WorldWideScience

Sample records for chemical shift prediction

  1. Protein Chemical Shift Prediction

    CERN Document Server

    Larsen, Anders S

    2014-01-01

    The protein chemical shifts holds a large amount of information about the 3-dimensional structure of the protein. A number of chemical shift predictors based on the relationship between structures resolved with X-ray crystallography and the corresponding experimental chemical shifts have been developed. These empirical predictors are very accurate on X-ray structures but tends to be insensitive to small structural changes. To overcome this limitation it has been suggested to make chemical shift predictors based on quantum mechanical(QM) calculations. In this thesis the development of the QM derived chemical shift predictor Procs14 is presented. Procs14 is based on 2.35 million density functional theory(DFT) calculations on tripeptides and contains corrections for hydrogen bonding, ring current and the effect of the previous and following residue. Procs14 is capable at performing predictions for the 13CA, 13CB, 13CO, 15NH, 1HN and 1HA backbone atoms. In order to benchmark Procs14, a number of QM NMR calculatio...

  2. Chemical shift prediction for denatured proteins

    Energy Technology Data Exchange (ETDEWEB)

    Prestegard, James H., E-mail: jpresteg@ccrc.uga.edu; Sahu, Sarata C.; Nkari, Wendy K.; Morris, Laura C.; Live, David; Gruta, Christian

    2013-02-15

    While chemical shift prediction has played an important role in aspects of protein NMR that include identification of secondary structure, generation of torsion angle constraints for structure determination, and assignment of resonances in spectra of intrinsically disordered proteins, interest has arisen more recently in using it in alternate assignment strategies for crosspeaks in {sup 1}H-{sup 15}N HSQC spectra of sparsely labeled proteins. One such approach involves correlation of crosspeaks in the spectrum of the native protein with those observed in the spectrum of the denatured protein, followed by assignment of the peaks in the latter spectrum. As in the case of disordered proteins, predicted chemical shifts can aid in these assignments. Some previously developed empirical formulas for chemical shift prediction have depended on basis data sets of 20 pentapeptides. In each case the central residue was varied among the 20 amino common acids, with the flanking residues held constant throughout the given series. However, previous choices of solvent conditions and flanking residues make the parameters in these formulas less than ideal for general application to denatured proteins. Here, we report {sup 1}H and {sup 15}N shifts for a set of alanine based pentapeptides under the low pH urea denaturing conditions that are more appropriate for sparse label assignments. New parameters have been derived and a Perl script was created to facilitate comparison with other parameter sets. A small, but significant, improvement in shift predictions for denatured ubiquitin is demonstrated.

  3. Improved chemical shift prediction by Rosetta conformational sampling

    Energy Technology Data Exchange (ETDEWEB)

    Tian Ye [Sanford Burnham Medical Research Institute (United States); Opella, Stanley J. [University of California San Diego, Department of Chemistry and Biochemistry (United States); Marassi, Francesca M., E-mail: fmarassi@sbmri.org [Sanford Burnham Medical Research Institute (United States)

    2012-11-15

    Chemical shift frequencies represent a time-average of all the conformational states populated by a protein. Thus, chemical shift prediction programs based on sequence and database analysis yield higher accuracy for rigid rather than flexible protein segments. Here we show that the prediction accuracy can be significantly improved by averaging over an ensemble of structures, predicted solely from amino acid sequence with the Rosetta program. This approach to chemical shift and structure prediction has the potential to be useful for guiding resonance assignments, especially in solid-state NMR structural studies of membrane proteins in proteoliposomes.

  4. Protein secondary structure prediction using NMR chemical shift data.

    Science.gov (United States)

    Zhao, Yuzhong; Alipanahi, Babak; Li, Shuai Cheng; Li, Ming

    2010-10-01

    Accurate determination of protein secondary structure from the chemical shift information is a key step for NMR tertiary structure determination. Relatively few work has been done on this subject. There needs to be a systematic investigation of algorithms that are (a) robust for large datasets; (b) easily extendable to (the dynamic) new databases; and (c) approaching to the limit of accuracy. We introduce new approaches using k-nearest neighbor algorithm to do the basic prediction and use the BCJR algorithm to smooth the predictions and combine different predictions from chemical shifts and based on sequence information only. Our new system, SUCCES, improves the accuracy of all existing methods on a large dataset of 805 proteins (at 86% Q(3) accuracy and at 92.6% accuracy when the boundary residues are ignored), and it is easily extendable to any new dataset without requiring any new training. The software is publicly available at http://monod.uwaterloo.ca/nmr/succes.

  5. Improving 3D structure prediction from chemical shift data

    Energy Technology Data Exchange (ETDEWEB)

    Schot, Gijs van der [Utrecht University, Computational Structural Biology, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry (Netherlands); Zhang, Zaiyong [Technische Universitaet Muenchen, Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie (Germany); Vernon, Robert [University of Washington, Department of Biochemistry (United States); Shen, Yang [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Vranken, Wim F. [VIB, Department of Structural Biology (Belgium); Baker, David [University of Washington, Department of Biochemistry (United States); Bonvin, Alexandre M. J. J., E-mail: a.m.j.j.bonvin@uu.nl [Utrecht University, Computational Structural Biology, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry (Netherlands); Lange, Oliver F., E-mail: oliver.lange@tum.de [Technische Universitaet Muenchen, Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie (Germany)

    2013-09-15

    We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70 % of the cases. All structures that passed the reliability filter were accurate (<2 A RMSD from the reference)

  6. 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.

  7. A probabilistic model for secondary structure prediction from protein chemical shifts.

    Science.gov (United States)

    Mechelke, Martin; Habeck, Michael

    2013-06-01

    Protein chemical shifts encode detailed structural information that is difficult and computationally costly to describe at a fundamental level. Statistical and machine learning approaches have been used to infer correlations between chemical shifts and secondary structure from experimental chemical shifts. These methods range from simple statistics such as the chemical shift index to complex methods using neural networks. Notwithstanding their higher accuracy, more complex approaches tend to obscure the relationship between secondary structure and chemical shift and often involve many parameters that need to be trained. We present hidden Markov models (HMMs) with Gaussian emission probabilities to model the dependence between protein chemical shifts and secondary structure. The continuous emission probabilities are modeled as conditional probabilities for a given amino acid and secondary structure type. Using these distributions as outputs of first- and second-order HMMs, we achieve a prediction accuracy of 82.3%, which is competitive with existing methods for predicting secondary structure from protein chemical shifts. Incorporation of sequence-based secondary structure prediction into our HMM improves the prediction accuracy to 84.0%. Our findings suggest that an HMM with correlated Gaussian distributions conditioned on the secondary structure provides an adequate generative model of chemical shifts.

  8. Prediction of hydrogen and carbon chemical shifts from RNA using database mining and support vector regression

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Joshua D.; Summers, Michael F. [University of Maryland Baltimore County, Howard Hughes Medical Institute (United States); Johnson, Bruce A., E-mail: bruce.johnson@asrc.cuny.edu [University of Maryland Baltimore County, Department of Chemistry and Biochemistry (United States)

    2015-09-15

    The Biological Magnetic Resonance Data Bank (BMRB) contains NMR chemical shift depositions for over 200 RNAs and RNA-containing complexes. We have analyzed the {sup 1}H NMR and {sup 13}C chemical shifts reported for non-exchangeable protons of 187 of these RNAs. Software was developed that downloads BMRB datasets and corresponding PDB structure files, and then generates residue-specific attributes based on the calculated secondary structure. Attributes represent properties present in each sequential stretch of five adjacent residues and include variables such as nucleotide type, base-pair presence and type, and tetraloop types. Attributes and {sup 1}H and {sup 13}C NMR chemical shifts of the central nucleotide are then used as input to train a predictive model using support vector regression. These models can then be used to predict shifts for new sequences. The new software tools, available as stand-alone scripts or integrated into the NMR visualization and analysis program NMRViewJ, should facilitate NMR assignment and/or validation of RNA {sup 1}H and {sup 13}C chemical shifts. In addition, our findings enabled the re-calibration a ring-current shift model using published NMR chemical shifts and high-resolution X-ray structural data as guides.

  9. From NMR chemical shifts to amino acid types: Investigation of the predictive power carried by nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Marin, Antoine; Malliavin, Therese E. [Institut de Biologie Physico-Chimique, Laboratoire de Biochimie Theorique, CNRS UPR 9080 (France)], E-mail: therese.malliavin@ibpc.fr; Nicolas, Pierre; Delsuc, Marc-Andre [INRA - Domaine de Vilvert, Unite Mathematique Informatique et Genome (France)

    2004-09-15

    An approach to automatic prediction of the amino acid type from NMR chemical shift values of its nuclei is presented here, in the frame of a model to calculate the probability of an amino acid type given the set of chemical shifts. The method relies on systematic use of all chemical shift values contained in the BioMagResBank (BMRB). Two programs were designed, one (BMRB stats) for extracting statistical chemical shift parameters from the BMRB and another one (RESCUE2) for computing the probabilities of each amino acid type, given a set of chemical shifts. The Bayesian prediction scheme presented here is compared to other methods already proposed: PROTYP (Grzesiek and Bax, J. Biomol. NMR, 3, 185-204, 1993) RESCUE (Pons and Delsuc, J. Biomol. NMR, 15, 15-26, 1999) and PLATON (Labudde et al., J. Biomol. NMR, 25, 41-53, 2003) and is found to be more sensitive and more specific. Using this scheme, we tested various sets of nuclei. The two nuclei carrying the most information are C{sub {beta}} and H{sub {beta}}, in agreement with observations made in Grzesiek and Bax, 1993. Based on four nuclei: H{sub {beta}}, C{sub {beta}}, C{sub {alpha}} and C', it is possible to increase correct predictions to a rate of more than 75%. Taking into account the correlations between the nuclei chemical shifts has only a slight impact on the percentage of correct predictions: indeed, the largest correlation coefficients display similar features on all amino acids.

  10. Prediction algorithm for amino acid types with their secondary structure in proteins (PLATON) using chemical shifts.

    Science.gov (United States)

    Labudde, D; Leitner, D; Krüger, M; Oschkinat, H

    2003-01-01

    The algorithm PLATON is able to assign sets of chemical shifts derived from a single residue to amino acid types with its secondary structure (amino acid species). A subsequent ranking procedure using optionally two different penalty functions yields predictions for possible amino acid species for the given set of chemical shifts. This was demonstrated in the case of the alpha-spectrin SH3 domain and applied to 9 further protein data sets taken from the BioMagRes database. A database consisting of reference chemical shift patterns (reference CSPs) was generated from assigned chemical shifts of proteins with known 3D-structure. This reference CSP database is used in our approach for extracting distributions of amino acid types with their most likely secondary structure elements (namely alpha-helix, beta-sheet, and coil) for single amino acids by comparison with query CSPs. Results obtained for the 10 investigated proteins indicates that the percentage of correct amino acid species in the first three positions in the ranking list, ranges from 71.4% to 93.2% for the more favorable penalty function. Where only the top result of the ranking list for these 10 proteins is considered, 36.5% to 83.1% of the amino acid species are correctly predicted. The main advantage of our approach, over other methods that rely on average chemical shift values is the ability to increase database content by incorporating newly derived CSPs, and therefore to improve PLATON's performance over time.

  11. Predicting Pt-195 NMR chemical shift using new relativistic all-electron basis set.

    Science.gov (United States)

    Paschoal, D; Guerra, C Fonseca; de Oliveira, M A L; Ramalho, T C; Dos Santos, H F

    2016-10-01

    Predicting NMR properties is a valuable tool to assist the experimentalists in the characterization of molecular structure. For heavy metals, such as Pt-195, only a few computational protocols are available. In the present contribution, all-electron Gaussian basis sets, suitable to calculate the Pt-195 NMR chemical shift, are presented for Pt and all elements commonly found as Pt-ligands. The new basis sets identified as NMR-DKH were partially contracted as a triple-zeta doubly polarized scheme with all coefficients obtained from a Douglas-Kroll-Hess (DKH) second-order scalar relativistic calculation. The Pt-195 chemical shift was predicted through empirical models fitted to reproduce experimental data for a set of 183 Pt(II) complexes which NMR sign ranges from -1000 to -6000 ppm. Furthermore, the models were validated using a new set of 75 Pt(II) complexes, not included in the descriptive set. The models were constructed using non-relativistic Hamiltonian at density functional theory (DFT-PBEPBE) level with NMR-DKH basis set for all atoms. For the best model, the mean absolute deviation (MAD) and the mean relative deviation (MRD) were 150 ppm and 6%, respectively, for the validation set (75 Pt-complexes) and 168 ppm (MAD) and 5% (MRD) for all 258 Pt(II) complexes. These results were comparable with relativistic DFT calculation, 200 ppm (MAD) and 6% (MRD). © 2016 Wiley Periodicals, Inc.

  12. Inferential protein structure determination and refinement using fast, electronic structure based backbone amide chemical shift predictions

    CERN Document Server

    Christensen, Anders S

    2015-01-01

    This report covers the development of a new, fast method for calculating the backbone amide proton chemical shifts in proteins. Through quantum chemical calculations, structure-based forudsiglese the chemical shift for amidprotonen in protein has been parameterized. The parameters are then implemented in a computer program called Padawan. The program has since been implemented in protein folding program Phaistos, wherein the method andvendes to de novo folding of the protein structures and to refine the existing protein structures.

  13. Predicting the redox state and secondary structure of cysteine residues using multi-dimensional classification analysis of NMR chemical shifts.

    Science.gov (United States)

    Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

    2016-09-01

    A tool for predicting the redox state and secondary structure of cysteine residues using multi-dimensional analyses of different combinations of nuclear magnetic resonance (NMR) chemical shifts has been developed. A data set of cysteine [Formula: see text], (13)C(α), (13)C(β), (1)H(α), (1)H(N), and (15)N(H) chemical shifts was created, classified according to redox state and secondary structure, using a library of 540 re-referenced BioMagResBank (BMRB) entries. Multi-dimensional analyses of three, four, five, and six chemical shifts were used to derive rules for predicting the structural states of cysteine residues. The results from 60 BMRB entries containing 122 cysteines showed that four-dimensional analysis of the C(α), C(β), H(α), and N(H) chemical shifts had the highest prediction accuracy of 100 and 95.9 % for the redox state and secondary structure, respectively. The prediction of secondary structure using 3D, 5D, and 6D analyses had the accuracy of ~90 %, suggesting that H(N) and [Formula: see text] chemical shifts may be noisy and made the discrimination worse. A web server (6DCSi) was established to enable users to submit NMR chemical shifts, either in BMRB or key-in formats, for prediction. 6DCSi displays predictions using sets of 3, 4, 5, and 6 chemical shifts, which shows their consistency and allows users to draw their own conclusions. This web-based tool can be used to rapidly obtain structural information regarding cysteine residues directly from experimental NMR data.

  14. Predicting Heats of Explosion of Nitroaromatic Compounds through NBO Charges and 15N NMR Chemical Shifts of Nitro Groups

    Directory of Open Access Journals (Sweden)

    Ricardo Infante-Castillo

    2012-01-01

    Full Text Available This work presents a new quantitative model to predict the heat of explosion of nitroaromatic compounds using the natural bond orbital (NBO charge and 15N NMR chemical shifts of the nitro groups (15NNitro as structural parameters. The values of the heat of explosion predicted for 21 nitroaromatic compounds using the model described here were compared with experimental data. The prediction ability of the model was assessed by the leave-one-out cross-validation method. The cross-validation results show that the model is significant and stable and that the predicted accuracy is within 0.146 MJ kg−1, with an overall root mean squared error of prediction (RMSEP below 0.183 MJ kg−1. Strong correlations were observed between the heat of explosion and the charges (R2 = 0.9533 and 15N NMR chemical shifts (R2 = 0.9531 of the studied compounds. In addition, the dependence of the heat of explosion on the presence of activating or deactivating groups of nitroaromatic explosives was analyzed. All calculations, including optimizations, NBO charges, and 15NNitro NMR chemical shifts analyses, were performed using density functional theory (DFT and a 6-311+G(2d,p basis set. Based on these results, this practical quantitative model can be used as a tool in the design and development of highly energetic materials (HEM based on nitroaromatic compounds.

  15. Predicting Heats of Explosion of Nitroaromatic Compounds through NBO Charges and 15N NMR Chemical Shifts of Nitro Groups

    OpenAIRE

    Ricardo Infante-Castillo; Samuel P. Hernández-Rivera

    2012-01-01

    This work presents a new quantitative model to predict the heat of explosion of nitroaromatic compounds using the natural bond orbital (NBO) charge and 15N NMR chemical shifts of the nitro groups (15NNitro) as structural parameters. The values of the heat of explosion predicted for 21 nitroaromatic compounds using the model described here were compared with experimental data. The prediction ability of the model was assessed by the leave-one-out cross-validation method. The cross-validation re...

  16. Complete (1)H and (13)C NMR chemical shift assignments of mono-, di-, and trisaccharides as basis for NMR chemical shift predictions of polysaccharides using the computer program casper.

    Science.gov (United States)

    Roslund, Mattias U; Säwén, Elin; Landström, Jens; Rönnols, Jerk; Jonsson, K Hanna M; Lundborg, Magnus; Svensson, Mona V; Widmalm, Göran

    2011-08-16

    The computer program casper uses (1)H and (13)C NMR chemical shift data of mono- to trisaccharides for the prediction of chemical shifts of oligo- and polysaccharides. In order to improve the quality of these predictions the (1)H and (13)C, as well as (31)P when applicable, NMR chemical shifts of 30 mono-, di-, and trisaccharides were assigned. The reducing sugars gave two distinct sets of NMR resonances due to the α- and β-anomeric forms. In total 35 (1)H and (13)C NMR chemical shift data sets were obtained from the oligosaccharides. One- and two-dimensional NMR experiments were used for the chemical shift assignments and special techniques were employed in some cases such as 2D (1)H,(13)C-HSQC Hadamard Transform methodology which was acquired approximately 45 times faster than a regular t(1) incremented (1)H,(13)C-HSQC experiment and a 1D (1)H,(1)H-CSSF-TOCSY experiment which was able to distinguish spin-systems in which the target protons were only 3.3Hz apart. The (1)H NMR chemical shifts were subsequently refined using total line-shape analysis with the PERCH NMR software. The acquired NMR data were then utilized in the casper program (http://www.casper.organ.su.se/casper/) for NMR chemical shift predictions of the O-antigen polysaccharides from Klebsiella O5, Shigella flexneri serotype X, and Salmonella arizonae O62. The data were compared to experimental data of the polysaccharides from the two former strains and the lipopolysaccharide of the latter strain showing excellent agreement between predicted and experimental (1)H and (13)C NMR chemical shifts.

  17. Fully automatic assignment of small molecules' NMR spectra without relying on chemical shift predictions.

    Science.gov (United States)

    Castillo, Andrés M; Bernal, Andrés; Patiny, Luc; Wist, Julien

    2015-08-01

    We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self-consistent peak-picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto-assignment routine used is based on branch-and-bound optimization and relies predominantly on integration and correlation data; chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web-based tool that runs without any user input other than the acquired spectra. Copyright © 2015 John Wiley & Sons, Ltd.

  18. Predicting paramagnetic 1H NMR chemical shifts and state-energy separations in spin-crossover host-guest systems.

    Science.gov (United States)

    Isley, William C; Zarra, Salvatore; Carlson, Rebecca K; Bilbeisi, Rana A; Ronson, Tanya K; Nitschke, Jonathan R; Gagliardi, Laura; Cramer, Christopher J

    2014-06-14

    The behaviour of metal-organic cages upon guest encapsulation can be difficult to elucidate in solution. Paramagnetic metal centres introduce additional dispersion of signals that is useful for characterisation of host-guest complexes in solution using nuclear magnetic resonance (NMR). However, paramagnetic centres also complicate spectral assignment due to line broadening, signal integration error, and large changes in chemical shifts, which can be difficult to assign even for known compounds. Quantum chemical predictions can provide information that greatly facilitates the assignment of NMR signals and identification of species present. Here we explore how the prediction of paramagnetic NMR spectra may be used to gain insight into the spin crossover (SCO) properties of iron(II)-based metal organic coordination cages, specifically examining how the structure of the local metal coordination environment affects SCO. To represent the tetrahedral metal-organic cage, a model system is generated by considering an isolated metal-ion vertex: fac-ML3(2+) (M = Fe(II), Co(II); L = N-phenyl-2-pyridinaldimine). The sensitivity of the (1)H paramagnetic chemical shifts to local coordination environments is assessed and utilised to shed light on spin crossover behaviour in iron complexes. Our data indicate that expansion of the metal coordination sphere must precede any thermal SCO. An attempt to correlate experimental enthalpies of SCO with static properties of bound guests shows that no simple relationship exists, and that effects are likely due to nuanced dynamic response to encapsulation.

  19. Predictions of the fluorine NMR chemical shifts of perfluorinated carboxylic acids, CnF(2n+1)COOH (n = 6-8).

    Science.gov (United States)

    Liu, Zizhong; Goddard, John D

    2009-12-17

    Perfluorinated carboxylic acids (PFCAs) are a class of persistent environmental pollutants. Commercially available PFCAs are mixtures of linear and branched isomers, possibly with impurities. Different isomers have different physical and chemical properties and toxicities. However, little is known about the properties and the finer details of the structures of the individual branched isomers. Full geometry optimizations for the linear n-alkane (C(6)-C(27)) PFCAs indicated that all have helical structures. The helical angle increases slightly with increasing chain length, from 16.3 degrees in C(6)F(13)COOH to 17.0 degrees in C(27)F(55)COOH. This study predicts (19)F NMR parameters for 69 linear and branched isomers of the perfluoro carboxylic acids C(6)F(13)COOH, C(7)F(15)COOH, and C(8)F(17)COOH. B3LYP-GIAO/6-31++G(d,p)//B3LYP/6-31G(d,p) was used for the NMR calculations with analysis of the chemical shifts by the natural bond orbital method. The predictions of the (19)F chemical shifts revealed the differences among the CF(3), CF(2), and CF groups. In general, the absolute values for the chemical shifts for the CF(3) group are smaller than 90 ppm, for the CF larger than 160 ppm, and for the CF(2) between 110 and 130 ppm. The chemical shifts of the branched isomers are smaller in magnitude than the linear ones. The decrease is correlated with the steric hindrance of the CF(3) groups, the more hindered the CF(3), the greater the decrease in the (19)F chemical shifts. The predicted (19)F chemical shifts are similar to those for analogous perfluoro compounds with other terminal functional groups such as -SO(3)H or -SO(3)NH(2)CH(2)CH(3).

  20. Free variable selection QSPR study to predict (19)F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods.

    Science.gov (United States)

    Goudarzi, Nasser

    2016-04-05

    In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the (19)F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the (19)F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

  1. Accessible surface area from NMR chemical shifts

    Energy Technology Data Exchange (ETDEWEB)

    Hafsa, Noor E.; Arndt, David; Wishart, David S., E-mail: david.wishart@ualberta.ca [University of Alberta, Department of Computing Science (Canada)

    2015-07-15

    Accessible surface area (ASA) is the surface area of an atom, amino acid or biomolecule that is exposed to solvent. The calculation of a molecule’s ASA requires three-dimensional coordinate data and the use of a “rolling ball” algorithm to both define and calculate the ASA. For polymers such as proteins, the ASA for individual amino acids is closely related to the hydrophobicity of the amino acid as well as its local secondary and tertiary structure. For proteins, ASA is a structural descriptor that can often be as informative as secondary structure. Consequently there has been considerable effort over the past two decades to try to predict ASA from protein sequence data and to use ASA information (derived from chemical modification studies) as a structure constraint. Recently it has become evident that protein chemical shifts are also sensitive to ASA. Given the potential utility of ASA estimates as structural constraints for NMR we decided to explore this relationship further. Using machine learning techniques (specifically a boosted tree regression model) we developed an algorithm called “ShiftASA” that combines chemical-shift and sequence derived features to accurately estimate per-residue fractional ASA values of water-soluble proteins. This method showed a correlation coefficient between predicted and experimental values of 0.79 when evaluated on a set of 65 independent test proteins, which was an 8.2 % improvement over the next best performing (sequence-only) method. On a separate test set of 92 proteins, ShiftASA reported a mean correlation coefficient of 0.82, which was 12.3 % better than the next best performing method. ShiftASA is available as a web server ( http://shiftasa.wishartlab.com http://shiftasa.wishartlab.com ) for submitting input queries for fractional ASA calculation.

  2. Prediction of microvascular invasion of hepatocellular carcinomas with gadoxetic acid-enhanced MR imaging: Impact of intra-tumoral fat detected on chemical-shift images

    Energy Technology Data Exchange (ETDEWEB)

    Min, Ji Hye [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Kim, Young Kon, E-mail: jmyr@dreamwiz.com [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Lim, Sanghyeok [Department of Radiology, Guri Hospital, Hanyang University College of Medicine, Guri (Korea, Republic of); Jeong, Woo Kyoung; Choi, Dongil; Lee, Won Jae [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

    2015-06-15

    Highlights: • Intra-tumoral fat detected with MR imaging may suggest lower risk for MVI of HCC. • Alfa-fetoprotein, tumor size, and fat component were associated with MVI of HCC. • Chemical shift MRI should be considered for the evaluation of HCC. - Abstract: Purpose: To investigate the impact of intra-tumoral fat detected by chemical-shift MR imaging in predicting the MVI of HCC. Materials and methods: Gadoxetic acid-enhanced MR imaging of 365 surgically proven HCCs from 365 patients (306 men, 59 women; mean age, 55.6 years) were evaluated. HCCs were classified into two groups, fat-containing and non-fat-containing, based on the presence of fat on chemical-shift images. Fat-containing HCCs were subdivided into diffuse or focal fatty change groups. Logistic regression analyses were used to identify clinical and MR findings associated with MVI. Results: Based on MR imaging, 66 tumors were classified as fat-containing HCCs and 299 as non-fat-containing HCCs. Among the 66 fat-containing HCCs, 38 (57.6%) showed diffuse fatty changes and 28 (42.4%) showed focal fatty changes. MVI was present in 18 (27.3%) fat-containing HCCs and in 117 (39.1%) non-fat-containing HCCs (P = 0.07). Univariate analysis revealed that serum alpha-fetoprotein (AFP) and tumor size were significantly associated with MVI (P < 0.001). A multiple logistic regression analysis showed that log AFP (odds ratio 1.178, P = 0.0016), tumor size (odds ratio 1.809, P < 0.001), and intra-tumoral fat (odds ratio 0.515, P = 0.0387) were independent variables associated with MVI. Conclusion: Intra-tumoral fat detected with MR imaging may suggest lower risk for MVI of HCC and, therefore, a possibly more favorable prognosis, but the clinical value of this finding is uncertain.

  3. Empirical isotropic chemical shift surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Czinki, Eszter; Csaszar, Attila G. [Eoetvoes University, Laboratory of Molecular Spectroscopy, Institute of Chemistry (Hungary)], E-mail: csaszar@chem.elte.hu

    2007-08-15

    A list of proteins is given for which spatial structures, with a resolution better than 2.5 A, are known from entries in the Protein Data Bank (PDB) and isotropic chemical shift (ICS) values are known from the RefDB database related to the Biological Magnetic Resonance Bank (BMRB) database. The structures chosen provide, with unknown uncertainties, dihedral angles {phi} and {psi} characterizing the backbone structure of the residues. The joint use of experimental ICSs of the same residues within the proteins, again with mostly unknown uncertainties, and ab initio ICS({phi},{psi}) surfaces obtained for the model peptides For-(l-Ala){sub n}-NH{sub 2}, with n = 1, 3, and 5, resulted in so-called empirical ICS({phi},{psi}) surfaces for all major nuclei of the 20 naturally occurring {alpha}-amino acids. Out of the many empirical surfaces determined, it is the 13C{sup {alpha}} ICS({phi},{psi}) surface which seems to be most promising for identifying major secondary structure types, {alpha}-helix, {beta}-strand, left-handed helix ({alpha}{sub D}), and polyproline-II. Detailed tests suggest that Ala is a good model for many naturally occurring {alpha}-amino acids. Two-dimensional empirical 13C{sup {alpha}}-{sup 1}H{sup {alpha}} ICS({phi},{psi}) correlation plots, obtained so far only from computations on small peptide models, suggest the utility of the experimental information contained therein and thus they should provide useful constraints for structure determinations of proteins.

  4. Bayesian inference of protein structure from chemical shift data

    DEFF Research Database (Denmark)

    Bratholm, Lars Andersen; Christensen, Anders Steen; Hamelryck, Thomas Wim

    2015-01-01

    content of the data. Here, we present the formulation of such a probability distribution where the error in chemical shift prediction is described by either a Gaussian or Cauchy distribution. The methodology is demonstrated and compared to a set of empirically weighted potentials through Markov chain......, the simulations suggests that sampling both the structure and the uncertainties in chemical shift prediction leads more accurate structures compared to conventional methods using empirical determined weights. The Cauchy distribution, using either sampled uncertainties or predetermined weights, did, however......Protein chemical shifts are routinely used to augment molecular mechanics force fields in protein structure simulations, with weights of the chemical shift restraints determined empirically. These weights, however, might not be an optimal descriptor of a given protein structure and predictive model...

  5. Bayesian inference of protein structure from chemical shift data

    Science.gov (United States)

    Bratholm, Lars A.; Christensen, Anders S.; Hamelryck, Thomas

    2015-01-01

    Protein chemical shifts are routinely used to augment molecular mechanics force fields in protein structure simulations, with weights of the chemical shift restraints determined empirically. These weights, however, might not be an optimal descriptor of a given protein structure and predictive model, and a bias is introduced which might result in incorrect structures. In the inferential structure determination framework, both the unknown structure and the disagreement between experimental and back-calculated data are formulated as a joint probability distribution, thus utilizing the full information content of the data. Here, we present the formulation of such a probability distribution where the error in chemical shift prediction is described by either a Gaussian or Cauchy distribution. The methodology is demonstrated and compared to a set of empirically weighted potentials through Markov chain Monte Carlo simulations of three small proteins (ENHD, Protein G and the SMN Tudor Domain) using the PROFASI force field and the chemical shift predictor CamShift. Using a clustering-criterion for identifying the best structure, together with the addition of a solvent exposure scoring term, the simulations suggests that sampling both the structure and the uncertainties in chemical shift prediction leads more accurate structures compared to conventional methods using empirical determined weights. The Cauchy distribution, using either sampled uncertainties or predetermined weights, did, however, result in overall better convergence to the native fold, suggesting that both types of distribution might be useful in different aspects of the protein structure prediction. PMID:25825683

  6. Bayesian inference of protein structure from chemical shift data

    DEFF Research Database (Denmark)

    Bratholm, Lars Andersen; Christensen, Anders Steen; Hamelryck, Thomas Wim;

    2015-01-01

    Protein chemical shifts are routinely used to augment molecular mechanics force fields in protein structure simulations, with weights of the chemical shift restraints determined empirically. These weights, however, might not be an optimal descriptor of a given protein structure and predictive model...... Monte Carlo simulations of three small proteins (ENHD, Protein G and the SMN Tudor Domain) using the PROFASI force field and the chemical shift predictor CamShift. Using a clustering-criterion for identifying the best structure, together with the addition of a solvent exposure scoring term......, result in overall better convergence to the native fold, suggesting that both types of distribution might be useful in different aspects of the protein structure prediction....

  7. Unraveling the meaning of chemical shifts in protein NMR.

    Science.gov (United States)

    Berjanskii, Mark V; Wishart, David S

    2017-07-15

    Chemical shifts are among the most informative parameters in protein NMR. They provide wealth of information about protein secondary and tertiary structure, protein flexibility, and protein-ligand binding. In this report, we review the progress in interpreting and utilizing protein chemical shifts that has occurred over the past 25years, with a particular focus on the large body of work arising from our group and other Canadian NMR laboratories. More specifically, this review focuses on describing, assessing, and providing some historical context for various chemical shift-based methods to: (1) determine protein secondary and super-secondary structure; (2) derive protein torsion angles; (3) assess protein flexibility; (4) predict residue accessible surface area; (5) refine 3D protein structures; (6) determine 3D protein structures and (7) characterize intrinsically disordered proteins. This review also briefly covers some of the methods that we previously developed to predict chemical shifts from 3D protein structures and/or protein sequence data. It is hoped that this review will help to increase awareness of the considerable utility of NMR chemical shifts in structural biology and facilitate more widespread adoption of chemical-shift based methods by the NMR spectroscopists, structural biologists, protein biophysicists, and biochemists worldwide. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017. Published by Elsevier B.V.

  8. Calculations of proton chemical shifts in olefins and aromatics

    CERN Document Server

    Escrihuela, M C

    2000-01-01

    induced reagents on alpha,beta unsaturated ketones has also been investigated in order to deduce molecular structures and to obtain the assignment of the spectra of these molecules. A semi-empirical calculation of the partial atomic charges in organic compounds based on molecular dipole moments (CHARGE3) was developed into a model capable of predicting proton chemical shifts in a wide variety of organic compounds to a reasonable degree of accuracy. The model has been modified to include condensed aromatic hydrocarbons and substituted benzenes, alkenes, halo-monosubstituted benzenes and halo-alkenes. Within the aromatic compounds the influence of the pi electron densities and the ring current have been investigated, along with the alpha, beta and gamma effects. The model gives the first accurate calculation of the proton chemical shifts of condensed aromatic compounds and the proton substituent chemical shifts (SCS) in the benzene ring. For the data set of 55 proton chemical shifts spanning 3 ppm the rms error...

  9. Protein Structure Determination Using Chemical Shifts

    DEFF Research Database (Denmark)

    Christensen, Anders Steen

    In this thesis, a protein structure determination using chemical shifts is presented. The method is implemented in the open source PHAISTOS protein simulation framework. The method combines sampling from a generative model with a coarse-grained force field and an energy function that includes...... chemical shifts. The method is benchmarked on folding simulations of five small proteins. In four cases the resulting structures are in excellent agreement with experimental data, the fifth case fail likely due to inaccuracies in the energy function. For the Chymotrypsin Inhibitor protein, a structure...... is determined using only chemical shifts recorded and assigned through automated processes. The CARMSD to the experimental X-ray for this structure is 1.1. Å. Additionally, the method is combined with very sparse NOE-restraints and evolutionary distance restraints and tested on several protein structures >100...

  10. Protein Structure Determination Using Chemical Shifts

    DEFF Research Database (Denmark)

    Christensen, Anders Steen

    In this thesis, a protein structure determination using chemical shifts is presented. The method is implemented in the open source PHAISTOS protein simulation framework. The method combines sampling from a generative model with a coarse-grained force field and an energy function that includes...... chemical shifts. The method is benchmarked on folding simulations of five small proteins. In four cases the resulting structures are in excellent agreement with experimental data, the fifth case fail likely due to inaccuracies in the energy function. For the Chymotrypsin Inhibitor protein, a structure...

  11. Random coil chemical shift for intrinsically disordered proteins

    DEFF Research Database (Denmark)

    Kjærgaard, Magnus; Brander, Søren; Poulsen, Flemming Martin

    2011-01-01

    . Temperature has a non-negligible effect on the (13)C random coil chemical shifts, so temperature coefficients are reported for the random coil chemical shifts to allow extrapolation to other temperatures. The pH dependence of the histidine random coil chemical shifts is investigated in a titration series......, which allows the accurate random coil chemical shifts to be obtained at any pH. By correcting the random coil chemical shifts for the effects of temperature and pH, systematic biases of the secondary chemical shifts are minimized, which will improve the reliability of detection of transient secondary...

  12. Chemical Function Predictions for Tox21 Chemicals

    Data.gov (United States)

    U.S. Environmental Protection Agency — Random forest chemical function predictions for Tox21 chemicals in personal care products uses and "other" uses. This dataset is associated with the following...

  13. Development of a (13)C NMR Chemical Shift Prediction Procedure Using B3LYP/cc-pVDZ and Empirically Derived Systematic Error Correction Terms: A Computational Small Molecule Structure Elucidation Method.

    Science.gov (United States)

    Xin, Dongyue; Sader, C Avery; Chaudhary, Om; Jones, Paul-James; Wagner, Klaus; Tautermann, Christofer S; Yang, Zheng; Busacca, Carl A; Saraceno, Reginaldo A; Fandrick, Keith R; Gonnella, Nina C; Horspool, Keith; Hansen, Gordon; Senanayake, Chris H

    2017-05-19

    An accurate and efficient procedure was developed for performing (13)C NMR chemical shift calculations employing density functional theory with the gauge invariant atomic orbitals (DFT-GIAO). Benchmarking analysis was carried out, incorporating several density functionals and basis sets commonly used for prediction of (13)C NMR chemical shifts, from which the B3LYP/cc-pVDZ level of theory was found to provide accurate results at low computational cost. Statistical analyses from a large data set of (13)C NMR chemical shifts in DMSO are presented with TMS as the calculated reference and with empirical scaling parameters obtained from a linear regression analysis. Systematic errors were observed locally for key functional groups and carbon types, and correction factors were determined. The application of this process and associated correction factors enabled assignment of the correct structures of therapeutically relevant compounds in cases where experimental data yielded inconclusive or ambiguous results. Overall, the use of B3LYP/cc-pVDZ with linear scaling and correction terms affords a powerful and efficient tool for structure elucidation.

  14. Protein structure prediction using global optimization by basin-hopping with NMR shift restraints.

    Science.gov (United States)

    Hoffmann, Falk; Strodel, Birgit

    2013-01-14

    Computational methods that utilize chemical shifts to produce protein structures at atomic resolution have recently been introduced. In the current work, we exploit chemical shifts by combining the basin-hopping approach to global optimization with chemical shift restraints using a penalty function. For three peptides, we demonstrate that this approach allows us to find near-native structures from fully extended structures within 10,000 basin-hopping steps. The effect of adding chemical shift restraints is that the α and β secondary structure elements form within 1000 basin-hopping steps, after which the orientation of the secondary structure elements, which produces the tertiary contacts, is driven by the underlying protein force field. We further show that our chemical shift-restraint BH approach also works for incomplete chemical shift assignments, where the information from only one chemical shift type is considered. For the proper implementation of chemical shift restraints in the basin-hopping approach, we determined the optimal weight of the chemical shift penalty energy with respect to the CHARMM force field in conjunction with the FACTS solvation model employed in this study. In order to speed up the local energy minimization procedure, we developed a function, which continuously decreases the width of the chemical shift penalty function as the minimization progresses. We conclude that the basin-hopping approach with chemical shift restraints is a promising method for protein structure prediction.

  15. Prediction of (195) Pt NMR chemical shifts of dissolution products of H2 [Pt(OH)6 ] in nitric acid solutions by DFT methods: how important are the counter-ion effects?

    Science.gov (United States)

    Tsipis, Athanassios C; Karapetsas, Ioannis N

    2016-08-01

    (195) Pt NMR chemical shifts of octahedral Pt(IV) complexes with general formula [Pt(NO3 )n (OH)6 - n ](2-) , [Pt(NO3 )n (OH2 )6 - n ](4 - n) (n = 1-6), and [Pt(NO3 )6 - n  - m (OH)m (OH2 )n ](-2 + n - m) formed by dissolution of platinic acid, H2 [Pt(OH)6 ], in aqueous nitric acid solutions are calculated employing density functional theory methods. Particularly, the gauge-including atomic orbitals (GIAO)-PBE0/segmented all-electron relativistically contracted-zeroth-order regular approximation (SARC-ZORA)(Pt) ∪ 6-31G(d,p)(E)/Polarizable Continuum Model computational protocol performs the best. Excellent second-order polynomial plots of δcalcd ((195) Pt) versus δexptl ((195) Pt) chemical shifts and δcalcd ((195) Pt) versus the natural atomic charge QPt are obtained. Despite of neglecting relativistic and spin orbit effects the good agreement of the calculated δ (195) Pt chemical shifts with experimental values is probably because of the fact that the contribution of relativistic and spin orbit effects to computed σ(iso) (195) Pt magnetic shielding of Pt(IV) coordination compounds is effectively cancelled in the computed δ (195) Pt chemical shifts, because the relativistic corrections are expected to be similar in the complexes and the proper reference standard used. To probe the counter-ion effects on the (195) Pt NMR chemical shifts of the anionic [Pt(NO3 )n (OH)6 - n ](2-) and cationic [Pt(NO3 )n (OH2 )6 - n ](4 - n) (n = 0-3) complexes we calculated the (195) Pt NMR chemical shifts of the neutral (PyH)2 [Pt(NO3 )n (OH)6 - n ] (n = 1-6; PyH = pyridinium cation, C5 H5 NH(+) ) and [Pt(NO3 )n (H2 O)6 - n ](NO3 )4 - n (n = 0-3) complexes. Counter-anion effects are very important for the accurate prediction of the (195) Pt NMR chemical shifts of the cationic [Pt(NO3 )n (OH2 )6 - n ](4 - n) complexes, while counter-cation effects are less important for the anionic [Pt(NO3 )n (OH)6

  16. PPM-One: a static protein structure based chemical shift predictor

    Energy Technology Data Exchange (ETDEWEB)

    Li, Dawei; Brüschweiler, Rafael, E-mail: bruschweiler.1@osu.edu [The Ohio State University, Campus Chemical Instrument Center (United States)

    2015-07-15

    We mined the most recent editions of the BioMagResDataBank and the protein data bank to parametrize a new empirical knowledge-based chemical shift predictor of protein backbone atoms using either a linear or an artificial neural network model. The resulting chemical shift predictor PPM-One accepts a single static 3D structure as input and emulates the effect of local protein dynamics via interatomic steric contacts. Furthermore, the chemical shift prediction was extended to most side-chain protons and it is found that the prediction accuracy is at a level allowing an independent assessment of stereospecific assignments. For a previously established set of test proteins some overall improvement was achieved over current top-performing chemical shift prediction programs.

  17. Synthesis, antimicrobial evaluation and theoretical prediction of NMR chemical shifts of thiazole and selenazole derivatives with high antifungal activity against Candida spp.

    Science.gov (United States)

    Łączkowski, Krzysztof Z.; Motylewska, Katarzyna; Baranowska-Łączkowska, Angelika; Biernasiuk, Anna; Misiura, Konrad; Malm, Anna; Fernández, Berta

    2016-03-01

    Synthesis and investigation of antimicrobial activities of novel thiazoles and selenazoles is presented. Their structures were determined using NMR, FAB(+)-MS, HRMS and elemental analyses. To support the experiment, theoretical calculations of the 1H NMR shifts were carried out for representative systems within the DFT B3LYP/6-311++G** approximation which additionally confirmed the structure of investigated compounds. Among the derivatives, compounds 4b, 4h, 4j and 4l had very strong activity against reference strains of Candida albicans ATCC and Candida parapsilosis ATCC 22019 with MIC = 0.49-7.81 μg/ml. In the case of compounds 4b, 4c, 4h - 4j and 4l, the activity was very strong against of Candida spp. isolated from clinical materials, i.e. C. albicans, Candida krusei, Candida inconspicua, Candida famata, Candida lusitaniae, Candida sake, C. parapsilosis and Candida dubliniensis with MIC = 0.24-15.62 μg/ml. The activity of several of these was similar to the activity of commonly used antifungal agent fluconazole. Additionally, compounds 4m - 4s were found to be active against Gram-positive bacteria, both pathogenic staphylococci Staphylococcus aureus ATCC with MIC = 31.25-125 μg/ml and opportunistic bacteria, such as Staphylococcus epidermidis ATCC 12228 and Micrococcus luteus ATCC 10240 with MIC = 7.81-31.25 μg/ml.

  18. Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with Application to Chemical Shift Predictions

    DEFF Research Database (Denmark)

    Svendsen, Casper Steinmann; Bratholm, L.A.; Olsen, Jógvan Magnus Haugaard

    2017-01-01

    Full-protein nuclear magnetic resonance (NMR) shielding constants based on ab initio calculations are desirable, because they can assist in elucidating protein structures from NMR experiments. In this work, we present NMR shielding constants computed using a new automated fragmentation (J. Phys. ...... can obtain a representative subset of snapshots that gives the smallest predicted error, compared to experiment. Finally, we use this subset of snapshots to calculate the NMR shielding constants at the PE-KT3/pcSseg-2 level of theory for all atoms in the protein GB3....

  19. Shifting wavelengths of ultraweak photon emissions from dying melanoma cells: their chemical enhancement and blocking are predicted by Cosic's theory of resonant recognition model for macromolecules.

    Science.gov (United States)

    Dotta, Blake T; Murugan, Nirosha J; Karbowski, Lukasz M; Lafrenie, Robert M; Persinger, Michael A

    2014-02-01

    During the first 24 h after removal from incubation, melanoma cells in culture displayed reliable increases in emissions of photons of specific wavelengths during discrete portions of this interval. Applications of specific filters revealed marked and protracted increases in infrared (950 nm) photons about 7 h after removal followed 3 h later by marked and protracted increases in near ultraviolet (370 nm) photon emissions. Specific wavelengths within the visible (400 to 800 nm) peaked 12 to 24 h later. Specific activators or inhibitors for specific wavelengths based upon Cosic's resonant recognition model elicited either enhancement or diminishment of photons at the specific wavelength as predicted. Inhibitors or activators predicted for other wavelengths, even within 10 nm, were less or not effective. There is now evidence for quantitative coupling between the wavelength of photon emissions and intrinsic cellular chemistry. The results are consistent with initial activation of signaling molecules associated with infrared followed about 3 h later by growth and protein-structural factors associated with ultraviolet. The greater-than-expected photon counts compared with raw measures through the various filters, which also function as reflective material to other photons, suggest that photons of different wavelengths might be self-stimulatory and could play a significant role in cell-to-cell communication.

  20. Is the Lamb shift chemically significant?

    Science.gov (United States)

    Dyall, Kenneth G.; Bauschlicher, Charles W., Jr.; Schwenke, David W.; Pyykko, Pekka; Arnold, James (Technical Monitor)

    2001-01-01

    The contribution of the Lamb shift to the atomization energies of some prototype molecules, BF3, AlF3, and GaF3, is estimated by a perturbation procedure. It is found to be in the range of 3-5% of the one-electron scalar relativistic contribution to the atomization energy. The maximum absolute value is 0.2 kcal/mol for GaF3. These sample calculations indicate that the Lamb shift is probably small enough to be neglected for energetics of molecules containing light atoms if the target accuracy is 1 kcal/mol, but for higher accuracy calculations and for molecules containing heavy elements it must be considered.

  1. Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

    DEFF Research Database (Denmark)

    Christensen, Anders Steen; Linnet, Troels Emtekær; Borg, Mikael;

    2013-01-01

    We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level...... QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift...

  2. Structure-based predictions of 13C-NMR chemical shifts for a series of 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indoles derivatives using GA-based MLR method

    Science.gov (United States)

    Ghavami, Raouf; Sadeghi, Faridoon; Rasouli, Zolikha; Djannati, Farhad

    2012-12-01

    Experimental values for the 13C NMR chemical shifts (ppm, TMS = 0) at 300 K ranging from 96.28 ppm (C4' of indole derivative 17) to 159.93 ppm (C4' of indole derivative 23) relative to deuteride chloroform (CDCl3, 77.0 ppm) or dimethylsulfoxide (DMSO, 39.50 ppm) as internal reference in CDCl3 or DMSO-d6 solutions have been collected from literature for thirty 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indole derivatives containing different substituted groups. An effective quantitative structure-property relationship (QSPR) models were built using hybrid method combining genetic algorithm (GA) based on stepwise selection multiple linear regression (SWS-MLR) as feature-selection tools and correlation models between each carbon atom of indole derivative and calculated descriptors. Each compound was depicted by molecular structural descriptors that encode constitutional, topological, geometrical, electrostatic, and quantum chemical features. The accuracy of all developed models were confirmed using different types of internal and external procedures and various statistical tests. Furthermore, the domain of applicability for each model which indicates the area of reliable predictions was defined.

  3. Identify Beta-Hairpin Motifs with Quadratic Discriminant Algorithm Based on the Chemical Shifts.

    Science.gov (United States)

    YongE, Feng; GaoShan, Kou

    2015-01-01

    Successful prediction of the beta-hairpin motif will be helpful for understanding the of the fold recognition. Some algorithms have been proposed for the prediction of beta-hairpin motifs. However, the parameters used by these methods were primarily based on the amino acid sequences. Here, we proposed a novel model for predicting beta-hairpin structure based on the chemical shift. Firstly, we analyzed the statistical distribution of chemical shifts of six nuclei in not beta-hairpin and beta-hairpin motifs. Secondly, we used these chemical shifts as features combined with three algorithms to predict beta-hairpin structure. Finally, we achieved the best prediction, namely sensitivity of 92%, the specificity of 94% with 0.85 of Mathew's correlation coefficient using quadratic discriminant analysis algorithm, which is clearly superior to the same method for the prediction of beta-hairpin structure from 20 amino acid compositions in the three-fold cross-validation. Our finding showed that the chemical shift is an effective parameter for beta-hairpin prediction, suggesting the quadratic discriminant analysis is a powerful algorithm for the prediction of beta-hairpin.

  4. Counterion influence on chemical shifts in strychnine salts

    Energy Technology Data Exchange (ETDEWEB)

    Metaxas, Athena E.; Cort, John R.

    2013-05-01

    The highly toxic plant alkaloid strychnine is often isolated in the form of the anion salt of its protonated tertiary amine. Here we characterize the relative influence of different counterions on 1H and 13C chemical shifts in several strychnine salts in D2O, methanol-d4 (CD3OD) and chloroform-d (CDCl3) solvents. In organic solvents, but not in water, substantial variation in chemical shifts of protons near the tertiary amine was observed among different salts. These secondary shifts reveal differences in the way each anion influences electronic structure within the protonated amine. The distributions of secondary shifts allow salts to be easily distinguished from each other as well as from the free base form. The observed effects are much greater in organic solvents than in water. Slight concentration-dependence in chemical shifts of some protons near the amine was observed for two salts in CDCl3, but this effect is small compared to the influence of the counterion. Distinct chemical shifts in different salt forms of the same compound may be useful as chemical forensic signatures for source attribution and sample matching of alkaloids such as strychnine and possibly other organic acid and base salts.

  5. Counterion influence on chemical shifts in strychnine salts.

    Science.gov (United States)

    Metaxas, Athena E; Cort, John R

    2013-05-01

    The highly toxic plant alkaloid strychnine is often isolated in the form of the anion salt of its protonated tertiary amine. Here, we characterize the relative influence of different counterions on (1)H and (13)C chemical shifts in several strychnine salts in D2O, methanol-d4 (CD3OD), and chloroform-d (CDCl3) solvents. In organic solvents but not in water, substantial variation in chemical shifts of protons near the tertiary amine was observed among different salts. These secondary shifts reveal differences in the way each anion influences electronic structure within the protonated amine. The distributions of secondary shifts allow salts to be easily distinguished from each other as well as from the free base form. Slight concentration dependence in chemical shifts of some protons near the amine was observed for two salts in CDCl3, but this effect is small compared with the influence of the counterion. Distinct chemical shifts in different salt forms of the same compound may be useful as chemical forensic signatures for source attribution and sample matching of alkaloids such as strychnine and possibly other organic acid and base salts. Copyright © 2013 John Wiley & Sons, Ltd.

  6. Chemical shift MRI can aid in the diagnosis of indeterminate skeletal lesions of the spine

    Energy Technology Data Exchange (ETDEWEB)

    Douis, H. [University Hospital Birmingham, Department of Radiology, Birmingham (United Kingdom); Royal Orthopaedic Hospital, Department of Radiology, Birmingham (United Kingdom); Davies, A.M. [Royal Orthopaedic Hospital, Department of Radiology, Birmingham (United Kingdom); Jeys, L. [Royal Orthopaedic Hospital, Department of Orthopaedic Oncology, Birmingham (United Kingdom); Sian, P. [Royal Orthopaedic Hospital, Department of Spinal Surgery and Spinal Oncology, Birmingham (United Kingdom)

    2016-04-15

    To evaluate the role of chemical shift MRI in the characterisation of indeterminate skeletal lesions of the spine as benign or malignant. Fifty-five patients (mean age 54.7 years) with 57 indeterminate skeletal lesions of the spine were included in this retrospective study. In addition to conventional MRI at 3 T which included at least sagittal T1WI and T2WI/STIR sequences, patients underwent chemical shift MRI. A cut-off value with a signal drop-out of 20 % was used to differentiate benign lesions from malignant lesions (signal drop-out <20 % being malignant). There were 45 benign lesions and 12 malignant lesions. Chemical shift imaging correctly diagnosed 33 of 45 lesions as benign and 11 of 12 lesions as malignant. In contrast, there were 12 false positive cases and 1 false negative case based on chemical shift MRI. This yielded a sensitivity of 91.7 %, a specificity of 73.3 %, a negative predictive value of 97.1 %, a positive predictive value of 47.8 % and a diagnostic accuracy of 82.5 %. Chemical shift MRI can aid in the characterisation of indeterminate skeletal lesions of the spine in view of its high sensitivity in diagnosing malignant lesions. Chemical shift MRI can potentially avoid biopsy in a considerable percentage of patients with benign skeletal lesions of the spine. (orig.)

  7. Theoretical Modeling of 99 Tc NMR Chemical Shifts

    Energy Technology Data Exchange (ETDEWEB)

    Hall, Gabriel B.; Andersen, Amity; Washton, Nancy M.; Chatterjee, Sayandev; Levitskaia, Tatiana G.

    2016-09-06

    Technetium (Tc) displays a rich chemistry due to the wide range of oxidation states (from -I to +VII) and ability to form coordination compounds. Determination of Tc speciation in complex mixtures is a major challenge, and 99Tc NMR spec-troscopy is widely used to probe chemical environments of Tc in odd oxidation states. However interpretation of the 99Tc NMR data is hindered by the lack of reference compounds. DFT computations can help fill this gap, but to date few com-putational studies have focused on 99Tc NMR of compounds and complexes. This work systematically evaluates the inclu-sion small percentages of Hartree-Fock exchange correlation and relativistic effects in DFT computations to support in-terpretation of the 99Tc NMR spectra. Hybrid functionals are found to perform better than their pure GGA counterparts, and non-relativistic calculations have been found to generally show a lower mean absolute deviation from experiment. Overall non-relativistic PBE0 and B3PW91 calculations are found to most accurately predict 99Tc NMR chemical shifts.

  8. Random-coil chemical shifts of phosphorylated amino acids

    Energy Technology Data Exchange (ETDEWEB)

    Bienkiewicz, Ewa A.; Lumb, Kevin J. [Colorado State University, Department of Biochemistry and Molecular Biology (United States)

    1999-11-15

    The {sup 1}H, {sup 13}C, {sup 15}N and {sup 31} P random-coil chemical shifts and phosphate pK{sub a} values of the phosphorylated amino acids pSer, pThr and pTyr in the protected peptide Ac-Gly-Gly-X-Gly-Gly-NH{sub 2} have been obtained in water at 25 deg. C over the pH range 2 to 9. Analysis of ROESY spectra indicates that the peptides are unstructured. Phosphorylation induces changes in random-coil chemical shifts, some of which are comparable to those caused by secondary structure formation, and are therefore significant in structural analyses based on the chemical shift.

  9. Protein Structure Validation and Refinement Using Chemical Shifts Derived from Quantum Mechanics

    DEFF Research Database (Denmark)

    Bratholm, Lars Andersen

    to within 3 A. Furthermore, a fast quantum mechanics based chemical shift predictor was developed together with methodology for using chemical shifts in structure simulations. The developed predictor was used for renement of several protein structures and for reducing the computational cost of quantum...... mechanics / molecular mechanics (QM/MM) computations of chemical shieldings. Several improvements to the predictor is ongoing, where among other things, kernel based machine learning techniques have successfully been used to improve the quantum mechanical level of theory used in the predictions....... experimental data in the form of chemical shifts, as well as distance restraints obtained either experimentally or from sequence co-evolution. Of notable results, One of the determined structures, aKMT, was not solved experimentally at the time, but was found to match the recently published X-ray structure...

  10. Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

    CERN Document Server

    Christensen, Anders S; Borg, Mikael; Boomsma, Wouter; Lindorff-Larsen, Kresten; Hamelryck, Thomas; Jensen, Jan H

    2013-01-01

    We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (h3JNC') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to refine protein structures to this...

  11. Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

    DEFF Research Database (Denmark)

    Christensen, Anders Steen; Linnet, Troels Emtekær; Borg, Mikael;

    2013-01-01

    We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level...

  12. Estimation of optical chemical shift in nuclear spin optical rotation

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Fang [Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China); Yao, Guo-hua [Key Laboratory of Ion Beam Bio-engineering, Institute of Technical Biology and Agriculture Engineering, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031 (China); He, Tian-jing [Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China); Chen, Dong-ming, E-mail: dmchen@ustc.edu.cn [Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China); Liu, Fan-chen, E-mail: fcliu@ustc.edu.cn [Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026 (China)

    2014-05-19

    Highlights: • Analytical theory of nuclear spin optical rotation (NSOR) is further developed. • Derive formula of NSOR ratio R between different nuclei in a same molecule. • Calculated results of R agree with the experiments. • Analyze influence factors on R and chemical distinction by NSOR. - Abstract: A recently proposed optical chemical shift in nuclear spin optical rotation (NSOR) is studied by theoretical comparison of NSOR magnitude between chemically non-equivalent or different element nuclei in the same molecule. Theoretical expressions of the ratio R between their NSOR magnitudes are derived by using a known semi-empirical formula of NSOR. Taking methanol, tri-ethyl-phosphite and 2-methyl-benzothiazole as examples, the ratios R are calculated and the results approximately agree with the experiments. Based on those, the important influence factors on R and chemical distinction by NSOR are discussed.

  13. Magnetic shift of the chemical freezeout and electric charge fluctuations

    CERN Document Server

    Fukushima, Kenji

    2016-01-01

    We discuss the effect of a strong magnetic field on the chemical freezeout points in the ultra-relativistic heavy-ion collision. As a result of the inverse magnetic catalysis or the magnetic inhibition, the crossover onset to hot and dense matter out of quarks and gluons should be shifted to a lower temperature. To quantify this shift we employ the hadron resonance gas model and an empirical condition for the chemical freezeout. We point out that the charged particle abundances are significantly affected by the magnetic field so that the electric charge fluctuation is largely enhanced especially at high baryon density. The charge conservation partially cancels the enhancement but our calculation shows that the electric charge fluctuation could serve as a magnetometer.

  14. Shift costs of predictable and unexpected set shifting in young and older adults.

    NARCIS (Netherlands)

    van Asselen, M.; Ridderinkhof, K.R.

    2000-01-01

    Examined the extent to which predictable, unexpected, and mixed costs associated with task shifts are subject to the effects of aging. 17 university students (aged 18-25 yrs) and 17 community residents (aged 66-81 yrs) completed a series of pure and mixed tasks. Results show that the costs of an

  15. Learning to predict chemical reactions.

    Science.gov (United States)

    Kayala, Matthew A; Azencott, Chloé-Agathe; Chen, Jonathan H; Baldi, Pierre

    2011-09-26

    Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry data set consisting of 1630 full multistep reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top-ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of nonproductive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system

  16. Database proton NMR chemical shifts for RNA signal assignment and validation

    Energy Technology Data Exchange (ETDEWEB)

    Barton, Shawn; Heng Xiao [University of Maryland, Baltimore County, Howard Hughes Medical Institute (United States); Johnson, Bruce A., E-mail: bruce@onemoonscientific.com [University of Maryland, Baltimore County, Department of Chemistry and Biochemistry (United States); Summers, Michael F., E-mail: summers@hhmi.umbc.edu [University of Maryland, Baltimore County, Howard Hughes Medical Institute (United States)

    2013-01-15

    The Biological Magnetic Resonance Data Bank contains NMR chemical shift depositions for 132 RNAs and RNA-containing complexes. We have analyzed the {sup 1}H NMR chemical shifts reported for non-exchangeable protons of residues that reside within A-form helical regions of these RNAs. The analysis focused on the central base pair within a stretch of three adjacent base pairs (BP triplets), and included both Watson-Crick (WC; G:C, A:U) and G:U wobble pairs. Chemical shift values were included for all 4{sup 3} possible WC-BP triplets, as well as 137 additional triplets that contain one or more G:U wobbles. Sequence-dependent chemical shift correlations were identified, including correlations involving terminating base pairs within the triplets and canonical and non-canonical structures adjacent to the BP triplets (i.e. bulges, loops, WC and non-WC BPs), despite the fact that the NMR data were obtained under different conditions of pH, buffer, ionic strength, and temperature. A computer program (RNAShifts) was developed that enables convenient comparison of RNA {sup 1}H NMR assignments with database predictions, which should facilitate future signal assignment/validation efforts and enable rapid identification of non-canonical RNA structures and RNA-ligand/protein interaction sites.

  17. Phylogeny predicts future habitat shifts due to climate change.

    Science.gov (United States)

    Kuntner, Matjaž; Năpăruş, Magdalena; Li, Daiqin; Coddington, Jonathan A

    2014-01-01

    Taxa may respond differently to climatic changes, depending on phylogenetic or ecological effects, but studies that discern among these alternatives are scarce. Here, we use two species pairs from globally distributed spider clades, each pair representing two lifestyles (generalist, specialist) to test the relative importance of phylogeny versus ecology in predicted responses to climate change. We used a recent phylogenetic hypothesis for nephilid spiders to select four species from two genera (Nephilingis and Nephilengys) that match the above criteria, are fully allopatric but combined occupy all subtropical-tropical regions. Based on their records, we modeled each species niche spaces and predicted their ecological shifts 20, 40, 60, and 80 years into the future using customized GIS tools and projected climatic changes. Phylogeny better predicts the species current ecological preferences than do lifestyles. By 2080 all species face dramatic reductions in suitable habitat (54.8-77.1%) and adapt by moving towards higher altitudes and latitudes, although at different tempos. Phylogeny and life style explain simulated habitat shifts in altitude, but phylogeny is the sole best predictor of latitudinal shifts. Models incorporating phylogenetic relatedness are an important additional tool to predict accurately biotic responses to global change.

  18. Sequence correction of random coil chemical shifts: correlation between neighbor correction factors and changes in the Ramachandran distribution

    Energy Technology Data Exchange (ETDEWEB)

    Kjaergaard, Magnus; Poulsen, Flemming M., E-mail: fmpoulsen@bio.ku.dk [University of Copenhagen, Department of Biology (Denmark)

    2011-06-15

    Random coil chemical shifts are necessary for secondary chemical shift analysis, which is the main NMR method for identification of secondary structure in proteins. One of the largest challenges in the determination of random coil chemical shifts is accounting for the effect of neighboring residues. The contributions from the neighboring residues are typically removed by using neighbor correction factors determined based on each residue's effect on glycine chemical shifts. Due to its unusual conformational freedom, glycine may be particularly unrepresentative for the remaining residue types. In this study, we use random coil peptides containing glutamine instead of glycine to determine the random coil chemical shifts and the neighbor correction factors. The resulting correction factors correlate to changes in the populations of the major wells in the Ramachandran plot, which demonstrates that changes in the conformational ensemble are an important source of neighbor effects in disordered proteins. Glutamine derived random coil chemical shifts and correction factors modestly improve our ability to predict {sup 13}C chemical shifts of intrinsically disordered proteins compared to existing datasets, and may thus improve the identification of small populations of transient structure in disordered proteins.

  19. Protein structural information derived from NMR chemical shift with the neural network program TALOS-N.

    Science.gov (United States)

    Shen, Yang; Bax, Ad

    2015-01-01

    Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trained to extract backbone and side-chain torsion angles from (1)H, (15)N, and (13)C shifts. The program is quite robust and typically yields backbone torsion angles for more than 90 % of the residues and side-chain χ 1 rotamer information for about half of these, in addition to reliably predicting secondary structure. The use of TALOS-N is illustrated for the protein DinI, and torsion angles obtained by TALOS-N analysis from the measured chemical shifts of its backbone and (13)C(β) nuclei are compared to those seen in a prior, experimentally determined structure. The program is also particularly useful for generating torsion angle restraints, which then can be used during standard NMR protein structure calculations.

  20. Modeling proteins using a super-secondary structure library and NMR chemical shift information.

    Science.gov (United States)

    Menon, Vilas; Vallat, Brinda K; Dybas, Joseph M; Fiser, Andras

    2013-06-04

    A remaining challenge in protein modeling is to predict structures for sequences with no sequence similarity to any experimentally solved structure. Based on earlier observations, the library of protein backbone supersecondary structure motifs (Smotifs) saturated about a decade ago. Therefore, it should be possible to build any structure from a combination of existing Smotifs with the help of limited experimental data that are sufficient to relate the backbone conformations of Smotifs between target proteins and known structures. Here, we present a hybrid modeling algorithm that relies on an exhaustive Smotif library and on nuclear magnetic resonance chemical shift patterns without any input of primary sequence information. In a test of 102 proteins, the algorithm delivered 90 homology-model-quality models, among them 24 high-quality ones, and a topologically correct solution for almost all cases. The current approach opens a venue to address the modeling of larger protein structures for which chemical shifts are available.

  1. Effects of Protein-pheromone Complexation on Correlated Chemical Shift Modulations

    Energy Technology Data Exchange (ETDEWEB)

    Perazzolo, Chiara; Wist, Julien [Ecole Polytechnique Federale de Lausanne, Institut des Sciences et Ingenierie Chimiques (Switzerland); Loth, Karine; Poggi, Luisa [Ecole Normale Superieure, Departement de chimie, associe au CNRS (France); Homans, Steve [University of Leeds, School of Biochemistry and Microbiology (United Kingdom); Bodenhausen, Geoffrey [Ecole Polytechnique Federale de Lausanne, Institut des Sciences et Ingenierie Chimiques (Switzerland)], E-mail: Geoffrey.Bodenhausen@ens.fr

    2005-12-15

    Major urinary protein (MUP) is a pheromone-carrying protein of the lipocalin family. Previous studies by isothermal titration calorimetry (ITC) show that the affinity of MUP for the pheromone 2-methoxy-3-isobutylpyrazine (IBMP) is mainly driven by enthalpy, with a small unfavourable entropic contribution. Entropic terms can be attributed in part to changes in internal motions of the protein upon binding. Slow internal motions can lead to correlated or anti-correlated modulations of the isotropic chemical shifts of carbonyl C' and amide N nuclei. Correlated chemical shift modulations (CSM/CSM) in MUP have been determined by measuring differences of the transverse relaxation rates of zero- and double-quantum coherences ZQC{l_brace}C'N{r_brace} and DQC{l_brace}C'N{r_brace}, and by accounting for the effects of correlated fluctuations of dipole-dipole couplings (DD/DD) and chemical shift anisotropies (CSA/CSA). The latter can be predicted from tensor parameters of C' and N nuclei that have been determined in earlier work. The effects of complexation on slow time-scale protein dynamics can be determined by comparing the temperature dependence of the relaxation rates of APO-MUP (i.e., without ligand) and HOLO-MUP (i.e., with IBMP as a ligand)

  2. Relationship between chemical shift value and accessible surface area for all amino acid atoms

    Directory of Open Access Journals (Sweden)

    Rieping Wolfgang

    2009-04-01

    Full Text Available Abstract Background Chemical shifts obtained from NMR experiments are an important tool in determining secondary, even tertiary, protein structure. The main repository for chemical shift data is the BioMagResBank, which provides NMR-STAR files with this type of information. However, it is not trivial to link this information to available coordinate data from the PDB for non-backbone atoms due to atom and chain naming differences, as well as sequence numbering changes. Results We here describe the analysis of a consistent set of chemical shift and coordinate data, in which we focus on the relationship between the per-atom solvent accessible surface area (ASA in the reported coordinates and their reported chemical shift value. The data is available online on http://www.ebi.ac.uk/pdbe/docs/NMR/shiftAnalysis/index.html. Conclusion Atoms with zero per-atom ASA have a significantly larger chemical shift dispersion and often have a different chemical shift distribution compared to those that are solvent accessible. With higher per-atom ASA, the chemical shift values also tend towards random coil values. The per-atom ASA, although not the determinant of the chemical shift, thus provides a way to directly correlate chemical shift information to the atomic coordinates.

  3. Applications of Chemical Shift Imaging to Marine Sciences

    Directory of Open Access Journals (Sweden)

    Haakil Lee

    2010-08-01

    Full Text Available The successful applications of magnetic resonance imaging (MRI in medicine are mostly due to the non-invasive and non-destructive nature of MRI techniques. Longitudinal studies of humans and animals are easily accomplished, taking advantage of the fact that MRI does not use harmful radiation that would be needed for plain film radiographic, computerized tomography (CT or positron emission (PET scans. Routine anatomic and functional studies using the strong signal from the most abundant magnetic nucleus, the proton, can also provide metabolic information when combined with in vivo magnetic resonance spectroscopy (MRS. MRS can be performed using either protons or hetero-nuclei (meaning any magnetic nuclei other than protons or 1H including carbon (13C or phosphorus (31P. In vivo MR spectra can be obtained from single region ofinterest (ROI or voxel or multiple ROIs simultaneously using the technique typically called chemical shift imaging (CSI. Here we report applications of CSI to marine samples and describe a technique to study in vivo glycine metabolism in oysters using 13C MRS 12 h after immersion in a sea water chamber dosed with [2-13C]-glycine. This is the first report of 13C CSI in a marine organism.

  4. Diagnostic value of chemical shift artifact in distinguishing benign lymphadenopathy

    Energy Technology Data Exchange (ETDEWEB)

    Farshchian, Nazanin, E-mail: farshchian.n@gmail.com [Department of Radiology, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Tamari, Saghar; Farshchian, Negin [Department of Radiology, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Madani, Hamid [Department of Pathology, Imam-Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Rezaie, Mansour [Department of Biostatistics, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Mohammadi-Motlagh, Hamid-Reza, E-mail: mohammadimotlagh@gmail.com [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of)

    2011-11-15

    Purpose: Today, distinguishing metastatic lymph nodes from secondary benign inflammatory ones via using non-invasive methods is increasingly favorable. In this study, the diagnostic value of chemical shift artifact (CSA) in magnetic resonance imaging (MRI) was evaluated to distinguish benign lymphadenopathy. Subjects and methods: A prospective intraindividual internal review board-approved study was carried out on 15 men and 15 women having lymphadenopathic lesions in different locations of the body who underwent contrast-enhanced dynamic MR imaging at 1.5 T. Then, the imaging findings were compared with pathology reports, using the statistics analyses. Results: Due to the findings of the CSA existence in MRI, a total of 56.7% of the studied lesions (17 of 30) were identified as benign lesions and the rest were malignant, whereas the pathology reports distinguished twelve malignant and eighteen benign cases. Furthermore, the CSA findings comparing the pathology reports indicated that CSA, with confidence of 79.5%, has a significant diagnostic value to differentiate benign lesions from malignant ones. Conclusion: Our study demonstrated that CSA in MR imaging has a suitable diagnostic potential nearing readiness for clinical trials. Furthermore, CSA seems to be a feasible tool to differentiate benign lymph nodes from malignant ones; however, further studies including larger numbers of patients are required to confirm our results.

  5. Predictive toxicology of chemicals and database mining

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The toxic chemicals from the database Registry of Toxic Effects of Chemical Substances (RTECS) were analyzed by structural similarity comparison, which shows that the structure patterns or characteristics of toxic chemicals exist in a sufficiently large database. Then, a two-step strategy was proposed to explore noncongeneric toxic chemicals in the database: the screening of structure patterns by similarity comparison and the derivation of detailed relationship between structure and activity by using comparative molecular field analysis (CoMFA) of Quantitative Structure-Activity Relationship (QSAR) technologies. From the performance of the procedure, such a stepwise scheme is demonstrated to be feasible and effective to mine a database of toxic chemicals. It can be anticipated that database mining of toxic chemicals will be a new area for predictive toxicology of chemicals.

  6. Prediction of the environmental fate of chemicals.

    Science.gov (United States)

    Vighi, M; Calamari, D

    1993-01-01

    An overview is presented of the possibilities of applying multimedia compartmental evaluative models, and in particular the fugacity approach, to predict the environmental distribution and fate of organic chemicals. The use of this predictive approach for the evaluation of exposure to pollutants in the aquatic system is described, with reference to different environments or discharge patterns (surface and groundwaters, point and diffuse sources of pollution). The value and limitations of this approach are noted and the need for more research to improve predictive capability and practical usefulness is indicated. Finally some practical applications of evaluative models in the proposal of quantitative indices for ecotoxicological evaluation of risk from chemicals are described.

  7. Cerebral asymmetry in twins: predictions of the right shift theory.

    Science.gov (United States)

    Annett, Marian

    2003-01-01

    A study of the heritability of lobar brain volumes in twins has introduced a new approach to questions about the genetics of cerebral asymmetry. In addition to the classic comparison between monozygotic (MZ) and dizygotic (DZ) twins, a contrast was made between pairs of two right-handers (RR pairs) and pairs including one or more non-right-hander (non-RR pairs), in the light of the right shift (RS) theory of handedness. This paper explains the predictions of the RS model for pair concordance for genotype, cerebral asymmetry and handedness in healthy MZ and DZ twins. It shows how predictions for cerebral asymmetry vary between RR and non-RR pairs over a range of incidences of left-handedness. Although MZ twins are always concordant for genotype and DZ twins may be discordant, differences for handedness and cerebral asymmetry are expected to be small, consistent with the scarcity of significant effects in the literature. Marked differences between RR and non-RR pairs are predicted at all levels of incidence, the differences slightly larger in MZ than DZ pairs.

  8. Magnetic couplings in the chemical shift of paramagnetic NMR.

    Science.gov (United States)

    Vaara, Juha; Rouf, Syed Awais; Mareš, Jiří

    2015-10-13

    We apply the Kurland-McGarvey (J. Magn. Reson. 1970, 2, 286) theory for the NMR shielding of paramagnetic molecules, particularly its special case limited to the ground-state multiplet characterized by zero-field splitting (ZFS) interaction of the form S·D·S. The correct formulation for this problem was recently presented by Soncini and Van den Heuvel (J. Chem. Phys. 2013, 138, 054113). With the effective electron spin quantum number S, the theory involves 2S+1 states, of which all but one are low-lying excited states, between which magnetic couplings take place by Zeeman and hyperfine interactions. We investigate these couplings as a function of temperature, focusing on both the high- and low-temperature behaviors. As has been seen in work by others, the full treatment of magnetic couplings is crucial for a realistic description of the temperature behavior of NMR shielding up to normal measurement temperatures. At high temperatures, depending on the magnitude of ZFS, the effect of magnetic couplings diminishes, and the Zeeman and hyperfine interactions become effectively averaged in the thermally occupied states of the multiplet. At still higher temperatures, the ZFS may be omitted altogether, and the shielding properties may be evaluated using a doublet-like formula, with all the 2S+1 states becoming effectively degenerate at the limit of vanishing magnetic field. We demonstrate these features using first-principles calculations of Ni(II), Co(II), Cr(II), and Cr(III) complexes, which have ZFS of different sizes and signs. A non-monotonic inverse temperature dependence of the hyperfine shift is predicted for axially symmetric integer-spin systems with a positive D parameter of ZFS. This is due to the magnetic coupling terms that are proportional to kT at low temperatures, canceling the Curie-type 1/kT prefactor of the hyperfine shielding in this case.

  9. Modelling Chemical Reasoning to Predict Reactions

    OpenAIRE

    Segler, Marwin H. S.; Waller, Mark P.

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outpe...

  10. Deuterium isotope effects on 13C chemical shifts of 10-Hydroxybenzo[h]quinolines

    DEFF Research Database (Denmark)

    Hansen, Poul Erik; Kamounah, Fadhil S.; Gryko, Daniel T.

    2013-01-01

    to be negative, indicating transmission via the hydrogen bond. In addition unusual long-range effects are seen. Structures, NMR chemical shifts and changes in nuclear shieldings upon deuteriation are calculated using DFT methods. Two-bond deuterium isotope effects on 13C chemical shifts are correlated......Deuterium isotope effects on 13C-NMR chemical shifts are investigated in a series of 10-hydroxybenzo[h]quinolines (HBQ’s) The OH proton is deuteriated. The isotope effects on 13C chemical shifts in these hydrogen bonded systems are rather unusual. The formal four-bond effects are found...... with calculated OH stretching frequencies. Isotope effects on chemical shifts are calculated for systems with OH exchanged by OD. Hydrogen bond potentials are discussed. New and more soluble nitro derivatives are synthesized....

  11. Two-dimensional NMR measurement and point dipole model prediction of paramagnetic shift tensors in solids

    Energy Technology Data Exchange (ETDEWEB)

    Walder, Brennan J.; Davis, Michael C.; Grandinetti, Philip J. [Department of Chemistry, Ohio State University, 100 West 18th Avenue, Columbus, Ohio 43210 (United States); Dey, Krishna K. [Department of Physics, Dr. H. S. Gour University, Sagar, Madhya Pradesh 470003 (India); Baltisberger, Jay H. [Division of Natural Science, Mathematics, and Nursing, Berea College, Berea, Kentucky 40403 (United States)

    2015-01-07

    A new two-dimensional Nuclear Magnetic Resonance (NMR) experiment to separate and correlate the first-order quadrupolar and chemical/paramagnetic shift interactions is described. This experiment, which we call the shifting-d echo experiment, allows a more precise determination of tensor principal components values and their relative orientation. It is designed using the recently introduced symmetry pathway concept. A comparison of the shifting-d experiment with earlier proposed methods is presented and experimentally illustrated in the case of {sup 2}H (I = 1) paramagnetic shift and quadrupolar tensors of CuCl{sub 2}⋅2D{sub 2}O. The benefits of the shifting-d echo experiment over other methods are a factor of two improvement in sensitivity and the suppression of major artifacts. From the 2D lineshape analysis of the shifting-d spectrum, the {sup 2}H quadrupolar coupling parameters are 〈C{sub q}〉 = 118.1 kHz and 〈η{sub q}〉 = 0.88, and the {sup 2}H paramagnetic shift tensor anisotropy parameters are 〈ζ{sub P}〉 = − 152.5 ppm and 〈η{sub P}〉 = 0.91. The orientation of the quadrupolar coupling principal axis system (PAS) relative to the paramagnetic shift anisotropy principal axis system is given by (α,β,γ)=((π)/2 ,(π)/2 ,0). Using a simple ligand hopping model, the tensor parameters in the absence of exchange are estimated. On the basis of this analysis, the instantaneous principal components and orientation of the quadrupolar coupling are found to be in excellent agreement with previous measurements. A new point dipole model for predicting the paramagnetic shift tensor is proposed yielding significantly better agreement than previously used models. In the new model, the dipoles are displaced from nuclei at positions associated with high electron density in the singly occupied molecular orbital predicted from ligand field theory.

  12. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

    Science.gov (United States)

    Balasubramanian, A.; Shamsuddin, R.; Prabhakaran, B.; Sawant, A.

    2017-03-01

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%) (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  13. Ab Initio Calculation of Nuclear Magnetic Resonance Chemical Shift Anisotropy Tensors 1. Influence of Basis Set on the Calculation of 31P Chemical Shifts

    Energy Technology Data Exchange (ETDEWEB)

    Alam, T.M.

    1998-09-01

    The influence of changes in the contracted Gaussian basis set used for ab initio calculations of nuclear magnetic resonance (NMR) phosphorous chemical shift anisotropy (CSA) tensors was investigated. The isotropic chemical shitl and chemical shift anisotropy were found to converge with increasing complexity of the basis set at the Hartree-Fock @IF) level. The addition of d polarization function on the phosphorous nucIei was found to have a major impact of the calculated chemical shi~ but diminished with increasing number of polarization fimctions. At least 2 d polarization fimctions are required for accurate calculations of the isotropic phosphorous chemical shift. The introduction of density fictional theory (DFT) techniques through tie use of hybrid B3LYP methods for the calculation of the phosphorous chemical shift tensor resulted in a poorer estimation of the NMR values, even though DFT techniques result in improved energy and force constant calculations. The convergence of the W parametem with increasing basis set complexity was also observed for the DFT calculations, but produced results with consistent large deviations from experiment. The use of a HF 6-31 l++G(242p) basis set represents a good compromise between accuracy of the simulation and the complexity of the calculation for future ab initio calculations of 31P NMR parameters in larger complexes.

  14. Modelling Chemical Reasoning to Predict Reactions

    CERN Document Server

    Segler, Marwin H S

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically ac...

  15. A robust algorithm for optimizing protein structures with NMR chemical shifts.

    Science.gov (United States)

    Berjanskii, Mark; Arndt, David; Liang, Yongjie; Wishart, David S

    2015-11-01

    Over the past decade, a number of methods have been developed to determine the approximate structure of proteins using minimal NMR experimental information such as chemical shifts alone, sparse NOEs alone or a combination of comparative modeling data and chemical shifts. However, there have been relatively few methods that allow these approximate models to be substantively refined or improved using the available NMR chemical shift data. Here, we present a novel method, called Chemical Shift driven Genetic Algorithm for biased Molecular Dynamics (CS-GAMDy), for the robust optimization of protein structures using experimental NMR chemical shifts. The method incorporates knowledge-based scoring functions and structural information derived from NMR chemical shifts via a unique combination of multi-objective MD biasing, a genetic algorithm, and the widely used XPLOR molecular modelling language. Using this approach, we demonstrate that CS-GAMDy is able to refine and/or fold models that are as much as 10 Å (RMSD) away from the correct structure using only NMR chemical shift data. CS-GAMDy is also able to refine of a wide range of approximate or mildly erroneous protein structures to more closely match the known/correct structure and the known/correct chemical shifts. We believe CS-GAMDy will allow protein models generated by sparse restraint or chemical-shift-only methods to achieve sufficiently high quality to be considered fully refined and "PDB worthy". The CS-GAMDy algorithm is explained in detail and its performance is compared over a range of refinement scenarios with several commonly used protein structure refinement protocols. The program has been designed to be easily installed and easily used and is available at http://www.gamdy.ca.

  16. A robust algorithm for optimizing protein structures with NMR chemical shifts

    Energy Technology Data Exchange (ETDEWEB)

    Berjanskii, Mark; Arndt, David; Liang, Yongjie; Wishart, David S., E-mail: david.wishart@ualberta.ca [University of Alberta, Department of Computing Science (Canada)

    2015-11-15

    Over the past decade, a number of methods have been developed to determine the approximate structure of proteins using minimal NMR experimental information such as chemical shifts alone, sparse NOEs alone or a combination of comparative modeling data and chemical shifts. However, there have been relatively few methods that allow these approximate models to be substantively refined or improved using the available NMR chemical shift data. Here, we present a novel method, called Chemical Shift driven Genetic Algorithm for biased Molecular Dynamics (CS-GAMDy), for the robust optimization of protein structures using experimental NMR chemical shifts. The method incorporates knowledge-based scoring functions and structural information derived from NMR chemical shifts via a unique combination of multi-objective MD biasing, a genetic algorithm, and the widely used XPLOR molecular modelling language. Using this approach, we demonstrate that CS-GAMDy is able to refine and/or fold models that are as much as 10 Å (RMSD) away from the correct structure using only NMR chemical shift data. CS-GAMDy is also able to refine of a wide range of approximate or mildly erroneous protein structures to more closely match the known/correct structure and the known/correct chemical shifts. We believe CS-GAMDy will allow protein models generated by sparse restraint or chemical-shift-only methods to achieve sufficiently high quality to be considered fully refined and “PDB worthy”. The CS-GAMDy algorithm is explained in detail and its performance is compared over a range of refinement scenarios with several commonly used protein structure refinement protocols. The program has been designed to be easily installed and easily used and is available at http://www.gamdy.ca http://www.gamdy.ca.

  17. Chemical shift assignments of two oleanane triterpenes from Euonymus hederaceus

    Institute of Scientific and Technical Information of China (English)

    HU He-jiao; WANG Kui-wu; WU Bin; SUN Cui-rong; PAN Yuan-jiang

    2005-01-01

    1H-NMR and 13C-NMR assignments of 12-oleanene-3,11-dione (compound 1) were completely described for the first time through conventional 1D NMR and 2D shift-correlated NMR experiments using 1H-1HCOSY, HMQC, HMBC techniques.Based on its NMR data, the assignments of 28-hydroxyolean-12-ene-3,11-dione (compound 2) were partially revised.

  18. Effects of structural differences on the NMR chemical shifts in isostructural dipeptides.

    Science.gov (United States)

    Altheimer, Benjamin D; Mehta, Manish A

    2014-04-10

    Porous crystalline dipeptides have gained recent attention for their potential as gas-storage materials. Within this large class is a group of dipeptides containing alanine, valine, and isoleucine with very similar crystal structures. We report the (13)C (carbonyl and Cα) and (15)N (amine and amide) solid-state NMR isotropic chemical shifts in a series of seven such isostructural porous dipeptides as well as shift tensor data for the carbonyl and amide sites. Using their known crystal structures and aided by ab initio quantum chemical calculations for the resonance assignments, we elucidate trends relating local structure, hydrogen-bonding patterns, and chemical shift. We find good correlation between the backbone dihedral angles and the Cα1 and Cα2 shifts. For the C1 shift tensor, the δ11 value shifts downfield as the hydrogen-bond distance increases, δ22 shifts upfield, and δ33 shows little variation. The C2 shift tensor shows no appreciable correlation with structural parameters. For the N2 tensor, δ11 shows little dependence on the hydrogen-bond length, whereas δ22 and δ33 both show a decrease in shielding as the hydrogen bond shortens. Our analysis teases apart some, but not all, structural contributors to the observed differences the solid-state NMR chemical shifts.

  19. Stereospecific assignment of the asparagine and glutamine sidechain amide protons in proteins from chemical shift analysis.

    Science.gov (United States)

    Harsch, Tobias; Schneider, Philipp; Kieninger, Bärbel; Donaubauer, Harald; Kalbitzer, Hans Robert

    2017-02-01

    Side chain amide protons of asparagine and glutamine residues in random-coil peptides are characterized by large chemical shift differences and can be stereospecifically assigned on the basis of their chemical shift values only. The bimodal chemical shift distributions stored in the biological magnetic resonance data bank (BMRB) do not allow such an assignment. However, an analysis of the BMRB shows, that a substantial part of all stored stereospecific assignments is not correct. We show here that in most cases stereospecific assignment can also be done for folded proteins using an unbiased artificial chemical shift data base (UACSB). For a separation of the chemical shifts of the two amide resonance lines with differences ≥0.40 ppm for asparagine and differences ≥0.42 ppm for glutamine, the downfield shifted resonance lines can be assigned to H(δ21) and H(ε21), respectively, at a confidence level >95%. A classifier derived from UASCB can also be used to correct the BMRB data. The program tool AssignmentChecker implemented in AUREMOL calculates the Bayesian probability for a given stereospecific assignment and automatically corrects the assignments for a given list of chemical shifts.

  20. Supramolecular chemical shift reagents inducing conformational transitions: NMR analysis of carbohydrate homooligomer mixtures

    DEFF Research Database (Denmark)

    Beeren, Sophie; Meier, Sebastian

    2015-01-01

    We introduce the concept of supramolecular chemical shift reagents as a tool to improve signal resolution for the NMR analysis of homooligomers. Non-covalent interactions with the shift reagent can constrain otherwise flexible analytes inducing a conformational transition that results in signal s...

  1. Analysis of {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shifts of cysteine and cystine residues in proteins: a quantum chemical approach

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Osvaldo A.; Villegas, Myriam E.; Vila, Jorge A. [Universidad Nacional de San Luis, Instituto de Matematica Aplicada San Luis (Argentina); Scheraga, Harold A., E-mail: has5@cornell.ed [Cornell University, Baker Laboratory of Chemistry and Chemical Biology (United States)

    2010-03-15

    Cysteines possess a unique property among the 20 naturally occurring amino acids: it can be present in proteins in either the reduced or oxidized form, and can regulate the activity of some proteins. Consequently, to augment our previous treatment of the other types of residues, the {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shifts of 837 cysteines in disulfide-bonded cystine from a set of seven non-redundant proteins, determined by X-ray crystallography and NMR spectroscopy, were computed at the DFT level of theory. Our results indicate that the errors between observed and computed {sup 13}C{sup {alpha}} chemical shifts of such oxidized cysteines can be attributed to several effects such as: (a) the quality of the NMR-determined models, as evaluated by the conformational-average (ca) rmsd value; (b) the existence of high B-factor or crystal-packing effects for the X-ray-determined structures; (c) the dynamics of the disulfide bonds in solution; and (d) the differences in the experimental conditions under which the observed {sup 13}C{sup {alpha}} chemical shifts and the protein models were determined by either X-ray crystallography or NMR-spectroscopy. These quantum-chemical-based calculations indicate the existence of two, almost non-overlapped, basins for the oxidized and reduced -SH {sup 13}C{sup {beta}}, but not for the {sup 13}C{sup {alpha}}, chemical shifts, in good agreement with the observation of 375 {sup 13}C{sup {alpha}} and 337 {sup 13}C{sup {beta}} resonances from 132 proteins by Sharma and Rajarathnam (2000). Overall, our results indicate that explicit consideration of the disulfide bonds is a necessary condition for an accurate prediction of {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shifts of cysteines in cystines.

  2. MR imaging of renal cortical tumours: qualitative and quantitative chemical shift imaging parameters.

    Science.gov (United States)

    Karlo, Christoph A; Donati, Olivio F; Burger, Irene A; Zheng, Junting; Moskowitz, Chaya S; Hricak, Hedvig; Akin, Oguz

    2013-06-01

    To assess qualitative and quantitative chemical shift MRI parameters of renal cortical tumours. A total of 251 consecutive patients underwent 1.5-T MRI before nephrectomy. Two readers (R1, R2) independently evaluated all tumours visually for a decrease in signal intensity (SI) on opposed- compared with in-phase chemical shift images. In addition, SI was measured on in- and opposed-phase images (SI(IP), SI(OP)) and the chemical shift index was calculated as a measure of percentage SI change. Histopathology served as the standard of reference. A visual decrease in SI was identified significantly more often in clear cell renal cell carcinoma (RCCs) (R1, 73 %; R2, 64 %) and angiomyolipomas (both, 80 %) than in oncocytomas (29 %, 12 %), papillary (29 %, 17 %) and chromophobe RCCs (13 %, 9 %; all, P chemical shift index was significantly greater in clear cell RCC and angiomyolipoma than in the other histological subtypes (both, P analysis (concordance correlation coefficient, 0.80). A decrease in SI on opposed-phase chemical shift images is not an identifying feature of clear cell RCCs or angiomyolipomas, but can also be observed in oncocytomas, papillary and chromophobe RCCs. After excluding angiomyolipomas, a decrease in SI of more than 25 % was diagnostic for clear cell RCCs. • Chemical shift MRI offers new information about fat within renal tumours. • Opposed-phase signal decrease can be observed in all renal cortical tumours. • A greater than 25 % decrease in signal appears to be diagnostic for clear cell RCCs.

  3. Effects of side-chain orientation on the {sup 13}C chemical shifts of antiparallel {beta}-sheet model peptides

    Energy Technology Data Exchange (ETDEWEB)

    Villegas, Myriam E.; Vila, Jorge A. [Facultad de Ciencias Fisico Matematicas y Naturales, Instituto de Matematica Aplicada San Luis, Universidad Nacional de San Luis, CONICET (Argentina); Scheraga, Harold A. [Cornell University, Baker Laboratory of Chemistry and Chemical Biology (United States)], E-mail: has5@cornell.edu

    2007-02-15

    The dependence of the {sup 13}C chemical shift on side-chain orientation was investigated at the density functional level for a two-strand antiparallel {beta}-sheet model peptide represented by the amino acid sequence Ac-(Ala){sub 3}-X-(Ala){sub 12}-NH{sub 2} where X represents any of the 17 naturally occurring amino acids, i.e., not including alanine, glycine and proline. The dihedral angles adopted for the backbone were taken from, and fixed at, observed experimental values of an antiparallel {beta}-sheet. We carried out a cluster analysis of the ensembles of conformations generated by considering the side-chain dihedral angles for each residue X as variables, and use them to compute the {sup 13}C chemical shifts at the density functional theory level. It is shown that the adoption of the locally-dense basis set approach for the quantum chemical calculations enabled us to reduce the length of the chemical-shift calculations while maintaining good accuracy of the results. For the 17 naturally occurring amino acids in an antiparallel {beta}-sheet, there is (i) good agreement between computed and observed {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shifts, with correlation coefficients of 0.95 and 0.99, respectively; (ii) significant variability of the computed {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shifts as a function of {chi}{sup 1} for all amino acid residues except Ser; and (iii) a smaller, although significant, dependence of the computed {sup 13}C{sup {alpha}} chemical shifts on {chi}{sup {xi}} (with {xi} {>=} 2) compared to {chi}{sup 1} for eleven out of seventeen residues. Our results suggest that predicted {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shifts, based only on backbone ({phi},{psi}) dihedral angles from high-resolution X-ray structure data or from NMR-derived models, may differ significantly from those observed in solution if the dihedral-angle preferences for the side chains are not taken into

  4. Proton chemical shift tensors determined by 3D ultrafast MAS double-quantum NMR spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Rongchun; Mroue, Kamal H.; Ramamoorthy, Ayyalusamy, E-mail: ramamoor@umich.edu [Biophysics and Department of Chemistry, The University of Michigan, Ann Arbor, Michigan 48109-1055 (United States)

    2015-10-14

    Proton NMR spectroscopy in the solid state has recently attracted much attention owing to the significant enhancement in spectral resolution afforded by the remarkable advances in ultrafast magic angle spinning (MAS) capabilities. In particular, proton chemical shift anisotropy (CSA) has become an important tool for obtaining specific insights into inter/intra-molecular hydrogen bonding. However, even at the highest currently feasible spinning frequencies (110–120 kHz), {sup 1}H MAS NMR spectra of rigid solids still suffer from poor resolution and severe peak overlap caused by the strong {sup 1}H–{sup 1}H homonuclear dipolar couplings and narrow {sup 1}H chemical shift (CS) ranges, which render it difficult to determine the CSA of specific proton sites in the standard CSA/single-quantum (SQ) chemical shift correlation experiment. Herein, we propose a three-dimensional (3D) {sup 1}H double-quantum (DQ) chemical shift/CSA/SQ chemical shift correlation experiment to extract the CS tensors of proton sites whose signals are not well resolved along the single-quantum chemical shift dimension. As extracted from the 3D spectrum, the F1/F3 (DQ/SQ) projection provides valuable information about {sup 1}H–{sup 1}H proximities, which might also reveal the hydrogen-bonding connectivities. In addition, the F2/F3 (CSA/SQ) correlation spectrum, which is similar to the regular 2D CSA/SQ correlation experiment, yields chemical shift anisotropic line shapes at different isotropic chemical shifts. More importantly, since the F2/F1 (CSA/DQ) spectrum correlates the CSA with the DQ signal induced by two neighboring proton sites, the CSA spectrum sliced at a specific DQ chemical shift position contains the CSA information of two neighboring spins indicated by the DQ chemical shift. If these two spins have different CS tensors, both tensors can be extracted by numerical fitting. We believe that this robust and elegant single-channel proton-based 3D experiment provides useful atomistic

  5. Further conventions for NMR shielding and chemical shifts (IUPAC Recommendations 2008)

    Energy Technology Data Exchange (ETDEWEB)

    Harris, R.K. [University of Durham, Durham (United Kingdom). Dept. of Chemistry; Becker, E.D. [National Institutes of Health, Bethesda, MD (United States); Menezes, S.M. Cabral de [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES); Granger, P. [University Louis Pasteur, Strasbourg (France). Inst. of Chemistry; Hoffman, R.E. [The Hebrew University of Jerusalem, Safra Campus, Jerusalem (Israel). Dept. of Organic Chemistry; Zilm, K.W., E-mail: r.k.harris@durham.ac.uk [Yale University, New Haven, CT (United States). Dept. of Chemistry

    2008-07-01

    IUPAC has published a number of recommendations regarding the reporting of nuclear magnetic resonance (NMR) data, especially chemical shifts. The most recent publication [Pure Appl. Chem. 73, 1795 (2001)] recommended that tetramethylsilane (TMS) serve as a universal reference for reporting the shifts of all nuclides, but it deferred recommendations for several aspects of this subject. This document first examines the extent to which the {sup 1}H shielding in TMS itself is subject to change by variation in temperature, concentration, and solvent. On the basis of recently published results, it has been established that the shielding of TMS in solution [along with that of sodium-3- (trimethylsilyl)propanesulfonate, DSS, often used as a reference for aqueous solutions] varies only slightly with temperature but is subject to solvent perturbations of a few tenths of a part per million (ppm). Recommendations are given for reporting chemical shifts under most routine experimental conditions and for quantifying effects of temperature and solvent variation, including the use of magnetic susceptibility corrections and of magic-angle spinning (MAS). This document provides the first IUPAC recommendations for referencing and reporting chemical shifts in solids, based on high-resolution MAS studies. Procedures are given for relating {sup 13}C NMR chemical shifts in solids to the scales used for high resolution studies in the liquid phase. The notation and terminology used for describing chemical shift and shielding tensors in solids are reviewed in some detail, and recommendations are given for best practice. (author)

  6. Regime shifts limit the predictability of land-system change

    DEFF Research Database (Denmark)

    Müller, Daniel; Sun, Zhanli; Vongvisouk, Thoumthone

    2014-01-01

    (China, Laos, Vietnam and Indonesia). The results show how sudden events and gradual changes in underlying drivers caused rapid, surprising and widespread land-system changes, including shifts to different regimes in China, Vietnam and Indonesia, whereas land systems in Laos remained stable in the study...

  7. Computational Protocols for Prediction of Solute NMR Relative Chemical Shifts

    DEFF Research Database (Denmark)

    Eriksen, Janus Juul; Olsen, Jógvan Magnus Haugaard; Aidas, Kestutis;

    2011-01-01

    In this study, we have applied two different spanning protocols for obtaining the molecular conformations of L-tryptophan in aqueous solution, namely a molecular dynamics simulation and a molecular mechanics conformational search with subsequent geometry re-optimization of the stable conformers...... using a quantum mechanically based method. These spanning protocols represent standard ways of obtaining a set of conformations on which NMR calculations may be performed. The results stemming from the solute–solvent configurations extracted from the MD simulation at 300 K are found to be inferior...

  8. Effect of shifting cultivation on soil physical and chemical properties in Bandarban hill district, Bangladesh

    Institute of Scientific and Technical Information of China (English)

    Khandakar Showkat Osman; M. Jashimuddin; S. M. Sirajul Haque; Sohag Miah

    2013-01-01

    This study reports the effects of shifting cultivation at slashing stage on soil physicochemical properties at Bandarban Sadar Upazila in Chittagong Hill Tracts of Bangladesh. At this initial stage of shifting cultivation no general trend was found for moisture content, maximum water holding capacity, field capacity, dry and moist bulk density, parti-cle density for some chemical properties between shifting cultivated land and forest having similar soil texture. Organic matter was significantly (p≤0.05) lower in 1-year and 3-year shifting cultivated lands and higher in 2-year shifting cultivation than in adjacent natural forest. Significant differences were also found for total N, exchangeable Ca, Mg and K and in CEC as well as for available P. Slashed area showed higher soil pH. Deterioration in land quality starts from burning of slashing materials and continues through subsequent stages of shifting cultivation.

  9. Eye dominance in families predicted by the right shift theory.

    Science.gov (United States)

    Annett, M

    1999-04-01

    The proportions of nonright-eyed children in families with 0, 1, or 2 nonright-eyed parents resemble those for nonright-handed children in the families of nonrighthanded parents. Both sets of proportions are consistent with the Annett right shift genetic model of human asymmetry. The suggestion that findings for eyedness in families are incompatible with genetic theories of handedness (Reiss & Reiss, 1997) is correct for the McManus theory but false for the Annett theory.

  10. Isotope effects on chemical shifts in the study of intramolecular hydrogen bonds

    DEFF Research Database (Denmark)

    Hansen, Poul Erik

    2015-01-01

    The paper deals with the use of isotope effects on chemical shifts in characterizing intramolecular hydrogen bonds. Both so-called resonance-assisted (RAHB) and non-RAHB systems are treated. The importance of RAHB will be discussed. Another very important issue is the borderline between “static......” and tautomeric systems. Isotope effects on chemical shifts are particularly useful in such studies. All kinds of intramolecular hydrogen bonded systems will be treated, typical hydrogen bond donors: OH, NH, SH and NH+, typical acceptors C=O, C=N, C=S C=N−. The paper will be deal with both secondary and primary...... isotope effects on chemical shifts. These two types of isotope effects monitor the same hydrogen bond, but from different angles...

  11. Novel approaches for bond order assignment and NMR shift prediction

    OpenAIRE

    Dehof, Anna Katharina

    2011-01-01

    Molecular modelling is one of the cornerstones of modern biological and pharmaceutical research. Accurate modelling approaches easily become computationally overwhelming and thus, different levels of approximations are typically employed. In this work, we develop such approximation approaches for problems arising in structural bioinformatics. A fundamental approximation of molecular physics is the classification of chemical bonds, usually in the form of integer bond orders. Many input data se...

  12. Deuterium isotope effects on 13C chemical shifts of negatively charged NH.N systems

    DEFF Research Database (Denmark)

    Hansen, Poul Erik; Pietrzak, Mariusz; Grech, Eugeniusz

    2013-01-01

    Deuterium isotope effects on 13C chemical shifts are investigated in anions of 1,8-bis(4-toluenesulphonamido)naphthalenes together with N,N-(naphthalene-1,8-diyl)bis(2,2,2-trifluoracetamide) all with bis(1,8-dimethylamino)napthaleneH+ as counter ion. These compounds represent both “static......” and equilibrium cases. NMR assignments of the former have been revised. The NH proton is deuteriated. The isotope effects on 13C chemical shifts are rather unusual in these strongly hydrogen bonded systems between a NH and a negatively charged nitrogen atom. The formal four-bond effects are found to be negative...

  13. Protein Structure Validation and Refinement Using Chemical Shifts Derived from Quantum Mechanics

    DEFF Research Database (Denmark)

    Bratholm, Lars Andersen

    In this thesis, my work involving dierent aspects of protein structure determination by computer modeling is presented. Determination of several protein's native fold were carried out with Markov chain Monte Carlo simulations in the PHAISTOS protein structure simulation framework, utilizing...... to within 3 A. Furthermore, a fast quantum mechanics based chemical shift predictor was developed together with methodology for using chemical shifts in structure simulations. The developed predictor was used for renement of several protein structures and for reducing the computational cost of quantum...

  14. Ontogenetic shift in response to prey-derived chemical cues in prairie rattlesnakes Crotalus viridis viridis

    Institute of Scientific and Technical Information of China (English)

    Anthony J.SAVIOLA; David CHISZAR; Stephen P.MACKESSY

    2012-01-01

    Snakes often have specialized diets that undergo a shift from one prey type to another depending on the life stage of the snake.Crotalus viridis viridis (prairie rattlesnake) takes different prey at different life stages,and neonates typically prey on ectotherms,while adults feed almost entirely on small endotherms.We hypothesized that elevated rates of tongue flicking to chemical stimuli should correlate with particular prey consumed,and that this response shifts from one prey type to another as individuals age.To examine if an ontogenetic shift in response to chemical cues occurred,we recorded the rate of tongue flicking for 25 neonate,20 subadult,and 20 adult (average SVL=280.9,552,789.5 mm,respectively) wild-caught C.v.viridis to chemical stimuli presented on a cotton-tipped applicator; water-soluble cues from two ectotherms (prairie lizard,Sceloporus undulatus,and house gecko,Hemidactylusfrenatus),two endotherms (deer mouse,Peromyscus maniculatus and lab mouse,Mus musculus),and water controls were used.Neonates tongue flicked significantly more to chemical cues of their common prey,S.undulatus,than to all other chemical cues; however,the response to this lizard's chemical cues decreased in adult rattlesnakes.Subadults tongue flicked with a higher rate of tongue flicking to both S.undulatus and P.maniculatus than to all other treatments,and adults tongue flicked significantly more to P.maniculatus than to all other chemical cues.In addition,all three sub-classes demonstrated a greater response for natural prey chemical cues over chemical stimuli of prey not encountered in the wild (M.musculus and H.frenatus).This shift in chemosensory response correlated with the previously described ontogenetic shifts in C.v.viridis diet.Because many vipers show a similar ontogenetic shift in diet and venom composition,we suggest that this shift in prey cue discrimination is likely a general phenomenon among viperid snakes.

  15. Energy gap in tunneling spectroscopy: effect of the chemical potential shift

    Science.gov (United States)

    Fedotov, N. I.; Zaitsev-Zotov, S. V.

    2016-12-01

    We study the effect of a shift of the chemical potential level on the tunneling conductance spectra. In the systems with gapped energy spectra, significant chemical-potential dependent distortions of the differential tunneling conductance curves, dI/dV, arise in the gap region. An expression is derived for the correction of the dI/dV, which in a number of cases was found to be large. The sign of the correction depends on the chemical potential level position with respect to the gap. The correction of the dI/dV associated with the chemical potential shift has a nearly linear dependence on the tip-sample separation z and vanishes at z → 0.

  16. An atomic electronegative distance vector and carbon-13 nuclear magnetic resonance chemical shifts of alcohols and alkanes

    Institute of Scientific and Technical Information of China (English)

    LIU, Shu-Shea; XIA, Zhi-Ning; CAI, Shao-Xi; LIU, Yan

    2000-01-01

    A novel atomic electronegative distance vector (AEDV) has been developed to express the chemical environment of various chemically equivalent carbon atoms in alcohols and alkanes.Combining AEDV and γ parameter, four five-parameter Iinear relationship equations of chemical shift for four types of carbon atoms are created by using multiple linear regression.Correlation coefficients are R = 0.9887, 0.9972, 0.9978 and 0.9968 and roots of mean square error are RMS = 0.906, 0.821, 1.091and 1.091of four types of carbons, i.e., type1,2, 3, and 4 for primary, secondary, tertiary, and quaternary carbons, respectively. The stability and prediction capacity for external samples of four models have been tested by cross- validation.

  17. Skeletal and chlorine effects on 13C-NMR chemical shifts of chlorinated polycyclic systems

    Directory of Open Access Journals (Sweden)

    Costa V.E.U.

    1999-01-01

    Full Text Available In order to establish a comparative analysis of chemical shifts caused by ring compression effects or by the presence of a chlorine atom on strained chlorinated carbons, a series of the chlorinated and dechlorinated polycyclic structures derived from "aldrin" (5 and "isodrin" (14 was studied. Compounds were classified in four different groups, according to their conformation and number of ring such as: endo-exo and endo-endo tetracyclics, pentacyclics and hexacyclics. The 13C chemical shift comparison between the chlorinated and dechlorinated compounds showed that when C-9 and C-10 are olefinic carbons, it occurs a shielding of 0.5-2.4 ppm for endo-endo tetracyclics and of 4.7-7.6 ppm for endo-exo tetracyclic. The chemical shift variation for C-11 reaches 49-53 ppm for endo-exo and endo-endo tetracyclics, 54 ppm for pentacyclic and 56-59 ppm for hexacyclic compounds. From these data, it was possible to observe the influence of ring compression on the chemical shifts.

  18. Can the current density map topology be extracted from the nucleus independent chemical shifts?

    NARCIS (Netherlands)

    Van Damme, Sofie; Acke, Guillaume; Havenith, Remco W. A.; Bultinck, Patrick

    2016-01-01

    Aromatic compounds are characterised by the presence of a ring current when in a magnetic field. As a consequence, current density maps are used to assess (the degree of) aromaticity of a compound. However, often a more discrete set of so-called Nucleus Independent Chemical Shift (NICS) values is us

  19. Computation of Chemical Shifts for Paramagnetic Molecules: A Laboratory Experiment for the Undergraduate Curriculum

    Science.gov (United States)

    Pritchard, Benjamin P.; Simpson, Scott; Zurek, Eva; Autschbach, Jochen

    2014-01-01

    A computational experiment investigating the [superscript 1]H and [superscript 13]C nuclear magnetic resonance (NMR) chemical shifts of molecules with unpaired electrons has been developed and implemented. This experiment is appropriate for an upper-level undergraduate laboratory course in computational, physical, or inorganic chemistry. The…

  20. Computation of Chemical Shifts for Paramagnetic Molecules: A Laboratory Experiment for the Undergraduate Curriculum

    Science.gov (United States)

    Pritchard, Benjamin P.; Simpson, Scott; Zurek, Eva; Autschbach, Jochen

    2014-01-01

    A computational experiment investigating the [superscript 1]H and [superscript 13]C nuclear magnetic resonance (NMR) chemical shifts of molecules with unpaired electrons has been developed and implemented. This experiment is appropriate for an upper-level undergraduate laboratory course in computational, physical, or inorganic chemistry. The…

  1. H-1 chemical shift imaging characterization of human brain tumor and edema

    NARCIS (Netherlands)

    Sijens, PE; Oudkerk, M

    Longitudinal (T1) and transverse (T2) relaxation times of metabolites in human brain tumor, peritumoral edema, and unaffected brain tissue were assessed from point resolved spectroscopy (PRESS) H-1 chemical shift imaging results at different repetition times (TR = 1500 and 5000 ms; T1: n = 19) and

  2. Using NMR chemical shifts to calculate the propensity for structural order and disorder in proteins

    NARCIS (Netherlands)

    Tamiola, Kamil; Mulder, Frans A. A.

    2012-01-01

    NMR spectroscopy offers the unique possibility to relate the structural propensities of disordered proteins and loop segments of folded peptides to biological function and aggregation behaviour. Backbone chemical shifts are ideally suited for this task, provided that appropriate reference data are a

  3. The statistical shift of the chemical potential causing anomalous conductivity in hydrogenated microcrystalline silicon

    NARCIS (Netherlands)

    Lof, R.W.; Schropp, R.E.I.

    2010-01-01

    The behavior of the electrical conductivity in hydrogenated microcrystalline silicon (μ c-Si:H) that is frequently observed is explained by considering the statistical shift in the chemical potential as a function of the crystalline fraction (Xc), the dangling bond density (N db), and the doping den

  4. Elucidating the Link between NMR Chemical Shifts and Electronic Structure in d(0) Olefin Metathesis Catalysts.

    Science.gov (United States)

    Halbert, Stéphanie; Copéret, Christophe; Raynaud, Christophe; Eisenstein, Odile

    2016-02-24

    The nucleophilic carbon of d(0) Schrock alkylidene metathesis catalysts, [M] = CHR, display surprisingly low downfield chemical shift (δ(iso)) and large chemical shift anisotropy. State-of-the-art four-component relativistic calculations of the chemical shift tensors combined with a two-component analysis in terms of localized orbitals allow a molecular-level understanding of their orientations, the magnitude of their principal components (δ11 > δ22 > δ33) and associated δ(iso). This analysis reveals the dominating influence of the paramagnetic contribution yielding a highly deshielded alkylidene carbon. The largest paramagnetic contribution, which originates from the coupling of alkylidene σ(MC) and π*(MC) orbitals under the action of the magnetic field, is analogous to that resulting from coupling σ(CC) and π*(CC) in ethylene; thus, δ11 is in the MCH plane and is perpendicular to the MC internuclear direction. The higher value of carbon-13 δ(iso) in alkylidene complexes relative to ethylene is thus due to the smaller energy gap between σ(MC) and π*(MC) vs this between σ(CC) and π*(CC) in ethylene. This effect also explains why the highest value of δ(iso) is observed for Mo and the lowest for Ta, the values for W and Re being in between. In the presence of agostic interaction, the chemical shift tensor principal components orientation (δ22 or δ33 parallel or perpendicular to π(MX)) is influenced by the MCH angle because it determines the orientation of the alkylidene CHR fragment relative to the MC internuclear axis. The orbital analysis shows how the paramagnetic terms, understood with a localized bond model, determine the chemical shift tensor and thereby δ(iso).

  5. Magnetic Shift of the Chemical Freeze-out and Electric Charge Fluctuations

    Science.gov (United States)

    Fukushima, Kenji; Hidaka, Yoshimasa

    2016-09-01

    We discuss the effect of a strong magnetic field on the chemical freeze-out points in ultrarelativistic heavy-ion collisions. As a result of inverse magnetic catalysis or magnetic inhibition, the crossover onset to hot and dense matter out of quarks and gluons should be shifted to a lower temperature. To quantify this shift we employ the hadron resonance gas model and an empirical condition for the chemical freeze-out. We point out that the charged particle abundances are significantly affected by the magnetic field so that the electric charge fluctuation is largely enhanced, especially at high baryon density. The charge conservation partially cancels the enhancement, but our calculation shows that the electric charge fluctuation could serve as a magnetometer. We find that the fluctuation exhibits a crossover behavior rapidly increased for e B ≳(0.4 GeV )2, while the charge chemical potential has smoother behavior with an increasing magnetic field.

  6. Can chemical structure predict reproductive toxicity?

    NARCIS (Netherlands)

    Maslankiewicz L; Hulzebos EM; Vermeire TG; Muller JJA; Piersma AH; SEC

    2005-01-01

    Structure-Activity Relationships (SARs), including Quantitative SARs, are applied to the hazard assessment of chemicals. This need is all the more urgent considering the proposed new EU policy on chemicals in REACH, which stresses the need for non-animal testing. DEREKfW and the TSCA Chemical

  7. Identification of zinc-ligated cysteine residues based on 13Calpha and 13Cbeta chemical shift data.

    Science.gov (United States)

    Kornhaber, Gregory J; Snyder, David; Moseley, Hunter N B; Montelione, Gaetano T

    2006-04-01

    Although a significant number of proteins include bound metals as part of their structure, the identification of amino acid residues coordinated to non-paramagnetic metals by NMR remains a challenge. Metal ligands can stabilize the native structure and/or play critical catalytic roles in the underlying biochemistry. An atom's chemical shift is exquisitely sensitive to its electronic environment. Chemical shift data can provide valuable insights into structural features, including metal ligation. In this study, we demonstrate that overlapped 13Cbeta chemical shift distributions of Zn-ligated and non-metal-ligated cysteine residues are largely resolved by the inclusion of the corresponding 13Calpha chemical shift information, together with secondary structural information. We demonstrate this with a bivariate distribution plot, and statistically with a multivariate analysis of variance (MANOVA) and hierarchical logistic regression analysis. Using 287 13Calpha/13Cbeta shift pairs from 79 proteins with known three-dimensional structures, including 86 13Calpha and 13Cbeta shifts for 43 Zn-ligated cysteine residues, along with corresponding oxidation state and secondary structure information, we have built a logistic regression model that distinguishes between oxidized cystines, reduced (non-metal ligated) cysteines, and Zn-ligated cysteines. Classifying cysteines/cystines with a statistical model incorporating all three phenomena resulted in a predictor of Zn ligation with a recall, precision and F-measure of 83.7%, and an accuracy of 95.1%. This model was applied in the analysis of Bacillus subtilis IscU, a protein involved in iron-sulfur cluster assembly. The model predicts that all three cysteines of IscU are metal ligands. We confirmed these results by (i) examining the effect of metal chelation on the NMR spectrum of IscU, and (ii) inductively coupled plasma mass spectrometry analysis. To gain further insight into the frequency of occurrence of non-cysteine Zn

  8. Stereoelectronic effects on 1H nuclear magnetic resonance chemical shifts in methoxybenzenes

    DEFF Research Database (Denmark)

    Lambert, Maja; Olsen, Lars; Jaroszewski, Jerzy W

    2006-01-01

    the Ar-OCH3 torsion out of the ring plane, resulting in large stereoelectronic effects on the chemical shift of Hpara. Conformational searches and geometry optimizations for 3-16 at the B3LYP/6-31G** level, followed by B3LYP/6-311++G(2d,2p) calculations for all low-energy conformers, gave excellent......Investigation of all O-methyl ethers of 1,2,3-benzenetriol and 4-methyl-1,2,3-benzenetriol (3-16) by 1H NMR spectroscopy and density-functional calculations disclosed practically useful conformational effects on 1H NMR chemical shifts in the aromatic ring. While the conversion of phenol (2......) to anisole (1) causes only small positive changes of 1H NMR chemical shifts (Delta delta Hmeta > Hpara, the experimental O-methylation induced shifts in ortho-disubstituted phenols are largest for Hpara, Delta delta equals; 0.19 +/- 0.02 ppm (n = 11...

  9. Predicting Drugs Side Effects Based on Chemical-Chemical Interactions and Protein-Chemical Interactions

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2013-01-01

    Full Text Available A drug side effect is an undesirable effect which occurs in addition to the intended therapeutic effect of the drug. The unexpected side effects that many patients suffer from are the major causes of large-scale drug withdrawal. To address the problem, it is highly demanded by pharmaceutical industries to develop computational methods for predicting the side effects of drugs. In this study, a novel computational method was developed to predict the side effects of drug compounds by hybridizing the chemical-chemical and protein-chemical interactions. Compared to most of the previous works, our method can rank the potential side effects for any query drug according to their predicted level of risk. A training dataset and test datasets were constructed from the benchmark dataset that contains 835 drug compounds to evaluate the method. By a jackknife test on the training dataset, the 1st order prediction accuracy was 86.30%, while it was 89.16% on the test dataset. It is expected that the new method may become a useful tool for drug design, and that the findings obtained by hybridizing various interactions in a network system may provide useful insights for conducting in-depth pharmacological research as well, particularly at the level of systems biomedicine.

  10. Predicting climate-driven regime shifts versus rebound potential in coral reefs.

    Science.gov (United States)

    Graham, Nicholas A J; Jennings, Simon; MacNeil, M Aaron; Mouillot, David; Wilson, Shaun K

    2015-02-05

    Climate-induced coral bleaching is among the greatest current threats to coral reefs, causing widespread loss of live coral cover. Conditions under which reefs bounce back from bleaching events or shift from coral to algal dominance are unknown, making it difficult to predict and plan for differing reef responses under climate change. Here we document and predict long-term reef responses to a major climate-induced coral bleaching event that caused unprecedented region-wide mortality of Indo-Pacific corals. Following loss of >90% live coral cover, 12 of 21 reefs recovered towards pre-disturbance live coral states, while nine reefs underwent regime shifts to fleshy macroalgae. Functional diversity of associated reef fish communities shifted substantially following bleaching, returning towards pre-disturbance structure on recovering reefs, while becoming progressively altered on regime shifting reefs. We identified threshold values for a range of factors that accurately predicted ecosystem response to the bleaching event. Recovery was favoured when reefs were structurally complex and in deeper water, when density of juvenile corals and herbivorous fishes was relatively high and when nutrient loads were low. Whether reefs were inside no-take marine reserves had no bearing on ecosystem trajectory. Although conditions governing regime shift or recovery dynamics were diverse, pre-disturbance quantification of simple factors such as structural complexity and water depth accurately predicted ecosystem trajectories. These findings foreshadow the likely divergent but predictable outcomes for reef ecosystems in response to climate change, thus guiding improved management and adaptation.

  11. High-Frequency (1)H NMR Chemical Shifts of Sn(II) and Pb(II) Hydrides Induced by Relativistic Effects: Quest for Pb(II) Hydrides.

    Science.gov (United States)

    Vícha, Jan; Marek, Radek; Straka, Michal

    2016-10-17

    The role of relativistic effects on (1)H NMR chemical shifts of Sn(II) and Pb(II) hydrides is investigated by using fully relativistic DFT calculations. The stability of possible Pb(II) hydride isomers is studied together with their (1)H NMR chemical shifts, which are predicted in the high-frequency region, up to 90 ppm. These (1)H signals are dictated by sizable relativistic contributions due to spin-orbit coupling at the heavy atom and can be as large as 80 ppm for a hydrogen atom bound to Pb(II). Such high-frequency (1)H NMR chemical shifts of Pb(II) hydride resonances cannot be detected in the (1)H NMR spectra with standard experimental setup. Extended (1)H NMR spectral ranges are thus suggested for studies of Pb(II) compounds. Modulation of spin-orbit relativistic contribution to (1)H NMR chemical shift is found to be important also in the experimentally known Sn(II) hydrides. Because the (1)H NMR chemical shifts were found to be rather sensitive to the changes in the coordination sphere of the central metal in both Sn(II) and Pb(II) hydrides, their application for structural investigation is suggested.

  12. PACSY, a relational database management system for protein structure and chemical shift analysis.

    Science.gov (United States)

    Lee, Woonghee; Yu, Wookyung; Kim, Suhkmann; Chang, Iksoo; Lee, Weontae; Markley, John L

    2012-10-01

    PACSY (Protein structure And Chemical Shift NMR spectroscopY) is a relational database management system that integrates information from the Protein Data Bank, the Biological Magnetic Resonance Data Bank, and the Structural Classification of Proteins database. PACSY provides three-dimensional coordinates and chemical shifts of atoms along with derived information such as torsion angles, solvent accessible surface areas, and hydrophobicity scales. PACSY consists of six relational table types linked to one another for coherence by key identification numbers. Database queries are enabled by advanced search functions supported by an RDBMS server such as MySQL or PostgreSQL. PACSY enables users to search for combinations of information from different database sources in support of their research. Two software packages, PACSY Maker for database creation and PACSY Analyzer for database analysis, are available from http://pacsy.nmrfam.wisc.edu.

  13. Two-Dimensional Proton Chemical-Shift Imaging of Human Muscle Metabolites

    Science.gov (United States)

    Hu, Jiani; Willcott, M. Robert; Moore, Gregory J.

    1997-06-01

    Large lipid signals and strong susceptibility gradients introduced by muscle-bone interfaces represent major technical challenges forin vivoproton MRS of human muscle. Here, the demonstration of two-dimensional proton chemical-shift imaging of human muscle metabolites is presented. This technique utilizes a chemical-shift-selective method for water and lipid suppression and automatic shimming for optimal homogeneity of the magnetic field. The 2D1H CSI technique described facilitates the acquisition of high-spatial-resolution spectra, and allows one to acquire data from multiple muscle groups in a single experiment. A preliminary investigation utilizing this technique in healthy adult males (n= 4) revealed a highly significant difference in the ratio of the creatine to trimethylamine resonance between the fast and slow twitch muscle groups examined. The technique is robust, can be implemented on a commercial scanner with relative ease, and should prove to be a useful tool for both clinical and basic investigators.

  14. Chemical shift selective magnetic resonance imaging of the optic nerve in patients with acute optic neuritis

    DEFF Research Database (Denmark)

    Larsson, H B; Thomsen, C; Frederiksen, J

    1988-01-01

    of the 16 patients, abnormalities were seen. In one patient with bilateral symptoms, signal hyperintensity and swelling of the right side of the chiasm were found. In another patient the optic nerve was found diffusely enlarged with only a marginally increased signal in the second echo. In the third patient......Optic neuritis is often the first manifestation of multiple sclerosis (MS). Sixteen patients with acute optic neuritis and one patient with benign intracranial hypertension (BIH) were investigated by magnetic resonance imaging, using a chemical shift selective double spin echo sequence. In 3...... an area of signal hyperintensity and swelling was seen in the left optic nerve. In the patient with BIH the subarachnoid space which surrounds the optic nerves was enlarged. Even using this refined pulse sequence, avoiding the major artefact in imaging the optic nerve, the chemical shift artefact, lesions...

  15. Identifying Stereoisomers by ab-initio Calculation of Secondary Isotope Shifts on NMR Chemical Shieldings

    Directory of Open Access Journals (Sweden)

    Karl-Heinz Böhm

    2014-04-01

    Full Text Available We present ab-initio calculations of secondary isotope effects on NMR chemical shieldings. The change of the NMR chemical shift of a certain nucleus that is observed if another nucleus is replaced by a different isotope can be calculated by computing vibrational corrections on the NMR parameters using electronic structure methods. We demonstrate that the accuracy of the computational results is sufficient to even distinguish different conformers. For this purpose, benchmark calculations for fluoro(2-2Hethane in gauche and antiperiplanar conformation are carried out at the HF, MP2 and CCSD(T level of theory using basis sets ranging from double- to quadruple-zeta quality. The methodology is applied to the secondary isotope shifts for 2-fluoronorbornane in order to resolve an ambiguity in the literature on the assignment of endo- and exo-2-fluoronorbornanes with deuterium substituents in endo-3 and exo-3 positions, also yielding insight into mechanistic details of the corresponding synthesis.

  16. An extrapolation scheme for solid-state NMR chemical shift calculations

    Science.gov (United States)

    Nakajima, Takahito

    2017-06-01

    Conventional quantum chemical and solid-state physical approaches include several problems to accurately calculate solid-state nuclear magnetic resonance (NMR) properties. We propose a reliable computational scheme for solid-state NMR chemical shifts using an extrapolation scheme that retains the advantages of these approaches but reduces their disadvantages. Our scheme can satisfactorily yield solid-state NMR magnetic shielding constants. The estimated values have only a small dependence on the low-level density functional theory calculation with the extrapolation scheme. Thus, our approach is efficient because the rough calculation can be performed in the extrapolation scheme.

  17. First-principles calculation of core-level binding energy shift in surface chemical processes

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Combined with third generation synchrotron radiation light sources, X-ray photoelectron spectroscopy (XPS) with higher energy resolution, brilliance, enhanced surface sensitivity and photoemission cross section in real time found extensive applications in solid-gas interface chemistry. This paper reports the calculation of the core-level binding energy shifts (CLS) using the first-principles density functional theory. The interplay between the CLS calculations and XPS measurements to uncover the structures, adsorption sites and chemical reactions in complex surface chemical processes are highlight. Its application on clean low index (111) and vicinal transition metal surfaces, molecular adsorption in terms of sites and configuration, and reaction kinetics are domonstrated.

  18. Relationship between electrophilicity index, Hammett constant and nucleus-independent chemical shift

    Indian Academy of Sciences (India)

    M Elango; R Parthasarathi; G Karthik Narayanan; A Md Sabeelullah; U Sarkar; N S Venkatasubramaniyan; V Subramanian; P K Chattaraj

    2005-01-01

    Inter-relationships between the electrophilicity index (), Hammett constant (ó) and nucleusindependent chemical shift (NICS (1) - NICS value one å ngstrom above the ring centre) have been investigated for a series of meta- and para-substituted benzoic acids. Good linear relationships between Hammett constant vs electrophilicity and Hammett constant vs NICS (1) values have been observed. However, the variation of NICS (1) against shows only a low correlation coefficient.

  19. Crime Scene Investigation: Clinical Application of Chemical Shift Imaging as a Problem Solving Tool

    Science.gov (United States)

    2016-02-26

    MDW/SGVU SUBJECT: Professional Presentation Approva l 26 FEB 2016 1. Your paper, entitled Crime Scene Investigation: Clinical Aoolication of...or technical information as a publication/presentation, a new 59 MDW Form 3039 must be submitted for review and approval.] Crime Scene Investiga...tion: Clinical Application of Chemical Shift Imaging as a Problem Solving Tool 1. TITLE OF MATERIAL TO BE PUBLISHED OR PRESENTED Crime Scene

  20. QSPR prediction of physico-chemical properties for REACH.

    Science.gov (United States)

    Dearden, J C; Rotureau, P; Fayet, G

    2013-01-01

    For registration of a chemical, European Union REACH legislation requires information on the relevant physico-chemical properties of the chemical. Predicted property values can be used when the predictions can be shown to be valid and adequate. The relevant physico-chemical properties that are amenable to prediction are: melting/freezing point, boiling point, relative density, vapour pressure, surface tension, water solubility, n-octanol-water partition coefficient, flash point, flammability, explosive properties, self-ignition temperature, adsorption/desorption, dissociation constant, viscosity, and air-water partition coefficient (Henry's law constant). Published quantitative structure-property relationship (QSPR) methods for all of these properties are discussed, together with relevant property prediction software, as an aid for those wishing to use predicted property values in submissions to the European Chemicals Agency (ECHA).

  1. Substituent effects in the 13C NMR chemical shifts of alpha-mono-substituted acetonitriles.

    Science.gov (United States)

    Reis, Adriana K C A; Rittner, Roberto

    2007-03-01

    13C chemical shifts empirical calculations, through a very simple additivity relationship, for the alpha-methylene carbon of some alpha-mono-substituted acetonitriles, Y-CH(2)-CN (Y=H, F, Cl, Br, I, OMe, OEt, SMe, SEt, NMe(2), NEt(2), Me and Et), lead to similar, or even better, results in comparison to the reported values obtained through Quantum Mechanics methods. The observed deviations, for some substituents, are very similar for both approaches. This divergence between experimental and calculated, either empirically or theoretically, values are smaller than for the corresponding acetones, amides, acetic acids and methyl esters, which had been named non-additivity effects (or intramolecular interaction chemical shifts, ICS) and attributed to some orbital interactions. Here, these orbital interactions do not seem to be the main reason for the non-additivity effects in the empirical calculations, which must be due solely to the magnetic anisotropy of the heavy atom present in the substituent. These deviations, which were also observed in the theoretical calculations, were attributed in that case to the non-inclusion of relativistic effects and spin-orbit coupling in the Hamiltonian. Some divergence is also observed for the cyano carbon chemical shifts, probably due to the same reasons.

  2. Chemical shift selective magnetic resonance imaging of the optic nerve in patients with acute optic neuritis

    Energy Technology Data Exchange (ETDEWEB)

    Larsson, H.B.W.; Thomsen, C.; Frederiksen, J.; Henriksen, O.; Olesen, J.

    Optic neuritis is often the first manifestion of multiple sclerosis (MS). Sixteen patients with acute optic neuritis and one patient with benign intracranial hypertension (BIH) were investigated by magnetic resonance imaging, using a chemical shift selective double spin echo sequence. In 3 of the 16 patients, abnormalities were seen. In one patient with bilateral symptoms, signal hyperintensity and swelling of the right side of the chiasm were found. In another patient the optic nerve was found diffusely enlarged with only a marginally increased signal in the second echo. In the third patient an area of signal hyperintensity and swelling was seen in the left optic nerve. In the patient with BIH the subarachnoid space which surrounds the optic nerves was enlarged. Even using this refined pulse sequence, avoiding the major artefact in imaging the optic nerve, the chemical shift artefact, lesions were only shown in 3/16 (19%) of the patients with optic neuritis. Nevertheless, the presented chemical shift selective double spin echo sequence may be of great value for detection of retrobulbar lesions.

  3. Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

    OpenAIRE

    2015-01-01

    We have determined refined multidimensional chemical shift ranges for intra-residue correlations ([superscript 13]C–[superscript 13]C, [superscript 15]N–[superscript 13]C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 [superscript 13]C chemical shifts and >3 million chemical...

  4. Atypical cerebral dominance: predictions and tests of the right shift theory.

    Science.gov (United States)

    Annett, M; Alexander, M P

    1996-12-01

    Alexander and Annett (Brain and Language, in press) described new cases of atypical cerebral specialization, and suggested that these observations and others in the literature could be explained by the right shift (RS) theory. The theory generates specific predictions as to the prevalence of different patterns of cerebral dominance and their distribution among right-handers and left-handers. Predictions differ between strict and generous criteria of sinistrality, as between left writers and non-right-handers. Tests of the predictions against reports in the literature reveal good fits for most data. New studies will test the RS theory if their design permits examination of the present predictions.

  5. Differentiation of osteoporotic and neoplastic vertebral fractures by chemical shift {l_brace}in-phase and out-of phase{r_brace} MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Ragab, Yasser [Radiology Department, Faculty of Medicine, Cairo University (Egypt); Radiology Department, Dr Erfan and Bagedo General Hospital (Saudi Arabia)], E-mail: yragab61@hotmail.com; Emad, Yasser [Rheumatology and Rehabilitation Department, Faculty of Medicine, Cairo University (Egypt); Rheumatology and Rehabilitation Department, Dr Erfan and Bagedo General Hospital (Saudi Arabia)], E-mail: yasseremad68@yahoo.com; Gheita, Tamer [Rheumatology and Rehabilitation Department, Faculty of Medicine, Cairo University (Egypt)], E-mail: gheitamer@yahoo.com; Mansour, Maged [Oncology Department, Faculty of Medicine, Cairo University (Egypt); Oncology Department, Dr Erfan and Bagedo General Hospital (Saudi Arabia)], E-mail: magedmansour@yahoo.com; Abou-Zeid, A. [Public Health Department, Faculty of Medicine, Cairo University, Cairo (Egypt)], E-mail: alaabouzeid@yahoo.com; Ferrari, Serge [Division of Bone Diseases, Department of Rehabilitation and Geriatrics, and WHO, Collaborating Center for Osteoporosis Prevention, Geneva University Hospital (Switzerland)], E-mail: serge.ferrari@medecine.unige.ch; Rasker, Johannes J. [Rheumatologist University of Twente, Enschede (Netherlands)], E-mail: j.j.rasker@utwente.nl

    2009-10-15

    Objective: The objective of this study was to establish the cut-off value of the signal intensity drop on chemical shift magnetic resonance imaging (MRI) with appropriate sensitivity and specificity to differentiate osteoporotic from neoplastic wedging of the spine. Patients and methods: All patients with wedging of vertebral bodies were included consecutively between February 2006 and January 2007. A chemical shift MRI was performed and signal intensity after (in-phase and out-phase) images were obtained. A DXA was performed in all. Results: A total of 40 patients were included, 20 with osteoporotic wedging (group 1) and 20 neoplastic (group 2). They were 21 males and 19 females. Acute vertebral collapse was observed in 15 patients in group 1 and subacute collapse in another 5 patients, while in group 2, 11 patients showed acute collapse and 9 patients (45%) showed subacute vertebral collapse. On the chemical shift MRI a substantial reduction in signal intensity was found in all lesions in both groups. The proportional changes observed in signal intensity of bone marrow lesions on in-phase compared with out-of-phase images showed significant differences in both groups (P < 0.05). At a cut-off value of 35%, the observed sensitivity of out-of-phase images was 95%, specificity was 100%, positive predictive value was 100% and negative predictive value was 95.2%. Conclusion: A chemical shift MRI is useful in order to differentiate patients with vertebral collapse due to underlying osteoporosis or neoplastic process.

  6. Temperature dependence of contact and dipolar NMR chemical shifts in paramagnetic molecules.

    Science.gov (United States)

    Martin, Bob; Autschbach, Jochen

    2015-02-07

    Using a recently proposed equation for NMR nuclear magnetic shielding for molecules with unpaired electrons [A. Soncini and W. Van den Heuvel, J. Chem. Phys. 138, 021103 (2013)], equations for the temperature (T) dependent isotropic shielding for multiplets with an effective spin S equal to 1/2, 1, 3/2, 2, and 5/2 in terms of electron paramagnetic resonance spin Hamiltonian parameters are derived and then expanded in powers of 1/T. One simplifying assumption used is that a matrix derived from the zero-field splitting (ZFS) tensor and the Zeeman coupling matrix (g-tensor) share the same principal axis system. The influence of the rhombic ZFS parameter E is only investigated for S = 1. Expressions for paramagnetic contact shielding (from the isotropic part of the hyperfine coupling matrix) and pseudo-contact or dipolar shielding (from the anisotropic part of the hyperfine coupling matrix) are considered separately. The leading order is always 1/T. A temperature dependence of the contact shielding as 1/T and of the dipolar shielding as 1/T(2), which is sometimes assumed in the assignment of paramagnetic chemical shifts, is shown to arise only if S ≥ 1 and zero-field splitting is appreciable, and only if the Zeeman coupling matrix is nearly isotropic (Δg = 0). In such situations, an assignment of contact versus dipolar shifts may be possible based only on linear and quadratic fits of measured variable-temperature chemical shifts versus 1/T. Numerical data are provided for nickelocene (S = 1). Even under the assumption of Δg = 0, a different leading order of contact and dipolar shifts in powers of 1/T is not obtained for S = 3/2. When Δg is not very small, dipolar and contact shifts both depend in leading order in 1/T in all cases, with sizable contributions in order 1/T(n) with n = 2 and higher.

  7. High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2014-01-01

    Full Text Available Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.

  8. High capacity reversible watermarking for audio by histogram shifting and predicted error expansion.

    Science.gov (United States)

    Wang, Fei; Xie, Zhaoxin; Chen, Zuo

    2014-01-01

    Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.

  9. Predicting Anatomical Therapeutic Chemical (ATC classification of drugs by integrating chemical-chemical interactions and similarities.

    Directory of Open Access Journals (Sweden)

    Lei Chen

    Full Text Available The Anatomical Therapeutic Chemical (ATC classification system, recommended by the World Health Organization, categories drugs into different classes according to their therapeutic and chemical characteristics. For a set of query compounds, how can we identify which ATC-class (or classes they belong to? It is an important and challenging problem because the information thus obtained would be quite useful for drug development and utilization. By hybridizing the informations of chemical-chemical interactions and chemical-chemical similarities, a novel method was developed for such purpose. It was observed by the jackknife test on a benchmark dataset of 3,883 drug compounds that the overall success rate achieved by the prediction method was about 73% in identifying the drugs among the following 14 main ATC-classes: (1 alimentary tract and metabolism; (2 blood and blood forming organs; (3 cardiovascular system; (4 dermatologicals; (5 genitourinary system and sex hormones; (6 systemic hormonal preparations, excluding sex hormones and insulins; (7 anti-infectives for systemic use; (8 antineoplastic and immunomodulating agents; (9 musculoskeletal system; (10 nervous system; (11 antiparasitic products, insecticides and repellents; (12 respiratory system; (13 sensory organs; (14 various. Such a success rate is substantially higher than 7% by the random guess. It has not escaped our notice that the current method can be straightforwardly extended to identify the drugs for their 2(nd-level, 3(rd-level, 4(th-level, and 5(th-level ATC-classifications once the statistically significant benchmark data are available for these lower levels.

  10. Phonology and Handedness in Primary School: Predictions of the Right Shift Theory

    Science.gov (United States)

    Smythe, Pamela; Annett, Marian

    2006-01-01

    Background: The right shift (RS) theory of handedness suggests that poor phonology may occur in the general population as a risk associated with absence of an agent of left cerebral speech, the hypothesised RS + gene. The theory predicts that poor phonology is associated with reduced bias to right-handedness. Methods: A representative cohort of…

  11. Combining a weed traits database with a population dynamics model predicts shifts in weed communities

    NARCIS (Netherlands)

    Storkey, J.; Holst, N.; Bøjer, Q.; Bigongiali, F.; Bocci, G.; Colbach, N.; Dorner, Z.; Riemens, M.M.; Sartorato, I.; Sønderskov, M.; Verschwele, A.

    2015-01-01

    A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, popul

  12. Prediction of β-hairpin Motif in Enzyme Based on Values of Matrix Scoring and Averaged Chemical Shifts%基于矩阵打分值和化学位移值预测酶蛋白质中β-发夹模体

    Institute of Scientific and Technical Information of China (English)

    宋航宇; 胡秀珍

    2014-01-01

    Enzyme is a kind of protein that acts with catalytic functions in living organisms ,thus the study of the structure and function of enzyme is essential .β-hairpin is a specific super -secondary structure motif which carries abundant folding information .The prediction of β-hairpin motifs in en-zyme protein is helpful to study the structure and function of enzyme .In this paper ,we constructed a non-redundant β-hairpin database ,w hich have 2 ,818β-hairpins and 1 ,098 non-β-hairpins motif in 1 ,080 enzyme protein chains .The hydropaths composed of position and adjacent to dipeptide hydro-paths composition of position extracted as parameter for matrix scoring algorithm ,the prediction re-sults were unsatisfactory .Then ,we selected the scores of hydropathy composition of position ,the scores of adjacent to dipeptide hydropathy composition of position and averaged chemical shift as the in-put parameters for Support Vector Machine algorithm ,the overall accuracy and Matthew ’s correlation coefficient reached 81 .8% and 0 .636 respectively by 5-fold cross-validation .%酶是一类具有催化功能的蛋白质,对其结构和功能的研究是非常有必要的。特殊模体β-发夹是一种简单的超二级结构,它们包含了丰富的折叠信息,对酶中β-发夹的预测有助于酶结构和功能的预测。本文建立了非冗余的β-发夹模体数据集,包含1080条酶蛋白质链,2818个β-发夹模体,1098个非β-发夹。提取位点亲疏水组分及位点亲疏水紧邻关联组分作为参数,运用矩阵打分算法得到的预测结果不理想。将位点亲疏水、位点亲疏水紧邻关联组分为参数得到的打分值和平均化学位移值共同作为特征参数,输入支持向量机算法对模体进行预测,5交叉检验预测总精度是81.8%,相关系数达到了0.636。

  13. Predicting chemical impacts on vertebrate endocrine systems.

    Science.gov (United States)

    Nichols, John W; Breen, Miyuki; Denver, Robert J; Distefano, Joseph J; Edwards, Jeremy S; Hoke, Robert A; Volz, David C; Zhang, Xiaowei

    2011-01-01

    Animals have evolved diverse protective mechanisms for responding to toxic chemicals of both natural and anthropogenic origin. From a governmental regulatory perspective, these protective responses complicate efforts to establish acceptable levels of chemical exposure. To explore this issue, we considered vertebrate endocrine systems as potential targets for environmental contaminants. Using the hypothalamic-pituitary-thyroid (HPT), hypothalamic-pituitary-gonad (HPG), and hypothalamic-pituitary-adrenal (HPA) axes as case examples, we identified features of these systems that allow them to accommodate and recover from chemical insults. In doing so, a distinction was made between effects on adults and those on developing organisms. This distinction was required because endocrine system disruption in early life stages may alter development of organs and organ systems, resulting in permanent changes in phenotypic expression later in life. Risk assessments of chemicals that impact highly regulated systems must consider the dynamics of these systems in relation to complex environmental exposures. A largely unanswered question is whether successful accommodation to a toxic insult exerts a fitness cost on individual animals, resulting in adverse consequences for populations. Mechanistically based mathematical models of endocrine systems provide a means for better understanding accommodation and recovery. In the short term, these models can be used to design experiments and interpret study findings. Over the long term, a set of validated models could be used to extrapolate limited in vitro and in vivo testing data to a broader range of untested chemicals, species, and exposure scenarios. With appropriate modification, Tier 2 assays developed in support of the U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program could be used to assess the potential for accommodation and recovery and inform the development of mechanistically based models.

  14. Lateral Ventricle Volume Asymmetry Predicts Midline Shift in Severe Traumatic Brain Injury

    Science.gov (United States)

    Schmalfuss, Ilona; Heaton, Shelley C.; Gabrielli, Andrea; Hannay, H. Julia; Papa, Linda; Brophy, Gretchen M.; Wang, Kevin K.W.; Büki, András; Schwarcz, Attila; Hayes, Ronald L.; Robertson, Claudia S.; Robicsek, Steven A.

    2015-01-01

    Abstract Midline shift following severe traumatic brain injury (sTBI) detected on computed tomography (CT) scans is an established predictor of poor outcome. We hypothesized that lateral ventricular volume (LVV) asymmetry is an earlier sign of developing asymmetric intracranial pathology than midline shift. This retrospective analysis was performed on data from 84 adults with blunt sTBI requiring a ventriculostomy who presented to a Level I trauma center. Seventy-six patients underwent serial CTs within 3 h and an average of three scans within the first 10 d of sTBI. Left and right LVVs were quantified by computer-assisted manual volumetric measurements. LVV ratios (LVR) were determined on the admission CT to evaluate ventricular asymmetry. The relationship between the admission LVR value and subsequent midline shift development was tested using receiver operating characteristic (ROC) analysis, and odds ratio (OR) and relative risk tests. Sixty patients had no >5 mm midline shift on the initial admission scan. Of these, 15 patients developed it subsequently (16 patients already had >5 mm midline shift on admission scans). For >5 mm midline shift development, admission LVR of >1.67 was shown to have a sensitivity of 73.3% and a specificity of 73.3% (area under the curve=0.782; p1.67 as exposure yielded an OR of 7.56 (p<0.01), and a risk ratio of 4.42 (p<0.01) for midline shift development as unfavorable outcome. We propose that LVR captures LVV asymmetry and is not only related to, but also predicts the development of midline shift already at admission CT examination. Lateral ventricles may have a higher “compliance” than midline structures to developing asymmetric brain pathology. LVR analysis is simple, rapidly accomplished and may allow earlier interventions to attenuate midline shift and potentially improve ultimate outcomes. PMID:25752227

  15. Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

    Energy Technology Data Exchange (ETDEWEB)

    Fritzsching, Keith J., E-mail: kfritzsc@brandeis.edu [Brandeis University, Department of Chemistry (United States); Hong, Mei [Massachusetts Institute of Technology, Department of Chemistry (United States); Schmidt-Rohr, Klaus, E-mail: srohr@brandeis.edu [Brandeis University, Department of Chemistry (United States)

    2016-02-15

    We have determined refined multidimensional chemical shift ranges for intra-residue correlations ({sup 13}C–{sup 13}C, {sup 15}N–{sup 13}C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 {sup 13}C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ∼94 % of the {sup 13}C NMR data and almost all {sup 15}N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the {sup 13}C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra

  16. Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria.

    Science.gov (United States)

    Fritzsching, Keith J; Hong, Mei; Schmidt-Rohr, Klaus

    2016-02-01

    We have determined refined multidimensional chemical shift ranges for intra-residue correlations ((13)C-(13)C, (15)N-(13)C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 (13)C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited "hand-picked" data sets, we show that ~94% of the (13)C NMR data and almost all (15)N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6% of the (13)C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. -2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a provided

  17. DFT calculations of 1H and 13C NMR chemical shifts in transition metal hydrides.

    Science.gov (United States)

    del Rosal, I; Maron, L; Poteau, R; Jolibois, F

    2008-08-14

    Transition metal hydrides are of great interest in chemistry because of their reactivity and their potential use as catalysts for hydrogenation. Among other available techniques, structural properties in transition metal (TM) complexes are often probed by NMR spectroscopy. In this paper we will show that it is possible to establish a viable methodological strategy in the context of density functional theory, that allows the determination of 1H NMR chemical shifts of hydride ligands attached to transition metal atoms in mononuclear systems and clusters with good accuracy with respect to experiment. 13C chemical shifts have also been considered in some cases. We have studied mononuclear ruthenium complexes such as Ru(L)(H)(dppm)2 with L = H or Cl, cationic complex [Ru(H)(H2O)(dppm)2]+ and Ru(H)2(dppm)(PPh3)2, in which hydride ligands are characterized by a negative 1H NMR chemical shift. For these complexes all calculations are in relatively good agreement compared to experimental data with errors not exceeding 20% except for the hydrogen atom in Ru(H)2(dppm)(PPh3)2. For this last complex, the relative error increases to 30%, probably owing to the necessity to take into account dynamical effects of phenyl groups. Carbonyl ligands are often encountered in coordination chemistry. Specific issues arise when calculating 1H or 13C NMR chemical shifts in TM carbonyl complexes. Indeed, while errors of 10 to 20% with respect to experiment are often considered good in the framework of density functional theory, this difference in the case of mononuclear carbonyl complexes culminates to 80%: results obtained with all-electron calculations are overall in very satisfactory agreement with experiment, the error in this case does not exceed 11% contrary to effective core potentials (ECPs) calculations which yield errors always larger than 20%. We conclude that for carbonyl groups the use of ECPs is not recommended, although their use could save time for very large systems, for

  18. Evaluation of vertebral bone marrow fat content by chemical-shift MRI in osteoporosis

    Energy Technology Data Exchange (ETDEWEB)

    Gokalp, Gokhan; Mutlu, Fatma Senturk; Yazici, Zeynep; Yildirim, Nalan [Uludag University Medical Faculty, Department of Radiology, Gorukle, Bursa (Turkey)

    2011-05-15

    To quantitatively evaluate vertebral bone marrow fat content and investigate its association with osteoporosis with chemical-shift magnetic resonance imaging (CS-MRI). Fifty-six female patients (age range 50-65 years) with varying bone mineral densities as documented with dual x-ray absorptiometry (DXA) were prospectively included in the study. According to the DXA results, the patients were grouped as normal bone density, osteopenic, or osteoporotic. In order to calculate fat content, the lumbar region was visualized in the sagittal plane by CS-MRI sequence. ''Region of interest'' (ROI)s were placed within L3 vertebral bodies and air (our reference point) at different time points by different radiologists. Fat content was calculated through ''signal intensity (SI) suppression rate'' and ''SI Index''. The quantitative values were compared statistically with those obtained from DXA examinations. Kruskal-Wallis, and Mann-Whitney U tests were used for comparisons between groups. The reliability of the measurements performed by two radiologists was evaluated with the ''intraclass correlation coefficient''. This study was approved by an institutional review board and all participants provided informed consent to participate in the study. Eighteen subjects with normal bone density (mean T score, 0.39 {+-} 1.3 [standard deviation]), 20 subjects with osteopenia (mean T score, -1.79 {+-} 0.38), and 18 subjects with osteoporosis (mean T score, -3 {+-} 0.5) were determined according to DXA results. The median age was 55.9 (age range 50-64 years) in the normal group, 55.5 (age range 50-64 years) in the osteopenic group, and 55.1 (age range 50-65 years) in the osteoporotic group (p = 0.872). In the CS-MRI examination, the values of ''SI suppression ratio'' and ''SI Index'' (median [min:max]) were calculated by the first and second reader, independently. There

  19. NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents

    Directory of Open Access Journals (Sweden)

    Benjamin Görling

    2016-09-01

    Full Text Available Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability of the urinary metabolites by NMR spectroscopy. The exchange solvents were methanol, acetonitrile, dimethyl sulfoxide, chloroform, acetone, dichloromethane, and dimethyl formamide. Some of these solvents showed promising results with a single batch of urine. To evaluate further differences between urine samples, various acid, base, and salt solutions were added in a defined way mimicking to some extent inter human differences. Corresponding chemical shift changes were monitored.

  20. Three model space experiments on chemical reactions. [Gibbs adsorption, equilibrium shift and electrodeposition

    Science.gov (United States)

    Grodzka, P.; Facemire, B.

    1977-01-01

    Three investigations conducted aboard Skylab IV and Apollo-Soyuz involved phenomena that are of interest to the biochemistry community. The formaldehyde clock reaction and the equilibrium shift reaction experiments conducted aboard Apollo Soyuz demonstrate the effect of low-g foams or air/liquid dispersions on reaction rate and chemical equilibrium. The electrodeposition reaction experiment conducted aboard Skylab IV demonstrate the effect of a low-g environment on an electrochemical displacement reaction. The implications of the three space experiments for various applications are considered.

  1. NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents

    Science.gov (United States)

    Görling, Benjamin; Bräse, Stefan; Luy, Burkhard

    2016-01-01

    Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability of the urinary metabolites by NMR spectroscopy. The exchange solvents were methanol, acetonitrile, dimethyl sulfoxide, chloroform, acetone, dichloromethane, and dimethyl formamide. Some of these solvents showed promising results with a single batch of urine. To evaluate further differences between urine samples, various acid, base, and salt solutions were added in a defined way mimicking to some extent inter human differences. Corresponding chemical shift changes were monitored. PMID:27598217

  2. Parameter-free calculation of K alpha chemical shifts for Al, Si, and Ge oxides

    DEFF Research Database (Denmark)

    Lægsgaard, Jesper

    2001-01-01

    The chemical shifts of the K alpha radiation line from Al, Si, and Ge ions between their elemental and oxide forms are calculated within the framework of density functional theory using ultrasoft pseudopotentials. It is demonstrated that this theoretical approach yields quantitatively accurate...... results fur the systems investigated, provided that relaxations of the valence electrons upon the core-hole transition are properly accounted for. Therefore, such calculations provide a powerful tool for identification of impurity states based on x-ray fluorescence data. Results for an Al impurity...

  3. Analyzing temperature-induced transitions in disordered proteins by NMR spectroscopy and secondary chemical shift analyses

    DEFF Research Database (Denmark)

    Kjærgaard, Magnus; Poulsen, Flemming Martin; Kragelund, Birthe Brandt

    2012-01-01

    Intrinsically disordered proteins are abundant in nature and perform many important physiological functions. Multidimensional NMR spectroscopy has been crucial for the understanding of the conformational properties of disordered proteins and is increasingly used to probe their conformational...... ensembles. Compared to folded proteins, disordered proteins are more malleable and more easily perturbed by environmental factors. Accordingly, the experimental conditions and especially the temperature modify the structural and functional properties of disordered proteins. This chapter discusses practical...... aspects of NMR studies of temperature-induced structural changes in disordered proteins using chemical shifts....

  4. Lateral Ventricle Volume Asymmetry Predicts Midline Shift in Severe Traumatic Brain Injury.

    Science.gov (United States)

    Tóth, Arnold; Schmalfuss, Ilona; Heaton, Shelley C; Gabrielli, Andrea; Hannay, H Julia; Papa, Linda; Brophy, Gretchen M; Wang, Kevin K W; Büki, András; Schwarcz, Attila; Hayes, Ronald L; Robertson, Claudia S; Robicsek, Steven A

    2015-09-01

    Midline shift following severe traumatic brain injury (sTBI) detected on computed tomography (CT) scans is an established predictor of poor outcome. We hypothesized that lateral ventricular volume (LVV) asymmetry is an earlier sign of developing asymmetric intracranial pathology than midline shift. This retrospective analysis was performed on data from 84 adults with blunt sTBI requiring a ventriculostomy who presented to a Level I trauma center. Seventy-six patients underwent serial CTs within 3 h and an average of three scans within the first 10 d of sTBI. Left and right LVVs were quantified by computer-assisted manual volumetric measurements. LVV ratios (LVR) were determined on the admission CT to evaluate ventricular asymmetry. The relationship between the admission LVR value and subsequent midline shift development was tested using receiver operating characteristic (ROC) analysis, and odds ratio (OR) and relative risk tests. Sixty patients had no >5 mm midline shift on the initial admission scan. Of these, 15 patients developed it subsequently (16 patients already had >5 mm midline shift on admission scans). For >5 mm midline shift development, admission LVR of >1.67 was shown to have a sensitivity of 73.3% and a specificity of 73.3% (area under the curve=0.782; p1.67 as exposure yielded an OR of 7.56 (pasymmetry and is not only related to, but also predicts the development of midline shift already at admission CT examination. Lateral ventricles may have a higher "compliance" than midline structures to developing asymmetric brain pathology. LVR analysis is simple, rapidly accomplished and may allow earlier interventions to attenuate midline shift and potentially improve ultimate outcomes.

  5. New perspectives in the PAW/GIPAW approach: J(P-O-Si) coupling constants, antisymmetric parts of shift tensors and NQR predictions.

    Science.gov (United States)

    Bonhomme, Christian; Gervais, Christel; Coelho, Cristina; Pourpoint, Frédérique; Azaïs, Thierry; Bonhomme-Coury, Laure; Babonneau, Florence; Jacob, Guy; Ferrari, Maude; Canet, Daniel; Yates, Jonathan R; Pickard, Chris J; Joyce, Siân A; Mauri, Francesco; Massiot, Dominique

    2010-12-01

    In 2001, Pickard and Mauri implemented the gauge including projected augmented wave (GIPAW) protocol for first-principles calculations of NMR parameters using periodic boundary conditions (chemical shift anisotropy and electric field gradient tensors). In this paper, three potentially interesting perspectives in connection with PAW/GIPAW in solid-state NMR and pure nuclear quadrupole resonance (NQR) are presented: (i) the calculation of J coupling tensors in inorganic solids; (ii) the calculation of the antisymmetric part of chemical shift tensors and (iii) the prediction of (14)N and (35)Cl pure NQR resonances including dynamics. We believe that these topics should open new insights in the combination of GIPAW, NMR/NQR crystallography, temperature effects and dynamics. Points (i), (ii) and (iii) will be illustrated by selected examples: (i) chemical shift tensors and heteronuclear (2)J(P-O-Si) coupling constants in the case of silicophosphates and calcium phosphates [Si(5)O(PO(4))(6), SiP(2)O(7) polymorphs and α-Ca(PO(3))(2)]; (ii) antisymmetric chemical shift tensors in cyclopropene derivatives, C(3)X(4) (X = H, Cl, F) and (iii) (14)N and (35)Cl NQR predictions in the case of RDX (C(3)H(6)N(6)O(6)), β-HMX (C(4)H(8)N(8)O(8)), α-NTO (C(2)H(2)N(4)O(3)) and AlOPCl(6). RDX, β-HMX and α-NTO are explosive compounds.

  6. Optimal voxel size for measuring global gray and white matter proton metabolite concentrations using chemical shift imaging

    DEFF Research Database (Denmark)

    Hanson, Lars Peter Grüner; Adalsteinsson, E; Pfefferbaum, A

    2000-01-01

    Quantification of gray and white matter levels of spectroscopically visible metabolites can provide important insights into brain development and pathological conditions. Chemical shift imaging offers a gain in efficiency for estimation of global gray and white matter metabolite concentrations...

  7. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    R. G. SILVA

    1999-03-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  8. Nonuniform backbone conformation of deoxyribonucleic acid indicated by phosphorus-31 nuclear magnetic resonance chemical shift anisotropy.

    Science.gov (United States)

    Shindo, H; Wooten, J B; Pheiffer, B H; Zimmerman, S B

    1980-02-05

    31P nuclear magnetic resonance of highly oriented DNA fibers has been observed for three different conformations, namely, the A, B, and C forms of DNA. At a parallel orientation of the fiber axis with respect to the magnetic field, DNA fibers in both the A and B forms exhibit a single, abnormally broad resonance; in contrast, fibers in the C form show almost the full span of the chemical shift anisotropy (170 ppm). The spectra of the fibers oriented perpendicular indicate that the DNA molecules undergo a considerable rotational motion about the helical axis, with a rate of greater than 2 x 10(3) s-1 for the B-form DNA. Theoretical considerations indicate that the 31P chemical shift data for the B-form DNA fibers are consistent with the atomic coordinates of the phosphodiester group proposed by Langridge et al. [Langridge, R., Wilson, H. R. Hooper, C. W., Wilkins, M. H. F., & Hamilton, L. D. (1960) J. Mol. Biol. 2, 19--37] but not with the corresponding coordinates proposed by Arnott and Hukins [Arnott, S., & Hukins, D. W. L. (1972) Biochem. Biophys. Res. Coomun. 47, 1504--1509], and also lead to the conclusion that the phosphodiester orientation must vary significantly along the DNA molecule. The latter result suggests that DNA has significant variations in its backbone conformation along the molecule.

  9. Paramagnetic NMR chemical shift in a spin state subject to zero-field splitting

    CERN Document Server

    Soncini, Alessandro

    2012-01-01

    We derive a general formula for the paramagnetic NMR nuclear shielding tensor of an open-shell molecule in a pure spin state, subject to a zero-field splitting (ZFS). Our findings are in contradiction with a previous proposal. We present a simple application of the newly derived formula to the case of a triplet ground state split by an easy-plane ZFS spin Hamiltonian. When $kT$ is much smaller than the ZFS gap, thus a single non-degenerate level is thermally populated, our approach correctly predicts a temperature-independent paramagnetic shift, while the previous theory leads to a Curie temperature dependence.

  10. Lamb Shift in Muonic Hydrogen. I. Verification and Update of Theoretical Predictions

    CERN Document Server

    Jentschura, U D

    2010-01-01

    In view of the recently observed discrepancy of theory and experiment for muonic hydrogen [R. Pohl et al., Nature vol. 466, p. 213 (2010)], we reexamine the theory on which the quantum electrodynamic (QED) predictions are based. In particular, we update the theory of the 2P-2S Lamb shift, by calculating the self-energy of the bound muon in the full Coulomb+vacuum polarization (Uehling) potential. We also investigate the relativistic two-body corrections to the vacuum polarization shift, and we analyze the influence of the shape of the nuclear charge distribution on the proton radius determination. The uncertainty associated with the third Zemach moment _2 in the determination of the proton radius from the measurement is estimated. An updated theoretical prediction for the 2S-2P transition is given.

  11. Shifting Evaluation Windows: Predictable Forward Primes with Long SOAs Eliminate the Impact of Backward Primes

    OpenAIRE

    Fockenberg, Daniel A.; Koole, Sander L; Daniël Lakens; Semin, Gün R.

    2013-01-01

    Shifting Evaluation Windows: Predictable Forward Primes with Long SOAs Eliminate the Impact of Backward Primes Daniel A. Fockenberg1*, Sander L. Koole2, Danie¨ l Lakens3, Gu¨ n R. Semin4,5 1 Institut fu¨ r Psychologie, Albert-Ludwigs-Universita¨t Freiburg, Freiburg, Germany, 2 Department of Clinical Psychology, VU University Amsterdam, Amsterdam, The Netherlands, 3 Eindhoven University of Technology, Eindhoven, The Netherlands, 4 Royal Netherlands Academy for Arts and Sciences,...

  12. Fragment-Based Approach for the Evaluation of NMR Chemical Shifts for Large Biomolecules Incorporating the Effects of the Solvent Environment.

    Science.gov (United States)

    Jose, K V Jovan; Raghavachari, Krishnan

    2017-03-14

    -NMR solvation protocols developed in this work may pave the way for very accurate de novo prediction of NMR chemical shifts of a range of large biomolecules in the future.

  13. Predicting Flaw-Induced Resonance Spectrum Shift with Theoretical Perturbation Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lai, Canhai; Sun, Xin

    2013-10-28

    Resonance inspection is an emerging non-destructive evaluation (NDE) technique which uses the resonance spectra differences between the good part population and the flawed parts to identify anomalous parts. It was previously established that finite-element (FE)-based modal analysis can be used to predict the resonance spectrum for an engineering scale part with relatively good accuracy. However, FE-based simulations can be time consuming in examining the spectrum shifts induced by all possible structural flaws. This paper aims at developing a computationally efficient perturbation technique to quantify the frequency shifts induced by small structural flaws, based on the FE simulated resonance spectrum for the perfect part. A generic automotive connecting rod is used as the example part for our study. The results demonstrate that the linear perturbation theory provides a very promising way in predicting frequency changes induced by small structural flaws. As the flaw size increases, the discrepancy between the perturbation analysis and the actual FE simulation results increases due to nonlinearity, yet the perturbation analysis is still able to predict the right trend in frequency shift.

  14. 125Te NMR chemical-shift trends in PbTe–GeTe and PbTe–SnTe alloys

    Energy Technology Data Exchange (ETDEWEB)

    Njegic, Bosiljka [Ames Laboratory; Levin, Evgenii M. [Ames Laboratory; Schmidt-Rohr, Klaus [Ames Laboratory

    2013-10-08

    Complex tellurides, such as doped PbTe, GeTe, and their alloys, are among the best thermoelectric materials. Knowledge of the change in 125Te NMR chemical shift due to bonding to dopant or “solute” atoms is useful for determination of phase composition, peak assignment, and analysis of local bonding. We have measured the 125Te NMR chemical shifts in PbTe-based alloys, Pb1-xGexTe and Pb1-xSnxTe, which have a rocksalt-like structure, and analyzed their trends. For low x, several peaks are resolved in the 22-kHz MAS 125Te NMR spectra. A simple linear trend in chemical shifts with the number of Pb neighbors is observed. No evidence of a proposed ferroelectric displacement of Ge atoms in a cubic PbTe matrix is detected at low Ge concentrations. The observed chemical shift trends are compared with the results of DFT calculations, which confirm the linear dependence on the composition of the first-neighbor shell. The data enable determination of the composition of various phases in multiphase telluride materials. They also provide estimates of the 125Te chemical shifts of GeTe and SnTe (+970 and +400±150 ppm, respectively, from PbTe), which are otherwise difficult to access due to Knight shifts of many hundreds of ppm in neat GeTe and SnTe.

  15. 125Te NMR chemical-shift trends in PbTe-GeTe and PbTe-SnTe alloys.

    Science.gov (United States)

    Njegic, B; Levin, E M; Schmidt-Rohr, K

    2013-01-01

    Complex tellurides, such as doped PbTe, GeTe, and their alloys, are among the best thermoelectric materials. Knowledge of the change in (125)Te NMR chemical shift due to bonding to dopant or "solute" atoms is useful for determination of phase composition, peak assignment, and analysis of local bonding. We have measured the (125)Te NMR chemical shifts in PbTe-based alloys, Pb1-xGexTe and Pb1-xSnxTe, which have a rocksalt-like structure, and analyzed their trends. For low x, several peaks are resolved in the 22-kHz MAS (125)Te NMR spectra. A simple linear trend in chemical shifts with the number of Pb neighbors is observed. No evidence of a proposed ferroelectric displacement of Ge atoms in a cubic PbTe matrix is detected at low Ge concentrations. The observed chemical shift trends are compared with the results of DFT calculations, which confirm the linear dependence on the composition of the first-neighbor shell. The data enable determination of the composition of various phases in multiphase telluride materials. They also provide estimates of the (125)Te chemical shifts of GeTe and SnTe (+970 and +400±150 ppm, respectively, from PbTe), which are otherwise difficult to access due to Knight shifts of many hundreds of ppm in neat GeTe and SnTe.

  16. Reassigning the Structures of Natural Products Using NMR Chemical Shifts Computed with Quantum Mechanics: A Laboratory Exercise

    Science.gov (United States)

    Palazzo, Teresa A.; Truong, Tiana T.; Wong, Shirley M. T.; Mack, Emma T.; Lodewyk, Michael W.; Harrison, Jason G.; Gamage, R. Alan; Siegel, Justin B.; Kurth, Mark J.; Tantillo, Dean J.

    2015-01-01

    An applied computational chemistry laboratory exercise is described in which students use modern quantum chemical calculations of chemical shifts to assign the structure of a recently isolated natural product. A pre/post assessment was used to measure student learning gains and verify that students demonstrated proficiency of key learning…

  17. Reassigning the Structures of Natural Products Using NMR Chemical Shifts Computed with Quantum Mechanics: A Laboratory Exercise

    Science.gov (United States)

    Palazzo, Teresa A.; Truong, Tiana T.; Wong, Shirley M. T.; Mack, Emma T.; Lodewyk, Michael W.; Harrison, Jason G.; Gamage, R. Alan; Siegel, Justin B.; Kurth, Mark J.; Tantillo, Dean J.

    2015-01-01

    An applied computational chemistry laboratory exercise is described in which students use modern quantum chemical calculations of chemical shifts to assign the structure of a recently isolated natural product. A pre/post assessment was used to measure student learning gains and verify that students demonstrated proficiency of key learning…

  18. The recognition of multi-class protein folds by adding average chemical shifts of secondary structure elements.

    Science.gov (United States)

    Feng, Zhenxing; Hu, Xiuzhen; Jiang, Zhuo; Song, Hangyu; Ashraf, Muhammad Aqeel

    2016-03-01

    The recognition of protein folds is an important step in the prediction of protein structure and function. Recently, an increasing number of researchers have sought to improve the methods for protein fold recognition. Following the construction of a dataset consisting of 27 protein fold classes by Ding and Dubchak in 2001, prediction algorithms, parameters and the construction of new datasets have improved for the prediction of protein folds. In this study, we reorganized a dataset consisting of 76-fold classes constructed by Liu et al. and used the values of the increment of diversity, average chemical shifts of secondary structure elements and secondary structure motifs as feature parameters in the recognition of multi-class protein folds. With the combined feature vector as the input parameter for the Random Forests algorithm and ensemble classification strategy, we propose a novel method to identify the 76 protein fold classes. The overall accuracy of the test dataset using an independent test was 66.69%; when the training and test sets were combined, with 5-fold cross-validation, the overall accuracy was 73.43%. This method was further used to predict the test dataset and the corresponding structural classification of the first 27-protein fold class dataset, resulting in overall accuracies of 79.66% and 93.40%, respectively. Moreover, when the training set and test sets were combined, the accuracy using 5-fold cross-validation was 81.21%. Additionally, this approach resulted in improved prediction results using the 27-protein fold class dataset constructed by Ding and Dubchak.

  19. A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm

    Science.gov (United States)

    de Brito, Daniel M.; Maracaja-Coutinho, Vinicius; de Farias, Savio T.; Batista, Leonardo V.; do Rêgo, Thaís G.

    2016-01-01

    Genomic Islands (GIs) are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP—Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me. PMID:26731657

  20. A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm.

    Directory of Open Access Journals (Sweden)

    Daniel M de Brito

    Full Text Available Genomic Islands (GIs are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP--Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.

  1. The interplay between transient a-helix formation and side chain rotamer distributions in disordered proteins probed by methyl chemical shifts

    DEFF Research Database (Denmark)

    Kjærgaard, Magnus; Iesmantavicius, Vytautas; Poulsen, Flemming M

    2011-01-01

    and retinoid receptors (ACTR). We find that small differences in the methyl carbon chemical shifts due to the ¿-gauche effect may provide information about the side chain rotamer distributions. However, the effects of neighboring residues on the methyl group chemical shifts obscure the direct observation...... of ¿-gauche effect. To overcome this, we reference the chemical shifts to those in a more disordered state resulting in residue specific random coil chemical shifts. The (13)C secondary chemical shifts of the methyl groups of valine, leucine, and isoleucine show sequence specific effects, which allow...

  2. Cognitive trait anxiety, situational stress, and mental effort predict shifting efficiency: Implications for attentional control theory.

    Science.gov (United States)

    Edwards, Elizabeth J; Edwards, Mark S; Lyvers, Michael

    2015-06-01

    Attentional control theory (ACT) predicts that trait anxiety and situational stress interact to impair performance on tasks that involve attentional shifting. The theory suggests that anxious individuals recruit additional effort to prevent shortfalls in performance effectiveness (accuracy), with deficits becoming evident in processing efficiency (the relationship between accuracy and time taken to perform the task). These assumptions, however, have not been systematically tested. The relationship between cognitive trait anxiety, situational stress, and mental effort in a shifting task (Wisconsin Card Sorting Task) was investigated in 90 participants. Cognitive trait anxiety was operationalized using questionnaire scores, situational stress was manipulated through ego threat instructions, and mental effort was measured using a visual analogue scale. Dependent variables were performance effectiveness (an inverse proportion of perseverative errors) and processing efficiency (an inverse proportion of perseverative errors divided by response time on perseverative error trials). The predictors were not associated with performance effectiveness; however, we observed a significant 3-way interaction on processing efficiency. At higher mental effort (+1 SD), higher cognitive trait anxiety was associated with poorer efficiency independently of situational stress, whereas at lower effort (-1 SD), this relationship was highly significant and most pronounced for those in the high-stress condition. These results are important because they provide the first systematic test of the relationship between trait anxiety, situational stress, and mental effort on shifting performance. The data are also consistent with the notion that effort moderates the relationship between anxiety and shifting efficiency, but not effectiveness.

  3. Family handedness in three generations predicted by the right shift theory.

    Science.gov (United States)

    Annett, M

    1979-05-01

    The hand preferences of Open University (OU) students and their relatives, including children, are described. As in earlier series, estimates of heritability are higher for mothers than fathers. There is no evidence of smaller heritability for paternal than maternal grandparents. The distribution of left-handedness in families is examined in the light of predictions of the right shift theory and on the assumption that the shift depends on a single gene. Good agreement is found between the observed and expected numbers of R x R, L x R and L x L families. Predictions are successful for both strict and generous criteria of sinistrality. Generation differences are found between OU students and their parents and between the students and their children. These are discussed from the viewpoint of a possible heterozygote advantage in intelligence. The higher proportion of sinistral children born to sinistral mothers than fathers can be partly accounted for by supposing that the right shift is more effective in females than males.

  4. Sequential acquisition of multi-dimensional heteronuclear chemical shift correlation spectra with 1H detection

    Science.gov (United States)

    Bellstedt, Peter; Ihle, Yvonne; Wiedemann, Christoph; Kirschstein, Anika; Herbst, Christian; Görlach, Matthias; Ramachandran, Ramadurai

    2014-03-01

    RF pulse schemes for the simultaneous acquisition of heteronuclear multi-dimensional chemical shift correlation spectra, such as {HA(CA)NH & HA(CACO)NH}, {HA(CA)NH & H(N)CAHA} and {H(N)CAHA & H(CC)NH}, that are commonly employed in the study of moderately-sized protein molecules, have been implemented using dual sequential 1H acquisitions in the direct dimension. Such an approach is not only beneficial in terms of the reduction of experimental time as compared to data collection via two separate experiments but also facilitates the unambiguous sequential linking of the backbone amino acid residues. The potential of sequential 1H data acquisition procedure in the study of RNA is also demonstrated here.

  5. Ab Initio Calculations of Deuterium Isotope Effects on Chemical Shifts of Salt-Bridged Lysines

    DEFF Research Database (Denmark)

    Ullah, Saif; Ishimoto, Takayoshi; Williamson, Mike P.;

    2011-01-01

    Deuterium isotope effects measure the change in chemical shift on substitution of a proton by deuterium. They have been calculated by direct treatment of the H/D nuclear quantum effect using a multicomponent ab initio molecular orbital method based on a non-Born−Oppenheimer approximation....... This method enables the determination of both the electronic and the protonic (deuteronic) wave functions simultaneously and can directly calculate the geometrical difference induced by H/D isotope effects. The calculations show that the one-bond deuterium isotope effects on 15N nuclear shielding, 1Δ15N......(D), in ammonium and amines decrease as a counterion or water molecule moves closer to the nitrogen. 1Δ15N(D) and 2Δ1H(D) of the NH3+ groups of lysine residues in the B1 domain of protein G have been calculated using truncated side chains and also determined experimentally by NMR. Comparisons show...

  6. Study of wavelength-shifting chemicals for use in large-scale water Cherenkov detectors

    CERN Document Server

    Sweany, M; Dazeley, S; Dunmore, J; Felde, J; Svoboda, R; Tripathi, M

    2011-01-01

    Cherenkov detectors employ various methods to maximize light collection at the photomultiplier tubes (PMTs). These generally involve the use of highly reflective materials lining the interior of the detector, reflective materials around the PMTs, or wavelength-shifting sheets around the PMTs. Recently, the use of water-soluble wavelength-shifters has been explored to increase the measurable light yield of Cherenkov radiation in water. These wave-shifting chemicals are capable of absorbing light in the ultravoilet and re-emitting the light in a range detectable by PMTs. Using a 250 L water Cherenkov detector, we have characterized the increase in light yield from three compounds in water: 4-Methylumbelliferone, Carbostyril-124, and Amino-G Salt. We report the gain in PMT response at a concentration of 1 ppm as: 1.88 $\\pm$ 0.02 for 4-Methylumbelliferone, stable to within 0.5% over 50 days, 1.37 $\\pm$ 0.03 for Carbostyril-124, and 1.20 $\\pm$ 0.02 for Amino-G Salt. The response of 4-Methylumbelliferone was modele...

  7. Handling the influence of chemical shift in amplitude-modulated heteronuclear dipolar recoupling solid-state NMR

    Science.gov (United States)

    Basse, Kristoffer; Shankar, Ravi; Bjerring, Morten; Vosegaard, Thomas; Nielsen, Niels Chr.; Nielsen, Anders B.

    2016-09-01

    We present a theoretical analysis of the influence of chemical shifts on amplitude-modulated heteronuclear dipolar recoupling experiments in solid-state NMR spectroscopy. The method is demonstrated using the Rotor Echo Short Pulse IRrAdiaTION mediated Cross-Polarization (RESPIRATIONCP) experiment as an example. By going into the pulse sequence rf interaction frame and employing a quintuple-mode operator-based Floquet approach, we describe how chemical shift offset and anisotropic chemical shift affect the efficiency of heteronuclear polarization transfer. In this description, it becomes transparent that the main attribute leading to non-ideal performance is a fictitious field along the rf field axis, which is generated from second-order cross terms arising mainly between chemical shift tensors and themselves. This insight is useful for the development of improved recoupling experiments. We discuss the validity of this approach and present quaternion calculations to determine the effective resonance conditions in a combined rf field and chemical shift offset interaction frame transformation. Based on this, we derive a broad-banded version of the RESPIRATIONCP experiment. The new sequence is experimentally verified using SNNFGAILSS amyloid fibrils where simultaneous 15N → 13CO and 15N → 13Cα coherence transfer is demonstrated on high-field NMR instrumentation, requiring great offset stability.

  8. 50 years anniversary of the discovery of the core level chemical shifts. The early years of photoelectron spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Mårtensson, Nils [Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden); Sokolowski, Evelyn [Tvär-Ramsdal 1, 611 99 Tystberga (Sweden); Svensson, Svante, E-mail: Svante.Svensson@fysik.uu.se [Department of Physics and Astronomy, Uppsala University, Box 516, 751 20 Uppsala (Sweden)

    2014-03-01

    Highlights: • 50 years since the discovery of t the core level chemical shift. • The pioneering years of ESCA. • A critical review of the first core electron chemical shift results. - Abstract: The pioneering years of photoelectron spectroscopy in Uppsala are discussed, especially the work leading to the discovery of the core level chemical shifts. At a very early stage of the project, the pioneering group observed what they described as evidence for chemical shifts in the core level binding energies. However, it can now be seen that the initial observations to a large extent was due to charging of the samples. It is interesting to note that the decisive experiment was realized, not as a result of a systematic study, but was obtained with a large element of serendipity. Only when a chemical binding energy shift was observed between two S2p electron lines in the same molecule, the results were accepted internationally, and the fascinating expansion of modern core level photoelectron spectroscopy could start.

  9. Prediction of Rate Constants for Catalytic Reactions with Chemical Accuracy.

    Science.gov (United States)

    Catlow, C Richard A

    2016-08-01

    Ex machina: A computational method for predicting rate constants for reactions within microporous zeolite catalysts with chemical accuracy has recently been reported. A key feature of this method is a stepwise QM/MM approach that allows accuracy to be achieved while using realistic models with accessible computer resources.

  10. The Formation Age of Comets: Predicted Physical and Chemical Trends

    Science.gov (United States)

    Nuth, J. A., III; Hill, H. G. M.

    2000-01-01

    The chemical composition of a comet has always been considered to be a function of where it formed in the nebula. We suggest that the most important factor in determining a comet's chemistry might actually be when it formed. Specific predictions are presented.

  11. Attainable entanglement of unitary transformed thermal states in liquid-state nuclear magnetic resonance with the chemical shift

    CERN Document Server

    Ota, Y; Ohba, I; Yoshida, N; Mikami, Shuji; Ohba, Ichiro; Ota, Yukihiro; Yoshida, Noriyuki

    2006-01-01

    Recently, Yu, Brown, and Chuang [Phys. Rev. A {\\bf 71}, 032341 (2005)] investigated the entanglement attainable from unitary transformed thermal states in liquid-state nuclear magnetic resonance (NMR). Their research gave an insight into the role of the entanglement in a liquid-state NMR quantum computer. Moreover, they attempted to reveal the role of mixed-state entanglement in quantum computing. However, they assumed that the Zeeman energy of each nuclear spin which corresponds to a qubit takes a common value for all; there is no chemical shift. In this paper, we research a model with the chemical shifts and analytically derive the physical parameter region where unitary transformed thermal states are entangled, by the positive partial transposition (PPT) criterion with respect to any bipartition. We examine the effect of the chemical shifts on the boundary between the separability and the nonseparability, and find it is negligible.

  12. Chemical shift tensor determination using magnetically oriented microcrystal array (MOMA): 13C solid-state CP NMR without MAS

    Science.gov (United States)

    Kusumi, R.; Kimura, F.; Song, G.; Kimura, T.

    2012-10-01

    Chemical shift tensors for the carboxyl and methyl carbons of L-alanine crystals were determined using a magnetically oriented microcrystal array (MOMA) prepared from a microcrystalline powder sample of L-alanine. A MOMA is a single-crystal-like composite in which microcrystals are aligned three-dimensionally in a matrix resin. The single-crystal rotation method was applied to the MOMA to determine the principal values and axes of the chemical shift tensors. The result showed good agreement with the literature data for the single crystal of L-alanine. This demonstrates that the present technique is a powerful tool for determining the chemical shift tensor of a crystal from a microcrystal powder sample.

  13. Chemical shift assignments of zinc finger domain of methionine aminopeptidase 1 (MetAP1) from Homo sapiens.

    Science.gov (United States)

    Rachineni, Kavitha; Arya, Tarun; Singarapu, Kiran Kumar; Addlagatta, Anthony; Bharatam, Jagadeesh

    2015-10-01

    Methionine aminopeptidase Type I (MetAP1) cleaves the initiator methionine from about 70 % of all newly synthesized proteins in almost every living cell. Human MetAP1 is a two domain protein with a zinc finger on the N-terminus and a catalytic domain on the C-terminus. Here, we report the chemical shift assignments of the amino terminal zinc binding domain (ZBD) (1-83 residues) of the human MetAP1 derived by using advanced NMR spectroscopic methods. We were able to assign the chemical shifts of ZBD of MetAP1 nearly complete, which reveal two helical fragments involving residues P44-L49 (α1) and Q59-K82 (α2). The protein structure unfolds upon complex formation with the addition of 2 M excess EDTA, indicated by the appearance of amide resonances in the random coil chemical shift region of (15)NHSQC spectrum.

  14. Origin of the conformational modulation of the 13C NMR chemical shift of methoxy groups in aromatic natural compounds.

    Science.gov (United States)

    Toušek, Jaromír; Straka, Michal; Sklenář, Vladimír; Marek, Radek

    2013-01-24

    The interpretation of nuclear magnetic resonance (NMR) parameters is essential to understanding experimental observations at the molecular and supramolecular levels and to designing new and more efficient molecular probes. In many aromatic natural compounds, unusual (13)C NMR chemical shifts have been reported for out-of-plane methoxy groups bonded to the aromatic ring (~62 ppm as compared to the typical value of ~56 ppm for an aromatic methoxy group). Here, we analyzed this phenomenon for a series of aromatic natural compounds using Density Functional Theory (DFT) calculations. First, we checked the methodology used to optimize the structure and calculate the NMR chemical shifts in aromatic compounds. The conformational effects of the methoxy group on the (13)C NMR chemical shift then were interpreted by the Natural Bond Orbital (NBO) and Natural Chemical Shift (NCS) approaches, and by excitation analysis of the chemical shifts, breaking down the total nuclear shielding tensor into the contributions from the different occupied orbitals and their magnetic interactions with virtual orbitals. We discovered that the atypical (13)C NMR chemical shifts observed are not directly related to a different conjugation of the lone pair of electrons of the methoxy oxygen with the aromatic ring, as has been suggested. Our analysis indicates that rotation of the methoxy group induces changes in the virtual molecular orbital space, which, in turn, correlate with the predominant part of the contribution of the paramagnetic deshielding connected with the magnetic interactions of the BD(CMet-H)→BD*(CMet-OMet) orbitals, resulting in the experimentally observed deshielding of the (13)C NMR resonance of the out-of-plane methoxy group.

  15. The influence of sulfur configuration in (1) H NMR chemical shifts of diasteromeric five-membered cyclic sulfites.

    Science.gov (United States)

    Obregón-Mendoza, Marco A; Sánchez-Castellanos, Mariano; Cuevas, Gabriel; Gnecco, Dino; Cassani, Julia; Poveda-Jaramillo, Juan C; Reynolds, William F; Enríquez, Raúl G

    2017-03-01

    The effect of the stereochemistry of the sulfur atom on (1) H chemical shifts of the diasteromeric pair of cyclic sulfites of 4-[methoxy(4-nitrophenyl)methyl]-5-phenyl-1,3,2-dioxathiolan-2-oxide was investigated. The complete (1) H and (13) C NMR spectral assignment was achieved by the use of one-dimensional and two-dimensional NMR techniques in combination with X-ray data. A correlation of experimental data with theoretical calculations of chemical shift tensors using density functional theory and topological theory of atoms in molecules was made. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  16. Regional Differences in Muscle Energy Metabolism in Human Muscle by 31P-Chemical Shift Imaging.

    Science.gov (United States)

    Kime, Ryotaro; Kaneko, Yasuhisa; Hongo, Yoshinori; Ohno, Yusuke; Sakamoto, Ayumi; Katsumura, Toshihito

    2016-01-01

    Previous studies have reported significant region-dependent differences in the fiber-type composition of human skeletal muscle. It is therefore hypothesized that there is a difference between the deep and superficial parts of muscle energy metabolism during exercise. We hypothesized that the inorganic phosphate (Pi)/phosphocreatine (PCr) ratio of the superficial parts would be higher, compared with the deep parts, as the work rate increases, because the muscle fiber-type composition of the fast-type may be greater in the superficial parts compared with the deep parts. This study used two-dimensional 31Phosphorus Chemical Shift Imaging (31P-CSI) to detect differences between the deep and superficial parts of the human leg muscles during dynamic knee extension exercise. Six healthy men participated in this study (age 27±1 year, height 169.4±4.1 cm, weight 65.9±8.4 kg). The experiments were carried out with a 1.5-T superconducting magnet with a 5-in. diameter circular surface coil. The subjects performed dynamic one-legged knee extension exercise in the prone position, with the transmit-receive coil placed under the right quadriceps muscles in the magnet. The subjects pulled down an elastic rubber band attached to the ankle at a frequency of 0.25, 0.5 and 1 Hz for 320 s each. The intracellular pH (pHi) was calculated from the median chemical shift of the Pi peak relative to PCr. No significant difference in Pi/PCr was observed between the deep and the superficial parts of the quadriceps muscles at rest. The Pi/PCr of the superficial parts was not significantly increased with increasing work rate. Compared with the superficial areas, the Pi/PCr of the deep parts was significantly higher (p<0.05) at 1 Hz. The pHi showed no significant difference between the two parts. These results suggest that muscle oxidative metabolism is different between deep and superficial parts of quadriceps muscles during dynamic exercise.

  17. Shifting evaluation windows: predictable forward primes with long SOAs eliminate the impact of backward primes.

    Science.gov (United States)

    Fockenberg, Daniel A; Koole, Sander L; Lakens, Daniël; Semin, Gün R

    2013-01-01

    Recent work suggests that people evaluate target stimuli within short and flexible time periods called evaluation windows. Stimuli that briefly precede a target (forward primes) or briefly succeed a target (backward primes) are often included in the target's evaluation. In this article, the authors propose that predictable forward primes act as "go" signals that prepare target processing, such that earlier forward primes pull the evaluation windows forward in time. Earlier forward primes may thus reduce the impact of backward primes. This shifting evaluation windows hypothesis was tested in two experiments using an evaluative decision task with predictable (vs. unpredictable) forward and backward primes. As expected, a longer time interval between a predictable forward prime and a target eliminated backward priming. In contrast, the time interval between an unpredictable forward primes and a target had no effects on backward priming. These findings suggest that predictable features of dynamic stimuli can shape target extraction by determining which information is included (or excluded) in rapid evaluation processes.

  18. Effects of Irritant Chemicals on Aedes aegypti Resting Behavior: Is There a Simple Shift to Untreated "Safe Sites"?

    Science.gov (United States)

    2011-07-26

    Effects of Irritant Chemicals on Aedes aegypti Resting Behavior: Is There a Simple Shift to Untreated ‘‘Safe Sites’’? Hortance Manda*, Luana M. Arce... aegypti to irritant and repellent chemicals that can be exploited to reduce man-vector contact. Maximum efficacy of interventions based on irritant...overall impact. Methods: Using a laboratory box assay, resting patterns of two population strains of female Ae. aegypti (THAI and PERU) were evaluated

  19. SUBSTITUENT CHEMICAL SHIFT (SCS) AND THE SEQUENCE STRUCTURE OF ETHYLENE-VINYL ALCOHOL COPOLYMERS

    Institute of Scientific and Technical Information of China (English)

    ZHOU Zinan; TIAN Wenjing; WU Shengrong; DAI Yingkun; FENG Zhiliu; SHEN Lianfang; YUAN Hanzhen

    1992-01-01

    Three ethylene-vinyl alcohol copolymers were studied by means of the substituent chemical shift(SCS) method. The SCS parameters of hydroxy (-OH)in two different solvents were obtained: in deuterium oxide/phenol (20/80 W/W ) the parameters are S1 = 42.77 ± 0.08ppm, S2 = 7.15 ±0.06 ppm,S3(s )=-4.08±0.02ppm, S3(t)=-3.09±0.20ppm,S4=0.48±0.03ppm, S5 =0.26±0.05ppm. In o-dichlorobenzen-d4 S1(s)=44.79±0.61ppm, S2=7.40±0.00ppm, S3 (s)=-4.51±0.17ppm, S3 (t)= -3.13± 0.00 ppm, S4 =0 . 63±0.04ppm, S5=0.36±0.00ppm. Simultaneously the 13CNMR spectra of EVA copolymers were assigned by using the SCS parameters obtained.

  20. Chemical shift imaging and localised magnetic resonance spectroscopy in full-term asphyxiated neonates

    Energy Technology Data Exchange (ETDEWEB)

    Brissaud, Olivier [Children' s Hospital, Paediatric Intensive Care Unit, Bordeaux (France); Chateil, Jean-Francois; Bordessoules, Martine; Brun, Muriel [Children' s Hospital, Radiology Unit, Bordeaux (France)

    2005-10-01

    Diagnosis of brain lesions after birth anoxia-ischemia is essential for appropriate management. Clinical evaluation is not sufficient. MRI has been proven to provide useful information. To compare abnormalities observed with MRI, including diffusion-weighted imaging (DWI), localised magnetic resonance spectroscopy (MRS) and chemical shift imaging (CSI) and correlate these findings with the clinical outcome. Fourteen full-term neonates with birth asphyxia were studied. MRI, MRS and CSI were performed within the first 4 days of life. Lesions observed with DWI were correlated with outcome, but the apparent diffusion coefficient (ADC) did improve diagnostic confidence. The mean value of Lac/Cr for the neonates with a favourable outcome was statically lower than for those who died (0.22 vs 1.04; P = 0.01). The same results were observed for the Lac/NAA ratio (0.21 vs 1.23; P = 0.01). Data obtained with localised MRS and CSI were correlated for the ratio N-acetyl-aspartate/choline, but not for the other metabolites. No correlation was found between the ADC values and the metabolite ratios. Combination of these techniques could be helpful in our understanding of the physiopathological events occurring in neonates with asphyxia. (orig.)

  1. Molecular structure and vibrational and chemical shift assignments of 3'-chloro-4-dimethylamino azobenzene by DFT calculations.

    Science.gov (United States)

    Toy, Mehmet; Tanak, Hasan

    2016-01-05

    In the present work, a combined experimental and theoretical study on ground state molecular structure, spectroscopic and nonlinear optical properties of azo compound 3'-chloro-4-dimethlamino azobenzene are reported. The molecular geometry, vibrational wavenumbers and the first order hyperpolarizability of the title compound were calculated with the help of density functional theory computations. The optimized geometric parameters obtained by using DFT (B3LYP/6-311++G(d,p)) show good agreement with the experimental data. The vibrational transitions were identified based on the recorded FT-IR spectra in the range of 4000-400cm(-1) for solid state. The (1)H isotropic chemical shifts with respect to TMS were also calculated using the gauge independent atomic orbital (GIAO) method and compared with the experimental data. Using the TD-DFT method, electronic absorption spectra of the title compound have been predicted, and good agreement is determined with the experimental ones. To investigate the NLO properties of the title compound, the polarizability and the first hyperpolarizability were calculated using the density functional B3LYP method with the 6-311++G(d,p) basis set. According to results, the title compound exhibits non-zero first hyperpolarizability value revealing second order NLO behavior. In addition, DFT calculations of the title compound, molecular electrostatic potential and frontier molecular orbitals were also performed at 6-311++G(d,p) level of theory.

  2. Molecular structure and vibrational and chemical shift assignments of 3‧-chloro-4-dimethylamino azobenzene by DFT calculations

    Science.gov (United States)

    Toy, Mehmet; Tanak, Hasan

    2016-01-01

    In the present work, a combined experimental and theoretical study on ground state molecular structure, spectroscopic and nonlinear optical properties of azo compound 3‧-chloro-4-dimethlamino azobenzene are reported. The molecular geometry, vibrational wavenumbers and the first order hyperpolarizability of the title compound were calculated with the help of density functional theory computations. The optimized geometric parameters obtained by using DFT (B3LYP/6-311++G(d,p)) show good agreement with the experimental data. The vibrational transitions were identified based on the recorded FT-IR spectra in the range of 4000-400 cm-1 for solid state. The 1H isotropic chemical shifts with respect to TMS were also calculated using the gauge independent atomic orbital (GIAO) method and compared with the experimental data. Using the TD-DFT method, electronic absorption spectra of the title compound have been predicted, and good agreement is determined with the experimental ones. To investigate the NLO properties of the title compound, the polarizability and the first hyperpolarizability were calculated using the density functional B3LYP method with the 6-311++G(d,p) basis set. According to results, the title compound exhibits non-zero first hyperpolarizability value revealing second order NLO behavior. In addition, DFT calculations of the title compound, molecular electrostatic potential and frontier molecular orbitals were also performed at 6-311++G(d,p) level of theory.

  3. The local order of supercooled water in solution with LiCl studied by NMR proton chemical shift

    Science.gov (United States)

    Corsaro, C.; Mallamace, D.; Vasi, S.; Cicero, N.; Dugo, G.; Mallamace, F.

    2016-05-01

    We study by means of Nuclear Magnetic Resonance (NMR) spectroscopy the local order of water molecules in solution with lithium chloride at eutectic concentration. In particular, by measuring the proton chemical shift as a function of the temperature in the interval 203{ K}Widom line for water supporting the liquid-liquid transition hypothesis.

  4. Sequence correction of random coil chemical shifts: correlation between neighbor correction factors and changes in the Ramachandran distribution

    DEFF Research Database (Denmark)

    Kjærgaard, Magnus; Poulsen, Flemming Martin

    2011-01-01

    use random coil peptides containing glutamine instead of glycine to determine the random coil chemical shifts and the neighbor correction factors. The resulting correction factors correlate to changes in the populations of the major wells in the Ramachandran plot, which demonstrates that changes...

  5. Elucidation of the substitution pattern of 9,10-anthraquinones through the chemical shifts of peri-hydroxyl protons

    DEFF Research Database (Denmark)

    Schripsema, Jan; Danigno, Denise

    1996-01-01

    In 9,10-anthraquinones the chemical shift of a peri-hydroxyl proton is affected by the substituents in the other benzenoid ring. These effects are additive. They are useful for the determination of substitution patterns and have been used to revise the structures of six previously reported anthra...

  6. Analysis of the contributions of ring current and electric field effects to the chemical shifts of RNA bases.

    Science.gov (United States)

    Sahakyan, Aleksandr B; Vendruscolo, Michele

    2013-02-21

    Ring current and electric field effects can considerably influence NMR chemical shifts in biomolecules. Understanding such effects is particularly important for the development of accurate mappings between chemical shifts and the structures of nucleic acids. In this work, we first analyzed the Pople and the Haigh-Mallion models in terms of their ability to describe nitrogen base conjugated ring effects. We then created a database (DiBaseRNA) of three-dimensional arrangements of RNA base pairs from X-ray structures, calculated the corresponding chemical shifts via a hybrid density functional theory approach and used the results to parametrize the ring current and electric field effects in RNA bases. Next, we studied the coupling of the electric field and ring current effects for different inter-ring arrangements found in RNA bases using linear model fitting, with joint electric field and ring current, as well as only electric field and only ring current approximations. Taken together, our results provide a characterization of the interdependence of ring current and electric field geometric factors, which is shown to be especially important for the chemical shifts of non-hydrogen atoms in RNA bases.

  7. Correlation of 1H NMR Chemical Shift for Aqueous Solutions by Statistical Associating Fluid Theory Association Model

    Institute of Scientific and Technical Information of China (English)

    许波; 李浩然; 王从敏; 许映杰; 韩世钧

    2005-01-01

    1H NMR chemical shifts of binary aqueous mixtures of acylamide, alcohol, dimethyl sulphoxide (DMSO), and acetone are correlated by statistical associating fluid theory (SAFT) association model. The comparison between SAFT association model and Wilson equation shows that the former is better for dealing with aqueous solutions. Finally, the specialties of both models are discussed.

  8. Halogen effect on structure and 13C NMR chemical shift of 3,6-disubstituted-N-alkyl carbazoles

    DEFF Research Database (Denmark)

    Radula-Janik, Klaudia; Kupka, Teobald; Ejsmont, Krzysztof

    2013-01-01

    Structures of selected 3,6-dihalogeno-N-alkyl carbazole derivatives were calculated at the B3LYP/6-311++G(3df,2pd) level of theory and their 13C NMR isotropic nuclear shieldings were predicted using density functional theory (DFT). The model compounds contained 9H-, N-methyl and N-ethyl derivatives......). The decreasing electronegativity of the halogen substituent (F, Cl, Br and I) was reflected in both nonrelativistic and relativistic NMR results as decreased values of chemical shifts of carbon atoms attached to halogen (C3 and C6) leading to a strong sensitivity to halogen atom type at 3 and 6 positions...

  9. Economic model predictive control theory, formulations and chemical process applications

    CERN Document Server

    Ellis, Matthew; Christofides, Panagiotis D

    2017-01-01

    This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes. In addition to being...

  10. A comparison of chemical shift sensitivity of trifluoromethyl tags: optimizing resolution in {sup 19}F NMR studies of proteins

    Energy Technology Data Exchange (ETDEWEB)

    Ye, Libin; Larda, Sacha Thierry; Frank Li, Yi Feng [University of Toronto, UTM, Department of Chemistry (Canada); Manglik, Aashish [Stanford University School of Medicine, Department of Molecular and Cellular Physiology (United States); Prosser, R. Scott, E-mail: scott.prosser@utoronto.ca [University of Toronto, UTM, Department of Chemistry (Canada)

    2015-05-15

    The elucidation of distinct protein conformers or states by fluorine ({sup 19}F) NMR requires fluorinated moieties whose chemical shifts are most sensitive to subtle changes in the local dielectric and magnetic shielding environment. In this study we evaluate the effective chemical shift dispersion of a number of thiol-reactive trifluoromethyl probes [i.e. 2-bromo-N-(4-(trifluoromethyl)phenyl)acetamide (BTFMA), N-(4-bromo-3-(trifluoromethyl)phenyl)acetamide (3-BTFMA), 3-bromo-1,1,1-trifluoropropan-2-ol (BTFP), 1-bromo-3,3,4,4,4-pentafluorobutan-2-one (BPFB), 3-bromo-1,1,1-trifluoropropan-2-one (BTFA), and 2,2,2-trifluoroethyl-1-thiol (TFET)] under conditions of varying polarity. In considering the sensitivity of the {sup 19}F NMR chemical shift to the local environment, a series of methanol/water mixtures were prepared, ranging from relatively non-polar (MeOH:H{sub 2}O = 4) to polar (MeOH:H{sub 2}O = 0.25). {sup 19}F NMR spectra of the tripeptide, glutathione ((2S)-2-amino-4-{[(1R)-1-[(carboxymethyl)carbamoyl] -2-sulfanylethyl]carbamoyl}butanoic acid), conjugated to each of the above trifluoromethyl probes, revealed that the BTFMA tag exhibited a significantly greater range of chemical shift as a function of solvent polarity than did either BTFA or TFET. DFT calculations using the B3LYP hybrid functional and the 6-31G(d,p) basis set, confirmed the observed trend in chemical shift dispersion with solvent polarity.

  11. Combining a weed traits database with a population dynamics model predicts shifts in weed communities

    DEFF Research Database (Denmark)

    Storkey, Jonathan; Holst, Niels; Bøjer, Ole Mission;

    2015-01-01

    A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed......, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters....... These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated ‘fitness contours’ (defined as population growth rates) within...

  12. Predicting shifts in parasite distribution with climate change: a multitrophic level approach.

    Science.gov (United States)

    Pickles, Rob S A; Thornton, Daniel; Feldman, Richard; Marques, Adam; Murray, Dennis L

    2013-09-01

    Climate change likely will lead to increasingly favourable environmental conditions for many parasites. However, predictions regarding parasitism's impacts often fail to account for the likely variability in host distribution and how this may alter parasite occurrence. Here, we investigate potential distributional shifts in the meningeal worm, Parelaphostrongylosis tenuis, a protostrongylid nematode commonly found in white-tailed deer in North America, whose life cycle also involves a free-living stage and a gastropod intermediate host. We modelled the distribution of the hosts and free-living larva as a complete assemblage to assess whether a complex trophic system will lead to an overall increase in parasite distribution with climate change, or whether divergent environmental niches may promote an ecological mismatch. Using an ensemble approach to climate modelling under two different carbon emission scenarios, we show that whereas the overall trend is for an increase in niche breadth for each species, mismatches arise in habitat suitability of the free-living larva vs. the definitive and intermediate hosts. By incorporating these projected mismatches into a combined model, we project a shift in parasite distribution accounting for all steps in the transmission cycle, and identify that overall habitat suitability of the parasite will decline in the Great Plains and southeastern USA, but will increase in the Boreal Forest ecoregion, particularly in Alberta. These results have important implications for wildlife conservation and management due to the known pathogenicity of parelaphostrongylosis to alternate hosts including moose, caribou and elk. Our results suggest that disease risk forecasts which fail to consider biotic interactions may be overly simplistic, and that accounting for each of the parasite's life stages is key to refining predicted responses to climate change. © 2013 John Wiley & Sons Ltd.

  13. Changes of brain metabolite concentrations during maturation in different brain regions measured by chemical shift imaging

    Energy Technology Data Exchange (ETDEWEB)

    Bueltmann, Eva; Lanfermann, Heinrich [Hannover Medical School, Institute of Diagnostic and Interventional Neuroradiology, Hannover (Germany); Naegele, Thomas [University of Tuebingen, Department of Diagnostic and Interventional Neuroradiology, Radiological University Hospital, Tuebingen (Germany); Klose, Uwe [University of Tuebingen, Section of Experimental MR of the CNS, Department of Neuroradiology, Radiological University Hospital, Tuebingen (Germany)

    2017-01-15

    We examined the effect of maturation on the regional distribution of brain metabolite concentrations using multivoxel chemical shift imaging. From our pool of pediatric MRI examinations, we retrospectively selected patients showing a normal cerebral MRI scan or no pathologic signal abnormalities at the level of the two-dimensional 1H MRS-CSI sequence and an age-appropriate global neurological development, except for focal neurological deficits. Seventy-one patients (4.5 months-20 years) were identified. Using LC Model, spectra were evaluated from voxels in the white matter, caudate head, and corpus callosum. The concentration of total N-acetylaspartate increased in all regions during infancy and childhood except in the right caudate head where it remained constant. The concentration of total creatine decreased in the caudate nucleus and splenium and minimally in the frontal white matter and genu. It remained largely constant in the parietal white matter. The concentration of choline-containing compounds had the tendency to decrease in all regions except in the parietal white matter where it remained constant. The concentration of myoinositol decreased slightly in the splenium and right frontal white matter, remained constant on the left side and in the caudate nucleus, and rose slightly in the parietal white matter and genu. CSI determined metabolite concentrations in multiple cerebral regions during routine MRI. The obtained data will be helpful in future pediatric CSI measurements deciding whether the ratios of the main metabolites are within the range of normal values or have to be considered as probably pathologic. (orig.)

  14. Female sea lamprey shift orientation toward a conspecific chemical cue to escape a sensory trap

    Science.gov (United States)

    Brant, Cory O.; Johnson, Nicholas; Li, Ke; Buchinger, Tyler J.; Li, Weiming

    2016-01-01

    The sensory trap model of signal evolution hypothesizes that signalers adapt to exploit a cue used by the receiver in another context. Although exploitation of receiver biases can result in conflict between the sexes, deceptive signaling systems that are mutually beneficial drive the evolution of stable communication systems. However, female responses in the nonsexual and sexual contexts may become uncoupled if costs are associated with exhibiting a similar response to a trait in both contexts. Male sea lamprey (Petromyzon marinus) signal with a mating pheromone, 3-keto petromyzonol sulfate (3kPZS), which may be a match to a juvenile cue used by females during migration. Upstream movement of migratory lampreys is partially guided by 3kPZS, but females only move toward 3kPZS with proximal accuracy during spawning. Here, we use in-stream behavioral assays paired with gonad histology to document the transition of female preference for juvenile- and male-released 3kPZS that coincides with the functional shift of 3kPZS as a migratory cue to a mating pheromone. Females became increasingly biased toward the source of synthesized 3kPZS as their maturation progressed into the reproductive phase, at which point, a preference for juvenile odor (also containing 3kPZS naturally) ceased to exist. Uncoupling of female responses during migration and spawning makes the 3kPZS communication system a reliable means of synchronizing mate search. The present study offers a rare example of a transition in female responses to a chemical cue between nonsexual and sexual contexts, provides insights into the origins of stable communication signaling systems.

  15. Utilization of chemical shift MRI in the diagnosis of disorders affecting pediatric bone marrow.

    Science.gov (United States)

    Winfeld, Matthew; Ahlawat, Shivani; Safdar, Nabile

    2016-09-01

    MRI signal intensity of pediatric bone marrow can be difficult to interpret using conventional methods. Chemical shift imaging (CSI), which can quantitatively assess relative fat content, may improve the ability to accurately diagnose bone marrow abnormalities in children. Consecutive pelvis and extremity MRI at a children's hospital over three months were retrospectively reviewed for inclusion of CSI. Medical records were reviewed for final pathological and/or clinical diagnosis. Cases were classified as normal or abnormal, and if abnormal, subclassified as marrow-replacing or non-marrow-replacing entities. Regions of interest (ROI) were then drawn on corresponding in and out-of-phase sequences over the marrow abnormality or over a metaphysis and epiphysis in normal studies. Relative signal intensity ratio for each case was then calculated to determine the degree of fat content in the ROI. In all, 241 MRI were reviewed and 105 met inclusion criteria. Of these, 61 had normal marrow, 37 had non-marrow-replacing entities (osteomyelitis without abscess n = 17, trauma n = 9, bone infarction n = 8, inflammatory arthropathy n = 3), and 7 had marrow-replacing entities (malignant neoplasm n = 4, bone cyst n = 1, fibrous dysplasia n = 1, and Langerhans cell histiocytosis n = 1). RSIR averages were: normal metaphyseal marrow 0.442 (0.352-0.533), normal epiphyseal marrow 0.632 (0.566-698), non-marrow-replacing diagnoses 0.715 (0.630-0.799), and marrow-replacing diagnoses 1.06 (0.867-1.26). RSIR for marrow-replacing entities proved significantly different from all other groups (p < 0.05). ROC analysis demonstrated an AUC of 0.89 for RSIR in distinguishing marrow-replacing entities. CSI techniques can help to differentiate pathologic processes that replace marrow in children from those that do not.

  16. Identification of Zinc-ligated Cysteine Residues Based on {sup 13}C{alpha} and {sup 13}C{beta} Chemical Shift Data

    Energy Technology Data Exchange (ETDEWEB)

    Kornhaber, Gregory J.; Snyder, David; Moseley, Hunter N. B.; Montelione, Gaetano T. [Rutgers University, Center for Advanced Biotechnology and Medicine, Department of Molecular Biology and Biochemistry (United States)], E-mail: guy@cabm.rutgers.edu

    2006-04-15

    Although a significant number of proteins include bound metals as part of their structure, the identification of amino acid residues coordinated to non-paramagnetic metals by NMR remains a challenge. Metal ligands can stabilize the native structure and/or play critical catalytic roles in the underlying biochemistry. An atom's chemical shift is exquisitely sensitive to its electronic environment. Chemical shift data can provide valuable insights into structural features, including metal ligation. In this study, we demonstrate that overlapped {sup 13}C{beta} chemical shift distributions of Zn-ligated and non-metal-ligated cysteine residues are largely resolved by the inclusion of the corresponding {sup 13}C{alpha} chemical shift information, together with secondary structural information. We demonstrate this with a bivariate distribution plot, and statistically with a multivariate analysis of variance (MANOVA) and hierarchical logistic regression analysis. Using 287 {sup 13}C{alpha}/{sup 13}C{beta} shift pairs from 79 proteins with known three-dimensional structures, including 86 {sup 13}C{alpha} and{sup 13}C{beta} shifts for 43 Zn-ligated cysteine residues, along with corresponding oxidation state and secondary structure information, we have built a logistic regression model that distinguishes between oxidized cystines, reduced (non-metal ligated) cysteines, and Zn-ligated cysteines. Classifying cysteines/cystines with a statisical model incorporating all three phenomena resulted in a predictor of Zn ligation with a recall, precision and F-measure of 83.7%, and an accuracy of 95.1%. This model was applied in the analysis of Bacillus subtilis IscU, a protein involved in iron-sulfur cluster assembly. The model predicts that all three cysteines of IscU are metal ligands. We confirmed these results by (i) examining the effect of metal chelation on the NMR spectrum of IscU, and (ii) inductively coupled plasma mass spectrometry analysis. To gain further insight into

  17. Pressure dependence of side chain (13)C chemical shifts in model peptides Ac-Gly-Gly-Xxx-Ala-NH2.

    Science.gov (United States)

    Beck Erlach, Markus; Koehler, Joerg; Crusca, Edson; Munte, Claudia E; Kainosho, Masatsune; Kremer, Werner; Kalbitzer, Hans Robert

    2017-09-14

    For evaluating the pressure responses of folded as well as intrinsically unfolded proteins detectable by NMR spectroscopy the availability of data from well-defined model systems is indispensable. In this work we report the pressure dependence of (13)C chemical shifts of the side chain atoms in the protected tetrapeptides Ac-Gly-Gly-Xxx-Ala-NH2 (Xxx, one of the 20 canonical amino acids). Contrary to expectation the chemical shifts of a number of nuclei have a nonlinear dependence on pressure in the range from 0.1 to 200 MPa. The size of the polynomial pressure coefficients B 1 and B 2 is dependent on the type of atom and amino acid studied. For H(N), N and C(α) the first order pressure coefficient B 1 is also correlated to the chemical shift at atmospheric pressure. The first and second order pressure coefficients of a given type of carbon atom show significant linear correlations suggesting that the NMR observable pressure effects in the different amino acids have at least partly the same physical cause. In line with this observation the magnitude of the second order coefficients of nuclei being direct neighbors in the chemical structure also are weakly correlated. The downfield shifts of the methyl resonances suggest that gauche conformers of the side chains are not preferred with pressure. The valine and leucine methyl groups in the model peptides were assigned using stereospecifically (13)C enriched amino acids with the pro-R carbons downfield shifted relative to the pro-S carbons.

  18. Combining a weed traits database with a population dynamics model predicts shifts in weed communities.

    Science.gov (United States)

    Storkey, J; Holst, N; Bøjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sønderskov, M; Verschwele, A

    2015-04-01

    A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

  19. Seasonally Varying Predation Behavior and Climate Shifts Are Predicted to Affect Predator-Prey Cycles.

    Science.gov (United States)

    Tyson, Rebecca; Lutscher, Frithjof

    2016-11-01

    The functional response of some predator species changes from a pattern characteristic for a generalist to that for a specialist according to seasonally varying prey availability. Current theory does not address the dynamic consequences of this phenomenon. Since season length correlates strongly with altitude and latitude and is predicted to change under future climate scenarios, including this phenomenon in theoretical models seems essential for correct prediction of future ecosystem dynamics. We develop and analyze a two-season model for the great horned owl (Bubo virginialis) and snowshoe hare (Lepus americanus). These species form a predator-prey system in which the generalist to specialist shift in predation pattern has been documented empirically. We study the qualitative behavior of this predator-prey model community as summer season length changes. We find that relatively small changes in summer season length can have a profound impact on the system. In particular, when the predator has sufficient alternative resources available during the summer season, it can drive the prey to extinction, there can be coexisting stable states, and there can be stable large-amplitude limit cycles coexisting with a stable steady state. Our results illustrate that the impacts of global change on local ecosystems can be driven by internal system dynamics and can potentially have catastrophic consequences.

  20. Decoding the Charitable Brain: Empathy, Perspective Taking, and Attention Shifts Differentially Predict Altruistic Giving.

    Science.gov (United States)

    Tusche, Anita; Böckler, Anne; Kanske, Philipp; Trautwein, Fynn-Mathis; Singer, Tania

    2016-04-27

    Altruistic behavior varies considerably across people and decision contexts. The relevant computational and motivational mechanisms that underlie its heterogeneity, however, are poorly understood. Using a charitable giving task together with multivariate decoding techniques, we identified three distinct psychological mechanisms underlying altruistic decision-making (empathy, perspective taking, and attentional reorienting) and linked them to dissociable neural computations. Neural responses in the anterior insula (AI) (but not temporoparietal junction [TPJ]) encoded trial-wise empathy for beneficiaries, whereas the TPJ (but not AI) predicted the degree of perspective taking. Importantly, the relative influence of both socio-cognitive processes differed across individuals: participants whose donation behavior was heavily influenced by affective empathy exhibited higher predictive accuracies for generosity in AI, whereas those who strongly relied on cognitive perspective taking showed improved predictions of generous donations in TPJ. Furthermore, subject-specific contributions of both processes for donations were reflected in participants' empathy and perspective taking responses in a separate fMRI task (EmpaToM), suggesting that process-specific inputs into altruistic choices may reflect participants' general propensity to either empathize or mentalize. Finally, using independent attention task data, we identified shared neural codes for attentional reorienting and generous donations in the posterior superior temporal sulcus, suggesting that domain-general attention shifts also contribute to generous behavior (but not in TPJ or AI). Overall, our findings demonstrate highly specific roles of AI for affective empathy and TPJ for cognitive perspective taking as precursors of prosocial behavior and suggest that these discrete routes of social cognition differentially drive intraindividual and interindividual differences in altruistic behavior. Human societies depend on

  1. Predictions of Chemical Weather in Asia: The EU Panda Project

    Science.gov (United States)

    Brasseur, G. P.; Petersen, A. K.; Wang, X.; Granier, C.; Bouarar, I.

    2014-12-01

    Air quality has become a pressing problem in Asia and specifically in China due to rapid economic development (i.e., rapidly expanding motor vehicle fleets, growing industrial and power generation activities, domestic and biomass burning). In spite of efforts to reduce chemical emissions, high levels of particle matter and ozone are observed and lead to severe health problems with a large number of premature deaths. To support efforts to reduce air pollution, the European Union is supporting the PANDA project whose objective is to use space and surface observations of chemical species as well as advanced meteorological and chemical models to analyze and predict air quality in China. The Project involves 7 European and 7 Chinese groups. The paper will describe the objectives of the project and present some first accomplishments. The project focuses on the improvement of methods for monitoring air quality from combined space and in-situ observations, the development of a comprehensive prediction system that makes use of these observations, the elaboration of indicators for air quality in support of policies, and the development of toolboxes for the dissemination of information.

  2. Modelling Chemical Reasoning to Predict and Invent Reactions.

    Science.gov (United States)

    Segler, Marwin H S; Waller, Mark P

    2016-11-11

    The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery.

  3. Proton Chemical Shift Imaging of the Brain in Pediatric and Adult Developmental Stuttering.

    Science.gov (United States)

    O'Neill, Joseph; Dong, Zhengchao; Bansal, Ravi; Ivanov, Iliyan; Hao, Xuejun; Desai, Jay; Pozzi, Elena; Peterson, Bradley S

    2017-01-01

    Developmental stuttering is a neuropsychiatric condition of incompletely understood brain origin. Our recent functional magnetic resonance imaging study indicates a possible partial basis of stuttering in circuits enacting self-regulation of motor activity, attention, and emotion. To further characterize the neurophysiology of stuttering through in vivo assay of neurometabolites in suspect brain regions. Proton chemical shift imaging of the brain was performed in a case-control study of children and adults with and without stuttering. Recruitment, assessment, and magnetic resonance imaging were performed in an academic research setting. Ratios of N-acetyl-aspartate plus N-acetyl-aspartyl-glutamate (NAA) to creatine (Cr) and choline compounds (Cho) to Cr in widespread cerebral cortical, white matter, and subcortical regions were analyzed using region of interest and data-driven voxel-based approaches. Forty-seven children and adolescents aged 5 to 17 years (22 with stuttering and 25 without) and 47 adults aged 21 to 51 years (20 with stuttering and 27 without) were recruited between June 2008 and March 2013. The mean (SD) ages of those in the stuttering and control groups were 12.2 (4.2) years and 13.4 (3.2) years, respectively, for the pediatric cohort and 31.4 (7.5) years and 30.5 (9.9) years, respectively, for the adult cohort. Region of interest-based findings included lower group mean NAA:Cr ratio in stuttering than nonstuttering participants in the right inferior frontal cortex (-7.3%; P = .02), inferior frontal white matter (-11.4%; P stuttering sample included higher NAA:Cr and Cho:Cr ratios (regression coefficient, 197.4-275; P stuttering severity (r = 0.40-0.52; P = .001-.02). This spectroscopy study of stuttering demonstrates brainwide neurometabolite alterations, including several regions implicated by other neuroimaging modalities. Prior ascription of a role in stuttering to inferior frontal and superior temporal gyri, caudate, and other

  4. NMR chemical shift pattern changed by ammonium sulfate precipitation in cyanobacterial phytochrome Cph1

    Directory of Open Access Journals (Sweden)

    Chen eSong

    2015-07-01

    Full Text Available Phytochromes are dimeric biliprotein photoreceptors exhibiting characteristic red/far-red photocycles. Full-length cyanobacterial phytochrome Cph1 from Synechocystis 6803 is soluble initially but tends to aggregate in a concentration-dependent manner, hampering attempts to solve the structure using NMR and crystallization methods. Otherwise, the Cph1 sensory module (Cph1Δ2, photochemically indistinguishable from the native protein and used extensively in structural and other studies, can be purified to homogeneity in >10 mg amounts at mM concentrations quite easily. Bulk precipitation of full-length Cph1 by ammonium sulfate (AmS was expected to allow us to produce samples for solid-state magic-angle spinning (MAS NMR from dilute solutions before significant aggregation began. It was not clear, however, what effects the process of partial dehydration might have on the molecular structure. Here we test this by running solid-state MAS NMR experiments on AmS-precipitated Cph1Δ2 in its red-absorbing Pr state carrying uniformly 13C/15N-labeled phycocyanobilin (PCB chromophore. 2D 13C–13C correlation experiments allowed a complete assignment of 13C responses of the chromophore. Upon precipitation, 13C chemical shifts for most of PCB carbons move upfield, in which we found major changes for C4 and C6 atoms associated with the A-ring positioning. Further, the broad spectral lines seen in the AmS 13C spectrum reflect primarily the extensive homogeneous broadening presumably due to an increase in the distribution of conformational states in the protein, in which less free water is available to partake in the hydration shells. Our data suggest that dehydration indeed leads to motional and electronic structural changes of the bilin chromophore and its binding pocket and is not restricted to the protein surface. The extent of the changes induced differs from the freezing process of the solution samples routinely used in previous MAS NMR and

  5. NMR chemical shift pattern changed by ammonium sulfate precipitation in cyanobacterial phytochrome Cph1.

    Science.gov (United States)

    Song, Chen; Lang, Christina; Kopycki, Jakub; Hughes, Jon; Matysik, Jörg

    2015-01-01

    Phytochromes are dimeric biliprotein photoreceptors exhibiting characteristic red/far-red photocycles. Full-length cyanobacterial phytochrome Cph1 from Synechocystis 6803 is soluble initially but tends to aggregate in a concentration-dependent manner, hampering attempts to solve the structure using NMR and crystallization methods. Otherwise, the Cph1 sensory module (Cph1Δ2), photochemically indistinguishable from the native protein and used extensively in structural and other studies, can be purified to homogeneity in >10 mg amounts at mM concentrations quite easily. Bulk precipitation of full-length Cph1 by ammonium sulfate (AmS) was expected to allow us to produce samples for solid-state magic-angle spinning (MAS) NMR from dilute solutions before significant aggregation began. It was not clear, however, what effects the process of partial dehydration might have on the molecular structure. Here we test this by running solid-state MAS NMR experiments on AmS-precipitated Cph1Δ2 in its red-absorbing Pr state carrying uniformly (13)C/(15)N-labeled phycocyanobilin (PCB) chromophore. 2D (13)C-(13)C correlation experiments allowed a complete assignment of (13)C responses of the chromophore. Upon precipitation, (13)C chemical shifts for most of PCB carbons move upfield, in which we found major changes for C4 and C6 atoms associated with the A-ring positioning. Further, the broad spectral lines seen in the AmS (13)C spectrum reflect primarily the extensive inhomogeneous broadening presumably due to an increase in the distribution of conformational states in the protein, in which less free water is available to partake in the hydration shells. Our data suggest that the effect of dehydration process indeed leads to changes of electronic structure of the bilin chromophore and a decrease in its mobility within the binding pocket, but not restricted to the protein surface. The extent of the changes induced differs from the freezing process of the solution samples routinely

  6. Modeling Nonlinear Adsorption with a Single Chemical Parameter: Predicting Chemical Median Langmuir Binding Constants.

    Science.gov (United States)

    Davis, Craig Warren; Di Toro, Dominic M

    2015-07-07

    Procedures for accurately predicting linear partition coefficients onto various sorbents (e.g., organic carbon, soils, clay) are reliable and well established. However, similar procedures for the prediction of sorption parameters of nonlinear isotherm models are not. The purpose of this paper is to present a procedure for predicting nonlinear isotherm parameters, specifically the median Langmuir binding constants, K̃L, obtained utilizing the single-chemical parameter log-normal Langmuir isotherm developed in the accompanying work. A reduced poly parameter linear free energy relationship (pp-LFER) is able to predict median Langmuir binding constants for graphite, charcoal, and Darco granular activated carbon (GAC) adsorption data. For the larger F400 GAC data set, a single pp-LFER model was insufficient, as a plateau is observed for the median Langmuir binding constants of larger molecular volume sorbates. This volumetric cutoff occurs in proximity to the median pore diameter for F400 GAC. A log-linear relationship exists between the aqueous solubility of these large compounds and their median Langmuir binding constants. Using this relationship for the chemicals above the volumetric cutoff and the pp-LFER below the cutoff, the median Langmuir binding constants can be predicted with a root-mean square error for graphite (n = 13), charcoal (n = 11), Darco GAC (n = 14), and F400 GAC (n = 44) of 0.129, 0.307, 0.407, and 0.424, respectively.

  7. Cuticular hydrocarbon divergence in the jewel wasp Nasonia : evolutionary shifts in chemical communication channels?

    NARCIS (Netherlands)

    Buellesbach, J.; Gadau, J.; Beukeboom, L. W.; Echinger, F.; Raychoudhury, R.; Werren, J. H.; Schmitt, T.

    2013-01-01

    The evolution and maintenance of intraspecific communication channels constitute a key feature of chemical signalling and sexual communication. However, how divergent chemical communication channels evolve while maintaining their integrity for both sender and receiver is poorly understood. In this s

  8. Combining ambiguous chemical shift mapping with structure-based backbone and NOE assignment from 15N-NOESY

    KAUST Repository

    Jang, Richard

    2011-01-01

    Chemical shift mapping is an important technique in NMRbased drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecule\\'s introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically. However, automated methods are necessary for high-throughput drug screening. We present PeakWalker, a novel peak walking algorithm for fast-exchange systems that models the errors explicitly and performs many-to-one mapping. On the proteins: hBclXL, UbcH5B, and histone H1, it achieves an average accuracy of over 95% with less than 1.5 residues predicted per target peak. Given these mappings as input, we present PeakAssigner, a novel combined structure-based backbone resonance and NOE assignment algorithm that uses just 15N-NOESY, while avoiding TOCSY experiments and 13C- labeling, to resolve the ambiguities for a one-toone mapping. On the three proteins, it achieves an average accuracy of 94% or better. Copyright © 2011 ACM.

  9. A NMR experiment for simultaneous correlations of valine and leucine/isoleucine methyls with carbonyl chemical shifts in proteins.

    Science.gov (United States)

    Tugarinov, Vitali; Venditti, Vincenzo; Marius Clore, G

    2014-01-01

    A methyl-detected 'out-and-back' NMR experiment for obtaining simultaneous correlations of methyl resonances of valine and isoleucine/leucine residues with backbone carbonyl chemical shifts, SIM-HMCM(CGCBCA)CO, is described. The developed pulse-scheme serves the purpose of convenience in recording a single data set for all Ile(δ1), Leu(δ) and Val(γ) (ILV) methyl positions instead of acquiring two separate spectra selective for valine or leucine/isoleucine residues. The SIM-HMCM(CGCBCA)CO experiment can be used for ILV methyl assignments in moderately sized protein systems (up to ~100 kDa) where the backbone chemical shifts of (13)C(α), (13)Cβ and (13)CO are known from prior NMR studies and where some losses in sensitivity can be tolerated for the sake of an overall reduction in NMR acquisition time.

  10. Stereochemistry of Complex Marine Natural Products by Quantum Mechanical Calculations of NMR Chemical Shifts: Solvent and Conformational Effects on Okadaic Acid

    Directory of Open Access Journals (Sweden)

    Humberto J. Domínguez

    2014-01-01

    Full Text Available Marine organisms are an increasingly important source of novel metabolites, some of which have already inspired or become new drugs. In addition, many of these molecules show a high degree of novelty from a structural and/or pharmacological point of view. Structure determination is generally achieved by the use of a variety of spectroscopic methods, among which NMR (nuclear magnetic resonance plays a major role and determination of the stereochemical relationships within every new molecule is generally the most challenging part in structural determination. In this communication, we have chosen okadaic acid as a model compound to perform a computational chemistry study to predict 1H and 13C NMR chemical shifts. The effect of two different solvents and conformation on the ability of DFT (density functional theory calculations to predict the correct stereoisomer has been studied.

  11. Computer programming for nucleic acid studies. II. Total chemical shifts calculation of all protons of double-stranded helices.

    Science.gov (United States)

    Giessner-Prettre, C; Ribas Prado, F; Pullman, B; Kan, L; Kast, J R; Ts'o, P O

    1981-01-01

    A FORTRAN computer program called SHIFTS is described. Through SHIFTS, one can calculate the NMR chemical shifts of the proton resonances of single and double-stranded nucleic acids of known sequences and of predetermined conformations. The program can handle RNA and DNA for an arbitrary sequence of a set of 4 out of the 6 base types A,U,G,C,I and T. Data files for the geometrical parameters are available for A-, A'-, B-, D- and S-conformations. The positions of all the atoms are calculated using a modified version of the SEQ program [1]. Then, based on this defined geometry three chemical shift effects exerted by the atoms of the neighboring nucleotides on the protons of each monomeric unit are calculated separately: the ring current shielding effect: the local atomic magnetic susceptibility effect (including both diamagnetic and paramagnetic terms); and the polarization or electric field effect. Results of the program are compared with experimental results for a gamma (ApApGpCpUpU) 2 helical duplex and with calculated results on this same helix based on model building of A'-form and B-form and on graphical procedure for evaluating the ring current effects.

  12. Towards the versatile DFT and MP2 computational schemes for 31P NMR chemical shifts taking into account relativistic corrections.

    Science.gov (United States)

    Fedorov, Sergey V; Rusakov, Yury Yu; Krivdin, Leonid B

    2014-11-01

    The main factors affecting the accuracy and computational cost of the calculation of (31)P NMR chemical shifts in the representative series of organophosphorous compounds are examined at the density functional theory (DFT) and second-order Møller-Plesset perturbation theory (MP2) levels. At the DFT level, the best functionals for the calculation of (31)P NMR chemical shifts are those of Keal and Tozer, KT2 and KT3. Both at the DFT and MP2 levels, the most reliable basis sets are those of Jensen, pcS-2 or larger, and those of Pople, 6-311G(d,p) or larger. The reliable basis sets of Dunning's family are those of at least penta-zeta quality that precludes their practical consideration. An encouraging finding is that basically, the locally dense basis set approach resulting in a dramatic decrease in computational cost is justified in the calculation of (31)P NMR chemical shifts within the 1-2-ppm error. Relativistic corrections to (31)P NMR absolute shielding constants are of major importance reaching about 20-30 ppm (ca 7%) improving (not worsening!) the agreement of calculation with experiment. Further better agreement with the experiment by 1-2 ppm can be obtained by taking into account solvent effects within the integral equation formalism polarizable continuum model solvation scheme. We recommend the GIAO-DFT-KT2/pcS-3//pcS-2 scheme with relativistic corrections and solvent effects taken into account as the most versatile computational scheme for the calculation of (31)P NMR chemical shifts characterized by a mean absolute error of ca 9 ppm in the range of 550 ppm.

  13. Porosity prediction of calcium phosphate cements based on chemical composition.

    Science.gov (United States)

    Öhman, Caroline; Unosson, Johanna; Carlsson, Elin; Ginebra, Maria Pau; Persson, Cecilia; Engqvist, Håkan

    2015-07-01

    The porosity of calcium phosphate cements has an impact on several important parameters, such as strength, resorbability and bioactivity. A model to predict the porosity for biomedical cements would hence be a useful tool. At the moment such a model only exists for Portland cements. The aim of this study was to develop and validate a first porosity prediction model for calcium phosphate cements. On the basis of chemical reaction, molar weight and density of components, a volume-based model was developed and validated using calcium phosphate cement as model material. 60 mol% β-tricalcium phosphate and 40 mol% monocalcium phosphate monohydrate were mixed with deionized water, at different liquid-to-powder ratios. Samples were set for 24 h at 37°C and 100% relative humidity. Thereafter, samples were dried either under vacuum at room temperature for 24 h or in air at 37 °C for 7 days. Porosity and phase composition were determined. It was found that the two drying protocols led to the formation of brushite and monetite, respectively. The model was found to predict well the experimental values and also data reported in the literature for apatite cements, as deduced from the small absolute average residual errors (brushite, monetite and apatite cements. The model gives a good estimate of the final porosity and has the potential to be used as a porosity prediction tool in the biomedical cement field.

  14. Measuring {sup 13}C{sup {beta}} chemical shifts of invisible excited states in proteins by relaxation dispersion NMR spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Lundstroem, Patrik [Linkoeping University, Molecular Biotechnology/IFM (Sweden); Lin Hong [Hospital for Sick Children, Molecular Structure and Function (Canada); Kay, Lewis E. [University of Toronto, Department of Medical Genetics (Canada)], E-mail: kay@pound.med.utoronto.ca

    2009-07-15

    A labeling scheme is introduced that facilitates the measurement of accurate {sup 13}C{sup {beta}} chemical shifts of invisible, excited states of proteins by relaxation dispersion NMR spectroscopy. The approach makes use of protein over-expression in a strain of E. coli in which the TCA cycle enzyme succinate dehydrogenase is knocked out, leading to the production of samples with high levels of {sup 13}C enrichment (30-40%) at C{sup {beta}} side-chain carbon positions for 15 of the amino acids with little {sup 13}C label at positions one bond removed ({approx}5%). A pair of samples are produced using [1-{sup 13}C]-glucose/NaH{sup 12}CO{sub 3} or [2-{sup 13}C]-glucose as carbon sources with isolated and enriched (>30%) {sup 13}C{sup {beta}} positions for 11 and 4 residues, respectively. The efficacy of the labeling procedure is established by NMR spectroscopy. The utility of such samples for measurement of {sup 13}C{sup {beta}} chemical shifts of invisible, excited states in exchange with visible, ground conformations is confirmed by relaxation dispersion studies of a protein-ligand binding exchange reaction in which the extracted chemical shift differences from dispersion profiles compare favorably with those obtained directly from measurements on ligand free and fully bound protein samples.

  15. Chemical shift of Mn and Cr K-edges in X-ray absorption spectroscopy with synchrotron radiation

    Indian Academy of Sciences (India)

    D Joseph; A K Yadav; S N Jha; D Bhattacharyya

    2013-11-01

    Mn and Cr K X-ray absorption edges were measured in various compounds containing Mn in Mn2+, Mn3+ and Mn4+ oxidation states and Cr in Cr3+ and Cr6+ oxidation states. Few compounds possess tetrahedral coordination in the 1st shell surrounding the cation while others possess octahedral coordination. Measurements have been carried out at the energy dispersive EXAFS beamline at INDUS-2 Synchrotron Radiation Source at Raja Ramanna Centre for Advanced Technology, Indore. Energy shifts of ∼8–16 eV were observed for Mn K edge in the Mn-compounds while a shift of 13–20 eV was observed for Cr K edge in Cr-compounds compared to values in elementalMn and Cr, respectively. The different chemical shifts observed for compounds having the same oxidation state of the cation but different anions or ligands show the effect of different chemical environments surrounding the cations in determining their X-ray absorption edges in the above compounds. The above chemical effect has been quantitatively described by determining the effective charges on Mn and Cr cations in the above compounds.

  16. Chemical production in electrocautery smoke by a novel predictive model.

    Science.gov (United States)

    Wu, Y-C; Tang, C-S; Huang, H-Y; Liu, C-H; Chen, Y-L; Chen, D-R; Lin, Y-W

    2011-01-01

    The hazards of electrocautery smoke have been known for decades. However, few clinical studies have been conducted to analyze the responsible variables of the smoke production. This study collected clinical smoke samples and systematically analyzed all possible factors. Thirty diathermy smoke samples were collected during mastectomy and abdominal cavity operations. Samples were analyzed using a gas chromatographer with a flame ionization detector. Data were applied to construct prediction models for chemical production from electrosurgeries to identify all possible factors that impact chemical production during electrosurgery. Toluene was detected in 27 smoke samples (90%) with concentrations of 0.003-0.463 mg/m(3) and production of 176.0-2,780.0 ng. Ethyl benzene and styrene were identified in very few cases. General linear regression analysis demonstrates that surgery type, patient age, electrocautery duration and imparted coagulation energy explained 67.63% of the variation in toluene production. Surgery type and patient age are known prior to surgery. In terms of risk precaution, the operating team should pay close attention to exposure when certain positive factors of increasing the chemical production are known in advance. Copyright © 2011 S. Karger AG, Basel.

  17. Structural Expression of Chemical Environment and C-13 NMR Chemical Shift for Carbons in Alcohols%脂肪醇分子碳环境结构表征与碳谱化学位移

    Institute of Scientific and Technical Information of China (English)

    刘树深; 徐红

    2000-01-01

    A novel atomic electronegative distance vector (AEDV) has been developed to express the chemical environment of various equivalent carbon in alcohols and four 4-parameter linear relationship between chemical shift and AEDV are created by using multiple linear regression.

  18. Improved Prediction of CYP-Mediated Metabolism with Chemical Fingerprints.

    Science.gov (United States)

    Zaretzki, Jed; Boehm, Kevin M; Swamidass, S Joshua

    2015-05-26

    Molecule and atom fingerprints, similar to path-based Daylight fingerprints, can substantially improve the accuracy of P450 site-of-metabolism prediction models. Only two chemical fingerprints have been used in metabolism prediction, so little is known about the importance of fingerprint parameters on site of metabolism predictions. It is possible that different fingerprints might yield more accurate models. Here, we study if tuning fingerprints to specific site of metabolism data sets can lead to improved models. We measure the impact of 484 specific chemical fingerprints on the accuracy of P450 site-of-metabolism prediction models on nine P450 isoform site of metabolism data sets. Using a range of search depths, we study path, circular, and subgraph fingerprints. Two different labelings, also, are considered, both standard SMILES labels and also a labeling that marks ring bonds differently than nonring bonds, enabling ortho, para, and meta positioning of substituents to be more clearly encoded. Optimal fingerprint models chosen by cross-validation performance on the full training data are, on average, 3.8% (Top-2; percent of molecules with a site of metabolism in the top two predictions) and 1.4% (AUC; area under the ROC curve) more accurate than base fingerprint models. These gains represent, respectively, a 25.6% and 16.7% reduction in error. A more rigorous assessment selects fingerprints within each cross-validation fold, sometimes selecting different fingerprints for different folds, but yielding a more reliable estimate of generalization error. In this assessment, averaging the scores from the top few fingerprints yields performances improvements of, on average, 3.0% (Top-2) and 0.7% (AUC). These gains are statistically significant and represent, respectively, a 20.1% and 8.8% reduction in error. Between different isoforms, not many consistencies were observed among the top performing fingerprints, with different fingerprints working best for different

  19. Bonding and chemical shifts in aluminosilicate glasses: importance of Madelung effects

    CERN Document Server

    Cruguel, H; Kerjan, O; Bart, F; Gautier-Soyer, M

    2003-01-01

    A detailed study of the XPS binding energy shifts of Si 2p, O 1s and Zr 3d in a series of aluminosilicate glasses (a three oxide glass: SiO sub 2 -Al sub 2 O sub 3 -CaO, three four-oxide glasses: SiO sub 2 -Al sub 2 O sub 3 -CaO-TiO sub 2 , ZrO sub 2 or CeO sub 2 , along with a six-oxide glass SiO sub 2 -Al sub 2 O sub 3 -CaO-TiO sub 2 -ZrO sub 2 -CeO sub 2) is presented. Their composition is such that these glasses have the same mean electronegativity, so that no changes in the atomic charges is expected. The binding energy shifts are interpreted in terms of initial and final state effects, and the balance of charge transfer contribution and electrostatic effects is discussed. Referred to the ternary glass, the binding energy shifts of the Si 2p, O 1s and Zr 3d lines in the complex glasses are due to an initial state effect, as the extraatomic relaxation is similar along the glass series. These shifts originate from electrostatic Madelung effects, likely coming from a structural change induced by the presenc...

  20. Thalassiosira spp. community composition shifts in response to chemical and physical forcing in the northeast Pacific Ocean.

    Science.gov (United States)

    Chappell, P Dreux; Whitney, Leeann P; Haddock, Traci L; Menden-Deuer, Susanne; Roy, Eric G; Wells, Mark L; Jenkins, Bethany D

    2013-01-01

    Diatoms are genetically diverse unicellular photosynthetic eukaryotes that are key primary producers in the ocean. Many of the over 100 extant diatom species in the cosmopolitan genus Thalassiosira are difficult to distinguish in mixed populations using light microscopy. Here, we examine shifts in Thalassiosira spp. composition along a coastal to open ocean transect that encountered a 3-month-old Haida eddy in the northeast Pacific Ocean. To quantify shifts in Thalassiosira species composition, we developed a targeted automated ribosomal intergenic spacer analysis (ARISA) method to identify Thalassiosira spp. in environmental samples. As many specific fragment lengths are indicative of individual Thalassiosira spp., the ARISA method is a useful screening tool to identify changes in the relative abundance and distribution of specific species. The method also enabled us to assess changes in Thalassiosira community composition in response to chemical and physical forcing. Thalassiosira spp. community composition in the core of a 3-month-old Haida eddy remained largely (>80%) similar over a 2-week period, despite moving 24 km southwestward. Shifts in Thalassiosira species correlated with changes in dissolved iron (Fe) and temperature throughout the sampling period. Simultaneously tracking community composition and relative abundance of Thalassiosira species within the physical and chemical context they occurred allowed us to identify quantitative linkages between environmental conditions and community response.

  1. Thalassiosira spp. community composition shifts in response to chemical and physical forcing in the northeast Pacific Ocean.

    Directory of Open Access Journals (Sweden)

    Phoebe Dreux Chappell

    2013-09-01

    Full Text Available Diatoms are genetically diverse unicellular photosynthetic eukaryotes that are key primary producers in the ocean. Many of the over 100 extant diatom species in the cosmopolitan genus Thalassiosira are difficult to distinguish in mixed populations using light microscopy. Here we examine shifts in Thalassiosira spp. composition along a coastal to open ocean transect that encountered a three-month-old Haida eddy in the northeast Pacific Ocean. To quantify shifts in Thalassiosira species composition, we developed a targeted automated ribosomal intergenic spacer analysis (ARISA method to identify Thalassiosira spp. in environmental samples. As many specific fragment lengths are indicative of individual Thalassiosira spp., the ARISA method is a useful screening tool to identify changes in the relative abundance and distribution of specific species. The method also enabled us to assess changes in Thalassiosira community composition in response to chemical and physical forcing. Thalassiosira spp. community composition in the core of a three-month-old Haida eddy remained largely (>80% similar over a two-week period, despite moving 24 km southwestward. Shifts in Thalassiosira species correlated with changes in dissolved iron (Fe and temperature throughout the sampling period. Simultaneously tracking community composition and relative abundance of Thalassiosira species within the physical and chemical context they occurred allowed us to identify quantitative linkages between environmental conditions and community response.

  2. Observed and calculated 1H and 13C chemical shifts induced by the in situ oxidation of model sulfides to sulfoxides and sulfones.

    Science.gov (United States)

    Dracínský, Martin; Pohl, Radek; Slavetínská, Lenka; Budesínský, Milos

    2010-09-01

    A series of model sulfides was oxidized in the NMR sample tube to sulfoxides and sulfones by the stepwise addition of meta-chloroperbenzoic acid in deuterochloroform. Various methods of quantum chemical calculations have been tested to reproduce the observed (1)H and (13)C chemical shifts of the starting sulfides and their oxidation products. It has been shown that the determination of the energy-minimized conformation is a very important condition for obtaining realistic data in the subsequent calculation of the NMR chemical shifts. The correlation between calculated and observed chemical shifts is very good for carbon atoms (even for the 'cheap' DFT B3LYP/6-31G* method) and somewhat less satisfactory for hydrogen atoms. The calculated chemical shifts induced by oxidation (the Delta delta values) agree even better with the experimental values and can also be used to determine the oxidation state of the sulfur atom (-S-, -SO-, -SO(2)-).

  3. A temporal predictive code for voice motor control: Evidence from ERP and behavioral responses to pitch-shifted auditory feedback.

    Science.gov (United States)

    Behroozmand, Roozbeh; Sangtian, Stacey; Korzyukov, Oleg; Larson, Charles R

    2016-04-01

    The predictive coding model suggests that voice motor control is regulated by a process in which the mismatch (error) between feedforward predictions and sensory feedback is detected and used to correct vocal motor behavior. In this study, we investigated how predictions about timing of pitch perturbations in voice auditory feedback would modulate ERP and behavioral responses during vocal production. We designed six counterbalanced blocks in which a +100 cents pitch-shift stimulus perturbed voice auditory feedback during vowel sound vocalizations. In three blocks, there was a fixed delay (500, 750 or 1000 ms) between voice and pitch-shift stimulus onset (predictable), whereas in the other three blocks, stimulus onset delay was randomized between 500, 750 and 1000 ms (unpredictable). We found that subjects produced compensatory (opposing) vocal responses that started at 80 ms after the onset of the unpredictable stimuli. However, for predictable stimuli, subjects initiated vocal responses at 20 ms before and followed the direction of pitch shifts in voice feedback. Analysis of ERPs showed that the amplitudes of the N1 and P2 components were significantly reduced in response to predictable compared with unpredictable stimuli. These findings indicate that predictions about temporal features of sensory feedback can modulate vocal motor behavior. In the context of the predictive coding model, temporally-predictable stimuli are learned and reinforced by the internal feedforward system, and as indexed by the ERP suppression, the sensory feedback contribution is reduced for their processing. These findings provide new insights into the neural mechanisms of vocal production and motor control.

  4. Predicting shifts in rainfall-runoff partitioning during multiyear drought: Roles of dry period and catchment characteristics

    Science.gov (United States)

    Saft, Margarita; Peel, Murray C.; Western, Andrew W.; Zhang, Lu

    2016-12-01

    While the majority of hydrological prediction methods assume that observed interannual variability explores the full range of catchment response dynamics, recent cases of prolonged climate drying suggest otherwise. During the ˜decade-long Millennium drought in south-eastern Australia significant shifts in hydrologic behavior were reported. Catchment rainfall-runoff partitioning changed from what was previously encountered during shorter droughts, with significantly less runoff than expected occurring in many catchments. In this article, we investigate the variability in the magnitude of shift in rainfall-runoff partitioning observed during the Millennium drought. We re-evaluate a large range of factors suggested to be responsible for the additional runoff reductions. Our results suggest that the shifts were mostly influenced by catchment characteristics related to predrought climate (aridity index and rainfall seasonality) and soil and groundwater storage dynamics (predrought interannual variability of groundwater storage and mean solum thickness). The shifts were amplified by seasonal rainfall changes during the drought (spring rainfall deficits). We discuss the physical mechanisms that are likely to be associated with these factors. Our results confirm that shifts in the annual rainfall-runoff relationship represent changes in internal catchment functioning, and emphasize the importance of cumulative multiyear changes in the catchment storage for runoff generation. Prolonged drying in some regions can be expected in the future, and our results provide an indication of which catchments characteristics are associated with catchments more susceptible to a shift in their runoff response behavior.

  5. Pressure dependence of backbone chemical shifts in the model peptides Ac-Gly-Gly-Xxx-Ala-NH2.

    Science.gov (United States)

    Erlach, Markus Beck; Koehler, Joerg; Crusca, Edson; Kremer, Werner; Munte, Claudia E; Kalbitzer, Hans Robert

    2016-06-01

    For a better understanding of nuclear magnetic resonance (NMR) detected pressure responses of folded as well as unstructured proteins the availability of data from well-defined model systems are indispensable. In this work we report the pressure dependence of chemical shifts of the backbone atoms (1)H(α), (13)C(α) and (13)C' in the protected tetrapeptides Ac-Gly-Gly-Xxx-Ala-NH2 (Xxx one of the 20 canonical amino acids). Contrary to expectation the chemical shifts of these nuclei have a nonlinear dependence on pressure in the range from 0.1 to 200 MPa. The polynomial pressure coefficients B 1 and B 2 are dependent on the type of amino acid studied. The coefficients of a given nucleus show significant linear correlations suggesting that the NMR observable pressure effects in the different amino acids have at least partly the same physical cause. In line with this observation the magnitude of the second order coefficients of nuclei being direct neighbors in the chemical structure are also weakly correlated.

  6. Measurement of carbonyl chemical shifts of excited protein states by relaxation dispersion NMR spectroscopy: comparison between uniformly and selectively {sup 13}C labeled samples

    Energy Technology Data Exchange (ETDEWEB)

    Lundstroem, Patrik; Hansen, D. Flemming; Kay, Lewis E. [University of Toronto, Department of Medical Genetics (Canada)], E-mail: kay@pound.med.utoronto.ca

    2008-09-15

    Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion nuclear magnetic resonance (NMR) spectroscopy has emerged as a powerful method for quantifying chemical shifts of excited protein states. For many applications of the technique that involve the measurement of relaxation rates of carbon magnetization it is necessary to prepare samples with isolated {sup 13}C spins so that experiments do not suffer from magnetization transfer between coupled carbon spins that would otherwise occur during the CPMG pulse train. In the case of {sup 13}CO experiments however the large separation between {sup 13}CO and {sup 13}C{sup {alpha}} chemical shifts offers hope that robust {sup 13}CO dispersion profiles can be recorded on uniformly {sup 13}C labeled samples, leading to the extraction of accurate {sup 13}CO chemical shifts of the invisible, excited state. Here we compare such chemical shifts recorded on samples that are selectively labeled, prepared using [1-{sup 13}C]-pyruvate and NaH{sup 13}CO{sub 3,} or uniformly labeled, generated from {sup 13}C-glucose. Very similar {sup 13}CO chemical shifts are obtained from analysis of CPMG experiments recorded on both samples, and comparison with chemical shifts measured using a second approach establishes that the shifts measured from relaxation dispersion are very accurate.

  7. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

    DEFF Research Database (Denmark)

    Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, D.

    2016-01-01

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts...... that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants...

  8. Halodemetallation of (Z)-1-[2-(Triarylstannyl)vinyl]-cyclooctanol and Correlation of Proton Chemical Shift with Electronegativity

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    @@ Introduction Organotin compounds have attracted attention as an optimal model for antitumour agents due to the function of the interesting intramolecular O→Sn coordination[1,2]. Our recent concern has been focused on the preparation of (Z)-1-[2-(triarylstannyl)vinyl]-cyclooctanol[3]. In order to find more appropriate compounds used as anticancer agents and explore the effect of the coordinate O→Sn interaction to the antitumor activity, the new compounds were halodemetallated and characterized. During the course of the process, some linear correlations between proton chemical shifts and the sum of the electronegativities of the tin substituents of halogens were found for the first time.

  9. The Effect of Molecular Conformation on the Accuracy of Theoretical (1)H and (13)C Chemical Shifts Calculated by Ab Initio Methods for Metabolic Mixture Analysis.

    Science.gov (United States)

    Chikayama, Eisuke; Shimbo, Yudai; Komatsu, Keiko; Kikuchi, Jun

    2016-04-14

    NMR spectroscopy is a powerful method for analyzing metabolic mixtures. The information obtained from an NMR spectrum is in the form of physical parameters, such as chemical shifts, and construction of databases for many metabolites will be useful for data interpretation. To increase the accuracy of theoretical chemical shifts for development of a database for a variety of metabolites, the effects of sets of conformations (structural ensembles) and the levels of theory on computations of theoretical chemical shifts were systematically investigated for a set of 29 small molecules in the present study. For each of the 29 compounds, 101 structures were generated by classical molecular dynamics at 298.15 K, and then theoretical chemical shifts for 164 (1)H and 123 (13)C atoms were calculated by ab initio quantum chemical methods. Six levels of theory were used by pairing Hartree-Fock, B3LYP (density functional theory), or second order Møller-Plesset perturbation with 6-31G or aug-cc-pVDZ basis set. The six average fluctuations in the (1)H chemical shift were ±0.63, ± 0.59, ± 0.70, ± 0.62, ± 0.75, and ±0.66 ppm for the structural ensembles, and the six average errors were ±0.34, ± 0.27, ± 0.32, ± 0.25, ± 0.32, and ±0.25 ppm. The results showed that chemical shift fluctuations with changes in the conformation because of molecular motion were larger than the differences between computed and experimental chemical shifts for all six levels of theory. In conclusion, selection of an appropriate structural ensemble should be performed before theoretical chemical shift calculations for development of an accurate database for a variety of metabolites.

  10. [Assessment of predictive dermal exposure to chemicals in the work environment].

    Science.gov (United States)

    Jankowska, Agnieszka; Czerczak, Sławomir; Kupczewska-Dobecka, Małgorzata

    2017-06-27

    Assessment of dermal exposure to chemicals in the work environment is problematic, mainly as a result of the lack of measurement data on occupational exposure to chemicals. Due to common prevalence of occupational skin exposure and its health consequences it is necessary to look for efficient solutions allowing for reliable exposure assessment. The aim of the study is to present predictive models used to assess non-measured dermal exposure, as well as to acquaint Polish users with the principles of the selected model functioning. This paper presents examples of models to assist the employer in the the assessment of occupational exposure associated with the skin contact with chemicals, developed in European Union (EU) countries, as well as in countries outside the EU. Based on the literature data dermal exposure models EASE (Estimation and Assessment of Substance Exposure), COSHH Essentials (Control of Substances Hazardous to Health Regulations), DREAM (Dermal Exposure Assessment Method), Stoffenmanager , ECETOC TRA (European Centre for Ecotoxicology and Toxicology of Chemicals Targeted Risk Assessment), MEASE (Metal's EASE), PHED (Pesticide Handlers Exposure Database), DERM (Dermal Exposure Ranking Method) and RISKOFDERM (Risk Assessment of Occupational Dermal Exposure to Chemicals) were briefly described. Moreover the characteristics of RISKOFDERM, guidelines for its use, information on input and output data were further detailed. Problem of full work shift dermal exposure assessment is described. An example of exposure assessment using RISKOFDERM and effectiveness evaluation to date were also presented. When no measurements are available, RISKOFDERM allows dermal exposure assessment and thus can improve the risk assessment quality and effectiveness of dermal risk management. Med Pr 2017;68(4):557-569. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

  11. Effect of pH, urea, peptide length, and neighboring amino acids on alanine alpha-proton random coil chemical shifts.

    Science.gov (United States)

    Carlisle, Elizabeth A; Holder, Jessica L; Maranda, Abby M; de Alwis, Adamberage R; Selkie, Ellen L; McKay, Sonya L

    2007-01-01

    Accurate random coil alpha-proton chemical shift values are essential for precise protein structure analysis using chemical shift index (CSI) calculations. The current study determines the chemical shift effects of pH, urea, peptide length and neighboring amino acids on the alpha-proton of Ala using model peptides of the general sequence GnXaaAYaaGn, where Xaa and Yaa are Leu, Val, Phe, Tyr, His, Trp or Pro, and n = 1-3. Changes in pH (2-6), urea (0-1M), and peptide length (n = 1-3) had no effect on Ala alpha-proton chemical shifts. Denaturing concentrations of urea (8M) caused significant downfield shifts (0.10 +/- 0.01 ppm) relative to an external DSS reference. Neighboring aliphatic residues (Leu, Val) had no effect, whereas aromatic amino acids (Phe, Tyr, His and Trp) and Pro caused significant shifts in the alanine alpha-proton, with the extent of the shifts dependent on the nature and position of the amino acid. Smaller aromatic residues (Phe, Tyr, His) caused larger shift effects when present in the C-terminal position (approximately 0.10 vs. 0.05 ppm N-terminal), and the larger aromatic tryptophan caused greater effects in the N-terminal position (0.15 ppm vs. 0.10 C-terminal). Proline affected both significant upfield (0.06 ppm, N-terminal) and downfield (0.25 ppm, C-terminal) chemical shifts. These new Ala correction factors detail the magnitude and range of variation in environmental chemical shift effects, in addition to providing insight into the molecular level interactions that govern protein folding.

  12. Modeling the chemical shift of lanthanide 4f electron binding energies

    NARCIS (Netherlands)

    Dorenbos, P.

    2012-01-01

    Lanthanides in compounds can adopt the tetravalent [Xe]4fn−1 (like Ce4+, Pr4+, Tb4+), the trivalent [Xe]4fn (all lanthanides), or the divalent [Xe]4f n+1 configuration (like Eu2+, Yb2+, Sm2+, Tm2+). The 4f-electron binding energy depends on the charge Q of the lanthanide ion and its chemical environ

  13. NMR chemical shift as analytical derivative of the Helmholtz free energy.

    Science.gov (United States)

    Van den Heuvel, Willem; Soncini, Alessandro

    2013-02-07

    We present a theory for the temperature-dependent nuclear magnetic shielding tensor of molecules with arbitrary electronic structure. The theory is a generalization of Ramsey's theory for closed-shell molecules. The shielding tensor is defined as a second derivative of the Helmholtz free energy of the electron system in equilibrium with the applied magnetic field and the nuclear magnetic moments. This derivative is analytically evaluated and expressed as a sum over states formula. Special consideration is given to a system with an isolated degenerate ground state for which the size of the degeneracy and the composition of the wave functions are arbitrary. In this case, the paramagnetic part of the shielding tensor is expressed in terms of the g and A tensors of the electron paramagnetic resonance spin Hamiltonian of the degenerate state. As an illustration of the proposed theory, we provide an explicit formula for the paramagnetic shift of the central lanthanide ion in endofullerenes Ln@C(60), with Ln = Ce(3+), Nd(3+), Sm(3+), Dy(3+), Er(3+), and Yb(3+), where the ground state can be a strongly spin-orbit coupled icosahedral sextet for which the paramagnetic shift cannot be described by previous theories.

  14. Integrating chemical footprinting data into RNA secondary structure prediction.

    Directory of Open Access Journals (Sweden)

    Kourosh Zarringhalam

    Full Text Available Chemical and enzymatic footprinting experiments, such as shape (selective 2'-hydroxyl acylation analyzed by primer extension, yield important information about RNA secondary structure. Indeed, since the [Formula: see text]-hydroxyl is reactive at flexible (loop regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints, which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be 'correct', in as much as the shape data is 'correct'. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

  15. pK(a) prediction from "Quantum Chemical Topology" descriptors.

    Science.gov (United States)

    Harding, A P; Wedge, D C; Popelier, P L A

    2009-08-01

    Knowing the pK(a) of a compound gives insight into many properties relevant to many industries, in particular the pharmaceutical industry during drug development processes. In light of this, we have used the theory of Quantum Chemical Topology (QCT), to provide ab initio descriptors that are able to accurately predict pK(a) values for 228 carboxylic acids. This Quantum Topological Molecular Similarity (QTMS) study involved the comparison of 5 increasingly more expensive levels of theory to conclude that HF/6-31G(d) and B3LYP/6-311+G(2d,p) provided an accurate representation of the compounds studies. We created global and subset models for the carboxylic acids using Partial Least Square (PLS), Support Vector Machines (SVM), and Radial Basis Function Neural Networks (RBFNN). The models were extensively validated using 4-, 7-, and 10-fold cross-validation, with the validation sets selected based on systematic and random sampling. HF/6-31G(d) in conjunction with SVM provided the best statistics when taking into account the large increase in CPU time required to optimize the geometries at the B3LYP/6-311+G(2d,p) level. The SVM models provided an average q(2) value of 0.886 and an RMSE value of 0.293 for all the carboxylic acids, a q(2) of 0.825 and RMSE of 0.378 for the ortho-substituted acids, a q(2) of 0.923 and RMSE of 0.112 for the para- and meta-substituted acids, and a q(2) of 0.906 and RMSE of 0.268 for the aliphatic acids. Our method compares favorably to ACD/Laboratories, VCCLAB, SPARC, and ChemAxon's pK(a) prediction software based of the RMSE calculated by the leave-one-out method.

  16. Predicting phase shift effects for vibrating fluid-conveying pipes due to Coriolis forces and fluid pulsation

    DEFF Research Database (Denmark)

    Enz, Stephanie; Thomsen, Jon Juel

    2011-01-01

    displacement and approximate axial shift in vibration phase. The analytical predictions are tested against pure numerical solution using representative examples, showing good agreement. Fluid pulsations are predicted not to influence CFM accuracy, since proper signal filtering is seen to allow......Knowing the influence of fluid flow perturbations on the dynamic behavior of fluid-conveying pipes is of relevance, e.g., when exploiting flow-induced oscillations of pipes to determine the fluids mass flow or density, as done with Coriolis flow meters (CFM). This could be used in the attempts...... the determination of the correct mean phase shift. Large amplitude motions, which could influence CFM robustness, do not appear to be induced by the investigated fluid pulsation. Pulsating fluid of the combination resonance type could, however, influence CFMs robustness, if induced pipe motions go unnoticed...

  17. Predicting phase shift of elastic waves in pipes due to fluid flow and imperfections

    DEFF Research Database (Denmark)

    Thomsen, Jon Juel; Dahl, Jonas; Fuglede, Niels

    2009-01-01

    Flexural vibrations of a fluid-conveying pipe is investigated, with special consideration to the spatial shift in phase caused by fluid flow and various imperfections, e.g., non-ideal supports, non-uniform stiffness or mass, non-proportional damping, weak nonlinearity, and flow pulsation. This is......Flexural vibrations of a fluid-conveying pipe is investigated, with special consideration to the spatial shift in phase caused by fluid flow and various imperfections, e.g., non-ideal supports, non-uniform stiffness or mass, non-proportional damping, weak nonlinearity, and flow pulsation....... This is relevant for understanding wave propagation in elastic media in general, and for the design and trouble-shooting of phase-shift measuring devices such as Coriolis mass flowmeters in particular. A multiple time scaling perturbation analysis is employed for a simple model of a fluid-conveying pipe...

  18. Heat Integration of the Water-Gas Shift Reaction System for Carbon Sequestration Ready IGCC Process with Chemical Looping

    Energy Technology Data Exchange (ETDEWEB)

    Juan M. Salazara; Stephen E. Zitney; Urmila M. Diwekara

    2010-01-01

    Integrated gasification combined cycle (IGCC) technology has been considered as an important alternative for efficient power systems that can reduce fuel consumption and CO2 emissions. One of the technological schemes combines water-gas shift reaction and chemical-looping combustion as post gasification techniques in order to produce sequestration-ready CO2 and potentially reduce the size of the gas turbine. However, these schemes have not been energetically integrated and process synthesis techniques can be applied to obtain an optimal flowsheet. This work studies the heat exchange network synthesis (HENS) for the water-gas shift reaction train employing a set of alternative designs provided by Aspen energy analyzer (AEA) and combined in a process superstructure that was simulated in Aspen Plus (AP). This approach allows a rigorous evaluation of the alternative designs and their combinations avoiding all the AEA simplifications (linearized models of heat exchangers). A CAPE-OPEN compliant capability which makes use of a MINLP algorithm for sequential modular simulators was employed to obtain a heat exchange network that provided a cost of energy that was 27% lower than the base case. Highly influential parameters for the pos gasification technologies (i.e. CO/steam ratio, gasifier temperature and pressure) were calculated to obtain the minimum cost of energy while chemical looping parameters (oxidation and reduction temperature) were ensured to be satisfied.

  19. Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

    Science.gov (United States)

    Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

    2012-01-01

    Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

  20. Theory of NMR chemical shift in an electronic state with arbitrary degeneracy

    CERN Document Server

    Heuvel, Willem Van den

    2012-01-01

    We present a theory of nuclear magnetic resonance (NMR) shielding tensors for electronic states with arbitrary degeneracy. The shieldings are here expressed in terms of generalized Zeeman ($g^{(k)}$) and hyperfine ($A^{(k)}$) tensors, of all ranks $k$ allowed by the size of degeneracy. Contrary to recent proposals [T. O. Pennanen and J. Vaara, Phys. Rev. Lett. 100, 133002 (2008)], our theory is valid in the strong spin-orbit coupling limit. Ab initio calculations for the 4-fold degenerate $\\Gamma_8$ ground state of lanthanide-doped fluorite crystals CaF$_2$:Ln (Ln = Pr$^{2+}$, Nd$^{3+}$, Sm$^{3+}$, and Dy$^{3+}$) show that previously neglected contributions can account for more than 50% of the paramagnetic shift.

  1. Quantitative analysis of deuterium using the isotopic effect on quaternary {sup 13}C NMR chemical shifts

    Energy Technology Data Exchange (ETDEWEB)

    Darwish, Tamim A., E-mail: tamim.darwish@ansto.gov.au [National Deuteration Facility, Australian Nuclear Science and Technology Organisation, Locked Bag 21, Kirrawee DC, NSW 2232 (Australia); Yepuri, Nageshwar Rao; Holden, Peter J. [National Deuteration Facility, Australian Nuclear Science and Technology Organisation, Locked Bag 21, Kirrawee DC, NSW 2232 (Australia); James, Michael [Australian Synchrotron, 800 Blackburn Road, Clayton, Victoria 3168 (Australia)

    2016-07-13

    Quantitative analysis of specifically deuterated compounds can be achieved by a number of conventional methods, such as mass spectroscopy, or by quantifying the residual {sup 1}H NMR signals compared to signals from internal standards. However, site specific quantification using these methods becomes challenging when dealing with non-specifically or randomly deuterated compounds that are produced by metal catalyzed hydrothermal reactions in D{sub 2}O, one of the most convenient deuteration methods. In this study, deuterium-induced NMR isotope shifts of quaternary {sup 13}C resonances neighboring deuterated sites have been utilized to quantify the degree of isotope labeling of molecular sites in non-specifically deuterated molecules. By probing {sup 13}C NMR signals while decoupling both proton and deuterium nuclei, it is possible to resolve {sup 13}C resonances of the different isotopologues based on the isotopic shifts and the degree of deuteration of the carbon atoms. We demonstrate that in different isotopologues, the same quaternary carbon, neighboring partially deuterated carbon atoms, are affected to an equal extent by relaxation. Decoupling both nuclei ({sup 1}H, {sup 2}H) resolves closely separated quaternary {sup 13}C signals of the different isotopologues, and allows their accurate integration and quantification under short relaxation delays (D1 = 1 s) and hence fast accumulative spectral acquisition. We have performed a number of approaches to quantify the deuterium content at different specific sites to demonstrate a convenient and generic analysis method for use in randomly deuterated molecules, or in cases of specifically deuterated molecules where back-exchange processes may take place during work up. - Graphical abstract: The relative intensities of quaternary {sup 13}C {"1H,"2H} resonances are equal despite the different relaxation delays, allowing the relative abundance of the different deuterated isotopologues to be calculated using NMR fast

  2. Predicting the future: opportunities and challenges for the chemical industry to apply 21st-century toxicity testing.

    Science.gov (United States)

    Settivari, Raja S; Ball, Nicholas; Murphy, Lynea; Rasoulpour, Reza; Boverhof, Darrell R; Carney, Edward W

    2015-03-01

    Interest in applying 21st-century toxicity testing tools for safety assessment of industrial chemicals is growing. Whereas conventional toxicology uses mainly animal-based, descriptive methods, a paradigm shift is emerging in which computational approaches, systems biology, high-throughput in vitro toxicity assays, and high-throughput exposure assessments are beginning to be applied to mechanism-based risk assessments in a time- and resource-efficient fashion. Here we describe recent advances in predictive safety assessment, with a focus on their strategic application to meet the changing demands of the chemical industry and its stakeholders. The opportunities to apply these new approaches is extensive and include screening of new chemicals, informing the design of safer and more sustainable chemical alternatives, filling information gaps on data-poor chemicals already in commerce, strengthening read-across methodology for categories of chemicals sharing similar modes of action, and optimizing the design of reduced-risk product formulations. Finally, we discuss how these predictive approaches dovetail with in vivo integrated testing strategies within repeated-dose regulatory toxicity studies, which are in line with 3Rs principles to refine, reduce, and replace animal testing. Strategic application of these tools is the foundation for informed and efficient safety assessment testing strategies that can be applied at all stages of the product-development process.

  3. Fast and accurate predictions of covalent bonds in chemical space

    Science.gov (United States)

    Chang, K. Y. Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (˜1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H 2+ . Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  4. Prediction of Wine Sensorial Quality by Routinely Measured Chemical Properties

    Directory of Open Access Journals (Sweden)

    Bednárová Adriána

    2014-12-01

    Full Text Available The determination of the sensorial quality of wines is of great interest for wine consumers and producers since it declares the quality in most of the cases. The sensorial assays carried out by a group of experts are time-consuming and expensive especially when dealing with large batches of wines. Therefore, an attempt was made to assess the possibility of estimating the wine sensorial quality with using routinely measured chemical descriptors as predictors. For this purpose, 131 Slovenian red wine samples of different varieties and years of production were analysed and correlation and principal component analysis were applied to find inter-relations between the studied oenological descriptors. The method of artificial neural networks (ANNs was utilised as the prediction tool for estimating overall sensorial quality of red wines. Each model was rigorously validated and sensitivity analysis was applied as a method for selecting the most important predictors. Consequently, acceptable results were obtained, when data representing only one year of production were included in the analysis. In this case, the coefficient of determination (R2 associated with training data was 0.95 and that for validation data was 0.90. When estimating sensorial quality in categorical form, 94 % and 85 % of correctly classified samples were achieved for training and validation subset, respectively.

  5. AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

    Science.gov (United States)

    A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

  6. AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

    Science.gov (United States)

    A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

  7. VITAL NMR: Using Chemical Shift Derived Secondary Structure Information for a Limited Set of Amino Acids to Assess Homology Model Accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, Michael C [University of Illinois, Urbana-Champaign; Nesbitt, Anna E [University of Illinois, Urbana-Champaign; Hallock, Michael J [University of Illinois, Urbana-Champaign; Rupasinghe, Sanjeewa [University of Illinois, Urbana-Champaign; Tang, Ming [University of Illinois, Urbana-Champaign; Harris, Jason B [ORNL; Baudry, Jerome Y [ORNL; Schuler, Mary A [University of Illinois, Urbana-Champaign; Rienstra, Chad M [University of Illinois, Urbana-Champaign

    2011-01-01

    Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., (13)C-(13)C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

  8. VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Brothers, Michael C.; Nesbitt, Anna E.; Hallock, Michael J. [University of Illinois at Urbana-Champaign, Department of Chemistry (United States); Rupasinghe, Sanjeewa G. [University of Illinois at Urbana-Champaign, Department of Cell and Developmental Biology (United States); Tang Ming [University of Illinois at Urbana-Champaign, Department of Chemistry (United States); Harris, Jason; Baudry, Jerome [University of Tennessee, Department of Biochemistry, Cellular and Molecular Biology (United States); Schuler, Mary A. [University of Illinois at Urbana-Champaign, Department of Cell and Developmental Biology (United States); Rienstra, Chad M., E-mail: rienstra@illinois.edu [University of Illinois at Urbana-Champaign, Department of Chemistry (United States)

    2012-01-15

    Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., {sup 13}C-{sup 13}C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (-0.75) commensurate to the control (-0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

  9. Prediction of the pull-out strength of chemical anchors in natural stone

    National Research Council Canada - National Science Library

    L. Contrafatto; R. Cosenza

    2014-01-01

    .... The numerical predictions, performed by means of engineering structural analysis software and advanced numerical codes, are compared with the results of an experimental research related to chemical...

  10. NMR chemical shift as analytical derivative of the Helmholtz free energy

    CERN Document Server

    Heuvel, Willem Van den

    2012-01-01

    We present a theory for the temperature-dependent nuclear magnetic shielding tensor of molecules with arbitrary electronic structure. The theory is a generalization of Ramsey's theory for closed-shell molecules. The shielding tensor is defined as a second derivative of the Helmholtz free energy of the electron system in equilibrium with the applied magnetic field and the nuclear magnetic moments. This derivative is analytically evaluated and expressed as a sum over states formula. Special consideration is given to a system with an isolated degenerate ground state for which the size of the degeneracy and the composition of the wave functions are arbitrary. In this case the paramagnetic part of the shielding tensor is expressed in terms of the $g$ and $A$ tensors of the EPR spin Hamiltonian of the degenerate state. As an illustration of the proposed theory, we provide an explicit formula for the paramagnetic shift of the central lanthanide ion in endofullerenes Ln@C$_{60}$, with Ln=Ce$^{3+}$, Nd$^{3+}$, Sm$^{3+...

  11. Liver fat quantification: Comparison of dual-echo and triple-echo chemical shift MRI to MR spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Satkunasingham, Janakan; Besa, Cecilia [Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029 (United States); Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029 (United States); Bane, Octavia [Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029 (United States); Shah, Ami [Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029 (United States); Oliveira, André de; Gilson, Wesley D.; Kannengiesser, Stephan [Siemens AG, Healthcare Sector, Erlangen (Germany); Taouli, Bachir, E-mail: bachir.taouli@mountsinai.org [Department of Radiology, Body MRI, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029 (United States); Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY 10029 (United States)

    2015-08-15

    Highlights: • We present a large cohort of patients who underwent dual and triple echo chemical shift imaging against multi-echo T{sub 2} corrected MR spectroscopy (MRS) for liver fat quantification. • Our data suggests that a triple-echo sequence is highly accurate for detection of liver fat, even in the presence of T{sub 2}{sup *} shortening, with minor discrepancies when compared with the advanced fat quantification method. - Abstract: Purpose: To assess the diagnostic value of MRI using dual-echo (2PD) and triple-echo (3PD) chemical shift imaging for liver fat quantification against multi-echo T{sub 2} corrected MR spectroscopy (MRS) used as the reference standard, and examine the effect of T{sub 2}{sup *} imaging on accuracy of MRI for fat quantification. Materials and methods: Patients who underwent 1.5 T liver MRI that incorporated 2PD, 3PD, multi-echo T{sub 2}{sup *} and MRS were included in this IRB approved prospective study. Regions of interest were placed in the liver to measure fat fraction (FF) with 2PD and 3PD and compared with MRS-FF. A random subset of 25 patients with a wide range of MRS-FF was analyzed with an advanced FF calculation method, to prove concordance with the 3PD. The statistical analysis included correlation stratified according to T{sub 2}{sup *}, Bland-Altman analysis, and calculation of diagnostic accuracy for detection of MRS-FF > 6.25%. Results: 220 MRI studies were identified in 217 patients (mean BMI 28.0 ± 5.6). 57/217 (26.2%) patients demonstrated liver steatosis (MRS-FF > 6.25%). Bland-Altman analysis revealed strong agreement between 3PD and MRS (mean ± 1.96 SD: −0.5% ± 4.6%) and weaker agreement between 2PD and MRS (4.7% ± 16.0%). Sensitivity of 3PD for diagnosing FF> 6.25% was higher than that of 2PD. 3PD-FF showed minor discrepancies (coefficient of variation <10%) from FF measured with the advanced method. Conclusion: Our large series study validates the use of 3PD chemical shift sequence for detection of

  12. Assessment of Romanian alpine habitats spatial shifts based on climate change prediction scenarios

    OpenAIRE

    CONSTANTINESCU Adrian; Hanganu, Jenica; Lehmann, Anthony; Ray, Nicolas

    2014-01-01

    Shifts in the ecosystems distribution as the result of climate change are of interest for decision-makers in biodiversity conservation at local and European level. This paper presents the use of modeling technique, Maxent (Maximum entropy modeling) and BIOCLIM (environmental envelope model), to estimate the impact of climate change on the Alpine bioregion of Continental Europe for improving the management policy in support of stopping biodiversity loss. The European Union priority habitat 623...

  13. Chemical structure elucidation from ¹³C NMR chemical shifts: efficient data processing using bipartite matching and maximal clique algorithms.

    Science.gov (United States)

    Koichi, Shungo; Arisaka, Masaki; Koshino, Hiroyuki; Aoki, Atsushi; Iwata, Satoru; Uno, Takeaki; Satoh, Hiroko

    2014-04-28

    Computer-assisted chemical structure elucidation has been intensively studied since the first use of computers in chemistry in the 1960s. Most of the existing elucidators use a structure-spectrum database to obtain clues about the correct structure. Such a structure-spectrum database is expected to grow on a daily basis. Hence, the necessity to develop an efficient structure elucidation system that can adapt to the growth of a database has been also growing. Therefore, we have developed a new elucidator using practically efficient graph algorithms, including the convex bipartite matching, weighted bipartite matching, and Bron-Kerbosch maximal clique algorithms. The utilization of the two matching algorithms especially is a novel point of our elucidator. Because of these sophisticated algorithms, the elucidator exactly produces a correct structure if all of the fragments are included in the database. Even if not all of the fragments are in the database, the elucidator proposes relevant substructures that can help chemists to identify the actual chemical structures. The elucidator, called the CAST/CNMR Structure Elucidator, plays a complementary role to the CAST/CNMR Chemical Shift Predictor, and together these two functions can be used to analyze the structures of organic compounds.

  14. Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker

    Energy Technology Data Exchange (ETDEWEB)

    Vernon, Robert [Hospital for Sick Children, Program in Molecular Structure and Function (Canada); Shen, Yang [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Baker, David [University of Washington, Department of Biochemistry (United States); Lange, Oliver F., E-mail: oliver.lange@tum.de [Technische Universitaet Muenchen, Department Chemie, Biomolecular NMR and Munich Center for Integrated Protein Science (Germany)

    2013-10-15

    A new fragment picker has been developed for CS-Rosetta that combines beneficial features of the original fragment picker, MFR, used with CS-Rosetta, and the fragment picker, NNMake, that was used for purely sequence based fragment selection in the context of ROSETTA de-novo structure prediction. Additionally, the new fragment picker has reduced sensitivity to outliers and other difficult to match data points rendering the protocol more robust and less likely to introduce bias towards wrong conformations in cases where data is bad, missing or inconclusive. The fragment picker protocol gives significant improvements on 6 of 23 CS-Rosetta targets. An independent benchmark on 39 protein targets, whose NMR data sets were published only after protocol optimization had been finished, also show significantly improved performance for the new fragment picker (van der Schot et al. in J Biomol NMR, 2013)

  15. Chemical shift powder spectra enhanced by multiple-contact cross-polarization under slow magic-angle spinning.

    Science.gov (United States)

    Raya, Jésus; Perrone, Barbara; Hirschinger, Jérôme

    2013-02-01

    A simple multiple-contact cross-polarization (CP) scheme is applied to a powder sample of ferrocene and β-calcium formate under static and magic-angle spinning (MAS) conditions. The method is described analytically through the density matrix formalism. We show that multiple equilibrations-re-equilibrations with the proton spin bath improves the polarization transfer efficiency at short contact times and provides higher signal enhancements than state-of-the art techniques such as adiabatic passage through the Hartmann-Hahn condition CP (APHH-CP) when MAS is applied. The resulting chemical shift powder spectra then are identical to the ones obtained by using ROtor-Directed Exchange of Orientations CP (APHH-RODEO-CP) with intensity gains of a factor 1.1-1.3.

  16. Chemical shift powder spectra enhanced by multiple-contact cross-polarization under slow magic-angle spinning

    Science.gov (United States)

    Raya, Jésus; Perrone, Barbara; Hirschinger, Jérôme

    2013-02-01

    A simple multiple-contact cross-polarization (CP) scheme is applied to a powder sample of ferrocene and β-calcium formate under static and magic-angle spinning (MAS) conditions. The method is described analytically through the density matrix formalism. We show that multiple equilibrations-re-equilibrations with the proton spin bath improves the polarization transfer efficiency at short contact times and provides higher signal enhancements than state-of-the art techniques such as adiabatic passage through the Hartmann-Hahn condition CP (APHH-CP) when MAS is applied. The resulting chemical shift powder spectra then are identical to the ones obtained by using ROtor-Directed Exchange of Orientations CP (APHH-RODEO-CP) with intensity gains of a factor 1.1-1.3.

  17. Portable Sequentially Shifted Excitation Raman spectroscopy as an innovative tool for in situ chemical interrogation of painted surfaces.

    Science.gov (United States)

    Conti, Claudia; Botteon, Alessandra; Bertasa, Moira; Colombo, Chiara; Realini, Marco; Sali, Diego

    2016-08-07

    We present the first validation and application of portable Sequentially Shifted Excitation (SSE) Raman spectroscopy for the survey of painted layers in art. The method enables the acquisition of shifted Raman spectra and the recovery of the spectral data through the application of a suitable reconstruction algorithm. The technique has a great potentiality in art where commonly a strong fluorescence obscures the Raman signal of the target, especially when conventional portable Raman spectrometers are used for in situ analyses. Firstly, the analytical capability of portable SSE Raman spectroscopy is critically discussed using reference materials and laboratory specimens, comparing its results with other conventional high performance laboratory instruments (benchtop FT-Raman and dispersive Raman spectrometers with an external fiber optic probe); secondly, it is applied directly in situ to study the complex polychromy of Italian prestigious terracotta sculptures of the 16(th) century. Portable SSE Raman spectroscopy represents a new investigation modality in art, expanding the portfolio of non-invasive, chemically specific analytical tools.

  18. Microscopic structures of ionic liquids 1-ethyl-3-methylimidazolium tetrafluoroborate in water probed by the relative chemical shift

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The relative chemical shifts (△δ) △δwere put forward to investigate the microscopic structure of 1-ethyl-3-methyl-imidazolium tetrafluoroborate (EmimBF4) during the dilution process with water.The concentration-dependent △δ(C2)H-(C4)H,△δ(C2)H-(C5)H and △δ(C4)H-(C5)H were analyzed.The results reveal that the variations of the microscopic structures of three aromatic protons are inconsistent.The strength of the H-bond between water and three aromatic protons follows the order:(C2)H···O > (C4)H···O > (C5)H···O.The concentration-dependent △δ(C6)H-(C7)H and △δ(C6)H-(C8)H indicate the formation of the H-bonds of (Calkyl)H···O is impossible,and more water is located around (C6)H than around (C7)H or (C8)H.The concentration-dependent △δ(C2)H-(C4)H and △δ(C2)H-(C5)H both increase rapidly when xwater > 0.9 or so,suggesting the ionic pairs of EmimBF4 are dissociated rapidly.The turning points of concentration-dependent △δ(C2)H-(C4)H and △δ(C2)H-(C5)H indicate that some physical properties of the EmimBF4/water mixtures also change at the corresponding concentration point.The microscopic structures of EmimBF4 in water could be clearly detected by the relative chemical shifts.

  19. Thickness-Dependent Binding Energy Shift in Few-Layer MoS2 Grown by Chemical Vapor Deposition.

    Science.gov (United States)

    Lin, Yu-Kai; Chen, Ruei-San; Chou, Tsu-Chin; Lee, Yi-Hsin; Chen, Yang-Fang; Chen, Kuei-Hsien; Chen, Li-Chyong

    2016-08-31

    The thickness-dependent surface states of MoS2 thin films grown by the chemical vapor deposition process on the SiO2-Si substrates are investigated by X-ray photoelectron spectroscopy. Raman and high-resolution transmission electron microscopy suggest the thicknesses of MoS2 films to be ranging from 3 to 10 layers. Both the core levels and valence band edges of MoS2 shift downward ∼0.2 eV as the film thickness increases, which can be ascribed to the Fermi level variations resulting from the surface states and bulk defects. Grainy features observed from the atomic force microscopy topographies, and sulfur-vacancy-induced defect states illustrated at the valence band spectra imply the generation of surface states that causes the downward band bending at the n-type MoS2 surface. Bulk defects in thick MoS2 may also influence the Fermi level oppositely compared to the surface states. When Au contacts with our MoS2 thin films, the Fermi level downshifts and the binding energy reduces due to the hole-doping characteristics of Au and easy charge transfer from the surface defect sites of MoS2. The shift of the onset potentials in hydrogen evolution reaction and the evolution of charge-transfer resistances extracted from the impedance measurement also indicate the Fermi level varies with MoS2 film thickness. The tunable Fermi level and the high chemical stability make our MoS2 a potential catalyst. The observed thickness-dependent properties can also be applied to other transition-metal dichalcogenides (TMDs), and facilitates the development in the low-dimensional electronic devices and catalysts.

  20. Artificial Neural Networks in the prediction of insolvency. A paradigm shift to traditional business practices recipes

    Directory of Open Access Journals (Sweden)

    Marcia M. Lastre Valdes

    2014-06-01

    Full Text Available In this paper a review and analysis of the major theories and models that address the prediction of corporate bankruptcy and insolvency is made. Neural networks are a tool of most recent appearance, although in recent years have received considerable attention from the academic and professional world, and have started to be implemented in different models testing organizations insolvency based on neural computation. The purpose of this paper is to yield evidence of the usefulness of Artificial Neural Networks in the problem of bankruptcy prediction insolence or so compare its predictive ability with the methods commonly used in that context. The findings suggest that high predictive capabilities can be achieved  using artificial neural networks, with qualitative and quantitative variables.

  1. Zero discharge tanning: a shift from chemical to biocatalytic leather processing.

    Science.gov (United States)

    Thanikaivelan, Palanisamy; Rao, Jonnalagadda Raghava; Nair, Balachandran Unni; Ramasami, Thirumalachari

    2002-10-01

    Beam house processes (Beam house processes generally mean liming-reliming processes, which employ beam.) contribute more than 60% of the total pollution from leather processing. The use of lime and sodium sulfide is of environmental concern (1, 2). Recently, the authors have developed an enzyme-based dehairing assisted with a very low amount of sodium sulfide, which completely avoids the use of lime. However, the dehaired pelt requires opening up of fiber bundles for further processing, where lime is employed to achieve this through osmotic swelling. Huge amounts of lime sludge and total solids are the main drawbacks of lime. An alternative bioprocess, based on alpha-amylase for fiber opening, has been attempted after enzymatic unhairing. This totally eliminates the use of lime in leather processing. This method enables subsequent processes and operations in leather making feasible without a deliming process. A control experiment was run in parallel using conventional liming-reliming processes. It has been found that the extent of opening up of fiber bundles using alpha-amylase is comparable to that of the control. This has been substantiated through scanning electron microscopic, stratigraphic chrome distribution analysis, and softness measurements. Performance of the leathers is shown to be on a par with leathers produced by the conventional process through physical and hand evaluation. Importantly, softness of the leathers is numerically proven to be comparable with that of control. The process also demonstrates reduction in chemical oxygen demand load by 45% and total solids load by 20% compared to the conventional process. The total dry sludge from the beam house processes is brought down from 152 to 8 kg for processing 1 ton of raw hides.

  2. Comparison of experimental and DFT-calculated NMR chemical shifts of 2-amino and 2-hydroxyl substituted phenyl benzimidazoles, benzoxazoles and benzothiazoles in four solvents using the IEF-PCM solvation model.

    Science.gov (United States)

    Pierens, Gregory K; Venkatachalam, T K; Reutens, David C

    2016-04-01

    A comparative study of experimental and calculated NMR chemical shifts of six compounds comprising 2-amino and 2-hydroxy phenyl benzoxazoles/benzothiazoles/benzimidazoles in four solvents is reported. The benzimidazoles showed interesting spectral characteristics, which are discussed. The proton and carbon chemical shifts were similar for all solvents. The largest chemical shift deviations were observed in benzene. The chemical shifts were calculated with density functional theory using a suite of four functionals and basis set combinations. The calculated chemical shifts revealed a good match to the experimentally observed values in most of the solvents. The mean absolute error was used as the primary metric. The use of an additional metric is suggested, which is based on the order of chemical shifts. The DP4 probability measures were also used to compare the experimental and calculated chemical shifts for each compound in the four solvents. Copyright © 2015 John Wiley & Sons, Ltd.

  3. Using deuterated PAH amendments to validate chemical extraction methods to predict PAH bioavailability in soils

    Energy Technology Data Exchange (ETDEWEB)

    Gomez-Eyles, Jose L., E-mail: j.l.gomezeyles@reading.ac.uk [University of Reading, School of Human and Environmental Sciences, Soil Research Centre, Reading, RG6 6DW Berkshire (United Kingdom); Collins, Chris D.; Hodson, Mark E. [University of Reading, School of Human and Environmental Sciences, Soil Research Centre, Reading, RG6 6DW Berkshire (United Kingdom)

    2011-04-15

    Validating chemical methods to predict bioavailable fractions of polycyclic aromatic hydrocarbons (PAHs) by comparison with accumulation bioassays is problematic. Concentrations accumulated in soil organisms not only depend on the bioavailable fraction but also on contaminant properties. A historically contaminated soil was freshly spiked with deuterated PAHs (dPAHs). dPAHs have a similar fate to their respective undeuterated analogues, so chemical methods that give good indications of bioavailability should extract the fresh more readily available dPAHs and historic more recalcitrant PAHs in similar proportions to those in which they are accumulated in the tissues of test organisms. Cyclodextrin and butanol extractions predicted the bioavailable fraction for earthworms (Eisenia fetida) and plants (Lolium multiflorum) better than the exhaustive extraction. The PAHs accumulated by earthworms had a larger dPAH:PAH ratio than that predicted by chemical methods. The isotope ratio method described here provides an effective way of evaluating other chemical methods to predict bioavailability. - Research highlights: > Isotope ratios can be used to evaluate chemical methods to predict bioavailability. > Chemical methods predicted bioavailability better than exhaustive extractions. > Bioavailability to earthworms was still far from that predicted by chemical methods. - A novel method using isotope ratios to assess the ability of chemical methods to predict PAH bioavailability to soil biota.

  4. Prediction and prevention of musculoskeletal injury: a paradigm shift in methodology.

    Science.gov (United States)

    Quatman, C E; Quatman, C C; Hewett, T E

    2009-12-01

    Traditional methods employed to study musculoskeletal injury mechanisms and joint biomechanics utilise in vivo or in vitro techniques. The advent of new technology and improved methods has also given rise to in silico (computer modelling) techniques. Under the current research paradigm, in vivo, in vitro and in silico methods independently provide information regarding the mechanisms and prevention of musculoskeletal injury. However, individually, each of these methods has multiple, inherent limitations and is likely to provide incomplete answers about multifactorial, complex injury conditions. The purpose of this treatise is to review current methods used to study, understand, and prevent musculoskeletal injury and to develop new conceptual-methodological frameworks that may help create a paradigm shift in musculoskeletal injury prevention research. We term the fusion of these three techniques in simulacra amalgama, or simply in sim, meaning a "union of models done on the likeness of phenomena." Anterior cruciate ligament (ACL) injury will be employed as a model example for the utility and applicability of the proposed, synthesised approach. Shifting the current experimental paradigm to incorporate a multifaceted, multidisciplinary, integration of in vivo, in vitro and in silico methods into the proposed in sim approaches may provide a platform for a more comprehensive understanding of the relationships between complex joint biomechanics and observed injury mechanisms.

  5. Predicting ecological regime shift under climate change: New modelling techniques and potential of molecular-based approaches

    Directory of Open Access Journals (Sweden)

    Richard STAFFORD, V. Anne SMITH, Dirk HUSMEIER, Thomas GRIMA, Barbara-ann GUINN

    2013-06-01

    Full Text Available Ecological regime shift is the rapid transition from one stable community structure to another, often ecologically inferior, stable community. Such regime shifts are especially common in shallow marine communities, such as the transition of kelp forests to algal turfs that harbour far lower biodiversity. Stable regimes in communities are a result of balanced interactions between species, and predicting new regimes therefore requires an evaluation of new species interactions, as well as the resilience of the ‘stable’ position. While computational optimisation techniques can predict new potential regimes, predicting the most likely community state of the various options produced is currently educated guess work. In this study we integrate a stable regime optimisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change (or, in practice, any other disturbance on each component species of a representative rocky shore community model. Combining the results, by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network, gives a refined set of model predictors, and demonstrates the use of the process in determining community changes, as might occur through processes such as climate change. To inform Bayesian priors, we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms, and show how such an approach could be linked to measureable stress variables in the field. Hence species-specific microarrays could be designed as biomarkers of in situ stress, and used to inform predictive modelling approaches such as those described here [Current Zoology 59 (3: 403–417, 2013].

  6. Predicting ecological regime shift under climate change:New modelling techniques and potential of molecular-based approaches

    Institute of Scientific and Technical Information of China (English)

    Richard STAFFORD; V.Anne SMITH; Dirk HUSMEIER; Thomas GRIMA; Barbara-ann GUINN

    2013-01-01

    Ecological regime shift is the rapid transition from one stable community structure to another,often ecologically inferior,stable community.Such regime shifts are especially common in shallow marine communities,such as the transition of kelp forests to algal turfs that harbour far lower biodiversity.Stable regimes in communities are a result of balanced interactions between species,and predicting new regimes therefore requires an evaluation of new species interactions,as well as the resilience of the ‘stable' position.While computational optimisation techniques can predict new potential regimes,predicting the most likely community state of the various options produced is currently educated guess work.In this study we integrate a stable regime optimisation approach with a Bayesian network used to infer prior knowledge of the likely stress of climate change (or,in practice,any other disturbance) on each component species of a representative rocky shore community model.Combining the results,by calculating the product of the match between resilient computational predictions and the posterior probabilities of the Bayesian network,gives a refined set of model predictors,and demonstrates the use of the process in determining community changes,as might occur through processes such as climate change.To inform Bayesian priors,we conduct a review of molecular approaches applied to the analysis of the transcriptome of rocky shore organisms,and show how such an approach could be linked to measureable stress variables in the field.Hence species-specific microarrays could be designed as biomarkers of in situ stress,and used to inform predictive modelling approaches such as those described here.

  7. Prediction of spectral shifts proportional to source distances by time-varying frequency or wavelength selection

    CERN Document Server

    Guruprasad, V

    2008-01-01

    Any frequency selective device with an ongoing drift will cause observed spectra to be variously and simultaneously scaled in proportion to their source distances. The reason is that detectors after the drifting selection will integrate instantaneous electric or magnetic field values from successive sinusoids, and these sinusoids would differ in both frequency and phase. Phase differences between frequencies are ordinarily irrelevant, and recalibration procedures at most correct for frequency differences. With drifting selection, however, each integrated field value comes from *the sinusoid of the instantaneously selected frequency at its instantaneous received phase*, hence the waveform constructed by the integration will follow the drifting selection with a phase acceleration given by the drift rate times the slope of the received phase spectrum. A phase acceleration is literally a frequency shift, and the phase spectrum slope of a received waveform is an asymptotic measure of the source distance, as the pa...

  8. Indirectly detected chemical shift correlation NMR spectroscopy in solids under fast magic angle spinning

    Energy Technology Data Exchange (ETDEWEB)

    Mao, Kanmi [Iowa State Univ., Ames, IA (United States)

    2011-01-01

    on decoupling efficiency as well as scaling factors. Indirect detection with assistance of PMLGm$\\bar{x}$ during INEPTR transfer proved to offer the highest sensitivity gains of 3-10. In addition, the CRAMPS sequence was applied under fast MAS to increase the 1H resolution during t1 evolution in the traditional, 13C detected HETCOR scheme. Two naturally abundant solids, tripeptide N-formyl-L-methionyl-L-leucyl-L-phenylalanine (f-MLF-OH) and brown coal, with well ordered and highly disordered structures, respectively, are studied to confirm the capabilities of these techniques. Concomitantly, a simple optimization of 1H homonuclear dipolar decoupling at MAS rates exceeding 10 kHz was developed (Chapter 4). The fine-tuned decoupling efficiency can be obtained by minimizing the signal loss due to transverse relaxation in a simple spin-echo experiment, using directly the sample of interest. The excellent agreement between observed decoupling pattern and earlier theoretical predictions confirmed the utility of this strategy. The properties of naturally abundant surface-bound fluorocarbon groups in mesoporous silica nanoparticles (MSNs) were investigated by the above-mentioned multidimensional solid-state NMR experiments and theoretical modeling (Chapter 5). Two conformations of (pentafluorophenyl)propyl groups (abbreviated as PFP) were determined as PFP-prone and PFP-upright, whose aromatic rings are located above the siloxane bridges and in roughly upright position, respectively. Several 1D and 2D NMR techniques were implemented in the characterizations, including indirectly detected 1H{l_brace}13C{r_brace} and 19F{l_brace}13C{r_brace} 2D HETCOR, Carr-Purcell-Meiboom-Gill (CPMG) assisted 29Si direct polarization and 29Si19F 2D experiments, 2D double-quantum (DQ) 19F MAS NMR spectra and spin-echo measurements

  9. Proton NMR Chemical Shift Behavior of Hydrogen-Bonded Amide Proton of Glycine-Containing Peptides and Polypeptides as Studied by ab initio MO Calculation

    Directory of Open Access Journals (Sweden)

    I. Ando

    2002-08-01

    Full Text Available Abstract: NMR chemical shifts of the amide proton of a supermolecule, an Nmethylacetamide hydrogen-bonded with a formamide, were calculated as functions of hydrogen-bond length RN…O and hydrogen-bond angles by FPT-GIAO method within the framework of HF/STO 6-31++G(d,p ab initio MO method. The calculations explained reasonably the experimental data reported previously that the isotropic proton chemical shifts move downfield with a decrease in RN…O. Further, the behavior of proton chemical shift tensor components depending on the hydrogen-bond length and hydrogen-bond angle was discussed.

  10. High accuracy NMR chemical shift corrected for bulk magnetization as a tool for structural elucidation of dilutable microemulsions. Part 1 - Proof of concept.

    Science.gov (United States)

    Hoffman, Roy E; Darmon, Eliezer; Aserin, Abraham; Garti, Nissim

    2016-02-01

    In microemulsions, changes in droplet size and shape and possible transformations occur under various conditions. They are difficult to characterize by most analytical tools because of their nano-sized structure and dynamic nature. Several methods are usually combined to obtain reliable information, guiding the scientist in understanding their physical behavior. We felt that there is a need for a technique that complements those in use today in order to provide more information on the microemulsion behavior, mainly as a function of dilution with water. The improvement of NMR chemical shift measurements independent of bulk magnetization effects makes it possible to study the very weak intermolecular chemical shift effects. In the present study, we used NMR high resolution magic angle spinning to measure the chemical shift very accurately, free of bulk magnetization effects. The chemical shift of microemulsion components is measured as a function of the water content in order to validate the method in an interesting and promising, U-type dilutable microemulsion, which had been previously studied by a variety of techniques. Phase transition points of the microemulsion (O/W, bicontinuous, W/O) and changes in droplet shape were successfully detected using high-accuracy chemical shift measurements. We analyzed the results and found them to be compatible with the previous studies, paving the way for high-accuracy chemical shifts to be used for the study of other microemulsion systems. We detected two transition points along the water dilution line of the concentrate (reverse micelles) corresponding to the transition from swollen W/O nano-droplets to bicontinuous to the O/W droplets along with the changes in the droplets' sizes and shapes. The method seems to be in excellent agreement with other previously studied techniques and shows the advantage of this easy and valid technique.

  11. Pathogen-host associations and predicted range shifts of human monkeypox in response to climate change in central Africa.

    Directory of Open Access Journals (Sweden)

    Henri A Thomassen

    Full Text Available Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV, an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX. Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC, and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4(th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts.

  12. Intermolecular Interactions in Crystalline Theobromine as Reflected in Electron Deformation Density and (13)C NMR Chemical Shift Tensors.

    Science.gov (United States)

    Bouzková, Kateřina; Babinský, Martin; Novosadová, Lucie; Marek, Radek

    2013-06-11

    An understanding of the role of intermolecular interactions in crystal formation is essential to control the generation of diverse crystalline forms which is an important concern for pharmaceutical industry. Very recently, we reported a new approach to interpret the relationships between intermolecular hydrogen bonding, redistribution of electron density in the system, and NMR chemical shifts (Babinský et al. J. Phys. Chem. A, 2013, 117, 497). Here, we employ this approach to characterize a full set of crystal interactions in a sample of anhydrous theobromine as reflected in (13)C NMR chemical shift tensors (CSTs). The important intermolecular contacts are identified by comparing the DFT-calculated NMR CSTs for an isolated theobromine molecule and for clusters composed of several molecules as selected from the available X-ray diffraction data. Furthermore, electron deformation density (EDD) and shielding deformation density (SDD) in the proximity of the nuclei involved in the proposed interactions are calculated and visualized. In addition to the recently reported observations for hydrogen bonding, we focus here particularly on the stacking interactions. Although the principal relations between the EDD and CST for hydrogen bonding (HB) and stacking interactions are similar, the real-space consequences are rather different. Whereas the C-H···X hydrogen bonding influences predominantly and significantly the in-plane principal component of the (13)C CST perpendicular to the HB path and the C═O···H hydrogen bonding modulates both in-plane components of the carbonyl (13)C CST, the stacking modulates the out-of-plane electron density resulting in weak deshielding (2-8 ppm) of both in-plane principal components of the CST and weak shielding (∼ 5 ppm) of the out-of-plane component. The hydrogen-bonding and stacking interactions may add to or subtract from one another to produce total values observed experimentally. On the example of theobromine, we demonstrate

  13. Predicted altitudinal shifts and reduced spatial distribution of Leishmania infantum vector species under climate change scenarios in Colombia.

    Science.gov (United States)

    González, Camila; Paz, Andrea; Ferro, Cristina

    2014-01-01

    Visceral leishmaniasis (VL) is caused by the trypanosomatid parasite Leishmania infantum (=Leishmania chagasi), and is epidemiologically relevant due to its wide geographic distribution, the number of annual cases reported and the increase in its co-infection with HIV. Two vector species have been incriminated in the Americas: Lutzomyia longipalpis and Lutzomyia evansi. In Colombia, L. longipalpis is distributed along the Magdalena River Valley while L. evansi is only found in the northern part of the Country. Regarding the epidemiology of the disease, in Colombia the incidence of VL has decreased over the last few years without any intervention being implemented. Additionally, changes in transmission cycles have been reported with urban transmission occurring in the Caribbean Coast. In Europe and North America climate change seems to be driving a latitudinal shift of leishmaniasis transmission. Here, we explored the spatial distribution of the two known vector species of L. infantum in Colombia and projected its future distribution into climate change scenarios to establish the expansion potential of the disease. An updated database including L. longipalpis and L. evansi collection records from Colombia was compiled. Ecological niche models were performed for each species using the Maxent software and 13 Worldclim bioclimatic coverages. Projections were made for the pessimistic CSIRO A2 scenario, which predicts the higher increase in temperature due to non-emission reduction, and the optimistic Hadley B2 Scenario predicting the minimum increase in temperature. The database contained 23 records for L. evansi and 39 records for L. longipalpis, distributed along the Magdalena River Valley and the Caribbean Coast, where the potential distribution areas of both species were also predicted by Maxent. Climate change projections showed a general overall reduction in the spatial distribution of the two vector species, promoting a shift in altitudinal distribution for L

  14. Quantum chemical aided prediction of the thermal decomposition mechanisms and temperatures of ionic liquids

    Energy Technology Data Exchange (ETDEWEB)

    Kroon, Maaike C. [Physical Chemistry and Molecular Thermodynamics, Department of Chemical Technology, Faculty of Applied Sciences, Delft University of Technology, Julianalaan 136, 2628 BL Delft (Netherlands); Process Equipment, Department of Process and Energy, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Leeghwaterstraat 44, 2628 CA Delft (Netherlands)], E-mail: maaike.kroon@gmail.com; Buijs, Wim [Catalysis Engineering, Department of Chemical Technology, Faculty of Applied Sciences, Delft University of Technology, Julianalaan 136, 2628 BL Delft (Netherlands); Peters, Cor J. [Physical Chemistry and Molecular Thermodynamics, Department of Chemical Technology, Faculty of Applied Sciences, Delft University of Technology, Julianalaan 136, 2628 BL Delft (Netherlands); Witkamp, Geert-Jan [Process Equipment, Department of Process and Energy, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Leeghwaterstraat 44, 2628 CA Delft (Netherlands)], E-mail: G.J.Witkamp@3me.tudelft.nl

    2007-12-15

    The long-term thermal stability of ionic liquids is of utmost importance for their industrial application. Although the thermal decomposition temperatures of various ionic liquids have been measured previously, experimental data on the thermal decomposition mechanisms and kinetics are scarce. It is desirable to develop quantitative chemical tools that can predict thermal decomposition mechanisms and temperatures (kinetics) of ionic liquids. In this work ab initio quantum chemical calculations (DFT-B3LYP) have been used to predict thermal decomposition mechanisms, temperatures and the activation energies of the thermal breakdown reactions. These quantum chemical calculations proved to be an excellent method to predict the thermal stability of various ionic liquids.

  15. Biased ART: a neural architecture that shifts attention toward previously disregarded features following an incorrect prediction.

    Science.gov (United States)

    Carpenter, Gail A; Gaddam, Sai Chaitanya

    2010-04-01

    Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved successful for both brain models and applications, computational examples show that attention to early critical features may later distort memory representations during online fast learning. For supervised learning, biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error. Small-scale, hand-computed analog and binary examples illustrate key model dynamics. Two-dimensional simulation examples demonstrate the evolution of bARTMAP memories as they are learned online. Benchmark simulations show that featural biasing also improves performance on large-scale examples. One example, which predicts movie genres and is based, in part, on the Netflix Prize database, was developed for this project. Both first principles and consistent performance improvements on all simulation studies suggest that featural biasing should be incorporated by default in all ARTMAP systems. Benchmark datasets and bARTMAP code are available from the CNS Technology Lab Website: http://techlab.bu.edu/bART/.

  16. Recent Shift in Climate Relationship Enables Prediction of the Timing of Bird Breeding.

    Science.gov (United States)

    Hinsley, Shelley A; Bellamy, Paul E; Hill, Ross A; Ferns, Peter N

    2016-01-01

    Large-scale climate processes influence many aspects of ecology including breeding phenology, reproductive success and survival across a wide range of taxa. Some effects are direct, for example, in temperate-zone birds, ambient temperature is an important cue enabling breeding effort to coincide with maximum food availability, and earlier breeding in response to warmer springs has been documented in many species. In other cases, time-lags of up to several years in ecological responses have been reported, with effects mediated through biotic mechanisms such as growth rates or abundance of food supplies. Here we use 23 years of data for a temperate woodland bird species, the great tit (Parus major), breeding in deciduous woodland in eastern England to demonstrate a time-lagged linear relationship between the on-set of egg laying and the winter index of the North Atlantic Oscillation such that timing can be predicted from the winter index for the previous year. Thus the timing of bird breeding (and, by inference, the timing of spring events in general) can be predicted one year in advance. We also show that the relationship with the winter index appears to arise through an abiotic time-lag with local spring warmth in our study area. Examining this link between local conditions and larger-scale processes in the longer-term showed that, in the past, significant relationships with the immediately preceding winter index were more common than those with the time-lagged index, and especially so from the late 1930s to the early 1970s. However, from the mid 1970s onwards, the time-lagged relationship has become the most significant, suggesting a recent change in climate patterns. The strength of the current time-lagged relationship suggests that it might have relevance for other temperature-dependent ecological relationships.

  17. Physical/chemical modeling for photovoltaic module life prediction

    Science.gov (United States)

    Moacanin, J.; Carroll, W. F.; Gupta, A.

    1979-01-01

    The paper presents a generalized methodology for identification and evaluation of potential degradation and failure of terrestrial photovoltaic encapsulation. Failure progression modeling and an interaction matrix are utilized to complement the conventional approach to failure degradation mode identification. Comparison of the predicted performance based on these models can produce: (1) constraints on system or component design, materials or operating conditions, (2) qualification (predicted satisfactory function), and (3) uncertainty. The approach has been applied to an investigation of an unexpected delamination failure; it is being used to evaluate thermomechanical interactions in photovoltaic modules and to study corrosion of contacts and interconnects.

  18. 13C-detected NMR experiments for measuring chemical shifts and coupling constants in nucleic acid bases.

    Science.gov (United States)

    Fiala, Radovan; Sklenár, Vladimír

    2007-10-01

    The paper presents a set of two-dimensional experiments that utilize direct (13)C detection to provide proton-carbon, carbon-carbon and carbon-nitrogen correlations in the bases of nucleic acids. The set includes a (13)C-detected proton-carbon correlation experiment for the measurement of (13)C-(13)C couplings, the CaCb experiment for correlating two quaternary carbons, the HCaCb experiment for the (13)C-(13)C correlations in cases where one of the carbons has a proton attached, the HCC-TOCSY experiment for correlating a proton with a network of coupled carbons, and a (13)C-detected (13)C-(15)N correlation experiment for detecting the nitrogen nuclei that cannot be detected via protons. The IPAP procedure is used for extracting the carbon-carbon couplings and/or carbon decoupling in the direct dimension, while the S(3)E procedure is preferred in the indirect dimension of the carbon-nitrogen experiment to obtain the value of the coupling constant. The experiments supply accurate values of (13)C and (15)N chemical shifts and carbon-carbon and carbon-nitrogen coupling constants. These values can help to reveal structural features of nucleic acids either directly or via induced changes when the sample is dissolved in oriented media.

  19. Chemical shifts assignments of the archaeal MC1 protein and a strongly bent 15 base pairs DNA duplex in complex.

    Science.gov (United States)

    Loth, Karine; Landon, Céline; Paquet, Françoise

    2015-04-01

    MC1 is the most abundant architectural protein present in Methanosarcina thermophila CHTI55 in laboratory growth conditions and is structurally unrelated to other DNA-binding proteins. MC1 functions are to shape and to protect DNA against thermal denaturation by binding to it. Therefore, MC1 has a strong affinity for any double-stranded DNA. However, it recognizes and preferentially binds to bent DNA, such as four-way junctions and negatively supercoiled DNA minicircles. Combining NMR data, electron microscopy data, biochemistry, molecular modelisation and docking approaches, we proposed recently a new type of DNA/protein complex, in which the monomeric protein MC1 binds on the concave side of a strongly bent 15 base pairs DNA. We present here the NMR chemical shifts assignments of each partner in the complex, (1)H (15)N MC1 protein and (1)H (13)C (15)N bent duplex DNA, as first step towards the first experimental 3D structure of this new type of DNA/protein complex.

  20. Shifting Phases for Patchy Particles - Effect of mutagenesis and chemical modification on the phase diagram of human gamma D crystallin

    Science.gov (United States)

    McManus, Jennifer J.; James, Susan; McNamara, Ruth; Quinn, Michelle

    2014-03-01

    Single mutations in human gamma D crystallin (HGD), a protein found in the eye lens are associated with several childhood cataracts. Phase diagrams for several of these protein mutants have been measured and reveal that phase boundaries are shifted compared with the native protein, leading to condensation of protein in a physiologically relevant regime. Using HGD as a model protein, we have constructed phase diagrams for double mutants of the protein, incorporating two single amino acid substitutions for which phase diagrams are already known. In doing so, the characteristics of each of the single mutations are maintained but both are now present in the same protein particle. While these proteins are not of interest physiologically, this strategy allows the controlled synthesis of nano-scale patchy particles in which features associated with a known phase behavior can be included. It can also provide a strategy for the controlled crystallisation of proteins. Phase boundaries also change after the chemical modification of the protein, through the covalent attachment of fluorescent labels, for example, and this will also be discussed. The authors acknowledge Science Foundation Ireland Stokes Lectureship and Grant 11/RFP.1/PHY/3165. The authors also acknowledge the Irish Research Council and the John and Pat Hume Scholarship.

  1. Predicting Chemical Toxicity from Proteomics and Computational Chemistry

    Science.gov (United States)

    2008-07-30

    cells. Results for the numerical invariants based on proteomics maps from liver tissue from rats exposed to peroxisome proliferators...characterizations of proteomic maps and chemically induced changes to proteomes, K Balasubramanian, K Khokhani and SC Basak, Proteome Res., 5,1133-1142 (2006...for proteomics maps: Application to rodent hepatotoxicity , SC Basak, BD Gute, KT Geiss and FA Witzmann, in Computation in Modern Science and

  2. Time shift in slope failure prediction between unimodal and bimodal modeling approaches

    Science.gov (United States)

    Ciervo, Fabio; Casini, Francesca; Nicolina Papa, Maria; Medina, Vicente

    2016-04-01

    Together with the need to use more appropriate mathematical expressions for describing hydro-mechanical soil processes, a challenge issue relates to the need of considering the effects induced by terrain heterogeneities on the physical mechanisms, taking into account the implications of the heterogeneities in affecting time-dependent hydro-mechanical variables, would improve the prediction capacities of models, such as the ones used in early warning systems. The presence of the heterogeneities in partially-saturated slopes results in irregular propagation of the moisture and suction front. To mathematically represent the "dual-implication" generally induced by the heterogeneities in describing the hydraulic terrain behavior, several bimodal hydraulic models have been presented in literature and replaced the conventional sigmoidal/unimodal functions; this presupposes that the scale of the macrostructure is comparable with the local scale (Darcy scale), thus the Richards' model can be assumed adequate to mathematically reproduce the processes. The purpose of this work is to focus on the differences in simulating flow infiltration processes and slope stability conditions originated from preliminary choices of hydraulic models and contextually between different approaches to evaluate the factor of safety (FoS). In particular, the results of two approaches are compared. The first one includes the conventional expression of the FoS under saturated conditions and the widespread used hydraulic model of van Genuchten-Mualem. The second approach includes a generalized FoS equation for infinite-slope model under variably saturated soil conditions (Lu and Godt, 2008) and the bimodal Romano et al.'s (2011) functions to describe the hydraulic response. The extension of the above mentioned approach to the bimodal context is based on an analytical method to assess the effects of the hydraulic properties on soil shear developed integrating a bimodal lognormal hydraulic function

  3. Predicting clinical outcome using brain activation associated with set-shifting and central coherence skills in Anorexia Nervosa.

    Science.gov (United States)

    Garrett, Amy S; Lock, James; Datta, Nandini; Beenhaker, Judy; Kesler, Shelli R; Reiss, Allan L

    2014-10-01

    Patients with Anorexia Nervosa (AN) have neuropsychological deficits in Set-Shifting (SS) and central coherence (CC) consistent with an inflexible thinking style and overly detailed processing style, respectively. This study investigates brain activation during SS and CC tasks in patients with AN and tests whether this activation is a biomarker that predicts response to treatment. FMRI data were collected from 21 females with AN while performing an SS task (the Wisconsin Card Sort) and a CC task (embedded figures), and used to predict outcome following 16 weeks of treatment (either 16 weeks of cognitive behavioral therapy or 8 weeks cognitive remediation therapy followed by 8 weeks of cognitive behavioral therapy). Significant activation during the SS task included bilateral dorsolateral and ventrolateral prefrontal cortex and left anterior middle frontal gyrus. Higher scores on the neuropsychological test of SS (measured outside the scanner at baseline) were correlated with greater DLPFC and VLPFC/insula activation. Improvements in SS following treatment were significantly predicted by a combination of low VLPFC/insula and high anterior middle frontal activation (R squared = .68, p = .001). For the CC task, visual and parietal cortical areas were activated, but were not significantly correlated with neuropsychological measures of CC and did not predict outcome. Cognitive flexibility requires the support of several prefrontal cortex resources. As previous studies suggest that the VLPFC is important for selecting context-appropriate responses, patients who have difficulties with this skill may benefit the most from cognitive therapy with or without cognitive remediation therapy. The ability to sustain inhibition of an unwanted response, subserved by the anterior middle frontal gyrus, is a cognitive feature that predicts favorable outcome to cognitive treatment. CC deficits may not be an effective predictor of clinical outcome. Copyright © 2014 Elsevier Ltd. All

  4. Molecular toxicity identification evaluation (mTIE) approach predicts chemical exposure in Daphnia magna.

    Science.gov (United States)

    Antczak, Philipp; Jo, Hun Je; Woo, Seonock; Scanlan, Leona; Poynton, Helen; Loguinov, Alex; Chan, Sarah; Falciani, Francesco; Vulpe, Chris

    2013-10-15

    Daphnia magna is a bioindicator organism accepted by several international water quality regulatory agencies. Current approaches for assessment of water quality rely on acute and chronic toxicity that provide no insight into the cause of toxicity. Recently, molecular approaches, such as genome wide gene expression responses, are enabling an alternative mechanism based approach to toxicity assessment. While these genomic methods are providing important mechanistic insight into toxicity, statistically robust prediction systems that allow the identification of chemical contaminants from the molecular response to exposure are needed. Here we apply advanced machine learning approaches to develop predictive models of contaminant exposure using a D. magna gene expression data set for 36 chemical exposures. We demonstrate here that we can discriminate between chemicals belonging to different chemical classes including endocrine disruptors and inorganic and organic chemicals based on gene expression. We also show that predictive models based on indices of whole pathway transcriptional activity can achieve comparable results while facilitating biological interpretability.

  5. Prediction of pregnancy-induced hypertension by a shift of blood pressure class according to the JSH 2009 guidelines.

    Science.gov (United States)

    Jwa, Seung Chik; Arata, Naoko; Sakamoto, Naoko; Watanabe, Noriyoshi; Aoki, Hiroaki; Kurauchi-Mito, Asako; Dongmei, Qiu; Ohya, Yukihiro; Ichihara, Atsuhiro; Kitagawa, Michihiro

    2011-11-01

    Elevated blood pressure (BP) at early or mid pregnancy is a known risk factor for pregnancy-induced hypertension (PIH). However, the association between BP changes during the first half of pregnancy and subsequent PIH development is unknown. We used changes in maternal BP between 16 and 20 weeks of gestation to evaluate the risk of PIH. A total of 976 pregnant women with BP estimations recorded before 16 weeks and at 20 weeks of gestation participated in this study. BPs were classified by the Japanese Society of Hypertension 2009 Hypertension Treatment Guidelines (JSH 2009). There was a significant trend for future PIH in women whose JSH 2009 BP class increased between 16 and 20 weeks of gestation, and the risk of PIH was highest among women whose BP was Class IV Hypertension (systolic BP≥140 mm Hg and/or diastolic BP≥90 mm Hg). The risk of PIH increased in women whose BPs shifted from Classes I Optimal (systolic BP<120 mm Hg and diastolic BP<80 mm Hg) and II Normal (systolic BP 120-129 mm Hg and/or diastolic BP 80-84 mm Hg) before 16 weeks to Class III High-Normal (systolic BP 130-139 mm Hg and/or diastolic BP 85-89 mm Hg) at 20 weeks of gestation. These shifts in BP class were significantly correlated with the risk of PIH after adjustments for variables (P-value for trend <0.05). Within JSH 2009 Classes I, II and III, a shift in BP from a low to a high class between 16 and 20 weeks of gestation predicts the subsequent development of PIH.

  6. Predicting partitioning of volatile organic compounds from air into plant cuticular matrix by quantum chemical descriptors

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Based on theoretical linear solvation energy relationship and quantum chemical descriptors computed by AM1 Hamiltonian, a new model is developed to predict the partitioning of some volatile organic compounds between the plant cuticular matrix and air.

  7. Multilinear relations between {sup 13} C NMR chemical shifts of aliphatic halides; Relacoes lineares multiplas entre deslocamentos quimicos em RMN {sup 13} C de haletos alifaticos

    Energy Technology Data Exchange (ETDEWEB)

    Doyama, Julio Toshimi [UNESP, Botucatu, SP (Brazil). Inst. de Biociencias. Dept. de Quimica e Bioquimica; Tornero, Maria Teresinha Trovarelli [UNESP, Botucatu, SP (Brazil). Inst. de Biociencias. Dept. de Bioestatistica; Yoshida, Massayoshi [UNESP, Araraquara, SP (Brazil). Inst. de Quimica. Dept. de Quimica Organica

    1999-07-01

    The {sup 13} C NMR chemical shifts of the {alpha}, {beta}, {gamma} and {delta} carbons of 17 sets of aliphatic halides (F, Cl, Br and I), including mono, bi and tricyclic compounds, can be reproduced by a linear equation composed with two constants and two variables: {delta}{sub RX} = A{sup *} {delta}{sub R-X2}, where A and B are constants derived from multilinear regression of {sup 13} C chemical shifts observed; {delta}{sub R-X}, the chemical shifts of aliphatic halide (R-X); and {delta}{sub R-X1}, {delta}{sub R-X2} the chemical shifts of other halides. It was observed a better correlation for aliphatic bromides (R-X) by using data of aliphatic fluorides (R-X 1) and aliphatic iodides (R-X 2), resulting R{sup 2} of 0.9989 and average absolute deviation (AVG) of 0.39 ppm. For the chlorides (R-X), the better correlation was observed by using data of bromides (R-X 1) was observed better correlation with data of bromides (R-X 1) and iodides (R-X 2), R{sup 2} of 0.997 and AVG of 1.10 ppm. For the iodides (R-X) was observed better correlation with data of fluorides (R-X 1) and bromides (R-X 2), R{sup 2} of 0.9972 and AVG of 0.60 ppm. (author)

  8. Chemical shift as a probe of molecular interfaces: NMR studies of DNA binding by the three amino-terminal zinc finger domains from transcription factor IIIA

    Energy Technology Data Exchange (ETDEWEB)

    Foster, Mark P.; Wuttke, Deborah S.; Clemens, Karen R.; Jahnke, Wolfgang; Radhakrishnan, Ishwar; Tennant, Linda; Reymond, Martine; Chung, John; Wright, Peter E. [Scripps Research Institute, Department of Molecular Biology and Skaggs Institute for Chemical Biology (United States)

    1998-07-15

    We report the NMR resonance assignments for a macromolecular protein/DNA complex containing the three amino-terminal zinc fingers (92 amino acid residues) of Xenopus laevis TFIIIA (termed zf1-3) bound to the physiological DNA target (15 base pairs), and for the free DNA. Comparisons are made of the chemical shifts of protein backbone{sup 1} H{sup N}, {sup 15}N,{sup 13} C{sup {alpha}} and{sup 13} C{sup {beta}} and DNA base and sugar protons of the free and bound species. Chemical shift changes are analyzed in the context of the structures of the zf1-3/DNA complex to assess the utility of chemical shift change as a probe of molecular interfaces. Chemical shift perturbations that occur upon binding in the zf1-3/DNA complex do not correspond directly to the structural interface, but rather arise from a number of direct and indirect structural and dynamic effects.

  9. Predictive models for the assessment of occupational exposure to chemicals: A new challenge for employers

    OpenAIRE

    Jan Piotr Gromiec; Małgorzata Kupczewska-Dobecka; Agnieszka Jankowska; Sławomir Czerczak

    2013-01-01

    Employers are obliged to carry out and document the risk associated with the use of chemical substances. The best but the most expensive method is to measure workplace concentrations of chemicals. At present no "measureless" method for risk assessment is available in Poland, but predictive models for such assessments have been developed in some countries. The purpose of this work is to review and evaluate the applicability of selected predictive methods for assessing occupational inhalation e...

  10. Significance of vapor phase chemical reactions on CVD rates predicted by chemically frozen and local thermochemical equilibrium boundary layer theories

    Science.gov (United States)

    Gokoglu, Suleyman A.

    1988-01-01

    This paper investigates the role played by vapor-phase chemical reactions on CVD rates by comparing the results of two extreme theories developed to predict CVD mass transport rates in the absence of interfacial kinetic barrier: one based on chemically frozen boundary layer and the other based on local thermochemical equilibrium. Both theories consider laminar convective-diffusion boundary layers at high Reynolds numbers and include thermal (Soret) diffusion and variable property effects. As an example, Na2SO4 deposition was studied. It was found that gas phase reactions have no important role on Na2SO4 deposition rates and on the predictions of the theories. The implications of the predictions of the two theories to other CVD systems are discussed.

  11. The many roles of quantum chemical predictions in synthetic organic chemistry.

    Science.gov (United States)

    Nguyen, Quynh Nhu N; Tantillo, Dean J

    2014-03-01

    This account discusses representative case studies for various applications of quantum chemical calculations in synthetic organic chemistry. These include confirmation of target structures, methodology development, and catalyst design. These examples demonstrate how predictions from quantum chemical calculations can be utilized to streamline synthetic efforts.

  12. Are individuals' nighttime sleep characteristics prior to shift-work exposure predictive for parameters of daytime sleep after commencing shift work?

    NARCIS (Netherlands)

    Lammers-van der Holst, H.M.; van Dongen, H.P.A.; Kerkhof, G.A.

    2006-01-01

    This study aimed to examine prospectively whether individual nighttime sleep characteristics at baseline (prior to shift‐work exposure) are related to parameters of daytime sleep after commencing shift work. A longitudinal field study was carried out with novice police officers of the Dutch Police F

  13. [Application of near infrared reflectance spectroscopy to predict meat chemical compositions: a review].

    Science.gov (United States)

    Tao, Lin-Li; Yang, Xiu-Juan; Deng, Jun-Ming; Zhang, Xi

    2013-11-01

    In contrast to conventional methods for the determination of meat chemical composition, near infrared reflectance spectroscopy enables rapid, simple, secure and simultaneous assessment of numerous meat properties. The present review focuses on the use of near infrared reflectance spectroscopy to predict meat chemical compositions. The potential of near infrared reflectance spectroscopy to predict crude protein, intramuscular fat, fatty acid, moisture, ash, myoglobin and collagen of beef, pork, chicken and lamb is reviewed. This paper discusses existing questions and reasons in the current research. According to the published results, although published results vary considerably, they suggest that near-infrared reflectance spectroscopy shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. In particular, under commercial conditions where simultaneous measurements of different chemical components are required, near infrared reflectance spectroscopy is expected to be the method of choice. The majority of studies selected feature-related wavelengths using principal components regression, developed the calibration model using partial least squares and modified partial least squares, and estimated the prediction accuracy by means of cross-validation using the same sample set previously used for the calibration. Meat fatty acid composition predicted by near-infrared spectroscopy and non-destructive prediction and visualization of chemical composition in meat using near-infrared hyperspectral imaging and multivariate regression are the hot studying field now. On the other hand, near infrared reflectance spectroscopy shows great difference for predicting different attributes of meat quality which are closely related to the selection of calibration sample set, preprocessing of near-infrared spectroscopy and modeling approach. Sample preparation also has an important effect on the reliability of NIR prediction; in particular

  14. Future climate change is predicted to shift long-term persistence zones in the cold-temperate kelp Laminaria hyperborea.

    Science.gov (United States)

    Assis, Jorge; Lucas, Ana Vaz; Bárbara, Ignacio; Serrão, Ester Álvares

    2016-02-01

    Global climate change is shifting species distributions worldwide. At rear edges (warmer, low latitude range margins), the consequences of small variations in environmental conditions can be magnified, producing large negative effects on species ranges. A major outcome of shifts in distributions that only recently received attention is the potential to reduce the levels of intra-specific diversity and consequently the global evolutionary and adaptive capacity of species to face novel disturbances. This is particularly important for low dispersal marine species, such as kelps, that generally retain high and unique genetic diversity at rear ranges resulting from long-term persistence, while ranges shifts during climatic glacial/interglacial cycles. Using ecological niche modelling, we (1) infer the major environmental forces shaping the distribution of a cold-temperate kelp, Laminaria hyperborea (Gunnerus) Foslie, and we (2) predict the effect of past climate changes in shaping regions of long-term persistence (i.e., climatic refugia), where this species might hypothetically harbour higher genetic diversity given the absence of bottlenecks and local extinctions over the long term. We further (3) assessed the consequences of future climate for the fate of L. hyperborea using different scenarios of greenhouse gas emissions (RCP 2.6 and RCP 8.5). Results show NW Iberia, SW Ireland and W English Channel, Faroe Islands and S Iceland, as regions where L. hyperborea may have persisted during past climate extremes until present day. All predictions for the future showed expansions to northern territories coupled with the significant loss of suitable habitats at low latitude range margins, where long-term persistence was inferred (e.g., NW Iberia). This pattern was particularly evident in the most agressive scenario of climate change (RCP 8.5), likely driving major biodiversity loss, changes in ecosystem functioning and the impoverishment of the global gene pool of L

  15. A binary classifier for prediction of the types of metabolic pathway of chemicals.

    Science.gov (United States)

    Fang, Yemin; Chen, Lei

    2016-12-15

    The study of metabolic pathway is one of the most important fields in biochemistry. Good comprehension of the metabolic pathway system is helpful to uncover the mechanism of some fundamental biological processes. Because chemicals are part of the main components of the metabolic pathway, correct identification of which metabolic pathways a given chemical can participate in is an important step for understanding the metabolic pathway system. Most previous methods only considered the chemical information, which tried to deal with a multi-label classification problem of assigning chemicals to proper metabolic pathways. In this study, the pathway information was also employed, thereby transforming the problem into a binary classification problem of identifying the pair of chemicals and metabolic pathways, i.e., a chemical and a metabolic pathway was paired as a sample to be considered in this study. To construct the prediction model, the association between chemical pathway type pairs was evaluated by integrating the association between chemicals and association between pathway types. The support vector machine was adopted as the prediction engine. The extensive tests show that the constructed model yields good performance with total prediction accuracy around 0.878. Furthermore, the comparison results indicate that our model is quite effective and suitable for the identification of whether a given chemical can participate in a given metabolic pathway.

  16. Characterization and prediction of chemical functions and weight fractions in consumer products

    Directory of Open Access Journals (Sweden)

    Kristin K. Isaacs

    2016-01-01

    Full Text Available Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents. We combined these functions with weight fraction data for 4115 personal care products (PCPs to characterize the composition of 66 different product categories (e.g., shampoos. We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties. We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-based chemical prioritization.

  17. Nonlinear model predictive control for chemical looping process

    Energy Technology Data Exchange (ETDEWEB)

    Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng

    2017-08-22

    A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to a CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.

  18. Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

    Directory of Open Access Journals (Sweden)

    Aleksandar Sabljic

    2004-12-01

    Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

  19. Chemical shift of U L3 edges in different uranium compounds obtained by X-ray absorption spectroscopy with synchrotron radiation

    Indian Academy of Sciences (India)

    D Joseph; C Nayak; P Venu Babu; S N Jha; D Bhattacharyya

    2014-05-01

    Uranium L3 X-ray absorption edge was measured in various compounds containing uranium in U4+, U5+ and U6+ oxidation states. The measurements have been carried out at the Energy Dispersive EXAFS beamline (BL-08) at INDUS-2 synchrotron radiation source at RRCAT, Indore. Energy shifts of ∼ 2–3 eV were observed for U L3 edge in the U-compounds compared to their value in elemental U. The different chemical shifts observed for the compounds having the same oxidation state of the cation but different anions or ligands show the effect of different chemical environments surrounding the cations in determining their X-ray absorption edges in the above compounds. The above chemical effect has been quantitatively described by determining the effective charges on U cation in the above compounds.

  20. Predicting diffusion coefficients of chemicals in and through packaging materials.

    Science.gov (United States)

    Fang, Xiaoyi; Vitrac, Olivier

    2017-01-22

    Most of the physicochemical properties in polymers such as activity and partition coefficients, diffusion coefficients, and their activation with temperature are accessible to direct calculations from first principles. Such predictions are particularly relevant for food packaging as they can be used (1) to demonstrate the compliance or safety of numerous polymer materials and of their constitutive substances (e.g. additives, residues…), when they are used: as containers, coatings, sealants, gaskets, printing inks, etc. (2) or to predict the indirect contamination of food by pollutants (e.g. from recycled polymers, storage ambiance…) (3) or to assess the plasticization of materials in contact by food constituents (e.g. fat matter, aroma…). This review article summarizes the classical and last mechanistic descriptions of diffusion in polymers and discusses the reliability of semi-empirical approaches used for compliance testing both in EU and US. It is concluded that simulation of diffusion in or through polymers is not limited to worst-case assumptions but could also be applied to real cases for risk assessment, designing packaging with low leaching risk or to synthesize plastic additives with low diffusion rates.

  1. Using chemical-shift MR imaging to quantify fatty degeneration within supraspinatus muscle due to supraspinatus tendon injuries

    Energy Technology Data Exchange (ETDEWEB)

    Gokalp, Gokhan; Yildirim, Nalan; Yazici, Zeynep [Uludag University Medical Faculty, Department of Radiology, Gorukle, Bursa (Turkey); Ercan, Ilker [Uludag University Medical Faculty, Department of Biostatistics, Gorukle, Bursa (Turkey)

    2010-12-15

    The objective of this study was to prospectively quantify the fatty degeneration of supraspinatus (SSP) muscle due to SSP tendon injuries by using chemical-shift magnetic resonance imaging (CS-MRI). Forty-one patients with suspected rotator cuff tear or impingement examined with MR arthrography were included in the study. The following images were obtained after injection of diluted gadolinium chelate into glenohumeral joint: fat-saturated T1-weighted spin echo in the coronal, axial, and sagittal-oblique plane; fat-saturated T2-weighted and intermediate-weighted fast spin-echo in the coronal-oblique plane; and T1-weighted spin echo in the sagittal-oblique plane. CS-MRI was performed in the coronal plane using a double-echo fast low-angle shot (FLASH) sequence. SSP tendon changes were classified as normal, tendinosis, and partial and complete tear according to MR arthrography findings. Fatty degeneration was quantified after measurement of signal intensity values within the region of interest (ROI) placed over SSP muscle. Signal intensity (SI) suppression ratio and SI index were calculated with the values obtained. Degrees of fatty degeneration depicted in normal subjects and subjects with rotator cuff injuries were compared. Median (min:max) was used as descriptive values. SI suppression ratio was -3.5% (-15.5:3.03) in normal subjects, whereas it was -13.5% (-28.55:-6.60), -30.7% (-41.5:-20.35), and -43.75% (-62:-24.90) in tendinosis, partial and complete tears, respectively. SI index was 0.75% (-6:11.5) in normal subjects. It was 10% (4.50:27), 26.5% (19.15:35.5), and 41% (23.9:57) in tendinosis, partial and complete tears, respectively. The increase in degree of fatty degeneration parallels the seriousness of tendon pathology. CS-MRI is a useful method for grading fat accumulation within SSP muscle. (orig.)

  2. Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com [Academy of Scientific and Innovative Research, Council of Scientific and Industrial Research, New Delhi (India); Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001 (India); Gupta, Shikha; Rai, Premanjali [Academy of Scientific and Innovative Research, Council of Scientific and Industrial Research, New Delhi (India); Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001 (India)

    2013-10-15

    Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models was performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and predictive

  3. Quantitative Regression Models for the Prediction of Chemical Properties by an Efficient Workflow.

    Science.gov (United States)

    Yin, Yongmin; Xu, Congying; Gu, Shikai; Li, Weihua; Liu, Guixia; Tang, Yun

    2015-10-01

    Rapid safety assessment is more and more needed for the increasing chemicals both in chemical industries and regulators around the world. The traditional experimental methods couldn't meet the current demand any more. With the development of the information technology and the growth of experimental data, in silico modeling has become a practical and rapid alternative for the assessment of chemical properties, especially for the toxicity prediction of organic chemicals. In this study, a quantitative regression workflow was built by KNIME to predict chemical properties. With this regression workflow, quantitative values of chemical properties can be obtained, which is different from the binary-classification model or multi-classification models that can only give qualitative results. To illustrate the usage of the workflow, two predictive models were constructed based on datasets of Tetrahymena pyriformis toxicity and Aqueous solubility. The qcv (2) and qtest (2) of 5-fold cross validation and external validation for both types of models were greater than 0.7, which implies that our models are robust and reliable, and the workflow is very convenient and efficient in prediction of various chemical properties. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. High pressure electrides: a predictive chemical and physical theory.

    Science.gov (United States)

    Miao, Mao-Sheng; Hoffmann, Roald

    2014-04-15

    Electrides, in which electrons occupy interstitial regions in the crystal and behave as anions, appear as new phases for many elements (and compounds) under high pressure. We propose a unified theory of high pressure electrides (HPEs) by treating electrons in the interstitial sites as filling the quantized orbitals of the interstitial space enclosed by the surrounding atom cores, generating what we call an interstitial quasi-atom, ISQ. With increasing pressure, the energies of the valence orbitals of atoms increase more significantly than the ISQ levels, due to repulsion, exclusion by the atom cores, effectively giving the valence electrons less room in which to move. At a high enough pressure, which depends on the element and its orbitals, the frontier atomic electron may become higher in energy than the ISQ, resulting in electron transfer to the interstitial space and the formation of an HPE. By using a He lattice model to compress (with minimal orbital interaction at moderate pressures between the surrounding He and the contained atoms or molecules) atoms and an interstitial space, we are able to semiquantitatively explain and predict the propensity of various elements to form HPEs. The slopes in energy of various orbitals with pressure (s > p > d) are essential for identifying trends across the entire Periodic Table. We predict that the elements forming HPEs under 500 GPa will be Li, Na (both already known to do so), Al, and, near the high end of this pressure range, Mg, Si, Tl, In, and Pb. Ferromagnetic electrides for the heavier alkali metals, suggested by Pickard and Needs, potentially compete with transformation to d-group metals.

  5. Predicting drug side-effect profiles: a chemical fragment-based approach.

    Science.gov (United States)

    Pauwels, Edouard; Stoven, Véronique; Yamanishi, Yoshihiro

    2011-05-18

    Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. The proposed method is expected to be useful in various stages of the drug development process.

  6. Prediction of simultaneously large and opposite generalized Goos-Hänchen shifts for TE and TM light beams in an asymmetric double-prism configuration.

    Science.gov (United States)

    Li, Chun-Fang; Wang, Qi

    2004-05-01

    It is predicted that large and opposite generalized Goos-Hänchen (GGH) shifts may occur simultaneously for TE and TM light beams upon reflection from an asymmetric double-prism configuration when the angle of incidence is below but near the critical angle for total reflection, which may lead to interesting applications in optical devices and integrated optics. Numerical simulations show that the magnitude of the GGH shift can be of the order of beam's width.

  7. Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies

    Science.gov (United States)

    Abel zur Wiesch, Pia; Cohen, Ted

    2017-01-01

    Identifying optimal dosing of antibiotics has proven challenging—some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood. PMID:28060813

  8. Study of improved methods for predicting chemical equilibria

    Energy Technology Data Exchange (ETDEWEB)

    Lenz, T.G.; Vaughan, J.D.

    1992-06-01

    The objective of our research has been to develop computational methods that have the capability of accurately predicting equilibrium constants of typical organic reactions in gas and liquid solution phases. We have chosen Diels-Alder reactions as prototypic systems for the investigation, chiefly because there are an adequate number of reported equilibrium constants for the candidate reactions in both gas and solution phases, which data provides a suitable basis for tests of the developed computational methods. Our approach has been to calculate the standard enthalpies of formation ({Delta}H{sub f}{sup 0}) at 298.15K and the standard thermodynamic functions (S{sup 0}, Cp{sup 0}, and (H{sup 0}-H{sub 0}{sup 0})/T) for a range of temperatures for reactants and products, and from these properties to calculate standard enthalpies, entropies, Gibbs free energies, and equilibrium constants ({Delta}H{sub T}{sup 0}, {Delta}S{sub T}{sup 0}, and K{sub a}) at various temperatures for the chosen reaction.

  9. Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.

    Science.gov (United States)

    Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted

    2017-01-01

    Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.

  10. Quantum chemical calculations to reveal the relationship between the chemical structure and the fluorescence characteristics of phenylquinolinylethynes and phenylisoquinolinylethynes derivatives, and to predict their relative fluorescence intensity.

    Science.gov (United States)

    Riahi, Siavash; Beheshti, Abolghasem; Ganjali, Mohammad Reza; Norouzi, Parviz

    2009-12-01

    In this paper the relationship between the chemical structure and fluorescence characteristics of 30 phenylquinolinylethyne (PhQE), and phenylisoquinolinylethyne (PhIE) derivatives compounds employing ab initio calculations have been elucidated. Quantum chemical calculations (6-31G) were carried out to obtain: the optimized geometry, energy levels, charges and dipole moments of these compounds, in the singlet (steady and excited states) and triplet states. The relationship between quantum chemical descriptors, and wavelength of maximum excitation and emission indicated that these two parameters have the most correlation with quantum chemical hardness (eta). Also, stokes shift has the most correlation with the square of difference between the maximum of positive charges in the singlet steady and singlet excited states. The quantitative structure-property relationship (QSPR) of PhQE and PhIE was studied for relative fluorescence intensity (RFI). The genetic algorithm (GA) was applied to select the variables that resulted in the best-fit models. After the variable selection, multiple linear regression (MLR) and support vector machine (SVM) were both utilized to construct linear and non-linear QSPR models, respectively. The SVM model demonstrated a better performance than that of the MLR model. The route mean square error (RMSE) in the training and the test sets for the SVM model was 0.195 and 0.324, and the correlation coefficients were 0.965 and 0.960, respectively, thus revealing the reliability of this model. The resulting data indicated that SVM could be used as a powerful modeling tool for QSPR studies. According to the best of our knowledge, this is the first research on QSPR studies to predict RFI for a series of PhQE and PhIE derivative compounds using SVM.

  11. Relativistic four-component DFT calculations of 1H NMR chemical shifts in transition-metal hydride complexes: unusual high-field shifts beyond the Buckingham-Stephens model.

    Science.gov (United States)

    Hrobárik, Peter; Hrobáriková, Veronika; Meier, Florian; Repiský, Michal; Komorovský, Stanislav; Kaupp, Martin

    2011-06-09

    State-of-the-art relativistic four-component DFT-GIAO-based calculations of (1)H NMR chemical shifts of a series of 3d, 4d, and 5d transition-metal hydrides have revealed significant spin-orbit-induced heavy atom effects on the hydride shifts, in particular for several 4d and 5d complexes. The spin-orbit (SO) effects provide substantial, in some cases even the dominant, contributions to the well-known characteristic high-field hydride shifts of complexes with a partially filled d-shell, and thereby augment the Buckingham-Stephens model of off-center paramagnetic ring currents. In contrast, complexes with a 4d(10) and 5d(10) configuration exhibit large deshielding SO effects on their hydride (1)H NMR shifts. The differences between the two classes of complexes are attributed to the dominance of π-type d-orbitals for the true transition-metal systems compared to σ-type orbitals for the d(10) systems.

  12. Proton-detected 3D (15)N/(1)H/(1)H isotropic/anisotropic/isotropic chemical shift correlation solid-state NMR at 70kHz MAS.

    Science.gov (United States)

    Pandey, Manoj Kumar; Yarava, Jayasubba Reddy; Zhang, Rongchun; Ramamoorthy, Ayyalusamy; Nishiyama, Yusuke

    2016-01-01

    Chemical shift anisotropy (CSA) tensors offer a wealth of information for structural and dynamics studies of a variety of chemical and biological systems. In particular, CSA of amide protons can provide piercing insights into hydrogen-bonding interactions that vary with the backbone conformation of a protein and dynamics. However, the narrow span of amide proton resonances makes it very difficult to measure (1)H CSAs of proteins even by using the recently proposed 2D (1)H/(1)H anisotropic/isotropic chemical shift (CSA/CS) correlation technique. Such difficulties due to overlapping proton resonances can in general be overcome by utilizing the broad span of isotropic chemical shifts of low-gamma nuclei like (15)N. In this context, we demonstrate a proton-detected 3D (15)N/(1)H/(1)H CS/CSA/CS correlation experiment at fast MAS frequency (70kHz) to measure (1)H CSA values of unresolved amide protons of N-acetyl-(15)N-l-valyl-(15)N-l-leucine (NAVL).

  13. Predictive performance of the Vitrigel-eye irritancy test method using 118 chemicals.

    Science.gov (United States)

    Yamaguchi, Hiroyuki; Kojima, Hajime; Takezawa, Toshiaki

    2016-08-01

    We recently developed a novel Vitrigel-eye irritancy test (EIT) method. The Vitrigel-EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time-dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel-EIT method by testing a total of 118 chemicals. The category determined by the Vitrigel-EIT method in comparison to the globally harmonized system classification revealed that the sensitivity, specificity and accuracy were 90.1%, 65.9% and 80.5%, respectively. Here, five of seven false-negative chemicals were acidic chemicals inducing the irregular rising of transepithelial electrical resistance values. In case of eliminating the test chemical solutions showing pH 5 or lower, the sensitivity, specificity and accuracy were improved to 96.8%, 67.4% and 84.4%, respectively. Meanwhile, nine of 16 false-positive chemicals were classified irritant by the US Environmental Protection Agency. In addition, the disappearance of ZO-1, a tight junction-associated protein and MUC1, a cell membrane-spanning mucin was immunohistologically confirmed in the HCE models after exposing not only eye irritant chemicals but also false-positive chemicals, suggesting that such false-positive chemicals have an eye irritant potential. These data demonstrated that the Vitrigel-EIT method could provide excellent predictive performance to judge the widespread eye irritancy, including very mild irritant chemicals. We hope that the Vitrigel-EIT method contributes to the development of safe commodity chemicals. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd.

  14. Solvent-induced chemical shifts of methoxyl nuclear resonance signals in chalcones by benzene and trifluoroacetic acid

    Science.gov (United States)

    Khurana, Shashi K.; Krishnamoorthy, V.; Parmar, Virinder S.

    The 1H NMR spectra of eight different methoxylated chalcones have separately been recorded, (1) in deuterated chloroform; (2) in a mixture (1:1) of deuterated chloroform and benzene; and (3) in a mixture of deuterated chloroform, benzene and trifluoroacetic acid (2:2:1) and the benzene induced and TFA induced shift values have been assigned to different methoxyl groups. These shift values can serve as a guide in determining the structures of natural or new chalcones. The steric, electronic and conformational factors are discussed to explain the shift values.

  15. Precision Measurement of the Quadrupole Coupling and Chemical Shift Tensors of the Deuterons in α-Calcium Formate

    Science.gov (United States)

    Schmitt, Heike; Zimmermann, H.; Körner, O.; Stumber, M.; Meinel, C.; Haeberlen, U.

    2001-07-01

    Using calcium formate, α-Ca(DCOO)2, as a test sample, we explore how precisely deuteron quadrupole coupling (QC) and chemical shift (CS) tensors Q and σ can currently be measured. The error limits, ±0.09 kHz for the components of Q and ±0.06 ppm for those of σ, are at least three times lower than in any comparable previous experiment. The concept of a new receiver is described. A signal/noise ratio of 100 is realized in single-shot FT spectra. The measurement strategies and a detailed error analysis are presented. The precision of the measurement of Q is limited by the uncertainty of the rotation angles of the sample and that of σ by the uncertainty of the phase correction parameters needed in FT spectroscopy. With a 4-sigma confidence, it is demonstrated for the first time that the unique QC tensor direction of a deuteron attached to a carbon deviates from the bond direction; the deviation found is (1.2±0.3°). Evidence is provided for intermolecular QC contributions. In terms of Q, their size is roughly 4 kHz. The deuteron QC tensors in α-Ca(DCOO)2 (two independent deuteron sites) are remarkable in three respects. For deuterons attached to sp2 carbons, first, the asymmetry factors η and, second, the quadrupole coupling constants CQ, are unusually small, η1=0.018, η2=0.011, and CQ1=(151.27±0.06) kHz, CQ2=(154.09±0.06) kHz. Third, the principal direction associated with the largest negative QC tensor component lies in and not, as usual, perpendicular to the molecular plane. A rationalization is provided for these observations. The CS tensors obtained are in quantitative agreement with the results of an earlier, less precise, line-narrowing multiple-pulse study of α-Ca(HCOO)2. The assignment proposed in that work is confirmed. Finally we argue that a further 10-fold increase of the measurement precision of deuteron QC tensors, and a 2-fold increase of that of CS tensors, should be possible. We indicate the measures that need to be taken.

  16. A relativistic DFT methodology for calculating the structures and NMR chemical shifts of octahedral platinum and iridium complexes.

    Science.gov (United States)

    Vícha, Jan; Patzschke, Michael; Marek, Radek

    2013-05-28

    A methodology for optimizing the geometry and calculating the NMR shielding constants is calibrated for octahedral complexes of Pt(IV) and Ir(III) with modified nucleic acid bases. The performance of seven different functionals (BLYP, B3LYP, BHLYP, BP86, TPSS, PBE, and PBE0) in optimizing the geometry of transition-metal complexes is evaluated using supramolecular clusters derived from X-ray data. The effects of the size of the basis set (ranging from SVP to QZVPP) and the dispersion correction (D3) on the interatomic distances are analyzed. When structural deviations and computational demands are employed as criteria for evaluating the optimizations of these clusters, the PBE0/def2-TZVPP/D3 approach provides excellent results. In the next step, the PBE0/def2-TZVPP approach is used with the continuum-like screening model (COSMO) to optimize the geometry of single molecules for the subsequent calculation of the NMR shielding constants in solution. The two-component zeroth-order regular approximation (SO-ZORA) is used to calculate the NMR shielding constants (PBE0/TZP/COSMO). The amount of exact exchange in the PBE0 functional is validated for the nuclear magnetic shieldings of atoms in the vicinity of heavy transition metals. For the PBE0/TZP/COSMO setup, an exact exchange of 40% is found to accurately reproduce the experimental NMR shielding constants for both types of complexes. Finally, the effect of the amount of exact exchange on the NMR shielding calculations (which is capable of compensating for the structural deficiencies) is analyzed for various molecular geometries (SCS-MP2, BHLYP, and PBE0) and the influence of a trans-substituent on the NMR chemical shift of nitrogen is discussed. The observed dependencies for an iridium complex cannot be rationalized by visualizing the Fermi-contact (FC) induced spin density and probably originate from changes in the d-d transitions that modulate the spin-orbit (SO) part of the SO/FC term.

  17. Protein structure refinement using a quantum mechanics-based chemical shielding predictor

    DEFF Research Database (Denmark)

    Bratholm, Lars Andersen; Jensen, Jan Halborg

    2017-01-01

    The accurate prediction of protein chemical shifts using a quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor...... of a protein backbone and CB chemical shifts (ProCS15, PeerJ, 2016, 3, e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic...

  18. Detection of chemical vapor with high sensitivity by using the symmetrical metal-cladding waveguide-enhanced Goos-Hänchen shift.

    Science.gov (United States)

    Nie, Yiyou; Li, Yuanhua; Wu, Zhijing; Wang, Xianping; Yuan, Wen; Sang, Minghuang

    2014-04-21

    We present a novel and simple optical structure, i.e., the symmetrical metal-cladding waveguide, in which a polymer layer is added into the guiding layer, for sensitive detection of chemical vapor by using the enhanced Goos-Hänchen (GH) shift (nearly a millimeter scale). Owing to the high sensitivity of the excited ultrahigh-order modes, the vapor-induced effect (swelling effect and refractive index change) in the polymer layer will lead to a dramatic variation of the GH shift. The detected GH shift signal is irrelevant to the power fluctuation of the incident light. The detection limit of 9.5 ppm for toluene and 28.5 ppm for benzene has been achieved.

  19. Chemical shifts of K-X-ray absorption edges on copper in different compounds by X-ray absorption spectroscopy (XAS) with Synchrotron radiation

    Energy Technology Data Exchange (ETDEWEB)

    Joseph, D., E-mail: djoseph@barc.gov.in [Nuclear Physics Division, Bhabha Atomic Research Centre, Mumbai 400085 (India); Basu, S.; Jha, S.N.; Bhattacharyya, D. [Applied Spectroscopy Division, Bhabha Atomic Research Centre, Mumbai 400085 (India)

    2012-03-01

    Cu K X-ray absorption edges were measured in compounds such as CuO, Cu(CH{sub 3}CO{sub 2}){sub 2}, Cu(CO{sub 3}){sub 2}, and CuSO{sub 4} where Cu is present in oxidation state of 2+, using the energy dispersive EXAFS beamline at INDUS-2 Synchrotron radiation source at RRCAT, Indore. Energy shifts of {approx}4-7 eV were observed for Cu K X-ray absorption edge in the above compounds compared to its value in elemental copper. The difference in the Cu K edge energy shifts in the different compounds having same oxidation state of Cu shows the effect of different chemical environments surrounding the cation in the above compounds. The above chemical effect has been quantitatively described by determining the effective charges on Cu cations in the above compounds.

  20. Solid state NMR of proteins at high MAS frequencies: symmetry-based mixing and simultaneous acquisition of chemical shift correlation spectra

    Energy Technology Data Exchange (ETDEWEB)

    Bellstedt, Peter [Fritz Lipmann Institute, Biomolecular NMR spectroscopy, Leibniz Institute for Age Research (Germany); Herbst, Christian [Ubon Ratchathani University, Department of Physics, Faculty of Science (Thailand); Haefner, Sabine; Leppert, Joerg; Goerlach, Matthias; Ramachandran, Ramadurai, E-mail: raman@fli-leibniz.de [Fritz Lipmann Institute, Biomolecular NMR spectroscopy, Leibniz Institute for Age Research (Germany)

    2012-12-15

    We have carried out chemical shift correlation experiments with symmetry-based mixing sequences at high MAS frequencies and examined different strategies to simultaneously acquire 3D correlation spectra that are commonly required in the structural studies of proteins. The potential of numerically optimised symmetry-based mixing sequences and the simultaneous recording of chemical shift correlation spectra such as: 3D NCAC and 3D NHH with dual receivers, 3D NC Prime C and 3D C Prime NCA with sequential {sup 13}C acquisitions, 3D NHH and 3D NC Prime H with sequential {sup 1}H acquisitions and 3D CANH and 3D C'NH with broadband {sup 13}C-{sup 15}N mixing are demonstrated using microcrystalline samples of the {beta}1 immunoglobulin binding domain of protein G (GB1) and the chicken {alpha}-spectrin SH3 domain.

  1. Chemical shifts of K-X-ray absorption edges on copper in different compounds by X-ray absorption spectroscopy (XAS) with Synchrotron radiation

    Science.gov (United States)

    Joseph, D.; Basu, S.; Jha, S. N.; Bhattacharyya, D.

    2012-03-01

    Cu K X-ray absorption edges were measured in compounds such as CuO, Cu(CH3CO2)2, Cu(CO3)2, and CuSO4 where Cu is present in oxidation state of 2+, using the energy dispersive EXAFS beamline at INDUS-2 Synchrotron radiation source at RRCAT, Indore. Energy shifts of ˜4-7 eV were observed for Cu K X-ray absorption edge in the above compounds compared to its value in elemental copper. The difference in the Cu K edge energy shifts in the different compounds having same oxidation state of Cu shows the effect of different chemical environments surrounding the cation in the above compounds. The above chemical effect has been quantitatively described by determining the effective charges on Cu cations in the above compounds.

  2. Chemical shifts of L3 X-ray absorption edges on lead and thallium compounds by DEXAFS using synchrotron radiation source

    Science.gov (United States)

    Kainth, Harpreet Singh; Singh, Ranjit

    2017-09-01

    The L3 absorption edges of 82Pb and 81Tl compounds have been measured using DEXAFS at INDUS-2 Synchrotron radiation source at RRCAT, Indore. The energy shift of ∼(-6 to 2) eV are observed in pre-edge of 82Pb compounds while energy shift varies ∼(-5 to 10) eV in pre-edge and ∼(2-9) eV in post-edge of 81Tl compounds. The chemical effects in both compounds have been described by calculating effective charge using Suchet and Pauling methods. A linear relation is established between chemical effect and effective charge of different compounds for the first time in literature.

  3. Quantification of the push-pull Effect in disubstituted alkynes - Application of occupation quotients π*/π and 13C chemical shift differences ΔδCtbnd C

    Science.gov (United States)

    Kleinpeter, Erich; Klaumünzer, Ute

    2014-09-01

    Structures, 13C chemical shifts, and the occupation quotients of anti-bonding π* and bonding π orbitals of the Ctbnd C triple bond along a series of push-pull alkynes (p)Xsbnd C6H4sbnd C(O)sbnd Ctbnd Csbnd NHsbnd C6H4sbnd Y(p) (X,Y = H, Me, OMe, NMe2, NO2, COMe, COOMe, F, Cl, Br) were computed at the DFT level (B3LYP/6-311G**) of theory. Both the stereochemistry (cis/trans-isomers) by steric twist and the push-pull character by both 13C chemical shift differences (ΔδCtbnd C) and the occupation quotient (π*Ctbnd C/πCtbnd C) were studied; the latter two parameters can be readily employed to precisely quantify the push-pull effect in alkynes.

  4. CHANGES IN THE C, N AND P CYCLES BY THE PREDICTED SALPS-KRILL SHIFT IN THE SOUTHERN OCEAN.

    Directory of Open Access Journals (Sweden)

    Miquel eAlcaraz

    2014-09-01

    Full Text Available The metabolic carbon requirements and excretion rates of three major zooplankton groups in the Southern Ocean were studied in February 2009. The research was conducted in the framework of the ATOS research project as part of the Spanish contribution to the International Polar Year. The objective was to ascertain the possible consequences of the predicted zooplankton shift from krill to salps in the Southern Ocean for the cycling of biogenic carbon and the concentration and stoichiometry of dissolved inorganic nutrients. The carbon respiratory demands and NH4-N and PO4-P excretion rates of < 5 mm size copepods, krill and salps were estimated by incubation experiments. The carbon-specific metabolic rates and N:P metabolic quotients of salps were higher than those of krill (furcilia spp. and adults and copepods, and as expected there was a significant negative relation between average individual zooplankton biomass and their metabolic rates, each metabolic process showing a particular response that lead to different metabolic N:P ratios. The predicted change from krill to salps in the Southern Ocean would encompass not only the substitution of a pivotal group for Antarctic food webs (krill by one with an indifferent trophic role (salps. In a zooplankton community dominated by salps the respiratory carbon demand by zooplankton will significantly increase, and therefore the proportion of primary production that should be allocated to compensate for the global respiratory C-losses of zooplankton. At the same time, the higher production by salps of larger, faster sinking fecal pellets will increase the sequestration rate of biogenic carbon. Similarly, the higher N and P excretion rates of zooplankton and the changes in the N:P stoichiometry of the metabolic products will modify the concentration and proportion of N and P in the nutrient pool, inducing quantitative and qualitative changes on primary producers that will translate to the whole Southern

  5. Prediction of Drug Indications Based on Chemical Interactions and Chemical Similarities

    Directory of Open Access Journals (Sweden)

    Guohua Huang

    2015-01-01

    Full Text Available Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs.

  6. Free magnesium levels in normal human brain and brain tumors: sup 31 P chemical-shift imaging measurements at 1. 5 T

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, J.S.; Vigneron, D.B.; Murphy-Boesch, J.; Nelson, S.J.; Kessler, H.B.; Coia, L.; Curran, W.; Brown, T.R. (Fox Chase Cancer Center, Philadelphia, PA (United States))

    1991-08-01

    The authors have studied a series of normal subjects and patients with brain tumors, by using {sup 31}P three-dimensional chemical shift imaging to obtain localized {sup 31}P spectra of the brain. A significant proportion of brain cytosolic ATP in normal brain is not complexed to Mg{sup 2+}, as indicated by the chemical shift {delta} of the {beta}-P resonance of ATP. The ATP {beta}P resonance position in brain thus is sensitive to changes in intracellular free Mg{sup 2+} concentration and in the proportion of ATP complexed with Mg because this shift lies on the rising portion of the {delta} vs. Mg{sup 2+} titration curve for ATP. They have measured the ATP {beta}-P shift and compared intracellular free Mg{sup 2+} concentration and fractions of free ATP for normal individuals and a limited series of patients with brain tumors. In four of the five spectra obtained from brain tissue containing a substantial proportion of tumor, intracellular free Mg{sup 2+} was increased, and the fraction of free ATP was decreased, compared with normal brain.

  7. Evidence of chemical-potential shift with hole doping in Bi sub 2 Sr sub 2 CaCu sub 2 O sub 8+. delta

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Z.; Dessau, D.S.; Wells, B.O. (Stanford Electronics Laboratory, Stanford University, Stanford, California 94305 (United States)); Olson, C.G. (Ames Laboratory, Iowa State University, Ames, Iowa 50011 (United States)); Mitzi, D.B.; Lombado, L. (Department of Applied Physics, Stanford University, Stanford, California 94305 (United States)); List, R.S.; Arko, A.J. (Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States))

    1991-12-01

    We have performed photoemission studies on high-quality Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8+{delta}} samples with various {delta}. Our results show a clear chemical-potential shift (0.15--0.2 eV) as a function of doping. This result and the existing angle-resolved-photoemission data give a rather standard doping behavior of this compound in its highly doped regime.

  8. Progress in spin dynamics solid-state nuclear magnetic resonance with the application of Floquet-Magnus expansion to chemical shift anisotropy.

    Science.gov (United States)

    Mananga, Eugene Stephane

    2013-01-01

    The purpose of this article is to present an historical overview of theoretical approaches used for describing spin dynamics under static or rotating experiments in solid state nuclear magnetic resonance. The article gives a brief historical overview for major theories in nuclear magnetic resonance and the promising theories. We present the first application of Floquet-Magnus expansion to chemical shift anisotropy when irradiated by BABA pulse sequence.

  9. CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

    Science.gov (United States)

    Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

    2011-03-14

    Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Structure elucidation of the designer drug N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-3-(4-fluorophenyl)-pyrazole-5-carboxamide and the relevance of predicted (13) C NMR shifts - a case study.

    Science.gov (United States)

    Girreser, Ulrich; Rösner, Peter; Vasilev, Andrej

    2016-07-01

    The detailed structure elucidation process of the new cannabimimetic designer drug, N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-3-(4-fluorophenyl)-pyrazole-5-carboxamide, with a highly substituted pyrazole skeleton, using nuclear magnetic resonance (NMR) spectroscopic and mass spectrometric (MS) techniques is described. After a first analysis of the NMR spectra and comparison with 48 possible pyrazole and imidazole structures, a subset of six positional isomeric pyrazoles and six imidazoles remained conceivable. Four substituents of the heterocyclic skeleton were identified: a proton bound to a pyrazole ring carbon atom; a 5-fluoropentyl group; a 4-fluorophenyl substituent; and a carbamoyl group, which is N-substituted with a methyl residue carrying a tert.-butyl and a carbamoyl substituent. The 5-fluoropentyl residue is situated at the nitrogen ring atom. Additional NMR experiments like the (1) H,(13) C HMBC were performed, but due to the small number of signals based on long-range couplings, the comparison of predicted and observed (13) C chemical shifts became necessary. The open access Internet shift prediction programs NMRDB, NMRSHIFTDB2, and CSEARCH were employed for the prediction of (13) C shift values which allowed an efficient and unambiguous structure determination. For the identified N-(1-amino-3,3-dimethyl-1-oxobutan-2-yl)-1-(5-fluoropentyl)-3-(4-fluorophenyl)-pyrazole-5-carboxamide, the best agreement between predicted (13) C shifts and the observed chemical shifts and long-range couplings for the pyrazole ring carbon atoms, with a standard error of about 2 ppm, was found with each of the predictions. For the comparison of measured and predicted chemical shifts model compounds with simple substituents proved helpful. The identified compound is a homologue of AZ-037 which is offered by Internet suppliers. Copyright © 2015 John Wiley & Sons, Ltd.

  11. Homonuclear chemical shift correlation in rotating solids via RN{sup {nu}}{sub n} symmetry-based adiabatic RF pulse schemes

    Energy Technology Data Exchange (ETDEWEB)

    Riedel, Kerstin; Leppert, Joerg; Haefner, Sabine; Ohlenschlaeger, Oliver; Goerlach, Matthias; Ramachandran, Ramadurai [Institut fuer Molekulare Biotechnologie, Abteilung Molekulare Biophysik/NMR-Spektroskopie (Germany)], E-mail: raman@imb-jena.de

    2004-12-15

    The efficacy of RN{sup {nu}}{sub n} symmetry-based adiabatic Zero-Quantum (ZQ) dipolar recoupling schemes for obtaining chemical shift correlation data at moderate magic angle spinning frequencies has been evaluated. RN{sub n}{sup {nu}} sequences generally employ basic inversion elements that correspond to a net 180 deg. rotation about the rotating frame x-axis. It is shown here via numerical simulations and experimental measurements that it is also possible to achieve efficient ZQ dipolar recoupling via RN{sub n}{sup {nu}} schemes employing adiabatic pulses. Such an approach was successfully used for obtaining {sup 1}3C chemical shift correlation spectra of a uniformly labelled sample of (CUG){sub 9}7- a triplet repeat expansion RNA that has been implicated in the neuromuscular disease myotonic dystrophy. An analysis of the {sup 1}3C sugar carbon chemical shifts suggests, in agreement with our recent {sup 1}5N MAS-NMR studies, that this RNA adopts an A-helical conformation.

  12. All-atom Molecular Dynamic Simulations Combined with the Chemical Shifts Study on the Weak Interactions of Ethanol-water System

    Institute of Scientific and Technical Information of China (English)

    ZHANG Rong; LUO San-Lai; WU Wen-Juan

    2008-01-01

    All-atom molecular dynamics(MD)simulation combined with chemical shifts was performed to investigate the interactions over the entire concentration range of the ethanol(EtOH)-water system.The results of the simulation were adopted to explain the NMR experiments by hydrogen bonding analysis.The strong hydrogen bonds and weak C-H…O contacts coexist in the mixtures through the analysis of the radial distribution functions.And the liquid structures in the whole concentration of EtOH-water mixtures can be classified into three regions by the statistic analysis of the hydrogen-bonding network in the MD simulations.Moreover,the chemical shifts of the hydrogen atom are in agreement witb the statistical results of the average number hydrogen bonds in the MD simulations.Interestingly,the excess relative extent Eηrel calculated by the MD simulations and chemical shifts in the EtOH aqueous solutions shows the largest deviation at XEtOH≈0.18.The excess properties present good agreement with the excess enthalpy in the concentration dependence.

  13. CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts.

    Science.gov (United States)

    Hafsa, Noor E; Arndt, David; Wishart, David S

    2015-07-01

    The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I', II' and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0.

  14. Multispecies QSAR modeling for predicting the aquatic toxicity of diverse organic chemicals for regulatory toxicology.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Kumar, Anuj; Mohan, Dinesh

    2014-05-19

    The research aims to develop multispecies quantitative structure-activity relationships (QSARs) modeling tools capable of predicting the acute toxicity of diverse chemicals in various Organization for Economic Co-operation and Development (OECD) recommended test species of different trophic levels for regulatory toxicology. Accordingly, the ensemble learning (EL) approach based classification and regression QSAR models, such as decision treeboost (DTB) and decision tree forest (DTF) implementing stochastic gradient boosting and bagging algorithms were developed using the algae (P. subcapitata) experimental toxicity data for chemicals. The EL-QSAR models were successfully applied to predict toxicities of wide groups of chemicals in other test species including algae (S. obliguue), daphnia, fish, and bacteria. Structural diversity of the selected chemicals and those of the end-point toxicity data of five different test species were tested using the Tanimoto similarity index and Kruskal-Wallis (K-W) statistics. Predictive and generalization abilities of the constructed QSAR models were compared using statistical parameters. The developed QSAR models (DTB and DTF) yielded a considerably high classification accuracy in complete data of model building (algae) species (97.82%, 99.01%) and ranged between 92.50%-94.26% and 92.14%-94.12% in four test species, respectively, whereas regression QSAR models (DTB and DTF) rendered high correlation (R(2)) between the measured and model predicted toxicity end-point values and low mean-squared error in model building (algae) species (0.918, 0.15; 0.905, 0.21) and ranged between 0.575 and 0.672, 0.18-0.51 and 0.605-0.689 and 0.20-0.45 in four different test species. The developed QSAR models exhibited good predictive and generalization abilities in different test species of varied trophic levels and can be used for predicting the toxicities of new chemicals for screening and prioritization of chemicals for regulation.

  15. In silico toxicology: computational methods for the prediction of chemical toxicity

    KAUST Repository

    Raies, Arwa B.

    2016-01-06

    Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.

  16. Predicting rare events in chemical reactions: Application to skin cell proliferation.

    Science.gov (United States)

    Lee, Chiu Fan

    2010-08-01

    In a well-stirred system undergoing chemical reactions, fluctuations in the reaction propensities are approximately captured by the corresponding chemical Langevin equation. Within this context, we discuss in this work how the Kramers escape theory can be used to predict rare events in chemical reactions. As an example, we apply our approach to a recently proposed model on cell proliferation with relevance to skin cancer [P. B. Warren, Phys. Rev. E 80, 030903 (2009)]. In particular, we provide an analytical explanation for the form of the exponential exponent observed in the onset rate of uncontrolled cell proliferation.

  17. Association of symmetrical alkane diols with pyridine: DFT/GIAO calculation of (1) H NMR chemical shifts.

    Science.gov (United States)

    Lomas, John S; Joubert, Laurent; Maurel, François

    2016-05-31

    Proton nuclear magnetic resonance (NMR) shifts of the free diol and of its 1 : 1 and 1 : 2 hydrogen-bonded complexes with pyridine have been computed for five symmetrical alkane diols on the basis of density functional theory, by applying the gauge-including atomic orbital method to geometry-optimized conformers. For certain conformers, intramolecular OH···OH interactions, evidenced by high NMR OH proton shifts, are further enhanced on going from the free diol to the corresponding 1 : 1 diol/pyridine complex. This is confirmed by atoms-in-molecules and non-covalent interaction plots. The computed OH and CH proton shifts for the diol and the two complexes correlate well with values obtained by analysing data from the NMR titration of the diols in benzene against pyridine. Shift values for the diols in neat pyridine are calculated by weighting the shifts of the various protons in the three forms (free diol, 1 : 1 and 1 : 2 diol/pyridine complexes) according to the experimentally determined association constants. The results are in good agreement with those observed, and after empirical scaling, the root mean square difference is 0.18 ppm. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  18. Uncovering symmetry-breaking vector and reliability order for assigning secondary structures of proteins from atomic NMR chemical shifts in amino acids

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Wookyung [Pusan National University, Department of Physics, Center for Proteome Biophysics (Korea, Republic of); Lee, Woonghee; Lee, Weontae [Yonsei University, Department of Biochemistry, Structural Biochemistry and Molecular Biophysics Laboratory (Korea, Republic of); Kim, Suhkmann [Pusan National University, Department of Chemistry, Biochemistry and Bio-NMR Laboratory (Korea, Republic of); Chang, Iksoo, E-mail: iksoochang@pusan.ac.kr [Pusan National University, Department of Physics, Center for Proteome Biophysics (Korea, Republic of)

    2011-12-15

    Unravelling the complex correlation between chemical shifts of {sup 13}C{sup {alpha}}, {sup 13}C{sup {beta}}, {sup 13}C Prime , {sup 1}H{sup {alpha}}, {sup 15}N, {sup 1}H{sup N} atoms in amino acids of proteins from NMR experiment and local structural environments of amino acids facilitates the assignment of secondary structures of proteins. This is an important impetus for both determining the three-dimensional structure and understanding the biological function of proteins. The previous empirical correlation scores which relate chemical shifts of {sup 13}C{sup {alpha}}, {sup 13}C{sup {beta}}, {sup 13}C Prime , {sup 1}H{sup {alpha}}, {sup 15}N, {sup 1}H{sup N} atoms to secondary structures resulted in progresses toward assigning secondary structures of proteins. However, the physical-mathematical framework for these was elusive partly due to both the limited and orthogonal exploration of higher-dimensional chemical shifts of hetero-nucleus and the lack of physical-mathematical understanding underlying those correlation scores. Here we present a simple multi-dimensional hetero-nuclear chemical shift score function (MDHN-CSSF) which captures systematically the salient feature of such complex correlations without any references to a random coil state of proteins. We uncover the symmetry-breaking vector and its reliability order not only for distinguishing different secondary structures of proteins but also for capturing the delicate sensitivity interplayed among chemical shifts of {sup 13}C{sup {alpha}}, {sup 13}C{sup {beta}}, {sup 13}C Prime , {sup 1}H{sup {alpha}}, {sup 15}N, {sup 1}H{sup N} atoms simultaneously, which then provides a straightforward framework toward assigning secondary structures of proteins. MDHN-CSSF could correctly assign secondary structures of training (validating) proteins with the favourable (comparable) Q3 scores in comparison with those from the previous correlation scores. MDHN-CSSF provides a simple and robust strategy for the

  19. Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

    Science.gov (United States)

    Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Oguseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

    2017-03-01

    Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in more cost-effective manner than traditional approaches. This article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents four recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA; adopting a stepwise process to employing predicative toxicology in AA beginning with prioritization of chemicals of concern; leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting trans-disciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. This article is protected by copyright. All rights reserved.

  20. Predicting drug side-effect profiles: a chemical fragment-based approach

    Directory of Open Access Journals (Sweden)

    Stoven Véronique

    2011-05-01

    Full Text Available Abstract Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments and side-effects. This is made possible using sparse canonical correlation analysis (SCCA. In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process.

  1. Stereospecificity of (1) H, (13) C and (15) N shielding constants in the isomers of methylglyoxal bisdimethylhydrazone: problem with configurational assignment based on (1) H chemical shifts.

    Science.gov (United States)

    Afonin, Andrei V; Pavlov, Dmitry V; Ushakov, Igor A; Keiko, Natalia A

    2012-07-01

    In the (13) C NMR spectra of methylglyoxal bisdimethylhydrazone, the (13) C-5 signal is shifted to higher frequencies, while the (13) C-6 signal is shifted to lower frequencies on going from the EE to ZE isomer following the trend found previously. Surprisingly, the (1) H-6 chemical shift and (1) J(C-6,H-6) coupling constant are noticeably larger in the ZE isomer than in the EE isomer, although the configuration around the -CH═N- bond does not change. This paradox can be rationalized by the C-H⋯N intramolecular hydrogen bond in the ZE isomer, which is found from the quantum-chemical calculations including Bader's quantum theory of atoms in molecules analysis. This hydrogen bond results in the increase of δ((1) H-6) and (1) J(C-6,H-6) parameters. The effect of the C-H⋯N hydrogen bond on the (1) H shielding and one-bond (13) C-(1) H coupling complicates the configurational assignment of the considered compound because of these spectral parameters. The (1) H, (13) C and (15) N chemical shifts of the 2- and 8-(CH(3) )(2) N groups attached to the -C(CH(3) )═N- and -CH═N- moieties, respectively, reveal pronounced difference. The ab initio calculations show that the 8-(CH(3) )(2) N group conjugate effectively with the π-framework, and the 2-(CH(3) )(2) N group twisted out from the plane of the backbone and loses conjugation. As a result, the degree of charge transfer from the N-2- and N-8- nitrogen lone pairs to the π-framework varies, which affects the (1) H, (13) C and (15) N shieldings. Copyright © 2012 John Wiley & Sons, Ltd.

  2. In Situ Solid-State Reactions Monitored by X-ray Absorption Spectroscopy: Temperature-Induced Proton Transfer Leads to Chemical Shifts.

    Science.gov (United States)

    Stevens, Joanna S; Walczak, Monika; Jaye, Cherno; Fischer, Daniel A

    2016-10-24

    The dramatic colour and phase alteration with the solid-state, temperature-dependent reaction between squaric acid and 4,4'-bipyridine has been probed in situ with X-ray absorption spectroscopy. The electronic and chemical sensitivity to the local atomic environment through chemical shifts in the near-edge X-ray absorption fine structure (NEXAFS) revealed proton transfer from the acid to the bipyridine base through the change in nitrogen protonation state in the high-temperature form. Direct detection of proton transfer coupled with structural analysis elucidates the nature of the solid-state process, with intermolecular proton transfer occurring along an acid-base chain followed by a domino effect to the subsequent acid-base chains, leading to the rapid migration along the length of the crystal. NEXAFS thereby conveys the ability to monitor the nature of solid-state chemical reactions in situ, without the need for a priori information or long-range order.

  3. A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

    Science.gov (United States)

    Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong

    2014-04-01

    In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

  4. Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

    2013-09-01

    The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Predicting Chemical Reactivity from the Charge Density through Gradient Bundle Analysis: Moving beyond Fukui Functions.

    Science.gov (United States)

    Morgenstern, Amanda; Wilson, Timothy R; Eberhart, M E

    2017-06-08

    Predicting chemical reactivity is a major goal of chemistry. Toward this end, atom condensed Fukui functions of conceptual density functional theory have been used to predict which atom is most likely to undergo electrophilic or nucleophilic attack, providing regioselectivity information. We show that the most probable regions for electrophilic attack within each atom can be predicted through analysis of gradient bundle volumes, a property that depends only on the charge density of the neutral molecules. We also introduce gradient bundle condensed Fukui functions to compare the stereoselectivity information obtained from gradient bundle volume analysis. We demonstrate this method using the test set of molecular fluorine, oxygen, nitrogen, carbon monoxide, and hydrogen cyanide.

  6. From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals

    DEFF Research Database (Denmark)

    Polesel, Fabio; Plósz, Benedek G.; Trapp, Stefan

    2015-01-01

    with freshwater or reclaimed wastewater. Recent research has shown the tendency for these substances to accumulate in food crops. In this study, we developed and applied a simulation tool to predict the fate of three ionizable trace chemicals (triclosan-TCS, furosemide-FUR, ciprofloxacin-CIP) from human...

  7. Comparison of chemical, electrophoretic and in vitro digestion methods for predicting fish meal nutritive quality

    DEFF Research Database (Denmark)

    Bassompierre, M.; Larsen, K.L.; Zimmermann, W.

    1998-01-01

    Chemical, electrophoretic and in vitro digestion methods were compared with respect to predictions given regarding fish meal (FM) quality. FMs were manufactured by mixing a press-cake, with spray dried stickwater concentrate from the identical raw material, thereby providing samples containing...

  8. Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure

    Science.gov (United States)

    Mathews, David H.; Disney, Matthew D.; Childs, Jessica L.; Schroeder, Susan J.; Zuker, Michael; Turner, Douglas H.

    2004-01-01

    A dynamic programming algorithm for prediction of RNA secondary structure has been revised to accommodate folding constraints determined by chemical modification and to include free energy increments for coaxial stacking of helices when they are either adjacent or separated by a single mismatch. Furthermore, free energy parameters are revised to account for recent experimental results for terminal mismatches and hairpin, bulge, internal, and multibranch loops. To demonstrate the applicability of this method, in vivo modification was performed on 5S rRNA in both Escherichia coli and Candida albicans with 1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate, dimethyl sulfate, and kethoxal. The percentage of known base pairs in the predicted structure increased from 26.3% to 86.8% for the E. coli sequence by using modification constraints. For C. albicans, the accuracy remained 87.5% both with and without modification data. On average, for these sequences and a set of 14 sequences with known secondary structure and chemical modification data taken from the literature, accuracy improves from 67% to 76%. This enhancement primarily reflects improvement for three sequences that are predicted with <40% accuracy on the basis of energetics alone. For these sequences, inclusion of chemical modification constraints improves the average accuracy from 28% to 78%. For the 11 sequences with <6% pseudoknotted base pairs, structures predicted with constraints from chemical modification contain on average 84% of known canonical base pairs. PMID:15123812

  9. Prediction of aqueous solubility, vapor pressure and critical micelle concentration for aquatic partitioning of perfluorinated chemicals.

    Science.gov (United States)

    Bhhatarai, Barun; Gramatica, Paola

    2011-10-01

    The majority of perfluorinated chemicals (PFCs) are of increasing risk to biota and environment due to their physicochemical stability, wide transport in the environment and difficulty in biodegradation. It is necessary to identify and prioritize these harmful PFCs and to characterize their physicochemical properties that govern the solubility, distribution and fate of these chemicals in an aquatic ecosystem. Therefore, available experimental data (10-35 compounds) of three important properties: aqueous solubility (AqS), vapor pressure (VP) and critical micelle concentration (CMC) on per- and polyfluorinated compounds were collected for quantitative structure-property relationship (QSPR) modeling. Simple and robust models based on theoretical molecular descriptors were developed and externally validated for predictivity. Model predictions on selected PFCs were compared with available experimental data and other published in silico predictions. The structural applicability domains (AD) of the models were verified on a bigger data set of 221 compounds. The predicted properties of the chemicals that are within the AD, are reliable, and they help to reduce the wide data gap that exists. Moreover, the predictions of AqS, VP, and CMC of most common PFCs were evaluated to understand the aquatic partitioning and to derive a relation with the available experimental data of bioconcentration factor (BCF).

  10. Effects of irritant chemicals on Aedes aegypti resting behavior: is there a simple shift to untreated "safe sites"?

    Directory of Open Access Journals (Sweden)

    Hortance Manda

    2011-07-01

    Full Text Available BACKGROUND: Previous studies have identified the behavioral responses of Aedes aegypti to irritant and repellent chemicals that can be exploited to reduce man-vector contact. Maximum efficacy of interventions based on irritant chemical actions will, however, require full knowledge of variables that influence vector resting behavior and how untreated "safe sites" contribute to overall impact. METHODS: Using a laboratory box assay, resting patterns of two population strains of female Ae. aegypti (THAI and PERU were evaluated against two material types (cotton and polyester at various dark:light surface area coverage (SAC ratio and contrast configuration (horizontal and vertical under chemical-free and treated conditions. Chemicals evaluated were alphacypermethrin and DDT at varying concentrations. RESULTS: Under chemical-free conditions, dark material had significantly higher resting counts compared to light material at all SAC, and significantly increased when material was in horizontal configuration. Cotton elicited stronger response than polyester. Within the treatment assays, significantly higher resting counts were observed on chemical-treated dark material compared to untreated light fabric. However, compared to matched controls, significantly less resting observations were made on chemical-treated dark material overall. Most importantly, resting observations on untreated light material (or "safe sites" in the treatment assay did not significantly increase for many of the tests, even at 25% SAC. Knockdown rates were ≤5% for all assays. Significantly more observations of flying mosquitoes were made in test assays under chemical-treatment conditions as compared to controls. CONCLUSIONS/SIGNIFICANCE: When preferred Ae. aegypti resting sites are treated with chemicals, even at reduced treatment coverage area, mosquitoes do not simply move to safe sites (untreated areas following contact with the treated material. Instead, they become agitated

  11. Transport-induced shifts in condensate dew-point and composition in multicomponent systems with chemical reaction

    Science.gov (United States)

    Rosner, D. E.; Nagarajan, R.

    1985-01-01

    Partial heterogeneous condensation phenomena in multicomponent reacting systems are analyzed taking into consideration the chemical element transport phenomena. It is demonstrated that the dew-point surface temperature in chemically reactive systems is not a purely thermodynamic quantity, but is influenced by the multicomponent diffusion and Soret-mass diffusion phenomena. Several distinct dew-points are shown to exist in such systems and, as a result of transport constraints, the 'sharp' locus between two chemically distinct condensates is systematically moved to a difference mainstream composition.

  12. Development of predictive models for predicting binding affinity of endocrine disrupting chemicals to fish sex hormone-binding globulin.

    Science.gov (United States)

    Liu, Huihui; Yang, Xianhai; Yin, Cen; Wei, Mengbi; He, Xiao

    2017-02-01

    Disturbing the transport process is a crucial pathway for endocrine disrupting chemicals (EDCs) exerting disrupting endocrine function. However, this mechanism has not received enough attention compared with that of hormones receptors and synthetase. Recently, we have explored the interaction between EDCs and sex hormone-binding globulin of human (hSHBG). In this study, interactions between EDCs and sex hormone-binding globulin of eight fish species (fSHBG) were investigated by employing classification methods and quantitative structure-activity relationships (QSAR). In the modeling, the relative binding affinity (RBA) of a chemical with 17β-estradiol binding to fSHBG was selected as the endpoint. Classification models were developed for two fish species, while QSAR models were established for the other six fish species. Statistical results indicated that the models had satisfactory goodness of fit, robustness and predictive ability, and that application domain covered a large number of endogenous and exogenous steroidal and non-steroidal chemicals. Additionally, by comparing the log RBA values, it was found that the same chemical may have different affinities for fSHBG from different fish species, thus species diversity should be taken into account. However, the affinity of fSHBG showed a high correlation for fishes within the same Order (i.e., Salmoniformes, Cypriniformes, Perciformes and Siluriformes), thus the fSHBG binding data for one fish species could be used to extrapolate other fish species in the same Order.

  13. Hydrogen Atomic Positions of O-H···O Hydrogen Bonds in Solution and in the Solid State: The Synergy of Quantum Chemical Calculations with ¹H-NMR Chemical Shifts and X-ray Diffraction Methods.

    Science.gov (United States)

    Siskos, Michael G; Choudhary, M Iqbal; Gerothanassis, Ioannis P

    2017-03-07

    The exact knowledge of hydrogen atomic positions of O-H···O hydrogen bonds in solution and in the solid state has been a major challenge in structural and physical organic chemistry. The objective of this review article is to summarize recent developments in the refinement of labile hydrogen positions with the use of: (i) density functional theory (DFT) calculations after a structure has been determined by X-ray from single crystals or from powders; (ii) ¹H-NMR chemical shifts as constraints in DFT calculations, and (iii) use of root-mean-square deviation between experimentally determined and DFT calculated ¹H-NMR chemical shifts considering the great sensitivity of ¹H-NMR shielding to hydrogen bonding properties.

  14. Thermochemical prediction of chemical form distributions of fission products in LWR mixed oxide fuels

    Energy Technology Data Exchange (ETDEWEB)

    Moriyama, Kouki; Furuya, Hirotaka [Kyushu Univ., Fukuoka (Japan). Faculty of Engineering

    1998-06-01

    Radial distribution of chemical forms of fission products (FPs) in LWR mixed oxide (MOX) fuel pins was theoretically predicted by a thermochemical computer code SOLGASMIX-PV. The amounts of fission products generated in the fuel were calculated by ORIGEN-2 code, and the radial distributions of temperature and oxygen potential were calculated by taking the neutron depression and oxygen redistribution in the fuel into account. A fuel pellet was radially divided into 51 sections and chemical forms of FPs were calculated in each section. The effects of linear heat rating (LHR) and average O/U ratio on radial distribution of chemical form were evaluated. It was found that the radial distribution of chemical forms depends strongly on the LHR and the O/M ratio, and is not proportional to that of burnup. (author)

  15. Soil parameters are key factors to predict metal bioavailability to snails based on chemical extractant data

    Energy Technology Data Exchange (ETDEWEB)

    Pauget, B.; Gimbert, F., E-mail: frederic.gimbert@univ-fcomte.fr; Scheifler, R.; Coeurdassier, M.; Vaufleury, A. de

    2012-08-01

    Although soil characteristics modulate metal mobility and bioavailability to organisms, they are often ignored in the risk assessment of metal transfer. This paper aims to determine the ability of chemical methods to assess and predict cadmium (Cd), lead (Pb) and zinc (Zn) environmental bioavailability to the land snail Cantareus aspersus. Snails were exposed in the laboratory for 28 days to 17 soils from around a former smelter. The soils were selected for their range of pH, organic matter, clay content, and Cd, Pb and Zn concentrations. The influence of soil properties on environmental availability (estimated using HF-HClO{sub 4}, EDTA, CaCl{sub 2}, NH{sub 4}NO{sub 3}, NaNO{sub 3}, free ion activity and total dissolved metal concentration in soil solution) and on environmental bioavailability (modelled using accumulation kinetics) was identified. Among the seven chemical methods, only the EDTA and the total soil concentration can be used to assess Cd and Pb environmental bioavailability to snails (r Superscript-Two {sub adj} = 0.67 and 0.77, respectively). For Zn, none of the chemical methods were suitable. Taking into account the influence of the soil characteristics (pH and CEC) allows a better prediction of Cd and Pb environmental bioavailability (r Superscript-Two {sub adj} = 0.82 and 0.83, respectively). Even though alone none of the chemical methods tested could assess Zn environmental bioavailability to snails, the addition of pH, iron and aluminium oxides allowed the variation of assimilation fluxes to be predicted. A conceptual and practical method to use soil characteristics for risk assessment is proposed based on these results. We conclude that as yet there is no universal chemical method to predict metal environmental bioavailability to snails, and that the soil factors having the greatest impact depend on the metal considered. - Highlights: Black-Right-Pointing-Pointer New approach to identify chemical methods able to predict metal bioavailability

  16. Evaluation of Predicted and Observed Data on Biotransformation of Twenty-Nine Trace Organic Chemicals

    KAUST Repository

    Bertolini, Maria

    2011-07-01

    Trace organic chemicals present in household products, pesticides, pharmaceuticals and personal care products may have adverse ecotoxicological effects once they are released to the environment. These chemicals are usually transported with the sewage to wastewater treatment facilities, where they might be attenuated depending on the degree of treatment applied prior to discharge to receiving streams. This study evaluates the removal performance of 29 trace organic compounds during two different activated sludge treatment systems. Predominant attenuation processes such as biotransformation and sorption for the target compounds were identified. Biotransformation rate constants determined in this study were used to assess removal of compounds from other treatment plants with similar operational conditions, using data gathered from the literature. The commercial software Catalogic was applied to predict environmental fate of chemicals. The software program consisted of four models able to simulate molecular transformations and to generate degradation trees. In order to assess the accuracy of this program in predicting biotransformation, one biodegradation model is used to contrast predicted degradation pathway with metabolic pathways reported in the literature. The predicted outcome was correct for more than 40 percent of the 29 targeted substances, while 38 percent of the chemicals exhibited some degree of lower agreement between predicted and observed pathways. Percent removal data determined for the two treatment facilities was compared with transformation probability output from Catalogic. About 80 percent of the 29 compounds exhibited a good correlation between probability of transformation of the parent compound and percent removal data from the two treatment plants (R2 = 0.82 and 0.9). Based upon findings for 29 trace organic chemicals regarding removal during activated sludge treatment, attacked fragments present in their structures, predicted data from

  17. [Development of Chemical Exposure Prediction Model for Aerobic Sewage Treatment Plant for Biochemical Wastewaters].

    Science.gov (United States)

    Zhou, Lin-jun; Liu, Ji-ning; Shi, Li-li; Feng, Jie; Xu, Yan-hua

    2016-01-15

    Sewage treatment plant (STP) is a key transfer station for chemicals distributed into different environment compartment, and hence models of exposure prediction play a crucial role in the environmental risk assessment and pollution prevention of chemicals. A mass balance model namely Chinese Sewage treatment plant (C-STP(O)) was developed to predict the fate and exposure of chemicals in a conventional sewage treatment plant. The model was expressed as 9 mixed boxes by compartment of air, water, suspended solids, and settled solids. It was based on the minimum input data required on the notification in new chemicals, such as molecular weight, absorption coefficient, vapor pressure, water solubility, ready or inherent biodegradability. The environment conditions ( Temperature = 283 K, wind speed = 2 m x s(-1)) and the classic STP scenario parameters of China, especially the scenario parameters of water quality and sludge properties were adopted in C-STP( 0) model to reflect Chinese characteristics, these parameters were sewage flow of 35 000 m3 x d(-1), influent BOD5 of 0.15 g x L(-1), influent SS of 0.2 kg x m(-3), effluent SS of 0.02 kg x m(-3), BOD5 removal in aerator of 90% sludge density of 1.6 kg x L(3) and organic carbon content of 0.18-0.19. It adopted the fugacity express for mechanism of linear absorption, first-order degradation, Whitman two resistances. An overall interphase transfer constant which was the sum of surface volatilization and stripping was used to assess the volatilization in aerator. The most important and uncertain input value was the biodegradation rate constant, and determination of which required a tier test strategy from ready or inherent biodegradability data to simulate test in STP. An extrapolated criterion of US EPA to derive biodegradation rate constant using the results of ready and inherent biodegradability was compared with that of EU and was recommended. C-STP ( 0 ) was valid to predict the relative emission of volatilization

  18. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

    Science.gov (United States)

    2015-01-01

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

  19. Solid state 13C NMR of unlabeled phosphatidylcholine bilayers: spectral assignments and measurement of carbon-phosphorus dipolar couplings and 13C chemical shift anisotropies.

    Science.gov (United States)

    Sanders, C R

    1993-01-01

    The direct measurement of 13C chemical shift anisotropies (CSA) and 31P-13C dipolar splitting in random dispersions of unlabeled L alpha-phase phosphatidylcholine (PC) has traditionally been difficult because of extreme spectral boradening due to anisotropy. In this study, mixtures of dimyristoyl phosphatidylcholine (DMPC) with three different detergents known to promote the magnetic orientation of DMPC were employed to eliminate the powder-pattern nature of signals without totally averaging out spectral anisotropy. The detergents utilized were CHAPSO, Triton X-100, and dihexanoylphosphatidylcholine (DHPC). Using such mixtures, many of the individual 13C resonances from DMPC were resolved and a number of 13C-31P dipolar couplings were evident. In addition, differing line widths were observed for the components of some dipolar doublets, suggestive of dipolar/chemical shift anisotropy (CSA) relaxation interference effects. Oriented sample resonance assignments were made by varying the CHAPSO or DHPC to DMPC ratio to systematically scale overall bilayer order towards the isotropic limit. In this manner, peaks could be identified based upon extrapolation to their isotropic positions, for which assignments have previously been made (Lee, C.W.B., and R.G. Griffin. 1989. Biophys. J. 55:355-358; Forbes, J., J. Bowers, X. Shan, L. Moran, E. Oldfield, and M.A. Moscarello. 1988. J. Chem. Soc., Faraday, Trans. 1 84:3821-3849). It was observed that the plots of CSA or dipolar coupling versus overall bilayer order obtained from DHPC and CHAPSO titrations were linear. Estimates of the intrinsic dipolar couplings and chemical shift anisotropies for pure DMPC bilayers were made by extrapolating shifts and couplings from the detergent titrations to zero detergent. Both detergent titrations led to similar "intrinsic" CSAs and dipolar couplings. Results extracted from an oriented Triton-DMPC mixture also led to similar estimates for the detergent-free DMPC shifts and couplings. The

  20. 1H NMR spectra. Part 30(+): 1H chemical shifts in amides and the magnetic anisotropy, electric field and steric effects of the amide group.

    Science.gov (United States)

    Abraham, Raymond J; Griffiths, Lee; Perez, Manuel

    2013-03-01

    The (1)H spectra of 37 amides in CDCl(3) solvent were analysed and the chemical shifts obtained. The molecular geometries and conformational analysis of these amides were considered in detail. The NMR spectral assignments are of interest, e.g. the assignments of the formamide NH(2) protons reverse in going from CDCl(3) to more polar solvents. The substituent chemical shifts of the amide group in both aliphatic and aromatic amides were analysed using an approach based on neural network data for near (≤3 bonds removed) protons and the electric field, magnetic anisotropy, steric and for aromatic systems π effects of the amide group for more distant protons. The electric field is calculated from the partial atomic charges on the N.C═O atoms of the amide group. The magnetic anisotropy of the carbonyl group was reproduced with the asymmetric magnetic anisotropy acting at the midpoint of the carbonyl bond. The values of the anisotropies Δχ(parl) and Δχ(perp) were for the aliphatic amides 10.53 and -23.67 (×10(-6) Å(3)/molecule) and for the aromatic amides 2.12 and -10.43 (×10(-6) Å(3)/molecule). The nitrogen anisotropy was 7.62 (×10(-6) Å(3)/molecule). These values are compared with previous literature values. The (1)H chemical shifts were calculated from the semi-empirical approach and also by gauge-independent atomic orbital calculations with the density functional theory method and B3LYP/6-31G(++) (d,p) basis set. The semi-empirical approach gave good agreement with root mean square error of 0.081 ppm for the data set of 280 entries. The gauge-independent atomic orbital approach was generally acceptable, but significant errors (ca. 1 ppm) were found for the NH and CHO protons and also for some other protons.

  1. Chemical shift magnetic resonance imaging in differentiation of benign from malignant vertebral collapse in a rural tertiary care hospital in North India

    Science.gov (United States)

    Mittal, Puneet; Gupta, Ranjana; Mittal, Amit; Joshi, Sandeep

    2016-01-01

    Introduction: Magnetic resonance imaging (MRI) is the modality of the first choice for evaluation of vertebral compression/collapse. Many MRI qualitative features help to differentiate benign from malignant collapse. We conducted this study to look for a quantitative difference in chemical shift values in benign and malignant collapse using dual-echo gradient echo in-phase/out-phase imaging. Materials and Methods: MRI examinations of a total of 38 patients were retrospectively included in the study who had vertebral compression/collapse with marrow edema in which final diagnosis was available at the time of imaging/follow-up. Signal intensity value in the region of abnormal marrow signal and adjacent normal vertebra was measured on in phase/out phase images. Signal intensity ratio (SIR) was measured by dividing signal intensity value on opposite phase images to that on in phase images. SIR was compared in normal vertebrae and benign and malignant vertebral collapse. Results: There were 21 males and 17 females with mean age of 52.4 years (range 28–76 years). Out of total 38 patients, 18 were of benign vertebral collapse and 20 of malignant vertebral collapse. SIR in normal vertebrae was 0.30 ± 0.14, 0.67 ± 0.18 in benign vertebral collapse, and 1.20 ± 0.27 in malignant vertebral collapse with significant difference in SIR of normal vertebrae versus benign collapse (P < 0.01) and in benign collapse versus malignant collapse (P < 0.01). Assuming a cutoff of <0.95 for benign collapse and ≥0.95 for malignant collapse, chemical shift imaging had a sensitivity of 90% and specificity of 94.4%. Conclusion: Chemical shift imaging is a rapid and useful sequence in differentiating benign from malignant vertebral collapse with good specificity and sensitivity.

  2. 平衡电负性与烷烃核磁共振碳谱位移%EQUILIBRIUM ELECTRONEGATIVITY AND 13C NMR CHEMICAL SHIFTS OF ALKANES

    Institute of Scientific and Technical Information of China (English)

    聂长明; 文松年

    2001-01-01

    In this paper, the atomic equilibrium electronegativity in a molecule has been defined and the model of 13C NMR chemical shifts of alkanes has been studied with the atomic equilibrium electronegativity and the structural information parameters NiH(i=0,α,β,γ) and NjC(j=α,β,γ). The results indicate that the 13C NMR chemical shifts of alkanes can be described as follows: CS=-1736.776+755.118AEE+5.2539N0H+1.8837NβH-0.2066NγH By the use of the formula the chemical shifts of 99 carbon atoms are predicated, and the standard error is only 0.9861ppm. The average absolute error is 0.78ppm, The calculated values conform very much to the observed values.%定义了烷烃分子中碳原子的平衡电负性(AEE),用平衡电负性和NiH(i=0,α,β,γ)和NjC(j=α,β,γ)结构信息参数研究了烷烃的13C NMR化学位移模型.结果表明,烷烃13C NMR化学位移(CS)可用下式来定量描述: CS=-1736.776+755.118AEE+5.2539N0H+1.8837NβH-0.2066NγH   用上式估算了99个碳原子的化学位移,标准差为0.9861ppm,平均绝对误差0.78ppm,预测值与实验值十分吻合.

  3. Prediction of novel synthetic pathways for the production of desired chemicals

    Directory of Open Access Journals (Sweden)

    Park Jin

    2010-03-01

    Full Text Available Abstract Background There have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism. Results In the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates. Conclusions It is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.

  4. Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

    Science.gov (United States)

    Bhhatarai, Barun; Gramatica, Paola

    2011-05-01

    Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

  5. Liver steatosis (LS) evaluated through chemical-shift magnetic resonance imaging liver enzymes in morbid obesity; effect of weight loss obtained with intragastric balloon gastric banding.

    Science.gov (United States)

    Folini, Laura; Veronelli, Annamaria; Benetti, Alberto; Pozzato, Carlo; Cappelletti, Marco; Masci, Enzo; Micheletto, Giancarlo; Pontiroli, Antonio E

    2014-01-01

    The aim of this study was to evaluate in morbid obesity clinical and metabolic effects related to weight loss on liver steatosis (LS), measured through chemical-shift magnetic resonance imaging (MRI) and liver enzymes. Forty obese subjects (8 M/32 W; BMI 42.8 ± 7.12 kg/m(2), mean ± SD) were evaluated for LS through ultrasound (US-LS), chemical-shift MRI (MRI-LS), liver enzymes [aspartate aminotransferase (AST), alanine aminotransferase (ALT), γ-glutamyltransferase (GGT), alkaline phosphatase (ALP)], anthropometric parameters [weight, BMI, waist circumference (WC)], lipids, insulin, insulin resistance (HOMA-IR), glycated hemoglobin (HbA1c), oral glucose tolerance test, and body composition [fat mass (FM) and fat-free mass (FFM) at bio-impedance analysis (BIA)]. Anthropometric measures, MRI-LS, BIA, and biochemical parameters were reevaluated 6 months later in 18 subjects undergoing restrictive bariatric approach, i.e., intragastric balloon (BIB, n = 13) or gastric banding (LAGB, n = 5), and in 13 subjects receiving hypocaloric diet. At baseline, US-LS correlates only with MRI-LS, and the latter correlates with ALT, AST, and GGT. After 6 months, subjects undergoing BIB or LAGB had significant changes of BMI, weight, WC, ALT, AST, GGT, ALP, HbA1c, insulin, HOMA-IR, FM, FFM, and MRI-LS. Diet-treated obese subjects had no significant change of any parameter under study; change of BMI, fat mass, and fat-free mass was significantly greater in LAGB/BIB subjects than in diet-treated subjects. Change of MRI-LS showed a significant correlation with changes in weight, BMI, WC, GGT, ALP, and basal MRI-LS. Significant weight loss after BIB or LAGB is associated with decrease in chemical-shift MRI-LS and with reduction in liver enzymes; chemical-shift MRI and liver enzymes allow monitoring of LS in follow-up studies.

  6. Accurate calculation of chemical shifts in highly dynamic H2@C60 through an integrated quantum mechanics/molecular dynamics scheme.

    Science.gov (United States)

    Jiménez-Osés, Gonzalo; García, José I; Corzana, Francisco; Elguero, José

    2011-05-20

    A new protocol combining classical MD simulations and DFT calculations is presented to accurately estimate the (1)H NMR chemical shifts of highly mobile guest-host systems and their thermal dependence. This strategy has been successfully applied for the hydrogen molecule trapped into C(60) fullerene, an unresolved and challenging prototypical case for which experimental values have never been reproduced. The dependence of the final values on the theoretical method and their implications to avoid over interpretation of the obtained results are carefully described.

  7. 1H, 13C and 15N backbone and side-chain chemical shift assignment of the Fyn SH2 domain and its complex with a phosphotyrosine peptide.

    Science.gov (United States)

    Huculeci, Radu; Buts, Lieven; Lenaerts, Tom; van Nuland, Nico A J

    2011-10-01

    SH2 domains are interaction modules uniquely dedicated to recognize phosphotyrosine sites, playing a central role in for instance the activation of tyrosine kinases or phosphatases. Here we report the (1)H, (15)N and (13)C backbone and side-chain chemical shift assignments of the SH2 domain of the human protein tyrosine kinase Fyn, both in its free state and bound to a high-affinity phosphotyrosine peptide corresponding to a specific sequence in the hamster middle-T antigen. The BMRB accession numbers are 17,368 and 17,369, respectively.

  8. Determining hydrogen-bond interactions in spider silk with 1H-13C HETCOR fast MAS solid-state NMR and DFT proton chemical shift calculations.

    Science.gov (United States)

    Holland, Gregory P; Mou, Qiushi; Yarger, Jeffery L

    2013-07-28

    Two-dimensional (2D) (1)H-(13)C heteronuclear correlation (HETCOR) solid-state NMR spectra collected with fast magic angle spinning (MAS) are used in conjunction with density functional theory (DFT) proton chemical shift calculations to determine the hydrogen-bonding strength for ordered β-sheet and disordered 310-helical structures in spider dragline silk. The hydrogen-bond strength is determined to be identical for both structures in spider silk with a 1.83-1.84 Å NH···OC hydrogen-bond distance.

  9. Other compounds isolated from Simira glaziovii and the {sup 1}H and {sup 13}C NMR chemical shift assignments of new 1-epi-castanopsol

    Energy Technology Data Exchange (ETDEWEB)

    Araujo, Marcelo F. de; Vieira, Ivo J. Curcino [Universidade Federal Rural do Rio de Janeiro, Seropedica, RJ (Brazil). Dept. de Quimica; Braz-Filho, Raimundo [Universidade Estadual do Norte Fluminense (UENF), Campos dos Goytacases, RJ (Brazil). Centro de Ciencias Tecnologicas. Lab. de Ciencias Quimicas; Carvalho, Mario G. de, E-mail: mgeraldo@ufrrj.br [Universidade Federal do Rio de Janeiro (NPPN/UFRJ), RJ (Brazil). Centro de Ciencias da Saude. Nucleo de Pesquisa em Produtos Naturais

    2012-07-01

    A new triterpene, 1-epi-castanopsol, besides eleven known compounds: sitosterol, stigmasterol, campesterol, lupeol, lupenone, simirane B, syringaresinol, scopoletin, isofraxidin, 6,7,8-trimethoxycoumarin and harman, were isolated from the wood of Simira glaziovii. The structures of the known compounds were defined by 1D, 2D {sup 1}H, {sup 13}C NMR spectra data analyses and comparison with literature data. The detailed spectral data analyses allowed the definition of the structure of the new 1-epi isomer of castanopsol and performance of {sup 1}H and {sup 13}C NMR chemical shift assignments. (author)

  10. In vitro perturbations of targets in cancer hallmark processes predict rodent chemical carcinogenesis.

    Science.gov (United States)

    Kleinstreuer, Nicole C; Dix, David J; Houck, Keith A; Kavlock, Robert J; Knudsen, Thomas B; Martin, Matthew T; Paul, Katie B; Reif, David M; Crofton, Kevin M; Hamilton, Kerry; Hunter, Ronald; Shah, Imran; Judson, Richard S

    2013-01-01

    Thousands of untested chemicals in the environment require efficient characterization of carcinogenic potential in humans. A proposed solution is rapid testing of chemicals using in vitro high-throughput screening (HTS) assays for targets in pathways linked to disease processes to build models for priority setting and further testing. We describe a model for predicting rodent carcinogenicity based on HTS data from 292 chemicals tested in 672 assays mapping to 455 genes. All data come from the EPA ToxCast project. The model was trained on a subset of 232 chemicals with in vivo rodent carcinogenicity data in the Toxicity Reference Database (ToxRefDB). Individual HTS assays strongly associated with rodent cancers in ToxRefDB were linked to genes, pathways, and hallmark processes documented to be involved in tumor biology and cancer progression. Rodent liver cancer endpoints were linked to well-documented pathways such as peroxisome proliferator-activated receptor signaling and TP53 and novel targets such as PDE5A and PLAUR. Cancer hallmark genes associated with rodent thyroid tumors were found to be linked to human thyroid tumors and autoimmune thyroid disease. A model was developed in which these genes/pathways function as hypothetical enhancers or promoters of rat thyroid tumors, acting secondary to the key initiating event of thyroid hormone disruption. A simple scoring function was generated to identify chemicals with significant in vitro evidence that was predictive of in vivo carcinogenicity in different rat tissues and organs. This scoring function was applied to an external test set of 33 compounds with carcinogenicity classifications from the EPA's Office of Pesticide Programs and successfully (p = 0.024) differentiated between chemicals classified as "possible"/"probable"/"likely" carcinogens and those designated as "not likely" or with "evidence of noncarcinogenicity." This model represents a chemical carcinogenicity prioritization tool supporting targeted

  11. Quantitative and qualitative shifts in defensive metabolites define chemical defense investment during leaf development in Inga, a genus of tropical trees.

    Science.gov (United States)

    Wiggins, Natasha L; Forrister, Dale L; Endara, María-José; Coley, Phyllis D; Kursar, Thomas A

    2016-01-01

    Selective pressures imposed by herbivores are often positively correlated with investments that plants make in defense. Research based on the framework of an evolutionary arms race has improved our understanding of why the amount and types of defenses differ between plant species. However, plant species are exposed to different selective pressures during the life of a leaf, such that expanding leaves suffer more damage from herbivores and pathogens than mature leaves. We hypothesize that this differential selective pressure may result in contrasting quantitative and qualitative defense investment in plants exposed to natural selective pressures in the field. To characterize shifts in chemical defenses, we chose six species of Inga, a speciose Neotropical tree genus. Focal species represent diverse chemical, morphological, and developmental defense traits and were collected from a single site in the Amazonian rainforest. Chemical defenses were measured gravimetrically and by characterizing the metabolome of expanding and mature leaves. Quantitative investment in phenolics plus saponins, the major classes of chemical defenses identified in Inga, was greater for expanding than mature leaves (46% and 24% of dry weight, respectively). This supports the theory that, because expanding leaves are under greater selective pressure from herbivores, they rely more upon chemical defense as an antiherbivore strategy than do mature leaves. Qualitatively, mature and expanding leaves were distinct and mature leaves contained more total and unique metabolites. Intraspecific variation was greater for mature leaves than expanding leaves, suggesting that leaf development is canalized. This study provides a snapshot of chemical defense investment in a speciose genus of tropical trees during the short, few-week period of leaf development. Exploring the metabolome through quantitative and qualitative profiling enables a more comprehensive examination of foliar chemical defense investment.

  12. 13C-NMR chemical shift databases as a quick tool to evaluate structural models of humic substances

    DEFF Research Database (Denmark)

    Nyrop Albers, Christian; Hansen, Poul Erik

    2010-01-01

    Models for humic and fulvic acids are discussed based on 13C liquid state NMR spectra combined with results from elemental analysis and titration studies. The analysis of NMR spectra is based on a full reconstruction of the NMR spectrum done with help of 13C-NMR data bases by adding up chemical s...

  13. [Predictive models for the assessment of occupational exposure to chemicals: a new challenge for employers].

    Science.gov (United States)

    Gromiec, Jan Piotr; Kupczewska-Dobecka, Małgorzata; Jankowska, Agnieszka; Czerczak, Sławomir

    2013-01-01

    Employers are obliged to carry out and document the risk associated with the use of chemical substances. The best but the most expensive method is to measure workplace concentrations of chemicals. At present no "measureless" method for risk assessment is available in Poland, but predictive models for such assessments have been developed in some countries. The purpose of this work is to review and evaluate the applicability of selected predictive methods for assessing occupational inhalation exposure and related risk to check the compliance with Occupational Exposure Limits (OELs), as well as the compliance with REACH obligations. Based on the literature data HSE COSHH Essentials, EASE, ECETOC TRA, Stoffenmanager, and EMKG-Expo-Tool were evaluated. The data on validation of predictive models were also examined. It seems that predictive models may be used as a useful method for Tier 1 assessment of occupational exposure by inhalation. Since the levels of exposure are frequently overestimated, they should be considered as "rational worst cases" for selection of proper control measures. Bearing in mind that the number of available exposure scenarios and PROC categories is limited, further validation by field surveys is highly recommended. Predictive models may serve as a good tool for preliminary risk assessment and selection of the most appropriate risk control measures in Polish small and medium size enterprises (SMEs) providing that they are available in the Polish language. This also requires an extensive training of their future users.

  14. Predictive models for the assessment of occupational exposure to chemicals: A new challenge for employers

    Directory of Open Access Journals (Sweden)

    Jan Piotr Gromiec

    2013-10-01

    Full Text Available Employers are obliged to carry out and document the risk associated with the use of chemical substances. The best but the most expensive method is to measure workplace concentrations of chemicals. At present no "measureless" method for risk assessment is available in Poland, but predictive models for such assessments have been developed in some countries. The purpose of this work is to review and evaluate the applicability of selected predictive methods for assessing occupational inhalation exposure and related risk to check the compliance with Occupational Exposure Limits (OELs, as well as the compliance with REACH obligations. Based on the literature data HSE COSHH Essentials, EASE, ECETOC TRA, Stoffenmanager, and EMKG-Expo-Tool were evaluated. The data on validation of predictive models were also examined. It seems that predictive models may be used as a useful method for Tier 1 assessment of occupational exposure by inhalation. Since the levels of exposure are frequently overestimated, they should be considered as "rational worst cases" for selection of proper control measures. Bearing in mind that the number of available exposure scenarios and PROC categories is limited, further validation by field surveys is highly recommended. Predictive models may serve as a good tool for preliminary risk assessment and selection of the most appropriate risk control measures in Polish small and medium size enterprises (SMEs providing that they are available in the Polish language. This also requires an extensive training of their future users. Med Pr 2013;64(5:699–716

  15. Predictive performance of the Vitrigel‐eye irritancy test method using 118 chemicals

    OpenAIRE

    Yamaguchi, Hiroyuki; KOJIMA Hajime; Takezawa, Toshiaki

    2015-01-01

    Abstract We recently developed a novel Vitrigel‐eye irritancy test (EIT) method. The Vitrigel‐EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time‐dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel‐EIT method by te...

  16. 205Tl Knight and chemical shift in the high- Tc superconductors Tl 2Ba 2CuO 6, Tl 2CaBa 2Cu 2O 8 and Tl 2Ca 2Ba 2Cu 3O 10

    Science.gov (United States)

    Winzek, N.; Hentsch, F.; Mehring, M.; Mattausch, Hj.; Kremer, R.; Simon, A.

    1990-06-01

    We report on the 205Tl NMR (nuclear magnetic resonance) spectra of the title compounds below and above the superconducting transition temperature Tc. The TlO layer NMR spectra are dominated by chemical shifts corresponding to Tl 3+ with a smaller additional positive Knight shift, whereas a “defect line” of Tl replacing Ca in the two and three layer compounds exhibits a large negative Knight shift, which is attributed to O-holes in the CuO 2 layers.

  17. Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae

    DEFF Research Database (Denmark)

    Rønsted, Nina; Symonds, Matthew R. E.; Birkholm, Trine

    2012-01-01

    a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown. Results: We produced a phylogenetic hypothesis......Background: During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer...... of acetylcholinesterase (AChE) and binding to the serotonin reuptake transporter (SERT) are significantly correlated with phylogeny. This has implications for the use of phylogenies to interpret chemical evolution and biosynthetic pathways, to select candidate taxa for lead discovery, and to make recommendations...

  18. Prediction of chemical, physical and sensory data from process parameters for frozen cod using multivariate analysis

    DEFF Research Database (Denmark)

    Bechmann, Iben Ellegaard; Jensen, H.S.; Bøknæs, Niels

    1998-01-01

    Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage. temperature, place of catch, season for catching and state of rigor) were...... varied systematically at two levels. The data obtained were evaluated using the multivariate methods, principal component analysis (PCA) and partial least squares (PLS) regression. The PCA models were used to identify which process parameters were actually most important for the quality of the frozen cod....... PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised...

  19. Predicting the Significance of Injuries Potentially Caused by Non-Lethal Weapons: Tympanic Membrane Rupture (TMR), Permanent Threshold Shift (PTS), and Photothermal Retinal Lesions

    Science.gov (United States)

    2016-06-21

    Membrane Rupture (TMR), Permanent Threshold Shift (PTS), and Photothermal Retinal Lesions Shelley M. Cazares Allison L. King Leon R. Hirsch Jenny R...and Photothermal Retinal Lesions Shelley M. Cazares Allison L. King Leon R. Hirsch Jenny R. Holzer Michael S. Finnin Predicting the Significance... Lesions Shelley Cazares, Allison King, Lee Hirsch, Jenny R. Holzer, Michael Finnin Institute for Defense Analyses 21 June 2016 IDA is a set of

  20. Pasta added with chickpea flour: chemical composition, In vitro starchdigestibility and predicted glycemic index

    OpenAIRE

    2008-01-01

    Pasta was prepared with of durum wheat flour mixed with chickpea flour at two different levels and its chemical composition, in vitro starch digestibility and predicted glycemic index were assessed. Protein, ash, lipid, and dietary fiber content increased while total starch decreased with the chickpea flour level in the composite pasta, all in accordance to the composition of the legume flour. Potentially available starch decreased and resistant starch (RS) increased by adding chickpea flour ...

  1. [Kinetics of chemical reactions for quality prediction of canned fish during storage].

    Science.gov (United States)

    Lukoshkina, M V; Odoeva, G A

    2003-01-01

    Changes in a wide range of quality characteristics of canned fish were studied during storage at different temperatures. A number of biochemical parameters were found, which undergo significant monotonic changes in the course of storage, correlating with organoleptic scores. It was demonstrated that simulation of thermal aging of canned fish, based on the laws of chemical kinetics, may be used for predicting quality changes and determining the shelf life.

  2. Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs

    OpenAIRE

    Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

    2012-01-01

    Objective Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Methods Many studies have utilized either chemical structures or molecular pathways of the drugs to ...

  3. Computer prediction of possible toxic action from chemical structure; the DEREK system.

    Science.gov (United States)

    Sanderson, D M; Earnshaw, C G

    1991-07-01

    1. The development of DEREK, a computer-based expert system (derived from the LHASA chemical synthesis design program) for the qualitative prediction of possible toxic action of compounds on the basis of their chemical structure is described. 2. The system is able to perceive chemical sub-structures within molecules and relate these to a rulebase linking the sub-structures with likely types of toxicity. 3. Structures can be drawn in directly at a computer graphics terminal or retrieved automatically from a suitable in-house database. 4. The system is intended to aid the selection of compounds based on toxicological considerations, or separately to indicate specific toxicological properties to be tested for early in the evaluation of a compound, so saving time, money and some laboratory animals and resources.

  4. Evaluation of the Kinetic Data for Intramolecular 1, x-Hydrogen Shifts in Alkyl Radicals and Structure/Reactivity Predictions from the Carbocyclic Model for the Transition State

    Energy Technology Data Exchange (ETDEWEB)

    Poutsma, Marvin L [ORNL

    2006-01-01

    Experimental and computational kinetic data for the intramolecular 1,x-hydrogen shift in alkyl radicals are compiled in Arrhenius format for x = 2-5. Significant experimental disparity remains, especially for x = 2 and 3. Experimental data for radicals with tert centers or bearing spectator substituents are lacking for all x, and none exist for x = 6. The common use of the strain energy of the unsubstituted (x+1)-carbocycle to coarsely model the activation energy for the 1,x-shift is extended to explore more subtle differences in progressively methyl-substituted systems by use of molecular mechanics estimates of differences in strain between radicals and carbocycles. For x = 5 and 6, a sterically driven increase in E is predicted for shifts in the tert {yields} tert class that apparently runs counter to the behavior of bimolecular hydrogen transfers. In contrast, a sterically driven decrease in E is predicted to result from spectator methyl groups for the prim {yields} prim reaction class for all x. There is no experimental basis to test these predictions; fragmentary computational evidence lends some support to the second but is ambiguous concerning the first. Possible deficiencies in the use of carbocycles as transition state models are discussed.

  5. Predicting chemical kinetics with computational chemistry: is QOO&(H)rarr;HOQO important in fuel ignition?

    Science.gov (United States)

    Green, William H.; Wijaya, Catherina D.; Yelvington, Paul E.; Sumathi, R.

    An overview of predictive chemical kinetics is presented, with an application to the simulation and design of homogeneous charge compression ignition (HCCI) engines. The engine simulations are sensitive to the details of hydroperoxyalkyl (QOOH) radical chemistry, which are only partially understood, and there is a significant discrepancy between the simulations and experiment that limits the usefulness of the simulations. One possible explanation is that QOOH decomposes by other channels not considered in existing combustion chemistry models. Rate constants for one of these neglected channels, the intramolecular radical attack on the QOOH peroxide linkage to form hydroxyalkoxyl (HOQO) radicals, are predicted using quantum chemistry (CBS-QB3), to test whether or not this proposed channel can explain the observed discrepancies in the engine simulations. Although this channel has a significant rate, the competing attack on the other O atom in the peroxide to form a cyclic ether+OH is computed to be an order of magnitude faster, so the HOQO channel does not appear to be fast enough to explain the discrepancy. Definitive judgement on the importance of this reaction channel will require a careful reconsideration of all the coupled chemically activated QOOH reaction channels using modern predictive chemical kinetics software.

  6. Toward structural dynamics: protein motions viewed by chemical shift modulations and direct detection of C'N multiple-quantum relaxation.

    Science.gov (United States)

    Mori, Mirko; Kateb, Fatiha; Bodenhausen, Geoffrey; Piccioli, Mario; Abergel, Daniel

    2010-03-17

    Multiple quantum relaxation in proteins reveals unexpected relationships between correlated or anti-correlated conformational backbone dynamics in alpha-helices or beta-sheets. The contributions of conformational exchange to the relaxation rates of C'N coherences (i.e., double- and zero-quantum coherences involving backbone carbonyl (13)C' and neighboring amide (15)N nuclei) depend on the kinetics of slow exchange processes, as well as on the populations of the conformations and chemical shift differences of (13)C' and (15)N nuclei. The relaxation rates of C'N coherences, which reflect concerted fluctuations due to slow chemical shift modulations (CSMs), were determined by direct (13)C detection in diamagnetic and paramagnetic proteins. In well-folded proteins such as lanthanide-substituted calbindin (CaLnCb), copper,zinc superoxide dismutase (Cu,Zn SOD), and matrix metalloproteinase (MMP12), slow conformational exchange occurs along the entire backbone. Our observations demonstrate that relaxation rates of C'N coherences arising from slow backbone dynamics have positive signs (characteristic of correlated fluctuations) in beta-sheets and negative signs (characteristic of anti-correlated fluctuations) in alpha-helices. This extends the prospects of structure-dynamics relationships to slow time scales that are relevant for protein function and enzymatic activity.

  7. Fractional enrichment of proteins using [2-{sup 13}C]-glycerol as the carbon source facilitates measurement of excited state {sup 13}Cα chemical shifts with improved sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Ahlner, Alexandra; Andresen, Cecilia; Khan, Shahid N. [Linköping University, Division of Chemistry, Department of Physics, Chemistry and Biology (Sweden); Kay, Lewis E. [The University of Toronto, Departments of Molecular Genetics, Biochemistry and Chemistry, One King’s College Circle (Canada); Lundström, Patrik, E-mail: patlu@ifm.liu.se [Linköping University, Division of Chemistry, Department of Physics, Chemistry and Biology (Sweden)

    2015-07-15

    A selective isotope labeling scheme based on the utilization of [2-{sup 13}C]-glycerol as the carbon source during protein overexpression has been evaluated for the measurement of excited state {sup 13}Cα chemical shifts using Carr–Purcell–Meiboom–Gill (CPMG) relaxation dispersion (RD) experiments. As expected, the fractional incorporation of label at the Cα positions is increased two-fold relative to labeling schemes based on [2-{sup 13}C]-glucose, effectively doubling the sensitivity of NMR experiments. Applications to a binding reaction involving an SH3 domain from the protein Abp1p and a peptide from the protein Ark1p establish that accurate excited state {sup 13}Cα chemical shifts can be obtained from RD experiments, with errors on the order of 0.06 ppm for exchange rates ranging from 100 to 1000 s{sup −1}, despite the small fraction of {sup 13}Cα–{sup 13}Cβ spin-pairs that are present for many residue types. The labeling approach described here should thus be attractive for studies of exchanging systems using {sup 13}Cα spin probes.

  8. Evaluation of a rabbit model for osteomyelitis by high field, high resolution imaging using the chemical-shift-specific-slice-selection technique.

    Science.gov (United States)

    Volk, A; Crémieux, A C; Belmatoug, N; Vallois, J M; Pocidalo, J J; Carbon, C

    1994-01-01

    The rabbit model of osteomyelitis introduced by C.W. Norden, based on injection of an infecting solution (Staphylococcus aureus, sodium morrhuate) into the tibia, was studied at 4.7 Tesla with a time-efficient chemical shift selective imaging technique, Chemical Shift Specific Slice Selection (C4S). The evolution of the disease over several weeks was followed on water-selective, fat-selective, and sum images obtained simultaneously with this imaging sequence. Experiments were performed either on different groups of rabbits at different times after infection with subsequent sacrifice of the animal and microbiological analysis of the infected tibia or on the same group of animals imaged several times after infection. Associated analysis of the water and fat selective images revealed marrow modifications very early (Day 5 after inoculation) demonstrating the high sensitivity of the employed imaging technique. Later on, bone modifications were best identified on the sum images. Additional experiments performed on animals injected with a noninfecting solution containing only sodium morrhuate showed however that the sclerosing agent alone can yield images similar to those produced by infection at early stages after inoculation. Therefore, the Norden model would not be suitable for monitoring quantitatively outcome of therapy by magnetic resonance imaging. It is however well adapted for the evaluation and optimization of MRI techniques or protocols intended to detect early changes of bone marrow produced by septic or aseptic infarct.

  9. Final Technical Report: A Paradigm Shift in Chemical Processing: New Sustainable Chemistries for Low-VOC Coatings

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Kenneth F.

    2006-07-26

    The project employed new processes to make emulsion polymers from reduced levels of petroleum-derived chemical feedstocks. Most waterborne paints contain spherical, emulsion polymer particles that serve as the film-forming binder phase. Our goal was to make emulsion polymer particles containing 30 percent feedstock that would function as effectively as commercial emulsions made from higher level feedstock. The processes developed yielded particles maintained their film formation capability and binding capacity while preserving the structural integrity of the particles after film formation. Rohm and Haas Company (ROH) and Archer Daniels Midland Company (ADM) worked together to employ novel polymer binders (ROH) and new, non-volatile, biomass-derived coalescing agents (ADM). The University of Minnesota Department of Chemical Engineering and Material Science utilized its unique microscopy capabilities to characterize films made from the New Emulsion Polymers (NEP).

  10. Optical Red shift in ZnO Nanoflowers Fabricated on Non-Seeded Substrates by Soft Wet Chemical Route

    Science.gov (United States)

    Murali, K. V.; Preetha, K. C.; Ragina, A. J.; Deepa, K.; Remadevi, T. L.

    2011-10-01

    Zinc oxide (ZnO) nanoflowers were fabricated on non-seeded glass substrates by successive ionic layer adsorption and reaction (SILAR) method using different complex agents. Influence of complex agents ammonia, lithium hydroxide and hexamine on the optical properties of the as-synthesized and the samples annealed at 400 °C was studied. Optical red shift was observed in ZnO samples and was analyzed with respect to the complex agents. All samples possessed a steep absorption edge in the wavelength range 375-425 nm. ZnO nanostructures except that synthesized using hexamine have low and steady absorbance and show higher transmittance (70-85%) in the entire visible region. SEM, XRD and EDAX studies confirmed the high surface-to-volume ratio, good optical quality, excellent crystalline nature and purity of the formed and annealed ZnO nanostructures.

  11. Predicting aquatic toxicities of chemical pesticides in multiple test species using nonlinear QSTR modeling approaches.

    Science.gov (United States)

    Basant, Nikita; Gupta, Shikha; Singh, Kunwar P

    2015-11-01

    In this study, we established nonlinear quantitative-structure toxicity relationship (QSTR) models for predicting the toxicities of chemical pesticides in multiple aquatic test species following the OECD (Organization for Economic Cooperation and Development) guidelines. The decision tree forest (DTF) and decision tree boost (DTB) based QSTR models were constructed using a pesticides toxicity dataset in Selenastrum capricornutum and a set of six descriptors. Other six toxicity data sets were used for external validation of the constructed QSTRs. Global QSTR models were also constructed using the combined dataset of all the seven species. The diversity in chemical structures and nonlinearity in the data were evaluated. Model validation was performed deriving several statistical coefficients for the test data and the prediction and generalization abilities of the QSTRs were evaluated. Both the QSTR models identified WPSA1 (weighted charged partial positive surface area) as the most influential descriptor. The DTF and DTB QSTRs performed relatively better than the single decision tree (SDT) and support vector machines (SVM) models used as a benchmark here and yielded R(2) of 0.886 and 0.964 between the measured and predicted toxicity values in the complete dataset (S. capricornutum). The QSTR models applied to six other aquatic species toxicity data yielded R(2) of >0.92 (DTF) and >0.97 (DTB), respectively. The prediction accuracies of the global models were comparable with those of the S. capricornutum models. The results suggest for the appropriateness of the developed QSTR models to reliably predict the aquatic toxicity of chemicals and can be used for regulatory purpose.

  12. A resonance shift prediction based on the Boltzmann-Ehrenfest principle for cylindrical cavities with a rigid sphere

    DEFF Research Database (Denmark)

    Orozco Santillan, Arturo; Cutanda Henríquez, Vicente

    2008-01-01

    devices. It is shown that the use of the Boltzmann-Ehrenfest principle of adiabatic invariance allows the derivation of an expression for the resonance frequency shift in a simpler and more direct way than a method based on a Green’s function reported in the literature. The position of the sphere can...

  13. Analytical predictions for vibration phase shifts along fluid-conveying pipes due to Coriolis forces and imperfections

    DEFF Research Database (Denmark)

    Thomsen, Jon Juel; Dahl, Jonas

    2010-01-01

    Resonant vibrations of a fluid-conveying pipe are investigated, with special consideration to axial shifts in vibration phase accompanying fluid flow and various imperfections. This is relevant for understanding elastic wave propagation in general, and for the design and trouble-shooting of phase...

  14. Color Shift Failure Prediction for Phosphor-Converted White LEDs by Modeling Features of Spectral Power Distribution with a Nonlinear Filter Approach.

    Science.gov (United States)

    Fan, Jiajie; Mohamed, Moumouni Guero; Qian, Cheng; Fan, Xuejun; Zhang, Guoqi; Pecht, Michael

    2017-07-18

    With the expanding application of light-emitting diodes (LEDs), the color quality of white LEDs has attracted much attention in several color-sensitive application fields, such as museum lighting, healthcare lighting and displays. Reliability concerns for white LEDs are changing from the luminous efficiency to color quality. However, most of the current available research on the reliability of LEDs is still focused on luminous flux depreciation rather than color shift failure. The spectral power distribution (SPD), defined as the radiant power distribution emitted by a light source at a range of visible wavelength, contains the most fundamental luminescence mechanisms of a light source. SPD is used as the quantitative inference of an LED's optical characteristics, including color coordinates that are widely used to represent the color shift process. Thus, to model the color shift failure of white LEDs during aging, this paper first extracts the features of an SPD, representing the characteristics of blue LED chips and phosphors, by multi-peak curve-fitting and modeling them with statistical functions. Then, because the shift processes of extracted features in aged LEDs are always nonlinear, a nonlinear state-space model is then developed to predict the color shift failure time within a self-adaptive particle filter framework. The results show that: (1) the failure mechanisms of LEDs can be identified by analyzing the extracted features of SPD with statistical curve-fitting and (2) the developed method can dynamically and accurately predict the color coordinates, correlated color temperatures (CCTs), and color rendering indexes (CRIs) of phosphor-converted (pc)-white LEDs, and also can estimate the residual color life.

  15. Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties.

    Science.gov (United States)

    Yue, Zhenyu; Zhang, Wenna; Lu, Yongming; Yang, Qiaoyue; Ding, Qiuying; Xia, Junfeng; Chen, Yan

    2015-01-01

    Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

  16. Prediction of organ toxicity endpoints by QSAR modeling based on precise chemical-histopathology annotations.

    Science.gov (United States)

    Myshkin, Eugene; Brennan, Richard; Khasanova, Tatiana; Sitnik, Tatiana; Serebriyskaya, Tatiana; Litvinova, Elena; Guryanov, Alexey; Nikolsky, Yuri; Nikolskaya, Tatiana; Bureeva, Svetlana

    2012-09-01

    The ability to accurately predict the toxicity of drug candidates from their chemical structure is critical for guiding experimental drug discovery toward safer medicines. Under the guidance of the MetaTox consortium (Thomson Reuters, CA, USA), which comprised toxicologists from the pharmaceutical industry and government agencies, we created a comprehensive ontology of toxic pathologies for 19 organs, classifying pathology terms by pathology type and functional organ substructure. By manual annotation of full-text research articles, the ontology was populated with chemical compounds causing specific histopathologies. Annotated compound-toxicity associations defined histologically from rat and mouse experiments were used to build quantitative structure-activity relationship models predicting subcategories of liver and kidney toxicity: liver necrosis, liver relative weight gain, liver lipid accumulation, nephron injury, kidney relative weight gain, and kidney necrosis. All models were validated using two independent test sets and demonstrated overall good performance: initial validation showed 0.80-0.96 sensitivity (correctly predicted toxic compounds) and 0.85-1.00 specificity (correctly predicted non-toxic compounds). Later validation against a test set of compounds newly added to the database in the 2 years following initial model generation showed 75-87% sensitivity and 60-78% specificity. General hepatotoxicity and nephrotoxicity models were less accurate, as expected for more complex endpoints.

  17. Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties

    Directory of Open Access Journals (Sweden)

    Zhenyu Yue

    2015-11-01

    Full Text Available Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

  18. Predicting soil sorption coefficients of organic chemicals using a neural network model

    Energy Technology Data Exchange (ETDEWEB)

    Gao, C.; Govind, R. [Univ. of Cincinnati, OH (United States). Dept. of Chemical Engineering; Tabak, H.H. [Environmental Protection Agency, Cincinnati, OH (United States)

    1996-07-01

    The soil/sediment adsorption partition coefficient normalized to organic carbon (K{sub oc}) is extensively used to assess the fate of organic chemicals in hazardous waste sites. Several attempts have been made to estimate the value of K{sub oc} from chemical structure or its parameters. The primary purpose of this study was to develop a nonlinear model for estimating K{sub oc} applicable to polar and nonpolar organics based on artificial neural networks using the octanol/water partition coefficient (K{sub ow}) and water solubility (S). An analytic equation was obtained by starting with a neural network, converging the bias and weight values using the available data on water solubility, octanol/water partition coefficient, and the normalized soil/sediment adsorption partition coefficient, and then combining the equations for each node in the final neural network. For the 119 chemicals in the training set, estimates using the neural network equation lie outside the 2{sigma} region (the standard deviation for the training set, {sigma} = 0.52) for only five chemicals, while all the chemicals in the test set lie within the 2{sigma} region. It was concluded that the neural network equation outperforms the linear models in fitting the K{sub oc} values for the training set and predicting them for the test set.

  19. Developing a predictive model for the chemical composition of soot nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Violi, Angela [Univ. of Michigan, Ann Arbor, MI (United States); Michelsen, Hope [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Hansen, Nils [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Wilson, Kevin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2017-04-07

    In order to provide the scientific foundation to enable technology breakthroughs in transportation fuel, it is important to develop a combustion modeling capability to optimize the operation and design of evolving fuels in advanced engines for transportation applications. The goal of this proposal is to develop a validated predictive model to describe the chemical composition of soot nanoparticles in premixed and diffusion flames. Atomistic studies in conjunction with state-of-the-art experiments are the distinguishing characteristics of this unique interdisciplinary effort. The modeling effort has been conducted at the University of Michigan by Prof. A. Violi. The experimental work has entailed a series of studies using different techniques to analyze gas-phase soot precursor chemistry and soot particle production in premixed and diffusion flames. Measurements have provided spatial distributions of polycyclic aromatic hydrocarbons and other gas-phase species and size and composition of incipient soot nanoparticles for comparison with model results. The experimental team includes Dr. N. Hansen and H. Michelsen at Sandia National Labs' Combustion Research Facility, and Dr. K. Wilson as collaborator at Lawrence Berkeley National Lab's Advanced Light Source. Our results show that the chemical and physical properties of nanoparticles affect the coagulation behavior in soot formation, and our results on an experimentally validated, predictive model for the chemical composition of soot nanoparticles will not only enhance our understanding of soot formation since but will also allow the prediction of particle size distributions under combustion conditions. These results provide a novel description of soot formation based on physical and chemical properties of the particles for use in the next generation of soot models and an enhanced capability for facilitating the design of alternative fuels and the engines they will power.

  20. Prediction of the sorption capacities and affinities of organic chemicals by XAD-7.

    Science.gov (United States)

    Yang, Kun; Qi, Long; Wei, Wei; Wu, Wenhao; Lin, Daohui

    2016-01-01

    Macro-porous resins are widely used as adsorbents for the treatment of organic contaminants in wastewater and for the pre-concentration of organic solutes from water. However, the sorption mechanisms for organic contaminants on such adsorbents have not been systematically investigated so far. Therefore, in this study, the sorption capacities and affinities of 24 organic chemicals by XAD-7 were investigated and the experimentally obtained sorption isotherms were fitted to the Dubinin-Ashtakhov model. Linear positive correlations were observed between the sorption capacities and the solubilities (SW) of the chemicals in water or octanol and between the sorption affinities and the solvatochromic parameters of the chemicals, indicating that the sorption of various organic compounds by XAD-7 occurred by non-linear partitioning into XAD-7, rather than by adsorption on XAD-7 surfaces. Both specific interactions (i.e., hydrogen-bonding interactions) as well as nonspecific interactions were considered to be responsible for the non-linear partitioning. The correlation equations obtained in this study allow the prediction of non-linear partitioning using well-known chemical parameters, namely SW, octanol-water partition coefficients (KOW), and the hydrogen-bonding donor parameter (αm). The effect of pH on the sorption of ionizable organic compounds (IOCs) could also be predicted by combining the correlation equations with additional equations developed from the estimation of IOC dissociation rates. The prediction equations developed in this study and the proposed non-linear partition mechanism shed new light on the selective removal and pre-concentration of organic solutes from water and on the regeneration of exhausted XAD-7 using solvent extraction.

  1. Developing a Semi-Quantitative Occupational Risk Prediction Model for Chemical Exposures and Its Application to a National Chemical Exposure Databank

    Directory of Open Access Journals (Sweden)

    Chiu-Ying Chen

    2013-07-01

    Full Text Available In this study, a semi-quantitative occupational chemical exposure risk prediction model, based on the calculation of exposure hazard indexes, was proposed, corrected, and applied to a national chemical exposure databank. The model comprises one factor used to describe toxicity (i.e., the toxicity index, and two factors used to reflect the exposure potential (i.e., the exposure index and protection deficiency index of workers exposed to chemicals. An expert system was used to correct the above proposed model. By applying the corrected model to data obtained from a national occupational chemical hazard survey program, chemical exposure risks of various manufacturing industries were determined and a national control strategy for the abatement of occupational chemical exposures was proposed. The results of the present study would provide useful information for governmental agencies to allocate their limited resources effectively for reducing chemical exposures of workers.

  2. Prediction of eye irritation from organic chemicals using membrane-interaction QSAR analysis.

    Science.gov (United States)

    Kulkarni, A; Hopfinger, A J; Osborne, R; Bruner, L H; Thompson, E D

    2001-02-01

    Eye irritation potency of a compound or mixture has traditionally been evaluated using the Draize rabbit-eye test (Draize et al., 1944). In order to aid predictions of eye irritation and to explore possible corresponding mechanisms of eye irritation, a methodology termed "membrane-interaction QSAR analysis" (MI-QSAR) has been developed (Kulkarni and Hopfinger 1999). A set of Draize eye-irritation data established by the European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) (Bagley et al., 1992) was used as a structurally diverse training set in an MI-QSAR analysis. Significant QSAR models were constructed based primarily upon aqueous solvation-free energy of the solute and the strength of solute binding to a model phospholipid (DMPC) monolayer. The results demonstrate that inclusion of parameters to model membrane interactions of potentially irritating chemicals provides significantly better predictions of eye irritation for structurally diverse compounds than does modeling based solely on physiochemical properties of chemicals. The specific MI-QSAR models reported here are, in fact, close to the upper limit in both significance and robustness that can be expected for the variability inherent to the eye-irritation scores of the ECETOC training set. The MI-QSAR models can be used with high reliability to classify compounds of low- and high-predicted eye irritation scores. Thus, the models offer the opportunity to reduce animal testing for compounds predicted to fall into these two extreme eye-irritation score sets. The MI-QSAR paradigm may also be applicable to other toxicological endpoints, such as skin irritation, where interactions with cellular membranes are likely.

  3. Armodafinil and modafinil in patients with excessive sleepiness associated with shift work disorder: a pharmacokinetic/pharmacodynamic model for predicting and comparing their concentration-effect relationships.

    Science.gov (United States)

    Darwish, Mona; Bond, Mary; Ezzet, Farkad

    2012-09-01

    Armodafinil, the longer lasting R-isomer of racemic modafinil, improves wakefulness in patients with excessive sleepiness associated with shift work disorder (SWD). Pharmacokinetic studies suggest that armodafinil achieves higher plasma concentrations than modafinil late in a dose interval following equal oral doses. Pooled Multiple Sleep Latency Test (MSLT) data from 2 randomized, double-blind, placebo-controlled trials in 463 patients with SWD, 1 with armodafinil 150 mg/d and 1 with modafinil 200 mg/d (both administered around 2200 h before night shifts), were used to build a pharmacokinetic/pharmacodynamic model. Predicted plasma drug concentrations were obtained by developing and applying a population pharmacokinetic model using nonlinear mixed-effects modeling. Armodafinil 200 mg produced a plasma concentration above the EC(50) (4.6 µg/mL) for 9 hours, whereas modafinil 200 mg did not exceed the EC(50). Consequently, armodafinil produced greater increases in predicted placebo-subtracted MSLT times of 0.5-1 minute (up to 10 hours after dosing) compared with modafinil. On a milligram-to-milligram basis, armodafinil 200 mg consistently increased wakefulness more than modafinil 200 mg, including times late in the 8-hour shift.

  4. Predicting metabolic pathways of small molecules and enzymes based on interaction information of chemicals and proteins.

    Science.gov (United States)

    Gao, Yu-Fei; Chen, Lei; Cai, Yu-Dong; Feng, Kai-Yan; Huang, Tao; Jiang, Yang

    2012-01-01

    Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.

  5. Prediction of drug disposition on the basis of its chemical structure.

    Science.gov (United States)

    Stepensky, David

    2013-06-01

    The chemical structure of any drug determines its pharmacokinetics and pharmacodynamics. Detailed understanding of relationships between the drug chemical structure and individual disposition pathways (i.e., distribution and elimination) is required for efficient use of existing drugs and effective development of new drugs. Different approaches have been developed for this purpose, ranging from statistics-based quantitative structure-property (or structure-pharmacokinetic) relationships (QSPR) analysis to physiologically based pharmacokinetic (PBPK) models. This review critically analyzes currently available approaches for analysis and prediction of drug disposition on the basis of chemical structure. Models that can be used to predict different aspects of disposition are presented, including: (a) value of the individual pharmacokinetic parameter (e.g., clearance or volume of distribution), (b) efficiency of the specific disposition pathway (e.g., biliary drug excretion or cytochrome P450 3A4 metabolism), (c) accumulation in a specific organ or tissue (e.g., permeability of the placenta or accumulation in the brain), and (d) the whole-body disposition in the individual patients. Examples of presented pharmacological agents include "classical" low-molecular-weight compounds, biopharmaceuticals, and drugs encapsulated in specialized drug-delivery systems. The clinical efficiency of agents from all these groups can be suboptimal, because of inefficient permeability of the drug to the site of action and/or excessive accumulation in other organs and tissues. Therefore, robust and reliable approaches for chemical structure-based prediction of drug disposition are required to overcome these limitations. PBPK models are increasingly being used for prediction of drug disposition. These models can reflect the complex interplay of factors that determine drug disposition in a mechanistically correct fashion and can be combined with other approaches, for example QSPR

  6. Correlations of the chemical shift on fasly rotating biological solids by means of NMR spectroscopy; Korrelationen der chemischen Verschiebung an schnell rotierenden biologischen Festkoerpern mittels NMR-Spektroskopie

    Energy Technology Data Exchange (ETDEWEB)

    Herbst, Christian

    2010-04-27

    The basic aim of the thesis was the development and improvement of homo- and heteronuclear feedback sequences for the generation of correlation spectra of the chemical shift. In a first step the possibility of the acquisition of {sup 13}C-{sup 13} correlation spectra of the chemical shift by means of inversion pulses with low RF power factor was studied. Furthermore it was shown that broad-band phase-modulated inversion and universal rotational pulses can be constructed by means of global optimization procedures like the genetic algorithms under regardment of the available RF field strength. By inversion, universal rotational, and 360 pulses as starting values of the optimization efficient homonuclear CN{sub n}{sup {nu}} and RN{sub n}{sup {nu}} mixing sequences as well as heteronuclear RN{sub n}{sup {nu}{sub s},{nu}{sub k}} feedback sequences were generated. The satisfactory power of the numerically optimized sequences was shown by means of the simulation as well by means of correlation experiments of the chemical shift of L-histidine, L-arginine, and the (CUG){sub 97}-RNA. This thesis deals furthermore with the possibility to acquire simultaneously different signals with several receivers. By means of numerically optimized RN{sub n}{sup {nu}{sub s},{nu}{sub k}} pulse sequences both {sup 15}N-{sup 13}C and {sup 13}C-{sup 15}N correlation spectra were simultaneously generated. Furthermore it could be shown that the simultaneous acquisition of 3D-{sup 15}N-{sup 13}C-{sup 13}C and {sup 13}C-{sup 15}N-({sup 1}H)-{sup 1}H correlation spectra is possible. By this in only one measurement process resonance assignments can be met and studies of the global folding performed. A further application of several receivers is the simultaneous acquisition of CHHC, NHHN, NHHC, as well as CHHN spectra. By such experiments it is possible to characterize the hydrogen-bonding pattern and the glycosidic torsion angle {sup {chi}} in RNA. This was demonstrated by means of the (CUG){sub 97

  7. Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

    Science.gov (United States)

    Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

    2017-01-01

    Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

  8. Predicting changes in aquatic toxicity of chemicals resulting from solvent or dispersant use as vehicle.

    Science.gov (United States)

    Kikuchi, Mikio; Nakagawa, Masamitsu; Tone, Suguru; Saito, Hotaka; Niino, Tatsuhiro; Nagasawa, Natsumi; Sawai, Jun

    2016-07-01

    The influence of two vehicles (N,N-dimethylformamide [DMF] as solvent and polyoxyethylene hydrogenated castor oil [HCO-40] as a dispersant) on the acute toxicity of eight hydrophobic chemicals with a non-specific mode of action to Daphnia magna was investigated according to the OECD Guidelines for the Testing of Chemicals, No. 202. An increased 48-h EC50 value for D. magna or reduced toxicity resulting from the addition of HCO-40 to the test medium was observed for five of the eight chemicals examined. Each of eight chemicals was dissolved in water at a concentration of either 10 mg/L or 1.0 mg/L, with or without DMF or HCO-40. Silicone film as a model of a biological membrane was then immersed in each solution, and the concentration of each chemical in the water was monitored until equilibrium was reached for each test substance, after which the adsorbed amount of each chemical was determined. The amounts of p-pentylphenol and four other substances with log Pow (1-octanol/water partition coefficient) values greater than 3.4 adsorbed onto the silicone film decreased with increasing concentrations of HCO-40. However, 3-chloro-4-fluoronitrobenzene and two other substances with log Pow values less than 2.6 demonstrated no changes in adsorption with either increasing HCO-40 concentration or the addition of DMF. The reduced adsorption in the presence of a vehicle on the silicone film correlated closely with changes in toxicity. These results indicate that the methodology developed in this study enables the prediction of changes in toxicity resulting from the addition of vehicles to a test system.

  9. On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculations

    Energy Technology Data Exchange (ETDEWEB)

    Fayet, Guillaume [Laboratoire d' Electrochimie et Chimie Analytique, CNRS UMR-7575, Ecole Nationale Superieure de Chimie de Paris, 11 rue P. et M. Curie, 75231 Paris Cedex 05 (France); Institut National de l' Environnement Industriel et des Risques (INERIS), Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte (France); Rotureau, Patricia, E-mail: patricia.rotureau@ineris.fr [Institut National de l' Environnement Industriel et des Risques (INERIS), Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte (France); Joubert, Laurent; Adamo, Carlo [Laboratoire d' Electrochimie et Chimie Analytique, CNRS UMR-7575, Ecole Nationale Superieure de Chimie de Paris, 11 rue P. et M. Curie, 75231 Paris Cedex 05 (France)

    2009-11-15

    This work presents a new approach to predict thermal stability of nitroaromatic compounds based on quantum chemical calculations and on quantitative structure-property relationship (QSPR) methods. The data set consists of 22 nitroaromatic compounds of known decomposition enthalpy (taken as a macroscopic property related to explosibility) obtained from differential scanning calorimetry. Geometric, electronic and energetic descriptors have been selected and computed using density functional theory (DFT) calculation to describe the 22 molecules. First approach consisted in looking at their linear correlations with the experimental decomposition enthalpy. Molecular weight, electrophilicity index, electron affinity and oxygen balance appeared as the most correlated descriptors (respectively R{sup 2} = 0.76, 0.75, 0.71 and 0.64). Then multilinear regression was computed with these descriptors. The obtained model is a six-parameter equation containing descriptors all issued from quantum chemical calculations. The prediction is satisfactory with a correlation coefficient R{sup 2} of 0.91 and a predictivity coefficient R{sub cv}{sup 2} of 0.84 using a cross validation method.

  10. A systematic prediction of multiple drug-target interactions from chemical, genomic, and pharmacological data.

    Directory of Open Access Journals (Sweden)

    Hua Yu

    Full Text Available In silico prediction of drug-target interactions from heterogeneous biological data can advance our system-level search for drug molecules and therapeutic targets, which efforts have not yet reached full fruition. In this work, we report a systematic approach that efficiently integrates the chemical, genomic, and pharmacological information for drug targeting and discovery on a large scale, based on two powerful methods of Random Forest (RF and Support Vector Machine (SVM. The performance of the derived models was evaluated and verified with internally five-fold cross-validation and four external independent validations. The optimal models show impressive performance of prediction for drug-target interactions, with a concordance of 82.83%, a sensitivity of 81.33%, and a specificity of 93.62%, respectively. The consistence of the performances of the RF and SVM models demonstrates the reliability and robustness of the obtained models. In addition, the validated models were employed to systematically predict known/unknown drugs and targets involving the enzymes, ion channels, GPCRs, and nuclear receptors, which can be further mapped to functional ontologies such as target-disease associations and target-target interaction networks. This approach is expected to help fill the existing gap between chemical genomics and network pharmacology and thus accelerate the drug discovery processes.

  11. Using phylogenetic information and chemical properties to predict species tolerances to pesticides.

    Science.gov (United States)

    Guénard, Guillaume; Carsten von der Ohe, Peter; Carlisle Walker, Steven; Lek, Sovan; Legendre, Pierre

    2014-08-22

    Direct estimation of species' tolerance to pesticides and other toxic organic substances is a combinatorial problem, because of the large number of species-substance pairs. We propose a statistical modelling approach to predict tolerances associated with untested species-substance pairs, by using models fitted to tested pairs. This approach is based on the phylogeny of species and physico-chemical descriptors of pesticides, with both kinds of information combined in a bilinear model. This bilinear modelling approach predicts tolerance in untested species-compound pairs based on the facts that closely related species often respond similarly to toxic compounds and that chemically similar compounds often have similar toxic effects. The three tolerance models (median lethal concentration after 96 h) used up to 25 aquatic animal species and up to nine pesticides (organochlorines, organophosphates and carbamates). Phylogeny was estimated using DNA sequences, while the pesticides were described by their mode of toxic action and their octanol-water partition coefficients. The models explained 77-84% of the among-species variation in tolerance (log10 LC50). In cross-validation, 84-87% of the predicted tolerances for individual species were within a factor of 10 of the observed values. The approach can also be used to model other species response to multivariate stress factors.

  12. Predicted Shifts in Small Mammal Distributions and Biodiversity in the Altered Future Environment of Alaska: An Open Access Data and Machine Learning Perspective.

    Directory of Open Access Journals (Sweden)

    A P Baltensperger

    Full Text Available Climate change is acting to reallocate biomes, shift the distribution of species, and alter community assemblages in Alaska. Predictions regarding how these changes will affect the biodiversity and interspecific relationships of small mammals are necessary to pro-actively inform conservation planning. We used a set of online occurrence records and machine learning methods to create bioclimatic envelope models for 17 species of small mammals (rodents and shrews across Alaska. Models formed the basis for sets of species-specific distribution maps for 2010 and were projected forward using the IPCC (Intergovernmental Panel on Climate Change A2 scenario to predict distributions of the same species for 2100. We found that distributions of cold-climate, northern, and interior small mammal species experienced large decreases in area while shifting northward, upward in elevation, and inland across the state. In contrast, many southern and continental species expanded throughout Alaska, and also moved down-slope and toward the coast. Statewide community assemblages remained constant for 15 of the 17 species, but distributional shifts resulted in novel species assemblages in several regions. Overall biodiversity patterns were similar for both time frames, but followed general species distribution movement trends. Biodiversity losses occurred in the Yukon-Kuskokwim Delta and Seward Peninsula while the Beaufort Coastal Plain and western Brooks Range experienced modest gains in species richness as distributions shifted to form novel assemblages. Quantitative species distribution and biodiversity change projections should help land managers to develop adaptive strategies for conserving dispersal corridors, small mammal biodiversity, and ecosystem functionality into the future.

  13. Numerical Simulations as Tool to Predict Chemical and Radiological Hazardous Diffusion in Case of Nonconventional Events

    Directory of Open Access Journals (Sweden)

    J.-F. Ciparisse

    2016-01-01

    Full Text Available CFD (Computational Fluid Dynamics simulations are widely used nowadays to predict the behaviour of fluids in pure research and in industrial applications. This approach makes it possible to get quantitatively meaningful results, often in good agreement with the experimental ones. The aim of this paper is to show how CFD calculations can help to understand the time evolution of two possible CBRNe (Chemical-Biological-Radiological-Nuclear-explosive events: (1 hazardous dust mobilization due to the interaction between a jet of air and a metallic powder in case of a LOVA (Loss Of Vacuum Accidents that is one of the possible accidents that can occur in experimental nuclear fusion plants; (2 toxic gas release in atmosphere. The scenario analysed in the paper has consequences similar to those expected in case of a release of dangerous substances (chemical or radioactive in enclosed or open environment during nonconventional events (like accidents or man-made or natural disasters.

  14. The second shift reflected in the second generation: do parents' gender roles at home predict children's aspirations?

    Science.gov (United States)

    Croft, Alyssa; Schmader, Toni; Block, Katharina; Baron, Andrew Scott

    2014-07-01

    Gender inequality at home continues to constrain gender equality at work. How do the gender disparities in domestic labor that children observe between their parents predict those children's visions for their future roles? The present research examined how parents' behaviors and implicit associations concerning domestic roles, over and above their explicit beliefs, predict their children's future aspirations. Data from 326 children aged 7 to 13 years revealed that mothers' explicit beliefs about domestic gender roles predicted the beliefs held by their children. In addition, when fathers enacted or espoused a more egalitarian distribution of household labor, their daughters in particular expressed a greater interest in working outside the home and having a less stereotypical occupation. Fathers' implicit gender-role associations also uniquely predicted daughters' (but not sons') occupational preferences. These findings suggest that a more balanced division of household labor between parents might promote greater workforce equality in future generations. © The Author(s) 2014.

  15. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

    Science.gov (United States)

    Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

    2016-03-25

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

  16. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals

    Directory of Open Access Journals (Sweden)

    Huixiao Hong

    2016-03-01

    Full Text Available Endocrine disruptors such as polychlorinated biphenyls (PCBs, diethylstilbestrol (DES and dichlorodiphenyltrichloroethane (DDT are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest and the molecular descriptors calculated from two-dimensional structures by Mold2 software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69% and external validations using 22 chemicals (balanced accuracy of 71%. Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

  17. 利用二元体系的C-H红外光谱推算汽液平衡数据%Prediction of Vapor-Liquid Equilibrium Data from C-H Band Shift of IR Spectra in Some Binary Systems

    Institute of Scientific and Technical Information of China (English)

    朱霄; 姚加; 李浩然; 韩世钧

    2007-01-01

    Prediction of vapor-liquid equilibrium (VLE) is extremely necessary to separate liquid mixture in chemical production, especially when the required experimental data are difficult to measure, or the measurement is not economical. The infinite dilution activities can be used to predict VLE. However, it needs both thc ends of the activities that are difficult to obtain for many systems. In the present study, a new model is proposed for correlating the frequency shift of C-H stretching band of IR spectra over the whole concentration. Investigated mixtures include water/2-propanol, water/N, N-dimethylformamide (DMF), water/methanol, water/ethanol, water/1, 4-dioxane,and water/dimethylsulfoxidc (DMSO) systems. Simultaneous correlations of C-H frequency shift and VLE data arc made. Furthermore, the VLE data were predicted with satisfactory results by the parameters obtained from IR spectra coupled with one of the infinite dilution activity coefficients.

  18. Assigning the stereochemistry of syn and anti β-trimethylsiloxy-α-trimethylsilyl alkanoic acid silyl esters using GIAO 1H NMR chemical shift calculations

    Science.gov (United States)

    Hadj Mohamed, Slim; Trabelsi, Mahmoud; Champagne, Benoît

    2017-08-01

    The stereostructure of β-trimethylsiloxy-α-trimethylsilyl alkanoic acid silyl esters synthesized by Bellassoued et al. [J. Org. Chem. 2001, 66, 5054-5057] using Mukaiyama aldol reaction has been reassigned using density functional theory NMR 1H chemical shifts calculations. It is now concluded that the major diastereoisomer is syn and the minor is anti. Within this assignment, for all silyl esters, δHa(anti) > δHa(syn), δHb(anti) 3JHa-Hb (syn). Since the experimental assignment was based on the stereostructure (E/Z) of the cinnamic acid obtained by elimination of trimethylsilyl 3-phenyl-3-(trimethylsiloxy)-2-(trimethylsilyl)propanoate in the presence of TiCl4 and on the assumption that this elimination is anti stereospecific in acidic medium, one arrives at the conclusion that the elimination of syn and anti β-trimethylsiloxy-α-trimethylsilyl alkanoic acid silyl esters is not anti stereospecific.

  19. Examination of anticipated chemical shift and shape distortion effect on materials commonly used in prosthetic socket fabrication when measured using MRI: a validation study.

    Science.gov (United States)

    Safari, Mohammad Reza; Rowe, Philip; Buis, Arjan

    2013-01-01

    The quality of lower-limb prosthetic socket fit is influenced by shape and volume consistency during the residual limb shape-capturing process (i.e., casting). Casting can be quantified with magnetic resonance imaging (MRI) technology. However, chemical shift artifact and image distortion may influence the accuracy of MRI when common socket/casting materials are used. We used a purpose-designed rig to examine seven different materials commonly used in socket fabrication during exposure to MRI. The rig incorporated glass marker tubes filled with water doped with 1 g/L copper sulfate (CS) and 9 plastic sample vials (film containers) to hold the specific material specimens. The specimens were scanned 9 times in different configurations. The absolute mean difference of the glass marker tube length was 1.39 mm (2.98%) (minimum = 0.13 mm [0.30%], maximum = 5.47 mm [14.03%], standard deviation = 0.89 mm). The absolute shift for all materials was <1.7 mm. This was less than the measurement tolerance of +/-2.18 mm based on voxel (three-dimensional pixel) dimensions. The results show that MRI is an accurate and repeatable method for dimensional measurement when using matter containing water. Additionally, silicone and plaster of paris plus 1 g/L CS do not show a significant shape distortion nor do they interfere with the MRI image of the residual limb.

  20. Examination of anticipated chemical shift and shape distortion effect on materials commonly used in prosthetic socket fabrication when measured using MRI: A validation study

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Safari, PhD

    2013-02-01

    Full Text Available The quality of lower-limb prosthetic socket fit is influenced by shape and volume consistency during the residual limb shape-capturing process (i.e., casting. Casting can be quantified with magnetic resonance imaging (MRI technology. However, chemical shift artifact and image distortion may influence the accuracy of MRI when common socket/casting materials are used. We used a purpose-designed rig to examine seven different materials commonly used in socket fabrication during exposure to MRI. The rig incorporated glass marker tubes filled with water doped with 1 g/L copper sulfate (CS and 9 plastic sample vials (film containers to hold the specific material specimens. The specimens were scanned 9 times in different configurations. The absolute mean difference of the glass marker tube length was 1.39 mm (2.98% (minimum = 0.13 mm [0.30%], maximum = 5.47 mm [14.03%], standard deviation = 0.89 mm. The absolute shift for all materials was <1.7 mm. This was less than the measurement tolerance of +/–2.18 mm based on voxel (three-dimensional pixel dimensions. The results show that MRI is an accurate and repeatable method for dimensional measurement when using matter containing water. Additionally, silicone and plaster of paris plus 1 g/L CS do not show a significant shape distortion nor do they interfere with the MRI image of the residual limb.

  1. Quantum chemical prediction of vibrational spectra of large molecular systems with radical or metallic electronic structure

    Science.gov (United States)

    Nishimoto, Yoshio; Irle, Stephan

    2017-01-01

    Quantum chemical simulation of infrared (IR) and Raman spectra for molecules with open-shell, radical, or multiradical electronic structure represents a major challenge. We report analytic second-order geometrical derivatives of the Mermin free energy for the second-order self-consistent-charge density-functional tight-binding (DFTB2) method with fractional occupation numbers (FONs). This new method is applied to the evaluation of Nsbnd O radical stretching modes in various open-shell molecules and to the prediction of the evolution of IR and Raman spectra of graphene nanoribbons with increasing molecular size.

  2. Predicting corn digestible and metabolizable energy content from its chemical composition in growing pigs

    Institute of Scientific and Technical Information of China (English)

    Quanfeng Li; Jianjun Zang; Dewen Liu; Xiangshu Piao; Changhua Lai; Defa Li

    2014-01-01

    Background:The nutrient composition of corn is variable. To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the energy content of corn and to develop a practical method to accurately estimate the digestible energy (DE) and metabolisable energy (ME) content of individual corn samples for growing pigs. Twenty samples were taken from each of five provinces in China (Jilin, Hebei, Shandong, Liaoning, and Henan) to obtain a range of quality. Results:The DE and ME contents of the 100 corn samples were measured in 35.3 ± 1.92 kg growing pigs (six pigs per corn sample). Sixty corn samples were used to build the prediction model;the remaining forty samples were used to test the suitability of these models. The chemical composition of each corn sample was determined, and the results were used to establish prediction equations for DE or ME content from chemical characteristics. The mean DE and ME content of the 100 samples were 4,053 and 3,923 kcal/kg (dry matter basis), respectively. The physical characteristics were determined, as well, and the results indicated that the bulk weight and 1,000-kernel weight were not associated with energy content. The DE and ME values could be accurately predicted from chemical characteristics. The best fit equations were as follows:DE, kcal/kg of DM=1062.68+(49.72 × EE)+(0.54 × GE)+(9.11 × starch), with R2=0.62, residual standard deviation (RSD)=48 kcal/kg, and P<0.01;ME, kcal/kg of dry matter basis (DM)=671.54+(0.89 × DE)-(5.57 × NDF)-(191.39 × ash), with R2=0.87, RSD=18 kcal/kg, and P<0.01. Conclusion:This experiment confirms the large variation in the energy content of corn, describes the factors that influence this variation, and presents equations based on chemical measurements that may be used to predict the DE and ME content of individual

  3. Prediction of Henry's law constants of triazine derived herbicides from quantum chemical continuum solvation models.

    Science.gov (United States)

    Delgado, Eduardo J; Alderete, Joel B

    2003-01-01

    The Henry's law constants (H) for triazine derived herbicides are calculated using quantum chemical solvation models, SM2, SM3, PCM-DFT, and CPCM-DFT, and their performances are discussed. The results show considerable differences in performance among the different levels of theory. The values of H calculated by the semiempirical methods agree much better with the experimental values than those obtained at the DFT level. The differences are discussed in terms of the different contributions, electrostatic and no-electrostatic, to Gibbs free energy of solvation. In addition, the Henry's law constants of some triazine derived herbicides whose values have not been reported earlier are predicted as well.

  4. Predicting dermal absorption of gas-phase chemicals: transient model development, evaluation, and application

    DEFF Research Database (Denmark)

    Gong, M.; Zhang, Y.; Weschler, Charles J.

    2014-01-01

    A transient model is developed to predict dermal absorption of gas-phase chemicals via direct air-to-skin-to-blood transport under non-steady-state conditions. It differs from published models in that it considers convective mass-transfer resistance in the boundary layer of air adjacent to the skin....... Results calculated with this transient model are in good agreement with the limited experimental results that are available for comparison. The sensitivity of the modeled estimates to key parameters is examined. The model is then used to estimate air-to-skin-to-blood absorption of six phthalate esters...

  5. A simple method for measuring signs of {sup 1}H{sup N} chemical shift differences between ground and excited protein states

    Energy Technology Data Exchange (ETDEWEB)

    Bouvignies, Guillaume; Korzhnev, Dmitry M.; Neudecker, Philipp; Hansen, D. Flemming [University of Toronto, Departments of Molecular Genetics, Biochemistry and Chemistry (Canada); Cordes, Matthew H. J. [University of Arizona, Department of Chemistry and Biochemistry (United States); Kay, Lewis E., E-mail: kay@pound.med.utoronto.c [University of Toronto, Departments of Molecular Genetics, Biochemistry and Chemistry (Canada)

    2010-06-15

    NMR relaxation dispersion spectroscopy is a powerful method for studying protein conformational dynamics whereby visible, ground and invisible, excited conformers interconvert on the millisecond time-scale. In addition to providing kinetics and thermodynamics parameters of the exchange process, the CPMG dispersion experiment also allows extraction of the absolute values of the chemical shift differences between interconverting states, |{Delta}{omega}-tilde|, opening the way for structure determination of excited state conformers. Central to the goal of structural analysis is the availability of the chemical shifts of the excited state that can only be obtained once the signs of {Delta}{omega}-tilde are known. Herein we describe a very simple method for determining the signs of {sup 1}H{sup N} {Delta}{omega}-tilde values based on a comparison of peak positions in the directly detected dimensions of a pair of {sup 1}H{sup N}-{sup 15}N correlation maps recorded at different static magnetic fields. The utility of the approach is demonstrated for three proteins that undergo millisecond time-scale conformational rearrangements. Although the method provides fewer signs than previously published techniques it does have a number of strengths: (1) Data sets needed for analysis are typically available from other experiments, such as those required for measuring signs of {sup 15}N {Delta}{omega}-tilde values, thus requiring no additional experimental time, (2) acquisition times in the critical detection dimension can be as long as necessary and (3) the signs obtained can be used to cross-validate those from other approaches.

  6. Comparison of CT and chemical-shift MRI for differentiating thymoma from non-thymomatous conditions in myasthenia gravis: value of qualitative and quantitative assessment.

    Science.gov (United States)

    Priola, A M; Priola, S M; Gned, D; Giraudo, M T; Fornari, A; Veltri, A

    2016-03-01

    To evaluate the usefulness of computed tomography (CT) and chemical-shift magnetic resonance imaging (MRI) in patients with myasthenia gravis (MG) for differentiating thymoma (THY) from thymic lymphoid hyperplasia (TLH) and normal thymus (NT), and to determine which technique is more accurate. Eighty-three patients with generalised MG who underwent surgery were divided into the TLH/NT group (A; 65 patients) and THY group (B; 24 patients). Differences in qualitative characteristics and quantitative data (CT: radiodensity in Hounsfield units; MRI: signal intensity index [SII]) between groups were tested using Fisher's exact test and Student's t-test. Logistic regression models were estimated for both qualitative and quantitative analyses. At quantitative analysis, discrimination abilities were determined according to the area under the receiver operating characteristic (ROC) curve (AUROC) with computation of optimal cut-off points. The diagnostic accuracies of CT and MRI were compared using McNemar's test. At qualitative assessment, MRI had higher accuracy than CT (96.4%, 80/83 and 86.7%, 72/83, respectively). At quantitative analysis, both the radiodensity and SII were significantly different between groups (pquantitative assessment, the AUROC of the radiodensity in discriminating between groups was 0.904 (optimal cut-off point, 20 HU) with an accuracy of 77.1% (64/83). For MRI, the AUROC of the SII was 0.989 (optimal cut-off point, 7.766%) with an accuracy of 96.4% (80/83), which was significantly higher than CT (pqualitative assessment, accuracy improved both for CT (89.2%, 74/83) and MRI (97.6%, 81/83). Quantitative analysis is useful in evaluating patients with MG and improves the diagnostic accuracy of CT and MRI based on qualitative assessment. Chemical-shift MRI is more reliable than CT in differentiating THYs from non-thymomatous conditions. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  7. A Solid-State 11B NMR and Computational Study of Boron Electric Field Gradient and Chemical Shift Tensors in Boronic Acids and Boronic Esters

    Science.gov (United States)

    2010-01-01

    The results of a solid-state 11B NMR study of a series of 10 boronic acids and boronic esters with aromatic substituents are reported. Boron-11 electric field gradient (EFG) and chemical shift (CS) tensors obtained from analyses of spectra acquired in magnetic fields of 9.4 and 21.1 T are demonstrated to be useful for gaining insight into the molecular and electronic structure about the boron nucleus. Data collected at 21.1 T clearly show the effects of chemical shift anisotropy (CSA), with tensor spans (Ω) on the order of 10−40 ppm. Signal enhancements of up to 2.95 were achieved with a DFS-modified QCPMG pulse sequence. To understand the relationship between the measured tensors and the local structure better, calculations of the 11B EFG and magnetic shielding tensors for these compounds were conducted. The best agreement was found between experimental results and those obtained from GGA revPBE DFT calculations. A positive correlation was found between Ω and the dihedral angle (ϕCCBO), which describes the orientation of the boronic acid/ester functional group relative to an aromatic system bound to boron. The small boron CSA is discussed in terms of paramagnetic shielding contributions as well as diamagnetic shielding contributions. Although there is a region of overlap, both Ω and the 11B quadrupolar coupling constants tend to be larger for boronic acids than for the esters. We conclude that the span is generally the most characteristic boron NMR parameter of the molecular and electronic environment for boronic acids and esters, and show that the values result from a delicate interplay of several competing factors, including hydrogen bonding, the value of ϕCCBO, and the electron-donating or withdrawing substituents bound to the aromatic ring. PMID:20337440

  8. Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae

    DEFF Research Database (Denmark)

    Rønsted, Nina; Symonds, Matthew RE; Birkholm, Trine;

    2012-01-01

    a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown. Results: We produced a phylogenetic hypothesis...... for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae) based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated......Background: During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer...

  9. Discovery of optimal zeolites for challenging separations and chemical transformations using predictive materials modeling

    Science.gov (United States)

    Bai, Peng; Jeon, Mi Young; Ren, Limin; Knight, Chris; Deem, Michael W.; Tsapatsis, Michael; Siepmann, J. Ilja

    2015-01-01

    Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure. To date, 213 framework types have been synthesized and >330,000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modelling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds.

  10. A chemical reactor network for oxides of nitrogen emission prediction in gas turbine combustor

    Science.gov (United States)

    Hao, Nguyen Thanh

    2014-06-01

    This study presents the use of a new chemical reactor network (CRN) model and non-uniform injectors to predict the NOx emission pollutant in gas turbine combustor. The CRN uses information from Computational Fluid Dynamics (CFD) combustion analysis with two injectors of CH4-air mixture. The injectors of CH4-air mixture have different lean equivalence ratio, and they control fuel flow to stabilize combustion and adjust combustor's equivalence ratio. Non-uniform injector is applied to improve the burning process of the turbine combustor. The results of the new CRN for NOx prediction in the gas turbine combustor show very good agreement with the experimental data from Korea Electric Power Research Institute.

  11. A practical approach for predicting retention time shifts due to pressure and temperature gradients in ultra-high-pressure liquid chromatography.

    Science.gov (United States)

    Åsberg, Dennis; Chutkowski, Marcin; Leśko, Marek; Samuelsson, Jörgen; Kaczmarski, Krzysztof; Fornstedt, Torgny

    2017-01-06

    Large pressure gradients are generated in ultra-high-pressure liquid chromatography (UHPLC) using sub-2μm particles causing significant temperature gradients over the column due to viscous heating. These pressure and temperature gradients affect retention and ultimately result in important selectivity shifts. In this study, we developed an approach for predicting the retention time shifts due to these gradients. The approach is presented as a step-by-step procedure and it is based on empirical linear relationships describing how retention varies as a function of temperature and pressure and how the average column temperature increases with the flow rate. It requires only four experiments on standard equipment, is based on straightforward calculations, and is therefore easy to use in method development. The approach was rigorously validated against experimental data obtained with a quality control method for the active pharmaceutical ingredient omeprazole. The accuracy of retention time predictions was very good with relative errors always less than 1% and in many cases around 0.5% (n=32). Selectivity shifts observed between omeprazole and the related impurities when changing the flow rate could also be accurately predicted resulting in good estimates of the resolution between critical peak pairs. The approximations which the presented approach are based on were all justified. The retention factor as a function of pressure and temperature was studied in an experimental design while the temperature distribution in the column was obtained by solving the fundamental heat and mass balance equations for the different experimental conditions. We strongly believe that this approach is sufficiently accurate and experimentally feasible for this separation to be a valuable tool when developing a UHPLC method. After further validation with other separation systems, it could become a useful approach in UHPLC method development, especially in the pharmaceutical industry where

  12. Prediction of monomer reactivity in radical copolymerizations from transition state quantum chemical descriptors

    Directory of Open Access Journals (Sweden)

    Zhengde Tan

    2013-01-01

    Full Text Available In comparison with the Q-e scheme, the Revised Patterns Scheme: the U, V Version (the U-V scheme has greatly improved both its accessibility and its accuracy in interpreting and predicting the reactivity of a monomer in free-radical copolymerizations. Quantitative structure-activity relationship (QSAR models were developed to predict the reactivity parameters u and v of the U-V scheme, by applying genetic algorithm (GA and support vector machine (SVM techniques. Quantum chemical descriptors used for QSAR models were calculated from transition state species with structures C¹H3 - C²HR³• or •C¹H2 - C²H2R³ (formed from vinyl monomers C¹H²=C²HR³ + H•, using density functional theory (DFT, at the UB3LYP level of theory with 6-31G(d basis set. The optimum support vector regression (SVR model of the reactivity parameter u based on Gaussian radial basis function (RBF kernel (C = 10, ε = 10- 5 and γ = 1.0 produced root-mean-square (rms errors for the training, validation and prediction sets being 0.220, 0.326 and 0.345, respectively. The optimal SVR model for v with the RBF kernel (C = 20, ε = 10- 4 and γ = 1.2 produced rms errors for the training set of 0.123, the validation set of 0.206 and the prediction set of 0.238. The feasibility of applying the transition state quantum chemical descriptors to develop SVM models for reactivity parameters u and v in the U-V scheme has been demonstrated.

  13. Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

    Science.gov (United States)

    The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

  14. Quantitative Structure-Use Relationship Model Predictions to evaluate Tox21 Chemicals as Functional Substitutes and Candidate Alternatives

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset provides a prediction for all Tox21 chemicals with available QSUR descriptors across all 41 valid QSUR models developed with FUse. This dataset is...

  15. Predicting dissolved oxygen concentration using kernel regression modeling approaches with nonlinear hydro-chemical data.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

    2014-05-01

    Kernel function-based regression models were constructed and applied to a nonlinear hydro-chemical dataset pertaining to surface water for predicting the dissolved oxygen levels. Initial features were selected using nonlinear approach. Nonlinearity in the data was tested using BDS statistics, which revealed the data with nonlinear structure. Kernel ridge regression, kernel principal component regression, kernel partial least squares regression, and support vector regression models were developed using the Gaussian kernel function and their generalization and predictive abilities were compared in terms of several statistical parameters. Model parameters were optimized using the cross-validation procedure. The proposed kernel regression methods successfully captured the nonlinear features of the original data by transforming it to a high dimensional feature space using the kernel function. Performance of all the kernel-based modeling methods used here were comparable both in terms of predictive and generalization abilities. Values of the performance criteria parameters suggested for the adequacy of the constructed models to fit the nonlinear data and their good predictive capabilities.

  16. Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization.

    Science.gov (United States)

    Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P; Simeonov, Anton

    2016-01-26

    Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼ 10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure-activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing.

  17. Discovery of optimal zeolites for challenging separations and chemical conversions through predictive materials modeling

    Science.gov (United States)

    Siepmann, J. Ilja; Bai, Peng; Tsapatsis, Michael; Knight, Chris; Deem, Michael W.

    2015-03-01

    Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure and the type or location of active sites. To date, 213 framework types have been synthesized and >330000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol beyond the ethanol/water azeotropic concentration in a single separation step from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modeling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds. Financial support from the Department of Energy Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-12ER16362 is gratefully acknowledged.

  18. Improving N(6)-methyladenosine site prediction with heuristic selection of nucleotide physical-chemical properties.

    Science.gov (United States)

    Zhang, Ming; Sun, Jia-Wei; Liu, Zi; Ren, Ming-Wu; Shen, Hong-Bin; Yu, Dong-Jun

    2016-09-01

    N(6)-methyladenosine (m(6)A) is one of the most common and abundant post-transcriptional RNA modifications found in viruses and most eukaryotes. m(6)A plays an essential role in many vital biological processes to regulate gene expression. Because of its widespread distribution across the genomes, the identification of m(6)A sites from RNA sequences is of significant importance for better understanding the regulatory mechanism of m(6)A. Although progress has been achieved in m(6)A site prediction, challenges remain. This article aims to further improve the performance of m(6)A site prediction by introducing a new heuristic nucleotide physical-chemical property selection (HPCS) algorithm. The proposed HPCS algorithm can effectively extract an optimized subset of nucleotide physical-chemical properties under the prescribed feature representation for encoding an RNA sequence into a feature vector. We demonstrate the efficacy of the proposed HPCS algorithm under different feature representations, including pseudo dinucleotide composition (PseDNC), auto-covariance (AC), and cross-covariance (CC). Based on the proposed HPCS algorithm, we implemented an m(6)A site predictor, called M6A-HPCS, which is freely available at http://csbio.njust.edu.cn/bioinf/M6A-HPCS. Experimental results over rigorous jackknife tests on benchmark datasets demonstrated that the proposed M6A-HPCS achieves higher success rates and outperforms existing state-of-the-art sequence-based m(6)A site predictors.

  19. Predicting physical-chemical properties of compounds from molecular structures by recursive neural networks.

    Science.gov (United States)

    Bernazzani, Luca; Duce, Celia; Micheli, Alessio; Mollica, Vincenzo; Sperduti, Alessandro; Starita, Antonina; Tiné, Maria Rosaria

    2006-01-01

    In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result, a completely new approach to quantitative structure-activity relationship/quantitative structure-property relationship (QSPR/QSAR) analysis is obtained. An original representation of the molecular structures has been developed accounting for both the occurrence of specific atoms/groups and the topological relationships among them. Gibbs free energy of solvation in water, Delta(solv)G degrees , has been chosen as a benchmark for the model. The different approaches proposed in the literature for the prediction of this property have been reconsidered from a general perspective. The advantages of RecNN as a suitable tool for the automatization of fundamental parts of the QSPR/QSAR analysis have been highlighted. The RecNN model has been applied to the analysis of the Delta(solv)G degrees in water of 138 monofunctional acyclic organic compounds and tested on an external data set of 33 compounds. As a result of the statistical analysis, we obtained, for the predictive accuracy estimated on the test set, correlation coefficient R = 0.9985, standard deviation S = 0.68 kJ mol(-1), and mean absolute error MAE = 0.46 kJ mol(-1). The inherent ability of RecNN to abstract chemical knowledge through the adaptive learning process has been investigated by principal components analysis of the internal representations computed by the network. It has been found that the model recognizes the chemical compounds on the

  20. Fluid Shifts

    Science.gov (United States)

    Stenger, M. B.; Hargens, A. R.; Dulchavsky, S. A.; Arbeille, P.; Danielson, R. W.; Ebert, D. J.; Garcia, K. M.; Johnston, S. L.; Laurie, S. S.; Lee, S. M. C.; Liu, J.; Macias, B.; Martin, D. S.; Minkoff, L.; Ploutz-Snyder, R.; Ribeiro, L. C.; Sargsyan, A.; Smith, S. M.

    2017-01-01

    Introduction. NASA's Human Research Program is focused on addressing health risks associated with long-duration missions on the International Space Station (ISS) and future exploration-class missions beyond low Earth orbit. Visual acuity changes observed after short-duration missions were largely transient, but now more than 50 percent of ISS astronauts have experienced more profound, chronic changes with objective structural findings such as optic disc edema, globe flattening and choroidal folds. These structural and functional changes are referred to as the visual impairment and intracranial pressure (VIIP) syndrome. Development of VIIP symptoms may be related to elevated intracranial pressure (ICP) secondary to spaceflight-induced cephalad fluid shifts, but this hypothesis has not been tested. The purpose of this study is to characterize fluid distribution and compartmentalization associated with long-duration spaceflight and to determine if a relation exists with vision changes and other elements of the VIIP syndrome. We also seek to determine whether the magnitude of fluid shifts during spaceflight, as well as any VIIP-related effects of those shifts, are predicted by the crewmember's pre-flight status and responses to acute hemodynamic manipulations, specifically posture changes and lower body negative pressure. Methods. We will examine a variety of physiologic variables in 10 long-duration ISS crewmembers using the test conditions and timeline presented in the figure below. Measures include: (1) fluid compartmentalization (total body water by D2O, extracellular fluid by NaBr, intracellular fluid by calculation, plasma volume by CO rebreathe, interstitial fluid by calculation); (2) forehead/eyelids, tibia, and calcaneus tissue thickness (by ultrasound); (3) vascular dimensions by ultrasound (jugular veins, cerebral and carotid arteries, vertebral arteries and veins, portal vein); (4) vascular dynamics by MRI (head/neck blood flow, cerebrospinal fluid

  1. Zebrafish whole-adult-organism chemogenomics for large-scale predictive and discovery chemical biology.

    Directory of Open Access Journals (Sweden)

    Siew Hong Lam

    2008-07-01

    Full Text Available The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly, is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated aromatic hydrocarbons [P(HAHs] and estrogenic compounds (ECs, we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR and estrogen receptor (ER agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology.

  2. Predicting physico-chemical properties of polychlorinated diphenyl ethers (PCDEs):potential persistent organic pollutants (POPs)

    Institute of Scientific and Technical Information of China (English)

    HUANG Jun; YU Gang; YANG Xi; ZHANG Zu-lin

    2004-01-01

    Polychlorinated diphenyl ethers(PCDEs) have received more and more concerns as a category of potentialpersistent organic pollutants( POPs). Modeling its environmental fate and exposure assessment require a number offundamental physico-chemical properties. However, the experimental data are currently limited due to the difficulty inanalysis caused by the complexity of PCDE congeners. As an alternative, the quantitative structure propertyrelationship(QSPR) approach could be used. In this paper, twelve kinds of molecular connectivity indices(MCIs) ofall 209 possible molecular structure patterns of PCDEs were calculated. Based on 106 PCDEs with three observedphysico-chemical properties-vapour pressure(PoL), aqueous solubility(Sw) and n-octanol/water(Kow) and theirMCIs data, a series of QSPR equations were established using multiple linear regression(MLR) method. As aresult, three equations with best performance were selected mainly from the view of high regression coefficient(R)and low standard error( SE). All of them showed significant relationship and high accuracy. With these equationsthe properties of other 103 patterns of PCDEs without the reported observed values were predicted. Furthermore,three partition properties for PCDE congeners-Henry' s Law constants(H), partition coefficients between gas/water(Kgw) and gas/n-octanol ( Kgo ) were calculated according to the internal relationship among these six properties.These observed and predicted values, in contrast with the criteria listed in the Stockholm treaty about POPs whichhas been signed by more than ninety countries in May 2001, illustrated that most of PCDEs congeners are potentialpersistent organic pollutants. As all descriptors/predictors are derived just from the molecular structure itself andwithout the import of any empirical parameters, this method is impersonal and promising for the estimation ofphysico-chemical properties of PCDEs.

  3. Measurement of the principal values of the chemical-shift tensors of overlapping protonated and unprotonated carbons with the 2D-SUPER technique and dipolar dephasing (DD-SUPER)

    Science.gov (United States)

    Liu, Wei; Wang, Wei D.; Wang, Wei; Bai, Shi; Dybowski, Cecil

    2010-09-01

    A modified 2D-SUPER technique is demonstrated to allow independent measurement of the principal values of the chemical-shift tensors of overlapping protonated and unprotonated carbons. The insertion of a dipolar-dephasing period into the sequence causes loss of signal from protonated carbons. The spectrum obtained with this modification allows one to determine the principal values of the unprotonated carbons with high precision. Subsequent fitting of the usual 2D-SUPER spectrum, with the chemical-shift parameters of the unprotonated carbons fixed, gives the parameters of the overlapped resonances of the protonated carbons. As an example, we report the determination of the 13C chemical-shift parameters of the carbons of form II of piroxicam. The experimental results are compared with those obtained from calculations using the DFT/GIAO method. Potential applications of this method are discussed.

  4. Characterization of mu s-ms dynamics of proteins using a combined analysis of N-15 NMR relaxation and chemical shift: Conformational exchange in plastocyanin induced by histidine protonations

    DEFF Research Database (Denmark)

    Hass, M. A. S.; Thuesen, Marianne Hallberg; Christensen, Hans Erik Mølager

    2004-01-01

    An approach is presented that allows a detailed, quantitative characterization of conformational exchange processes in proteins on the mus-ms time scale. The approach relies on a combined analysis of NMR relaxation rates and chemical shift changes and requires that the chemical shift...... of the exchanging species can be determined independently of the relaxation rates. The applicability of the approach is demonstrated by a detailed analysis of the conformational exchange processes previously observed in the reduced form of the blue copper protein, plastocyanin from the cyanobacteria Anabaena...... quantitatively by the correlation between the R-ex terms and the corresponding chemical shift differences of the exchanging species. By this approach, the R-ex terms of N-15 nuclei belonging to contiguous regions in the protein could be assigned to the same exchange process. Furthermore, the analysis...

  5. High-Throughput Predictive Approaches to Evaluating Chemicals in Food Contact Materials: Migration, Exposure, and Alternatives Identification

    Science.gov (United States)

    This is a presentation describing CSS research on HT predictive methods to modeling exposure and predicting functional substitutes. It will be presented at a forum co-sponsored by the State of California and UC Berekeley on evaluation of chemical alternatives for food contact ch...

  6. Prediction of chemical composition and peroxide value in unground pet foods by near-infrared spectroscopy.

    Science.gov (United States)

    De Marchi, M; Righi, F; Meneghesso, M; Manfrin, D; Ricci, R

    2016-12-20

    The massive development of the pet food industry in recent years has lead to the formulation of hundreds of canine and feline complete extruded foods with the objective of meeting both the needs of the animals and numerous demands from pet owners. In the meantime, highly variable raw material compositions and the industry's new production techniques oblige manufacturers to monitor all phases of the extrusion process closely in order to ensure the targeted composition and quality of the products. This study aimed at evaluating the potential of infrared technology (visible and near-infrared spectrophotometer; 570-1842 nm) in predicting the chemical composition and peroxide value (PV) of unground commercial extruded dog foods. Six hundred and forty-nine commercial extruded dog foods were collected. For each product, an unground aliquot was analysed by infrared instrument while a second aliquot was sent to a laboratory for proximate analysis and PV quantification. The wide range of extruded dog food typologies included in the study was responsible for the wide variability observed within each nutritional trait, especially crude fibre and ash. The mean value of the 208 pet foods sampled for PV quantification was 17.49 mEq O2 /kg fat (min 2.2 and max 94.10 mEq O2 /kg fat). The coefficients of determination in cross-validation of NIRS prediction models were 0.77, 0.97, 0.83, 0.86, 0.78 and 0.94 for moisture, crude protein, crude fat, crude fibre, ash and nitrogen-free extract (NFE) respectively. PV prediction was less precise, as demonstrated by the coefficient of determination in cross-validation (0.66). The results demonstrated the potential of NIRS in predicting chemical composition in unground samples, with lower accuracy for moisture and ash, while PV prediction models suggest use for screening purposes only. Journal of Animal Physiology and Animal Nutrition © 2016 Blackwell Verlag GmbH.

  7. Predictive elution window stretching and shifting as a generic search strategy for automated method development for liquid chromatography.

    Science.gov (United States)

    Tyteca, Eva; Liekens, Anuschka; Clicq, David; Fanigliulo, Ameriga; Debrus, Benjamin; Rudaz, Serge; Guillarme, Davy; Desmet, Gert

    2012-09-18

    We report on the possibilities of a new method development (MD) algorithm that searches the chromatographic parameter space by systematically shifting and stretching the elution window over different parts of the time-axis. In this way, the search automatically focuses on the most promising areas of the solution space. Since only the retention properties of the first and last eluting compounds of the sample need to be (approximately) known, the algorithm can be directly applied to samples with unknown composition, and the proposed solutions are not sensitive to any modeling errors. The search efficiency of the algorithm has been evaluated on an extensive set of random-generated in silico samples covering a broad range of different retention properties. Compared to a pure grid-based search, the algorithm could reduce the number of missed components by 50% and more. The algorithm has also been applied to solve three different real-world separation problems from the pharmaceutical industry. All problems could be successfully solved in a very short time (order of 12 h of instrument time).

  8. Prediction of Effective Drug Combinations by Chemical Interaction, Protein Interaction and Target Enrichment of KEGG Pathways

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2013-01-01

    Full Text Available Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1 chemical interaction between drugs, (2 protein interactions between drugs’ targets, and (3 target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations.

  9. Concurrent Increases and Decreases in Local Stability and Conformational Heterogeneity in Cu, Zn Superoxide Dismutase Variants Revealed by Temperature-Dependence of Amide Chemical Shifts.

    Science.gov (United States)

    Doyle, Colleen M; Rumfeldt, Jessica A; Broom, Helen R; Sekhar, Ashok; Kay, Lewis E; Meiering, Elizabeth M

    2016-03-08

    The chemical shifts of backbone amide protons in proteins are sensitive reporters of local structural stability and conformational heterogeneity, which can be determined from their readily measured linear and nonlinear temperature-dependences, respectively. Here we report analyses of amide proton temperature-dependences for native dimeric Cu, Zn superoxide dismutase (holo pWT SOD1) and structurally diverse mutant SOD1s associated with amyotrophic lateral sclerosis (ALS). Holo pWT SOD1 loses structure with temperature first at its periphery and, while having extremely high global stability, nevertheless exhibits extensive conformational heterogeneity, with ∼1 in 5 residues showing evidence for population of low energy alternative states. The holo G93A and E100G ALS mutants have moderately decreased global stability, whereas V148I is slightly stabilized. Comparison of the holo mutants as well as the marginally stable immature monomeric unmetalated and disulfide-reduced (apo(2SH)) pWT with holo pWT shows that changes in the local structural stability of individual amides vary greatly, with average changes corresponding to differences in global protein stability measured by differential scanning calorimetry. Mutants also exhibit altered conformational heterogeneity compared to pWT. Strikingly, substantial increases as well as decreases in local stability and conformational heterogeneity occur, in particular upon maturation and for G93A. Thus, the temperature-dependence of amide shifts for SOD1 variants is a rich source of information on the location and extent of perturbation of structure upon covalent changes and ligand binding. The implications for potential mechanisms of toxic misfolding of SOD1 in disease and for general aspects of protein energetics, including entropy-enthalpy compensation, are discussed.

  10. The effects of librations on the 13C chemical shift and 2H electric field gradient tensors in β-calcium formate

    Science.gov (United States)

    Hallock, Kevin J.; Lee, Dong Kuk; Ramamoorthy, A.

    2000-12-01

    The magnitudes and orientations of the principal elements of the 13C chemical shift anisotropy (CSA) tensor in the molecular frame of the formate ion in β-calcium formate is determined using one-dimensional dipolar-shift spectroscopy. The magnitudes of the principal elements of the 13C CSA tensor are σ11C=104 ppm, σ22C=179 ppm, and σ33C=233 ppm. The least shielding element of the 13C CSA tensor, σ33C, is found to be collinear with the C-H bond. The temperature dependence of the 13C CSA and the 2H quadrupole coupling tensors in β-calcium formate are analyzed for a wide range of temperature (173-373 K). It was found that the span of the 13C CSA and the magnitude of the 2H quadrupole coupling interactions are averaged with the increasing temperature. The experimental results also show that the 2H quadrupole coupling tensor becomes more asymmetric with increasing temperature. A librational motion about the σ22C axis of the 13C CSA tensor is used to model the temperature dependence of the 13C CSA tensor. The temperature dependence of the mean-square amplitude of the librational motion is found to be =2.6×10-4(T) rad2 K-1. The same librational motion also accounts for the temperature-dependence of the 2H quadrupole coupling tensor after the relative orientation of the 13C CSA and 2H electric field gradient tensors are taken into account. Reconsideration of the results of a previous study found that the librational motion, not the vibrational motion, accounts for an asymmetry in the 1H-13C dipolar coupling tensor of α-calcium formate at room temperature.

  11. A lanthanide complex with dual biosensing properties: CEST (chemical exchange saturation transfer) and BIRDS (biosensor imaging of redundant deviation in shifts) with europium DOTA-tetraglycinate.

    Science.gov (United States)

    Coman, Daniel; Kiefer, Garry E; Rothman, Douglas L; Sherry, A Dean; Hyder, Fahmeed

    2011-12-01

    Responsive contrast agents (RCAs) composed of lanthanide(III) ion (Ln3R) complexes with a variety of1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate (DOTA4S) derivatives have shown great potential as molecular imaging agents for MR. A variety of LnDOTA–tetraamide complexes have been demonstrated as RCAs for molecular imaging using chemical exchange saturation transfer (CEST). The CEST method detects proton exchange between bulk water and any exchangeable sites on the ligand itself or an inner sphere of bound water that is shifted by a paramagnetic Ln3R ion bound in the core of the macrocycle. It has also been shown that molecular imaging is possible when the RCA itself is observed (i.e. not its effect on bulk water) using a method called biosensor imaging of redundant deviation in shifts (BIRDS). The BIRDS method utilizes redundant information stored in the nonexchangeable proton resonances emanating from the paramagnetic RCA for ambient factors such as temperature and/or pH.Thus, CEST and BIRDS rely on exchangeable and nonexchangeable protons, respectively, for biosensing. We posited that it would be feasible to combine these two biosensing features into the same RCA (i.e. dual CEST and BIRDS properties). A complex between europium(III) ion (Eu3R) and DOTA–tetraglycinate [DOTA–(gly)S4] was used to demonstrate that its CEST characteristics are preserved, while its BIRDS properties are also detectable. The in vitro temperature sensitivity of EuDOTA–(gly)S4 was used to show that qualitative MR contrast with CEST can be calibrated using quantitative MR mapping with BIRDS, thereby enabling quantitative molecular imaging at high spatial resolution.

  12. Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, J Lynn

    2014-06-24

    Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have

  13. Comparison of qualitative and quantitative evaluation of diffusion-weighted MRI and chemical-shift imaging in the differentiation of benign and malignant vertebral body fractures.

    Science.gov (United States)

    Geith, Tobias; Schmidt, Gerwin; Biffar, Andreas; Dietrich, Olaf; Dürr, Hans Roland; Reiser, Maximilian; Baur-Melnyk, Andrea

    2012-11-01

    The objective of our study was to compare the diagnostic value of qualitative diffusion-weighted imaging (DWI), quantitative DWI, and chemical-shift imaging in a single prospective cohort of patients with acute osteoporotic and malignant vertebral fractures. The study group was composed of patients with 26 osteoporotic vertebral fractures (18 women, eight men; mean age, 69 years; age range, 31 years 6 months to 86 years 2 months) and 20 malignant vertebral fractures (nine women, 11 men; mean age, 63.4 years; age range, 24 years 8 months to 86 years 4 months). T1-weighted, STIR, and T2-weighted sequences were acquired at 1.5 T. A DW reverse fast imaging with steady-state free precession (PSIF) sequence at different delta values was evaluated qualitatively. A DW echo-planar imaging (EPI) sequence and a DW single-shot turbo spin-echo (TSE) sequence at different b values were evaluated qualitatively and quantitatively using the apparent diffusion coefficient. Opposed-phase sequences were used to assess signal intensity qualitatively. The signal loss between in- and opposed-phase images was determined quantitatively. Two-tailed Fisher exact test, Mann-Whitney test, and receiver operating characteristic analysis were performed. Sensitivities, specificities, and accuracies were determined. Qualitative DW-PSIF imaging (delta = 3 ms) showed the best performance for distinguishing between benign and malignant fractures (sensitivity, 100%; specificity, 88.5%; accuracy, 93.5%). Qualitative DW-EPI (b = 50 s/mm(2) [p = 1.00]; b = 250 s/mm(2) [p = 0.50]) and DW single-shot TSE imaging (b = 100 s/mm(2) [p = 1.00]; b = 250 s/mm(2) [p = 0.18]; b = 400 s/mm(2) [p = 0.18]; b = 600 s/mm(2) [p = 0.39]) did not indicate significant differences between benign and malignant fractures. DW-EPI using a b value of 500 s/mm(2) (p = 0.01) indicated significant differences between benign and malignant vertebral fractures. Quantitative DW-EPI (p = 0.09) and qualitative opposed-phase imaging (p = 0

  14. ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

    Science.gov (United States)

    Kayala, Matthew A; Baldi, Pierre

    2012-10-22

    Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of Reaction

  15. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Gupta, Shikha

    2014-03-15

    Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the

  16. Chemical constituents of Ottonia corcovadensis Miq. from Amazon forest: {sup 1}H and {sup 13}C chemical shift assignments; Constituintes quimicos de Ottonia corcovadensis Miq. da floresta Amazonica - atribuicao dos deslocamentos quimicos dos atomos de hidrogenio e carbono

    Energy Technology Data Exchange (ETDEWEB)

    Facundo, Valdir A. [Rondonia Univ., Porto Velho, RO (Brazil). Dept. de Quimica; Morais, Selene M. [Ceara Univ., Fortaleza, CE (Brazil). Dept. de Quimica e Fisica; Braz Filho, Raimundo [Universidade Estadual do Norte Fluminense (UENF), Campos dos Goytacases, RJ (Brazil). Setor de Quimica de Produtos Naturais. Lab. de Ciencias Quimicas. Setor de Quimica de Produtos Naturais]. E-mail: braz@uenf.br

    2004-02-01

    In an ethanolic extract of leaves of Ottonia corcovadensis (Piperaceae) were identified sixteen terpenoids of essential oil and the three flavonoids 3',4',5,5',7-penta methoxyflavone (1), 3',4',5,7-tetra methoxyflavone (2) and 5-hydroxy-3',4',5',7-tetra methoxyflavone (3) and cafeic acid (4). Two amides (5 and 6) were isolated from an ethanolic extract of the roots. The structures were established by spectral analysis, meanly NMR (1D and 2D) and mass spectra. Extensive NMR analysis was also used to complete {sup 1}H and {sup 13}C chemical shift assignments of the flavonoids and amides. The components of the essential oil were identified by computer library search, retention indices and visual interpretation of mass spectra. (author)

  17. Quantized beam shifts

    CERN Document Server

    Kort-Kamp, W J M; Dalvit, D A R

    2015-01-01

    We predict quantized Imbert-Fedorov, Goos-H\\"anchen, and photonic spin Hall shifts for light beams impinging on a graphene-on-substrate system in an external magnetic field. In the quantum Hall regime the Imbert-Fedorov and photonic spin Hall shifts are quantized in integer multiples of the fine structure constant $\\alpha$, while the Goos- H\\"anchen ones in multiples of $\\alpha^2$. We investigate the influence on these shifts of magnetic field, temperature, and material dispersion and dissipation. An experimental demonstration of quantized beam shifts could be achieved at terahertz frequencies for moderate values of the magnetic field.

  18. Visualization and prediction of porosity in roller compacted ribbonswith near infrared chemical imaging (NIR-CI)

    DEFF Research Database (Denmark)

    Khorasani, Milad Rouhi; Amigo Rubio, Jose Manuel; Sonnergaard, Jørn

    2015-01-01

    The porosity of roller compacted ribbon is recognized as an important critical quality attribute which has a huge impact on the final product quality. The purpose of this study was to investigate the use of near-infrared chemical imaging (NIR-CI) for porosity estimation of ribbons produced...... at different roll pressures. Two off-line methods were utilized as reference methods. The relatively fast method (oil absorption) was comparable with the more time-consuming mercury intrusion method (R2 = 0.98). Therefore, the oil method was selected as the reference off line method. It was confirmed by both...... reference methods that ribbons compressed at a higher pressure resulted in a lower mean porosity. Using NIR-CI in combination with multivariate data analysis it was possible to visualize and predict the porosity distribution of the ribbons. This approach is considered important for process monitoring...

  19. Standard Guide for Predicting Radiation-Induced Transition Temperature Shift in Reactor Vessel Materials, E706 (IIF)

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2002-01-01

    1.1 This guide presents a method for predicting reference transition temperature adjustments for irradiated light-water cooled power reactor pressure vessel materials based on Charpy V-notch 30-ftlbf (41-J) data. Radiation damage calculative procedures have been developed from a statistical analysis of an irradiated material database that was available as of May 2000. The embrittlement correlation used in this guide was developed using the following variables: copper and nickel contents, irradiation temperature, and neutron fluence. The form of the model was based on current understanding for two mechanisms of embrittlement: stable matrix damage (SMD) and copper-rich precipitation (CRP); saturation of copper effects (for different weld materials) was included. This guide is applicable for the following specific materials, copper, nickel, and phosphorus contents, range of irradiation temperature, and neutron fluence based on the overall database: 1.1.1 MaterialsA 533 Type B Class 1 and 2, A302 Grade B, A302 G...

  20. Predicting coal ash fusion temperature based on its chemical composition using ACO-BP neural network

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Y.P.; Wu, M.G.; Qian, J.X. [Institute of Industrial Control Technology, College of Info Science and Engineering, Zhejiang University, Hangzhou 310027 (China)

    2007-02-15

    Coal ash fusion temperature is important to boiler designers and operators of power plants. Fusion temperature is determined by the chemical composition of coal ash, however, their relationships are not precisely known. A novel neural network, ACO-BP neural network, is used to model coal ash fusion temperature based on its chemical composition. Ant colony optimization (ACO) is an ecological system algorithm, which draws its inspiration from the foraging behavior of real ants. A three-layer network is designed with 10 hidden nodes. The oxide contents consist of the inputs of the network and the fusion temperature is the output. Data on 80 typical Chinese coal ash samples were used for training and testing. Results show that ACO-BP neural network can obtain better performance compared with empirical formulas and BP neural network. The well-trained neural network can be used as a useful tool to predict coal ash fusion temperature according to the oxide contents of the coal ash. (author)

  1. Predicting the carcinogenicity of chemicals in humans from rodent bioassay data

    Energy Technology Data Exchange (ETDEWEB)

    Goodman, G. (Harvard Univ., Cambridge, MA (United States) School of Public Health, Boston, MA (United States)); Wilson, R. (Harvard Univ., Cambridge, MA (United States))

    1991-08-01

    Regulatory agencies currently rely on rodent carcinogenicity bioassay data to predict whether or not a given chemical poses a carcinogenic threat to humans. The authors argue that it is always more useful to know a chemical's carcinogenic potency (with confidence limits) than to be able to say only qualitatively that it has been found to be a carcinogen. In a typical bioassay, a chemical is administered to groups of 50 to 100 rodents at the highest feasible level (the maximum tolerated dose) and rarely at less than 1/10 this dose in order to maximize the statistical significance of any increase in tumors that might result. Recently, much experimental work has focused on the mechanisms by which site-specific toxicity arising from chronic administration at the maximum tolerated dose may lead to carcinogenicity. Extrapolation of high-dose results to low dose does not take into consideration the possibility of a threshold dose, below which the carcinogenic potency is much lower or even zero. Threshold dose-response phenomena may be much more relevant to the etiology of cancer in the rodent bioassays than was earlier realized; if so, there is an even greater need for establishing dose-dependent potency estimates. The emphasis of this review is in the interspecies comparison of high-dose potencies. The qualitative and quantitative comparison of carcinogenicities between mice and rats and between rodents and humans is reviewed and discussed. They conclude that there is a good qualitative (yes/no) correlation for both the rat/mouse and the rodent/human comparison.

  2. Scan time reduction in {sup 23}Na-Magnetic Resonance Imaging using the chemical shift imaging sequence. Evaluation of an iterative reconstruction method

    Energy Technology Data Exchange (ETDEWEB)

    Weingaertner, Sebastian; Konstandin, Simon; Schad, Lothar R. [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Wetterling, Friedrich [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Dublin Univ. (Ireland) Trinity Inst. of Neuroscience; Fatar, Marc [Heidelberg Univ., Mannheim (Germany). Dept. of Neurology; Neumaier-Probst, Eva [Heidelberg Univ., Mannheim (Germany). Dept. of Neuroradiology

    2015-07-01

    To evaluate potential scan time reduction in {sup 23}Na-Magnetic Resonance Imaging with the chemical shift imaging sequence (CSI) using undersampled data of high-quality datasets, reconstructed with an iterative constrained reconstruction, compared to reduced resolution or reduced signal-to-noise ratio. CSI {sup 23}Na-images were retrospectively undersampled and reconstructed with a constrained reconstruction scheme. The results were compared to conventional methods of scan time reduction. The constrained reconstruction scheme used a phase constraint and a finite object support, which was extracted from a spatially registered {sup 1}H-image acquired with a double-tuned coil. The methods were evaluated using numerical simulations, phantom images and in-vivo images of a healthy volunteer and a patient who suffered from cerebral ischemic stroke. The constrained reconstruction scheme showed improved image quality compared to a decreased number of averages, images with decreased resolution or circular undersampling with weighted averaging for any undersampling factor. Brain images of a stroke patient, which were reconstructed from three-fold undersampled k-space data, resulted in only minor differences from the original image (normalized root means square error < 12%) and an almost identical delineation of the stroke region (mismatch < 6%). The acquisition of undersampled {sup 23}Na-CSI images enables up to three-fold scan time reduction with improved image quality compared to conventional methods of scan time saving.

  3. Reproducibility of Intra- and Inter-scanner Measurements of Liver Fat Using Complex Confounder-corrected Chemical Shift Encoded MRI at 3.0 Tesla

    Science.gov (United States)

    Wu, Bing; Han, Wei; Li, Zhenhong; Zhao, Yonghua; Ge, Mingmei; Guo, Xueqing; Wu, Xinhuai

    2016-01-01

    The purpose of this study was to prospectively evaluate the reproducibility of the proton density fat-fraction (PDFF) of the liver using the IDEAL algorithm, a quantitative confounder-corrected chemical-shift-encoded MRI method. Data were obtained from 15 volunteers on four different days. The first and the third examinations were conducted on scanner one with one-week intervals, while the second and the fourth tests were performed on scanner two with same time interval. For each test, two MR scans were performed, one before and one after a meal. Regions-of-interest measurements were manually calculated to estimate the PDFF in the right and left lobes on the PDFF images. Reproducibility was measured using the intra-class correlation coefficient (ICC). The ICCs of the PDFF in the right and left lobes were 0.935 and 0.878, respectively. The intra-scanner ICCs of the right lobe before and after a meal or at a one-week interval were 0.924 and 0.953, respectively. The inter-scanner ICCs of PDFF the next day and at a one-week interval were 0.920 and 0.864, respectively. The PDFF of liver derived from IDEAL demonstrated high intra- and inter-scanner measurement reproducibility. The PDFF of the right lobe before a meal was more reproducible than after-meal measurements. PMID:26763303

  4. Determination of the Orientation and Dynamics of Ergosterol in Model Membranes Using Uniform 13C Labeling and Dynamically Averaged 13C Chemical Shift Anisotropies as Experimental Restraints

    Science.gov (United States)

    Soubias, O.; Jolibois, F.; Massou, S.; Milon, A.; Réat, V.

    2005-01-01

    A new strategy was established to determine the average orientation and dynamics of ergosterol in dimyristoylphosphatidylcholine model membranes. It is based on the analysis of chemical shift anisotropies (CSAs) averaged by the molecular dynamics. Static 13C CSA tensors were computed by quantum chemistry, using the gauge-including atomic-orbital approach within Hartree-Fock theory. Uniformly 13C-labeled ergosterol was purified from Pichia pastoris cells grown on labeled methanol. After reconstitution into dimyristoylphosphatidylcholine lipids, the complete 1H and 13C assignment of ergosterol's resonances was performed using a combination of magic-angle spinning two-dimensional experiments. Dynamically averaged CSAs were determined by standard side-band intensity analysis for isolated 13C resonances (C3 and ethylenic carbons) and by off-magic-angle spinning experiments for other carbons. A set of 18 constraints was thus obtained, from which the sterol's molecular order parameter and average orientation could be precisely defined. The validity of using computed CSAs in this strategy was verified on cholesterol model systems. This new method allowed us to quantify ergosterol's dynamics at three molar ratios: 16 mol % (Ld phase), 30 mol % (Lo phase), and 23 mol % (mixed phases). Contrary to cholesterol, ergosterol's molecular diffusion axis makes an important angle (14°) with the inertial axis of the rigid four-ring system. PMID:15923221

  5. ¹³C solid-state NMR analysis of the most common pharmaceutical excipients used in solid drug formulations, Part I: Chemical shifts assignment.

    Science.gov (United States)

    Pisklak, Dariusz Maciej; Zielińska-Pisklak, Monika Agnieszka; Szeleszczuk, Łukasz; Wawer, Iwona

    2016-04-15

    Solid-state NMR is an excellent and useful method for analyzing solid-state forms of drugs. In the (13)C CP/MAS NMR spectra of the solid dosage forms many of the signals originate from the excipients and should be distinguished from those of active pharmaceutical ingredient (API). In this work the most common pharmaceutical excipients used in the solid drug formulations: anhydrous α-lactose, α-lactose monohydrate, mannitol, sucrose, sorbitol, sodium starch glycolate type A and B, starch of different origin, microcrystalline cellulose, hypromellose, ethylcellulose, methylcellulose, hydroxyethylcellulose, sodium alginate, magnesium stearate, sodium laurilsulfate and Kollidon(®) were analyzed. Their (13)C CP/MAS NMR spectra were recorded and the signals were assigned, employing the results (R(2): 0.948-0.998) of GIPAW calculations and theoretical chemical shifts. The (13)C ssNMR spectra for some of the studied excipients have not been published before while for the other signals in the spectra they were not properly assigned or the assignments were not correct. The results summarize and complement the data on the (13)C ssNMR analysis of the most common pharmaceutical excipients and are essential for further NMR studies of API-excipient interactions in the pharmaceutical formulations.

  6. 129Xe NMR chemical shift in Xe@C60 calculated at experimental conditions: essential role of the relativity, dynamics, and explicit solvent.

    Science.gov (United States)

    Standara, Stanislav; Kulhánek, Petr; Marek, Radek; Straka, Michal

    2013-08-15

    The isotropic (129)Xe nuclear magnetic resonance (NMR) chemical shift (CS) in Xe@C60 dissolved in liquid benzene was calculated by piecewise approximation to faithfully simulate the experimental conditions and to evaluate the role of different physical factors influencing the (129)Xe NMR CS. The (129)Xe shielding constant was obtained by averaging the (129)Xe nuclear magnetic shieldings calculated for snapshots obtained from the molecular dynamics trajectory of the Xe@C60 system embedded in a periodic box of benzene molecules. Relativistic corrections were added at the Breit-Pauli perturbation theory (BPPT) level, included the solvent, and were dynamically averaged. It is demonstrated that the contribution of internal dynamics of the Xe@C60 system represents about 8% of the total nonrelativistic NMR CS, whereas the effects of dynamical solvent add another 8%. The dynamically averaged relativistic effects contribute by 9% to the total calculated (129)Xe NMR CS. The final theoretical value of 172.7 ppm corresponds well to the experimental (129)Xe CS of 179.2 ppm and lies within the estimated errors of the model. The presented computational protocol serves as a prototype for calculations of (129)Xe NMR parameters in different Xe atom guest-host systems. Copyright © 2013 Wiley Periodicals, Inc.

  7. Cross correlations between {sup 13}C-{sup 1}H dipolar interactions and {sup 15}N chemical shift anisotropy in nucleic acids

    Energy Technology Data Exchange (ETDEWEB)

    Ravindranathan, Sapna [Institut de Chimie Moleculaire et Biologique, Ecole Polytechnique Federale de Lausanne, BCH (Switzerland); Kim, Chul-Hyun [University of California, Department of Chemistry (United States); Bodenhausen, Geoffrey [Institut de Chimie Moleculaire et Biologique, Ecole Polytechnique Federale de Lausanne, BCH (Switzerland)], E-mail: Geoffrey.Bodenhausen@ens.fr

    2003-12-15

    Two sets of cross-correlated relaxation rates involving chemical shift anisotropy and dipolar interactions have been measured in an RNA kissing complex. In one case, both the CSA and dipolar interaction tensors are located on the same nucleotide base and are rigidly fixed with respect to each other. In the other case, the CSA tensor is located on the nucleotide base whereas the dipolar interaction is located on the adjoining ribose unit. Analysis of the measured rates in terms of isotropic or anisotropic rotational diffusion has been carried out for both cases. A marked difference between the two models is observed for the cross-correlation rates involving rigidly fixed spin interactions. The influence of internal motions about the glycosidic linkage between the nucleotide base and the ribose unit on cross-correlated relaxation rates has been estimated by applying a model of restricted rotational diffusion. Local motions seem to have a more pronounced effect on cross-correlated relaxation rates when the two spin interactions are not rigidly fixed with respect to each other.

  8. Chemical reactivity predictions: use of data mining techniques for analyzing regioselective azidolysis of epoxides.

    Science.gov (United States)

    Borghini, Alice; Crotti, Paolo; Pietra, Daniele; Favero, Lucilla; Bianucci, Anna Maria

    2010-11-15

    Azidolysis of epoxides followed by reduction of the intermediate azido alcohols constitutes a valuable synthetic tool for the construction of beta-amino alcohols, an important chemical functionality occurring in many biologically active compounds of natural origin. However, depending on conditions under which the azidolysis is carried out, two regioisomeric products can be formed, as a consequence of the nucleophilic attack on both the oxirane carbon atoms. In this work, predictive models for quantitative structure-reactivity relationships were developed by means of multiple linear regression, k-nearest neighbor, locally weighted regression, and Gaussian Process regression algorithms. The specific nature of the problem at hand required the creation of appropriate new descriptors, able to properly reflect the most relevant features of molecular moieties directly involved in the opening process. The models so obtained are able to predict the regioselectivity of the azidolysis of epoxides promoted by sodium azide, in the presence of lithium perchlorate, on the basis of steric hindrance, and charge distribution of the substituents directly attached to the oxirane ring.

  9. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  10. Teleconnection, Regime Shift, and Predictability of Climate Extremes: A Case Study for the Russian Heat Wave and Pakistan Flood in Summer 2010

    Science.gov (United States)

    Lau, W. K.; Reale, O.; Kim, K.

    2011-01-01

    In this talk, we present observational evidence showing that the two major extremes events of the summer of 2010, i.e., the Russian heat wave and the Pakistan flood were physically connected. We find that the Pakistan flood was contributed by a series of unusually heavy rain events over the upper Indus River Basin in July-August. The rainfall regimes shifted from an episodic heavy rain regime in mid-to-late July to a steady heavy rain regime in August. An atmospheric Rossby wave associated with the development of the Russian heat wave was instrumental in spurring the episodic rain events , drawing moisture from the Bay of Bengal and the northern Arabian Sea. The steady rain regime was maintained primarily by monsoon moisture surges from the deep tropics. From experiments with the GEOS-5 forecast system, we assess the predictability of the heavy rain events associated with the Pakistan flood. Preliminary results indicate that there are significantly higher skills in the rainfall forecasts during the episodic heavy rain events in July, compared to the steady rain period in early to mid-August. The change in rainfall predictability may be related to scale interactions between the extratropics and the tropics resulting in a modulation of rainfall predictability by the circulation regimes.

  11. Teleconnection, regime shift, and predictability of climate extremes: A case study for the Russian heat wave and Pakistan flood in summer 2010.

    Science.gov (United States)

    Lau, W. K.; Reale, O.; Kim, K.

    2011-12-01

    In this talk, we present observational evidence showing that the two major extremes events of the summer of 2010, i.e., the Russian heat wave and the Pakistan flood were physically connected. We find that the Pakistan flood was contributed by a series of unusually heavy rain events over the upper Indus River Basin in July-August. The rainfall regimes shifted from an episodic heavy rain regime in mid-to-late July to a steady heavy rain regime in August. An atmospheric Rossby wave associated with the development of the Russian heat wave was instrumental in spurring the episodic rain events , drawing moisture from the Bay of Bengal and the northern Arabian Sea. The steady rain regime was maintained primarily by monsoon moisture surges from the deep tropics. From experiments with the GEOS-5 forecast system, we assess the predictability of the heavy rain events associated with the Pakistan flood. Preliminary results indicate that there are significantly higher skills in the rainfall forecasts during the episodic heavy rain events in July, compared to the steady rain period in early to mid-August. The change in rainfall predictability may be related to scale interactions between the extratropics and the tropics, resulting in a modulation of rainfall predictability by the circulation regimes.

  12. The importance of considering shifts in seasonal changes in discharges when predicting future phosphorus loads in streams

    Science.gov (United States)

    LaBeau, Meredith B.; Mayer, Alex S.; Griffis, Veronica; Watkins, David Jr.; Robertson, Dale; Gyawali, Rabi

    2015-01-01

    In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses throughout the U.S. Great Lakes Basin. We develop annual seasonal load-discharge regression models for each watershed and apply these models with simulated discharges generated for future climate scenarios to simulate future P loading patterns for two periods: 2046–2065 and 2081–2100. We utilize output from the Coupled Model Intercomparison Project phase 3 downscaled climate change projections that are input into the Large Basin Runoff Model to generate future discharge scenarios, which are in turn used as inputs to the seasonal P load regression models. In almost all cases, the seasonal load-discharge models match observed loads better than the annual models. Results using the seasonal models show that the concurrence of nonlinearity in the load-discharge model and changes in high discharges in the spring months leads to the most significant changes in P loading for selected tributaries under future climate projections. These results emphasize the importance of using seasonal models to understand the effects of future climate change on nutrient loads.

  13. Filling high aspect ratio trenches by superconformal chemical vapor deposition: Predictive modeling and experiment

    Science.gov (United States)

    Wang, Wenjiao B.; Abelson, John R.

    2014-11-01

    Complete filling of a deep recessed structure with a second material is a challenge in many areas of nanotechnology fabrication. A newly discovered superconformal coating method, applicable in chemical vapor deposition systems that utilize a precursor in combination with a co-reactant, can solve this problem. However, filling is a dynamic process in which the trench progressively narrows and the aspect ratio (AR) increases. This reduces species diffusion within the trench and may drive the component partial pressures out of the regime for superconformal coating. We therefore derive two theoretical models that can predict the possibility for filling. First, we recast the diffusion-reaction equation for the case of a sidewall with variable taper angle. This affords a definition of effective AR, which is larger than the nominal AR due to the reduced species transport. We then deri