochondrial trafficking, and augmented mitophagy), delaying neuronal development. WFS1 deficiency induces endoplasmic reticulum (ER) stress, leading to inositol 1,4,5-trisphosphate receptor (IP3R) dysfunction and disturbed cytosolic Ca2+ homeostasis, which, in turn, alters mitochondrial dynamics. Importantly, ER stress, impaired Ca2+ homeostasis, altered mitochondrial dynamics, and delayed neuronal development are causatively related events because interventions at all these levels improved the downstream processes. Our data shed light on the mechanisms of neuronal abnormalities in Wolfram syndrome and point out potential therapeutic targets. This work may have broader implications for understanding the role of mitochondrial dynamics in neuropsychiatric diseases.

  18. Role of Mitochondrial Dynamics in Neuronal Development: Mechanism for Wolfram Syndrome.

    Directory of Open Access Journals (Sweden)

    Michal Cagalinec

    2016-07-01

    Full Text Available Deficiency of the protein Wolfram syndrome 1 (WFS1 is associated with multiple neurological and psychiatric abnormalities similar to those observed in pathologies showing alterations in mitochondrial dynamics. The aim of this study was to examine the hypothesis that WFS1 deficiency affects neuronal function via mitochondrial abnormalities. We show that down-regulation of WFS1 in neurons leads to dramatic changes in mitochondrial dynamics (inhibited mitochondrial fusion, altered mitochondrial trafficking, and augmented mitophagy, delaying neuronal development. WFS1 deficiency induces endoplasmic reticulum (ER stress, leading to inositol 1,4,5-trisphosphate receptor (IP3R dysfunction and disturbed cytosolic Ca2+ homeostasis, which, in turn, alters mitochondrial dynamics. Importantly, ER stress, impaired Ca2+ homeostasis, altered mitochondrial dynamics, and delayed neuronal development are causatively related events because interventions at all these levels improved the downstream processes. Our data shed light on the mechanisms of neuronal abnormalities in Wolfram syndrome and point out potential therapeutic targets. This work may have broader implications for understanding the role of mitochondrial dynamics in neuropsychiatric diseases.

  19. Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks

    Institute of Scientific and Technical Information of China (English)

    LI Meng; ZHANG Lin; XIAO Yong-kang; SHAN Xiu-ming

    2004-01-01

    Energy and bandwidth are the scarce resources in ad hoc networks because most of the mobile nodes are battery-supplied and share the exclusive wireless medium. Integrating the power control into MAC protocol is a promising technique to fully exploit these precious resources of ad hoc wireless networks. In this paper, a new intelligent power-controlled Medium Access Control (MAC) (iMAC) protocol with dynamic neighbor prediction is proposed. Through the elaborate design of the distributed transmit-receive strategy of mobile nodes, iMAC greatly outperforms the prevailing IEEE 802.11 MAC protocols in not only energy conservation but also network throughput. Using the Dynamic Neighbor Prediction (DNP), iMAC performs well in mobile scenes. To the best of our knowledge, iMAC is the first protocol that considers the performance deterioration of power-controlled MAC protocols in mobile scenes and then proposes a solution. Simulation results indicate that DNP is important and necessary for power-controlled MAC protocols in mobile ad hoc networks.

  20. Upper intestinal lipids regulate energy and glucose homeostasis.

    Science.gov (United States)

    Cheung, Grace W C; Kokorovic, Andrea; Lam, Tony K T

    2009-09-01

    Upon the entry of nutrients into the small intestine, nutrient sensing mechanisms are activated to allow the body to adapt appropriately to the incoming nutrients. To date, mounting evidence points to the existence of an upper intestinal lipid-induced gut-brain neuronal axis to regulate energy homeostasis. Moreover, a recent discovery has also revealed an upper intestinal lipid-induced gut-brain-liver neuronal axis involved in the regulation of glucose homeostasis. In this mini-review, we will focus on the mechanisms underlying the activation of these respective neuronal axes by upper intestinal lipids.

  1. Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

    Science.gov (United States)

    Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

    2015-03-01

    Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.

  2. Neurodegeneration in ataxia-telangiectasia: Multiple roles of ATM kinase in cellular homeostasis.

    Science.gov (United States)

    Choy, Kay Rui; Watters, Dianne J

    2018-01-01

    Ataxia-telangiectasia (A-T) is characterized by neuronal degeneration, cancer, diabetes, immune deficiency, and increased sensitivity to ionizing radiation. A-T is attributed to the deficiency of the protein kinase coded by the ATM (ataxia-telangiectasia mutated) gene. ATM is a sensor of DNA double-strand breaks (DSBs) and signals to cell cycle checkpoints and the DNA repair machinery. ATM phosphorylates numerous substrates and activates many cell-signaling pathways. There has been considerable debate about whether a defective DNA damage response is causative of the neurological aspects of the disease. In proliferating cells, ATM is localized mainly in the nucleus; however, in postmitotic cells such as neurons, ATM is mostly cytoplasmic. Recent studies reveal an increasing number of roles for ATM in the cytoplasm, including activation by oxidative stress. ATM associates with organelles including mitochondria and peroxisomes, both sources of reactive oxygen species (ROS), which have been implicated in neurodegenerative diseases and aging. ATM is also associated with synaptic vesicles and has a role in regulating cellular homeostasis and autophagy. The cytoplasmic roles of ATM provide a new perspective on the neurodegenerative process in A-T. This review will examine the expanding roles of ATM in cellular homeostasis and relate these functions to the complex A-T phenotype. Developmental Dynamics 247:33-46, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  3. Predictive coding of dynamical variables in balanced spiking networks.

    Science.gov (United States)

    Boerlin, Martin; Machens, Christian K; Denève, Sophie

    2013-01-01

    Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

  4. Guest editor's introduction: Energy homeostasis in context.

    Science.gov (United States)

    Schneider, Jill E

    2014-06-01

    This article is part of a Special Issue "Energy Balance". Energy homeostasis is achieved through neuroendocrine and metabolic control of energy intake, storage, and expenditure. Traditionally, these controls have been studied in an unrealistic and narrow context. The appetite for food, for example, is most often assumed to be independent of other motivations, such as sexual desire, fearfulness, and competition. Furthermore, our understanding of all aspects of energy homeostasis is based on studying males of only a few species. The baseline control subjects are most often housed in enclosed spaces, with continuous, unlimited access to food. In the last century, this approach has generated useful information, but all the while, the global prevalence of obesity has increased and remains at unprecedented levels (Ogden et al., 2013, 2014). It is likely, however, that the mechanisms that control ingestive behavior were molded by evolutionary forces, and that few, if any vertebrate species evolved in the presence of a limitless food supply, in an enclosed 0.5 × 1 ft space, and exposed to a constant ambient temperature of 22+2 °C. This special issue of Hormones and Behavior therefore contains 9 review articles and 7 data articles that consider energy homeostasis within the context of other motivations and physiological processes, such as early development, sexual differentiation, sexual motivation, reproduction, seasonality, hibernation, and migration. Each article is focused on a different species or on a set of species, and most vertebrate classes are represented. Energy homeostasis is viewed in the context of the selection pressures that simultaneously molded multiple aspects of energy intake, storage, and expenditure. This approach yields surprising conclusions regarding the function of those traits and their underlying neuroendocrine mechanisms. Copyright © 2014. Published by Elsevier Inc.

  5. Air pollution particles and iron homeostasis

    Science.gov (United States)

    Background: The mechanism underlying biological effects of particles deposited in the lung has not been defined. Major Conclusions: A disruption in iron homeostasis follows exposure of cells to all particulate matter including air pollution particles. Following endocytosis, fun...

  6. Association of SSTR2 Polymorphisms and Glucose Homeostasis Phenotypes

    OpenAIRE

    Sutton, Beth S.; Palmer, Nicholette D.; Langefeld, Carl D.; Xue, Bingzhong; Proctor, Alexandria; Ziegler, Julie T.; Haffner, Steven M.; Norris, Jill M.; Bowden, Donald W.

    2009-01-01

    OBJECTIVE This study evaluated the influence of somatostatin receptor type 2 (SSTR2) polymorphisms on measures of glucose homeostasis in the Insulin Resistance Atherosclerosis Family Study (IRASFS). SSTR2 is a G-protein?coupled receptor that, in response to somatostatin, mediates inhibition of insulin, glucagon, and growth hormone release and thus may affect glucose homeostasis. RESEARCH DESIGN AND METHODS Ten single nucleotide polymorphisms (SNPs) spanning the gene were chosen using a SNP de...

  7. Supervision and prognosis architecture based on dynamical classification method for the predictive maintenance of dynamical evolving systems

    International Nuclear Information System (INIS)

    Traore, M.; Chammas, A.; Duviella, E.

    2015-01-01

    In this paper, we are concerned by the improvement of the safety, availability and reliability of dynamical systems’ components subjected to slow degradations (slow drifts). We propose an architecture for efficient Predictive Maintenance (PM) according to the real time estimate of the future state of the components. The architecture is built on supervision and prognosis tools. The prognosis method is based on an appropriated supervision technique that consists in drift tracking of the dynamical systems using AUDyC (AUto-adaptive and Dynamical Clustering), that is an auto-adaptive dynamical classifier. Thus, due to the complexity and the dynamical of the considered systems, the Failure Mode Effect and Criticity Analysis (FMECA) is used to identify the key components of the systems. A component is defined as an element of the system that can be impacted by only one failure. A failure of a key component causes a long downtime of the system. From the FMECA, a Fault Tree Analysis (FTA) of the system are built to determine the propagation laws of a failure on the system by using a deductive method. The proposed architecture is implemented for the PM of a thermoregulator. The application on this real system highlights the interests and the performances of the proposed architecture

  8. Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

    Science.gov (United States)

    Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

    2016-01-01

    Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

  9. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases.

    Science.gov (United States)

    Peterson, A Townsend; Martínez-Campos, Carmen; Nakazawa, Yoshinori; Martínez-Meyer, Enrique

    2005-09-01

    Numerous human diseases-malaria, dengue, yellow fever and leishmaniasis, to name a few-are transmitted by insect vectors with brief life cycles and biting activity that varies in both space and time. Although the general geographic distributions of these epidemiologically important species are known, the spatiotemporal variation in their emergence and activity remains poorly understood. We used ecological niche modeling via a genetic algorithm to produce time-specific predictive models of monthly distributions of Aedes aegypti in Mexico in 1995. Significant predictions of monthly mosquito activity and distributions indicate that predicting spatiotemporal dynamics of disease vector species is feasible; significant coincidence with human cases of dengue indicate that these dynamics probably translate directly into transmission of dengue virus to humans. This approach provides new potential for optimizing use of resources for disease prevention and remediation via automated forecasting of disease transmission risk.

  10. Vertical Wind Tunnel for Prediction of Rocket Flight Dynamics

    Directory of Open Access Journals (Sweden)

    Hoani Bryson

    2016-03-01

    Full Text Available A customized vertical wind tunnel has been built by the University of Canterbury Rocketry group (UC Rocketry. This wind tunnel has been critical for the success of UC Rocketry as it allows the optimization of avionics and control systems before flight. This paper outlines the construction of the wind tunnel and includes an analysis of flow quality including swirl. A minimal modelling methodology for roll dynamics is developed that can extrapolate wind tunnel behavior at low wind speeds to much higher velocities encountered during flight. The models were shown to capture the roll flight dynamics in two rocket launches with mean roll angle errors varying from 0.26° to 1.5° across the flight data. The identified model parameters showed consistent and predictable variations over both wind tunnel tests and flight, including canard–fin interaction behavior. These results demonstrate that the vertical wind tunnel is an important tool for the modelling and control of sounding rockets.

  11. A comparison of molecular dynamics and diffuse interface model predictions of Lennard-Jones fluid evaporation

    Energy Technology Data Exchange (ETDEWEB)

    Barbante, Paolo [Dipartimento di Matematica, Politecnico di Milano - Piazza Leonardo da Vinci 32 - 20133 Milano (Italy); Frezzotti, Aldo; Gibelli, Livio [Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano - Via La Masa 34 - 20156 Milano (Italy)

    2014-12-09

    The unsteady evaporation of a thin planar liquid film is studied by molecular dynamics simulations of Lennard-Jones fluid. The obtained results are compared with the predictions of a diffuse interface model in which capillary Korteweg contributions are added to hydrodynamic equations, in order to obtain a unified description of the liquid bulk, liquid-vapor interface and vapor region. Particular care has been taken in constructing a diffuse interface model matching the thermodynamic and transport properties of the Lennard-Jones fluid. The comparison of diffuse interface model and molecular dynamics results shows that, although good agreement is obtained in equilibrium conditions, remarkable deviations of diffuse interface model predictions from the reference molecular dynamics results are observed in the simulation of liquid film evaporation. It is also observed that molecular dynamics results are in good agreement with preliminary results obtained from a composite model which describes the liquid film by a standard hydrodynamic model and the vapor by the Boltzmann equation. The two mathematical model models are connected by kinetic boundary conditions assuming unit evaporation coefficient.

  12. The vagal innervation of the gut and immune homeostasis.

    Science.gov (United States)

    Matteoli, Gianluca; Boeckxstaens, Guy E

    2013-08-01

    The central nervous system interacts dynamically with the immune system to modulate inflammation through humoral and neural pathways. Recently, in animal models of sepsis, the vagus nerve (VN) has been proposed to play a crucial role in the regulation of the immune response, also referred to as the cholinergic anti-inflammatory pathway. The VN, through release of acetylcholine, dampens immune cell activation by interacting with α-7 nicotinic acetylcholine receptors. Recent evidence suggests that the vagal innervation of the gastrointestinal tract also plays a major role controlling intestinal immune activation. Indeed, VN electrical stimulation potently reduces intestinal inflammation restoring intestinal homeostasis, whereas vagotomy has the reverse effect. In this review, we will discuss the current understanding concerning the mechanisms and effects involved in the cholinergic anti-inflammatory pathway in the gastrointestinal tract. Deeper investigation on this counter-regulatory neuroimmune mechanism will provide new insights in the cross-talk between the nervous and immune system leading to the identification of new therapeutic targets to treat intestinal immune disease.

  13. Predicting Low Energy Dopant Implant Profiles in Semiconductors using Molecular Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Beardmore, K.M.; Gronbech-Jensen, N.

    1999-05-02

    The authors present a highly efficient molecular dynamics scheme for calculating dopant density profiles in group-IV alloy, and III-V zinc blende structure materials. Their scheme incorporates several necessary methods for reducing computational overhead, plus a rare event algorithm to give statistical accuracy over several orders of magnitude change in the dopant concentration. The code uses a molecular dynamics (MD) model to describe ion-target interactions. Atomic interactions are described by a combination of 'many-body' and pair specific screened Coulomb potentials. Accumulative damage is accounted for using a Kinchin-Pease type model, inelastic energy loss is represented by a Firsov expression, and electronic stopping is described by a modified Brandt-Kitagawa model which contains a single adjustable ion-target dependent parameter. Thus, the program is easily extensible beyond a given validation range, and is therefore truly predictive over a wide range of implant energies and angles. The scheme is especially suited for calculating profiles due to low energy and to situations where a predictive capability is required with the minimum of experimental validation. They give examples of using the code to calculate concentration profiles and 2D 'point response' profiles of dopants in crystalline silicon and gallium-arsenide. Here they can predict the experimental profile over five orders of magnitude for <100> and <110> channeling and for non-channeling implants at energies up to hundreds of keV.

  14. Homeostasis, inflammation, and disease susceptibility.

    Science.gov (United States)

    Kotas, Maya E; Medzhitov, Ruslan

    2015-02-26

    While modernization has dramatically increased lifespan, it has also witnessed the increasing prevalence of diseases such as obesity, hypertension, and type 2 diabetes. Such chronic, acquired diseases result when normal physiologic control goes awry and may thus be viewed as failures of homeostasis. However, while nearly every process in human physiology relies on homeostatic mechanisms for stability, only some have demonstrated vulnerability to dysregulation. Additionally, chronic inflammation is a common accomplice of the diseases of homeostasis, yet the basis for this connection is not fully understood. Here we review the design of homeostatic systems and discuss universal features of control circuits that operate at the cellular, tissue, and organismal levels. We suggest a framework for classification of homeostatic signals that is based on different classes of homeostatic variables they report on. Finally, we discuss how adaptability of homeostatic systems with adjustable set points creates vulnerability to dysregulation and disease. This framework highlights the fundamental parallels between homeostatic and inflammatory control mechanisms and provides a new perspective on the physiological origin of inflammation. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Development of crankshaft dynamic stress prediction; Jitsudoji crankshaft oryoku yosoku shuho no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, S; Iwamoto, A; Miyazawa, H; Sato, K; Ozaki, H [Honda R and D Co. Ltd., Tokyo (Japan)

    1997-10-01

    In this paper, the development of the simulation model which predicts the stress of the crankshaft under running condition precisely is described. This simulation model considers about the nonlinearity of the oil film stiffness in the main bearing, the dynamic characteristic of the crankshaft system including resonance and the cylinder block stiffness. By the development of this stress analysis simulation, the stress m each part of the crankshaft during durability testing could be precisely predicted. 1 ref., 10 figs.

  16. Regulation of leucocyte homeostasis in the circulation.

    Science.gov (United States)

    Scheiermann, Christoph; Frenette, Paul S; Hidalgo, Andrés

    2015-08-01

    The functions of blood cells extend well beyond the immune functions of leucocytes or the respiratory and hemostatic functions of erythrocytes and platelets. Seen as a whole, the bloodstream is in charge of nurturing and protecting all organs by carrying a mixture of cell populations in transit from one organ to another. To optimize these functions, evolution has provided blood and the vascular system that carries it with various mechanisms that ensure the appropriate influx and egress of cells into and from the circulation where and when needed. How this homeostatic control of blood is achieved has been the object of study for over a century, and although the major mechanisms that govern it are now fairly well understood, several new concepts and mediators have recently emerged that emphasize the dynamism of this liquid tissue. Here we review old and new concepts that relate to the maintenance and regulation of leucocyte homeostasis in blood and briefly discuss the mechanisms for platelets and red blood cells. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

  17. Sleep apnea predicts distinct alterations in glucose homeostasis and biomarkers in obese adults with normal and impaired glucose metabolism

    Directory of Open Access Journals (Sweden)

    Hill Nathan R

    2010-12-01

    Full Text Available Abstract Background Notwithstanding previous studies supporting independent associations between obstructive sleep apnea (OSA and prevalence of diabetes, the underlying pathogenesis of impaired glucose regulation in OSA remains unclear. We explored mechanisms linking OSA with prediabetes/diabetes and associated biomarker profiles. We hypothesized that OSA is associated with distinct alterations in glucose homeostasis and biomarker profiles in subjects with normal (NGM and impaired glucose metabolism (IGM. Methods Forty-five severely obese adults (36 women without certain comorbidities/medications underwent anthropometric measurements, polysomnography, and blood tests. We measured fasting serum glucose, insulin, selected cytokines, and calculated homeostasis model assessment estimates of insulin sensitivity (HOMA-IS and pancreatic beta-cell function (HOMA-B. Results Both increases in apnea-hypopnea index (AHI and the presence of prediabetes/diabetes were associated with reductions in HOMA-IS in the entire cohort even after adjustment for sex, race, age, and BMI (P = 0.003. In subjects with NGM (n = 30, OSA severity was associated with significantly increased HOMA-B (a trend towards decreased HOMA-IS independent of sex and adiposity. OSA-related oxyhemoglobin desaturations correlated with TNF-α (r=-0.76; P = 0.001 in women with NGM and with IL-6 (rho=-0.55; P = 0.035 in women with IGM (n = 15 matched individually for age, adiposity, and AHI. Conclusions OSA is independently associated with altered glucose homeostasis and increased basal beta-cell function in severely obese adults with NGM. The findings suggest that moderate to severe OSA imposes an excessive functional demand on pancreatic beta-cells, which may lead to their exhaustion and impaired secretory capacity over time. The two distinct biomarker profiles linking sleep apnea with NGM and IGM via TNF-α and IL-6 have been discerned in our study to suggest that sleep apnea and particularly

  18. Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

    Science.gov (United States)

    Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

    2013-11-01

    Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland

  19. Components of calcium homeostasis in Archaeon Methanobacterium thermoautotrophicum

    International Nuclear Information System (INIS)

    Varecka, L.; Smigan, P.; Vancek, M.; Greksak, M.

    1998-01-01

    The cells of Archaea are interesting from several points of view. Among others there are: (a) the evolutionary relationship to procaryotes and eucaryotes and (b) the involvement of Na + and H + gradient in archaeal bio-energetics. The observations are presented which are devoted to the description of components of Ca 2+ homeostasis, an apparatus is vital for both procaryotic and eukaryotic organisms, in obligate anaerobe Methanobacterium thermoautotrophicum. This is, after the demonstration of the ATP-dependent Ca 2+ transport in Halobacterium halobium membrane vesicles, the first complex description of processes of Ca 2+ homeostasis in Archaea. The Ca 2+ influx and efflux was measured using radionuclide 4 5 Ca 2+ . The experiment were performed under strictly anaerobic conditions. The measurement of the membrane potential by means of 3 H-tetraphenyl phosphonium chloride showed that the presence of Na + depolarized the membrane from -110 to -60 mV. The growth of M. thermoautotrophicum and methanogenesis was suppressed but nor arrested by the presence EGTA suggesting that the Ca 2+ homeostasis may be involved in controlling these cellular functions. The results indicate the presence of three components involved in establishing the Ca 2+ homeostasis in cell of M. thermoautotrophicum. The first is the Ca 2+ -carrier mediating the CA 2+ influx driven by the proton motive force or the membrane potential. The Ca 2+ efflux is mediated by two transport systems, Na + /Ca 2+ and H + /Ca 2+ anti-porters. The evidence for the presence of the Ca 2+ -transporting ATPase was not obtained so far. (authors)

  20. Extracellular matrix in lung development, homeostasis and disease.

    Science.gov (United States)

    Zhou, Yong; Horowitz, Jeffrey C; Naba, Alexandra; Ambalavanan, Namasivayam; Atabai, Kamran; Balestrini, Jenna; Bitterman, Peter B; Corley, Richard A; Ding, Bi-Sen; Engler, Adam J; Hansen, Kirk C; Hagood, James S; Kheradmand, Farrah; Lin, Qing S; Neptune, Enid; Niklason, Laura; Ortiz, Luis A; Parks, William C; Tschumperlin, Daniel J; White, Eric S; Chapman, Harold A; Thannickal, Victor J

    2018-03-08

    The lung's unique extracellular matrix (ECM), while providing structural support for cells, is critical in the regulation of developmental organogenesis, homeostasis and injury-repair responses. The ECM, via biochemical or biomechanical cues, regulates diverse cell functions, fate and phenotype. The composition and function of lung ECM become markedly deranged in pathological tissue remodeling. ECM-based therapeutics and bioengineering approaches represent promising novel strategies for regeneration/repair of the lung and treatment of chronic lung diseases. In this review, we assess the current state of lung ECM biology, including fundamental advances in ECM composition, dynamics, topography, and biomechanics; the role of the ECM in normal and aberrant lung development, adult lung diseases and autoimmunity; and ECM in the regulation of the stem cell niche. We identify opportunities to advance the field of lung ECM biology and provide a set recommendations for research priorities to advance knowledge that would inform novel approaches to the pathogenesis, diagnosis, and treatment of chronic lung diseases. Copyright © 2017. Published by Elsevier B.V.

  1. Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?

    Directory of Open Access Journals (Sweden)

    Elizabeth A. Becker

    2016-02-01

    Full Text Available Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered “measured data”, but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE, observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.

  2. Cell Extrusion: A Stress-Responsive Force for Good or Evil in Epithelial Homeostasis.

    Science.gov (United States)

    Ohsawa, Shizue; Vaughen, John; Igaki, Tatsushi

    2018-02-05

    Epithelial tissues robustly respond to internal and external stressors via dynamic cellular rearrangements. Cell extrusion acts as a key regulator of epithelial homeostasis by removing apoptotic cells, orchestrating morphogenesis, and mediating competitive cellular battles during tumorigenesis. Here, we delineate the diverse functions of cell extrusion during development and disease. We emphasize the expanding role for apoptotic cell extrusion in exerting morphogenetic forces, as well as the strong intersection of cell extrusion with cell competition, a homeostatic mechanism that eliminates aberrant or unfit cells. While cell competition and extrusion can exert potent, tumor-suppressive effects, dysregulation of either critical homeostatic program can fuel cancer progression. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. Engineering redox homeostasis to develop efficient alcohol-producing microbial cell factories.

    Science.gov (United States)

    Zhao, Chunhua; Zhao, Qiuwei; Li, Yin; Zhang, Yanping

    2017-06-24

    The biosynthetic pathways of most alcohols are linked to intracellular redox homeostasis, which is crucial for life. This crucial balance is primarily controlled by the generation of reducing equivalents, as well as the (reduction)-oxidation metabolic cycle and the thiol redox homeostasis system. As a main oxidation pathway of reducing equivalents, the biosynthesis of most alcohols includes redox reactions, which are dependent on cofactors such as NADH or NADPH. Thus, when engineering alcohol-producing strains, the availability of cofactors and redox homeostasis must be considered. In this review, recent advances on the engineering of cellular redox homeostasis systems to accelerate alcohol biosynthesis are summarized. Recent approaches include improving cofactor availability, manipulating the affinity of redox enzymes to specific cofactors, as well as globally controlling redox reactions, indicating the power of these approaches, and opening a path towards improving the production of a number of different industrially-relevant alcohols in the near future.

  4. Data based identification and prediction of nonlinear and complex dynamical systems

    Science.gov (United States)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  5. Data based identification and prediction of nonlinear and complex dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

    2016-07-12

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

  6. Data based identification and prediction of nonlinear and complex dynamical systems

    International Nuclear Information System (INIS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-01-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

  7. Gut commensal flora: tolerance and homeostasis

    OpenAIRE

    Rescigno, Maria

    2009-01-01

    Commensal microorganisms are not ignored by the intestinal immune system. Recent evidence shows that commensals actively participate in maintaining intestinal immune homeostasis by interacting with intestinal epithelial cells and delivering tolerogenic signals that are transmitted to the underlying cells of the immune system.

  8. Mitochondrial Dynamics in Type 2 Diabetes and Cancer

    Directory of Open Access Journals (Sweden)

    Michelle Williams

    2018-04-01

    Full Text Available Mitochondria are bioenergetic, biosynthetic, and signaling organelles that control various aspects of cellular and organism homeostasis. Quality control mechanisms are in place to ensure maximal mitochondrial function and metabolic homeostasis at the cellular level. Dysregulation of these pathways is a common theme in human disease. In this mini-review, we discuss how alterations of the mitochondrial network influences mitochondrial function, focusing on the molecular regulators of mitochondrial dynamics (organelle’s shape and localization. We highlight similarities and critical differences in the mitochondrial network of cancer and type 2 diabetes, which may be relevant for treatment of these diseases.

  9. Imbalanced immune homeostasis in immune thrombocytopenia.

    Science.gov (United States)

    Yazdanbakhsh, Karina

    2016-04-01

    Immune thrombocytopenia (ITP) is an autoimmune bleeding disorder resulting from low platelet counts caused by inadequate production as well as increased destruction by autoimmune mechanisms. As with other autoimmune disorders, chronic ITP is characterized by perturbations of immune homeostasis with hyperactivated effector cells as well as defective regulatory arm of the adaptive immune system, which will be reviewed here. Interestingly, some ITP treatments are associated with restoring the regulatory imbalance, although it remains unclear whether the immune system is redirected to a state of tolerance once treatment is discontinued. Understanding the mechanisms that result in breakdown of immune homeostasis in ITP will help to identify novel pathways for restoring tolerance and inhibiting effector cell responses. This information can then be translated into developing therapies for averting autoimmunity not only in ITP but also many autoimmune disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity

    International Nuclear Information System (INIS)

    Vassiliadis, D.

    1992-01-01

    The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms

  11. Prediction and validation of diffusion coefficients in a model drug delivery system using microsecond atomistic molecular dynamics simulation and vapour sorption analysis.

    Science.gov (United States)

    Forrey, Christopher; Saylor, David M; Silverstein, Joshua S; Douglas, Jack F; Davis, Eric M; Elabd, Yossef A

    2014-10-14

    Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.

  12. Dynamic Data-Driven Prediction of Lean Blowout in a Swirl-Stabilized Combustor

    Directory of Open Access Journals (Sweden)

    Soumalya Sarkar

    2015-09-01

    Full Text Available This paper addresses dynamic data-driven prediction of lean blowout (LBO phenomena in confined combustion processes, which are prevalent in many physical applications (e.g., land-based and aircraft gas-turbine engines. The underlying concept is built upon pattern classification and is validated for LBO prediction with time series of chemiluminescence sensor data from a laboratory-scale swirl-stabilized dump combustor. The proposed method of LBO prediction makes use of the theory of symbolic dynamics, where (finite-length time series data are partitioned to produce symbol strings that, in turn, generate a special class of probabilistic finite state automata (PFSA. These PFSA, called D-Markov machines, have a deterministic algebraic structure and their states are represented by symbol blocks of length D or less, where D is a positive integer. The D-Markov machines are constructed in two steps: (i state splitting, i.e., the states are split based on their information contents, and (ii state merging, i.e., two or more states (of possibly different lengths are merged together to form a new state without any significant loss of the embedded information. The modeling complexity (e.g., number of states of a D-Markov machine model is observed to be drastically reduced as the combustor approaches LBO. An anomaly measure, based on Kullback-Leibler divergence, is constructed to predict the proximity of LBO. The problem of LBO prediction is posed in a pattern classification setting and the underlying algorithms have been tested on experimental data at different extents of fuel-air premixing and fuel/air ratio. It is shown that, over a wide range of fuel-air premixing, D-Markov machines with D > 1 perform better as predictors of LBO than those with D = 1.

  13. Thoracolumbar spine model with articulated ribcage for the prediction of dynamic spinal loading.

    Science.gov (United States)

    Ignasiak, Dominika; Dendorfer, Sebastian; Ferguson, Stephen J

    2016-04-11

    Musculoskeletal modeling offers an invaluable insight into the spine biomechanics. A better understanding of thoracic spine kinetics is essential for understanding disease processes and developing new prevention and treatment methods. Current models of the thoracic region are not designed for segmental load estimation, or do not include the complex construct of the ribcage, despite its potentially important role in load transmission. In this paper, we describe a numerical musculoskeletal model of the thoracolumbar spine with articulated ribcage, modeled as a system of individual vertebral segments, elastic elements and thoracic muscles, based on a previously established lumbar spine model and data from the literature. The inverse dynamics simulations of the model allow the prediction of spinal loading as well as costal joints kinetics and kinematics. The intradiscal pressure predicted by the model correlated well (R(2)=0.89) with reported intradiscal pressure measurements, providing a first validation of the model. The inclusion of the ribcage did not affect segmental force predictions when the thoracic spine did not perform motion. During thoracic motion tasks, the ribcage had an important influence on the predicted compressive forces and muscle activation patterns. The compressive forces were reduced by up to 32%, or distributed more evenly between thoracic vertebrae, when compared to the predictions of the model without ribcage, for mild thoracic flexion and hyperextension tasks, respectively. The presented musculoskeletal model provides a tool for investigating thoracic spine loading and load sharing between vertebral column and ribcage during dynamic activities. Further validation for specific applications is still necessary. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Prediction of Cognitive Performance and Subjective Sleepiness Using a Model of Arousal Dynamics.

    Science.gov (United States)

    Postnova, Svetlana; Lockley, Steven W; Robinson, Peter A

    2018-04-01

    A model of arousal dynamics is applied to predict objective performance and subjective sleepiness measures, including lapses and reaction time on a visual Performance Vigilance Test (vPVT), performance on a mathematical addition task (ADD), and the Karolinska Sleepiness Scale (KSS). The arousal dynamics model is comprised of a physiologically based flip-flop switch between the wake- and sleep-active neuronal populations and a dynamic circadian oscillator, thus allowing prediction of sleep propensity. Published group-level experimental constant routine (CR) and forced desynchrony (FD) data are used to calibrate the model to predict performance and sleepiness. Only the studies using dim light (performance measures during CR and FD protocols, with sleep-wake cycles ranging from 20 to 42.85 h and a 2:1 wake-to-sleep ratio. New metrics relating model outputs to performance and sleepiness data are developed and tested against group average outcomes from 7 (vPVT lapses), 5 (ADD), and 8 (KSS) experimental protocols, showing good quantitative and qualitative agreement with the data (root mean squared error of 0.38, 0.19, and 0.35, respectively). The weights of the homeostatic and circadian effects are found to be different between the measures, with KSS having stronger homeostatic influence compared with the objective measures of performance. Using FD data in addition to CR data allows us to challenge the model in conditions of both acute sleep deprivation and structured circadian misalignment, ensuring that the role of the circadian and homeostatic drives in performance is properly captured.

  15. Phospholipid Homeostasis Regulates Dendrite Morphogenesis in Drosophila Sensory Neurons

    Directory of Open Access Journals (Sweden)

    Shan Meltzer

    2017-10-01

    Full Text Available Disruptions in lipid homeostasis have been observed in many neurodevelopmental disorders that are associated with dendrite morphogenesis defects. However, the molecular mechanisms of how lipid homeostasis affects dendrite morphogenesis are unclear. We find that easily shocked (eas, which encodes a kinase with a critical role in phospholipid phosphatidylethanolamine (PE synthesis, and two other enzymes in this synthesis pathway are required cell autonomously in sensory neurons for dendrite growth and stability. Furthermore, we show that the level of Sterol Regulatory Element-Binding Protein (SREBP activity is important for dendrite development. SREBP activity increases in eas mutants, and decreasing the level of SREBP and its transcriptional targets in eas mutants largely suppresses the dendrite growth defects. Furthermore, reducing Ca2+ influx in neurons of eas mutants ameliorates the dendrite morphogenesis defects. Our study uncovers a role for EAS kinase and reveals the in vivo function of phospholipid homeostasis in dendrite morphogenesis.

  16. DC dynamic pull-in predictions for a generalized clamped–clamped micro-beam based on a continuous model and bifurcation analysis

    International Nuclear Information System (INIS)

    Chao, Paul C-P; Chiu, C W; Liu, Tsu-Hsien

    2008-01-01

    This study is devoted to providing precise predictions of the dc dynamic pull-in voltages of a clamped–clamped micro-beam based on a continuous model. A pull-in phenomenon occurs when the electrostatic force on the micro-beam exceeds the elastic restoring force exerted by beam deformation, leading to contact between the actuated beam and bottom electrode. DC dynamic pull-in means that an instantaneous application of the voltage (a step function such as voltage) is applied. To derive the pull-in voltage, a dynamic model in partial differential equations is established based on the equilibrium among beam flexibility, inertia, residual stress, squeeze film, distributed electrostatic forces and its electrical field fringing effects. The method of Galerkin decomposition is then employed to convert the established system equations into reduced discrete modal equations. Considering lower-order modes and approximating the beam deflection by a different order series, bifurcation based on phase portraits is conducted to derive static and dynamic pull-in voltages. It is found that the static pull-in phenomenon follows dynamic instabilities, and the dc dynamic pull-in voltage is around 91–92% of the static counterpart. However, the derived dynamic pull-in voltage is found to be dependent on the varied beam parameters, different from a fixed predicted value derived in past works, where only lumped models are assumed. Furthermore, accurate closed-form predictions are provided for non-narrow beams. The predictions are finally validated by finite element analysis and available experimental data

  17. Human Cardiac 31P-MR Spectroscopy at 3 Tesla Cannot Detect Failing Myocardial Energy Homeostasis during Exercise

    Directory of Open Access Journals (Sweden)

    Adrianus J. Bakermans

    2017-11-01

    Full Text Available Phosphorus-31 magnetic resonance spectroscopy (31P-MRS is a unique non-invasive imaging modality for probing in vivo high-energy phosphate metabolism in the human heart. We investigated whether current 31P-MRS methodology would allow for clinical applications to detect exercise-induced changes in (patho-physiological myocardial energy metabolism. Hereto, measurement variability and repeatability of three commonly used localized 31P-MRS methods [3D image-selected in vivo spectroscopy (ISIS and 1D ISIS with 1D chemical shift imaging (CSI oriented either perpendicular or parallel to the surface coil] to quantify the myocardial phosphocreatine (PCr to adenosine triphosphate (ATP ratio in healthy humans (n = 8 at rest were determined on a clinical 3 Tesla MR system. Numerical simulations of myocardial energy homeostasis in response to increased cardiac work rates were performed using a biophysical model of myocardial oxidative metabolism. Hypertrophic cardiomyopathy was modeled by either inefficient sarcomere ATP utilization or decreased mitochondrial ATP synthesis. The effect of creatine depletion on myocardial energy homeostasis was explored for both conditions. The mean in vivo myocardial PCr/ATP ratio measured with 3D ISIS was 1.57 ± 0.17 with a large repeatability coefficient of 40.4%. For 1D CSI in a 1D ISIS-selected slice perpendicular to the surface coil, the PCr/ATP ratio was 2.78 ± 0.50 (repeatability 42.5%. With 1D CSI in a 1D ISIS-selected slice parallel to the surface coil, the PCr/ATP ratio was 1.70 ± 0.56 (repeatability 43.7%. The model predicted a PCr/ATP ratio reduction of only 10% at the maximal cardiac work rate in normal myocardium. Hypertrophic cardiomyopathy led to lower PCr/ATP ratios for high cardiac work rates, which was exacerbated by creatine depletion. Simulations illustrated that when conducting cardiac 31P-MRS exercise stress testing with large measurement error margins, results obtained under pathophysiologic

  18. Human Cardiac 31P-MR Spectroscopy at 3 Tesla Cannot Detect Failing Myocardial Energy Homeostasis during Exercise

    Science.gov (United States)

    Bakermans, Adrianus J.; Bazil, Jason N.; Nederveen, Aart J.; Strijkers, Gustav J.; Boekholdt, S. Matthijs; Beard, Daniel A.; Jeneson, Jeroen A. L.

    2017-01-01

    Phosphorus-31 magnetic resonance spectroscopy (31P-MRS) is a unique non-invasive imaging modality for probing in vivo high-energy phosphate metabolism in the human heart. We investigated whether current 31P-MRS methodology would allow for clinical applications to detect exercise-induced changes in (patho-)physiological myocardial energy metabolism. Hereto, measurement variability and repeatability of three commonly used localized 31P-MRS methods [3D image-selected in vivo spectroscopy (ISIS) and 1D ISIS with 1D chemical shift imaging (CSI) oriented either perpendicular or parallel to the surface coil] to quantify the myocardial phosphocreatine (PCr) to adenosine triphosphate (ATP) ratio in healthy humans (n = 8) at rest were determined on a clinical 3 Tesla MR system. Numerical simulations of myocardial energy homeostasis in response to increased cardiac work rates were performed using a biophysical model of myocardial oxidative metabolism. Hypertrophic cardiomyopathy was modeled by either inefficient sarcomere ATP utilization or decreased mitochondrial ATP synthesis. The effect of creatine depletion on myocardial energy homeostasis was explored for both conditions. The mean in vivo myocardial PCr/ATP ratio measured with 3D ISIS was 1.57 ± 0.17 with a large repeatability coefficient of 40.4%. For 1D CSI in a 1D ISIS-selected slice perpendicular to the surface coil, the PCr/ATP ratio was 2.78 ± 0.50 (repeatability 42.5%). With 1D CSI in a 1D ISIS-selected slice parallel to the surface coil, the PCr/ATP ratio was 1.70 ± 0.56 (repeatability 43.7%). The model predicted a PCr/ATP ratio reduction of only 10% at the maximal cardiac work rate in normal myocardium. Hypertrophic cardiomyopathy led to lower PCr/ATP ratios for high cardiac work rates, which was exacerbated by creatine depletion. Simulations illustrated that when conducting cardiac 31P-MRS exercise stress testing with large measurement error margins, results obtained under pathophysiologic conditions may

  19. Chaperone-protease networks in mitochondrial protein homeostasis.

    Science.gov (United States)

    Voos, Wolfgang

    2013-02-01

    As essential organelles, mitochondria are intimately integrated into the metabolism of a eukaryotic cell. The maintenance of the functional integrity of the mitochondrial proteome, also termed protein homeostasis, is facing many challenges both under normal and pathological conditions. First, since mitochondria are derived from bacterial ancestor cells, the proteins in this endosymbiotic organelle have a mixed origin. Only a few proteins are encoded on the mitochondrial genome, most genes for mitochondrial proteins reside in the nuclear genome of the host cell. This distribution requires a complex biogenesis of mitochondrial proteins, which are mostly synthesized in the cytosol and need to be imported into the organelle. Mitochondrial protein biogenesis usually therefore comprises complex folding and assembly processes to reach an enzymatically active state. In addition, specific protein quality control (PQC) processes avoid an accumulation of damaged or surplus polypeptides. Mitochondrial protein homeostasis is based on endogenous enzymatic components comprising a diverse set of chaperones and proteases that form an interconnected functional network. This review describes the different types of mitochondrial proteins with chaperone functions and covers the current knowledge of their roles in protein biogenesis, folding, proteolytic removal and prevention of aggregation, the principal reactions of protein homeostasis. This article is part of a Special Issue entitled: Protein Import and Quality Control in Mitochondria and Plastids. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. Evolving chemometric models for predicting dynamic process parameters in viscose production

    Energy Technology Data Exchange (ETDEWEB)

    Cernuda, Carlos [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Lughofer, Edwin, E-mail: edwin.lughofer@jku.at [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Suppan, Lisbeth [Kompetenzzentrum Holz GmbH, St. Peter-Str. 25, 4021 Linz (Austria); Roeder, Thomas; Schmuck, Roman [Lenzing AG, 4860 Lenzing (Austria); Hintenaus, Peter [Software Research Center, Paris Lodron University Salzburg (Austria); Maerzinger, Wolfgang [i-RED Infrarot Systeme GmbH, Linz (Austria); Kasberger, Juergen [Recendt GmbH, Linz (Austria)

    2012-05-06

    Highlights: Black-Right-Pointing-Pointer Quality assurance of process parameters in viscose production. Black-Right-Pointing-Pointer Automatic prediction of spin-bath concentrations based on FTNIR spectra. Black-Right-Pointing-Pointer Evolving chemometric models for efficiently handling changing system dynamics over time (no time-intensive re-calibration needed). Black-Right-Pointing-Pointer Significant reduction of huge errors produced by statistical state-of-the-art calibration methods. Black-Right-Pointing-Pointer Sufficient flexibility achieved by gradual forgetting mechanisms. - Abstract: In viscose production, it is important to monitor three process parameters in order to assure a high quality of the final product: the concentrations of H{sub 2}SO{sub 4}, Na{sub 2}SO{sub 4} and Z{sub n}SO{sub 4}. During on-line production these process parameters usually show a quite high dynamics depending on the fiber type that is produced. Thus, conventional chemometric models, which are trained based on collected calibration spectra from Fourier transform near infrared (FT-NIR) measurements and kept fixed during the whole life-time of the on-line process, show a quite imprecise and unreliable behavior when predicting the concentrations of new on-line data. In this paper, we are demonstrating evolving chemometric models which are able to adapt automatically to varying process dynamics by updating their inner structures and parameters in a single-pass incremental manner. These models exploit the Takagi-Sugeno fuzzy model architecture, being able to model flexibly different degrees of non-linearities implicitly contained in the mapping between near infrared spectra (NIR) and reference values. Updating the inner structures is achieved by moving the position of already existing local regions and by evolving (increasing non-linearity) or merging (decreasing non-linearity) new local linear predictors on demand, which are guided by distance-based and similarity criteria. Gradual

  1. PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models.

    Science.gov (United States)

    Ford, Matthew D; Nikolov, Hristo N; Milner, Jaques S; Lownie, Stephen P; Demont, Edwin M; Kalata, Wojciech; Loth, Francis; Holdsworth, David W; Steinman, David A

    2008-04-01

    Computational fluid dynamics (CFD) modeling of nominally patient-specific cerebral aneurysms is increasingly being used as a research tool to further understand the development, prognosis, and treatment of brain aneurysms. We have previously developed virtual angiography to indirectly validate CFD-predicted gross flow dynamics against the routinely acquired digital subtraction angiograms. Toward a more direct validation, here we compare detailed, CFD-predicted velocity fields against those measured using particle imaging velocimetry (PIV). Two anatomically realistic flow-through phantoms, one a giant internal carotid artery (ICA) aneurysm and the other a basilar artery (BA) tip aneurysm, were constructed of a clear silicone elastomer. The phantoms were placed within a computer-controlled flow loop, programed with representative flow rate waveforms. PIV images were collected on several anterior-posterior (AP) and lateral (LAT) planes. CFD simulations were then carried out using a well-validated, in-house solver, based on micro-CT reconstructions of the geometries of the flow-through phantoms and inlet/outlet boundary conditions derived from flow rates measured during the PIV experiments. PIV and CFD results from the central AP plane of the ICA aneurysm showed a large stable vortex throughout the cardiac cycle. Complex vortex dynamics, captured by PIV and CFD, persisted throughout the cardiac cycle on the central LAT plane. Velocity vector fields showed good overall agreement. For the BA, aneurysm agreement was more compelling, with both PIV and CFD similarly resolving the dynamics of counter-rotating vortices on both AP and LAT planes. Despite the imposition of periodic flow boundary conditions for the CFD simulations, cycle-to-cycle fluctuations were evident in the BA aneurysm simulations, which agreed well, in terms of both amplitudes and spatial distributions, with cycle-to-cycle fluctuations measured by PIV in the same geometry. The overall good agreement

  2. Dynamic transitions in a model of the hypothalamic-pituitary-adrenal axis

    Science.gov (United States)

    Čupić, Željko; Marković, Vladimir M.; Maćešić, Stevan; Stanojević, Ana; Damjanović, Svetozar; Vukojević, Vladana; Kolar-Anić, Ljiljana

    2016-03-01

    Dynamic properties of a nonlinear five-dimensional stoichiometric model of the hypothalamic-pituitary-adrenal (HPA) axis were systematically investigated. Conditions under which qualitative transitions between dynamic states occur are determined by independently varying the rate constants of all reactions that constitute the model. Bifurcation types were further characterized using continuation algorithms and scale factor methods. Regions of bistability and transitions through supercritical Andronov-Hopf and saddle loop bifurcations were identified. Dynamic state analysis predicts that the HPA axis operates under basal (healthy) physiological conditions close to an Andronov-Hopf bifurcation. Dynamic properties of the stress-control axis have not been characterized experimentally, but modelling suggests that the proximity to a supercritical Andronov-Hopf bifurcation can give the HPA axis both, flexibility to respond to external stimuli and adjust to new conditions and stability, i.e., the capacity to return to the original dynamic state afterwards, which is essential for maintaining homeostasis. The analysis presented here reflects the properties of a low-dimensional model that succinctly describes neurochemical transformations underlying the HPA axis. However, the model accounts correctly for a number of experimentally observed properties of the stress-response axis. We therefore regard that the presented analysis is meaningful, showing how in silico investigations can be used to guide the experimentalists in understanding how the HPA axis activity changes under chronic disease and/or specific pharmacological manipulations.

  3. Complex systems dynamics in aging: new evidence, continuing questions.

    Science.gov (United States)

    Cohen, Alan A

    2016-02-01

    There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.

  4. Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Vikas, E-mail: vikas.kumar@urv.cat [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Barros, Felipe P.J. de [Sonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles 90089, CA (United States); Schuhmacher, Marta [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier [Hydrogeology Group, Department of Geotechnical Engineering and Geosciences, University Politècnica de Catalunya-BarcelonaTech, Barcelona 08034 (Spain)

    2013-12-15

    Highlights: • Dynamic parametric interaction in daily dose prediction under uncertainty. • Importance of temporal dynamics associated with the dose. • Different dose experienced by different population cohorts as a function of time. • Relevance of uncertainty reduction in the input parameters shows temporal dynamism. -- Abstract: We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty.

  5. Amino acids and autophagy: cross-talk and co-operation to control cellular homeostasis.

    Science.gov (United States)

    Carroll, Bernadette; Korolchuk, Viktor I; Sarkar, Sovan

    2015-10-01

    Maintenance of amino acid homeostasis is important for healthy cellular function, metabolism and growth. Intracellular amino acid concentrations are dynamic; the high demand for protein synthesis must be met with constant dietary intake, followed by cellular influx, utilization and recycling of nutrients. Autophagy is a catabolic process via which superfluous or damaged proteins and organelles are delivered to the lysosome and degraded to release free amino acids into the cytoplasm. Furthermore, autophagy is specifically activated in response to amino acid starvation via two key signaling cascades: the mammalian target of rapamycin (mTOR) complex 1 (mTORC1) and the general control nonderepressible 2 (GCN2) pathways. These pathways are key regulators of the integration between anabolic (amino acid depleting) and catabolic (such as autophagy which is amino acid replenishing) processes to ensure intracellular amino acid homeostasis. Here, we discuss the key roles that amino acids, along with energy (ATP, glucose) and oxygen, are playing in cellular growth and proliferation. We further explore how sophisticated methods are employed by cells to sense intracellular amino acid concentrations, how amino acids can act as a switch to dictate the temporal and spatial activation of anabolic and catabolic processes and how autophagy contributes to the replenishment of free amino acids, all to ensure cell survival. Relevance of these molecular processes to cellular and organismal physiology and pathology is also discussed.

  6. Predicting Dynamic Response of Structures under Earthquake Loads Using Logical Analysis of Data

    Directory of Open Access Journals (Sweden)

    Ayman Abd-Elhamed

    2018-04-01

    Full Text Available In this paper, logical analysis of data (LAD is used to predict the seismic response of building structures employing the captured dynamic responses. In order to prepare the data, computational simulations using a single degree of freedom (SDOF building model under different ground motion records are carried out. The selected excitation records are real and of different peak ground accelerations (PGA. The sensitivity of the seismic response in terms of displacements of floors to the variation in earthquake characteristics, such as soil class, characteristic period, and time step of records, peak ground displacement, and peak ground velocity, have also been considered. The dynamic equation of motion describing the building model and the applied earthquake load are presented and solved incrementally using the Runge-Kutta method. LAD then finds the characteristic patterns which lead to forecast the seismic response of building structures. The accuracy of LAD is compared to that of an artificial neural network (ANN, since the latter is the most known machine learning technique. Based on the conducted study, the proposed LAD model has been proven to be an efficient technique to learn, simulate, and blindly predict the dynamic response behaviour of building structures subjected to earthquake loads.

  7. Liver immunology and its role in inflammation and homeostasis.

    Science.gov (United States)

    Robinson, Mark W; Harmon, Cathal; O'Farrelly, Cliona

    2016-05-01

    The human liver is usually perceived as a non-immunological organ engaged primarily in metabolic, nutrient storage and detoxification activities. However, we now know that the healthy liver is also a site of complex immunological activity mediated by a diverse immune cell repertoire as well as non-hematopoietic cell populations. In the non-diseased liver, metabolic and tissue remodeling functions require elements of inflammation. This inflammation, in combination with regular exposure to dietary and microbial products, creates the potential for excessive immune activation. In this complex microenvironment, the hepatic immune system tolerates harmless molecules while at the same time remaining alert to possible infectious agents, malignant cells or tissue damage. Upon appropriate immune activation to challenge by pathogens or tissue damage, mechanisms to resolve inflammation are essential to maintain liver homeostasis. Failure to clear 'dangerous' stimuli or regulate appropriately activated immune mechanisms leads to pathological inflammation and disrupted tissue homeostasis characterized by the progressive development of fibrosis, cirrhosis and eventual liver failure. Hepatic inflammatory mechanisms therefore have a spectrum of roles in the healthy adult liver; they are essential to maintain tissue and organ homeostasis and, when dysregulated, are key drivers of the liver pathology associated with chronic infection, autoimmunity and malignancy. In this review, we explore the changing perception of inflammation and inflammatory mediators in normal liver homeostasis and propose targeting of liver-specific immune regulation pathways as a therapeutic approach to treat liver disease.

  8. Unacknowledged contributions of Pavlov and Barcroft to Cannon's theory of homeostasis.

    Science.gov (United States)

    Smith, Gerard P

    2008-11-01

    Cannon's theory of homeostasis is the first, major, American contribution to physiological thought. Although it is clear that Cannon's account of homeostasis is personal and based primarily on the work of his laboratory, Cannon made it easy for readers to mistake his 1929 paper and 1932 book for a comprehensive review of the literature relevant to homeostasis. This is unfortunate because Cannon never acknowledged the important contributions of two of his contemporaries, Ivan Pavlov and Joseph Barcroft. Since he did not mention them, their contributions are rarely discussed. This paper attempts to correct this historical problem in two ways. First, I describe the unacknowledged contributions of Pavlov and Barcroft. Then I consider the possible reasons why Cannon ignored them.

  9. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  10. Consumption of added sugars from liquid but not solid sources predicts impaired glucose homeostasis and insulin resistance among youth at risk of obesity.

    Science.gov (United States)

    Wang, Jiawei; Light, Kelly; Henderson, Mélanie; O'Loughlin, Jennifer; Mathieu, Marie-Eve; Paradis, Gilles; Gray-Donald, Katherine

    2014-01-01

    Little is known about longitudinal associations between added sugar consumption (solid and liquid sources) and glucose-insulin homeostasis among youth. Caucasian children (8-10 y) with at least one obese biological parent were recruited in the QUébec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort (n = 630) and followed-up 2 y later (n = 564). Added sugars were assessed by 3 24-h dietary recalls at baseline. Two-year changes were examined in multivariate linear regression models, adjusting for baseline level, age, sex, Tanner stage, energy intake, fat mass (dual-energy X-ray absorptiometry), and physical activity (7 d accelerometer). Added sugar intake in either liquid or solid sources was not related to changes in adiposity measures (fat mass, body mass index, or waist circumference). However, a higher consumption (10 g/d) of added sugars from liquid sources was associated with 0.04 mmol/L higher fasting glucose, 2.3 pmol/L higher fasting insulin, 0.1 unit higher homeostasis model assessment of insulin resistance (HOMA-IR), and 0.4 unit lower Matsuda-insulin sensitivity index (Matsuda-ISI) in all participants (P added sugars from solid sources. Overweight/obese children at baseline had greater increases in adiposity indicators, fasting insulin, and HOMA-IR and decreases in Matsuda-ISI during those 2 y than normal-weight children. Consumption of added sugars from liquid or solid sources was not associated with changes in adiposity, but liquid added sugars were a risk factor for the development of impaired glucose homeostasis and insulin resistance over 2 y among youth at risk of obesity.

  11. Diagnostic Accuracies of Glycated Hemoglobin, Fructosamine, and Homeostasis Model Assessment of Insulin Resistance in Predicting Impaired Fasting Glucose, Impaired Glucose Tolerance, or New Onset Diabetes After Transplantation.

    Science.gov (United States)

    Rosettenstein, Kerri; Viecelli, Andrea; Yong, Kenneth; Nguyen, Hung Do; Chakera, Aron; Chan, Doris; Dogra, Gursharan; Lim, Ee Mun; Wong, Germaine; Lim, Wai H

    2016-07-01

    New onset diabetes after transplantation (NODAT) is associated with a 3-fold greater risk of cardiovascular disease events, with early identification and treatment potentially attenuating this risk. The optimal screening test to identify those with NODAT remains unclear, and the aim of this study was to examine the diagnostic accuracies of 4 screening tests in identifying impaired fasting glucose, impaired glucose tolerance (IGT), and NODAT. This is a single-center prospective cohort study of 83 nondiabetic kidney transplant recipients between 2008 and 2011. Oral glucose tolerance test was considered the gold standard in identifying IFG/IGT or NODAT. Diagnostic accuracies of random blood glucose, glycated hemoglobin (HBA1c), fructosamine, and Homeostasis Model Assessment-Insulin Resistance in predicting IFG/IGT or NODAT were assessed using the area under the receiver operating characteristic curve. Forty (48%) recipients had IFG/IGT or NODAT. Compared with HBA1c with adjusted area under the curve (AUC) of 0.88 (95% confidence interval [95% CI], 0.77-0.93), fructosamine was the most accurate test with adjusted AUC of 0.92 (95% CI, 0.83-0.96). The adjusted AUCs of random blood glucose and Homeostasis Model Assessment-Insulin Resistance in identifying IFG/IGT were between 0.81 and 0.85. Restricting to identifying IGT/NODAT using 2-hour oral glucose tolerance test (n = 66), fructosamine was the most accurate diagnostic test with adjusted AUC of 0.93 (95% CI, 0.84-0.99), but not statistically different to HBA1c with adjusted AUC of 0.88 (95% CI, 0.76-0.96). Although HBA1c is an acceptable and widely used screening test in detecting IFG/IGT or NODAT, fructosamine may be a more accurate diagnostic test but this needs to be further examined in larger cohorts.

  12. Calcium homeostasis in fly photoreceptor cells

    NARCIS (Netherlands)

    Oberwinkler, J

    2002-01-01

    In fly photoreceptor cells, two processes dominate the Ca2+ homeostasis: light-induced Ca2+ influx through members of the TRP family of ion channels, and Ca2+ extrusion by Na+/Ca2+ exchange.Ca2+ release from intracellular stores is quantitatively insignificant. Both, the light-activated channels and

  13. Molecular monitoring of equine joint homeostasis

    NARCIS (Netherlands)

    de Grauw, J.C.

    2010-01-01

    Chronic joint disorders are a major cause of impaired mobility and loss of quality of life in both humans and horses. Regardless of the primary insult, any joint disorder is characterized by an upset in normal joint homeostasis, the balance between tissue anabolism and catabolism that is normally

  14. Control of Immune Cell Homeostasis and Function by lncRNAs.

    Science.gov (United States)

    Mowel, Walter K; Kotzin, Jonathan J; McCright, Sam J; Neal, Vanessa D; Henao-Mejia, Jorge

    2018-01-01

    The immune system is composed of diverse cell types that coordinate responses to infection and maintain tissue homeostasis. In each of these cells, extracellular cues determine highly specific epigenetic landscapes and transcriptional profiles to promote immunity while maintaining homeostasis. New evidence indicates that long non-coding RNAs (lncRNAs) play crucial roles in epigenetic and transcriptional regulation in mammals. Thus, lncRNAs have emerged as key regulatory molecules of immune cell gene expression programs in response to microbial and tissue-derived cues. We review here how lncRNAs control the function and homeostasis of cell populations during immune responses, emphasizing the diverse molecular mechanisms by which lncRNAs tune highly contextualized transcriptional programs. In addition, we discuss the new challenges faced in interrogating lncRNA mechanisms and function in the immune system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Assessing Genomic Selection Prediction Accuracy in a Dynamic Barley Breeding Population

    Directory of Open Access Journals (Sweden)

    A. H. Sallam

    2015-03-01

    Full Text Available Prediction accuracy of genomic selection (GS has been previously evaluated through simulation and cross-validation; however, validation based on progeny performance in a plant breeding program has not been investigated thoroughly. We evaluated several prediction models in a dynamic barley breeding population comprised of 647 six-row lines using four traits differing in genetic architecture and 1536 single nucleotide polymorphism (SNP markers. The breeding lines were divided into six sets designated as one parent set and five consecutive progeny sets comprised of representative samples of breeding lines over a 5-yr period. We used these data sets to investigate the effect of model and training population composition on prediction accuracy over time. We found little difference in prediction accuracy among the models confirming prior studies that found the simplest model, random regression best linear unbiased prediction (RR-BLUP, to be accurate across a range of situations. In general, we found that using the parent set was sufficient to predict progeny sets with little to no gain in accuracy from generating larger training populations by combining the parent set with subsequent progeny sets. The prediction accuracy ranged from 0.03 to 0.99 across the four traits and five progeny sets. We explored characteristics of the training and validation populations (marker allele frequency, population structure, and linkage disequilibrium, LD as well as characteristics of the trait (genetic architecture and heritability, . Fixation of markers associated with a trait over time was most clearly associated with reduced prediction accuracy for the mycotoxin trait DON. Higher trait in the training population and simpler trait architecture were associated with greater prediction accuracy.

  16. Sleep Homeostasis and Synaptic Plasticity

    Science.gov (United States)

    2017-06-01

    Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202...circuit (a homeostat) that operates in concert with the circadian circuitry or does sleep drive accumulate everywhere in the brain? To answer these...neurons is capable of generating sleep drive. RNAi-mediated knockdown of insomniac in R2 neurons abolished sleep homeostasis without affecting baseline

  17. Grasshoppers regulate N:p stoichiometric homeostasis by changing phosphorus contents in their frass.

    Science.gov (United States)

    Zhang, Zijia; Elser, James J; Cease, Arianne J; Zhang, Ximei; Yu, Qiang; Han, Xingguo; Zhang, Guangming

    2014-01-01

    Nitrogen (N) and phosphorus (P) are important limiting nutrients for plant production and consumer performance in a variety of ecosystems. As a result, the N:P stoichiometry of herbivores has received increased attention in ecology. However, the mechanisms by which herbivores maintain N:P stoichiometric homeostasis are poorly understood. Here, using a field manipulation experiment we show that the grasshopper Oedaleus asiaticus maintains strong N:P stoichiometric homeostasis regardless of whether grasshoppers were reared at low or high density. Grasshoppers maintained homeostasis by increasing P excretion when eating plants with higher P contents. However, while grasshoppers also maintained constant body N contents, we found no changes in N excretion in response to changing plant N content over the range measured. These results suggest that O. asiaticus maintains P homeostasis primarily by changing P absorption and excretion rates, but that other mechanisms may be more important for regulating N homeostasis. Our findings improve our understanding of consumer-driven P recycling and may help in understanding the factors affecting plant-herbivore interactions and ecosystem processes in grasslands.

  18. Development of iron homeostasis in infants and young children.

    Science.gov (United States)

    Lönnerdal, Bo

    2017-12-01

    Healthy, term, breastfed infants usually have adequate iron stores that, together with the small amount of iron that is contributed by breast milk, make them iron sufficient until ≥6 mo of age. The appropriate concentration of iron in infant formula to achieve iron sufficiency is more controversial. Infants who are fed formula with varying concentrations of iron generally achieve sufficiency with iron concentrations of 2 mg/L (i.e., with iron status that is similar to that of breastfed infants at 6 mo of age). Regardless of the feeding choice, infants' capacity to regulate iron homeostasis is important but less well understood than the regulation of iron absorption in adults, which is inverse to iron status and strongly upregulated or downregulated. Infants who were given daily iron drops compared with a placebo from 4 to 6 mo of age had similar increases in hemoglobin concentrations. In addition, isotope studies have shown no difference in iron absorption between infants with high or low hemoglobin concentrations at 6 mo of age. Together, these findings suggest a lack of homeostatic regulation of iron homeostasis in young infants. However, at 9 mo of age, homeostatic regulatory capacity has developed although, to our knowledge, its extent is not known. Studies in suckling rat pups showed similar results with no capacity to regulate iron homeostasis at 10 d of age when fully nursing, but such capacity occurred at 20 d of age when pups were partially weaned. The major iron transporters in the small intestine divalent metal-ion transporter 1 (DMT1) and ferroportin were not affected by pup iron status at 10 d of age but were strongly affected by iron status at 20 d of age. Thus, mechanisms that regulate iron homeostasis are developed at the time of weaning. Overall, studies in human infants and experimental animals suggest that iron homeostasis is absent or limited early in infancy largely because of a lack of regulation of the iron transporters DMT1 and ferroportin

  19. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    Directory of Open Access Journals (Sweden)

    Cecilia Noecker

    2015-03-01

    Full Text Available Upon infection of a new host, human immunodeficiency virus (HIV replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV. First, we found that the mode of virus production by infected cells (budding vs. bursting has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral

  20. Prediction of main factors’ values of air transportation system safety based on system dynamics

    Science.gov (United States)

    Spiridonov, A. Yu; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikova, E. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Kushnikov, O. V.; Fominykh, D. S.

    2018-05-01

    On the basis of the system-dynamic approach [1-8], a set of models has been developed that makes it possible to analyse and predict the values of the main safety indicators for the operation of aviation transport systems.

  1. Dynamical 3-Space Predicts Hotter Early Universe: Resolves CMB-BBN 7-Li and 4-He Abundance Anomalies

    Directory of Open Access Journals (Sweden)

    Cahill R. T.

    2010-01-01

    Full Text Available The observed abundances of 7-Li and 4-He are significantly inconsistent with the predictions from Big Bang Nucleosynthesis (BBN when using the $Lambda$CDM cosmological model together with the value for $Omega_B h^2 = 0.0224pm0.0009$ from WMAP CMB fluctuations, with the value from BBN required to fit observed abundances being $0.009 < Omega_B h^2 < 0.013$. The dynamical 3-space theory is shown to predict a 20% hotter universe in the radiation-dominated epoch, which then results in a remarkable parameter-free agreement between the BBN and the WMAP value for $Omega_B h^2$. The dynamical 3-space also gives a parameter-free fit to the supernova redshift data, and predicts that the flawed $Lambda$CDM model would require $Omega_Lambda = 0.73$ and $Omega_M = 0.27$ to fit the 3-space dynamics Hubble expansion, and independently of the supernova data. These results amount to the discovery of new physics for the early universe that is matched by numerous other successful observational and experimental tests.

  2. Lyapunov exponent as a metric for assessing the dynamic content and predictability of large-eddy simulations

    Science.gov (United States)

    Nastac, Gabriel; Labahn, Jeffrey W.; Magri, Luca; Ihme, Matthias

    2017-09-01

    Metrics used to assess the quality of large-eddy simulations commonly rely on a statistical assessment of the solution. While these metrics are valuable, a dynamic measure is desirable to further characterize the ability of a numerical simulation for capturing dynamic processes inherent in turbulent flows. To address this issue, a dynamic metric based on the Lyapunov exponent is proposed which assesses the growth rate of the solution separation. This metric is applied to two turbulent flow configurations: forced homogeneous isotropic turbulence and a turbulent jet diffusion flame. First, it is shown that, despite the direct numerical simulation (DNS) and large-eddy simulation (LES) being high-dimensional dynamical systems with O (107) degrees of freedom, the separation growth rate qualitatively behaves like a lower-dimensional dynamical system, in which the dimension of the Lyapunov system is substantially smaller than the discretized dynamical system. Second, a grid refinement analysis of each configuration demonstrates that as the LES filter width approaches the smallest scales of the system the Lyapunov exponent asymptotically approaches a plateau. Third, a small perturbation is superimposed onto the initial conditions of each configuration, and the Lyapunov exponent is used to estimate the time required for divergence, thereby providing a direct assessment of the predictability time of simulations. By comparing inert and reacting flows, it is shown that combustion increases the predictability of the turbulent simulation as a result of the dilatation and increased viscosity by heat release. The predictability time is found to scale with the integral time scale in both the reacting and inert jet flows. Fourth, an analysis of the local Lyapunov exponent is performed to demonstrate that this metric can also determine flow-dependent properties, such as regions that are sensitive to small perturbations or conditions of large turbulence within the flow field. Finally

  3. Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics

    Science.gov (United States)

    Greulich, Philip; Doležal, Jakub; Scott, Matthew; Evans, Martin R.; Allen, Rosalind J.

    2017-12-01

    Understanding how antibiotics inhibit bacteria can help to reduce antibiotic use and hence avoid antimicrobial resistance—yet few theoretical models exist for bacterial growth inhibition by a clinically relevant antibiotic treatment regimen. In particular, in the clinic, antibiotic treatment is time-dependent. Here, we use a theoretical model, previously applied to steady-state bacterial growth, to predict the dynamical response of a bacterial cell to a time-dependent dose of ribosome-targeting antibiotic. Our results depend strongly on whether the antibiotic shows reversible transport and/or low-affinity ribosome binding (‘low-affinity antibiotic’) or, in contrast, irreversible transport and/or high affinity ribosome binding (‘high-affinity antibiotic’). For low-affinity antibiotics, our model predicts that growth inhibition depends on the duration of the antibiotic pulse, and can show a transient period of very fast growth following removal of the antibiotic. For high-affinity antibiotics, growth inhibition depends on peak dosage rather than dose duration, and the model predicts a pronounced post-antibiotic effect, due to hysteresis, in which growth can be suppressed for long times after the antibiotic dose has ended. These predictions are experimentally testable and may be of clinical significance.

  4. Coupling between phosphate and calcium homeostasis: a mathematical model.

    Science.gov (United States)

    Granjon, David; Bonny, Olivier; Edwards, Aurélie

    2017-12-01

    We developed a mathematical model of calcium (Ca) and phosphate (PO 4 ) homeostasis in the rat to elucidate the hormonal mechanisms that underlie the regulation of Ca and PO 4 balance. The model represents the exchanges of Ca and PO 4 between the intestine, plasma, kidneys, bone, and the intracellular compartment, and the formation of Ca-PO 4 -fetuin-A complexes. It accounts for the regulation of these fluxes by parathyroid hormone (PTH), vitamin D 3 , fibroblast growth factor 23, and Ca 2+ -sensing receptors. Our results suggest that the Ca and PO 4 homeostatic systems are robust enough to handle small perturbations in the production rate of either PTH or vitamin D 3 The model predicts that large perturbations in PTH or vitamin D 3 synthesis have a greater impact on the plasma concentration of Ca 2+ ([Ca 2+ ] p ) than on that of PO 4 ([PO 4 ] p ); due to negative feedback loops, [PO 4 ] p does not consistently increase when the production rate of PTH or vitamin D 3 is decreased. Our results also suggest that, following a large PO 4 infusion, the rapidly exchangeable pool in bone acts as a fast, transient storage PO 4 compartment (on the order of minutes), whereas the intracellular pool is able to store greater amounts of PO 4 over several hours. Moreover, a large PO 4 infusion rapidly lowers [Ca 2+ ] p owing to the formation of CaPO 4 complexes. A large Ca infusion, however, has a small impact on [PO 4 ] p , since a significant fraction of Ca binds to albumin. This mathematical model is the first to include all major regulatory factors of Ca and PO 4 homeostasis. Copyright © 2017 the American Physiological Society.

  5. Development of dynamic compartment models for prediction of radionuclide behaviors in rice paddy fields

    International Nuclear Information System (INIS)

    Takahashi, Tomoyuki; Tomita, Ken'ichi; Yamamoto, Kazuhide; Uchida, Shigeo

    2007-01-01

    We are developing dynamic compartment models for prediction of behaviors of some important radionuclides in rice paddy fields for safety assessment of nuclear facilities. For a verification of these models, we report calculations for several different deposition patterns of radionuclides. (author)

  6. Prediction of population with Alzheimer's disease in the European Union using a system dynamics model.

    Science.gov (United States)

    Tomaskova, Hana; Kuhnova, Jitka; Cimler, Richard; Dolezal, Ondrej; Kuca, Kamil

    2016-01-01

    Alzheimer's disease (AD) is a slowly progressing neurodegenerative brain disease with irreversible brain effects; it is the most common cause of dementia. With increasing age, the probability of suffering from AD increases. In this research, population growth of the European Union (EU) until the year 2080 and the number of patients with AD are modeled. The aim of this research is to predict the spread of AD in the EU population until year 2080 using a computer simulation. For the simulation of the EU population and the occurrence of AD in this population, a system dynamics modeling approach has been used. System dynamics is a useful and effective method for the investigation of complex social systems. Over the past decades, its applicability has been demonstrated in a wide variety of applications. In this research, this method has been used to investigate the growth of the EU population and predict the number of patients with AD. The model has been calibrated on the population prediction data created by Eurostat. Based on data from Eurostat, the EU population until year 2080 has been modeled. In 2013, the population of the EU was 508 million and the number of patients with AD was 7.5 million. Based on the prediction, in 2040, the population of the EU will be 524 million and the number of patients with AD will be 13.1 million. By the year 2080, the EU population will be 520 million and the number of patients with AD will be 13.7 million. System dynamics modeling approach has been used for the prediction of the number of patients with AD in the EU population till the year 2080. These results can be used to determine the economic burden of the treatment of these patients. With different input data, the simulation can be used also for the different regions as well as for different noncontagious disease predictions.

  7. A Dynamic Hydrology-Critical Zone Framework for Rainfall-triggered Landslide Hazard Prediction

    Science.gov (United States)

    Dialynas, Y. G.; Foufoula-Georgiou, E.; Dietrich, W. E.; Bras, R. L.

    2017-12-01

    Watershed-scale coupled hydrologic-stability models are still in their early stages, and are characterized by important limitations: (a) either they assume steady-state or quasi-dynamic watershed hydrology, or (b) they simulate landslide occurrence based on a simple one-dimensional stability criterion. Here we develop a three-dimensional landslide prediction framework, based on a coupled hydrologic-slope stability model and incorporation of the influence of deep critical zone processes (i.e., flow through weathered bedrock and exfiltration to the colluvium) for more accurate prediction of the timing, location, and extent of landslides. Specifically, a watershed-scale slope stability model that systematically accounts for the contribution of driving and resisting forces in three-dimensional hillslope segments was coupled with a spatially-explicit and physically-based hydrologic model. The landslide prediction framework considers critical zone processes and structure, and explicitly accounts for the spatial heterogeneity of surface and subsurface properties that control slope stability, including soil and weathered bedrock hydrological and mechanical characteristics, vegetation, and slope morphology. To test performance, the model was applied in landslide-prone sites in the US, the hydrology of which has been extensively studied. Results showed that both rainfall infiltration in the soil and groundwater exfiltration exert a strong control on the timing and magnitude of landslide occurrence. We demonstrate the extent to which three-dimensional slope destabilizing factors, which are modulated by dynamic hydrologic conditions in the soil-bedrock column, control landslide initiation at the watershed scale.

  8. Winnerless competition principle and prediction of the transient dynamics in a Lotka-Volterra model

    Science.gov (United States)

    Afraimovich, Valentin; Tristan, Irma; Huerta, Ramon; Rabinovich, Mikhail I.

    2008-12-01

    Predicting the evolution of multispecies ecological systems is an intriguing problem. A sufficiently complex model with the necessary predicting power requires solutions that are structurally stable. Small variations of the system parameters should not qualitatively perturb its solutions. When one is interested in just asymptotic results of evolution (as time goes to infinity), then the problem has a straightforward mathematical image involving simple attractors (fixed points or limit cycles) of a dynamical system. However, for an accurate prediction of evolution, the analysis of transient solutions is critical. In this paper, in the framework of the traditional Lotka-Volterra model (generalized in some sense), we show that the transient solution representing multispecies sequential competition can be reproducible and predictable with high probability.

  9. Mitochondrial Iron Transport and Homeostasis in Plants

    Directory of Open Access Journals (Sweden)

    Anshika eJain

    2013-09-01

    Full Text Available Iron (Fe is an essential nutrient for plants and although the mechanisms controlling iron uptake from the soil are relatively well understood, comparatively little is known about subcellular trafficking of iron in plant cells. Mitochondria represent a significant iron sink within cells, as iron is required for the proper functioning of respiratory chain protein complexes. Mitochondria are a site of Fe-S cluster synthesis, and possibly heme synthesis as well. Here we review recent insights into the molecular mechanisms controlling mitochondrial iron transport and homeostasis. We focus on the recent identification of a mitochondrial iron uptake transporter in rice and a possible role for metalloreductases in iron uptake by mitochondria. In addition, we highlight recent advances in mitochondrial iron homeostasis with an emphasis on the roles of frataxin and ferritin in iron trafficking and storage within mitochondria.

  10. Recurrent and Dynamic Models for Predicting Streaming Video Quality of Experience.

    Science.gov (United States)

    Bampis, Christos G; Li, Zhi; Katsavounidis, Ioannis; Bovik, Alan C

    2018-07-01

    Streaming video services represent a very large fraction of global bandwidth consumption. Due to the exploding demands of mobile video streaming services, coupled with limited bandwidth availability, video streams are often transmitted through unreliable, low-bandwidth networks. This unavoidably leads to two types of major streaming-related impairments: compression artifacts and/or rebuffering events. In streaming video applications, the end-user is a human observer; hence being able to predict the subjective Quality of Experience (QoE) associated with streamed videos could lead to the creation of perceptually optimized resource allocation strategies driving higher quality video streaming services. We propose a variety of recurrent dynamic neural networks that conduct continuous-time subjective QoE prediction. By formulating the problem as one of time-series forecasting, we train a variety of recurrent neural networks and non-linear autoregressive models to predict QoE using several recently developed subjective QoE databases. These models combine multiple, diverse neural network inputs, such as predicted video quality scores, rebuffering measurements, and data related to memory and its effects on human behavioral responses, using them to predict QoE on video streams impaired by both compression artifacts and rebuffering events. Instead of finding a single time-series prediction model, we propose and evaluate ways of aggregating different models into a forecasting ensemble that delivers improved results with reduced forecasting variance. We also deploy appropriate new evaluation metrics for comparing time-series predictions in streaming applications. Our experimental results demonstrate improved prediction performance that approaches human performance. An implementation of this work can be found at https://github.com/christosbampis/NARX_QoE_release.

  11. Comparative dynamics, seasonality in transmission, and predictability of childhood infections in Mexico

    Science.gov (United States)

    Mahmud, A. S.; Metcalf, C. J. E.; Grenfell, B. T.

    2018-01-01

    The seasonality and periodicity of infections, and the mechanisms underlying observed dynamics, can have implications for control efforts. This is particularly true for acute childhood infections. Among these, the dynamics of measles is the best understood and has been extensively studied, most notably in the UK prior to the start of vaccination. Less is known about the dynamics of other childhood diseases, particularly outside Europe and the US. In this paper, we leverage a unique dataset to examine the epidemiology of six childhood infections - measles, mumps, rubella, varicella, scarlet fever and pertussis - across 32 states in Mexico from 1985 to 2007. This dataset provides us with a spatiotemporal probe into the dynamics of six common childhood infections, and allows us to compare them in the same setting over the same time period. We examine three key epidemiological characteristics of these infections – the age profile of infections, spatiotemporal dynamics, and seasonality in transmission - and compare with predictions from existing theory and past findings. Our analysis reveals interesting epidemiological differences between the six pathogens, and variations across space. We find signatures of term time forcing (reduced transmission during the summer) for measles, mumps, rubella, varicella, and scarlet fever; for pertussis, a lack of term time forcing could not be rejected. PMID:27873563

  12. Ultrasonic inspection of studs (bolts) using dynamic predictive deconvolution and wave shaping.

    Science.gov (United States)

    Suh, D M; Kim, W W; Chung, J G

    1999-01-01

    Bolt degradation has become a major issue in the nuclear industry since the 1980's. If small cracks in stud bolts are not detected early enough, they grow rapidly and cause catastrophic disasters. Their detection, despite its importance, is known to be a very difficult problem due to the complicated structures of the stud bolts. This paper presents a method of detecting and sizing a small crack in the root between two adjacent crests in threads. The key idea is from the fact that the mode-converted Rayleigh wave travels slowly down the face of the crack and turns from the intersection of the crack and the root of thread to the transducer. Thus, when a crack exists, a small delayed pulse due to the Rayleigh wave is detected between large regularly spaced pulses from the thread. The delay time is the same as the propagation delay time of the slow Rayleigh wave and is proportional to the site of the crack. To efficiently detect the slow Rayleigh wave, three methods based on digital signal processing are proposed: wave shaping, dynamic predictive deconvolution, and dynamic predictive deconvolution combined with wave shaping.

  13. A physical model to predict climate dynamics in ventilated bulk-storage of agricultural produce

    NARCIS (Netherlands)

    Lukasse, L.J.S.; Kramer-Cuppen, de J.E.; Voort, van der A.J.

    2007-01-01

    This paper presents a physical model for predicting climate dynamics in ventilated bulk-storage of agricultural produce. A well-ordered model presentation was obtained by combining an object-oriented zonal decomposition with a process-oriented decomposition through matrix¿vector notation. The

  14. Enteric Virome Sensing—Its Role in Intestinal Homeostasis and Immunity

    Directory of Open Access Journals (Sweden)

    Rebecca N. Metzger

    2018-03-01

    Full Text Available Pattern recognition receptors (PRRs sensing commensal microorganisms in the intestine induce tightly controlled tonic signaling in the intestinal mucosa, which is required to maintain intestinal barrier integrity and immune homeostasis. At the same time, PRR signaling pathways rapidly trigger the innate immune defense against invasive pathogens in the intestine. Intestinal epithelial cells and mononuclear phagocytes in the intestine and the gut-associated lymphoid tissues are critically involved in sensing components of the microbiome and regulating immune responses in the intestine to sustain immune tolerance against harmless antigens and to prevent inflammation. These processes have been mostly investigated in the context of the bacterial components of the microbiome so far. The impact of viruses residing in the intestine and the virus sensors, which are activated by these enteric viruses, on intestinal homeostasis and inflammation is just beginning to be unraveled. In this review, we will summarize recent findings indicating an important role of the enteric virome for intestinal homeostasis as well as pathology when the immune system fails to control the enteric virome. We will provide an overview of the virus sensors and signaling pathways, operative in the intestine and the mononuclear phagocyte subsets, which can sense viruses and shape the intestinal immune response. We will discuss how these might interact with resident enteric viruses directly or in context with the bacterial microbiome to affect intestinal homeostasis.

  15. Enteric Virome Sensing-Its Role in Intestinal Homeostasis and Immunity.

    Science.gov (United States)

    Metzger, Rebecca N; Krug, Anne B; Eisenächer, Katharina

    2018-03-23

    Pattern recognition receptors (PRRs) sensing commensal microorganisms in the intestine induce tightly controlled tonic signaling in the intestinal mucosa, which is required to maintain intestinal barrier integrity and immune homeostasis. At the same time, PRR signaling pathways rapidly trigger the innate immune defense against invasive pathogens in the intestine. Intestinal epithelial cells and mononuclear phagocytes in the intestine and the gut-associated lymphoid tissues are critically involved in sensing components of the microbiome and regulating immune responses in the intestine to sustain immune tolerance against harmless antigens and to prevent inflammation. These processes have been mostly investigated in the context of the bacterial components of the microbiome so far. The impact of viruses residing in the intestine and the virus sensors, which are activated by these enteric viruses, on intestinal homeostasis and inflammation is just beginning to be unraveled. In this review, we will summarize recent findings indicating an important role of the enteric virome for intestinal homeostasis as well as pathology when the immune system fails to control the enteric virome. We will provide an overview of the virus sensors and signaling pathways, operative in the intestine and the mononuclear phagocyte subsets, which can sense viruses and shape the intestinal immune response. We will discuss how these might interact with resident enteric viruses directly or in context with the bacterial microbiome to affect intestinal homeostasis.

  16. Molecular aspects of bacterial pH sensing and homeostasis

    Science.gov (United States)

    Krulwich, Terry A.; Sachs, George; Padan, Etana

    2011-01-01

    Diverse mechanisms for pH-sensing and cytoplasmic pH homeostasis enable most bacteria to tolerate or grow at external pH values that are outside the cytoplasmic pH range they must maintain for growth. The most extreme cases are exemplified by the extremophiles that inhabit environments whose pH is below 3 or above 11. Here we describe how recent insights into the structure and function of key molecules and their regulators reveal novel strategies of bacterial pH-homeostasis. These insights may help us better target certain pathogens and better harness the capacities of environmental bacteria. PMID:21464825

  17. A Cross-Age Study of Student Understanding of the Concept of Homeostasis.

    Science.gov (United States)

    Westbrook, Susan L.; Marek, Edmund A.

    1992-01-01

    The conceptual views of homeostasis held by students (n=300) in seventh grade life science, tenth grade biology, and college zoology were examined. A biographical questionnaire, the results from two Piagetian-like developmental tasks, and a concept evaluation statement of homeostasis were collected from each student. Understanding of the concept…

  18. Dynamic Loads and Wake Prediction for Large Wind Turbines Based on Free Wake Method

    Institute of Scientific and Technical Information of China (English)

    Cao Jiufa; Wang Tongguang; Long Hui; Ke Shitang; Xu Bofeng

    2015-01-01

    With large scale wind turbines ,the issue of aerodynamic elastic response is even more significant on dy-namic behaviour of the system .Unsteady free vortex wake method is proposed to calculate the shape of wake and aerodynamic load .Considering the effect of aerodynamic load ,inertial load and gravity load ,the decoupling dy-namic equations are established by using finite element method in conjunction of the modal method and equations are solved numerically by Newmark approach .Finally ,the numerical simulation of a large scale wind turbine is performed through coupling the free vortex wake modelling with structural modelling .The results show that this coupling model can predict the flexible wind turbine dynamic characteristics effectively and efficiently .Under the influence of the gravitational force ,the dynamic response of flapwise direction contributes to the dynamic behavior of edgewise direction under the operational condition of steady wind speed .The difference in dynamic response be-tween the flexible and rigid wind turbines manifests when the aerodynamics/structure coupling effect is of signifi-cance in both wind turbine design and performance calculation .

  19. Role of perisynaptic parameters in neurotransmitter homeostasis - computational study of a general synapse

    Science.gov (United States)

    Pendyam, Sandeep; Mohan, Ashwin; Kalivas, Peter W.; Nair, Satish S.

    2015-01-01

    Extracellular neurotransmitter concentrations vary over a wide range depending on the type of neurotransmitter and location in the brain. Neurotransmitter homeostasis near a synapse is achieved by a balance of several mechanisms including vesicular release from the presynapse, diffusion, uptake by transporters, non-synaptic production, and regulation of release by autoreceptors. These mechanisms are also affected by the glia surrounding the synapse. However, the role of these mechanisms in achieving neurotransmitter homeostasis is not well understood. A biophysical modeling framework was proposed to reverse engineer glial configurations and parameters related to homeostasis for synapses that support a range of neurotransmitter gradients. Model experiments reveal that synapses with extracellular neurotransmitter concentrations in the micromolar range require non-synaptic neurotransmitter sources and tight synaptic isolation by extracellular glial formations. The model was used to identify the role of perisynaptic parameters on neurotransmitter homeostasis, and to propose glial configurations that could support different levels of extracellular neurotransmitter concentrations. Ranking the parameters based on their effect on neurotransmitter homeostasis, non-synaptic sources were found to be the most important followed by transporter concentration and diffusion coefficient. PMID:22460547

  20. Using the Ubiquitin-modified Proteome to Monitor Distinct and Spatially Restricted Protein Homeostasis Dysfunction.

    Science.gov (United States)

    Gendron, Joshua M; Webb, Kristofor; Yang, Bing; Rising, Lisa; Zuzow, Nathan; Bennett, Eric J

    2016-08-01

    Protein homeostasis dysfunction has been implicated in the development and progression of aging related human pathologies. There is a need for the establishment of quantitative methods to evaluate global protein homoeostasis function. As the ubiquitin (ub) proteasome system plays a key role in regulating protein homeostasis, we applied quantitative proteomic methods to evaluate the sensitivity of site-specific ubiquitylation events as markers for protein homeostasis dysfunction. Here, we demonstrate that the ub-modified proteome can exceed the sensitivity of engineered fluorescent reporters as a marker for proteasome dysfunction and can provide unique signatures for distinct proteome challenges which is not possible with engineered reporters. We demonstrate that combining ub-proteomics with subcellular fractionation can effectively separate degradative and regulatory ubiquitylation events on distinct protein populations. Using a recently developed potent inhibitor of the critical protein homeostasis factor p97/VCP, we demonstrate that distinct insults to protein homeostasis function can elicit robust and largely unique alterations to the ub-modified proteome. Taken together, we demonstrate that proteomic approaches to monitor the ub-modified proteome can be used to evaluate global protein homeostasis and can be used to monitor distinct functional outcomes for spatially separated protein populations. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  1. Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

    Science.gov (United States)

    Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

    2016-08-11

    Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

  2. Sleep duration and sleep quality are associated differently with alterations of glucose homeostasis

    DEFF Research Database (Denmark)

    Byberg, Stine; Hansen, Anne-Louise Smidt; Christensen, Dirk Lund

    2012-01-01

    Abstract Aims  Studies suggest that inadequate sleep duration and poor sleep quality increase the risk of impaired glucose regulation and diabetes. However, associations with specific markers of glucose homeostasis are less well explained. The objective of this study was to explore possible...... associations of sleep duration and sleep quality with markers of glucose homeostasis and glucose tolerance status in a healthy population-based study sample. Methods  The study comprised 771 participants from the Danish, population-based cross-sectional ‘Health2008’ study. Sleep duration and sleep quality were...... measured by self-report. Markers of glucose homeostasis were derived from a 3-point oral glucose tolerance test and included fasting plasma glucose, 2-h plasma glucose, HbA1c, two measures of insulin sensitivity (the insulin sensitivity index0,120 and homeostasis model assessment of insulin sensitivity...

  3. Reproductive success is predicted by social dynamics and kinship in managed animal populations [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Saul J. Newman

    2016-05-01

    Full Text Available Kin and group interactions are important determinants of reproductive success in many species. Their optimization could, therefore, potentially improve the productivity and breeding success of managed populations used for agricultural and conservation purposes. Here we demonstrate this potential using a novel approach to measure and predict the effect of kin and group dynamics on reproductive output in a well-known species, the meerkat Suricata suricatta. Variation in social dynamics predicts 30% of the individual variation in reproductive success of this species in managed populations, and accurately forecasts reproductive output at least two years into the future. Optimization of social dynamics in captive meerkat populations doubles their projected reproductive output. These results demonstrate the utility of a quantitative approach to breeding programs informed by social and kinship dynamics. They suggest that this approach has great potential for improvements in the management of social endangered and agricultural species.

  4. [Glucose homeostasis and gut-brain connection].

    Science.gov (United States)

    De Vadder, Filipe; Mithieux, Gilles

    2015-02-01

    Since the XIX(th) century, the brain has been known for its role in regulating food intake (via the control of hunger sensation) and glucose homeostasis. Further interest has come from the discovery of gut hormones, which established a clear link between the gut and the brain in regulating glucose and energy homeostasis. The brain has two particular structures, the hypothalamus and the brainstem, which are sensitive to information coming either from peripheral organs or from the gut (via circulating hormones or nutrients) about the nutritional status of the organism. However, the efforts for a better understanding of these mechanisms have allowed to unveil a new gut-brain neural axis as a key regulator of the metabolic status of the organism. Certain nutrients control the hypothalamic homeostatic function via this axis. In this review, we describe how the gut is connected to the brain via different neural pathways, and how the interplay between these two organs drives the energy balance. © 2015 médecine/sciences – Inserm.

  5. Innate immunity orchestrates adipose tissue homeostasis.

    Science.gov (United States)

    Lin, Yi-Wei; Wei, Li-Na

    2017-06-23

    Obesity is strongly associated with multiple diseases including insulin resistance, type 2 diabetes, cardiovascular diseases, fatty liver disease, neurodegenerative diseases and cancers, etc. Adipose tissue (AT), mainly brown AT (BAT) and white AT (WAT), is an important metabolic and endocrine organ that maintains whole-body homeostasis. BAT contributes to non-shivering thermogenesis in a cold environment; WAT stores energy and produces adipokines that fine-tune metabolic and inflammatory responses. Obesity is often characterized by over-expansion and inflammation of WAT where inflammatory cells/mediators are abundant, especially pro-inflammatory (M1) macrophages, resulting in chronic low-grade inflammation and leading to insulin resistance and metabolic complications. Macrophages constitute the major component of innate immunity and can be activated as a M1 or M2 (anti-inflammatory) phenotype in response to environmental stimuli. Polarized M1 macrophage causes AT inflammation, whereas polarized M2 macrophage promotes WAT remodeling into the BAT phenotype, also known as WAT browning/beiging, which enhances insulin sensitivity and metabolic health. This review will discuss the regulation of AT homeostasis in relation to innate immunity.

  6. Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

    Directory of Open Access Journals (Sweden)

    E Penelope Holland

    Full Text Available Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.

  7. Microbiota-Dependent Crosstalk Between Macrophages and ILC3 Promotes Intestinal Homeostasis

    Science.gov (United States)

    Mortha, Arthur; Chudnovskiy, Aleksey; Hashimoto, Daigo; Bogunovic, Milena; Spencer, Sean P.; Belkaid, Yasmine; Merad, Miriam

    2014-01-01

    The intestinal microbiota and tissue-resident myeloid cells promote immune responses that maintain intestinal homeostasis in the host. However, the cellular cues that translate microbial signals into intestinal homeostasis remain unclear. Here, we show that deficient granulocyte-macrophage colony-stimulating factor (GM-CSF) production altered mononuclear phagocyte effector functions and led to reduced regulatory T cell (Treg) numbers and impaired oral tolerance. We observed that RORγt+ innate lymphoid cells (ILCs) are the primary source of GM-CSF in the gut and that ILC-driven GM-CSF production was dependent on the ability of macrophages to sense microbial signals and produce interleukin-1β. Our findings reveal that commensal microbes promote a crosstalk between innate myeloid and lymphoid cells that leads to immune homeostasis in the intestine. PMID:24625929

  8. Microbiota-dependent crosstalk between macrophages and ILC3 promotes intestinal homeostasis.

    Science.gov (United States)

    Mortha, Arthur; Chudnovskiy, Aleksey; Hashimoto, Daigo; Bogunovic, Milena; Spencer, Sean P; Belkaid, Yasmine; Merad, Miriam

    2014-03-28

    The intestinal microbiota and tissue-resident myeloid cells promote immune responses that maintain intestinal homeostasis in the host. However, the cellular cues that translate microbial signals into intestinal homeostasis remain unclear. Here, we show that deficient granulocyte-macrophage colony-stimulating factor (GM-CSF) production altered mononuclear phagocyte effector functions and led to reduced regulatory T cell (T(reg)) numbers and impaired oral tolerance. We observed that RORγt(+) innate lymphoid cells (ILCs) are the primary source of GM-CSF in the gut and that ILC-driven GM-CSF production was dependent on the ability of macrophages to sense microbial signals and produce interleukin-1β. Our findings reveal that commensal microbes promote a crosstalk between innate myeloid and lymphoid cells that leads to immune homeostasis in the intestine.

  9. Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

    Science.gov (United States)

    Sunnåker, Mikael; Zamora-Sillero, Elias; Dechant, Reinhard; Ludwig, Christina; Busetto, Alberto Giovanni; Wagner, Andreas; Stelling, Joerg

    2013-05-28

    Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms.

  10. Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

    Directory of Open Access Journals (Sweden)

    Adam M Wilson

    2016-03-01

    Full Text Available Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

  11. Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes

    Science.gov (United States)

    Kvaternik, Raymond G.

    2013-01-01

    Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.

  12. Targeting Cardiomyocyte Ca2+ Homeostasis in Heart Failure

    Science.gov (United States)

    Røe, Åsmund T.; Frisk, Michael; Louch, William E.

    2015-01-01

    Improved treatments for heart failure patients will require the development of novel therapeutic strategies that target basal disease mechanisms. Disrupted cardiomyocyte Ca2+ homeostasis is recognized as a major contributor to the heart failure phenotype, as it plays a key role in systolic and diastolic dysfunction, arrhythmogenesis, and hypertrophy and apoptosis signaling. In this review, we outline existing knowledge of the involvement of Ca2+ homeostasis in these deficits, and identify four promising targets for therapeutic intervention: the sarcoplasmic reticulum Ca2+ ATPase, the Na+-Ca2+ exchanger, the ryanodine receptor, and t-tubule structure. We discuss experimental data indicating the applicability of these targets that has led to recent and ongoing clinical trials, and suggest future therapeutic approaches. PMID:25483944

  13. Central insulin action in energy and glucose homeostasis.

    Science.gov (United States)

    Plum, Leona; Belgardt, Bengt F; Brüning, Jens C

    2006-07-01

    Insulin has pleiotropic biological effects in virtually all tissues. However, the relevance of insulin signaling in peripheral tissues has been studied far more extensively than its role in the brain. An evolving body of evidence indicates that in the brain, insulin is involved in multiple regulatory mechanisms including neuronal survival, learning, and memory, as well as in regulation of energy homeostasis and reproductive endocrinology. Here we review insulin's role as a central homeostatic signal with regard to energy and glucose homeostasis and discuss the mechanisms by which insulin communicates information about the body's energy status to the brain. Particular emphasis is placed on the controversial current debate about the similarities and differences between hypothalamic insulin and leptin signaling at the molecular level.

  14. Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities

    Science.gov (United States)

    Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred

    2012-07-01

    The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in

  15. Redox Homeostasis in Pancreatic beta Cells

    Czech Academy of Sciences Publication Activity Database

    Ježek, Petr; Dlasková, Andrea; Plecitá-Hlavatá, Lydie

    2012-01-01

    Roč. 2012, č. 2012 (2012), s. 932838 ISSN 1942-0900 R&D Projects: GA ČR(CZ) GAP302/10/0346; GA ČR(CZ) GPP304/10/P204 Institutional support: RVO:67985823 Keywords : beta cells * reactive oxygen species homeostasis * mitochondria Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition Impact factor: 3.393, year: 2012

  16. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Eric A Yen

    2014-05-01

    Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

  17. Interactions of calcium homeostasis, acetylcholine metabolism, behavior and 3, 4-diaminopyridine during aging

    International Nuclear Information System (INIS)

    Gibson, G.E.; Peterson, C.

    1986-01-01

    Acetylcholine synthesis declines with aging in both whole brain and in various brain regions. Since neither enzyme activities nor acetylcholine concentrations, accurately reflect the dynamics of the cholinergic system, in vivo acetylcholine formation was measured. Incorporation of U-C 14-glucose of 2 H 4 choline into whole brain acetylcholine decreases from 100% (3 months) in two strains of mice. The diminished synthesis is apparently not due to a lack of precursor availability because U- C 14-glucose and 2 H 4 choline entry into the brain is similar at all ages. It is shown that altered brain calcium homeostasis during aging may underlie the deficits in acetylcholine metabolism, as well as those in behavior. Diminished calcium uptake during aging parallels the decline in the calcium dependent release of acetylcholine

  18. Regulation of intestinal homeostasis by innate and adaptive immunity.

    Science.gov (United States)

    Kayama, Hisako; Takeda, Kiyoshi

    2012-11-01

    The intestine is a unique tissue where an elaborate balance is maintained between tolerance and immune responses against a variety of environmental factors such as food and the microflora. In a healthy individual, the microflora stimulates innate and adaptive immune systems to maintain gut homeostasis. However, the interaction of environmental factors with particular genetic backgrounds can lead to dramatic changes in the composition of the microflora (i.e. dysbiosis). Many of the specific commensal-bacterial products and the signaling pathways they trigger have been characterized. The role of T(h)1, T(h)2 and T(h)17 cells in inflammatory bowel disease has been widely investigated, as has the contribution of epithelial cells and subsets of dendritic cells and macrophages. To date, multiple regulatory cells in adaptive immunity, such as regulatory T cells and regulatory B cells, have been shown to maintain gut homeostasis by preventing inappropriate innate and adaptive immune responses to commensal bacteria. Additionally, regulatory myeloid cells have recently been identified that prevent intestinal inflammation by inhibiting T-cell proliferation. An increasing body of evidence has shown that multiple regulatory mechanisms contribute to the maintenance of gut homeostasis.

  19. Predicting the effects of organ motion on the dose delivered by dynamic intensity modulation

    International Nuclear Information System (INIS)

    Yu, C.X.; Jaffray, David; Martinez, A.A.; Wong, J.W.

    1997-01-01

    Purpose: Computer-optimized treatment plans, aimed to enhance tumor control and reduce normal tissue complication, generally require non-uniform beam intensities. One of the techniques for delivering intensity-modulated beams is the use of dynamic multileaf collimation, where the beam aperture and field shape change during irradiation. When intensity-modulated beams are delivered with dynamic collimation, intra-treatment organ motion may not only cause geometric misses at the field boundaries but also create hot and cold spots in the target. The mechanism for producing such effects has not been well understood. This study analyzes the dosimetric effects of intra-treatment organ motion on dynamic intensity modulation. A numerical method is developed for predicting the intensity distributions in a moving target before dose is delivered with dynamic intensity modulation. Material and Methods: In the numerical algorithm, the change in position and shape of the beam aperture with time were modeled as a three-dimensional 'tunnel', with the shape of the field aperture described in the x-y plane and its temporal position shown in the z-dimension. A point in the target had to be in the tunnel in order to receive irradiation and the dose to the point was proportional to the amount of time that this point stayed in the tunnel. Since each point in the target were analyzed separately, non-rigid body variations could easily be handled. The dependency of the dose variations on all parameters involved, including the speed of collimator motion, the frequency and amplitude of the target motion, and the size of the field segments, was analyzed. The algorithm was verified by irradiating moving phantoms with beams of dynamically modulated intensities. Predictions were also made for a treatment of a thoracic tumor using a dynamic wedge. The changes of target position with time were based on the MRI images of the chest region acquired using fast MRI scans in a cine fashion for a duration

  20. Predicting U.S. food demand in the 20th century: a new look at system dynamics

    Science.gov (United States)

    Moorthy, Mukund; Cellier, Francois E.; LaFrance, Jeffrey T.

    1998-08-01

    The paper describes a new methodology for predicting the behavior of macroeconomic variables. The approach is based on System Dynamics and Fuzzy Inductive Reasoning. A four- layer pseudo-hierarchical model is proposed. The bottom layer makes predications about population dynamics, age distributions among the populace, as well as demographics. The second layer makes predications about the general state of the economy, including such variables as inflation and unemployment. The third layer makes predictions about the demand for certain goods or services, such as milk products, used cars, mobile telephones, or internet services. The fourth and top layer makes predictions about the supply of such goods and services, both in terms of their prices. Each layer can be influenced by control variables the values of which are only determined at higher levels. In this sense, the model is not strictly hierarchical. For example, the demand for goods at level three depends on the prices of these goods, which are only determined at level four. Yet, the prices are themselves influenced by the expected demand. The methodology is exemplified by means of a macroeconomic model that makes predictions about US food demand during the 20th century.

  1. Fast dynamics perturbation analysis for prediction of protein functional sites

    Directory of Open Access Journals (Sweden)

    Cohn Judith D

    2008-01-01

    Full Text Available Abstract Background We present a fast version of the dynamics perturbation analysis (DPA algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

  2. Taste bud homeostasis in health, disease, and aging.

    Science.gov (United States)

    Feng, Pu; Huang, Liquan; Wang, Hong

    2014-01-01

    The mammalian taste bud is an onion-shaped epithelial structure with 50-100 tightly packed cells, including taste receptor cells, supporting cells, and basal cells. Taste receptor cells detect nutrients and toxins in the oral cavity and transmit the sensory information to gustatory nerve endings in the buds. Supporting cells may play a role in the clearance of excess neurotransmitters after their release from taste receptor cells. Basal cells are precursor cells that differentiate into mature taste cells. Similar to other epithelial cells, taste cells turn over continuously, with an average life span of about 8-12 days. To maintain structural homeostasis in taste buds, new cells are generated to replace dying cells. Several recent studies using genetic lineage tracing methods have identified populations of progenitor/stem cells for taste buds, although contributions of these progenitor/stem cell populations to taste bud homeostasis have yet to be fully determined. Some regulatory factors of taste cell differentiation and degeneration have been identified, but our understanding of these aspects of taste bud homoeostasis remains limited. Many patients with various diseases develop taste disorders, including taste loss and taste distortion. Decline in taste function also occurs during aging. Recent studies suggest that disruption or alteration of taste bud homeostasis may contribute to taste dysfunction associated with disease and aging.

  3. Taste Bud Homeostasis in Health, Disease, and Aging

    Science.gov (United States)

    2014-01-01

    The mammalian taste bud is an onion-shaped epithelial structure with 50–100 tightly packed cells, including taste receptor cells, supporting cells, and basal cells. Taste receptor cells detect nutrients and toxins in the oral cavity and transmit the sensory information to gustatory nerve endings in the buds. Supporting cells may play a role in the clearance of excess neurotransmitters after their release from taste receptor cells. Basal cells are precursor cells that differentiate into mature taste cells. Similar to other epithelial cells, taste cells turn over continuously, with an average life span of about 8–12 days. To maintain structural homeostasis in taste buds, new cells are generated to replace dying cells. Several recent studies using genetic lineage tracing methods have identified populations of progenitor/stem cells for taste buds, although contributions of these progenitor/stem cell populations to taste bud homeostasis have yet to be fully determined. Some regulatory factors of taste cell differentiation and degeneration have been identified, but our understanding of these aspects of taste bud homoeostasis remains limited. Many patients with various diseases develop taste disorders, including taste loss and taste distortion. Decline in taste function also occurs during aging. Recent studies suggest that disruption or alteration of taste bud homeostasis may contribute to taste dysfunction associated with disease and aging. PMID:24287552

  4. Global brain dynamics during social exclusion predict subsequent behavioral conformity.

    Science.gov (United States)

    Wasylyshyn, Nick; Hemenway Falk, Brett; Garcia, Javier O; Cascio, Christopher N; O'Donnell, Matthew Brook; Bingham, C Raymond; Simons-Morton, Bruce; Vettel, Jean M; Falk, Emily B

    2018-02-01

    Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt their behavior to fit in with others. We examined whether functional brain connectivity during social exclusion in the fMRI scanner can be used to predict subsequent conformity to peer norms. Adolescent males (n = 57) completed a two-part study on teen driving risk: a social exclusion task (Cyberball) during an fMRI session and a subsequent driving simulator session in which they drove alone and in the presence of a peer who expressed risk-averse or risk-accepting driving norms. We computed the difference in functional connectivity between social exclusion and social inclusion from each node in the brain to nodes in two brain networks, one previously associated with mentalizing (medial prefrontal cortex, temporoparietal junction, precuneus, temporal poles) and another with social pain (dorsal anterior cingulate cortex, anterior insula). Using predictive modeling, this measure of global connectivity during exclusion predicted the extent of conformity to peer pressure during driving in the subsequent experimental session. These findings extend our understanding of how global neural dynamics guide social behavior, revealing functional network activity that captures individual differences.

  5. A Quick-responsive DNA Nanotechnology Device for Bio-molecular Homeostasis Regulation.

    Science.gov (United States)

    Wu, Songlin; Wang, Pei; Xiao, Chen; Li, Zheng; Yang, Bing; Fu, Jieyang; Chen, Jing; Wan, Neng; Ma, Cong; Li, Maoteng; Yang, Xiangliang; Zhan, Yi

    2016-08-10

    Physiological processes such as metabolism, cell apoptosis and immune responses, must be strictly regulated to maintain their homeostasis and achieve their normal physiological functions. The speed with which bio-molecular homeostatic regulation occurs directly determines the ability of an organism to adapt to conditional changes. To produce a quick-responsive regulatory system that can be easily utilized for various types of homeostasis, a device called nano-fingers that facilitates the regulation of physiological processes was constructed using DNA origami nanotechnology. This nano-fingers device functioned in linked open and closed phases using two types of DNA tweezers, which were covalently coupled with aptamers that captured specific molecules when the tweezer arms were sufficiently close. Via this specific interaction mechanism, certain physiological processes could be simultaneously regulated from two directions by capturing one biofactor and releasing the other to enhance the regulatory capacity of the device. To validate the universal application of this device, regulation of the homeostasis of the blood coagulant thrombin was attempted using the nano-fingers device. It was successfully demonstrated that this nano-fingers device achieved coagulation buffering upon the input of fuel DNA. This nano-device could also be utilized to regulate the homeostasis of other types of bio-molecules.

  6. CREBH Maintains Circadian Glucose Homeostasis by Regulating Hepatic Glycogenolysis and Gluconeogenesis.

    Science.gov (United States)

    Kim, Hyunbae; Zheng, Ze; Walker, Paul D; Kapatos, Gregory; Zhang, Kezhong

    2017-07-15

    Cyclic AMP-responsive element binding protein, hepatocyte specific (CREBH), is a liver-enriched, endoplasmic reticulum-tethered transcription factor known to regulate the hepatic acute-phase response and lipid homeostasis. In this study, we demonstrate that CREBH functions as a circadian transcriptional regulator that plays major roles in maintaining glucose homeostasis. The proteolytic cleavage and posttranslational acetylation modification of CREBH are regulated by the circadian clock. Functionally, CREBH is required in order to maintain circadian homeostasis of hepatic glycogen storage and blood glucose levels. CREBH regulates the rhythmic expression of the genes encoding the rate-limiting enzymes for glycogenolysis and gluconeogenesis, including liver glycogen phosphorylase (PYGL), phosphoenolpyruvate carboxykinase 1 (PCK1), and the glucose-6-phosphatase catalytic subunit (G6PC). CREBH interacts with peroxisome proliferator-activated receptor α (PPARα) to synergize its transcriptional activities in hepatic gluconeogenesis. The acetylation of CREBH at lysine residue 294 controls CREBH-PPARα interaction and synergy in regulating hepatic glucose metabolism in mice. CREBH deficiency leads to reduced blood glucose levels but increases hepatic glycogen levels during the daytime or upon fasting. In summary, our studies revealed that CREBH functions as a key metabolic regulator that controls glucose homeostasis across the circadian cycle or under metabolic stress. Copyright © 2017 American Society for Microbiology.

  7. Cadm2 regulates body weight and energy homeostasis in mice

    Directory of Open Access Journals (Sweden)

    Xin Yan

    2018-02-01

    Full Text Available Objective: Obesity is strongly linked to genes regulating neuronal signaling and function, implicating the central nervous system in the maintenance of body weight and energy metabolism. Genome-wide association studies identified significant associations between body mass index (BMI and multiple loci near Cell adhesion molecule2 (CADM2, which encodes a mediator of synaptic signaling enriched in the brain. Here we sought to further understand the role of Cadm2 in the pathogenesis of hyperglycemia and weight gain. Methods: We first analyzed Cadm2 expression in the brain of both human subjects and mouse models and subsequently characterized a loss-of-function mouse model of Cadm2 for alterations in glucose and energy homeostasis. Results: We show that the risk variant rs13078960 associates with increased CADM2 expression in the hypothalamus of human subjects. Increased Cadm2 expression in several brain regions of Lepob/ob mice was ameliorated after leptin treatment. Deletion of Cadm2 in obese mice (Cadm2/ob resulted in reduced adiposity, systemic glucose levels, and improved insulin sensitivity. Cadm2-deficient mice exhibited increased locomotor activity, energy expenditure rate, and core body temperature identifying Cadm2 as a potent regulator of systemic energy homeostasis. Conclusions: Together these data illustrate that reducing Cadm2 expression can reverse several traits associated with the metabolic syndrome including obesity, insulin resistance, and impaired glucose homeostasis. Keywords: Cadm2/SynCAM2, Energy homeostasis, Insulin sensitivity, Genome-wide association studies, Leptin signaling

  8. Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

    Science.gov (United States)

    McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

    2014-03-01

    Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

  9. On some descriptive and predictive methods for the dynamics of cancer growth

    Directory of Open Access Journals (Sweden)

    Iulian T. Vlad

    2015-09-01

    Full Text Available Cancer is a widely spread disease that affects a large proportion of the human population, and many research teams are developing algorithms to help medics to understand this disease. In particular, tumor growth has been studied from different viewpoints and several mathematical models have been proposed. In this paper, we review a set of comprehensive and modern tools that are useful for prediction of cancer growth in space and time. We comment on three alternative approaches. We first consider spatio-temporal stochastic processes within a Bayesian framework to model spatial heterogeneity, temporal dependence and spatio-temporal interactions amongst the pixels, providing a general modeling framework for such dynamics. We then consider predictions based on geometric properties of plane curves and vectors, and propose two methods of geometric prediction. Finally we focus on functional data analysis to statistically compare tumor contour evolutions. We also analyze real data on brain tumor.

  10. Neurohypophyseal hormones: novel actors of striated muscle development and homeostasis

    Directory of Open Access Journals (Sweden)

    Alessandra Costa

    2014-09-01

    Full Text Available Since the 1980's, novel functional roles of the neurohypophyseal hormones vasopressin and oxytocin have emerged. Several studies have investigated the effects of these two neurohormones on striated muscle tissues, both in vitro and in vivo. The effects of vasopressin on skeletal myogenic cells, developing muscle and muscle homeostasis have been documented. Oxytocin appears to have a greater influence on cardiomyocite differentiation and heart homeostasis. This review summarizes the studies on these novel roles of the two neurohypophyseal hormones, and open the possibility of new therapeutic approaches for diseases affecting striated muscle.

  11. Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

    Science.gov (United States)

    Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

    2018-01-01

    The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

  12. The liver in regulation of iron homeostasis.

    Science.gov (United States)

    Rishi, Gautam; Subramaniam, V Nathan

    2017-09-01

    The liver is one of the largest and most functionally diverse organs in the human body. In addition to roles in detoxification of xenobiotics, digestion, synthesis of important plasma proteins, gluconeogenesis, lipid metabolism, and storage, the liver also plays a significant role in iron homeostasis. Apart from being the storage site for excess body iron, it also plays a vital role in regulating the amount of iron released into the blood by enterocytes and macrophages. Since iron is essential for many important physiological and molecular processes, it increases the importance of liver in the proper functioning of the body's metabolism. This hepatic iron-regulatory function can be attributed to the expression of many liver-specific or liver-enriched proteins, all of which play an important role in the regulation of iron homeostasis. This review focuses on these proteins and their known roles in the regulation of body iron metabolism. Copyright © 2017 the American Physiological Society.

  13. Chatty Mitochondria: Keeping Balance in Cellular Protein Homeostasis.

    Science.gov (United States)

    Topf, Ulrike; Wrobel, Lidia; Chacinska, Agnieszka

    2016-08-01

    Mitochondria are multifunctional cellular organelles that host many biochemical pathways including oxidative phosphorylation (OXPHOS). Defective mitochondria pose a threat to cellular homeostasis and compensatory responses exist to curtail the source of stress and/or its consequences. The mitochondrial proteome comprises proteins encoded by the nuclear and mitochondrial genomes. Disturbances in protein homeostasis may originate from mistargeting of nuclear encoded mitochondrial proteins. Defective protein import and accumulation of mistargeted proteins leads to stress that triggers translation alterations and proteasomal activation. These cytosolic pathways are complementary to the mitochondrial unfolded protein response (UPRmt) that aims to increase the capacity of protein quality control mechanisms inside mitochondria. They constitute putative targets for interventions aimed at increasing the fitness, stress resistance, and longevity of cells and organisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. The Human Bathtub: Safety and Risk Predictions Including the Dynamic Probability of Operator Errors

    International Nuclear Information System (INIS)

    Duffey, Romney B.; Saull, John W.

    2006-01-01

    Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the 'learning hypothesis' that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new 'best' equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world's commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum

  15. Gastrointestinal Transit Time, Glucose Homeostasis and Metabolic Health: Modulation by Dietary Fibers.

    Science.gov (United States)

    Müller, Mattea; Canfora, Emanuel E; Blaak, Ellen E

    2018-02-28

    Gastrointestinal transit time may be an important determinant of glucose homeostasis and metabolic health through effects on nutrient absorption and microbial composition, among other mechanisms. Modulation of gastrointestinal transit may be one of the mechanisms underlying the beneficial health effects of dietary fibers. These effects include improved glucose homeostasis and a reduced risk of developing metabolic diseases such as obesity and type 2 diabetes mellitus. In this review, we first discuss the regulation of gastric emptying rate, small intestinal transit and colonic transit as well as their relation to glucose homeostasis and metabolic health. Subsequently, we briefly address the reported health effects of different dietary fibers and discuss to what extent the fiber-induced health benefits may be mediated through modulation of gastrointestinal transit.

  16. Mga2 transcription factor regulates an oxygen-responsive lipid homeostasis pathway in fission yeast

    DEFF Research Database (Denmark)

    Burr, Risa; Stewart, Emerson V; Shao, Wei

    2016-01-01

    -binding protein (SREBP) transcription factors regulate lipid homeostasis. In mammals, SREBP-2 controls cholesterol biosynthesis, whereas SREBP-1 controls triacylglycerol and glycerophospholipid biosynthesis. In the fission yeast Schizosaccharomyces pombe, the SREBP-2 homolog Sre1 regulates sterol homeostasis....... In the absence of mga2, fission yeast exhibited growth defects under both normoxia and low oxygen conditions. Mga2 transcriptional targets were enriched for lipid metabolism genes, and mga2Δ cells showed disrupted triacylglycerol and glycerophospholipid homeostasis, most notably with an increase in fatty acid...

  17. Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

    Science.gov (United States)

    Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

    2016-09-01

    We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

  18. FIG4 regulates lysosome membrane homeostasis independent of phosphatase function.

    Science.gov (United States)

    Bharadwaj, Rajnish; Cunningham, Kathleen M; Zhang, Ke; Lloyd, Thomas E

    2016-02-15

    FIG4 is a phosphoinositide phosphatase that is mutated in several diseases including Charcot-Marie-Tooth Disease 4J (CMT4J) and Yunis-Varon syndrome (YVS). To investigate the mechanism of disease pathogenesis, we generated Drosophila models of FIG4-related diseases. Fig4 null mutant animals are viable but exhibit marked enlargement of the lysosomal compartment in muscle cells and neurons, accompanied by an age-related decline in flight ability. Transgenic animals expressing Drosophila Fig4 missense mutations corresponding to human pathogenic mutations can partially rescue lysosomal expansion phenotypes, consistent with these mutations causing decreased FIG4 function. Interestingly, Fig4 mutations predicted to inactivate FIG4 phosphatase activity rescue lysosome expansion phenotypes, and mutations in the phosphoinositide (3) phosphate kinase Fab1 that performs the reverse enzymatic reaction also causes a lysosome expansion phenotype. Since FIG4 and FAB1 are present together in the same biochemical complex, these data are consistent with a model in which FIG4 serves a phosphatase-independent biosynthetic function that is essential for lysosomal membrane homeostasis. Lysosomal phenotypes are suppressed by genetic inhibition of Rab7 or the HOPS complex, demonstrating that FIG4 functions after endosome-to-lysosome fusion. Furthermore, disruption of the retromer complex, implicated in recycling from the lysosome to Golgi, does not lead to similar phenotypes as Fig4, suggesting that the lysosomal defects are not due to compromised retromer-mediated recycling of endolysosomal membranes. These data show that FIG4 plays a critical noncatalytic function in maintaining lysosomal membrane homeostasis, and that this function is disrupted by mutations that cause CMT4J and YVS. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  19. Stochastic Simulation of Cardiac Ventricular Myocyte Calcium Dynamics and Waves

    OpenAIRE

    Tuan, Hoang-Trong Minh; Williams, George S. B.; Chikando, Aristide C.; Sobie, Eric A.; Lederer, W. Jonathan; Jafri, M. Saleet

    2011-01-01

    A three dimensional model of calcium dynamics in the rat ventricular myocyte was developed to study the mechanism of calcium homeostasis and pathological calcium dynamics during calcium overload. The model contains 20,000 calcium release units (CRUs) each containing 49 ryanodine receptors. The model simulates calcium sparks with a realistic spontaneous calcium spark rate. It suggests that in addition to the calcium spark-based leak, there is an invisible calcium leak caused by the stochastic ...

  20. Effectiveness of carnosine on disturbed electrolytes homeostasis ...

    African Journals Online (AJOL)

    Jane

    2011-07-20

    Jul 20, 2011 ... of the cells to cisplatin may result from the interaction of specific proteins with ..... respiration, which is similar to uncoupling of oxidative phosphorylation (Binet ... cellular ion homeostasis with decreased cellular K+ content, increased ... of sodium and hydrogen ions will take place passively. Also, magnesium ...

  1. Integration of Pathway Knowledge and Dynamic Bayesian Networks for the Prediction of Oral Cancer Recurrence.

    Science.gov (United States)

    Kourou, Konstantina; Papaloukas, Costas; Fotiadis, Dimitrios I

    2017-03-01

    Oral squamous cell carcinoma has been characterized as a complex disease which involves dynamic genomic changes at the molecular level. These changes indicate the worth to explore the interactions of the molecules and especially of differentially expressed genes that contribute to cancer progression. Moreover, based on this knowledge the identification of differentially expressed genes and related molecular pathways is of great importance. In the present study, we exploit differentially expressed genes in order to further perform pathway enrichment analysis. According to our results we found significant pathways in which the disease associated genes have been identified as strongly enriched. Furthermore, based on the results of the pathway enrichment analysis we propose a methodology for predicting oral cancer recurrence using dynamic Bayesian networks. The methodology takes into consideration time series gene expression data in order to predict a disease recurrence. Subsequently, we are able to conjecture about the causal interactions between genes in consecutive time intervals. Concerning the performance of the predictive models, the overall accuracy of the algorithm is 81.8% and the area under the ROC curve 89.2% regarding the knowledge from the overrepresented pre-NOTCH Expression and processing pathway.

  2. Iron Homeostasis in Peripheral Nervous System, Still a Black Box?

    Science.gov (United States)

    Taveggia, Carla

    2014-01-01

    Abstract Significance: Iron is the most abundant transition metal in biology and an essential cofactor for many cellular enzymes. Iron homeostasis impairment is also a component of peripheral neuropathies. Recent Advances: During the past years, much effort has been paid to understand the molecular mechanism involved in maintaining systemic iron homeostasis in mammals. This has been stimulated by the evidence that iron dyshomeostasis is an initial cause of several disorders, including genetic and sporadic neurodegenerative disorders. Critical Issues: However, very little has been done to investigate the physiological role of iron in peripheral nervous system (PNS), despite the development of suitable cellular and animal models. Future Directions: To stimulate research on iron metabolism and peripheral neuropathy, we provide a summary of the knowledge on iron homeostasis in the PNS, on its transport across the blood–nerve barrier, its involvement in myelination, and we identify unresolved questions. Furthermore, we comment on the role of iron in iron-related disorder with peripheral component, in demyelinating and metabolic peripheral neuropathies. Antioxid. Redox Signal. 21, 634–648. PMID:24409826

  3. Large-scale evaluation of dynamically important residues in proteins predicted by the perturbation analysis of a coarse-grained elastic model

    Directory of Open Access Journals (Sweden)

    Tekpinar Mustafa

    2009-07-01

    Full Text Available Abstract Backgrounds It is increasingly recognized that protein functions often require intricate conformational dynamics, which involves a network of key amino acid residues that couple spatially separated functional sites. Tremendous efforts have been made to identify these key residues by experimental and computational means. Results We have performed a large-scale evaluation of the predictions of dynamically important residues by a variety of computational protocols including three based on the perturbation and correlation analysis of a coarse-grained elastic model. This study is performed for two lists of test cases with >500 pairs of protein structures. The dynamically important residues predicted by the perturbation and correlation analysis are found to be strongly or moderately conserved in >67% of test cases. They form a sparse network of residues which are clustered both in 3D space and along protein sequence. Their overall conservation is attributed to their dynamic role rather than ligand binding or high network connectivity. Conclusion By modeling how the protein structural fluctuations respond to residue-position-specific perturbations, our highly efficient perturbation and correlation analysis can be used to dissect the functional conformational changes in various proteins with a residue level of detail. The predictions of dynamically important residues serve as promising targets for mutational and functional studies.

  4. Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

    Science.gov (United States)

    Gilra, Aditya; Gerstner, Wulfram

    2017-11-27

    The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

  5. Zinc and the modulation of redox homeostasis

    Science.gov (United States)

    Oteiza, Patricia I.

    2012-01-01

    Zinc, a redox inactive metal, has been long viewed as a component of the antioxidant network, and growing evidence points to its involvement in redox-regulated signaling. These actions are exerted through several mechanisms based on the unique chemical and functional properties of zinc. Overall, zinc contributes to maintain the cell redox balance through different mechanisms including: i) the regulation of oxidant production and metal-induced oxidative damage; ii) the dynamic association of zinc with sulfur in protein cysteine clusters, from which the metal can be released by nitric oxide, peroxides, oxidized glutathione and other thiol oxidant species; iii) zinc-mediated induction of the zinc-binding protein metallothionein, which releases the metal under oxidative conditions and act per se scavenging oxidants; iv) the involvement of zinc in the regulation of glutathione metabolism and of the overall protein thiol redox status; and v) a direct or indirect regulation of redox signaling. Findings of oxidative stress, altered redox signaling, and associated cell/tissue disfunction in cell and animal models of zinc deficiency, stress the relevant role of zinc in the preservation of cell redox homeostasis. However, while the participation of zinc in antioxidant protection, redox sensing, and redox-regulated signaling is accepted, the involved molecules, targets and mechanisms are still partially known and the subject of active research. PMID:22960578

  6. DYNAMIC MODELLING AND ADVANCED PREDICTIVE CONTROL OF A CONTINUOUS PROCESS OF ENZYME PURIFICATION

    Directory of Open Access Journals (Sweden)

    Dechechi E.C.

    1997-01-01

    Full Text Available A dynamic mathematical model, simulation and computer control of a Continuous Affinity Recycle Extraction (CARE process, a protein purification technique based on protein adsorption on solid-phase adsorbents is described in this work. This process, consisting of three reactors, is a multivariable process with considerable time delay in the on-line analyses of the controlled variable. An advanced predictive control configuration, specifically the Dynamic Matrix Control (DMC, was applied. The DMC algorithm was applied in process schemes where the aim was to maintain constant the enzyme concentration in the outlet of the third reactor. The performance of the DMC controller was analyzed in the feed-flow disturbances and the results are presented.

  7. Visual Analysis of Nonlinear Dynamical Systems: Chaos, Fractals, Self-Similarity and the Limits of Prediction

    Directory of Open Access Journals (Sweden)

    Geoff Boeing

    2016-11-01

    Full Text Available Nearly all nontrivial real-world systems are nonlinear dynamical systems. Chaos describes certain nonlinear dynamical systems that have a very sensitive dependence on initial conditions. Chaotic systems are always deterministic and may be very simple, yet they produce completely unpredictable and divergent behavior. Systems of nonlinear equations are difficult to solve analytically, and scientists have relied heavily on visual and qualitative approaches to discover and analyze the dynamics of nonlinearity. Indeed, few fields have drawn as heavily from visualization methods for their seminal innovations: from strange attractors, to bifurcation diagrams, to cobweb plots, to phase diagrams and embedding. Although the social sciences are increasingly studying these types of systems, seminal concepts remain murky or loosely adopted. This article has three aims. First, it argues for several visualization methods to critically analyze and understand the behavior of nonlinear dynamical systems. Second, it uses these visualizations to introduce the foundations of nonlinear dynamics, chaos, fractals, self-similarity and the limits of prediction. Finally, it presents Pynamical, an open-source Python package to easily visualize and explore nonlinear dynamical systems’ behavior.

  8. Glucose Homeostasis Variables in Pregnancy versus Maternal and Infant Body Composition

    Directory of Open Access Journals (Sweden)

    Pontus Henriksson

    2015-07-01

    Full Text Available Intrauterine factors influence infant size and body composition but the mechanisms involved are to a large extent unknown. We studied relationships between the body composition of pregnant women and variables related to their glucose homeostasis, i.e., glucose, HOMA-IR (homeostasis model assessment-insulin resistance, hemoglobin A1c and IGFBP-1 (insulin-like growth factor binding protein-1, and related these variables to the body composition of their infants. Body composition of 209 women in gestational week 32 and of their healthy, singleton and full-term one-week-old infants was measured using air displacement plethysmography. Glucose homeostasis variables were assessed in gestational week 32. HOMA-IR was positively related to fat mass index and fat mass (r2 = 0.32, p < 0.001 of the women. Maternal glucose and HOMA-IR values were positively (p ≤ 0.006 associated, while IGFBP-1was negatively (p = 0.001 associated, with infant fat mass. HOMA-IR was positively associated with fat mass of daughters (p < 0.001, but not of sons (p = 0.65 (Sex-interaction: p = 0.042. In conclusion, glucose homeostasis variables of pregnant women are related to their own body composition and to that of their infants. The results suggest that a previously identified relationship between fat mass of mothers and daughters is mediated by maternal insulin resistance.

  9. Seasonal prediction of the Leeuwin Current using the POAMA dynamical seasonal forecast model

    Energy Technology Data Exchange (ETDEWEB)

    Hendon, Harry H.; Wang, Guomin [Centre for Australian Weather and Climate Research, Bureau of Meteorology, PO Box 1289, Melbourne (Australia)

    2010-06-15

    The potential for predicting interannual variations of the Leeuwin Current along the west coast of Australia is addressed. The Leeuwin Current flows poleward against the prevailing winds and transports warm-fresh tropical water southward along the coast, which has a great impact on local climate and ecosystems. Variations of the current are tightly tied to El Nino/La Nina (weak during El Nino and strong during La Nina). Skilful seasonal prediction of the Leeuwin Current to 9-month lead time is achieved by empirical downscaling of dynamical coupled model forecasts of El Nino and the associated upper ocean heat content anomalies off the north west coast of Australia from the Australian Bureau of Meteorology Predictive Ocean Atmosphere Model for Australia (POAMA) seasonal forecast system. Prediction of the Leeuwin Current is possible because the heat content fluctuations off the north west coast are the primary driver of interannual annual variations of the current and these heat content variations are tightly tied to the occurrence of El Nino/La Nina. POAMA can skilfully predict both the occurrence of El Nino/La Nina and the subsequent transmission of the heat content anomalies from the Pacific onto the north west coast. (orig.)

  10. Environmental metabolomics with data science for investigating ecosystem homeostasis.

    Science.gov (United States)

    Kikuchi, Jun; Ito, Kengo; Date, Yasuhiro

    2018-02-01

    A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches. Copyright © 2017. Published by Elsevier B.V.

  11. Senescent intervertebral disc cells exhibit perturbed matrix homeostasis phenotype.

    Science.gov (United States)

    Ngo, Kevin; Patil, Prashanti; McGowan, Sara J; Niedernhofer, Laura J; Robbins, Paul D; Kang, James; Sowa, Gwendolyn; Vo, Nam

    2017-09-01

    Aging greatly increases the risk for intervertebral disc degeneration (IDD) as a result of proteoglycan loss due to reduced synthesis and enhanced degradation of the disc matrix proteoglycan (PG). How disc matrix PG homeostasis becomes perturbed with age is not known. The goal of this study is to determine whether cellular senescence is a source of this perturbation. We demonstrated that disc cellular senescence is dramatically increased in the DNA repair-deficient Ercc1 -/Δ mouse model of human progeria. In these accelerated aging mice, increased disc cellular senescence is closely associated with the rapid loss of disc PG. We also directly examine PG homeostasis in oxidative damage-induced senescent human cells using an in vitro cell culture model system. Senescence of human disc cells treated with hydrogen peroxide was confirmed by growth arrest, senescence-associated β-galactosidase activity, γH2AX foci, and acquisition of senescence-associated secretory phenotype. Senescent human disc cells also exhibited perturbed matrix PG homeostasis as evidenced by their decreased capacity to synthesize new matrix PG and enhanced degradation of aggrecan, a major matrix PG. of the disc. Our in vivo and in vitro findings altogether suggest that disc cellular senescence is an important driver of PG matrix homeostatic perturbation and PG loss. Published by Elsevier B.V.

  12. Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

    Science.gov (United States)

    Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

    2015-12-01

    Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

  13. Redox and Ionic Homeostasis Regulations against Oxidative, Salinity and Drought Stress in Wheat (A Systems Biology Approach

    Directory of Open Access Journals (Sweden)

    Zahid Hussain Shah

    2017-10-01

    Full Text Available Systems biology and omics has provided a comprehensive understanding about the dynamics of the genome, metabolome, transcriptome, and proteome under stress. In wheat, abiotic stresses trigger specific networks of pathways involved in redox and ionic homeostasis as well as osmotic balance. These networks are considerably more complicated than those in model plants, and therefore, counter models are proposed by unifying the approaches of omics and stress systems biology. Furthermore, crosstalk among these pathways is monitored by the regulation and streaming of transcripts and genes. In this review, we discuss systems biology and omics as a promising tool to study responses to oxidative, salinity, and drought stress in wheat.

  14. In utero fuel homeostasis: Lessons for a clinician

    Directory of Open Access Journals (Sweden)

    P. N Suman Rao

    2013-01-01

    Full Text Available Fetus exists in a complex, dynamic, and yet intriguing symbiosis with its mother as far as fuel metabolism is concerned. Though the dependence on maternal fuel is nearly complete to cater for its high requirement, the fetus is capable of some metabolism of its own. The first half of gestation is a period of maternal anabolism and storage whereas the second half results in exponential fetal growth where maternal stores are mobilized. Glucose is the primary substrate for energy production in the fetus though capable of utilizing alternate sources like lactate, ketoacids, amino acids, fatty acids, and glycogen as fuel under special circumstances. Key transporters like glucose transporters (GLUT are responsible for preferential transfers, which are in turn regulated by complex interaction of maternal and fetal hormones. Amino acids are preferentially utilized for growth and essential fatty acids for development of brain and retina. Insulin, insulin like growth factors, glucagon, catecholamines, and letpin are the hormones implicated in this fascinating process. Hormonal regulation of metabolic substrate utilization and anabolism in the fetus is secondary to the supply of nutrient substrates. The knowledge of fuel homeostasis is crucial for a clinician caring for pregnant women and neonates to manage disorders of metabolism (diabetes, growth (intrauterine growth restriction, and transitional adaptation (hypoglycemia.

  15. Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics

    KAUST Repository

    Roy, S.; Schmeier, S.; Arner, E.; Alam, Tanvir; Parihar, S. P.; Ozturk, M.; Tamgue, O.; Kawaji, H.; de Hoon, M. J. L.; Itoh, M.; Lassmann, T.; Carninci, P.; Hayashizaki, Y.; Forrest, A. R. R.; Bajic, Vladimir B.; Guler, R.; Consortium, F.; Brombacher, F.; Suzuki, H.

    2015-01-01

    Classically or alternatively activated macrophages (M1 and M2, respectively) play distinct and important roles for microbiocidal activity, regulation of inflammation and tissue homeostasis. Despite this, their transcriptional regulatory dynamics

  16. An electrically actuated imperfect microbeam: Dynamical integrity for interpreting and predicting the device response

    KAUST Repository

    Ruzziconi, Laura

    2013-02-20

    In this study we deal with a microelectromechanical system (MEMS) and develop a dynamical integrity analysis to interpret and predict the experimental response. The device consists of a clamped-clamped polysilicon microbeam, which is electrostatically and electrodynamically actuated. It has non-negligible imperfections, which are a typical consequence of the microfabrication process. A single-mode reduced-order model is derived and extensive numerical simulations are performed in a neighborhood of the first symmetric natural frequency, via frequency response diagrams and behavior chart. The typical softening behavior is observed and the overall scenario is explored, when both the frequency and the electrodynamic voltage are varied. We show that simulations based on direct numerical integration of the equation of motion in time yield satisfactory agreement with the experimental data. Nevertheless, these theoretical predictions are not completely fulfilled in some aspects. In particular, the range of existence of each attractor is smaller in practice than in the simulations. This is because these theoretical curves represent the ideal limit case where disturbances are absent, which never occurs under realistic conditions. A reliable prediction of the actual (and not only theoretical) range of existence of each attractor is essential in applications. To overcome this discrepancy and extend the results to the practical case where disturbances exist, a dynamical integrity analysis is developed. After introducing dynamical integrity concepts, integrity profiles and integrity charts are drawn. They are able to describe if each attractor is robust enough to tolerate the disturbances. Moreover, they detect the parameter range where each branch can be reliably observed in practice and where, instead, becomes vulnerable, i.e. they provide valuable information to operate the device in safe conditions according to the desired outcome and depending on the expected disturbances

  17. Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment

    Science.gov (United States)

    S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska

    2012-01-01

    Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) – remotely estimated from LiDAR – control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...

  18. High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Flueck, Alex [Illinois Inst. of Technology, Chicago, IL (United States)

    2017-07-14

    The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform for modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to

  19. Investigation of manganese homeostasis in dogs with anaemia and ...

    African Journals Online (AJOL)

    Investigation of manganese homeostasis in dogs with anaemia and chronic enteropathy. Marisa da Fonseca Ferreira, Arielle Elizabeth Ann Aylor, Richard John Mellanby, Susan Mary Campbell, Adam George Gow ...

  20. Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

    Science.gov (United States)

    Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

    2018-02-01

    The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

  1. Mechanisms of Cell Polarity-Controlled Epithelial Homeostasis and Immunity in the Intestine.

    Science.gov (United States)

    Klunder, Leon J; Faber, Klaas Nico; Dijkstra, Gerard; van IJzendoorn, Sven C D

    2017-07-05

    Intestinal epithelial cell polarity is instrumental to maintain epithelial homeostasis and balance communications between the gut lumen and bodily tissue, thereby controlling the defense against gastrointestinal pathogens and maintenance of immune tolerance to commensal bacteria. In this review, we highlight recent advances with regard to the molecular mechanisms of cell polarity-controlled epithelial homeostasis and immunity in the human intestine. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

  2. Treg cell-IgA axis in maintenance of host immune homeostasis with microbiota

    OpenAIRE

    Feng, Ting; Elson, Charles O.; Cong, Yingzi

    2010-01-01

    The intestine is the home to a vast diversity of microbiota and a complex of mucosal immune system. Multiple regulatory mechanisms control host immune responses to microbiota and maintain intestinal immune homeostasis. This mini review will provide evidence indicating a Treg cell-IgA axis and such axis playing a major role in maintenance of intestinal homeostasis.

  3. Vitamin D Level Between Calcium-Phosphorus Homeostasis and Immune System: New Perspective in Osteoporosis.

    Science.gov (United States)

    Bellavia, Daniele; Costa, Viviana; De Luca, Angela; Maglio, Melania; Pagani, Stefania; Fini, Milena; Giavaresi, Gianluca

    2016-10-13

    Vitamin D is a key molecule in calcium and phosphate homeostasis; however, increasing evidence has recently shown that it also plays a crucial role in the immune system, both innate and adaptive. A deregulation of vitamin D levels, due also to mutations and polymorphisms in the genes of the vitamin D pathway, determines severe alterations in the homeostasis of the organism, resulting in a higher risk of onset of some diseases, including osteoporosis. This review gives an overview of the influence of vitamin D levels on the pathogenesis of osteoporosis, between bone homeostasis and immune system.

  4. Can lymphovascular invasion be predicted by preoperative multiphasic dynamic CT in patients with advanced gastric cancer?

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Zelan; Liang, Cuishan; Huang, Xiaomei; Liu, Zaiyi [Southern Medical University, Guangzhou, Guangdong (China); Guangdong General Hospital, Guangdong Academy of Medical Sciences, Department of Radiology, Guangzhou, Guangdong Province (China); Liang, Changhong; Huang, Yanqi [Guangdong General Hospital, Guangdong Academy of Medical Sciences, Department of Radiology, Guangzhou, Guangdong Province (China); He, Lan [Guangdong General Hospital, Guangdong Academy of Medical Sciences, Department of Radiology, Guangzhou, Guangdong Province (China); South China University of Technology, School of Medicine, Guangzhou, Guangdong (China); Chen, Xin [The Affiliated Guangzhou First People' Hospital, Guangzhou Medical University, Department of Radiology, Guangzhou, Guangdong (China); Xiong, Yabing [Southern Medical University, Guangzhou, Guangdong (China)

    2017-08-15

    To determine whether multiphasic dynamic CT can preoperatively predict lymphovascular invasion (LVI) in advanced gastric cancer (AGC). 278 patients with AGC who underwent preoperative multiphasic dynamic CT were retrospectively recruited. Tumour CT attenuation difference between non-contrast and arterial (Δ{sub AP}), portal (Δ{sub PP}) and delayed phase (Δ{sub DP}), tumour-spleen attenuation difference in the portal phase (Δ{sub T-S}), tumour contrast enhancement ratios (CERs), tumour-to-spleen ratio (TSR) and tumour volumes were obtained. All CT-derived parameters and clinicopathological variables associated with LVI were analysed by univariate analysis, followed by multivariate and receiver operator characteristics (ROC) analysis. Associations between CT predictors for LVI and histopathological characteristics were evaluated by the chi-square test. Δ{sub PP} (OR, 1.056; 95% CI: 1.032-1.080) and Δ{sub T-S} (OR, 1.043; 95% CI: 1.020-1.066) are independent predictors for LVI in AGC. Δ{sub PP}, Δ{sub T-S} and their combination correctly predicted LVI in 74.8% (AUC, 0.775; sensitivity, 88.6%; specificity, 54.1%), 68.7% (AUC, 0.747; sensitivity, 68.3%; specificity, 69.4%) and 71.7% (AUC, 0.800; sensitivity, 67.6%; specificity, 77.8%), respectively. There were significant associations between CT predictors for LVI with tumour histological differentiation and Lauren classification. Multiphasic dynamic CT provides a non-invasive method to predict LVI in AGC through quantitative enhancement measurement. (orig.)

  5. Using Synchrotron X-ray Fluorescence Microprobes in the Study of Metal Homeostasis in Plants

    International Nuclear Information System (INIS)

    Punshon, T.; Guerinot, M.; Lanzirotti, A.

    2009-01-01

    Background and Aims: This Botanical Briefing reviews the application of synchrotron X-ray fluorescence (SXRF) microprobes to the plant sciences; how the technique has expanded our knowledge of metal(loid) homeostasis, and how it can be used in the future. Scope: The use of SXRF microspectroscopy and microtomography in research on metal homeostasis in plants is reviewed. The potential use of SXRF as part of the ionomics toolbox, where it is able to provide fundamental information on the way that plants control metal homeostasis, is recommended. Conclusions: SXRF is one of the few techniques capable of providing spatially resolved in-vivo metal abundance data on a sub-micrometre scale, without the need for chemical fixation, coating, drying or even sectioning of samples. This gives researchers the ability to uncover mechanisms of plant metal homeostasis that can potentially be obscured by the artefacts of sample preparation. Further, new generation synchrotrons with smaller beam sizes and more sensitive detection systems will allow for the imaging of metal distribution within single living plant cells. Even greater advances in our understanding of metal homeostasis in plants can be gained by overcoming some of the practical boundaries that exist in the use of SXRF analysis.

  6. Prediction of the Chapman-Jouguet chemical equilibrium state in a detonation wave from first principles based reactive molecular dynamics.

    Science.gov (United States)

    Guo, Dezhou; Zybin, Sergey V; An, Qi; Goddard, William A; Huang, Fenglei

    2016-01-21

    The combustion or detonation of reacting materials at high temperature and pressure can be characterized by the Chapman-Jouguet (CJ) state that describes the chemical equilibrium of the products at the end of the reaction zone of the detonation wave for sustained detonation. This provides the critical properties and product kinetics for input to macroscale continuum simulations of energetic materials. We propose the ReaxFF Reactive Dynamics to CJ point protocol (Rx2CJ) for predicting the CJ state parameters, providing the means to predict the performance of new materials prior to synthesis and characterization, allowing the simulation based design to be done in silico. Our Rx2CJ method is based on atomistic reactive molecular dynamics (RMD) using the QM-derived ReaxFF force field. We validate this method here by predicting the CJ point and detonation products for three typical energetic materials. We find good agreement between the predicted and experimental detonation velocities, indicating that this method can reliably predict the CJ state using modest levels of computation.

  7. IN-CYLINDER MASS FLOW ESTIMATION AND MANIFOLD PRESSURE DYNAMICS FOR STATE PREDICTION IN SI ENGINES

    Directory of Open Access Journals (Sweden)

    Wojnar Sławomir

    2014-06-01

    Full Text Available The aim of this paper is to present a simple model of the intake manifold dynamics of a spark ignition (SI engine and its possible application for estimation and control purposes. We focus on pressure dynamics, which may be regarded as the foundation for estimating future states and for designing model predictive control strategies suitable for maintaining the desired air fuel ratio (AFR. The flow rate measured at the inlet of the intake manifold and the in-cylinder flow estimation are considered as parts of the proposed model. In-cylinder flow estimation is crucial for engine control, where an accurate amount of aspired air forms the basis for computing the manipulated variables. The solutions presented here are based on the mean value engine model (MVEM approach, using the speed-density method. The proposed in-cylinder flow estimation method is compared to measured values in an experimental setting, while one-step-ahead prediction is illustrated using simulation results.

  8. Homeostasis and Gauss statistics: barriers to understanding natural variability.

    Science.gov (United States)

    West, Bruce J

    2010-06-01

    In this paper, the concept of knowledge is argued to be the top of a three-tiered system of science. The first tier is that of measurement and data, followed by information consisting of the patterns within the data, and ending with theory that interprets the patterns and yields knowledge. Thus, when a scientific theory ceases to be consistent with the database the knowledge based on that theory must be re-examined and potentially modified. Consequently, all knowledge, like glory, is transient. Herein we focus on the non-normal statistics of physiologic time series and conclude that the empirical inverse power-law statistics and long-time correlations are inconsistent with the theoretical notion of homeostasis. We suggest replacing the notion of homeostasis with that of Fractal Physiology.

  9. The Role of Eif6 in Skeletal Muscle Homeostasis Revealed by Endurance Training Co-expression Networks

    Directory of Open Access Journals (Sweden)

    Kim Clarke

    2017-11-01

    Full Text Available Regular endurance training improves muscle oxidative capacity and reduces the risk of age-related disorders. Understanding the molecular networks underlying this phenomenon is crucial. Here, by exploiting the power of computational modeling, we show that endurance training induces profound changes in gene regulatory networks linking signaling and selective control of translation to energy metabolism and tissue remodeling. We discovered that knockdown of the mTOR-independent factor Eif6, which we predicted to be a key regulator of this process, affects mitochondrial respiration efficiency, ROS production, and exercise performance. Our work demonstrates the validity of a data-driven approach to understanding muscle homeostasis.

  10. Thermal conductivity prediction of nanoscale phononic crystal slabs using a hybrid lattice dynamics-continuum mechanics technique

    Directory of Open Access Journals (Sweden)

    Charles M. Reinke

    2011-12-01

    Full Text Available Recent work has demonstrated that nanostructuring of a semiconductor material to form a phononic crystal (PnC can significantly reduce its thermal conductivity. In this paper, we present a classical method that combines atomic-level information with the application of Bloch theory at the continuum level for the prediction of the thermal conductivity of finite-thickness PnCs with unit cells sized in the micron scale. Lattice dynamics calculations are done at the bulk material level, and the plane-wave expansion method is implemented at the macrosale PnC unit cell level. The combination of the lattice dynamics-based and continuum mechanics-based dispersion information is then used in the Callaway-Holland model to calculate the thermal transport properties of the PnC. We demonstrate that this hybrid approach provides both accurate and efficient predictions of the thermal conductivity.

  11. A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

    Science.gov (United States)

    Yasami, Yasser; Safaei, Farshad

    2018-02-01

    The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of

  12. The tumor necrosis factor-alpha-induced protein 8 family in immune homeostasis and inflammatory cancer diseases.

    Science.gov (United States)

    Luan, Y Y; Yao, Y M; Sheng, Z Y

    2013-01-01

    Within the immune system homeostasis is maintained by a myriad of mechanisms that include the regulation of immune cell activation and programmed cell death. The breakdown of immune homeostasis may lead to fatal inflammatory diseases. We set out to identify genes of tumor necrosis factor-alpha-induced protein 8 (TNFAIP8) family that has a functional role in the process of immune homeostasis. Tumor necrosis factor-alpha-induced protein 8 (TNFAIP8), which functions as an oncogenic molecule, is also associated with enhanced cell survival and inhibition of apoptosis. Tumor necrosis factor-alpha-induced protein 8-like 2 (TIPE2) governs immune homeostasis in both the innate and adaptive immune system and prevents hyper-responsiveness by negatively regulating signaling via T cell receptors and Toll-like receptors (TLRs). There also exist two highly homologous but uncharacterized proteins, TIPE1 and TIPE3. This review is an attempt to provide a summary of TNFAIP8 family associated with immune homeostasis and inflammatory cancer diseases.

  13. Prediction of coking dynamics for wet coal charge

    Directory of Open Access Journals (Sweden)

    Kardaś Dariusz

    2015-09-01

    Full Text Available A one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal pressure were presented and analysed. The theoretical predictions of temperature change in the centre plane of the coke oven were compared with industrialscale measurements. Both, the experimental data and obtained numerical results show that moisture content determines the coking process dynamics, lagging the temperature increase above the water steam evaporation temperature and in consequence the total coking time. The phenomenon of internal pressure generation in the context of overlapping effects of simultaneously occurring coal transitions - devolatilisation and coal permeability decrease under plastic stage - was also discussed.

  14. Predicting Reactive Transport Dynamics in Carbonates using Initial Pore Structure

    Science.gov (United States)

    Menke, H. P.; Nunes, J. P. P.; Blunt, M. J.

    2017-12-01

    Understanding rock-fluid interaction at the pore-scale is imperative for accurate predictive modelling of carbon storage permanence. However, coupled reactive transport models are computationally expensive, requiring either a sacrifice of resolution or high performance computing to solve relatively simple geometries. Many recent studies indicate that initial pore structure many be the dominant mechanism in determining the dissolution regime. Here we investigate how well the initial pore structure is predictive of distribution and amount of dissolution during reactive flow using particle tracking on the initial image. Two samples of carbonate rock with varying initial pore space heterogeneity were reacted with reservoir condition CO2-saturated brine and scanned dynamically during reactive flow at a 4-μm resolution between 4 and 40 times using 4D X-ray micro-tomography over the course of 1.5 hours using μ-CT. Flow was modelled on the initial binarized image using a Navier-Stokes solver. Particle tracking was then run on the velocity fields, the streamlines were traced, and the streamline density was calculated both on a voxel-by-voxel and a channel-by-channel basis. The density of streamlines was then compared to the amount of dissolution in subsequent time steps during reaction. It was found that for the flow and transport regimes studied, the streamline density distribution in the initial image accurately predicted the dominant pathways of dissolution and gave good indicators of the type of dissolution regime that would later develop. This work suggests that the eventual reaction-induced changes in pore structure are deterministic rather than stochastic and can be predicted with high resolution imaging of unreacted rock.

  15. Predicting lymphatic filariasis transmission and elimination dynamics using a multi-model ensemble framework

    Directory of Open Access Journals (Sweden)

    Morgan E. Smith

    2017-03-01

    Full Text Available Mathematical models of parasite transmission provide powerful tools for assessing the impacts of interventions. Owing to complexity and uncertainty, no single model may capture all features of transmission and elimination dynamics. Multi-model ensemble modelling offers a framework to help overcome biases of single models. We report on the development of a first multi-model ensemble of three lymphatic filariasis (LF models (EPIFIL, LYMFASIM, and TRANSFIL, and evaluate its predictive performance in comparison with that of the constituents using calibration and validation data from three case study sites, one each from the three major LF endemic regions: Africa, Southeast Asia and Papua New Guinea (PNG. We assessed the performance of the respective models for predicting the outcomes of annual MDA strategies for various baseline scenarios thought to exemplify the current endemic conditions in the three regions. The results show that the constructed multi-model ensemble outperformed the single models when evaluated across all sites. Single models that best fitted calibration data tended to do less well in simulating the out-of-sample, or validation, intervention data. Scenario modelling results demonstrate that the multi-model ensemble is able to compensate for variance between single models in order to produce more plausible predictions of intervention impacts. Our results highlight the value of an ensemble approach to modelling parasite control dynamics. However, its optimal use will require further methodological improvements as well as consideration of the organizational mechanisms required to ensure that modelling results and data are shared effectively between all stakeholders.

  16. A Dual-Sensing Receptor Confers Robust Cellular Homeostasis

    Directory of Open Access Journals (Sweden)

    Hannah Schramke

    2016-06-01

    Full Text Available Cells have evolved diverse mechanisms that maintain intracellular homeostasis in fluctuating environments. In bacteria, control is often exerted by bifunctional receptors acting as both kinase and phosphatase to regulate gene expression, a design known to provide robustness against noise. Yet how such antagonistic enzymatic activities are balanced as a function of environmental change remains poorly understood. We find that the bifunctional receptor that regulates K+ uptake in Escherichia coli is a dual sensor, which modulates its autokinase and phosphatase activities in response to both extracellular and intracellular K+ concentration. Using mathematical modeling, we show that dual sensing is a superior strategy for ensuring homeostasis when both the supply of and demand for a limiting resource fluctuate. By engineering standards, this molecular control system displays a strikingly high degree of functional integration, providing a reference for the vast numbers of receptors for which the sensing strategy remains elusive.

  17. Glucocorticoid receptor polymorphism in obesity and glucose homeostasis.

    Science.gov (United States)

    Majer-Łobodzińska, Agnieszka; Adamiec-Mroczek, Joanna

    2017-01-01

    Glucocorticoid receptor (GR) activity plays a significant role in the etiology of obesity and is essential for glucose homeostasis, the development of hyperinsulinaemia and subsequent increased fat deposition. Several polymorphisms in the GR gene have been described, and at least three of them seem to be associated with altered glucocorticoid sensitivity and changes in glucose homeostasis, and other metabolic parameters. The N363S polymorphism has been associated with increased sensitivity to glucocorticoides, increased insulin response to dexamethasone and increased plasma glucose level. BclI polymorphism is associated with increased abdominal obesity, hyperinsulinaemia and increased insulin resistance. Another polymorphism, ER22/23EK, in contrast to the others, is associated with relative resistance to glucocoricides actions and more beneficial metabolic profile-lower insulin resistance level, decreased lower cardiovascular risk and subseuent prolongation of life time. More research is still needed to understand the mechanisms behind these associations at the molecular level.

  18. A new vesicle trafficking regulator CTL1 plays a crucial role in ion homeostasis.

    Science.gov (United States)

    Gao, Yi-Qun; Chen, Jiu-Geng; Chen, Zi-Ru; An, Dong; Lv, Qiao-Yan; Han, Mei-Ling; Wang, Ya-Ling; Salt, David E; Chao, Dai-Yin

    2017-12-01

    Ion homeostasis is essential for plant growth and environmental adaptation, and maintaining ion homeostasis requires the precise regulation of various ion transporters, as well as correct root patterning. However, the mechanisms underlying these processes remain largely elusive. Here, we reported that a choline transporter gene, CTL1, controls ionome homeostasis by regulating the secretory trafficking of proteins required for plasmodesmata (PD) development, as well as the transport of some ion transporters. Map-based cloning studies revealed that CTL1 mutations alter the ion profile of Arabidopsis thaliana. We found that the phenotypes associated with these mutations are caused by a combination of PD defects and ion transporter misregulation. We also established that CTL1 is involved in regulating vesicle trafficking and is thus required for the trafficking of proteins essential for ion transport and PD development. Characterizing choline transporter-like 1 (CTL1) as a new regulator of protein sorting may enable researchers to understand not only ion homeostasis in plants but also vesicle trafficking in general.

  19. Available states and available space: Static properties that predict dynamics of confined fluids

    OpenAIRE

    Goel, Gaurav; Krekelberg, William P.; Pond, Mark J.; Mittal, Jeetain; Shen, Vincent K.; Errington, Jeffrey R.; Truskett, Thomas M.

    2009-01-01

    Although density functional theory provides reliable predictions for the static properties of simple fluids under confinement, a theory of comparative accuracy for the transport coefficients has yet to emerge. Nonetheless, there is evidence that knowledge of how confinement modifies static behavior can aid in forecasting dynamics. Specifically, molecular simulation studies have shown that the relationship between excess entropy and self diffusivity of a bulk equilibrium fluid changes only mod...

  20. Thermophysical properties of liquid UO2, ZrO2 and corium by molecular dynamics and predictive models

    International Nuclear Information System (INIS)

    Kim, Woong Kee; Shim, Ji Hoon; Kaviany Massoud

    2016-01-01

    The analysis of such accidents (fate of the melt), requires accurate corium thermophysical properties data up to 5000 K. In addition, the initial corium melt superheat melt, determined from such properties, are key in predicting the fuel-coolant interactions (FCIs) and convection and retention of corium in accident scenarios, e.g., core-melt down corium discharge from reactor pressure vessels and spreading in external core-catcher. Due to the high temperatures, data on molten corium and its constituents are limited, so there are much data scatters and mostly extrapolations (even from solid state) have been used. Here we predict the thermophysical properties of molten UO 2 and ZrO 2 using classical molecular dynamics (MD) simulations (properties of corium are predicted using the mixture theories and UO 2 and ZrO 2 properties). The thermophysical properties (density, compressibility, heat capacity, viscosity and surface tension) of liquid UO 2 and ZrO 2 are predicted using classical molecular dynamics simulations, up to 5000 K. For atomic interactions, the CRG and the Teter potential models are found most appropriate. The liquid behavior is verified with the random motion of the constituent atoms and the pair-distribution functions, starting with the solid phase and raising the temperature to realize liquid phase. The viscosity and thermal conductivity are calculated with the Green-Kubo autocorrelation decay formulae and compared with the predictive models of Andrade and Bridgman. For liquid UO 2 , the CRG model gives satisfactory MD predictions. For ZrO 2 , the density is reliably predicted with the CRG potential model, while the compressibility and viscosity are more accurately predicted by the Teter model

  1. Macrophages in intestinal homeostasis and inflammation

    Science.gov (United States)

    Bain, Calum C; Mowat, Allan McI

    2014-01-01

    The intestine contains the largest pool of macrophages in the body which are essential for maintaining mucosal homeostasis in the face of the microbiota and the constant need for epithelial renewal but are also important components of protective immunity and are involved in the pathology of inflammatory bowel disease (IBD). However, defining the biological roles of intestinal macrophages has been impeded by problems in defining the phenotype and origins of different populations of myeloid cells in the mucosa. Here, we discuss how multiple parameters can be used in combination to discriminate between functionally distinct myeloid cells and discuss the roles of macrophages during homeostasis and how these may change when inflammation ensues. We also discuss the evidence that intestinal macrophages do not fit the current paradigm that tissue-resident macrophages are derived from embryonic precursors that self-renew in situ, but require constant replenishment by blood monocytes. We describe our recent work demonstrating that classical monocytes constantly enter the intestinal mucosa and how the environment dictates their subsequent fate. We believe that understanding the factors that drive intestinal macrophage development in the steady state and how these may change in response to pathogens or inflammation could provide important insights into the treatment of IBD. PMID:24942685

  2. The Greater Phenotypic Homeostasis of the Allopolyploid Coffea arabica Improved the Transcriptional Homeostasis Over that of Both Diploid Parents.

    Science.gov (United States)

    Bertrand, Benoît; Bardil, Amélie; Baraille, Hélène; Dussert, Stéphane; Doulbeau, Sylvie; Dubois, Emeric; Severac, Dany; Dereeper, Alexis; Etienne, Hervé

    2015-10-01

    Polyploidy impacts the diversity of plant species, giving rise to novel phenotypes and leading to ecological diversification. In order to observe adaptive and evolutionary capacities of polyploids, we compared the growth, primary metabolism and transcriptomic expression level in the leaves of the newly formed allotetraploid Coffea arabica species compared with its two diploid parental species (Coffea eugenioides and Coffea canephora), exposed to four thermal regimes (TRs; 18-14, 23-19, 28-24 and 33-29°C). The growth rate of the allopolyploid C. arabica was similar to that of C. canephora under the hottest TR and that of C. eugenioides under the coldest TR. For metabolite contents measured at the hottest TR, the allopolyploid showed similar behavior to C. canephora, the parent which tolerates higher growth temperatures in the natural environment. However, at the coldest TR, the allopolyploid displayed higher sucrose, raffinose and ABA contents than those of its two parents and similar linolenic acid leaf composition and Chl content to those of C. eugenioides. At the gene expression level, few differences between the allopolyploid and its parents were observed for studied genes linked to photosynthesis, respiration and the circadian clock, whereas genes linked to redox activity showed a greater capacity of the allopolyploid for homeostasis. Finally, we found that the overall transcriptional response to TRs of the allopolyploid was more homeostatic compared with its parents. This better transcriptional homeostasis of the allopolyploid C. arabica afforded a greater phenotypic homeostasis when faced with environments that are unsuited to the diploid parental species. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  3. Ets transcription factor GABP controls T cell homeostasis and immunity.

    Science.gov (United States)

    Luo, Chong T; Osmanbeyoglu, Hatice U; Do, Mytrang H; Bivona, Michael R; Toure, Ahmed; Kang, Davina; Xie, Yuchen; Leslie, Christina S; Li, Ming O

    2017-10-20

    Peripheral T cells are maintained in the absence of vigorous stimuli, and respond to antigenic stimulation by initiating cell cycle progression and functional differentiation. Here we show that depletion of the Ets family transcription factor GA-binding protein (GABP) in T cells impairs T-cell homeostasis. In addition, GABP is critically required for antigen-stimulated T-cell responses in vitro and in vivo. Transcriptome and genome-wide GABP-binding site analyses identify GABP direct targets encoding proteins involved in cellular redox balance and DNA replication, including the Mcm replicative helicases. These findings show that GABP has a nonredundant role in the control of T-cell homeostasis and immunity.

  4. Brain glucose sensing, counterregulation, and energy homeostasis.

    Science.gov (United States)

    Marty, Nell; Dallaporta, Michel; Thorens, Bernard

    2007-08-01

    Neuronal circuits in the central nervous system play a critical role in orchestrating the control of glucose and energy homeostasis. Glucose, beside being a nutrient, is also a signal detected by several glucose-sensing units that are located at different anatomical sites and converge to the hypothalamus to cooperate with leptin and insulin in controlling the melanocortin pathway.

  5. ALTERATIONS OF FE HOMEOSTASIS IN RAT CARDIOVASCULAR DISEASE MODELS AND ITS CONTRIBUTION TO CARDIOPULMONARY TOXICITY

    Science.gov (United States)

    Introduction: Fe homeostasis can be disrupted in human cardiovascular diseases (CVD). We addressed how dysregulation of Fe homeostasis affected the pulmonary inflammation/oxidative stress response and disease progression after exposure to Libby amphibole (LA), an asbestifonn mine...

  6. Hormonal homeostasis in lung cancer patients under combined and radiation treatment

    International Nuclear Information System (INIS)

    Zotova, I.A.; Firsova, P.P.; Matveenko, E.G.

    1984-01-01

    Radioimmunoassay of hormonal homeostasis was performed in 200 lung cancer patients before and after combined and radiation treatment and in 25 healthy subjects (controls). The study showed an increase in the basal level of hormones of pituitary - adrenal system matched by a decline in thyroid function. Adequate combined and radiation treatment brought hormone levels to normal. Hormonal disorders accompanying recurrence were identical to those registered at disease onset. In some cases, changes in hormonal homeostasis developed as early as 3-6 months prior to clinically manifest recurrences or dissemination

  7. Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model

    Energy Technology Data Exchange (ETDEWEB)

    Plaza, Cesar; Polo, Alfredo [Consejo Superior de Investigaciones Cientificas, Madrid (Spain). Inst. de Ciencias Agrarias; Gollany, Hero T. [Columbia Plateau Conservation Research Center, Pendleton, OR (United States). USDA-ARS; Baldoni, Guido; Ciavatta, Claudio [Bologna Univ. (Italy). Dept. of Agroenvironmental Sciences and Technologies

    2012-04-15

    Purpose: The CQESTR model is a process-based C model recently developed to simulate soil organic matter (SOM) dynamics and uses readily available or easily measurable input parameters. The current version of CQESTR (v. 2.0) has been validated successfully with a number of datasets from agricultural sites in North America but still needs to be tested in other geographic areas and soil types under diverse organic management systems. Materials and methods: We evaluated the predictive performance of CQESTR to simulate long-term (34 years) soil organic C (SOC) changes in a SOM-depleted European soil either unamended or amended with solid manure, liquid manure, or crop residue. Results and discussion: Measured SOC levels declined over the study period in the unamended soil, remained constant in the soil amended with crop residues, and tended to increase in the soils amended with manure, especially with solid manure. Linear regression analysis of measured SOC contents and CQESTR predictions resulted in a correlation coefficient of 0.626 (P < 0.001) and a slope and an intercept not significantly different from 1 and 0, respectively (95% confidence level). The mean squared deviation and root mean square error were relatively small. Simulated values fell within the 95% confidence interval of the measured SOC, and predicted errors were mainly associated with data scattering. Conclusions: The CQESTR model was shown to predict, with a reasonable degree of accuracy, the organic C dynamics in the soils examined. The CQESTR performance, however, could be improved by adding an additional parameter to differentiate between pre-decomposed organic amendments with varying degrees of stability. (orig.)

  8. Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices.

    Science.gov (United States)

    Belfatto, Antonella; Vidal Urbinati, Ailyn M; Ciardo, Delia; Franchi, Dorella; Cattani, Federica; Lazzari, Roberta; Jereczek-Fossa, Barbara A; Orecchia, Roberto; Baroni, Guido; Cerveri, Pietro

    2017-05-01

    Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images. We propose a macroscale model of tumor evolution based on three dynamics, namely active portion, necrotic portion, and oxygenation. The model parameters were assessed on the volume size of seven cervical cancer patients administered with 28 fractions of intensity modulated radiation therapy (IMRT) (1.8 Gy/fraction). For each patient, five Doppler ultrasound tests were acquired before, during, and after the treatment. The lesion was manually contoured by an expert physician using 4D View ® (General Electric Company - Fairfield, Connecticut, United States), which automatically provided the overall tumor volume size along with three vascularization and/or blood flow indices. Volume data only were fed to the model for training purpose, while the predicted oxygenation was compared a posteriori to the measured Doppler indices. The model was able to fit the tumor volume evolution within 8% error (range: 3-8%). A strong correlation between the intrapatient longitudinal indices from Doppler measurements and oxygen predicted by the model (about 90% or above) was found in three cases. Two patients showed an average correlation value (50-70%) and the remaining

  9. The Predictive Value of the Foot Posture Index on Dynamic Function

    DEFF Research Database (Denmark)

    Mølgaard, Carsten Møller; Olesen Gammelgaard, Christian; Nielsen, R. G.

    2008-01-01

    Keenan et. al. identified the six-item version of the Foot Posture Index (FPI) as a valid, simple and clinically useful tool. The model combines measures of the standing foot posture in multiple planes and anatomical segments. It provides an alternative to existing static clinical measures when...... dynamic measures are not feasible. Redmond et. al. found the model able to predict 41% of the variation in the complex rotation of the ankle joint, representing inversion/eversion, during midstance of walking. To our knowledge no studies have been published on the relationship between FPI and the movement...

  10. Prediction of the Arctic Oscillation in Boreal Winter by Dynamical Seasonal Forecasting Systems

    Science.gov (United States)

    Kang, Daehyun; Lee, Myong-In; Im, Jungho; Kim, Daehyun; Kim, Hye-Mi; Kang, Hyun-Suk; Schubert, Siegfried D.; Arribas, Alberto; MacLachlan, Craig

    2014-01-01

    This study assesses the skill of boreal winter Arctic Oscillation (AO) predictions with state-of-the-art dynamical ensemble prediction systems (EPSs): GloSea4, CFSv2, GEOS-5, CanCM3, CanCM4, and CM2.1. Long-term reforecasts with the EPSs are used to evaluate how well they represent the AO and to assess the skill of both deterministic and probabilistic forecasts of the AO. The reforecasts reproduce the observed changes in the large-scale patterns of the Northern Hemispheric surface temperature, upper level wind, and precipitation associated with the different phases of the AO. The results demonstrate that most EPSs improve upon persistence skill scores for lead times up to 2 months in boreal winter, suggesting some potential for skillful prediction of the AO and its associated climate anomalies at seasonal time scales. It is also found that the skill of AO forecasts during the recent period (1997-2010) is higher than that of the earlier period (1983-1996).

  11. The Commensal Microbiota Drives Immune Homeostasis

    OpenAIRE

    Arrieta, Marie-Claire; Finlay, Barton Brett

    2012-01-01

    For millions of years, microbes have coexisted with eukaryotic cells at the mucosal surfaces of vertebrates in a complex, yet usually harmonious symbiosis. An ever-expanding number of reports describe how eliminating or shifting the intestinal microbiota has profound effects on the development and functionality of the mucosal and systemic immune systems. Here, we examine some of the mechanisms by which bacterial signals affect immune homeostasis. Focusing on the strategies that microbes use t...

  12. Mitochondrial activity and dynamics changes regarding metabolism in ageing and obesity.

    Science.gov (United States)

    López-Lluch, Guillermo

    2017-03-01

    Mitochondria play an essential role in ageing and longevity. During ageing, a general deregulation of metabolism occurs, affecting molecular, cellular and physiological activities in the organism. Dysfunction of mitochondria has been associated with ageing and age-related diseases indicating their importance in the maintenance of cell homeostasis. Three major nutritional sensors, mTOR, AMPK and Sirtuins are involved in the control of mitochondrial physiology. These nutritional sensors control mitochondrial biogenesis, dynamics by regulating fusion and fission processes, and turnover through mito- and autophagy. Apart of the known factors involved in fusion, OPA1 and mitofusins, and fission, DRP1 and FIS1, emerging factors such as prohibitins and sestrins can play important functions in mitochondrial dynamics regulation. Mitochondria is also affected by sexual hormones that suffer drastic changes during ageing. The recent literature demonstrates the complex interaction between nutritional sensors and mitochondrial homeostasis in the physiology of adipose tissue and in the accumulation of fat in other organs such as muscle and liver. In this article, the role of mitochondrial homeostasis in ageing and age-dependent fat accumulation is revised. This review highlights the importance of mitochondria in the accumulation of fat during ageing and related diseases such as obesity, metabolic syndrome or type 2 diabetes mellitus. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction

    International Nuclear Information System (INIS)

    Lehtivarjo, Juuso; Tuppurainen, Kari; Hassinen, Tommi; Laatikainen, Reino; Peräkylä, Mikael

    2012-01-01

    While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein 1 H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6–17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for 1 Hα, 1 HN, 13 Cα, 13 Cβ, 13 CO and backbone 15 N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspothttp://www.uef.fi/4dspot.

  14. Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction

    Energy Technology Data Exchange (ETDEWEB)

    Lehtivarjo, Juuso, E-mail: juuso.lehtivarjo@uef.fi; Tuppurainen, Kari; Hassinen, Tommi; Laatikainen, Reino [University of Eastern Finland, School of Pharmacy (Finland); Peraekylae, Mikael [University of Eastern Finland, Institute of Biomedicine (Finland)

    2012-03-15

    While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein {sup 1}H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6-17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for {sup 1}H{alpha}, {sup 1}HN, {sup 13}C{alpha}, {sup 13}C{beta}, {sup 13}CO and backbone {sup 15}N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspothttp://www.uef.fi/4dspot.

  15. Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

    Science.gov (United States)

    Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

    2017-01-01

    The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

  16. Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network

    Directory of Open Access Journals (Sweden)

    C. H. López-Caraballo

    2015-01-01

    Full Text Available An artificial neural network (ANN based on particle swarm optimization (PSO was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term xt+6. The performance prediction was evaluated and compared with other studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO in order to obtain a new estimator of the predictions, which also allowed us to compute the uncertainties of predictions for noisy Mackey-Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level σN from 0.01 to 0.1.

  17. Hormones and the autonomic nervous system are involved in suprachiasmatic nucleus modulation of glucose homeostasis.

    Science.gov (United States)

    Ruiter, Marieke; Buijs, Ruud M; Kalsbeek, Andries

    2006-05-01

    Glucose is one of the most important energy sources for the body in general, and the brain in particular. It is essential for survival to keep glucose levels within strict boundaries. Acute disturbances of glucose homeostasis are rapidly corrected by hormonal and neuronal mechanisms. Furthermore, changes in energy expenditure associated with the light-dark cycle induce variations in the plasma glucose concentration that are more gradual. Organisms take advantage of adapting their internal physiology to the predictable daily changes in energy expenditure, because it enables them to anticipate these changes and to prevent unnecessary disturbance of homeostasis. The hypothalamic biological clock, located in the suprachiasmatic nucleus (SCN), receives light information from the eyes and transmits this information to the rest of the body to synchronize physiology to the environment. Here we review several studies providing evidence for biological clock control of the daily variation in several aspects of glucose metabolism. Although both hormones and the autonomic nervous system can stimulate glucose uptake or production by organs in the periphery, we have shown that the biological clock control of glucose metabolism mostly occurs through the autonomic nervous system. The critical involvement of the biological clock is also indicated by several studies, indicating that disturbance of the biological clock is often associated with metabolic diseases, such as obesity, diabetes mellitus and hypertension.

  18. UNRES server for physics-based coarse-grained simulations and prediction of protein structure, dynamics and thermodynamics.

    Science.gov (United States)

    Czaplewski, Cezary; Karczynska, Agnieszka; Sieradzan, Adam K; Liwo, Adam

    2018-04-30

    A server implementation of the UNRES package (http://www.unres.pl) for coarse-grained simulations of protein structures with the physics-based UNRES model, coined a name UNRES server, is presented. In contrast to most of the protein coarse-grained models, owing to its physics-based origin, the UNRES force field can be used in simulations, including those aimed at protein-structure prediction, without ancillary information from structural databases; however, the implementation includes the possibility of using restraints. Local energy minimization, canonical molecular dynamics simulations, replica exchange and multiplexed replica exchange molecular dynamics simulations can be run with the current UNRES server; the latter are suitable for protein-structure prediction. The user-supplied input includes protein sequence and, optionally, restraints from secondary-structure prediction or small x-ray scattering data, and simulation type and parameters which are selected or typed in. Oligomeric proteins, as well as those containing D-amino-acid residues and disulfide links can be treated. The output is displayed graphically (minimized structures, trajectories, final models, analysis of trajectory/ensembles); however, all output files can be downloaded by the user. The UNRES server can be freely accessed at http://unres-server.chem.ug.edu.pl.

  19. Predictive microbiology in a dynamic environment: a system theory approach.

    Science.gov (United States)

    Van Impe, J F; Nicolaï, B M; Schellekens, M; Martens, T; De Baerdemaeker, J

    1995-05-01

    The main factors influencing the microbial stability of chilled prepared food products for which there is an increased consumer interest-are temperature, pH, and water activity. Unlike the pH and the water activity, the temperature may vary extensively throughout the complete production and distribution chain. The shelf life of this kind of foods is usually limited due to spoilage by common microorganisms, and the increased risk for food pathogens. In predicting the shelf life, mathematical models are a powerful tool to increase the insight in the different subprocesses and their interactions. However, the predictive value of the sigmoidal functions reported in the literature to describe a bacterial growth curve as an explicit function of time is only guaranteed at a constant temperature within the temperature range of microbial growth. As a result, they are less appropriate in optimization studies of a whole production and distribution chain. In this paper a more general modeling approach, inspired by system theory concepts, is presented if for instance time varying temperature profiles are to be taken into account. As a case study, we discuss a recently proposed dynamic model to predict microbial growth and inactivation under time varying temperature conditions from a system theory point of view. Further, the validity of this methodology is illustrated with experimental data of Brochothrix thermosphacta and Lactobacillus plantarum. Finally, we propose some possible refinements of this model inspired by experimental results.

  20. Highly controlled nest homeostasis of honey bees helps deactivate phenolics in nectar

    Science.gov (United States)

    Liu, Fanglin; He, Jianzhong; Fu, Wenjun

    2005-06-01

    Honey bees have a highly developed nest homeostasis, for example, maintaining low CO2 levels and stable nest temperatures at 35°C.We investigate the role of nest homeostasis in deactivating phenolic compounds present in the nectar of Aloe littoralis. We show that the phenolic content in nectar was reduced (from 0.65% to 0.49%) after nectar was incubated in a nest of Apis cerana, and that it was reduced still more (from 0.65% to 0.37%) if nectar was mixed with hypopharyngeal gland proteins (HGP) of worker bees before being placed inside a nest. HGP had little effect on samples outside a nest, indicating that nest conditions are necessary for HGP to deactivate phenolics in nectar. Consequently, the highly controlled nest homeostasis of honey bees facilitates direct deactivation of phenolics in nectar, and plays a role in the action of HGP as well.

  1. Semiquantitative dynamic computed tomography to predict response to anti-platelet therapy in acute cerebral infarction

    International Nuclear Information System (INIS)

    Chokyu, K.; Shimizu, K.; Fukumoto, M.; Mori, T.; Mokudai, T.; Mori, K.

    2002-01-01

    We investigated whether dynamic computed tomography (CT) in patients with acute cerebral infarction could identify patients likely to respond to anti-platelet therapy. Seventy patients underwent semiquantitative dynamic CT within 6 h as well as cerebral angiography. All then received anti-platelet therapy with a thromboxane A2 synthetase inhibitor. Peak value (pv) and time-to-peak (tp) (time-density curves) for the Sylvian fissure were extracted from dynamic CT data and standardizing interpatient data, two indices, PV/TP index and TP index, were prepared following a standard semiquantitative manner. Both PV/TP index and TP index were effective in discriminating between 48 responders (modified Rankin scale (mRS): 0 to 2) and 22 non-responders (mRS: 3 to 5, or death: 6; both P 1.1) and non-compensated rCBF. Intermediate PV/TP values could not predict outcome. Dynamic CT prior to therapy can identify patients with acute cerebral infarction who are treatable with anti-platelet therapy alone. (orig.)

  2. A comparison between wavelet based static and dynamic neural network approaches for runoff prediction

    Science.gov (United States)

    Shoaib, Muhammad; Shamseldin, Asaad Y.; Melville, Bruce W.; Khan, Mudasser Muneer

    2016-04-01

    In order to predict runoff accurately from a rainfall event, the multilayer perceptron type of neural network models are commonly used in hydrology. Furthermore, the wavelet coupled multilayer perceptron neural network (MLPNN) models has also been found superior relative to the simple neural network models which are not coupled with wavelet. However, the MLPNN models are considered as static and memory less networks and lack the ability to examine the temporal dimension of data. Recurrent neural network models, on the other hand, have the ability to learn from the preceding conditions of the system and hence considered as dynamic models. This study for the first time explores the potential of wavelet coupled time lagged recurrent neural network (TLRNN) models for runoff prediction using rainfall data. The Discrete Wavelet Transformation (DWT) is employed in this study to decompose the input rainfall data using six of the most commonly used wavelet functions. The performance of the simple and the wavelet coupled static MLPNN models is compared with their counterpart dynamic TLRNN models. The study found that the dynamic wavelet coupled TLRNN models can be considered as alternative to the static wavelet MLPNN models. The study also investigated the effect of memory depth on the performance of static and dynamic neural network models. The memory depth refers to how much past information (lagged data) is required as it is not known a priori. The db8 wavelet function is found to yield the best results with the static MLPNN models and with the TLRNN models having small memory depths. The performance of the wavelet coupled TLRNN models with large memory depths is found insensitive to the selection of the wavelet function as all wavelet functions have similar performance.

  3. The influence of bile acids homeostasis by cryptotanshinone ...

    African Journals Online (AJOL)

    Background: Herbs might affect the homeostasis of bile acids through influence of multiple metabolic pathways of bile acids. Aim: The present study aims to investigate the inhibition of cryptotanshinone towards the glucuronidation of LCA, trying to indicate the possible influence of cryptotanshinone-containing herbs towards ...

  4. Colonic macrophage polarization in homeostasis, inflammation, and cancer

    Science.gov (United States)

    Appleyard, Caroline B.

    2016-01-01

    Our review focuses on the colonic macrophage, a monocyte-derived, tissue-resident macrophage, and the role it plays in health and disease, specifically in inflammatory conditions such as inflammatory bowel disease and cancer of the colon and rectum. We give special emphasis to macrophage polarization, or phenotype, in these different states. We focus on macrophages because they are one of the most numerous leukocytes in the colon, and because they normally contribute to homeostasis through an anti-inflammatory phenotype. However, in conditions such as inflammatory bowel disease, proinflammatory macrophages are increased in the colon and have been linked to disease severity and progression. In colorectal cancer, tumor cells may employ anti-inflammatory macrophages to promote tumor growth and dissemination, whereas proinflammatory macrophages may antagonize tumor growth. Given the key roles that this cell type plays in homeostasis, inflammation, and cancer, the colonic macrophage is an intriguing therapeutic target. As such, potential macrophage-targeting strategies are discussed. PMID:27229123

  5. The emerging role of lysosomes in copper homeostasis.

    Science.gov (United States)

    Polishchuk, Elena V; Polishchuk, Roman S

    2016-09-01

    The lysosomal system operates as a focal point where a number of important physiological processes such as endocytosis, autophagy and nutrient sensing converge. One of the key functions of lysosomes consists of regulating the metabolism/homeostasis of metals. Metal-containing components are carried to the lysosome through incoming membrane flows, while numerous transporters allow metal ions to move across the lysosome membrane. These properties enable lysosomes to direct metal fluxes to the sites where metal ions are either used by cellular components or sequestered. Copper belongs to a group of metals that are essential for the activity of vitally important enzymes, although it is toxic when in excess. Thus, copper uptake, supply and intracellular compartmentalization have to be tightly regulated. An increasing number of publications have indicated that these processes involve lysosomes. Here we review studies that reveal the expanding role of the lysosomal system as a hub for the control of Cu homeostasis and for the regulation of key Cu-dependent processes in health and disease.

  6. Cellular Links between Neuronal Activity and Energy Homeostasis.

    Science.gov (United States)

    Shetty, Pavan K; Galeffi, Francesca; Turner, Dennis A

    2012-01-01

    Neuronal activity, astrocytic responses to this activity, and energy homeostasis are linked together during baseline, conscious conditions, and short-term rapid activation (as occurs with sensory or motor function). Nervous system energy homeostasis also varies during long-term physiological conditions (i.e., development and aging) and with adaptation to pathological conditions, such as ischemia or low glucose. Neuronal activation requires increased metabolism (i.e., ATP generation) which leads initially to substrate depletion, induction of a variety of signals for enhanced astrocytic function, and increased local blood flow and substrate delivery. Energy generation (particularly in mitochondria) and use during ATP hydrolysis also lead to considerable heat generation. The local increases in blood flow noted following neuronal activation can both enhance local substrate delivery but also provides a heat sink to help cool the brain and removal of waste by-products. In this review we highlight the interactions between short-term neuronal activity and energy metabolism with an emphasis on signals and factors regulating astrocyte function and substrate supply.

  7. Local sleep homeostasis in the avian brain: convergence of sleep function in mammals and birds?

    Science.gov (United States)

    Lesku, John A; Vyssotski, Alexei L; Martinez-Gonzalez, Dolores; Wilzeck, Christiane; Rattenborg, Niels C

    2011-08-22

    The function of the brain activity that defines slow wave sleep (SWS) and rapid eye movement (REM) sleep in mammals is unknown. During SWS, the level of electroencephalogram slow wave activity (SWA or 0.5-4.5 Hz power density) increases and decreases as a function of prior time spent awake and asleep, respectively. Such dynamics occur in response to waking brain use, as SWA increases locally in brain regions used more extensively during prior wakefulness. Thus, SWA is thought to reflect homeostatically regulated processes potentially tied to maintaining optimal brain functioning. Interestingly, birds also engage in SWS and REM sleep, a similarity that arose via convergent evolution, as sleeping reptiles and amphibians do not show similar brain activity. Although birds deprived of sleep show global increases in SWA during subsequent sleep, it is unclear whether avian sleep is likewise regulated locally. Here, we provide, to our knowledge, the first electrophysiological evidence for local sleep homeostasis in the avian brain. After staying awake watching David Attenborough's The Life of Birds with only one eye, SWA and the slope of slow waves (a purported marker of synaptic strength) increased only in the hyperpallium--a primary visual processing region--neurologically connected to the stimulated eye. Asymmetries were specific to the hyperpallium, as the non-visual mesopallium showed a symmetric increase in SWA and wave slope. Thus, hypotheses for the function of mammalian SWS that rely on local sleep homeostasis may apply also to birds.

  8. Dynamic regulation of neurotransmitter specification: Relevance to nervous system homeostasis

    Science.gov (United States)

    Borodinsky, Laura N.; Belgacem, Yesser Hadj; Swapna, Immani; Sequerra, Eduardo Bouth

    2013-01-01

    During nervous system development the neurotransmitter identity changes and coexpression of several neurotransmitters is a rather generalized feature of developing neurons. In the mature nervous system, different physiological and pathological circumstances recreate this phenomenon. The rules of neurotransmitter respecification are multiple. Among them, the goal of assuring balanced excitability appears as an important driving force for the modifications in neurotransmitter phenotype expression. The functional consequences of these dynamic revisions in neurotransmitter identity span a varied range, from fine-tuning the developing neural circuit to modifications in addictive and locomotor behaviors. Current challenges include determining the mechanisms underlying neurotransmitter phenotype respecification and how they intersect with genetic programs of neuronal specialization. PMID:23270605

  9. Regulation of protein homeostasis in neurodegenerative diseases : the role of coding and non-coding genes

    NARCIS (Netherlands)

    Alvarenga Fernandes Sin, Olga; Nollen, Ellen A. A.

    Protein homeostasis is fundamental for cell function and survival, because proteins are involved in all aspects of cellular function, ranging from cell metabolism and cell division to the cell's response to environmental challenges. Protein homeostasis is tightly regulated by the synthesis, folding,

  10. An analytical model for the prediction of the dynamic response of premixed flames stabilized on a heat-conducting perforated plate

    KAUST Repository

    Kedia, Kushal S.

    2013-01-01

    The dynamic response of a premixed flame stabilized on a heat-conducting perforated plate depends critically on their coupled thermal interaction. The objective of this paper is to develop an analytical model to capture this coupling. The model predicts the mean flame base standoff distance; the flame base area, curvature and speed; and the burner plate temperature given the operating conditions; the mean velocity, temperature and equivalence ratio of the reactants; thermal conductivity and the perforation ratio of the burner. This coupled model is combined with our flame transfer function (FTF) model to predict the dynamic response of the flame to velocity perturbations. We show that modeling the thermal coupling between the flame and the burner, while accounting for the two-dimensionality of the former, is critical to predicting the dynamic response characteristics such as the overshoot in the gain curve (resonant condition) and the phase delay. Good agreement with the numerical and experimental results is demonstrated over a range of conditions. © 2012 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

  11. Application of Intelligent Dynamic Bayesian Network with Wavelet Analysis for Probabilistic Prediction of Storm Track Intensity Index

    Directory of Open Access Journals (Sweden)

    Ming Li

    2018-06-01

    Full Text Available The effective prediction of storm track (ST is greatly beneficial for analyzing the development and anomalies of mid-latitude weather systems. For the non-stationarity, nonlinearity, and uncertainty of ST intensity index (STII, a new probabilistic prediction model was proposed based on dynamic Bayesian network (DBN and wavelet analysis (WA. We introduced probability theory and graph theory for the first time to quantitatively describe the nonlinear relationship and uncertain interaction of the ST system. Then a casual prediction network (i.e., DBN was constructed through wavelet decomposition, structural learning, parameter learning, and probabilistic inference, which was used for expression of relation among predictors and probabilistic prediction of STII. The intensity prediction of the North Pacific ST with data from 1961–2010 showed that the new model was able to give more comprehensive prediction information and higher prediction accuracy and had strong generalization ability and good stability.

  12. Molecular monitoring of equine joint homeostasis

    OpenAIRE

    de Grauw, J.C.

    2010-01-01

    Chronic joint disorders are a major cause of impaired mobility and loss of quality of life in both humans and horses. Regardless of the primary insult, any joint disorder is characterized by an upset in normal joint homeostasis, the balance between tissue anabolism and catabolism that is normally maintained by resident articular cells. This upset is often fuelled by a local inflammatory response in the synovial membrane and the articular cartilage. Our current understanding of the pathogenesi...

  13. Orm family proteins mediate sphingolipid homeostasis

    DEFF Research Database (Denmark)

    Breslow, David K; Collins, Sean R; Bodenmiller, Bernd

    2010-01-01

    a conserved complex with serine palmitoyltransferase, the first and rate-limiting enzyme in sphingolipid production. We also define a regulatory pathway in which phosphorylation of Orm proteins relieves their inhibitory activity when sphingolipid production is disrupted. Changes in ORM gene expression...... or mutations to their phosphorylation sites cause dysregulation of sphingolipid metabolism. Our work identifies the Orm proteins as critical mediators of sphingolipid homeostasis and raises the possibility that sphingolipid misregulation contributes to the development of childhood asthma....

  14. Rictor/mTORC2 facilitates central regulation of energy and glucose homeostasis

    OpenAIRE

    Kocalis, Heidi E.; Hagan, Scott L.; George, Leena; Turney, Maxine K.; Siuta, Michael A.; Laryea, Gloria N.; Morris, Lindsey C.; Muglia, Louis J.; Printz, Richard L.; Stanwood, Gregg D.; Niswender, Kevin D.

    2014-01-01

    Insulin signaling in the central nervous system (CNS) regulates energy balance and peripheral glucose homeostasis. Rictor is a key regulatory/structural subunit of the mTORC2 complex and is required for hydrophobic motif site phosphorylation of Akt at serine 473. To examine the contribution of neuronal Rictor/mTORC2 signaling to CNS regulation of energy and glucose homeostasis, we utilized Cre-LoxP technology to generate mice lacking Rictor in all neurons, or in either POMC or AgRP expressing...

  15. Validation of Molecular Dynamics Simulations for Prediction of Three-Dimensional Structures of Small Proteins.

    Science.gov (United States)

    Kato, Koichi; Nakayoshi, Tomoki; Fukuyoshi, Shuichi; Kurimoto, Eiji; Oda, Akifumi

    2017-10-12

    Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton's equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10-46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10-34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

  16. Exploring the role of glucagon in glucose homeostasis

    NARCIS (Netherlands)

    Dongen, Maria Gertrud Jobina van

    2015-01-01

    The aim of this thesis was to gain further insight into the role of glucagon in glucose homeostasis in healthy volunteers and type 2 diabetes mellitus (T2DM) patients, and to explore the novel antisense glucagon receptor antagonist. Chapter 2 showed that the effect of meal replacers containing

  17. The joint power of sex and stress to modulate brain-gut-microbiota axis and intestinal barrier homeostasis: implications for irritable bowel syndrome.

    Science.gov (United States)

    Pigrau, M; Rodiño-Janeiro, B K; Casado-Bedmar, M; Lobo, B; Vicario, M; Santos, J; Alonso-Cotoner, C

    2016-04-01

    Intestinal homeostasis is a dynamic process that takes place at the interface between the lumen and the mucosa of the gastrointestinal tract, where a constant scrutiny for antigens and toxins derived from food and microorganisms is carried out by the vast gut-associated immune system. Intestinal homeostasis is preserved by the ability of the mucus layer and the mucosal barrier to keep the passage of small-sized and antigenic molecules across the epithelium highly selective. When combined and preserved, immune surveillance and barrier's selective permeability, the host capacity of preventing the development of intestinal inflammation is optimized, and viceversa. In addition, the brain-gut-microbiome axis, a multidirectional communication system that integrates distant and local regulatory networks through neural, immunological, metabolic, and hormonal signaling pathways, also regulates intestinal function. Dysfunction of the brain-gut-microbiome axis may induce the loss of gut mucosal homeostasis, leading to uncontrolled permeation of toxins and immunogenic particles, increasing the risk of appearance of intestinal inflammation, mucosal damage, and gut disorders. Irritable bowel syndrome is prevalent stress-sensitive gastrointestinal disorder that shows a female predominance. Interestingly, the role of stress, sex and gonadal hormones in the regulation of intestinal mucosal and the brain-gut-microbiome axis functioning is being increasingly recognized. We aim to critically review the evidence linking sex, and stress to intestinal barrier and brain-gut-microbiome axis dysfunction and the implications for irritable bowel syndrome. © 2015 John Wiley & Sons Ltd.

  18. A treasure trove of hypothalamic neurocircuitries governing body weight homeostasis.

    Science.gov (United States)

    Vianna, Claudia R; Coppari, Roberto

    2011-01-01

    Changes in physical activities and feeding habits have transformed the historically rare disease of obesity into a modern metabolic pandemic. Obesity occurs when energy intake exceeds energy expenditure over time. This energy imbalance significantly increases the risk for cardiovascular disease and type 2 diabetes mellitus and as such represents an enormous socioeconomic burden and health threat. To combat obesity, a better understanding of the molecular mechanisms and neurocircuitries underlying normal body weight homeostasis is required. In the 1940s, pioneering lesion experiments unveiled the importance of medial and lateral hypothalamic structures. In the 1980s and 1990s, several neuropeptides and peripheral hormones critical for appropriate feeding behavior, energy expenditure, and hence body weight homeostasis were identified. In the 2000s, results from metabolic analyses of genetically engineered mice bearing mutations only in selected neuronal groups greatly advanced our knowledge of the peripheral/brain feedback-loop modalities by which central neurons control energy balance. In this review, we will summarize these recent progresses with particular emphasis on the biochemical identities of hypothalamic neurons and molecular components underlying normal appetite, energy expenditure, and body weight homeostasis. We will also parse which of those neurons and molecules are critical components of homeostatic adaptive pathways against obesity induced by hypercaloric feeding.

  19. [Zinc signaling : a novel regulatory system on bone homeostasis, and immune and allergic responses].

    Science.gov (United States)

    Fukada, Toshiyuki; Nishida, Keigo; Yamasaki, Satoru; Hojyo, Shintaro

    2012-11-01

    Zinc (Zn) is an essential trace element that is required for proliferation, differentiation, and variety of cellular functions, and unbalanced homeostasis of Zn ion (Zn(2 + )) results in health problems such as abnormal bone formation and immunodeficiency. Recent studies have shed light on important roles of Zn(2 + )as a signaling mediator, called Zn signal. Zn(2 + )homeostasis is regulated through Zn transporters and cation channels. Advances of genetic and molecular approaches have revealed that Zn signal regulates mammalian physiology and pathogenesis. We will address that Zn signal undoubtedly contributes to our health, by highlighting it in bone homeostasis and immune regulation, and discuss that the "Zn signal axis" selectively controls intracellular signal transduction to fine-tune cellular functions.

  20. Sustained sleep fragmentation induces sleep homeostasis in mice

    KAUST Repository

    Baud, Maxime O.; Magistretti, Pierre J.; Petit, Jean Marie

    2015-01-01

    Study Objectives: Sleep fragmentation (SF) is an integral feature of sleep apnea and other prevalent sleep disorders. Although the effect of repetitive arousals on cognitive performance is well documented, the effects of long-term SF on electroencephalography (EEG) and molecular markers of sleep homeostasis remain poorly investigated. To address this question, we developed a mouse model of chronic SF and characterized its effect on EEG spectral frequencies and the expression of genes previously linked to sleep homeostasis including clock genes, heat shock proteins, and plasticity-related genes. Design: N/A. Setting: Animal sleep research laboratory. Participants : Sixty-six C57BL6/J adult mice. Interventions: Instrumental sleep disruption at a rate of 60/h during 14 days Measurements and Results: Locomotor activity and EEG were recorded during 14 days of SF followed by recovery for 2 days. Despite a dramatic number of arousals and decreased sleep bout duration, SF minimally reduced total quantity of sleep and did not significantly alter its circadian distribution. Spectral analysis during SF revealed a homeostatic drive for slow wave activity (SWA; 1-4 Hz) and other frequencies as well (4-40 Hz). Recordings during recovery revealed slow wave sleep consolidation and a transient rebound in SWA, and paradoxical sleep duration. The expression of selected genes was not induced following chronic SF. Conclusions: Chronic sleep fragmentation (SF) increased sleep pressure confirming that altered quality with preserved quantity triggers core sleep homeostasis mechanisms. However, it did not induce the expression of genes induced by sleep loss, suggesting that these molecular pathways are not sustainably activated in chronic diseases involving SF.

  1. Sustained sleep fragmentation induces sleep homeostasis in mice

    KAUST Repository

    Baud, Maxime O.

    2015-04-01

    Study Objectives: Sleep fragmentation (SF) is an integral feature of sleep apnea and other prevalent sleep disorders. Although the effect of repetitive arousals on cognitive performance is well documented, the effects of long-term SF on electroencephalography (EEG) and molecular markers of sleep homeostasis remain poorly investigated. To address this question, we developed a mouse model of chronic SF and characterized its effect on EEG spectral frequencies and the expression of genes previously linked to sleep homeostasis including clock genes, heat shock proteins, and plasticity-related genes. Design: N/A. Setting: Animal sleep research laboratory. Participants : Sixty-six C57BL6/J adult mice. Interventions: Instrumental sleep disruption at a rate of 60/h during 14 days Measurements and Results: Locomotor activity and EEG were recorded during 14 days of SF followed by recovery for 2 days. Despite a dramatic number of arousals and decreased sleep bout duration, SF minimally reduced total quantity of sleep and did not significantly alter its circadian distribution. Spectral analysis during SF revealed a homeostatic drive for slow wave activity (SWA; 1-4 Hz) and other frequencies as well (4-40 Hz). Recordings during recovery revealed slow wave sleep consolidation and a transient rebound in SWA, and paradoxical sleep duration. The expression of selected genes was not induced following chronic SF. Conclusions: Chronic sleep fragmentation (SF) increased sleep pressure confirming that altered quality with preserved quantity triggers core sleep homeostasis mechanisms. However, it did not induce the expression of genes induced by sleep loss, suggesting that these molecular pathways are not sustainably activated in chronic diseases involving SF.

  2. Rictor/mTORC2 facilitates central regulation of energy and glucose homeostasis

    Science.gov (United States)

    Kocalis, Heidi E.; Hagan, Scott L.; George, Leena; Turney, Maxine K.; Siuta, Michael A.; Laryea, Gloria N.; Morris, Lindsey C.; Muglia, Louis J.; Printz, Richard L.; Stanwood, Gregg D.; Niswender, Kevin D.

    2014-01-01

    Insulin signaling in the central nervous system (CNS) regulates energy balance and peripheral glucose homeostasis. Rictor is a key regulatory/structural subunit of the mTORC2 complex and is required for hydrophobic motif site phosphorylation of Akt at serine 473. To examine the contribution of neuronal Rictor/mTORC2 signaling to CNS regulation of energy and glucose homeostasis, we utilized Cre-LoxP technology to generate mice lacking Rictor in all neurons, or in either POMC or AgRP expressing neurons. Rictor deletion in all neurons led to increased fat mass and adiposity, glucose intolerance and behavioral leptin resistance. Disrupting Rictor in POMC neurons also caused obesity and hyperphagia, fasting hyperglycemia and pronounced glucose intolerance. AgRP neuron specific deletion did not impact energy balance but led to mild glucose intolerance. Collectively, we show that Rictor/mTORC2 signaling, especially in POMC-expressing neurons, is important for central regulation of energy and glucose homeostasis. PMID:24944899

  3. Rictor/mTORC2 facilitates central regulation of energy and glucose homeostasis.

    Science.gov (United States)

    Kocalis, Heidi E; Hagan, Scott L; George, Leena; Turney, Maxine K; Siuta, Michael A; Laryea, Gloria N; Morris, Lindsey C; Muglia, Louis J; Printz, Richard L; Stanwood, Gregg D; Niswender, Kevin D

    2014-07-01

    Insulin signaling in the central nervous system (CNS) regulates energy balance and peripheral glucose homeostasis. Rictor is a key regulatory/structural subunit of the mTORC2 complex and is required for hydrophobic motif site phosphorylation of Akt at serine 473. To examine the contribution of neuronal Rictor/mTORC2 signaling to CNS regulation of energy and glucose homeostasis, we utilized Cre-LoxP technology to generate mice lacking Rictor in all neurons, or in either POMC or AgRP expressing neurons. Rictor deletion in all neurons led to increased fat mass and adiposity, glucose intolerance and behavioral leptin resistance. Disrupting Rictor in POMC neurons also caused obesity and hyperphagia, fasting hyperglycemia and pronounced glucose intolerance. AgRP neuron specific deletion did not impact energy balance but led to mild glucose intolerance. Collectively, we show that Rictor/mTORC2 signaling, especially in POMC-expressing neurons, is important for central regulation of energy and glucose homeostasis.

  4. Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans.

    Science.gov (United States)

    Juneja, Vijay K; Mishra, Abhinav; Pradhan, Abani K

    2018-02-01

    Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol-egg yolk-polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination ( R 2 ), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R 2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between -0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

  5. Mathematical modeling of antibody drug conjugates with the target and tubulin dynamics to predict AUC.

    Science.gov (United States)

    Byun, Jong Hyuk; Jung, Il Hyo

    2018-04-14

    Antibody drug conjugates (ADCs)are one of the most recently developed chemotherapeutics to treat some types of tumor cells. They consist of monoclonal antibodies (mAbs), linkers, and potent cytotoxic drugs. Unlike common chemotherapies, ADCs combine selectively with a target at the surface of the tumor cell, and a potent cytotoxic drug (payload) effectively prevents microtubule polymerization. In this work, we construct an ADC model that considers both the target of antibodies and the receptor (tubulin) of the cytotoxic payloads. The model is simulated with brentuximab vedotin, one of ADCs, and used to investigate the pharmacokinetic (PK) characteristics of ADCs in vivo. It also predicts area under the curve (AUC) of ADCs and the payloads by identifying the half-life. The results show that dynamical behaviors fairly coincide with the observed data and half-life and capture AUC. Thus, the model can be used for estimating some parameters, fitting experimental observations, predicting AUC, and exploring various dynamical behaviors of the target and the receptor. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Calcium homeostasis during pregnancy and lactation: role of vitamin ...

    African Journals Online (AJOL)

    Arun Kumar Agnihotri

    skinned but also even Caucasian women tend to go into vitamin D deficiency during ... homeostasis in this phase of life is still controversial. Studies are .... calcium balance in lactating women. .... work on vitamin D. In general these authors.

  7. Paneth cells, antimicrobial peptides and maintenance of intestinal homeostasis.

    Science.gov (United States)

    Bevins, Charles L; Salzman, Nita H

    2011-05-01

    Building and maintaining a homeostatic relationship between a host and its colonizing microbiota entails ongoing complex interactions between the host and the microorganisms. The mucosal immune system, including epithelial cells, plays an essential part in negotiating this equilibrium. Paneth cells (specialized cells in the epithelium of the small intestine) are an important source of antimicrobial peptides in the intestine. These cells have become the focus of investigations that explore the mechanisms of host-microorganism homeostasis in the small intestine and its collapse in the processes of infection and chronic inflammation. In this Review, we provide an overview of the intestinal microbiota and describe the cell biology of Paneth cells, emphasizing the composition of their secretions and the roles of these cells in intestinal host defence and homeostasis. We also highlight the implications of Paneth cell dysfunction in susceptibility to chronic inflammatory bowel disease.

  8. Modulation of intestinal sulfur assimilation metabolism regulates iron homeostasis

    Science.gov (United States)

    Hudson, Benjamin H.; Hale, Andrew T.; Irving, Ryan P.; Li, Shenglan; York, John D.

    2018-01-01

    Sulfur assimilation is an evolutionarily conserved pathway that plays an essential role in cellular and metabolic processes, including sulfation, amino acid biosynthesis, and organismal development. We report that loss of a key enzymatic component of the pathway, bisphosphate 3′-nucleotidase (Bpnt1), in mice, both whole animal and intestine-specific, leads to iron-deficiency anemia. Analysis of mutant enterocytes demonstrates that modulation of their substrate 3′-phosphoadenosine 5′-phosphate (PAP) influences levels of key iron homeostasis factors involved in dietary iron reduction, import and transport, that in part mimic those reported for the loss of hypoxic-induced transcription factor, HIF-2α. Our studies define a genetic basis for iron-deficiency anemia, a molecular approach for rescuing loss of nucleotidase function, and an unanticipated link between nucleotide hydrolysis in the sulfur assimilation pathway and iron homeostasis. PMID:29507250

  9. Origins and Hallmarks of Macrophages: Development, Homeostasis, and Disease

    Science.gov (United States)

    Wynn, Thomas A.; Chawla, Ajay; Pollard, Jeffrey W.

    2013-01-01

    Preface Macrophages the most plastic cells of the hematopoietic system are found in all tissues and exhibit great functional diversity. They have roles in development, homeostasis, tissue repair, and immunity. While anatomically distinct, resident tissue macrophages exhibit different transcriptional profiles, and functional capabilities, they are all required for the maintenance of homeostasis. However, these reparative and homeostatic functions can be subverted by chronic insults, resulting in a causal association of macrophages with disease states. In this review, we discuss how macrophages regulate normal physiology and development and provide several examples of their pathophysiologic roles in disease. We define the “hallmarks” of macrophages performing particular functions, taking into account novel insights into the diversity of their lineages, identity, and regulation. This diversity is essential to understand because macrophages have emerged as important therapeutic targets in many important human diseases. PMID:23619691

  10. Rigid-Plastic Approximations for Predicting Plastic Deformation of Cylindrical Shells Subject to Dynamic Loading

    Directory of Open Access Journals (Sweden)

    Michelle S. Hoo Fatt

    1996-01-01

    Full Text Available A theoretical approach was developed for predicting the plastic deformation of a cylindrical shell subject to asymmetric dynamic loads. The plastic deformation of the leading generator of the shell is found by solving for the transverse deflections of a rigid-plastic beam/string-on-foundation. The axial bending moment and tensile force in the beam/string are equivalent to the longitudinal bending moments and membrane forces of the shell, while the plastic foundation force is equivalent to the shell circumferential bending moment and membrane resistances. Closed-form solutions for the transient and final deformation profile of an impulsive loaded shell when it is in a “string” state were derived using the eigenfunction expansion method. These results were compared to DYNA 3D predictions. The analytical predictions of the transient shell and final centerline deflections were within 25% of the DYNA 3D results.

  11. Salt stress induced ion accumulation, ion homeostasis, membrane ...

    African Journals Online (AJOL)

    Salt stress induced ion accumulation, ion homeostasis, membrane injury and sugar contents in salt-sensitive rice ( Oryza sativa L. spp. indica ) roots under isoosmotic conditions. ... The accumulation of sugars in PT1 roots may be a primary salt-defense mechanism and may function as an osmotic control. Key words: ...

  12. Regulation of calcium homeostasis in activated human neutrophils ...

    African Journals Online (AJOL)

    Objectives. The objectives of the current study were to: (i) present an integrated model for the restoration of calcium homeostasis in activated human neutrophils based on current knowledge and recent research; and (ii) identify potential targets for the modulation of calcium fluxes in activated neutrophils based on this model ...

  13. Predicting the elastic properties of double-walled carbon nanotubes by molecular dynamics simulation

    International Nuclear Information System (INIS)

    Zhang Chenli; Shen Huishen

    2008-01-01

    Molecular dynamics simulation is performed on a double-walled carbon nanotube (DWCNT) to predict its elastic properties based on a double-walled shear deformable shell model. By direct buckling measurement, we present here a method for uniquely determining the effective wall thickness for the shell model. Accounting for two different kinds of DWCNTs by adding an inner or outer tube to a fiducial tube, the mechanical properties of DWCNTs are carefully investigated as compared with those of the fiducial tube. It is found that the predicted values of Young's and shear moduli depend strongly on the construction and helicity of DWCNTs, while the dependence on nanotube length is relatively small. The results also confirm that the temperature variation has a significant effect on the elastic properties of DWCNTs

  14. WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

    Science.gov (United States)

    Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

    2013-12-01

    Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before

  15. Nonlinear joint models for individual dynamic prediction of risk of death using Hamiltonian Monte Carlo: application to metastatic prostate cancer

    Directory of Open Access Journals (Sweden)

    Solène Desmée

    2017-07-01

    Full Text Available Abstract Background Joint models of longitudinal and time-to-event data are increasingly used to perform individual dynamic prediction of a risk of event. However the difficulty to perform inference in nonlinear models and to calculate the distribution of individual parameters has long limited this approach to linear mixed-effect models for the longitudinal part. Here we use a Bayesian algorithm and a nonlinear joint model to calculate individual dynamic predictions. We apply this approach to predict the risk of death in metastatic castration-resistant prostate cancer (mCRPC patients with frequent Prostate-Specific Antigen (PSA measurements. Methods A joint model is built using a large population of 400 mCRPC patients where PSA kinetics is described by a biexponential function and the hazard function is a PSA-dependent function. Using Hamiltonian Monte Carlo algorithm implemented in Stan software and the estimated population parameters in this population as priors, the a posteriori distribution of the hazard function is computed for a new patient knowing his PSA measurements until a given landmark time. Time-dependent area under the ROC curve (AUC and Brier score are derived to assess discrimination and calibration of the model predictions, first on 200 simulated patients and then on 196 real patients that are not included to build the model. Results Satisfying coverage probabilities of Monte Carlo prediction intervals are obtained for longitudinal and hazard functions. Individual dynamic predictions provide good predictive performances for landmark times larger than 12 months and horizon time of up to 18 months for both simulated and real data. Conclusions As nonlinear joint models can characterize the kinetics of biomarkers and their link with a time-to-event, this approach could be useful to improve patient’s follow-up and the early detection of most at risk patients.

  16. Cortical delta-opioid receptors potentiate K+ homeostasis during anoxia and oxygen-glucose deprivation.

    Science.gov (United States)

    Chao, Dongman; Donnelly, David F; Feng, Yin; Bazzy-Asaad, Alia; Xia, Ying

    2007-02-01

    Central neurons are extremely vulnerable to hypoxic/ischemic insult, which is a major cause of neurologic morbidity and mortality as a consequence of neuronal dysfunction and death. Our recent work has shown that delta-opioid receptor (DOR) is neuroprotective against hypoxic and excitotoxic stress, although the underlying mechanisms remain unclear. Because hypoxia/ischemia disrupts ionic homeostasis with an increase in extracellular K(+), which plays a role in neuronal death, we asked whether DOR activation preserves K(+) homeostasis during hypoxic/ischemic stress. To test this hypothesis, extracellular recordings with K(+)-sensitive microelectrodes were performed in mouse cortical slices under anoxia or oxygen-glucose deprivation (OGD). The main findings in this study are that (1) DOR activation with [D-Ala(2), D-Leu(5)]-enkephalinamide attenuated the anoxia- and OGD-induced increase in extracellular K(+) and decrease in DC potential in cortical slices; (2) DOR inhibition with naltrindole, a DOR antagonist, completely abolished the DOR-mediated prevention of increase in extracellular K(+) and decrease in DC potential; (3) inhibition of protein kinase A (PKA) with N-(2-[p-bromocinnamylamino]-ethyl)-5-isoquinolinesulfonamide dihydrochloride had no effect on the DOR protection; and (4) inhibition of protein kinase C (PKC) with chelerythrine chloride reduced the DOR protection, whereas the PKC activator (phorbol 12-myristate 13-acetate) mimicked the effect of DOR activation on K(+) homeostasis. These data suggest that activation of DOR protects the cortex against anoxia- or ODG-induced derangement of potassium homeostasis, and this protection occurs via a PKC-dependent and PKA-independent pathway. We conclude that an important aspect of DOR-mediated neuroprotection is its early action against derangement of K(+) homeostasis during anoxia or ischemia.

  17. Serotonin 2C receptors in pro-opiomelanocortin neurons regulate energy and glucose homeostasis.

    Science.gov (United States)

    Berglund, Eric D; Liu, Chen; Sohn, Jong-Woo; Liu, Tiemin; Kim, Mi Hwa; Lee, Charlotte E; Vianna, Claudia R; Williams, Kevin W; Xu, Yong; Elmquist, Joel K

    2013-12-01

    Energy and glucose homeostasis are regulated by central serotonin 2C receptors. These receptors are attractive pharmacological targets for the treatment of obesity; however, the identity of the serotonin 2C receptor-expressing neurons that mediate the effects of serotonin and serotonin 2C receptor agonists on energy and glucose homeostasis are unknown. Here, we show that mice lacking serotonin 2C receptors (Htr2c) specifically in pro-opiomelanocortin (POMC) neurons had normal body weight but developed glucoregulatory defects including hyperinsulinemia, hyperglucagonemia, hyperglycemia, and insulin resistance. Moreover, these mice did not show anorectic responses to serotonergic agents that suppress appetite and developed hyperphagia and obesity when they were fed a high-fat/high-sugar diet. A requirement of serotonin 2C receptors in POMC neurons for the maintenance of normal energy and glucose homeostasis was further demonstrated when Htr2c loss was induced in POMC neurons in adult mice using a tamoxifen-inducible POMC-cre system. These data demonstrate that serotonin 2C receptor-expressing POMC neurons are required to control energy and glucose homeostasis and implicate POMC neurons as the target for the effect of serotonin 2C receptor agonists on weight-loss induction and improved glycemic control.

  18. Novel modeling of task versus rest brain state predictability using a dynamic time warping spectrum: comparisons and contrasts with other standard measures of brain dynamics

    Directory of Open Access Journals (Sweden)

    Martin eDinov

    2016-05-01

    Full Text Available Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches and the sum squared error (SSE from a multilayer perceptron (MLP prediction of the EEG timeseries, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach.

  19. Dynamic Travel Time Prediction Models for Buses Using Only GPS Data

    Directory of Open Access Journals (Sweden)

    Wei Fan

    2015-01-01

    Full Text Available Providing real-time and accurate travel time information of transit vehicles can be very helpful as it assists passengers in planning their trips to minimize waiting times. The purpose of this research is to develop and compare dynamic travel time prediction models which can provide accurate prediction of bus travel time in order to give real-time information at a given downstream bus stop using only global positioning system (GPS data. Historical Average (HA, Kalman Filtering (KF and Artificial Neural Network (ANN models are considered and developed in this paper. A case has been studied by making use of the three models. Promising results are obtained from the case study, indicating that the models can be used to implement an Advanced Public Transport System. The implementation of this system could assist transit operators in improving the reliability of bus services, thus attracting more travelers to transit vehicles and helping relieve congestion. The performances of the three models were assessed and compared with each other under two criteria: overall prediction accuracy and robustness. It was shown that the ANN outperformed the other two models in both aspects. In conclusion, it is shown that bus travel time information can be reasonably provided using only arrival and departure time information at stops even in the absence of traffic-stream data.

  20. nfluence of antidepressants on glucose homeostasis : effects and mechanisms

    NARCIS (Netherlands)

    Derijks, H.J.

    2009-01-01

    Depression has shown to be a common morbidity in patients with diabetes mellitus and comorbid depression in diabetes mellitus patients is frequently treated with antidepressants. It has been postulated that antidepressants may interfere with glucose homeostasis and that the interference of

  1. Asiatic acid influences glucose homeostasis in P. berghei murine ...

    African Journals Online (AJOL)

    Background: Glucose homeostasis derangement is a common pathophysiology of malaria whose aetiology is still controversial. The Plasmodium parasite, immunological and inflammatory responses, as well as chemotherapeutics currently used cause hypoglycaemia in malaria. Anti-parasitic and anti-disease drugs are ...

  2. Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

    Science.gov (United States)

    Medvigy, David; Moorcroft, Paul R

    2012-01-19

    Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

  3. Setting sail for glucose homeostasis with the AKAP150-PP2B-anchor.

    Science.gov (United States)

    Teo, Adrian Kee Keong; Kulkarni, Rohit N

    2012-10-17

    Glucose-stimulated insulin secretion, controlled by multiple protein phosphorylation events, is critical for the regulation of glucose homeostasis. Protein kinase A (PKA) is known to play a role in β cell physiology, but the role of its anchoring protein is not fully understood. Hinke et al (2012) illustrate the significance of A-kinase anchoring protein 150 in tethering protein phosphatase 2B to mediate nutrient-stimulated insulin secretion and thus modulate glucose homeostasis.

  4. TRPV5, the gateway to Ca2+ homeostasis.

    NARCIS (Netherlands)

    Mensenkamp, A.R.; Hoenderop, J.G.J.; Bindels, R.J.M.

    2007-01-01

    Ca2+ homeostasis in the body is tightly controlled, and is a balance between absorption in the intestine, excretion via the urine, and exchange from bone. Recently, the epithelial Ca2+ channel (TRPV5) has been identified as the gene responsible for the Ca2+ influx in epithelial cells of the renal

  5. The influence of bile acids homeostasis by cryptotanshinone ...

    African Journals Online (AJOL)

    The homeostasis of bile acids can be tightly regulated through feed-back and feed-forward regula- tion pathways. Bile acids exert their toxicity towards cells at high concentrations, and the accumulation of bile acids can induce the severe damage towards liver cells 2. Bile acids have been reported to induce cell injury.

  6. Characterization of the glass transition of water predicted by molecular dynamics simulations using nonpolarizable intermolecular potentials.

    Science.gov (United States)

    Kreck, Cara A; Mancera, Ricardo L

    2014-02-20

    Molecular dynamics simulations allow detailed study of the experimentally inaccessible liquid state of supercooled water below its homogeneous nucleation temperature and the characterization of the glass transition. Simple, nonpolarizable intermolecular potentials are commonly used in classical molecular dynamics simulations of water and aqueous systems due to their lower computational cost and their ability to reproduce a wide range of properties. Because the quality of these predictions varies between the potentials, the predicted glass transition of water is likely to be influenced by the choice of potential. We have thus conducted an extensive comparative investigation of various three-, four-, five-, and six-point water potentials in both the NPT and NVT ensembles. The T(g) predicted from NPT simulations is strongly correlated with the temperature of minimum density, whereas the maximum in the heat capacity plot corresponds to the minimum in the thermal expansion coefficient. In the NVT ensemble, these points are instead related to the maximum in the internal pressure and the minimum of its derivative, respectively. A detailed analysis of the hydrogen-bonding properties at the glass transition reveals that the extent of hydrogen-bonds lost upon the melting of the glassy state is related to the height of the heat capacity peak and varies between water potentials.

  7. Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.

    Directory of Open Access Journals (Sweden)

    Rahul Karnik

    Full Text Available The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs.

  8. Disruption of gut homeostasis by opioids accelerates HIV disease progression

    Directory of Open Access Journals (Sweden)

    Jingjing eMeng

    2015-06-01

    Full Text Available Cumulative studies during the past 30 years have established the correlation between opioid abuse and human immunodeficiency virus (HIV infection. Further studies also demonstrate that opioid addiction is associated with faster progression to AIDS in patients. Recently, it was revealed that disruption of gut homeostasis and subsequent microbial translocation play important roles in pathological activation of the immune system during HIV infection and contributes to accelerated disease progression. Similarly, opioids have been shown to modulate gut immunity and induce gut bacterial translocation. This review will explore the mechanisms by which opioids accelerate HIV disease progression by disrupting gut homeostasis. Better understanding of these mechanisms will facilitate the search for new therapeutic interventions to treat HIV infection especially in opioid abusing population.

  9. Central insulin and leptin-mediated autonomic control of glucose homeostasis.

    Science.gov (United States)

    Marino, Joseph S; Xu, Yong; Hill, Jennifer W

    2011-07-01

    Largely as a result of rising obesity rates, the incidence of type 2 diabetes is escalating rapidly. Type 2 diabetes results from multi-organ dysfunctional glucose metabolism. Recent publications have highlighted hypothalamic insulin- and adipokine-sensing as a major determinant of peripheral glucose and insulin responsiveness. The preponderance of evidence indicates that the brain is the master regulator of glucose homeostasis, and that hypothalamic insulin and leptin signaling in particular play a crucial role in the development of insulin resistance. This review discusses the neuronal crosstalk between the hypothalamus, autonomic nervous system, and tissues associated with the pathogenesis of type 2 diabetes, and how hypothalamic insulin and leptin signaling are integral to maintaining normal glucose homeostasis. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

    Science.gov (United States)

    Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

    2017-01-01

    Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

  11. Dynamic Shaping of the Defensive Peripersonal Space through Predictive Motor Mechanisms: When the "Near" Becomes "Far".

    Science.gov (United States)

    Bisio, Ambra; Garbarini, Francesca; Biggio, Monica; Fossataro, Carlotta; Ruggeri, Piero; Bove, Marco

    2017-03-01

    The hand blink reflex is a subcortical defensive response, known to dramatically increase when the stimulated hand is statically positioned inside the defensive peripersonal space (DPPS) of the face. Here, we tested in a group of healthy human subjects the hand blink reflex in dynamic conditions, investigating whether the direction of the hand movements (up-to/down-from the face) could modulate it. We found that, on equal hand position, the response enhancement was present only when the hand approached to (and not receded from) the DPPS of the face. This means that, when the hand is close to the face but the subject is planning to move the hand down, the predictive motor system can anticipate the consequence of the movement: the "near" becomes "far." We found similar results both in passive movement condition, when only afferent (visual and proprioceptive) information can be used to estimate the final state of the system, and in motor imagery task, when only efferent (intentional) information is available to predict the consequences of the movement. All these findings provide evidence that the DPPS is dynamically shaped by predictive mechanisms run by the motor system and based on the integration of feedforward and sensory feedback signals. SIGNIFICANCE STATEMENT The defensive peripersonal space (DPPS) has a crucial role for survival, and its modulation is fundamental when we interact with the environment, as when we move our arms. Here, we focused on a defensive response, the hand blink reflex, known to increase when a static hand is stimulated inside the DPPS of the face. We tested the hand blink reflex in dynamic conditions (voluntary, passive, and imagined movements) and we found that, on equal hand position, the response enhancement was present only when the hand approached to (and not receded from) the DPPS of the face. This suggests that, through the integration of efferent and afferent signals, the safety boundary around the body is continuously shaped by

  12. Control of Homeostasis and Dendritic Cell Survival by the GTPase RhoA

    DEFF Research Database (Denmark)

    Li, Shuai; Dislich, Bastian; Brakebusch, Cord H

    2015-01-01

    11b(-)CD8(+) and CD11b(+)Esam(hi) DC subsets, whereas CD11b(+)Esam(lo) DCs were not affected in conditional RhoA-deficient mice. Proteome analyses revealed a defective prosurvival pathway via PI3K/protein kinase B (Akt1)/Bcl-2-associated death promoter in the absence of RhoA. Taken together, our...... findings identify RhoA as a central regulator of DC homeostasis, and its deletion decreases DC numbers below critical thresholds for immune protection and homeostasis, causing aberrant compensatory DC proliferation....

  13. Bone morphogenetic proteins in inflammation, glucose homeostasis and adipose tissue energy metabolism

    DEFF Research Database (Denmark)

    Grgurevic, Lovorka; Christensen, Gitte Lund; Schulz, Tim J

    2016-01-01

    implicated in pancreas development as well as control of adult glucose homeostasis. Lastly, we review the recently recognized role of BMPs in brown adipose tissue formation and their consequences for energy expenditure and adiposity. In summary, BMPs play a pivotal role in metabolism beyond their role...... homeostasis (anaemia, hemochromatosis) and oxidative damage. The second and third parts of this review focus on BMPs in the development of metabolic pathologies such as type-2 diabetes mellitus and obesity. The pancreatic beta cells are the sole source of the hormone insulin and BMPs have recently been...

  14. De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.

    Science.gov (United States)

    Lee, Juyong; Lee, Jinhyuk; Sasaki, Takeshi N; Sasai, Masaki; Seok, Chaok; Lee, Jooyoung

    2011-08-01

    Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods. Copyright © 2011 Wiley-Liss, Inc.

  15. Postradiation immunoendocrine homeostasis in patients with cancer of the buccal mucosa

    International Nuclear Information System (INIS)

    Savina, N.P.; Pavlov, A.S.; Lyasko, L.I.

    1993-01-01

    A follow-up of the immune and endocrine homeostasis was carried out for 1 to 3 years in 80 patients with cancer of the buccal mucose (T 1-2 , N 0 , M 0 ), exposed to intratissue therapy with 252 Cf and 60 Co alone and in combination with longdistance gamma-beam therapy. The status of the postradiation immune and endocrine homeostasis was found to depend on the dose load of the critical organs, the thymus and hypophysis. Complete recovery of the parameters was obsered in the patients administered lower irradiation dose, whereas after higher doses of irradiation no complete recovery was observed in remote periods after radiotherapy

  16. Signalling from the periphery to the brain that regulates energy homeostasis.

    Science.gov (United States)

    Kim, Ki-Suk; Seeley, Randy J; Sandoval, Darleen A

    2018-04-01

    The CNS regulates body weight; however, we still lack a clear understanding of what drives decisions about when, how much and what to eat. A vast array of peripheral signals provides information to the CNS regarding fluctuations in energy status. The CNS then integrates this information to influence acute feeding behaviour and long-term energy homeostasis. Previous paradigms have delegated the control of long-term energy homeostasis to the hypothalamus and short-term changes in feeding behaviour to the hindbrain. However, recent studies have identified target hindbrain neurocircuitry that integrates the orchestration of individual bouts of ingestion with the long-term regulation of energy balance.

  17. Combined Molecular Dynamics Simulation-Molecular-Thermodynamic Theory Framework for Predicting Surface Tensions.

    Science.gov (United States)

    Sresht, Vishnu; Lewandowski, Eric P; Blankschtein, Daniel; Jusufi, Arben

    2017-08-22

    A molecular modeling approach is presented with a focus on quantitative predictions of the surface tension of aqueous surfactant solutions. The approach combines classical Molecular Dynamics (MD) simulations with a molecular-thermodynamic theory (MTT) [ Y. J. Nikas, S. Puvvada, D. Blankschtein, Langmuir 1992 , 8 , 2680 ]. The MD component is used to calculate thermodynamic and molecular parameters that are needed in the MTT model to determine the surface tension isotherm. The MD/MTT approach provides the important link between the surfactant bulk concentration, the experimental control parameter, and the surfactant surface concentration, the MD control parameter. We demonstrate the capability of the MD/MTT modeling approach on nonionic alkyl polyethylene glycol surfactants at the air-water interface and observe reasonable agreement of the predicted surface tensions and the experimental surface tension data over a wide range of surfactant concentrations below the critical micelle concentration. Our modeling approach can be extended to ionic surfactants and their mixtures with both ionic and nonionic surfactants at liquid-liquid interfaces.

  18. Can foot anthropometric measurements predict dynamic plantar surface contact area?

    Directory of Open Access Journals (Sweden)

    Collins Natalie

    2009-10-01

    Full Text Available Abstract Background Previous studies have suggested that increased plantar surface area, associated with pes planus, is a risk factor for the development of lower extremity overuse injuries. The intent of this study was to determine if a single or combination of foot anthropometric measures could be used to predict plantar surface area. Methods Six foot measurements were collected on 155 subjects (97 females, 58 males, mean age 24.5 ± 3.5 years. The measurements as well as one ratio were entered into a stepwise regression analysis to determine the optimal set of measurements associated with total plantar contact area either including or excluding the toe region. The predicted values were used to calculate plantar surface area and were compared to the actual values obtained dynamically using a pressure sensor platform. Results A three variable model was found to describe the relationship between the foot measures/ratio and total plantar contact area (R2 = 0.77, p R2 = 0.76, p Conclusion The results of this study indicate that the clinician can use a combination of simple, reliable, and time efficient foot anthropometric measurements to explain over 75% of the plantar surface contact area, either including or excluding the toe region.

  19. Dynamic Prediction of Power Storage and Delivery by Data-Based Fractional Differential Models of a Lithium Iron Phosphate Battery

    Directory of Open Access Journals (Sweden)

    Yunfeng Jiang

    2016-07-01

    Full Text Available A fractional derivative system identification approach for modeling battery dynamics is presented in this paper, where fractional derivatives are applied to approximate non-linear dynamic behavior of a battery system. The least squares-based state-variable filter (LSSVF method commonly used in the identification of continuous-time models is extended to allow the estimation of fractional derivative coefficents and parameters of the battery models by monitoring a charge/discharge demand signal and a power storage/delivery signal. In particular, the model is combined by individual fractional differential models (FDMs, where the parameters can be estimated by a least-squares algorithm. Based on experimental data, it is illustrated how the fractional derivative model can be utilized to predict the dynamics of the energy storage and delivery of a lithium iron phosphate battery (LiFePO 4 in real-time. The results indicate that a FDM can accurately capture the dynamics of the energy storage and delivery of the battery over a large operating range of the battery. It is also shown that the fractional derivative model exhibits improvements on prediction performance compared to standard integer derivative model, which in beneficial for a battery management system.

  20. Challenging homeostasis to define biomarkers for nutrition related health

    NARCIS (Netherlands)

    Ommen, van B.; Keijer, J.; Heil, S.G.; Kaput, J.

    2009-01-01

    A primary goal of nutrition research is to optimize health and prevent or delay disease. Biomarkers to quantify health optimization are needed since many if not most biomarkers are developed for diseases. Quantifying normal homeostasis and developing validated biomarkers are formidable tasks because

  1. Renal renin secretion as regulator of body fluid homeostasis

    DEFF Research Database (Denmark)

    Damkjær, Mads; Isaksson, Gustaf L; Stubbe, Jane

    2013-01-01

    The renin-angiotensin system is essential for body fluid homeostasis and blood pressure regulation. This review focuses on the homeostatic regulation of the secretion of active renin in the kidney, primarily in humans. Under physiological conditions, renin secretion is determined mainly by sodium...

  2. Activating transcription factor 3 regulates immune and metabolic homeostasis

    Czech Academy of Sciences Publication Activity Database

    Ryneš, J.; Donohoe, C. D.; Frommolt, P.; Brodesser, S.; Jindra, Marek; Uhlířová, M.

    2012-01-01

    Roč. 32, č. 19 (2012), s. 3949-3962 ISSN 0270-7306 R&D Projects: GA ČR(CZ) GD204/09/H058 Institutional support: RVO:60077344 Keywords : metabolic homeostasis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.372, year: 2012

  3. Multilevel control of glucose homeostasis by adenylyl cyclase 8

    NARCIS (Netherlands)

    Raoux, Matthieu; Vacher, Pierre; Papin, Julien; Picard, Alexandre; Kostrzewa, Elzbieta; Devin, Anne; Gaitan, Julien; Limon, Isabelle; Kas, Martien J.; Magnan, Christophe; Lang, Jochen

    2015-01-01

    Aims/hypothesis: Nutrient homeostasis requires integration of signals generated by glucose metabolism and hormones. Expression of the calcium-stimulated adenylyl cyclase ADCY8 is regulated by glucose and the enzyme is capable of integrating signals from multiple pathways. It may thus have an

  4. Integrative studies on cartilage tissue engineering and joint homeostasis

    NARCIS (Netherlands)

    Rutgers, M.

    2014-01-01

    The impact of cartilage injury to the joint is often larger than the initial clinical symptoms suggest. Through an alteration in joint homeostasis and biomechanical loading, cartilage lesions may accelerate osteoarthritis onset. Although good clinical results are achieved in patients treated by the

  5. Atmospheric Convective Organization: Self-Organized Criticality or Homeostasis?

    Science.gov (United States)

    Yano, Jun-Ichi

    2015-04-01

    Atmospheric convection has a tendency organized on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden-Julian oscillation. The present talk examines two major possible mechanisms of self-organization identified in wider literature from a phenomenological thermodynamic point of view by analysing a planetary-scale cloud-resolving model simulation. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with the increasing column-integrated water, reminiscence of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as cloud-resolving model (CRM) experiments give mixed results. A satellite data analysis suggests self-organized criticality. Some observational data as well as CRM experiments support homeostasis. Other analyses point to a combination of these two interpretations. In this study, a CRM experiment over a planetary-scale domain with a constant sea-surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms are further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes. These self-organization mechanisms are most likely be best theoretically understood by the energy cycle of the convective systems consisting of the kinetic energy and the cloud-work function. The author has already investigated the behavior of this

  6. Tuning of redox regulatory mechanisms, reactive oxygen species and redox homeostasis under salinity stress

    Directory of Open Access Journals (Sweden)

    Hossain eSazzad

    2016-05-01

    Full Text Available Soil salinity is a crucial environmental constraint which limits biomass production at many sites on a global scale. Saline growth conditions cause osmotic and ionic imbalances, oxidative stress and perturb metabolism, e.g. the photosynthetic electron flow. The plant ability to tolerate salinity is determined by multiple biochemical and physiological mechanisms protecting cell functions, in particular by regulating proper water relations and maintaining ion homeostasis. Redox homeostasis is a fundamental cell property. Its regulation includes control of reactive oxygen species (ROS generation, sensing deviation from and readjustment of the cellular redox state. All these redox related functions have been recognized as decisive factors in salinity acclimation and adaptation. This review focuses on the core response of plants to overcome the challenges of salinity stress through regulation of ROS generation and detoxification systems and to maintain redox homeostasis. Emphasis is given to the role of NADH oxidase (RBOH, alternative oxidase (AOX, the plastid terminal oxidase (PTOX and the malate valve with the malate dehydrogenase isoforms under salt stress. Overwhelming evidence assigns an essential auxiliary function of ROS and redox homeostasis to salinity acclimation of plants.

  7. Prediction of dynamic cutting force and regenerative chatter stability in inserted cutters milling

    Science.gov (United States)

    Li, Zhongqun; Liu, Qiang; Yuan, Songmei; Huang, Kaisheng

    2013-05-01

    Currently, the modeling of cutting process mainly focuses on two aspects: one is the setup of the universal cutting force model that can be adapted to a broader cutting condition; the other is the setup of the exact cutting force model that can accurately reflect a true cutting process. However, there is little research on the prediction of chatter stablity in milling. Based on the generalized mathematical model of inserted cutters introduced by ENGIN, an improved geometrical, mechanical and dynamic model for the vast variety of inserted cutters widely used in engineering applications is presented, in which the average directional cutting force coefficients are obtained by means of a numerical approach, thus leading to an analytical determination of stability lobes diagram (SLD) on the axial depth of cut. A new kind of SLD on the radial depth of cut is also created to satisfy the special requirement of inserted cutter milling. The corresponding algorithms used for predicting cutting forces, vibrations, dimensional surface finish and stability lobes in inserted cutter milling under different cutting conditions are put forward. Thereafter, a dynamic simulation module of inserted cutter milling is implemented by using hybrid program of Matlab with Visual Basic. Verification tests are conducted on a vertical machine center for Aluminum alloy LC4 by using two different types of inserted cutters, and the effectiveness of the model and the algorithm is verified by the good agreement of simulation result with that of cutting tests under different cutting conditions. The proposed model can predict the cutting process accurately under a variety of cutting conditions, and a high efficient and chatter-free milling operation can be achieved by a cutting condition optimization in industry applications.

  8. Neuroimmune interaction and the regulation of intestinal immune homeostasis.

    Science.gov (United States)

    Verheijden, Simon; Boeckxstaens, Guy E

    2018-01-01

    Many essential gastrointestinal functions, including motility, secretion, and blood flow, are regulated by the autonomic nervous system (ANS), both through intrinsic enteric neurons and extrinsic (sympathetic and parasympathetic) innervation. Recently identified neuroimmune mechanisms, in particular the interplay between enteric neurons and muscularis macrophages, are now considered to be essential for fine-tuning peristalsis. These findings shed new light on how intestinal immune cells can support enteric nervous function. In addition, both intrinsic and extrinsic neural mechanisms control intestinal immune homeostasis in different layers of the intestine, mainly by affecting macrophage activation through neurotransmitter release. In this mini-review, we discuss recent insights on immunomodulation by intrinsic enteric neurons and extrinsic innervation, with a particular focus on intestinal macrophages. In addition, we discuss the relevance of these novel mechanisms for intestinal immune homeostasis in physiological and pathological conditions, mainly focusing on motility disorders (gastroparesis and postoperative ileus) and inflammatory disorders (colitis).

  9. CNS-targets in control of energy and glucose homeostasis.

    Science.gov (United States)

    Kleinridders, André; Könner, A Christine; Brüning, Jens C

    2009-12-01

    The exceeding efforts in understanding the signals initiated by nutrients and hormones in the central nervous system (CNS) to regulate glucose and energy homeostasis have largely revolutionized our understanding of the neurocircuitry in control of peripheral metabolism. The ability of neurons to sense nutrients and hormones and to adopt a coordinated response to these signals is of crucial importance in controlling food intake, energy expenditure, glucose and lipid metabolism. Anatomical lesion experiments, pharmacological inhibition of signaling pathways, and, more recently, the analysis of conditional mouse mutants with modifications of hormone and nutrient signaling in defined neuronal populations have broadened our understanding of these complex neurocircuits. This review summarizes recent findings regarding the role of the CNS in sensing and transmitting nutritional and hormonal signals to control energy and glucose homeostasis and aims to define them as potential novel drug targets for the treatment of obesity and type 2 diabetes mellitus.

  10. Energy homeostasis regulatory peptides in hibernating grizzly bears.

    Science.gov (United States)

    Gardi, János; Nelson, O Lynne; Robbins, Charles T; Szentirmai, Eva; Kapás, Levente; Krueger, James M

    2011-05-15

    Grizzly bears (Ursus arctos horribilis) are inactive for up to 6 months during hibernation. They undergo profound seasonal changes in food intake, body mass, and energy expenditure. The circa-annual regulation of metabolism is poorly understood. In this study, we measured plasma ghrelin, leptin, obestatin, and neuropeptide-Y (NPY) levels, hormones known to be involved in the regulation of energy homeostasis, in ten grizzly bears. Blood samples were collected during the active summer period, early hibernation and late hibernation. Plasma levels of leptin, obestatin, and NPY did not change between the active and the hibernation periods. Plasma total ghrelin and desacyl-ghrelin concentrations significantly decreased during the inactive winter period compared to summer levels. The elevated ghrelin levels may help enhance body mass during pre-hibernation, while the low plasma ghrelin concentrations during hibernation season may contribute to the maintenance of hypophagia, low energy utilization and behavioral inactivity. Our results suggest that ghrelin plays a potential role in the regulation of metabolic changes and energy homeostasis during hibernation in grizzly bears. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Interleukin-33 in Tissue Homeostasis, Injury, and Inflammation.

    Science.gov (United States)

    Molofsky, Ari B; Savage, Adam K; Locksley, Richard M

    2015-06-16

    Interleukin-33 (IL-33) is a nuclear-associated cytokine of the IL-1 family originally described as a potent inducer of allergic type 2 immunity. IL-33 signals via the receptor ST2, which is highly expressed on group 2 innate lymphoid cells (ILC2s) and T helper 2 (Th2) cells, thus underpinning its association with helminth infection and allergic pathology. Recent studies have revealed ST2 expression on subsets of regulatory T cells, and for a role for IL-33 in tissue homeostasis and repair that suggests previously unrecognized interactions within these cellular networks. IL-33 can participate in pathologic fibrotic reactions, or, in the setting of microbial invasion, can cooperate with inflammatory cytokines to promote responses by cytotoxic NK cells, Th1 cells, and CD8(+) T cells. Here, we highlight the regulation and function of IL-33 and ST2 and review their roles in homeostasis, damage, and inflammation, suggesting a conceptual framework for future studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Cellular Links Between Neuronal Activity and Energy Homeostasis

    Directory of Open Access Journals (Sweden)

    Pavan K Shetty

    2012-03-01

    Full Text Available Neuronal activity, astrocytic responses to this activity, and energy homeostasis are linked together during baseline, conscious conditions, and short-term rapid activation (as occurs with sensory or motor function. Nervous system energy homeostasis also varies during long-term physiological conditions (ie, development and aging and with adaptation to pathological conditions, such as ischemia or low glucose. Neuronal activation requires increased metabolism (i.e., ATP generation which leads initially to substrate depletion, induction of a variety of signals for enhanced astrocytic function, and increased local blood flow and substrate delivery. Energy generation (particularly in mitochondria and use during ATP hydrolysis also lead to considerable heat generation. The local increases in blood flow noted following neuronal activation can both enhance local substrate delivery but also provides a heat sink to help cool the brain and removal of waste byproducts. In this review we highlight the interactions between short-term neuronal activity and energy metabolism with an emphasis on signals and factors regulating astrocyte function and substrate supply.

  13. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    Science.gov (United States)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  14. Acute activation of GLP-1-expressing neurons promotes glucose homeostasis and insulin sensitivity

    OpenAIRE

    Xuemei Shi; Shaji Chacko; Feng Li; Depei Li; Douglas Burrin; Lawrence Chan; Xinfu Guan

    2017-01-01

    Objective: Glucagon-like peptides are co-released from enteroendocrine L cells in the gut and preproglucagon (PPG) neurons in the brainstem. PPG-derived GLP-1/2 are probably key neuroendocrine signals for the control of energy balance and glucose homeostasis. The objective of this study was to determine whether activation of PPG neurons per se modulates glucose homeostasis and insulin sensitivity in vivo. Methods: We generated glucagon (Gcg) promoter-driven Cre transgenic mice and injected...

  15. Immune homeostasis, dysbiosis and therapeutic modulation of the gut microbiota.

    Science.gov (United States)

    Peterson, C T; Sharma, V; Elmén, L; Peterson, S N

    2015-03-01

    The distal gut harbours ∼10(13) bacteria, representing the most densely populated ecosystem known. The functional diversity expressed by these communities is enormous and relatively unexplored. The past decade of research has unveiled the profound influence that the resident microbial populations bestow to host immunity and metabolism. The evolution of these communities from birth generates a highly adapted and highly personalized microbiota that is stable in healthy individuals. Immune homeostasis is achieved and maintained due in part to the extensive interplay between the gut microbiota and host mucosal immune system. Imbalances of gut microbiota may lead to a number of pathologies such as obesity, type I and type II diabetes, inflammatory bowel disease (IBD), colorectal cancer (CRC) and inflammaging/immunosenscence in the elderly. In-depth understanding of the underlying mechanisms that control homeostasis and dysbiosis of the gut microbiota represents an important step in our ability to reliably modulate the gut microbiota with positive clinical outcomes. The potential of microbiome-based therapeutics to treat epidemic human disease is of great interest. New therapeutic paradigms, including second-generation personalized probiotics, prebiotics, narrow spectrum antibiotic treatment and faecal microbiome transplantation, may provide safer and natural alternatives to traditional clinical interventions for chronic diseases. This review discusses host-microbiota homeostasis, consequences of its perturbation and the associated challenges in therapeutic developments that lie ahead. © 2014 British Society for Immunology.

  16. Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

    KAUST Repository

    Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

    2011-01-01

    This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques

  17. Cholesterol efflux is differentially regulated in neurons and astrocytes: implications for brain cholesterol homeostasis

    Science.gov (United States)

    Chen, Jing; Zhang, Xiaolu; Kusumo, Handojo; Costa, Lucio G.; Guizzetti, Marina

    2012-01-01

    Disruption of cholesterol homeostasis in the central nervous system (CNS) has been associated with neurological, neurodegenerative, and neurodevelopmental disorders. The CNS is a closed system with regard to cholesterol homeostasis, as cholesterol-delivering lipoproteins from the periphery cannot pass the blood-brain-barrier and enter the brain. Different cell types in the brain have different functions in the regulation of cholesterol homeostasis, with astrocytes producing and releasing apolipoprotein E and lipoproteins, and neurons metabolizing cholesterol to 24(S)-hydroxycholesterol. We present evidence that astrocytes and neurons adopt different mechanisms also in regulating cholesterol efflux. We found that in astrocytes cholesterol efflux is induced by both lipid-free apolipoproteins and lipoproteins, while cholesterol removal from neurons is triggered only by lipoproteins. The main pathway by which apolipoproteins induce cholesterol efflux is through ABCA1. By upregulating ABCA1 levels and by inhibiting its activity and silencing its expression, we show that ABCA1 is involved in cholesterol efflux from astrocytes but not from neurons. Furthermore, our results suggest that ABCG1 is involved in cholesterol efflux to apolipoproteins and lipoproteins from astrocytes but not from neurons, while ABCG4, whose expression is much higher in neurons than astrocytes, is involved in cholesterol efflux from neurons but not astrocytes. These results indicate that different mechanisms regulate cholesterol efflux from neurons and astrocytes, reflecting the different roles that these cell types play in brain cholesterol homeostasis. These results are important in understanding cellular targets of therapeutic drugs under development for the treatments of conditions associated with altered cholesterol homeostasis in the CNS. PMID:23010475

  18. Gene Expression Dynamics Accompanying the Sponge Thermal Stress Response.

    Science.gov (United States)

    Guzman, Christine; Conaco, Cecilia

    2016-01-01

    Marine sponges are important members of coral reef ecosystems. Thus, their responses to changes in ocean chemistry and environmental conditions, particularly to higher seawater temperatures, will have potential impacts on the future of these reefs. To better understand the sponge thermal stress response, we investigated gene expression dynamics in the shallow water sponge, Haliclona tubifera (order Haplosclerida, class Demospongiae), subjected to elevated temperature. Using high-throughput transcriptome sequencing, we show that these conditions result in the activation of various processes that interact to maintain cellular homeostasis. Short-term thermal stress resulted in the induction of heat shock proteins, antioxidants, and genes involved in signal transduction and innate immunity pathways. Prolonged exposure to thermal stress affected the expression of genes involved in cellular damage repair, apoptosis, signaling and transcription. Interestingly, exposure to sublethal temperatures may improve the ability of the sponge to mitigate cellular damage under more extreme stress conditions. These insights into the potential mechanisms of adaptation and resilience of sponges contribute to a better understanding of sponge conservation status and the prediction of ecosystem trajectories under future climate conditions.

  19. Deflection Prediction of No-Fines Lightweight Concrete Wall Using Neural Network Caused Dynamic Loads

    Directory of Open Access Journals (Sweden)

    Ridho Bayuaji

    2018-04-01

    Full Text Available No-fines lightweight concrete wall with horizontal reinforcement refers to an alternative material for wall construction with an aim of improving the wall quality towards horizontal loads. This study is focused on artificial neural network (ANN application to predicting the deflection deformation caused by dynamic loads. The ANN method is able to capture the complex interactions among input/output variables in a system without any knowledge of interaction nature and without any explicit assumption to model form. This paper explains the existing data research, data selection and process of ANN modelling training process and validation. The results of this research show that the deformation can be predicted more accurately, simply and quickly due to the alternating horizontal loads.

  20. Nonlinear quasi-static finite element simulations predict in vitro strength of human proximal femora assessed in a dynamic sideways fall setup.

    Science.gov (United States)

    Varga, Peter; Schwiedrzik, Jakob; Zysset, Philippe K; Fliri-Hofmann, Ladina; Widmer, Daniel; Gueorguiev, Boyko; Blauth, Michael; Windolf, Markus

    2016-04-01

    Osteoporotic proximal femur fractures are caused by low energy trauma, typically when falling on the hip from standing height. Finite element simulations, widely used to predict the fracture load of femora in fall, usually include neither mass-related inertial effects, nor the viscous part of bone׳s material behavior. The aim of this study was to elucidate if quasi-static non-linear homogenized finite element analyses can predict in vitro mechanical properties of proximal femora assessed in dynamic drop tower experiments. The case-specific numerical models of 13 femora predicted the strength (R(2)=0.84, SEE=540N, 16.2%), stiffness (R(2)=0.82, SEE=233N/mm, 18.0%) and fracture energy (R(2)=0.72, SEE=3.85J, 39.6%); and provided fair qualitative matches with the fracture patterns. The influence of material anisotropy was negligible for all predictions. These results suggest that quasi-static homogenized finite element analysis may be used to predict mechanical properties of proximal femora in the dynamic sideways fall situation. Copyright © 2015 Elsevier Ltd. All rights reserved.