RoboSCell: An automated single cell arraying and analysis instrument

KAUST Repository

Sakaki, Kelly; Foulds, Ian G.; Liu, William; Dechev, Nikolai; Burke, Robert Douglas; Park, Edward

2009-01-01

Single cell research has the potential to revolutionize experimental methods in biomedical sciences and contribute to clinical practices. Recent studies suggest analysis of single cells reveals novel features of intracellular processes, cell-to-cell

Development of the automated circulating tumor cell recovery system with microcavity array.

Science.gov (United States)

Negishi, Ryo; Hosokawa, Masahito; Nakamura, Seita; Kanbara, Hisashige; Kanetomo, Masafumi; Kikuhara, Yoshihito; Tanaka, Tsuyoshi; Matsunaga, Tadashi; Yoshino, Tomoko

2015-05-15

Circulating tumor cells (CTCs) are well recognized as useful biomarker for cancer diagnosis and potential target of drug discovery for metastatic cancer. Efficient and precise recovery of extremely low concentrations of CTCs from blood has been required to increase the detection sensitivity. Here, an automated system equipped with a microcavity array (MCA) was demonstrated for highly efficient and reproducible CTC recovery. The use of MCA allows selective recovery of cancer cells from whole blood on the basis of differences in size between tumor and blood cells. Intra- and inter-assays revealed that the automated system achieved high efficiency and reproducibility equal to the assay manually performed by well-trained operator. Under optimized assay workflow, the automated system allows efficient and precise cell recovery for non-small cell lung cancer cells spiked in whole blood. The automated CTC recovery system will contribute to high-throughput analysis in the further clinical studies on large cohort of cancer patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Establishment of automated culture system for murine induced pluripotent stem cells

Directory of Open Access Journals (Sweden)

Koike Hiroyuki

2012-11-01

Full Text Available Abstract Background Induced pluripotent stem (iPS cells can differentiate into any cell type, which makes them an attractive resource in fields such as regenerative medicine, drug screening, or in vitro toxicology. The most important prerequisite for these industrial applications is stable supply and uniform quality of iPS cells. Variation in quality largely results from differences in handling skills between operators in laboratories. To minimize these differences, establishment of an automated iPS cell culture system is necessary. Results We developed a standardized mouse iPS cell maintenance culture, using an automated cell culture system housed in a CO2 incubator commonly used in many laboratories. The iPS cells propagated in a chamber uniquely designed for automated culture and showed specific colony morphology, as for manual culture. A cell detachment device in the system passaged iPS cells automatically by dispersing colonies to single cells. In addition, iPS cells were passaged without any change in colony morphology or expression of undifferentiated stem cell markers during the 4 weeks of automated culture. Conclusions Our results show that use of this compact, automated cell culture system facilitates stable iPS cell culture without obvious effects on iPS cell pluripotency or colony-forming ability. The feasibility of iPS cell culture automation may greatly facilitate the use of this versatile cell source for a variety of biomedical applications.

Method for semi-automated microscopy of filtration-enriched circulating tumor cells.

Science.gov (United States)

Pailler, Emma; Oulhen, Marianne; Billiot, Fanny; Galland, Alexandre; Auger, Nathalie; Faugeroux, Vincent; Laplace-Builhé, Corinne; Besse, Benjamin; Loriot, Yohann; Ngo-Camus, Maud; Hemanda, Merouan; Lindsay, Colin R; Soria, Jean-Charles; Vielh, Philippe; Farace, Françoise

2016-07-14

Circulating tumor cell (CTC)-filtration methods capture high numbers of CTCs in non-small-cell lung cancer (NSCLC) and metastatic prostate cancer (mPCa) patients, and hold promise as a non-invasive technique for treatment selection and disease monitoring. However filters have drawbacks that make the automation of microscopy challenging. We report the semi-automated microscopy method we developed to analyze filtration-enriched CTCs from NSCLC and mPCa patients. Spiked cell lines in normal blood and CTCs were enriched by ISET (isolation by size of epithelial tumor cells). Fluorescent staining was carried out using epithelial (pan-cytokeratins, EpCAM), mesenchymal (vimentin, N-cadherin), leukocyte (CD45) markers and DAPI. Cytomorphological staining was carried out with Mayer-Hemalun or Diff-Quik. ALK-, ROS1-, ERG-rearrangement were detected by filter-adapted-FISH (FA-FISH). Microscopy was carried out using an Ariol scanner. Two combined assays were developed. The first assay sequentially combined four-color fluorescent staining, scanning, automated selection of CD45(-) cells, cytomorphological staining, then scanning and analysis of CD45(-) cell phenotypical and cytomorphological characteristics. CD45(-) cell selection was based on DAPI and CD45 intensity, and a nuclear area >55 μm(2). The second assay sequentially combined fluorescent staining, automated selection of CD45(-) cells, FISH scanning on CD45(-) cells, then analysis of CD45(-) cell FISH signals. Specific scanning parameters were developed to deal with the uneven surface of filters and CTC characteristics. Thirty z-stacks spaced 0.6 μm apart were defined as the optimal setting, scanning 82 %, 91 %, and 95 % of CTCs in ALK-, ROS1-, and ERG-rearranged patients respectively. A multi-exposure protocol consisting of three separate exposure times for green and red fluorochromes was optimized to analyze the intensity, size and thickness of FISH signals. The semi-automated microscopy method reported here

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

Science.gov (United States)

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

Biomek Cell Workstation: A Variable System for Automated Cell Cultivation.

Science.gov (United States)

Lehmann, R; Severitt, J C; Roddelkopf, T; Junginger, S; Thurow, K

2016-06-01

Automated cell cultivation is an important tool for simplifying routine laboratory work. Automated methods are independent of skill levels and daily constitution of laboratory staff in combination with a constant quality and performance of the methods. The Biomek Cell Workstation was configured as a flexible and compatible system. The modified Biomek Cell Workstation enables the cultivation of adherent and suspension cells. Until now, no commercially available systems enabled the automated handling of both types of cells in one system. In particular, the automated cultivation of suspension cells in this form has not been published. The cell counts and viabilities were nonsignificantly decreased for cells cultivated in AutoFlasks in automated handling. The proliferation of manual and automated bioscreening by the WST-1 assay showed a nonsignificant lower proliferation of automatically disseminated cells associated with a mostly lower standard error. The disseminated suspension cell lines showed different pronounced proliferations in descending order, starting with Jurkat cells followed by SEM, Molt4, and RS4 cells having the lowest proliferation. In this respect, we successfully disseminated and screened suspension cells in an automated way. The automated cultivation and dissemination of a variety of suspension cells can replace the manual method. © 2015 Society for Laboratory Automation and Screening.

Optimization-based Method for Automated Road Network Extraction

International Nuclear Information System (INIS)

Xiong, D

2001-01-01

Automated road information extraction has significant applicability in transportation. It provides a means for creating, maintaining, and updating transportation network databases that are needed for purposes ranging from traffic management to automated vehicle navigation and guidance. This paper is to review literature on the subject of road extraction and to describe a study of an optimization-based method for automated road network extraction

An engineered approach to stem cell culture: automating the decision process for real-time adaptive subculture of stem cells.

Directory of Open Access Journals (Sweden)

Dai Fei Elmer Ker

Full Text Available Current cell culture practices are dependent upon human operators and remain laborious and highly subjective, resulting in large variations and inconsistent outcomes, especially when using visual assessments of cell confluency to determine the appropriate time to subculture cells. Although efforts to automate cell culture with robotic systems are underway, the majority of such systems still require human intervention to determine when to subculture. Thus, it is necessary to accurately and objectively determine the appropriate time for cell passaging. Optimal stem cell culturing that maintains cell pluripotency while maximizing cell yields will be especially important for efficient, cost-effective stem cell-based therapies. Toward this goal we developed a real-time computer vision-based system that monitors the degree of cell confluency with a precision of 0.791±0.031 and recall of 0.559±0.043. The system consists of an automated phase-contrast time-lapse microscope and a server. Multiple dishes are sequentially imaged and the data is uploaded to the server that performs computer vision processing, predicts when cells will exceed a pre-defined threshold for optimal cell confluency, and provides a Web-based interface for remote cell culture monitoring. Human operators are also notified via text messaging and e-mail 4 hours prior to reaching this threshold and immediately upon reaching this threshold. This system was successfully used to direct the expansion of a paradigm stem cell population, C2C12 cells. Computer-directed and human-directed control subcultures required 3 serial cultures to achieve the theoretical target cell yield of 50 million C2C12 cells and showed no difference for myogenic and osteogenic differentiation. This automated vision-based system has potential as a tool toward adaptive real-time control of subculturing, cell culture optimization and quality assurance/quality control, and it could be integrated with current and

The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS

Directory of Open Access Journals (Sweden)

Kamal Attari

2017-01-01

Full Text Available Single-junction solar cells are the most available in the market and the most simple in terms of the realization and fabrication comparing to the other solar devices. However, these single-junction solar cells need more development and optimization for higher conversion efficiency. In addition to the doping densities and compromises between different layers and their best thickness value, the choice of the materials is also an important factor on improving the efficiency. In this paper, an efficient single-junction solar cell model of GaAs is presented and optimized. In the first step, an initial model was simulated and then the results were processed by an algorithm code. In this work, the proposed optimization method is a genetic search algorithm implemented in Matlab receiving ATLAS data to generate an optimum output power solar cell. Other performance parameters such as photogeneration rates, external quantum efficiency (EQE, and internal quantum efficiency (EQI are also obtained. The simulation shows that the proposed method provides significant conversion efficiency improvement of 29.7% under AM1.5G illumination. The other results were Jsc = 34.79 mA/cm2, Voc = 1 V, and fill factor (FF = 85%.

Method for semi-automated microscopy of filtration-enriched circulating tumor cells

International Nuclear Information System (INIS)

Pailler, Emma; Oulhen, Marianne; Billiot, Fanny; Galland, Alexandre; Auger, Nathalie; Faugeroux, Vincent; Laplace-Builhé, Corinne; Besse, Benjamin; Loriot, Yohann; Ngo-Camus, Maud; Hemanda, Merouan; Lindsay, Colin R.; Soria, Jean-Charles; Vielh, Philippe; Farace, Françoise

2016-01-01

Circulating tumor cell (CTC)-filtration methods capture high numbers of CTCs in non-small-cell lung cancer (NSCLC) and metastatic prostate cancer (mPCa) patients, and hold promise as a non-invasive technique for treatment selection and disease monitoring. However filters have drawbacks that make the automation of microscopy challenging. We report the semi-automated microscopy method we developed to analyze filtration-enriched CTCs from NSCLC and mPCa patients. Spiked cell lines in normal blood and CTCs were enriched by ISET (isolation by size of epithelial tumor cells). Fluorescent staining was carried out using epithelial (pan-cytokeratins, EpCAM), mesenchymal (vimentin, N-cadherin), leukocyte (CD45) markers and DAPI. Cytomorphological staining was carried out with Mayer-Hemalun or Diff-Quik. ALK-, ROS1-, ERG-rearrangement were detected by filter-adapted-FISH (FA-FISH). Microscopy was carried out using an Ariol scanner. Two combined assays were developed. The first assay sequentially combined four-color fluorescent staining, scanning, automated selection of CD45 − cells, cytomorphological staining, then scanning and analysis of CD45 − cell phenotypical and cytomorphological characteristics. CD45 − cell selection was based on DAPI and CD45 intensity, and a nuclear area >55 μm 2 . The second assay sequentially combined fluorescent staining, automated selection of CD45 − cells, FISH scanning on CD45 − cells, then analysis of CD45 − cell FISH signals. Specific scanning parameters were developed to deal with the uneven surface of filters and CTC characteristics. Thirty z-stacks spaced 0.6 μm apart were defined as the optimal setting, scanning 82 %, 91 %, and 95 % of CTCs in ALK-, ROS1-, and ERG-rearranged patients respectively. A multi-exposure protocol consisting of three separate exposure times for green and red fluorochromes was optimized to analyze the intensity, size and thickness of FISH signals. The semi-automated microscopy method reported here

Automated cell type discovery and classification through knowledge transfer

Science.gov (United States)

Lee, Hao-Chih; Kosoy, Roman; Becker, Christine E.

2017-01-01

Abstract Motivation: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and hinders translation of new biological understanding into clinical applications. Previous studies have applied machine learning to facilitate processing of mass cytometry data. However, manual inspection is still inevitable and becoming the barrier to reliable large-scale analysis. Results: We present a new algorithm called Automated Cell-type Discovery and Classification (ACDC) that fully automates the classification of canonical cell populations and highlights novel cell types in mass cytometry data. Evaluations on real-world data show ACDC provides accurate and reliable estimations compared to manual gating results. Additionally, ACDC automatically classifies previously ambiguous cell types to facilitate discovery. Our findings suggest that ACDC substantially improves both reliability and interpretability of results obtained from high-dimensional mass cytometry profiling data. Availability and Implementation: A Python package (Python 3) and analysis scripts for reproducing the results are availability on https://bitbucket.org/dudleylab/acdc. Contact: brian.kidd@mssm.edu or joel.dudley@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28158442

Self-optimizing approach for automated laser resonator alignment

Science.gov (United States)

Brecher, C.; Schmitt, R.; Loosen, P.; Guerrero, V.; Pyschny, N.; Pavim, A.; Gatej, A.

2012-02-01

Nowadays, the assembly of laser systems is dominated by manual operations, involving elaborate alignment by means of adjustable mountings. From a competition perspective, the most challenging problem in laser source manufacturing is price pressure, a result of cost competition exerted mainly from Asia. From an economical point of view, an automated assembly of laser systems defines a better approach to produce more reliable units at lower cost. However, the step from today's manual solutions towards an automated assembly requires parallel developments regarding product design, automation equipment and assembly processes. This paper introduces briefly the idea of self-optimizing technical systems as a new approach towards highly flexible automation. Technically, the work focuses on the precision assembly of laser resonators, which is one of the final and most crucial assembly steps in terms of beam quality and laser power. The paper presents a new design approach for miniaturized laser systems and new automation concepts for a robot-based precision assembly, as well as passive and active alignment methods, which are based on a self-optimizing approach. Very promising results have already been achieved, considerably reducing the duration and complexity of the laser resonator assembly. These results as well as future development perspectives are discussed.

A high sensitivity, high throughput, automated single-cell gel electrophoresis ('Comet') DNA damage assay

International Nuclear Information System (INIS)

Vojnovic, B.; Barber, P.R.; Johnston, P.J.; Gregory, H.C.; Locke, R.J.

2003-01-01

A fully automated microscopy machine vision image capture and analysis system for the collection of data from slides of 'comets' has been developed. The novel image processing algorithms employed in delineating the 'comet head' from the 'comet tail' allow us to determine accurately very low levels of damage. In conjunction with calibrated and automated image capture methods, we are able to eliminate operator subjectivity and analyse large numbers of cells (>2500) in a short time (<1 hour). The image processing algorithm is designed to handle particularly difficult nuclei containing a high degree of structure, due to DNA clumping. We also present techniques used to extend the assay's dynamic range by removing interfering background fluorescence and to define a region of interest. If subtle biological variations are to be quantified (e.g. cell cycle dependant damage), then the use of large cell populations is dictated. Under those circumstances, the use of a fully automated system is particularly advantageous providing that the manner in which data is extracted does not introduce any inadvertent bias. In practice, it is essential that the image processing steps are geared towards the correct recognition of an acceptable cell nucleus, i.e. comet 'head'. We acknowledge the financial support of CRUK, Programme Grant C133/A1812 - SP 2195-01/02 and the US Department of Energy Low Dose Radiation Research Program grant DE-FG07-99ER62878

Imaging Live Cells at the Nanometer-Scale with Single-Molecule Microscopy: Obstacles and Achievements in Experiment Optimization for Microbiology

Science.gov (United States)

Haas, Beth L.; Matson, Jyl S.; DiRita, Victor J.; Biteen, Julie S.

2015-01-01

Single-molecule fluorescence microscopy enables biological investigations inside living cells to achieve millisecond- and nanometer-scale resolution. Although single-molecule-based methods are becoming increasingly accessible to non-experts, optimizing new single-molecule experiments can be challenging, in particular when super-resolution imaging and tracking are applied to live cells. In this review, we summarize common obstacles to live-cell single-molecule microscopy and describe the methods we have developed and applied to overcome these challenges in live bacteria. We examine the choice of fluorophore and labeling scheme, approaches to achieving single-molecule levels of fluorescence, considerations for maintaining cell viability, and strategies for detecting single-molecule signals in the presence of noise and sample drift. We also discuss methods for analyzing single-molecule trajectories and the challenges presented by the finite size of a bacterial cell and the curvature of the bacterial membrane. PMID:25123183

An optimized method for automated analysis of algal pigments by HPLC

NARCIS (Netherlands)

van Leeuwe, M. A.; Villerius, L. A.; Roggeveld, J.; Visser, R. J. W.; Stefels, J.

2006-01-01

A recent development in algal pigment analysis by high-performance liquid chromatography (HPLC) is the application of automation. An optimization of a complete sampling and analysis protocol applied specifically in automation has not yet been performed. In this paper we show that automation can only

Single cell analysis: the new frontier in 'Omics'

Energy Technology Data Exchange (ETDEWEB)

Wang, Daojing; Bodovitz, Steven

2010-01-14

Cellular heterogeneity arising from stochastic expression of genes, proteins, and metabolites is a fundamental principle of cell biology, but single cell analysis has been beyond the capabilities of 'Omics' technologies. This is rapidly changing with the recent examples of single cell genomics, transcriptomics, proteomics, and metabolomics. The rate of change is expected to accelerate owing to emerging technologies that range from micro/nanofluidics to microfabricated interfaces for mass spectrometry to third- and fourth-generation automated DNA sequencers. As described in this review, single cell analysis is the new frontier in Omics, and single cell Omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity.

Approach to analysis of single nucleotide polymorphisms by automated constant denaturant capillary electrophoresis

International Nuclear Information System (INIS)

Bjoerheim, Jens; Abrahamsen, Torveig Weum; Kristensen, Annette Torgunrud; Gaudernack, Gustav; Ekstroem, Per O.

2003-01-01

Melting gel techniques have proven to be amenable and powerful tools in point mutation and single nucleotide polymorphism (SNP) analysis. With the introduction of commercially available capillary electrophoresis instruments, a partly automated platform for denaturant capillary electrophoresis with potential for routine screening of selected target sequences has been established. The aim of this article is to demonstrate the use of automated constant denaturant capillary electrophoresis (ACDCE) in single nucleotide polymorphism analysis of various target sequences. Optimal analysis conditions for different single nucleotide polymorphisms on ACDCE are evaluated with the Poland algorithm. Laboratory procedures include only PCR and electrophoresis. For direct genotyping of individual SNPs, the samples are analyzed with an internal standard and the alleles are identified by co-migration of sample and standard peaks. In conclusion, SNPs suitable for melting gel analysis based on theoretical thermodynamics were separated by ACDCE under appropriate conditions. With this instrumentation (ABI 310 Genetic Analyzer), 48 samples could be analyzed without any intervention. Several institutions have capillary instrumentation in-house, thus making this SNP analysis method accessible to large groups of researchers without any need for instrument modification

Cell-Detection Technique for Automated Patch Clamping

Science.gov (United States)

McDowell, Mark; Gray, Elizabeth

2008-01-01

A unique and customizable machinevision and image-data-processing technique has been developed for use in automated identification of cells that are optimal for patch clamping. [Patch clamping (in which patch electrodes are pressed against cell membranes) is an electrophysiological technique widely applied for the study of ion channels, and of membrane proteins that regulate the flow of ions across the membranes. Patch clamping is used in many biological research fields such as neurobiology, pharmacology, and molecular biology.] While there exist several hardware techniques for automated patch clamping of cells, very few of those techniques incorporate machine vision for locating cells that are ideal subjects for patch clamping. In contrast, the present technique is embodied in a machine-vision algorithm that, in practical application, enables the user to identify good and bad cells for patch clamping in an image captured by a charge-coupled-device (CCD) camera attached to a microscope, within a processing time of one second. Hence, the present technique can save time, thereby increasing efficiency and reducing cost. The present technique involves the utilization of cell-feature metrics to accurately make decisions on the degree to which individual cells are "good" or "bad" candidates for patch clamping. These metrics include position coordinates (x,y) in the image plane, major-axis length, minor-axis length, area, elongation, roundness, smoothness, angle of orientation, and degree of inclusion in the field of view. The present technique does not require any special hardware beyond commercially available, off-the-shelf patch-clamping hardware: A standard patchclamping microscope system with an attached CCD camera, a personal computer with an imagedata- processing board, and some experience in utilizing imagedata- processing software are all that are needed. A cell image is first captured by the microscope CCD camera and image-data-processing board, then the image

Automated analysis of invadopodia dynamics in live cells

Directory of Open Access Journals (Sweden)

Matthew E. Berginski

2014-07-01

Full Text Available Multiple cell types form specialized protein complexes that are used by the cell to actively degrade the surrounding extracellular matrix. These structures are called podosomes or invadopodia and collectively referred to as invadosomes. Due to their potential importance in both healthy physiology as well as in pathological conditions such as cancer, the characterization of these structures has been of increasing interest. Following early descriptions of invadopodia, assays were developed which labelled the matrix underneath metastatic cancer cells allowing for the assessment of invadopodia activity in motile cells. However, characterization of invadopodia using these methods has traditionally been done manually with time-consuming and potentially biased quantification methods, limiting the number of experiments and the quantity of data that can be analysed. We have developed a system to automate the segmentation, tracking and quantification of invadopodia in time-lapse fluorescence image sets at both the single invadopodia level and whole cell level. We rigorously tested the ability of the method to detect changes in invadopodia formation and dynamics through the use of well-characterized small molecule inhibitors, with known effects on invadopodia. Our results demonstrate the ability of this analysis method to quantify changes in invadopodia formation from live cell imaging data in a high throughput, automated manner.

Allogeneic cell therapy bioprocess economics and optimization: single-use cell expansion technologies.

Science.gov (United States)

Simaria, Ana S; Hassan, Sally; Varadaraju, Hemanthram; Rowley, Jon; Warren, Kim; Vanek, Philip; Farid, Suzanne S

2014-01-01

For allogeneic cell therapies to reach their therapeutic potential, challenges related to achieving scalable and robust manufacturing processes will need to be addressed. A particular challenge is producing lot-sizes capable of meeting commercial demands of up to 10(9) cells/dose for large patient numbers due to the current limitations of expansion technologies. This article describes the application of a decisional tool to identify the most cost-effective expansion technologies for different scales of production as well as current gaps in the technology capabilities for allogeneic cell therapy manufacture. The tool integrates bioprocess economics with optimization to assess the economic competitiveness of planar and microcarrier-based cell expansion technologies. Visualization methods were used to identify the production scales where planar technologies will cease to be cost-effective and where microcarrier-based bioreactors become the only option. The tool outputs also predict that for the industry to be sustainable for high demand scenarios, significant increases will likely be needed in the performance capabilities of microcarrier-based systems. These data are presented using a technology S-curve as well as windows of operation to identify the combination of cell productivities and scale of single-use bioreactors required to meet future lot sizes. The modeling insights can be used to identify where future R&D investment should be focused to improve the performance of the most promising technologies so that they become a robust and scalable option that enables the cell therapy industry reach commercially relevant lot sizes. The tool outputs can facilitate decision-making very early on in development and be used to predict, and better manage, the risk of process changes needed as products proceed through the development pathway. © 2013 Wiley Periodicals, Inc.

ASTROS: A multidisciplinary automated structural design tool

Science.gov (United States)

Neill, D. J.

1989-01-01

ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.

High-recovery visual identification and single-cell retrieval of circulating tumor cells for genomic analysis using a dual-technology platform integrated with automated immunofluorescence staining

International Nuclear Information System (INIS)

Campton, Daniel E; Ramirez, Arturo B; Nordberg, Joshua J; Drovetto, Nick; Clein, Alisa C; Varshavskaya, Paulina; Friemel, Barry H; Quarre, Steve; Breman, Amy; Dorschner, Michael; Blau, Sibel; Blau, C Anthony; Sabath, Daniel E; Stilwell, Jackie L; Kaldjian, Eric P

2015-01-01

Circulating tumor cells (CTCs) are malignant cells that have migrated from solid cancers into the blood, where they are typically present in rare numbers. There is great interest in using CTCs to monitor response to therapies, to identify clinically actionable biomarkers, and to provide a non-invasive window on the molecular state of a tumor. Here we characterize the performance of the AccuCyte® – CyteFinder® system, a comprehensive, reproducible and highly sensitive platform for collecting, identifying and retrieving individual CTCs from microscopic slides for molecular analysis after automated immunofluorescence staining for epithelial markers. All experiments employed a density-based cell separation apparatus (AccuCyte) to separate nucleated cells from the blood and transfer them to microscopic slides. After staining, the slides were imaged using a digital scanning microscope (CyteFinder). Precisely counted model CTCs (mCTCs) from four cancer cell lines were spiked into whole blood to determine recovery rates. Individual mCTCs were removed from slides using a single-cell retrieval device (CytePicker™) for whole genome amplification and subsequent analysis by PCR and Sanger sequencing, whole exome sequencing, or array-based comparative genomic hybridization. Clinical CTCs were evaluated in blood samples from patients with different cancers in comparison with the CellSearch® system. AccuCyte – CyteFinder presented high-resolution images that allowed identification of mCTCs by morphologic and phenotypic features. Spike-in mCTC recoveries were between 90 and 91%. More than 80% of single-digit spike-in mCTCs were identified and even a single cell in 7.5 mL could be found. Analysis of single SKBR3 mCTCs identified presence of a known TP53 mutation by both PCR and whole exome sequencing, and confirmed the reported karyotype of this cell line. Patient sample CTC counts matched or exceeded CellSearch CTC counts in a small feasibility cohort. The AccuCyte �

Automated Multivariate Optimization Tool for Energy Analysis: Preprint

Energy Technology Data Exchange (ETDEWEB)

Ellis, P. G.; Griffith, B. T.; Long, N.; Torcellini, P. A.; Crawley, D.

2006-07-01

Building energy simulations are often used for trial-and-error evaluation of ''what-if'' options in building design--a limited search for an optimal solution, or ''optimization''. Computerized searching has the potential to automate the input and output, evaluate many options, and perform enough simulations to account for the complex interactions among combinations of options. This paper describes ongoing efforts to develop such a tool. The optimization tool employs multiple modules, including a graphical user interface, a database, a preprocessor, the EnergyPlus simulation engine, an optimization engine, and a simulation run manager. Each module is described and the overall application architecture is summarized.

An Automated DAKOTA and VULCAN-CFD Framework with Application to Supersonic Facility Nozzle Flowpath Optimization

Science.gov (United States)

Axdahl, Erik L.

2015-01-01

Removing human interaction from design processes by using automation may lead to gains in both productivity and design precision. This memorandum describes efforts to incorporate high fidelity numerical analysis tools into an automated framework and applying that framework to applications of practical interest. The purpose of this effort was to integrate VULCAN-CFD into an automated, DAKOTA-enabled framework with a proof-of-concept application being the optimization of supersonic test facility nozzles. It was shown that the optimization framework could be deployed on a high performance computing cluster with the flow of information handled effectively to guide the optimization process. Furthermore, the application of the framework to supersonic test facility nozzle flowpath design and optimization was demonstrated using multiple optimization algorithms.

Long-term maintenance of human induced pluripotent stem cells by automated cell culture system.

Science.gov (United States)

Konagaya, Shuhei; Ando, Takeshi; Yamauchi, Toshiaki; Suemori, Hirofumi; Iwata, Hiroo

2015-11-17

Pluripotent stem cells, such as embryonic stem cells and induced pluripotent stem (iPS) cells, are regarded as new sources for cell replacement therapy. These cells can unlimitedly expand under undifferentiated conditions and be differentiated into multiple cell types. Automated culture systems enable the large-scale production of cells. In addition to reducing the time and effort of researchers, an automated culture system improves the reproducibility of cell cultures. In the present study, we newly designed a fully automated cell culture system for human iPS maintenance. Using an automated culture system, hiPS cells maintained their undifferentiated state for 60 days. Automatically prepared hiPS cells had a potency of differentiation into three germ layer cells including dopaminergic neurons and pancreatic cells.

A robotics platform for automated batch fabrication of high density, microfluidics-based DNA microarrays, with applications to single cell, multiplex assays of secreted proteins

Science.gov (United States)

Ahmad, Habib; Sutherland, Alex; Shin, Young Shik; Hwang, Kiwook; Qin, Lidong; Krom, Russell-John; Heath, James R.

2011-09-01

Microfluidics flow-patterning has been utilized for the construction of chip-scale miniaturized DNA and protein barcode arrays. Such arrays have been used for specific clinical and fundamental investigations in which many proteins are assayed from single cells or other small sample sizes. However, flow-patterned arrays are hand-prepared, and so are impractical for broad applications. We describe an integrated robotics/microfluidics platform for the automated preparation of such arrays, and we apply it to the batch fabrication of up to eighteen chips of flow-patterned DNA barcodes. The resulting substrates are comparable in quality with hand-made arrays and exhibit excellent substrate-to-substrate consistency. We demonstrate the utility and reproducibility of robotics-patterned barcodes by utilizing two flow-patterned chips for highly parallel assays of a panel of secreted proteins from single macrophage cells.

A robotics platform for automated batch fabrication of high density, microfluidics-based DNA microarrays, with applications to single cell, multiplex assays of secreted proteins.

Science.gov (United States)

Ahmad, Habib; Sutherland, Alex; Shin, Young Shik; Hwang, Kiwook; Qin, Lidong; Krom, Russell-John; Heath, James R

2011-09-01

Microfluidics flow-patterning has been utilized for the construction of chip-scale miniaturized DNA and protein barcode arrays. Such arrays have been used for specific clinical and fundamental investigations in which many proteins are assayed from single cells or other small sample sizes. However, flow-patterned arrays are hand-prepared, and so are impractical for broad applications. We describe an integrated robotics/microfluidics platform for the automated preparation of such arrays, and we apply it to the batch fabrication of up to eighteen chips of flow-patterned DNA barcodes. The resulting substrates are comparable in quality with hand-made arrays and exhibit excellent substrate-to-substrate consistency. We demonstrate the utility and reproducibility of robotics-patterned barcodes by utilizing two flow-patterned chips for highly parallel assays of a panel of secreted proteins from single macrophage cells. © 2011 American Institute of Physics

Shielded cells transfer automation

International Nuclear Information System (INIS)

Fisher, J.J.

1984-01-01

Nuclear waste from shielded cells is removed, packaged, and transferred manually in many nuclear facilities. Radiation exposure is absorbed by operators during these operations and limited only through procedural controls. Technological advances in automation using robotics have allowed a production waste removal operation to be automated to reduce radiation exposure. The robotic system bags waste containers out of glove box and transfers them to a shielded container. Operators control the system outside the system work area via television cameras. 9 figures

21 CFR 864.5200 - Automated cell counter.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated cell counter. 864.5200 Section 864.5200 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Automated and Semi-Automated Hematology Devices § 864...

Feasibility evaluation of 3 automated cellular drug screening assays on a robotic workstation.

Science.gov (United States)

Soikkeli, Anne; Sempio, Cristina; Kaukonen, Ann Marie; Urtti, Arto; Hirvonen, Jouni; Yliperttula, Marjo

2010-01-01

This study presents the implementation and optimization of 3 cell-based assays on a TECAN Genesis workstation-the Caspase-Glo 3/7 and sulforhodamine B (SRB) screening assays and the mechanistic Caco-2 permeability protocol-and evaluates their feasibility for automation. During implementation, the dispensing speed to add drug solutions and fixative trichloroacetic acid and the aspiration speed to remove the supernatant immediately after fixation were optimized. Decontamination steps for cleaning the tips and pipetting tubing were also added. The automated Caspase-Glo 3/7 screen was successfully optimized with Caco-2 cells (Z' 0.7, signal-to-base ratio [S/B] 1.7) but not with DU-145 cells. In contrast, the automated SRB screen was successfully optimized with the DU-145 cells (Z' 0.8, S/B 2.4) but not with the Caco-2 cells (Z' -0.8, S/B 1.4). The automated bidirectional Caco-2 permeability experiments separated successfully low- and high-permeability compounds (Z' 0.8, S/B 84.2) and passive drug permeation from efflux-mediated transport (Z' 0.5, S/B 8.6). Of the assays, the homogeneous Caspase-Glo 3/7 assay benefits the most from automation, but also the heterogeneous SRB assay and Caco-2 permeability experiments gain advantages from automation.

Optimization of Human NK Cell Manufacturing: Fully Automated Separation, Improved Ex Vivo Expansion Using IL-21 with Autologous Feeder Cells, and Generation of Anti-CD123-CAR-Expressing Effector Cells.

Science.gov (United States)

Klöß, Stephan; Oberschmidt, Olaf; Morgan, Michael; Dahlke, Julia; Arseniev, Lubomir; Huppert, Volker; Granzin, Markus; Gardlowski, Tanja; Matthies, Nadine; Soltenborn, Stephanie; Schambach, Axel; Koehl, Ulrike

2017-10-01

The administration of ex vivo expanded natural killer (NK) cells as potential antitumor effector cells appears to be suitable for effector cell-based immunotherapies in high-risk cancer patients. However, good manufacturing practice (GMP)-compliant manufacturing of clinical-grade NK cells at sufficiently high numbers represents a great challenge. Therefore, previous expansion protocols for those effector cells were improved and optimized by using newly developed culture medium, interleukin (IL)-21, and autologous feeder cells (FCs). Separation of primary human NK cells (CD56 + CD3 - ) was carried out with the CliniMACS Prodigy ® in a single process, starting with approximately 1.2 × 10 9 leukocytes collected by small-scale lymphapheresis or from buffy coats. Enriched NK cells were adjusted to starting cell concentrations within approximately 1 × 10 6 effector cells/mL and cultured in comparative expansion experiments for 14 days with IL-2 (1,000 IU/mL) in different GMP-compliant media (X-VIVO ™ 10, CellGro ® , TexMACS ™ , and NK MACS ® ). After medium optimization, beneficial effects for functionality and phenotype were investigated at the beginning of cell expansion with irradiated (25 Gy) autologous FCs at a ratio of 20:1 (feeder: NK) in the presence or absence of IL-21 (100 ng/mL). Additionally, expanded NK cells were gene modified to express chimeric antigen receptors (CARs) against CD123, a common marker for acute myeloid leukemia (AML). Cytotoxicity, degranulation, and cytokine release of transduced NK cells were determined against KG1a cells in flow cytometric analysis and fluorescent imaging. The Prodigy manufacturing process revealed high target cell viabilities (median 95.4%), adequate NK cell recovery (median 60.4%), and purity of 95.4% in regard to CD56 + CD3 - target cells. The process in its early phase of development led to a median T-cell depletion of log 3.5 after CD3 depletion and log 3.6 after the whole process, including CD3

Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time.

Science.gov (United States)

Wollman, Adam J M; Leake, Mark C

2015-01-01

We present a single-molecule tool called the CoPro (concentration of proteins) method that uses millisecond imaging with convolution analysis, automated image segmentation and super-resolution localization microscopy to generate robust estimates for protein concentration in different compartments of single living cells, validated using realistic simulations of complex multiple compartment cell types. We demonstrate its utility experimentally on model Escherichia coli bacteria and Saccharomyces cerevisiae budding yeast cells, and use it to address the biological question of how signals are transduced in cells. Cells in all domains of life dynamically sense their environment through signal transduction mechanisms, many involving gene regulation. The glucose sensing mechanism of S. cerevisiae is a model system for studying gene regulatory signal transduction. It uses the multi-copy expression inhibitor of the GAL gene family, Mig1, to repress unwanted genes in the presence of elevated extracellular glucose concentrations. We fluorescently labelled Mig1 molecules with green fluorescent protein (GFP) via chromosomal integration at physiological expression levels in living S. cerevisiae cells, in addition to the RNA polymerase protein Nrd1 with the fluorescent protein reporter mCherry. Using CoPro we make quantitative estimates of Mig1 and Nrd1 protein concentrations in the cytoplasm and nucleus compartments on a cell-by-cell basis under physiological conditions. These estimates indicate a ∼4-fold shift towards higher values in the concentration of diffusive Mig1 in the nucleus if the external glucose concentration is raised, whereas equivalent levels in the cytoplasm shift to smaller values with a relative change an order of magnitude smaller. This compares with Nrd1 which is not involved directly in glucose sensing, and which is almost exclusively localized in the nucleus under high and low external glucose levels. CoPro facilitates time-resolved quantification of

Automated Physico-Chemical Cell Model Development through Information Theory

Energy Technology Data Exchange (ETDEWEB)

Peter J. Ortoleva

2005-11-29

The objective of this project was to develop predictive models of the chemical responses of microbial cells to variations in their surroundings. The application of these models is optimization of environmental remediation and energy-producing biotechnical processes.The principles on which our project is based are as follows: chemical thermodynamics and kinetics; automation of calibration through information theory; integration of multiplex data (e.g. cDNA microarrays, NMR, proteomics), cell modeling, and bifurcation theory to overcome cellular complexity; and the use of multiplex data and information theory to calibrate and run an incomplete model. In this report we review four papers summarizing key findings and a web-enabled, multiple module workflow we have implemented that consists of a set of interoperable systems biology computational modules.

Automated migration analysis based on cell texture: method & reliability

Directory of Open Access Journals (Sweden)

Chittenden Thomas W

2005-03-01

Full Text Available Abstract Background In this paper, we present and validate a way to measure automatically the extent of cell migration based on automated examination of a series of digital photographs. It was designed specifically to identify the impact of Second Hand Smoke (SHS on endothelial cell migration but has broader applications. The analysis has two stages: (1 preprocessing of image texture, and (2 migration analysis. Results The output is a graphic overlay that indicates the front lines of cell migration superimposed on each original image, with automated reporting of the distance traversed vs. time. Expert preference compares to manual placement of leading edge shows complete equivalence of automated vs. manual leading edge definition for cell migration measurement. Conclusion Our method is indistinguishable from careful manual determinations of cell front lines, with the advantages of full automation, objectivity, and speed.

Application of a non-hazardous vital dye for cell counting with automated cell counters.

Science.gov (United States)

Kim, Soo In; Kim, Hyun Jeong; Lee, Ho-Jae; Lee, Kiwon; Hong, Dongpyo; Lim, Hyunchang; Cho, Keunchang; Jung, Neoncheol; Yi, Yong Weon

2016-01-01

Recent advances in automated cell counters enable us to count cells more easily with consistency. However, the wide use of the traditional vital dye trypan blue (TB) raises environmental and health concerns due to its potential teratogenic effects. To avoid this chemical hazard, it is of importance to introduce an alternative non-hazardous vital dye that is compatible with automated cell counters. Erythrosin B (EB) is a vital dye that is impermeable to biological membranes and is used as a food additive. Similarly to TB, EB stains only nonviable cells with disintegrated membranes. However, EB is less popular than TB and is seldom used with automated cell counters. We found that cell counting accuracy with EB was comparable to that with TB. EB was found to be an effective dye for accurate counting of cells with different viabilities across three different automated cell counters. In contrast to TB, EB was less toxic to cultured HL-60 cells during the cell counting process. These results indicate that replacing TB with EB for use with automated cell counters will significantly reduce the hazardous risk while producing comparable results. Copyright © 2015 Logos Biosystems, Inc. Published by Elsevier Inc. All rights reserved.

Simulation-Based Optimization for Storage Allocation Problem of Outbound Containers in Automated Container Terminals

Directory of Open Access Journals (Sweden)

Ning Zhao

2015-01-01

Full Text Available Storage allocation of outbound containers is a key factor of the performance of container handling system in automated container terminals. Improper storage plans of outbound containers make QC waiting inevitable; hence, the vessel handling time will be lengthened. A simulation-based optimization method is proposed in this paper for the storage allocation problem of outbound containers in automated container terminals (SAPOBA. A simulation model is built up by Timed-Colored-Petri-Net (TCPN, used to evaluate the QC waiting time of storage plans. Two optimization approaches, based on Particle Swarm Optimization (PSO and Genetic Algorithm (GA, are proposed to form the complete simulation-based optimization method. Effectiveness of this method is verified by experiment, as the comparison of the two optimization approaches.

21 CFR 864.5220 - Automated differential cell counter.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated differential cell counter. 864.5220 Section 864.5220 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Automated and Semi-Automated Hematology Devices...

21 CFR 864.5260 - Automated cell-locating device.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated cell-locating device. 864.5260 Section 864.5260 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Automated and Semi-Automated Hematology Devices...

Oxygen-controlled automated neural differentiation of mouse embryonic stem cells.

Science.gov (United States)

Mondragon-Teran, Paul; Tostoes, Rui; Mason, Chris; Lye, Gary J; Veraitch, Farlan S

2013-03-01

Automation and oxygen tension control are two tools that provide significant improvements to the reproducibility and efficiency of stem cell production processes. the aim of this study was to establish a novel automation platform capable of controlling oxygen tension during both the cell-culture and liquid-handling steps of neural differentiation processes. We built a bespoke automation platform, which enclosed a liquid-handling platform in a sterile, oxygen-controlled environment. An airtight connection was used to transfer cell culture plates to and from an automated oxygen-controlled incubator. Our results demonstrate that our system yielded comparable cell numbers, viabilities, metabolism profiles and differentiation efficiencies when compared with traditional manual processes. Interestingly, eliminating exposure to ambient conditions during the liquid-handling stage resulted in significant improvements in the yield of MAP2-positive neural cells, indicating that this level of control can improve differentiation processes. This article describes, for the first time, an automation platform capable of maintaining oxygen tension control during both the cell-culture and liquid-handling stages of a 2D embryonic stem cell differentiation process.

Automated Cell-Cutting for Cell Cloning

Science.gov (United States)

Ichikawa, Akihiko; Tanikawa, Tamio; Matsukawa, Kazutsugu; Takahashi, Seiya; Ohba, Kohtaro

We develop an automated cell-cutting technique for cell cloning. Animal cells softened by the cytochalasin treatment are injected into a microfluidic chip. The microfluidic chip contains two orthogonal channels: one microchannel is wide, used to transport cells, and generates the cutting flow; the other is thin and used for aspiration, fixing, and stretching of the cell. The injected cell is aspirated and stretched in the thin microchannel. Simultaneously, the volumes of the cell before and after aspiration are calculated; the volumes are used to calculate the fluid flow required to aspirate half the volume of the cell into the thin microchannel. Finally, we apply a high-speed flow in the orthogonal microchannel to bisect the cell. This paper reports the cutting process, the cutting system, and the results of the experiment.

21 CFR 864.9285 - Automated cell-washing centrifuge for immuno-hematology.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated cell-washing centrifuge for immuno... Establishments That Manufacture Blood and Blood Products § 864.9285 Automated cell-washing centrifuge for immuno-hematology. (a) Identification. An automated cell-washing centrifuge for immuno-hematology is a device used...

Full space device optimization for solar cells.

Science.gov (United States)

Baloch, Ahmer A B; Aly, Shahzada P; Hossain, Mohammad I; El-Mellouhi, Fedwa; Tabet, Nouar; Alharbi, Fahhad H

2017-09-20

Advances in computational materials have paved a way to design efficient solar cells by identifying the optimal properties of the device layers. Conventionally, the device optimization has been governed by single or double descriptors for an individual layer; mostly the absorbing layer. However, the performance of the device depends collectively on all the properties of the material and the geometry of each layer in the cell. To address this issue of multi-property optimization and to avoid the paradigm of reoccurring materials in the solar cell field, a full space material-independent optimization approach is developed and presented in this paper. The method is employed to obtain an optimized material data set for maximum efficiency and for targeted functionality for each layer. To ensure the robustness of the method, two cases are studied; namely perovskite solar cells device optimization and cadmium-free CIGS solar cell. The implementation determines the desirable optoelectronic properties of transport mediums and contacts that can maximize the efficiency for both cases. The resulted data sets of material properties can be matched with those in materials databases or by further microscopic material design. Moreover, the presented multi-property optimization framework can be extended to design any solid-state device.

High-dimensional single-cell cancer biology.

Science.gov (United States)

Irish, Jonathan M; Doxie, Deon B

2014-01-01

Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

Automated Planning of Tangential Breast Intensity-Modulated Radiotherapy Using Heuristic Optimization

International Nuclear Information System (INIS)

Purdie, Thomas G.; Dinniwell, Robert E.; Letourneau, Daniel; Hill, Christine; Sharpe, Michael B.

2011-01-01

Purpose: To present an automated technique for two-field tangential breast intensity-modulated radiotherapy (IMRT) treatment planning. Method and Materials: A total of 158 planned patients with Stage 0, I, and II breast cancer treated using whole-breast IMRT were retrospectively replanned using automated treatment planning tools. The tools developed are integrated into the existing clinical treatment planning system (Pinnacle 3 ) and are designed to perform the manual volume delineation, beam placement, and IMRT treatment planning steps carried out by the treatment planning radiation therapist. The automated algorithm, using only the radio-opaque markers placed at CT simulation as inputs, optimizes the tangential beam parameters to geometrically minimize the amount of lung and heart treated while covering the whole-breast volume. The IMRT parameters are optimized according to the automatically delineated whole-breast volume. Results: The mean time to generate a complete treatment plan was 6 min, 50 s ± 1 min 12 s. For the automated plans, 157 of 158 plans (99%) were deemed clinically acceptable, and 138 of 158 plans (87%) were deemed clinically improved or equal to the corresponding clinical plan when reviewed in a randomized, double-blinded study by one experienced breast radiation oncologist. In addition, overall the automated plans were dosimetrically equivalent to the clinical plans when scored for target coverage and lung and heart doses. Conclusion: We have developed robust and efficient automated tools for fully inversed planned tangential breast IMRT planning that can be readily integrated into clinical practice. The tools produce clinically acceptable plans using only the common anatomic landmarks from the CT simulation process as an input. We anticipate the tools will improve patient access to high-quality IMRT treatment by simplifying the planning process and will reduce the effort and cost of incorporating more advanced planning into clinical practice.

Simulation based optimization on automated fibre placement process

Science.gov (United States)

Lei, Shi

2018-02-01

In this paper, a software simulation (Autodesk TruPlan & TruFiber) based method is proposed to optimize the automate fibre placement (AFP) process. Different types of manufacturability analysis are introduced to predict potential defects. Advanced fibre path generation algorithms are compared with respect to geometrically different parts. Major manufacturing data have been taken into consideration prior to the tool paths generation to achieve high success rate of manufacturing.

Development of An Optimization Method for Determining Automation Rate in Nuclear Power Plants

International Nuclear Information System (INIS)

Lee, Seung Min; Seong, Poong Hyun; Kim, Jong Hyun

2014-01-01

Since automation was introduced in various industrial fields, it has been known that automation provides positive effects like greater efficiency and fewer human errors, and negative effect defined as out-of-the-loop (OOTL). Thus, before introducing automation in nuclear field, the estimation of the positive and negative effects of automation on human operators should be conducted. In this paper, by focusing on CPS, the optimization method to find an appropriate proportion of automation is suggested by integrating the suggested cognitive automation rate and the concepts of the level of ostracism. The cognitive automation rate estimation method was suggested to express the reduced amount of human cognitive loads, and the level of ostracism was suggested to express the difficulty in obtaining information from the automation system and increased uncertainty of human operators' diagnosis. The maximized proportion of automation that maintains the high level of attention for monitoring the situation is derived by an experiment, and the automation rate is estimated by the suggested automation rate estimation method. It is expected to derive an appropriate inclusion proportion of the automation system avoiding the OOTL problem and having maximum efficacy at the same time

Image-Based Single Cell Profiling: High-Throughput Processing of Mother Machine Experiments.

Directory of Open Access Journals (Sweden)

Christian Carsten Sachs

Full Text Available Microfluidic lab-on-chip technology combined with live-cell imaging has enabled the observation of single cells in their spatio-temporal context. The mother machine (MM cultivation system is particularly attractive for the long-term investigation of rod-shaped bacteria since it facilitates continuous cultivation and observation of individual cells over many generations in a highly parallelized manner. To date, the lack of fully automated image analysis software limits the practical applicability of the MM as a phenotypic screening tool.We present an image analysis pipeline for the automated processing of MM time lapse image stacks. The pipeline supports all analysis steps, i.e., image registration, orientation correction, channel/cell detection, cell tracking, and result visualization. Tailored algorithms account for the specialized MM layout to enable a robust automated analysis. Image data generated in a two-day growth study (≈ 90 GB is analyzed in ≈ 30 min with negligible differences in growth rate between automated and manual evaluation quality. The proposed methods are implemented in the software molyso (MOther machine AnaLYsis SOftware that provides a new profiling tool to analyze unbiasedly hitherto inaccessible large-scale MM image stacks.Presented is the software molyso, a ready-to-use open source software (BSD-licensed for the unsupervised analysis of MM time-lapse image stacks. molyso source code and user manual are available at https://github.com/modsim/molyso.

Controller Design Automation for Aeroservoelastic Design Optimization of Wind Turbines

NARCIS (Netherlands)

Ashuri, T.; Van Bussel, G.J.W.; Zaayer, M.B.; Van Kuik, G.A.M.

2010-01-01

The purpose of this paper is to integrate the controller design of wind turbines with structure and aerodynamic analysis and use the final product in the design optimization process (DOP) of wind turbines. To do that, the controller design is automated and integrated with an aeroelastic simulation

Cell wall-bound silicon optimizes ammonium uptake and metabolism in rice cells.

Science.gov (United States)

Sheng, Huachun; Ma, Jie; Pu, Junbao; Wang, Lijun

2018-05-16

Turgor-driven plant cell growth depends on cell wall structure and mechanics. Strengthening of cell walls on the basis of an association and interaction with silicon (Si) could lead to improved nutrient uptake and optimized growth and metabolism in rice (Oryza sativa). However, the structural basis and physiological mechanisms of nutrient uptake and metabolism optimization under Si assistance remain obscure. Single-cell level biophysical measurements, including in situ non-invasive micro-testing (NMT) of NH4+ ion fluxes, atomic force microscopy (AFM) of cell walls, and electrolyte leakage and membrane potential, as well as whole-cell proteomics using isobaric tags for relative and absolute quantification (iTRAQ), were performed. The altered cell wall structure increases the uptake rate of the main nutrient NH4+ in Si-accumulating cells, whereas the rate is only half in Si-deprived counterparts. Rigid cell walls enhanced by a wall-bound form of Si as the structural basis stabilize cell membranes. This, in turn, optimizes nutrient uptake of the cells in the same growth phase without any requirement for up-regulation of transmembrane ammonium transporters. Optimization of cellular nutrient acquisition strategies can substantially improve performance in terms of growth, metabolism and stress resistance.

Automated design and optimization of flexible booster autopilots via linear programming, volume 1

Science.gov (United States)

Hauser, F. D.

1972-01-01

A nonlinear programming technique was developed for the automated design and optimization of autopilots for large flexible launch vehicles. This technique, which resulted in the COEBRA program, uses the iterative application of linear programming. The method deals directly with the three main requirements of booster autopilot design: to provide (1) good response to guidance commands; (2) response to external disturbances (e.g. wind) to minimize structural bending moment loads and trajectory dispersions; and (3) stability with specified tolerances on the vehicle and flight control system parameters. The method is applicable to very high order systems (30th and greater per flight condition). Examples are provided that demonstrate the successful application of the employed algorithm to the design of autopilots for both single and multiple flight conditions.

An Algorithm to Automate Yeast Segmentation and Tracking

Science.gov (United States)

Doncic, Andreas; Eser, Umut; Atay, Oguzhan; Skotheim, Jan M.

2013-01-01

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation. PMID:23520484

Enhanced power generation in annular single-chamber microbial fuel cell via optimization of electrode spacing using chocolate industry wastewater.

Science.gov (United States)

Noori, Parisa; Najafpour Darzi, Ghasem

2016-05-01

Development and practical application of microbial fuel cell (MFC) is restricted because of the limitations such as low power output. To overcome low power limitation, the optimization of specific parameters including electrode materials and surface area, electrode spacing, and MFC's cell shape was investigated. To the best of our knowledge, no investigation has been reported in the literature to implement an annular single-chamber microbial fuel cell (ASCMFC) using chocolate industry wastewater. ASCMFC was fabricated via optimization of the stated parameters. The aspects of ASCMFC were comprehensively examined. In this study, the optimization of electrode spacing and its impact on performance of the ASCMFC were conducted. Reduction of electrode spacing by 46.15% (1.3-0.7 cm) resulted in a decrease in internal resistance from 100 to 50 Ω, which enhanced the power density and current output to 22.898 W/m(3) and 6.42 mA, respectively. An optimum electrode spacing of 0.7 cm was determined. Through this paper, the effects of these parameters and the performance of ASCMFC are also evaluated. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Numerical Analysis of Hydrodynamic Flow in Microfluidic Biochip for Single-Cell Trapping Application

Directory of Open Access Journals (Sweden)

Amelia Ahmad Khalili

2015-11-01

Full Text Available Single-cell analysis has become the interest of a wide range of biological and biomedical engineering research. It could provide precise information on individual cells, leading to important knowledge regarding human diseases. To perform single-cell analysis, it is crucial to isolate the individual cells before further manipulation is carried out. Recently, microfluidic biochips have been widely used for cell trapping and single cell analysis, such as mechanical and electrical detection. This work focuses on developing a finite element simulation model of single-cell trapping system for any types of cells or particles based on the hydrodynamic flow resistance (Rh manipulations in the main channel and trap channel to achieve successful trapping. Analysis is carried out using finite element ABAQUS-FEA™ software. A guideline to design and optimize single-cell trapping model is proposed and the example of a thorough optimization analysis is carried out using a yeast cell model. The results show the finite element model is able to trap a single cell inside the fluidic environment. Fluid’s velocity profile and streamline plots for successful and unsuccessful single yeast cell trapping are presented according to the hydrodynamic concept. The single-cell trapping model can be a significant important guideline in designing a new chip for biomedical applications.

Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

Science.gov (United States)

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

Simple heuristics: A bridge between manual core design and automated optimization methods

International Nuclear Information System (INIS)

White, J.R.; Delmolino, P.M.

1993-01-01

The primary function of RESCUE is to serve as an aid in the analysis and identification of feasible loading patterns for LWR reload cores. The unique feature of RESCUE is that its physics model is based on some recent advances in generalized perturbation theory (GPT) methods. The high order GPT techniques offer the accuracy, computational efficiency, and flexibility needed for the implementation of a full range of capabilities within a set of compatible interactive (manual and semi-automated) and automated design tools. The basic design philosophy and current features within RESCUE are reviewed, and the new semi-automated capability is highlighted. The online advisor facility appears quite promising and it provides a natural bridge between the traditional trial-and-error manual process and the recent progress towards fully automated optimization sequences. (orig.)

Automated measurement of cell motility and proliferation

Directory of Open Access Journals (Sweden)

Goff Julie

2005-04-01

Full Text Available Abstract Background Time-lapse microscopic imaging provides a powerful approach for following changes in cell phenotype over time. Visible responses of whole cells can yield insight into functional changes that underlie physiological processes in health and disease. For example, features of cell motility accompany molecular changes that are central to the immune response, to carcinogenesis and metastasis, to wound healing and tissue regeneration, and to the myriad developmental processes that generate an organism. Previously reported image processing methods for motility analysis required custom viewing devices and manual interactions that may introduce bias, that slow throughput, and that constrain the scope of experiments in terms of the number of treatment variables, time period of observation, replication and statistical options. Here we describe a fully automated system in which images are acquired 24/7 from 384 well plates and are automatically processed to yield high-content motility and morphological data. Results We have applied this technology to study the effects of different extracellular matrix compounds on human osteoblast-like cell lines to explore functional changes that may underlie processes involved in bone formation and maintenance. We show dose-response and kinetic data for induction of increased motility by laminin and collagen type I without significant effects on growth rate. Differential motility response was evident within 4 hours of plating cells; long-term responses differed depending upon cell type and surface coating. Average velocities were increased approximately 0.1 um/min by ten-fold increases in laminin coating concentration in some cases. Comparison with manual tracking demonstrated the accuracy of the automated method and highlighted the comparative imprecision of human tracking for analysis of cell motility data. Quality statistics are reported that associate with stage noise, interference by non-cell

Single-Cell mRNA-Seq Using the Fluidigm C1 System and Integrated Fluidics Circuits.

Science.gov (United States)

Gong, Haibiao; Do, Devin; Ramakrishnan, Ramesh

2018-01-01

Single-cell mRNA-seq is a valuable tool to dissect expression profiles and to understand the regulatory network of genes. Microfluidics is well suited for single-cell analysis owing both to the small volume of the reaction chambers and easiness of automation. Here we describe the workflow of single-cell mRNA-seq using C1 IFC, which can isolate and process up to 96 cells. Both on-chip procedure (lysis, reverse transcription, and preamplification PCR) and off-chip sequencing library preparation protocols are described. The workflow generates full-length mRNA information, which is more valuable compared to 3' end counting method for many applications.

Automation of 3D cell culture using chemically defined hydrogels.

Science.gov (United States)

Rimann, Markus; Angres, Brigitte; Patocchi-Tenzer, Isabel; Braum, Susanne; Graf-Hausner, Ursula

2014-04-01

Drug development relies on high-throughput screening involving cell-based assays. Most of the assays are still based on cells grown in monolayer rather than in three-dimensional (3D) formats, although cells behave more in vivo-like in 3D. To exemplify the adoption of 3D techniques in drug development, this project investigated the automation of a hydrogel-based 3D cell culture system using a liquid-handling robot. The hydrogel technology used offers high flexibility of gel design due to a modular composition of a polymer network and bioactive components. The cell inert degradation of the gel at the end of the culture period guaranteed the harmless isolation of live cells for further downstream processing. Human colon carcinoma cells HCT-116 were encapsulated and grown in these dextran-based hydrogels, thereby forming 3D multicellular spheroids. Viability and DNA content of the cells were shown to be similar in automated and manually produced hydrogels. Furthermore, cell treatment with toxic Taxol concentrations (100 nM) had the same effect on HCT-116 cell viability in manually and automated hydrogel preparations. Finally, a fully automated dose-response curve with the reference compound Taxol showed the potential of this hydrogel-based 3D cell culture system in advanced drug development.

21 CFR 864.5240 - Automated blood cell diluting apparatus.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated blood cell diluting apparatus. 864.5240 Section 864.5240 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Automated and Semi-Automated Hematology Devices...

Automated Tracking of Cell Migration with Rapid Data Analysis.

Science.gov (United States)

DuChez, Brian J

2017-09-01

Cell migration is essential for many biological processes including development, wound healing, and metastasis. However, studying cell migration often requires the time-consuming and labor-intensive task of manually tracking cells. To accelerate the task of obtaining coordinate positions of migrating cells, we have developed a graphical user interface (GUI) capable of automating the tracking of fluorescently labeled nuclei. This GUI provides an intuitive user interface that makes automated tracking accessible to researchers with no image-processing experience or familiarity with particle-tracking approaches. Using this GUI, users can interactively determine a minimum of four parameters to identify fluorescently labeled cells and automate acquisition of cell trajectories. Additional features allow for batch processing of numerous time-lapse images, curation of unwanted tracks, and subsequent statistical analysis of tracked cells. Statistical outputs allow users to evaluate migratory phenotypes, including cell speed, distance, displacement, and persistence, as well as measures of directional movement, such as forward migration index (FMI) and angular displacement. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Mass Spectrometric Method for Analyzing Metabolites in Yeast with Single Cell Sensitivity

NARCIS (Netherlands)

Amantonico, Andrea; Oh, Joo Yeon; Sobek, Jens; Heinemann, Matthias; Zenobi, Renato

2008-01-01

Getting a look-in: An optimized MALDI-MS procedure has been developed to detect endogenous primary metabolites directly in the cell extract. A detection limit corresponding to metabolites from less than a single cell has been attained, opening the door to single-cell metabolomics by mass

Inertial Microfluidic Cell Stretcher (iMCS): Fully Automated, High-Throughput, and Near Real-Time Cell Mechanotyping.

Science.gov (United States)

Deng, Yanxiang; Davis, Steven P; Yang, Fan; Paulsen, Kevin S; Kumar, Maneesh; Sinnott DeVaux, Rebecca; Wang, Xianhui; Conklin, Douglas S; Oberai, Assad; Herschkowitz, Jason I; Chung, Aram J

2017-07-01

Mechanical biomarkers associated with cytoskeletal structures have been reported as powerful label-free cell state identifiers. In order to measure cell mechanical properties, traditional biophysical (e.g., atomic force microscopy, micropipette aspiration, optical stretchers) and microfluidic approaches were mainly employed; however, they critically suffer from low-throughput, low-sensitivity, and/or time-consuming and labor-intensive processes, not allowing techniques to be practically used for cell biology research applications. Here, a novel inertial microfluidic cell stretcher (iMCS) capable of characterizing large populations of single-cell deformability near real-time is presented. The platform inertially controls cell positions in microchannels and deforms cells upon collision at a T-junction with large strain. The cell elongation motions are recorded, and thousands of cell deformability information is visualized near real-time similar to traditional flow cytometry. With a full automation, the entire cell mechanotyping process runs without any human intervention, realizing a user friendly and robust operation. Through iMCS, distinct cell stiffness changes in breast cancer progression and epithelial mesenchymal transition are reported, and the use of the platform for rapid cancer drug discovery is shown as well. The platform returns large populations of single-cell quantitative mechanical properties (e.g., shear modulus) on-the-fly with high statistical significances, enabling actual usages in clinical and biophysical studies. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

Science.gov (United States)

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

An algorithm to automate yeast segmentation and tracking.

Directory of Open Access Journals (Sweden)

Andreas Doncic

Full Text Available Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.

Automated detection of fluorescent cells in in-resin fluorescence sections for integrated light and electron microscopy.

Science.gov (United States)

Delpiano, J; Pizarro, L; Peddie, C J; Jones, M L; Griffin, L D; Collinson, L M

2018-04-26

Integrated array tomography combines fluorescence and electron imaging of ultrathin sections in one microscope, and enables accurate high-resolution correlation of fluorescent proteins to cell organelles and membranes. Large numbers of serial sections can be imaged sequentially to produce aligned volumes from both imaging modalities, thus producing enormous amounts of data that must be handled and processed using novel techniques. Here, we present a scheme for automated detection of fluorescent cells within thin resin sections, which could then be used to drive automated electron image acquisition from target regions via 'smart tracking'. The aim of this work is to aid in optimization of the data acquisition process through automation, freeing the operator to work on other tasks and speeding up the process, while reducing data rates by only acquiring images from regions of interest. This new method is shown to be robust against noise and able to deal with regions of low fluorescence. © 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

Partial Red Blood Cell Exchange in Children and Young Patients with Sickle Cell Disease: Manual Versus Automated Procedure.

Science.gov (United States)

Escobar, Carlos; Moniz, Marta; Nunes, Pedro; Abadesso, Clara; Ferreira, Teresa; Barra, António; Lichtner, Anabela; Loureiro, Helena; Dias, Alexandra; Almeida, Helena

2017-10-31

The benefits of manual versus automated red blood cell exchange have rarely been documented and studies in young sickle cell disease patients are scarce. We aim to describe and compare our experience in these two procedures. Young patients (≤ 21 years old) who underwent manual- or automated-red blood cell exchange for prevention or treatment of sickle cell disease complications were included. Clinical, technical and hematological data were prospectively recorded and analyzed. Ninety-four red blood cell exchange sessions were performed over a period of 68 months, including 57 manual and 37 automated, 63 for chronic complications prevention, 30 for acute complications and one in the pre-operative setting. Mean decrease in sickle hemoglobin levels was higher in automated-red blood cell exchange (p exchange and access alarm on automated-red blood cell exchange. No major complication or alloimunization was recorded. Automated-red blood cell exchange decreased sickle hemoglobin levels more efficiently than manual procedure in the setting of acute and chronic complications of sickle cell disease, with minor technical concerns mainly due to vascular access. The threshold of sickle hemoglobin should be individualized for clinical and hematological goals. In our cohort of young patients, the need for an acceptable venous access was a limiting factor, but iron-overload was avoided. Automated red blood cell exchange is safe and well tolerated. It permits a higher sickle hemoglobin removal efficacy, better volume status control and iron-overload avoidance.

Automated magnetic divertor design for optimal power exhaust

Energy Technology Data Exchange (ETDEWEB)

Blommaert, Maarten

2017-07-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation

Automated magnetic divertor design for optimal power exhaust

International Nuclear Information System (INIS)

Blommaert, Maarten

2017-01-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation. These flaws

Design of an optimal automation system : Finding a balance between a human's task engagement and exhaustion

NARCIS (Netherlands)

Klein, Michel; van Lambalgen, Rianne

2011-01-01

In demanding tasks, human performance can seriously degrade as a consequence of increased workload and limited resources. In such tasks it is very important to maintain an optimal performance quality, therefore automation assistance is required. On the other hand, automation can also impose

Context based mixture model for cell phase identification in automated fluorescence microscopy

Directory of Open Access Journals (Sweden)

Zhou Xiaobo

2007-01-01

Full Text Available Abstract Background Automated identification of cell cycle phases of individual live cells in a large population captured via automated fluorescence microscopy technique is important for cancer drug discovery and cell cycle studies. Time-lapse fluorescence microscopy images provide an important method to study the cell cycle process under different conditions of perturbation. Existing methods are limited in dealing with such time-lapse data sets while manual analysis is not feasible. This paper presents statistical data analysis and statistical pattern recognition to perform this task. Results The data is generated from Hela H2B GFP cells imaged during a 2-day period with images acquired 15 minutes apart using an automated time-lapse fluorescence microscopy. The patterns are described with four kinds of features, including twelve general features, Haralick texture features, Zernike moment features, and wavelet features. To generate a new set of features with more discriminate power, the commonly used feature reduction techniques are used, which include Principle Component Analysis (PCA, Linear Discriminant Analysis (LDA, Maximum Margin Criterion (MMC, Stepwise Discriminate Analysis based Feature Selection (SDAFS, and Genetic Algorithm based Feature Selection (GAFS. Then, we propose a Context Based Mixture Model (CBMM for dealing with the time-series cell sequence information and compare it to other traditional classifiers: Support Vector Machine (SVM, Neural Network (NN, and K-Nearest Neighbor (KNN. Being a standard practice in machine learning, we systematically compare the performance of a number of common feature reduction techniques and classifiers to select an optimal combination of a feature reduction technique and a classifier. A cellular database containing 100 manually labelled subsequence is built for evaluating the performance of the classifiers. The generalization error is estimated using the cross validation technique. The

Optimal Control of Connected and Automated Vehicles at Roundabouts

Energy Technology Data Exchange (ETDEWEB)

Zhao, Liuhui [University of Delaware; Malikopoulos, Andreas [ORNL; Rios-Torres, Jackeline [ORNL

2018-01-01

Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This study investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other and to an infrastructure in roundabouts to achieve a smooth traffic flow without stop-and-go driving. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the efficiency of the proposed approach is validated through simulation and it is shown that coordination of vehicles can reduce total travel time by 3~49% and fuel consumption by 2~27% with respect to different traffic levels. In addition, network throughput is improved by up to 25% due to elimination of stop-and-go driving behavior.

Clinical utility of an automated instrument for gram staining single slides.

Science.gov (United States)

Baron, Ellen Jo; Mix, Samantha; Moradi, Wais

2010-06-01

Gram stains of 87 different clinical samples were prepared by the laboratory's conventional methods (automated or manual) and by a new single-slide-type automated staining instrument, GG&B AGS-1000. Gram stains from either heat- or methanol-fixed slides stained with the new instrument were easy to interpret, and results were essentially the same as those from the methanol-fixed slides prepared as a part of the routine workflow. This instrument is well suited to a rapid-response laboratory where Gram stain requests are commonly received on a stat basis.

Automated electrochemical assembly of the protected potential TMG-chitotriomycin precursor based on rational optimization of the carbohydrate building block.

Science.gov (United States)

Nokami, Toshiki; Isoda, Yuta; Sasaki, Norihiko; Takaiso, Aki; Hayase, Shuichi; Itoh, Toshiyuki; Hayashi, Ryutaro; Shimizu, Akihiro; Yoshida, Jun-ichi

2015-03-20

The anomeric arylthio group and the hydroxyl-protecting groups of thioglycosides were optimized to construct carbohydrate building blocks for automated electrochemical solution-phase synthesis of oligoglucosamines having 1,4-β-glycosidic linkages. The optimization study included density functional theory calculations, measurements of the oxidation potentials, and the trial synthesis of the chitotriose trisaccharide. The automated synthesis of the protected potential N,N,N-trimethyl-d-glucosaminylchitotriomycin precursor was accomplished by using the optimized building block.

Geometry Based Design Automation : Applied to Aircraft Modelling and Optimization

OpenAIRE

Amadori, Kristian

2012-01-01

Product development processes are continuously challenged by demands for increased efficiency. As engineering products become more and more complex, efficient tools and methods for integrated and automated design are needed throughout the development process. Multidisciplinary Design Optimization (MDO) is one promising technique that has the potential to drastically improve concurrent design. MDO frameworks combine several disciplinary models with the aim of gaining a holistic perspective of ...

Using micro-patterned sensors and cell self-assembly for measuring the oxygen consumption rate of single cells

International Nuclear Information System (INIS)

Etzkorn, James R; Parviz, Babak A; Wu, Wen-Chung; Tian, Zhiyuan; Kim, Prince; Jang, Sei-Hum; Jen, Alex K-Y; Meldrum, Deirdre R

2010-01-01

We present a method for self-assembling arrays of live single cells on a glass chip using a photopatternable polymer to form micro-traps. We have studied the single-cell self-assembly method and optimized the process to obtain a 52% yield of single-trapped cells. We also report a method to measure the oxygen consumption rate of a single cell using micro-patterned sensors. These molecular oxygen sensors were fabricated around each micro-trap allowing optical interrogation of oxygen concentration in the immediate environment of the trapped cell. Micromachined micro-wells were then used to seal the trap, sensor and cell in order to determine the oxygen consumption rate of single cells. These techniques reported here add to the collection of tools for performing 'singe-cell' biology. An oxygen consumption rate of 1.05 ± 0.28 fmol min −1 was found for a data set consisting of 25 single A549 cells.

Novel automated blood separations validate whole cell biomarkers.

Directory of Open Access Journals (Sweden)

Douglas E Burger

Full Text Available Progress in clinical trials in infectious disease, autoimmunity, and cancer is stymied by a dearth of successful whole cell biomarkers for peripheral blood lymphocytes (PBLs. Successful biomarkers could help to track drug effects at early time points in clinical trials to prevent costly trial failures late in development. One major obstacle is the inaccuracy of Ficoll density centrifugation, the decades-old method of separating PBLs from the abundant red blood cells (RBCs of fresh blood samples.To replace the Ficoll method, we developed and studied a novel blood-based magnetic separation method. The magnetic method strikingly surpassed Ficoll in viability, purity and yield of PBLs. To reduce labor, we developed an automated platform and compared two magnet configurations for cell separations. These more accurate and labor-saving magnet configurations allowed the lymphocytes to be tested in bioassays for rare antigen-specific T cells. The automated method succeeded at identifying 79% of patients with the rare PBLs of interest as compared with Ficoll's uniform failure. We validated improved upfront blood processing and show accurate detection of rare antigen-specific lymphocytes.Improving, automating and standardizing lymphocyte detections from whole blood may facilitate development of new cell-based biomarkers for human diseases. Improved upfront blood processes may lead to broad improvements in monitoring early trial outcome measurements in human clinical trials.

Novel automated blood separations validate whole cell biomarkers.

Science.gov (United States)

Burger, Douglas E; Wang, Limei; Ban, Liqin; Okubo, Yoshiaki; Kühtreiber, Willem M; Leichliter, Ashley K; Faustman, Denise L

2011-01-01

Progress in clinical trials in infectious disease, autoimmunity, and cancer is stymied by a dearth of successful whole cell biomarkers for peripheral blood lymphocytes (PBLs). Successful biomarkers could help to track drug effects at early time points in clinical trials to prevent costly trial failures late in development. One major obstacle is the inaccuracy of Ficoll density centrifugation, the decades-old method of separating PBLs from the abundant red blood cells (RBCs) of fresh blood samples. To replace the Ficoll method, we developed and studied a novel blood-based magnetic separation method. The magnetic method strikingly surpassed Ficoll in viability, purity and yield of PBLs. To reduce labor, we developed an automated platform and compared two magnet configurations for cell separations. These more accurate and labor-saving magnet configurations allowed the lymphocytes to be tested in bioassays for rare antigen-specific T cells. The automated method succeeded at identifying 79% of patients with the rare PBLs of interest as compared with Ficoll's uniform failure. We validated improved upfront blood processing and show accurate detection of rare antigen-specific lymphocytes. Improving, automating and standardizing lymphocyte detections from whole blood may facilitate development of new cell-based biomarkers for human diseases. Improved upfront blood processes may lead to broad improvements in monitoring early trial outcome measurements in human clinical trials.

Parameter Screening in Microfluidics Based Hydrodynamic Single-Cell Trapping

Directory of Open Access Journals (Sweden)

B. Deng

2014-01-01

Full Text Available Microfluidic cell-based arraying technology is widely used in the field of single-cell analysis. However, among developed devices, there is a compromise between cellular loading efficiencies and trapped cell densities, which deserves further analysis and optimization. To address this issue, the cell trapping efficiency of a microfluidic device with two parallel micro channels interconnected with cellular trapping sites was studied in this paper. By regulating channel inlet and outlet status, the microfluidic trapping structure can mimic key functioning units of previously reported devices. Numerical simulations were used to model this cellular trapping structure, quantifying the effects of channel on/off status and trapping structure geometries on the cellular trapping efficiency. Furthermore, the microfluidic device was fabricated based on conventional microfabrication and the cellular trapping efficiency was quantified in experiments. Experimental results showed that, besides geometry parameters, cellular travelling velocities and sizes also affected the single-cell trapping efficiency. By fine tuning parameters, more than 95% of trapping sites were taken by individual cells. This study may lay foundation in further studies of single-cell positioning in microfluidics and push forward the study of single-cell analysis.

Chip based single cell analysis for nanotoxicity assessment.

Science.gov (United States)

Shah, Pratikkumar; Kaushik, Ajeet; Zhu, Xuena; Zhang, Chengxiao; Li, Chen-Zhong

2014-05-07

Nanomaterials, because of their tunable properties and performances, have been utilized extensively in everyday life related consumable products and technology. On exposure, beyond the physiological range, nanomaterials cause health risks via affecting the function of organisms, genomic systems, and even the central nervous system. Thus, new analytical approaches for nanotoxicity assessment to verify the feasibility of nanomaterials for future use are in demand. The conventional analytical techniques, such as spectrophotometric assay-based techniques, usually require a lengthy and time-consuming process and often produce false positives, and often cannot be implemented at a single cell level measurement for studying cell behavior without interference from its surrounding environment. Hence, there is a demand for a precise, accurate, sensitive assessment for toxicity using single cells. Recently, due to the advantages of automation of fluids and minimization of human errors, the integration of a cell-on-a-chip (CoC) with a microfluidic system is in practice for nanotoxicity assessments. This review explains nanotoxicity and its assessment approaches with advantages/limitations and new approaches to overcome the confines of traditional techniques. Recent advances in nanotoxicity assessment using a CoC integrated with a microfluidic system are also discussed in this review, which may be of use for nanotoxicity assessment and diagnostics.

A fully automated primary screening system for the discovery of therapeutic antibodies directly from B cells.

Science.gov (United States)

Tickle, Simon; Howells, Louise; O'Dowd, Victoria; Starkie, Dale; Whale, Kevin; Saunders, Mark; Lee, David; Lightwood, Daniel

2015-04-01

For a therapeutic antibody to succeed, it must meet a range of potency, stability, and specificity criteria. Many of these characteristics are conferred by the amino acid sequence of the heavy and light chain variable regions and, for this reason, can be screened for during antibody selection. However, it is important to consider that antibodies satisfying all these criteria may be of low frequency in an immunized animal; for this reason, it is essential to have a mechanism that allows for efficient sampling of the immune repertoire. UCB's core antibody discovery platform combines high-throughput B cell culture screening and the identification and isolation of single, antigen-specific IgG-secreting B cells through a proprietary technique called the "fluorescent foci" method. Using state-of-the-art automation to facilitate primary screening, extremely efficient interrogation of the natural antibody repertoire is made possible; more than 1 billion immune B cells can now be screened to provide a useful starting point from which to identify the rare therapeutic antibody. This article will describe the design, construction, and commissioning of a bespoke automated screening platform and two examples of how it was used to screen for antibodies against two targets. © 2014 Society for Laboratory Automation and Screening.

AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES.

Science.gov (United States)

Kong, Jun; Wang, Fusheng; Teodoro, George; Liang, Yanhui; Zhu, Yangyang; Tucker-Burden, Carol; Brat, Daniel J

2015-04-01

A large number of cell-oriented cancer investigations require an effective and reliable cell segmentation method on three dimensional (3D) fluorescence microscopic images for quantitative analysis of cell biological properties. In this paper, we present a fully automated cell segmentation method that can detect cells from 3D fluorescence microscopic images. Enlightened by fluorescence imaging techniques, we regulated the image gradient field by gradient vector flow (GVF) with interpolated and smoothed data volume, and grouped voxels based on gradient modes identified by tracking GVF field. Adaptive thresholding was then applied to voxels associated with the same gradient mode where voxel intensities were enhanced by a multiscale cell filter. We applied the method to a large volume of 3D fluorescence imaging data of human brain tumor cells with (1) small cell false detection and missing rates for individual cells; and (2) trivial over and under segmentation incidences for clustered cells. Additionally, the concordance of cell morphometry structure between automated and manual segmentation was encouraging. These results suggest a promising 3D cell segmentation method applicable to cancer studies.

Optimizing wireless LAN for longwall coal mine automation

Energy Technology Data Exchange (ETDEWEB)

Hargrave, C.O.; Ralston, J.C.; Hainsworth, D.W. [Exploration & Mining Commonwealth Science & Industrial Research Organisation, Pullenvale, Qld. (Australia)

2007-01-15

A significant development in underground longwall coal mining automation has been achieved with the successful implementation of wireless LAN (WLAN) technology for communication on a longwall shearer. WIreless-FIdelity (Wi-Fi) was selected to meet the bandwidth requirements of the underground data network, and several configurations were installed on operating longwalls to evaluate their performance. Although these efforts demonstrated the feasibility of using WLAN technology in longwall operation, it was clear that new research and development was required in order to establish optimal full-face coverage. By undertaking an accurate characterization of the target environment, it has been possible to achieve great improvements in WLAN performance over a nominal Wi-Fi installation. This paper discusses the impact of Fresnel zone obstructions and multipath effects on radio frequency propagation and reports an optimal antenna and system configuration. Many of the lessons learned in the longwall case are immediately applicable to other underground mining operations, particularly wherever there is a high degree of obstruction from mining equipment.

Single cell adhesion assay using computer controlled micropipette.

Directory of Open Access Journals (Sweden)

Rita Salánki

Full Text Available Cell adhesion is a fundamental phenomenon vital for all multicellular organisms. Recognition of and adhesion to specific macromolecules is a crucial task of leukocytes to initiate the immune response. To gain statistically reliable information of cell adhesion, large numbers of cells should be measured. However, direct measurement of the adhesion force of single cells is still challenging and today's techniques typically have an extremely low throughput (5-10 cells per day. Here, we introduce a computer controlled micropipette mounted onto a normal inverted microscope for probing single cell interactions with specific macromolecules. We calculated the estimated hydrodynamic lifting force acting on target cells by the numerical simulation of the flow at the micropipette tip. The adhesion force of surface attached cells could be accurately probed by repeating the pick-up process with increasing vacuum applied in the pipette positioned above the cell under investigation. Using the introduced methodology hundreds of cells adhered to specific macromolecules were measured one by one in a relatively short period of time (∼30 min. We blocked nonspecific cell adhesion by the protein non-adhesive PLL-g-PEG polymer. We found that human primary monocytes are less adherent to fibrinogen than their in vitro differentiated descendants: macrophages and dendritic cells, the latter producing the highest average adhesion force. Validation of the here introduced method was achieved by the hydrostatic step-pressure micropipette manipulation technique. Additionally the result was reinforced in standard microfluidic shear stress channels. Nevertheless, automated micropipette gave higher sensitivity and less side-effect than the shear stress channel. Using our technique, the probed single cells can be easily picked up and further investigated by other techniques; a definite advantage of the computer controlled micropipette. Our experiments revealed the existence of a

Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

Science.gov (United States)

Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria

2014-08-30

Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

An automated cell-counting algorithm for fluorescently-stained cells in migration assays

Directory of Open Access Journals (Sweden)

Novielli Nicole M

2011-10-01

Full Text Available Abstract A cell-counting algorithm, developed in Matlab®, was created to efficiently count migrated fluorescently-stained cells on membranes from migration assays. At each concentration of cells used (10,000, and 100,000 cells, images were acquired at 2.5 ×, 5 ×, and 10 × objective magnifications. Automated cell counts strongly correlated to manual counts (r2 = 0.99, P

An automated image analysis framework for segmentation and division plane detection of single live Staphylococcus aureus cells which can operate at millisecond sampling time scales using bespoke Slimfield microscopy

Science.gov (United States)

Wollman, Adam J. M.; Miller, Helen; Foster, Simon; Leake, Mark C.

2016-10-01

Staphylococcus aureus is an important pathogen, giving rise to antimicrobial resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here we report an image analysis framework for automated detection and image segmentation of cells in S. aureus cell clusters, and explicit identification of their cell division planes. We use a new combination of several existing analytical tools of image analysis to detect cellular and subcellular morphological features relevant to cell division from millisecond time scale sampled images of live pathogens at a detection precision of single molecules. We demonstrate this approach using a fluorescent reporter GFP fused to the protein EzrA that localises to a mid-cell plane during division and is involved in regulation of cell size and division. This image analysis framework presents a valuable platform from which to study candidate new antimicrobials which target the cell division machinery, but may also have more general application in detecting morphologically complex structures of fluorescently labelled proteins present in clusters of other types of cells.

Clinical Utility of an Automated Instrument for Gram Staining Single Slides ▿

Science.gov (United States)

Baron, Ellen Jo; Mix, Samantha; Moradi, Wais

2010-01-01

Gram stains of 87 different clinical samples were prepared by the laboratory's conventional methods (automated or manual) and by a new single-slide-type automated staining instrument, GG&B AGS-1000. Gram stains from either heat- or methanol-fixed slides stained with the new instrument were easy to interpret, and results were essentially the same as those from the methanol-fixed slides prepared as a part of the routine workflow. This instrument is well suited to a rapid-response laboratory where Gram stain requests are commonly received on a stat basis. PMID:20410348

Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology.

Science.gov (United States)

Li, Qingli; Zhou, Mei; Liu, Hongying; Wang, Yiting; Guo, Fangmin

2015-12-01

Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.

Optimizing a Drone Network to Deliver Automated External Defibrillators.

Science.gov (United States)

Boutilier, Justin J; Brooks, Steven C; Janmohamed, Alyf; Byers, Adam; Buick, Jason E; Zhan, Cathy; Schoellig, Angela P; Cheskes, Sheldon; Morrison, Laurie J; Chan, Timothy C Y

2017-06-20

Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. We applied our model to 53 702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event. © 2017 American Heart Association, Inc.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images.

Science.gov (United States)

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.

Single Cell Assay for Analyzing Single Cell Exosome and Endocrine Secretion and Cancer Markers

Science.gov (United States)

Chiu, Yu-Jui

To understand the inhomogeneity of cells in biological systems, there is a growing demand for the capability to characterize the properties of individual single cells. Since single cell studies require continuous monitoring of the cell behaviors instead of a snapshot test at a single time point, an effective single-cell assay that can support time lapsed studies in a high throughput manner is desired. Most currently available single-cell technologies cannot provide proper environments to sustain cell growth and cannot provide, for appropriate cell types, proliferation of single cells and convenient, non-invasive tests of single cell behaviors from molecular markers. In this dissertation, I present a highly versatile single-cell assay that can accommodate different cellular types, enable easy and efficient single cell loading and culturing, and be suitable for the study of effects of in-vitro environmental factors in combination with drug screening. The salient features of the assay are the non-invasive collection and surveying of single cell secretions at different time points and massively parallel translocation of single cells by user defined criteria, producing very high compatibility to the downstream process such as single cell qPCR and sequencing. Above all, the acquired information is quantitative -- for example, one of the studies is measured by the number of exosomes each single cell secretes for a given time period. Therefore, our single-cell assay provides a convenient, low-cost, and enabling tool for quantitative, time lapsed studies of single cell properties.

Automated platform for designing multiple robot work cells

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Osman, N. S.; Rahman, M. A. A.; Rahman, A. A. Abdul; Kamsani, S. H.; Bali Mohamad, B. M.; Mohamad, E.; Zaini, Z. A.; Rahman, M. F. Ab; Mohamad Hatta, M. N. H.

2017-06-01

Designing the multiple robot work cells is very knowledge-intensive, intricate, and time-consuming process. This paper elaborates the development process of a computer-aided design program for generating the multiple robot work cells which offer a user-friendly interface. The primary purpose of this work is to provide a fast and easy platform for less cost and human involvement with minimum trial and errors adjustments. The automated platform is constructed based on the variant-shaped configuration concept with its mathematical model. A robot work cell layout, system components, and construction procedure of the automated platform are discussed in this paper where integration of these items will be able to automatically provide the optimum robot work cell design according to the information set by the user. This system is implemented on top of CATIA V5 software and utilises its Part Design, Assembly Design, and Macro tool. The current outcomes of this work provide a basis for future investigation in developing a flexible configuration system for the multiple robot work cells.

Optimization of spin-coated electrodes for electrolyte-supported solid oxide fuel cells

International Nuclear Information System (INIS)

Nobrega, Shayenne Diniz da; Monteiro, Natalia Kondo; Tabuti, Francisco; Fonseca, Fabio Coral; Florio, Daniel Zanetti de

2017-01-01

Electrodes for electrolyte-supported solid oxide fuel cells (SOFC’s) were fabricated by spin coating. Strontium-doped lanthanum manganite (LSM) cathode and nickel yttria-stabilized zirconia cermet anodes were synthesized and processed for enhanced deposition conditions. The influence of electrode microstructural parameters was investigated by a systematic experimental procedure aiming at optimized electrochemical performance of single cells. Polarization curves showed a strong dependence on both electrode thickness and sintering temperature. By a systematic control of such parameters, the performance of single cells was significantly enhanced due to decreasing of polarization resistance from 26 Ω cm² to 0.6 Ω cm² at 800°C. The results showed that spin-coated electrodes can be optimized for fast and cost effective fabrication of SOFCs. (author)

Optimization of spin-coated electrodes for electrolyte-supported solid oxide fuel cells

Energy Technology Data Exchange (ETDEWEB)

Nobrega, Shayenne Diniz da; Monteiro, Natalia Kondo; Tabuti, Francisco; Fonseca, Fabio Coral, E-mail: shaynnedn@hotmail.com, E-mail: nataliakm@usp.br, E-mail: fntabuti@ipen.br, E-mail: fabiocf@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN/SP), Sao Paulo, SP (Brazil); Florio, Daniel Zanetti de, E-mail: daniel.florio@ufabc.edu.br [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil)

2017-01-15

Electrodes for electrolyte-supported solid oxide fuel cells (SOFC’s) were fabricated by spin coating. Strontium-doped lanthanum manganite (LSM) cathode and nickel yttria-stabilized zirconia cermet anodes were synthesized and processed for enhanced deposition conditions. The influence of electrode microstructural parameters was investigated by a systematic experimental procedure aiming at optimized electrochemical performance of single cells. Polarization curves showed a strong dependence on both electrode thickness and sintering temperature. By a systematic control of such parameters, the performance of single cells was significantly enhanced due to decreasing of polarization resistance from 26 Ω cm² to 0.6 Ω cm² at 800°C. The results showed that spin-coated electrodes can be optimized for fast and cost effective fabrication of SOFCs. (author)

On the use of PGD for optimal control applied to automated fibre placement

Science.gov (United States)

Bur, N.; Joyot, P.

2017-10-01

Automated Fibre Placement (AFP) is an incipient manufacturing process for composite structures. Despite its concep-tual simplicity it involves many complexities related to the necessity of melting the thermoplastic at the interface tape-substrate, ensuring the consolidation that needs the diffusion of molecules and control the residual stresses installation responsible of the residual deformations of the formed parts. The optimisation of the process and the determination of the process window cannot be achieved in a traditional way since it requires a plethora of trials/errors or numerical simulations, because there are many parameters involved in the characterisation of the material and the process. Using reduced order modelling such as the so called Proper Generalised Decomposition method, allows the construction of multi-parametric solution taking into account many parameters. This leads to virtual charts that can be explored on-line in real time in order to perform process optimisation or on-line simulation-based control. Thus, for a given set of parameters, determining the power leading to an optimal temperature becomes easy. However, instead of controlling the power knowing the temperature field by particularizing an abacus, we propose here an approach based on optimal control: we solve by PGD a dual problem from heat equation and optimality criteria. To circumvent numerical issue due to ill-conditioned system, we propose an algorithm based on Uzawa's method. That way, we are able to solve the dual problem, setting the desired state as an extra-coordinate in the PGD framework. In a single computation, we get both the temperature field and the required heat flux to reach a parametric optimal temperature on a given zone.

Reliable single cell array CGH for clinical samples.

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Zbigniew T Czyż

Full Text Available BACKGROUND: Disseminated cancer cells (DCCs and circulating tumor cells (CTCs are extremely rare, but comprise the precursors cells of distant metastases or therapy resistant cells. The detailed molecular analysis of these cells may help to identify key events of cancer cell dissemination, metastatic colony formation and systemic therapy escape. METHODOLOGY/PRINCIPAL FINDINGS: Using the Ampli1™ whole genome amplification (WGA technology and high-resolution oligonucleotide aCGH microarrays we optimized conditions for the analysis of structural copy number changes. The protocol presented here enables reliable detection of numerical genomic alterations as small as 0.1 Mb in a single cell. Analysis of single cells from well-characterized cell lines and single normal cells confirmed the stringent quantitative nature of the amplification and hybridization protocol. Importantly, fixation and staining procedures used to detect DCCs showed no significant impact on the outcome of the analysis, proving the clinical usability of our method. In a proof-of-principle study we tracked the chromosomal changes of single DCCs over a full course of high-dose chemotherapy treatment by isolating and analyzing DCCs of an individual breast cancer patient at four different time points. CONCLUSIONS/SIGNIFICANCE: The protocol enables detailed genome analysis of DCCs and thereby assessment of the clonal evolution during the natural course of the disease and under selection pressures. The results from an exemplary patient provide evidence that DCCs surviving selective therapeutic conditions may be recruited from a pool of genomically less advanced cells, which display a stable subset of specific genomic alterations.

On the combination of molecular replacement and single-wavelength anomalous diffraction phasing for automated structure determination

International Nuclear Information System (INIS)

Panjikar, Santosh; Parthasarathy, Venkataraman; Lamzin, Victor S.; Weiss, Manfred S.; Tucker, Paul A.

2009-01-01

The combination of molecular replacement and single-wavelength anomalous diffraction improves the performance of automated structure determination with Auto-Rickshaw. A combination of molecular replacement and single-wavelength anomalous diffraction phasing has been incorporated into the automated structure-determination platform Auto-Rickshaw. The complete MRSAD procedure includes molecular replacement, model refinement, experimental phasing, phase improvement and automated model building. The improvement over the standard SAD or MR approaches is illustrated by ten test cases taken from the JCSG diffraction data-set database. Poor MR or SAD phases with phase errors larger than 70° can be improved using the described procedure and a large fraction of the model can be determined in a purely automatic manner from X-ray data extending to better than 2.6 Å resolution

Automated Cell Enrichment of Cytomegalovirus-specific T cells for Clinical Applications using the Cytokine-capture System.

Science.gov (United States)

Kumaresan, Pappanaicken; Figliola, Mathew; Moyes, Judy S; Huls, M Helen; Tewari, Priti; Shpall, Elizabeth J; Champlin, Richard; Cooper, Laurence J N

2015-10-05

The adoptive transfer of pathogen-specific T cells can be used to prevent and treat opportunistic infections such as cytomegalovirus (CMV) infection occurring after allogeneic hematopoietic stem-cell transplantation. Viral-specific T cells from allogeneic donors, including third party donors, can be propagated ex vivo in compliance with current good manufacturing practice (cGMP), employing repeated rounds of antigen-driven stimulation to selectively propagate desired T cells. The identification and isolation of antigen-specific T cells can also be undertaken based upon the cytokine capture system of T cells that have been activated to secrete gamma-interferon (IFN-γ). However, widespread human application of the cytokine capture system (CCS) to help restore immunity has been limited as the production process is time-consuming and requires a skilled operator. The development of a second-generation cell enrichment device such as CliniMACS Prodigy now enables investigators to generate viral-specific T cells using an automated, less labor-intensive system. This device separates magnetically labeled cells from unlabeled cells using magnetic activated cell sorting technology to generate clinical-grade products, is engineered as a closed system and can be accessed and operated on the benchtop. We demonstrate the operation of this new automated cell enrichment device to manufacture CMV pp65-specific T cells obtained from a steady-state apheresis product obtained from a CMV seropositive donor. These isolated T cells can then be directly infused into a patient under institutional and federal regulatory supervision. All the bio-processing steps including removal of red blood cells, stimulation of T cells, separation of antigen-specific T cells, purification, and washing are fully automated. Devices such as this raise the possibility that T cells for human application can be manufactured outside of dedicated good manufacturing practice (GMP) facilities and instead be produced

A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters.

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Daniel H Rapoport

Full Text Available Automated microscopy is currently the only method to non-invasively and label-free observe complex multi-cellular processes, such as cell migration, cell cycle, and cell differentiation. Extracting biological information from a time-series of micrographs requires each cell to be recognized and followed through sequential microscopic snapshots. Although recent attempts to automatize this process resulted in ever improving cell detection rates, manual identification of identical cells is still the most reliable technique. However, its tedious and subjective nature prevented tracking from becoming a standardized tool for the investigation of cell cultures. Here, we present a novel method to accomplish automated cell tracking with a reliability comparable to manual tracking. Previously, automated cell tracking could not rival the reliability of manual tracking because, in contrast to the human way of solving this task, none of the algorithms had an independent quality control mechanism; they missed validation. Thus, instead of trying to improve the cell detection or tracking rates, we proceeded from the idea to automatically inspect the tracking results and accept only those of high trustworthiness, while rejecting all other results. This validation algorithm works independently of the quality of cell detection and tracking through a systematic search for tracking errors. It is based only on very general assumptions about the spatiotemporal contiguity of cell paths. While traditional tracking often aims to yield genealogic information about single cells, the natural outcome of a validated cell tracking algorithm turns out to be a set of complete, but often unconnected cell paths, i.e. records of cells from mitosis to mitosis. This is a consequence of the fact that the validation algorithm takes complete paths as the unit of rejection/acceptance. The resulting set of complete paths can be used to automatically extract important biological parameters

Development of an automated chip culture system with integrated on-line monitoring for maturation culture of retinal pigment epithelial cells

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Mee-Hae Kim

2017-10-01

Full Text Available In cell manufacturing, the establishment of a fully automated, microfluidic, cell culture system that can be used for long-term cell cultures, as well as for process optimization is highly desirable. This study reports the development of a novel chip bioreactor system that can be used for automated long-term maturation cultures of retinal pigment epithelial (RPE cells. The system consists of an incubation unit, a medium supply unit, a culture observation unit, and a control unit. In the incubation unit, the chip contains a closed culture vessel (2.5 mm diameter, working volume 9.1 μL, which can be set to 37 °C and 5% CO2, and uses a gas-permeable resin (poly- dimethylsiloxane as the vessel wall. RPE cells were seeded at 5.0 × 104 cells/cm2 and the medium was changed every day by introducing fresh medium using the medium supply unit. Culture solutions were stored either in the refrigerator or the freezer, and fresh medium was prepared before any medium change by warming to 37 °C and mixing. Automated culture was allowed to continue for 30 days to allow maturation of the RPE cells. This chip culture system allows for the long-term, bubble-free, culture of RPE cells, while also being able to observe cells in order to elucidate their cell morphology or show the presence of tight junctions. This culture system, along with an integrated on-line monitoring system, can therefore be applied to long-term cultures of RPE cells, and should contribute to process control in RPE cell manufacturing.

Comparison of semi-automated center-dot and fully automated endothelial cell analyses from specular microscopy images.

Science.gov (United States)

Maruoka, Sachiko; Nakakura, Shunsuke; Matsuo, Naoko; Yoshitomi, Kayo; Katakami, Chikako; Tabuchi, Hitoshi; Chikama, Taiichiro; Kiuchi, Yoshiaki

2017-10-30

To evaluate two specular microscopy analysis methods across different endothelial cell densities (ECDs). Endothelial images of one eye from each of 45 patients were taken by using three different specular microscopes (three replicates each). To determine the consistency of the center-dot method, we compared SP-6000 and SP-2000P images. CME-530 and SP-6000 images were compared to assess the consistency of the fully automated method. The SP-6000 images from the two methods were compared. Intraclass correlation coefficients (ICCs) for the three measurements were calculated, and parametric multiple comparisons tests and Bland-Altman analysis were performed. The ECD mean value was 2425 ± 883 (range 516-3707) cells/mm 2 . ICC values were > 0.9 for all three microscopes for ECD, but the coefficients of variation (CVs) were 0.3-0.6. For ECD measurements, Bland-Altman analysis revealed that the mean difference was 42 cells/mm 2 between the SP-2000P and SP-6000 for the center-dot method; 57 cells/mm 2 between the SP-6000 measurements from both methods; and -5 cells/mm 2 between the SP-6000 and CME-530 for the fully automated method (95% limits of agreement: - 201 to 284 cell/mm 2 , - 410 to 522 cells/mm 2 , and - 327 to 318 cells/mm 2 , respectively). For CV measurements, the mean differences were - 3, - 12, and 13% (95% limits of agreement - 18 to 11, - 26 to 2, and - 5 to 32%, respectively). Despite using three replicate measurements, the precision of the center-dot method with the SP-2000P and SP-6000 software was only ± 10% for ECD data and was even worse for the fully automated method. Japan Clinical Trials Register ( http://www.umin.ac.jp/ctr/index/htm9 ) number UMIN 000015236.

Comparison of manual & automated analysis methods for corneal endothelial cell density measurements by specular microscopy.

Science.gov (United States)

Huang, Jianyan; Maram, Jyotsna; Tepelus, Tudor C; Modak, Cristina; Marion, Ken; Sadda, SriniVas R; Chopra, Vikas; Lee, Olivia L

2017-08-07

To determine the reliability of corneal endothelial cell density (ECD) obtained by automated specular microscopy versus that of validated manual methods and factors that predict such reliability. Sharp central images from 94 control and 106 glaucomatous eyes were captured with Konan specular microscope NSP-9900. All images were analyzed by trained graders using Konan CellChek Software, employing the fully- and semi-automated methods as well as Center Method. Images with low cell count (input cells number <100) and/or guttata were compared with the Center and Flex-Center Methods. ECDs were compared and absolute error was used to assess variation. The effect on ECD of age, cell count, cell size, and cell size variation was evaluated. No significant difference was observed between the Center and Flex-Center Methods in corneas with guttata (p=0.48) or low ECD (p=0.11). No difference (p=0.32) was observed in ECD of normal controls <40 yrs old between the fully-automated method and manual Center Method. However, in older controls and glaucomatous eyes, ECD was overestimated by the fully-automated method (p=0.034) and semi-automated method (p=0.025) as compared to manual method. Our findings show that automated analysis significantly overestimates ECD in the eyes with high polymegathism and/or large cell size, compared to the manual method. Therefore, we discourage reliance upon the fully-automated method alone to perform specular microscopy analysis, particularly if an accurate ECD value is imperative. Copyright © 2017. Published by Elsevier España, S.L.U.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images.

Directory of Open Access Journals (Sweden)

Yuliang Wang

Full Text Available Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.

Direct Correlation between Motile Behavior and Protein Abundance in Single Cells.

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Yann S Dufour

2016-09-01

Full Text Available Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB at different levels, we quantitatively mapped motile phenotype (tumble bias to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.

Digital microfluidics for automated hanging drop cell spheroid culture.

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Aijian, Andrew P; Garrell, Robin L

2015-06-01

Cell spheroids are multicellular aggregates, grown in vitro, that mimic the three-dimensional morphology of physiological tissues. Although there are numerous benefits to using spheroids in cell-based assays, the adoption of spheroids in routine biomedical research has been limited, in part, by the tedious workflow associated with spheroid formation and analysis. Here we describe a digital microfluidic platform that has been developed to automate liquid-handling protocols for the formation, maintenance, and analysis of multicellular spheroids in hanging drop culture. We show that droplets of liquid can be added to and extracted from through-holes, or "wells," and fabricated in the bottom plate of a digital microfluidic device, enabling the formation and assaying of hanging drops. Using this digital microfluidic platform, spheroids of mouse mesenchymal stem cells were formed and maintained in situ for 72 h, exhibiting good viability (>90%) and size uniformity (% coefficient of variation <10% intraexperiment, <20% interexperiment). A proof-of-principle drug screen was performed on human colorectal adenocarcinoma spheroids to demonstrate the ability to recapitulate physiologically relevant phenomena such as insulin-induced drug resistance. With automatable and flexible liquid handling, and a wide range of in situ sample preparation and analysis capabilities, the digital microfluidic platform provides a viable tool for automating cell spheroid culture and analysis. © 2014 Society for Laboratory Automation and Screening.

Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.

Science.gov (United States)

Urtnasan, Erdenebayar; Park, Jong-Uk; Joo, Eun-Yeon; Lee, Kyoung-Joung

2018-04-23

In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers including activation, pooling, and dropout layers. One-dimensional (1D) convolution, rectified linear units (ReLU), and max pooling were applied to the convolution, activation, and pooling layers, respectively. For training and evaluation of the CNN model, a single-lead ECG dataset was collected from 82 subjects with OSA and was divided into training (including data from 63 patients with 34,281 events) and testing (including data from 19 patients with 8571 events) datasets. Using this CNN model, a precision of 0.99%, a recall of 0.99%, and an F 1 -score of 0.99% were attained with the training dataset; these values were all 0.96% when the CNN was applied to the testing dataset. These results show that the proposed CNN model can be used to detect OSA accurately on the basis of a single-lead ECG. Ultimately, this CNN model may be used as a screening tool for those suspected to suffer from OSA.

Labeling of mesenchymal stem cells for MRI with single-cell sensitivity

Directory of Open Access Journals (Sweden)

Ariza de Schellenberger A

2016-04-01

Full Text Available Angela Ariza de Schellenberger,1 Harald Kratz,1 Tracy D Farr,2,3 Norbert Löwa,4 Ralf Hauptmann,1 Susanne Wagner,1 Matthias Taupitz,1 Jörg Schnorr,1 Eyk A Schellenberger1 1Department of Radiology, 2Department of Experimental Neurology, Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany; 3School of Life Sciences, University of Nottingham, Medical School, Nottingham, UK; 4Department of Biomagnetic Signals, Physikalisch-Technische Bundesanstalt Berlin, Berlin, Germany Abstract: Sensitive cell detection by magnetic resonance imaging (MRI is an important tool for the development of cell therapies. However, clinically approved contrast agents that allow single-cell detection are currently not available. Therefore, we compared very small iron oxide nanoparticles (VSOP and new multicore carboxymethyl dextran-coated iron oxide nanoparticles (multicore particles, MCP designed by our department for magnetic particle imaging (MPI with discontinued Resovist® regarding their suitability for detection of single mesenchymal stem cells (MSC by MRI. We achieved an average intracellular nanoparticle (NP load of >10 pg Fe per cell without the use of transfection agents. NP loading did not lead to significantly different results in proliferation, colony formation, and multilineage in vitro differentiation assays in comparison to controls. MRI allowed single-cell detection using VSOP, MCP, and Resovist® in conjunction with high-resolution T2*-weighted imaging at 7 T with postprocessing of phase images in agarose cell phantoms and in vivo after delivery of 2,000 NP-labeled MSC into mouse brains via the left carotid artery. With optimized labeling conditions, a detection rate of ~45% was achieved; however, the experiments were limited by nonhomogeneous NP loading of the MSC population. Attempts should be made to achieve better cell separation for homogeneous NP loading and to thus improve NP

The optimal number, type and location of devices in automation of electrical distribution networks

Directory of Open Access Journals (Sweden)

Popović Željko N.

2015-01-01

Full Text Available This paper presents the mixed integer linear programming based model for determining optimal number, type and location of remotely controlled and supervised devices in distribution networks in the presence of distributed generators. The proposed model takes into consideration a number of different devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised and local fault passage indicators along with the following: expected outage cost to consumers and producers due to momentary and long-term interruptions, automated device expenses (capital investment, installation, and annual operation and maintenance costs, number and expenses of crews involved in the isolation and restoration process. Furthermore, the other possible benefits of each of automated device are also taken into account (e.g., benefits due to decreasing the cost of switching operations in normal conditions. The obtained numerical results emphasize the importance of consideration of different types of automation devices simultaneously. They also show that the proposed approach have a potential to improve the process of determining of the best automation strategy in real life distribution networks.

Dynamic single-cell NAD(P)H measurement reveals oscillatory metabolism throughout the E. coli cell division cycle.

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Zhang, Zheng; Milias-Argeitis, Andreas; Heinemann, Matthias

2018-02-01

Recent work has shown that metabolism between individual bacterial cells in an otherwise isogenetic population can be different. To investigate such heterogeneity, experimental methods to zoom into the metabolism of individual cells are required. To this end, the autofluoresence of the redox cofactors NADH and NADPH offers great potential for single-cell dynamic NAD(P)H measurements. However, NAD(P)H excitation requires UV light, which can cause cell damage. In this work, we developed a method for time-lapse NAD(P)H imaging in single E. coli cells. Our method combines a setup with reduced background emission, UV-enhanced microscopy equipment and optimized exposure settings, overall generating acceptable NAD(P)H signals from single cells, with minimal negative effect on cell growth. Through different experiments, in which we perturb E. coli's redox metabolism, we demonstrated that the acquired fluorescence signal indeed corresponds to NAD(P)H. Using this new method, for the first time, we report that intracellular NAD(P)H levels oscillate along the bacterial cell division cycle. The developed method for dynamic measurement of NAD(P)H in single bacterial cells will be an important tool to zoom into metabolism of individual cells.

High-Throughput Screening Enhances Kidney Organoid Differentiation from Human Pluripotent Stem Cells and Enables Automated Multidimensional Phenotyping.

Science.gov (United States)

Czerniecki, Stefan M; Cruz, Nelly M; Harder, Jennifer L; Menon, Rajasree; Annis, James; Otto, Edgar A; Gulieva, Ramila E; Islas, Laura V; Kim, Yong Kyun; Tran, Linh M; Martins, Timothy J; Pippin, Jeffrey W; Fu, Hongxia; Kretzler, Matthias; Shankland, Stuart J; Himmelfarb, Jonathan; Moon, Randall T; Paragas, Neal; Freedman, Benjamin S

2018-05-15

Organoids derived from human pluripotent stem cells are a potentially powerful tool for high-throughput screening (HTS), but the complexity of organoid cultures poses a significant challenge for miniaturization and automation. Here, we present a fully automated, HTS-compatible platform for enhanced differentiation and phenotyping of human kidney organoids. The entire 21-day protocol, from plating to differentiation to analysis, can be performed automatically by liquid-handling robots, or alternatively by manual pipetting. High-content imaging analysis reveals both dose-dependent and threshold effects during organoid differentiation. Immunofluorescence and single-cell RNA sequencing identify previously undetected parietal, interstitial, and partially differentiated compartments within organoids and define conditions that greatly expand the vascular endothelium. Chemical modulation of toxicity and disease phenotypes can be quantified for safety and efficacy prediction. Screening in gene-edited organoids in this system reveals an unexpected role for myosin in polycystic kidney disease. Organoids in HTS formats thus establish an attractive platform for multidimensional phenotypic screening. Copyright © 2018 Elsevier Inc. All rights reserved.

Automated Manufacturing of Potent CD20-Directed Chimeric Antigen Receptor T Cells for Clinical Use.

Science.gov (United States)

Lock, Dominik; Mockel-Tenbrinck, Nadine; Drechsel, Katharina; Barth, Carola; Mauer, Daniela; Schaser, Thomas; Kolbe, Carolin; Al Rawashdeh, Wael; Brauner, Janina; Hardt, Olaf; Pflug, Natali; Holtick, Udo; Borchmann, Peter; Assenmacher, Mario; Kaiser, Andrew

2017-10-01

The clinical success of gene-engineered T cells expressing a chimeric antigen receptor (CAR), as manifested in several clinical trials for the treatment of B cell malignancies, warrants the development of a simple and robust manufacturing procedure capable of reducing to a minimum the challenges associated with its complexity. Conventional protocols comprise many open handling steps, are labor intensive, and are difficult to upscale for large numbers of patients. Furthermore, extensive training of personnel is required to avoid operator variations. An automated current Good Manufacturing Practice-compliant process has therefore been developed for the generation of gene-engineered T cells. Upon installation of the closed, single-use tubing set on the CliniMACS Prodigy™, sterile welding of the starting cell product, and sterile connection of the required reagents, T cells are magnetically enriched, stimulated, transduced using lentiviral vectors, expanded, and formulated. Starting from healthy donor (HD) or lymphoma or melanoma patient material (PM), the robustness and reproducibility of the manufacturing of anti-CD20 specific CAR T cells were verified. Independent of the starting material, operator, or device, the process consistently yielded a therapeutic dose of highly viable CAR T cells. Interestingly, the formulated product obtained with PM was comparable to that of HD with respect to cell composition, phenotype, and function, even though the starting material differed significantly. Potent antitumor reactivity of the produced anti-CD20 CAR T cells was shown in vitro as well as in vivo. In summary, the automated T cell transduction process meets the requirements for clinical manufacturing that the authors intend to use in two separate clinical trials for the treatment of melanoma and B cell lymphoma.

Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow.

Science.gov (United States)

Stockton, David B; Santamaria, Fidel

2017-10-01

We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI's feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.

Real-time direct cell concentration and viability determination using a fully automated microfluidic platform for standalone process monitoring

DEFF Research Database (Denmark)

Rodrigues de Sousa Nunes, Pedro André; Kjaerulff, S.; Dufva, Martin

2015-01-01

system performance by monitoring in real time the cell concentration and viability of yeast extracted directly from an in-house made bioreactor. This is the first demonstration of using the Dean drag force, generated due to the implementation of a curved microchannel geometry in conjunction with high...... flow rates, to promote passive mixing of cell samples and thus homogenization of the diluted cell plug. The autonomous operation of the fluidics furthermore allows implementation of intelligent protocols for administering air bubbles from the bioreactor in the microfluidic system, so...... and thereby ensure optimal cell production, by prolonging the fermentation cycle and increasing the bioreactor output. In this work, we report on the development of a fully automated microfluidic system capable of extracting samples directly from a bioreactor, diluting the sample, staining the cells...

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

Science.gov (United States)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

HT-COMET: a novel automated approach for high throughput assessment of human sperm chromatin quality

Science.gov (United States)

Albert, Océane; Reintsch, Wolfgang E.; Chan, Peter; Robaire, Bernard

2016-01-01

STUDY QUESTION Can we make the comet assay (single-cell gel electrophoresis) for human sperm a more accurate and informative high throughput assay? SUMMARY ANSWER We developed a standardized automated high throughput comet (HT-COMET) assay for human sperm that improves its accuracy and efficiency, and could be of prognostic value to patients in the fertility clinic. WHAT IS KNOWN ALREADY The comet assay involves the collection of data on sperm DNA damage at the level of the single cell, allowing the use of samples from severe oligozoospermic patients. However, this makes comet scoring a low throughput procedure that renders large cohort analyses tedious. Furthermore, the comet assay comes with an inherent vulnerability to variability. Our objective is to develop an automated high throughput comet assay for human sperm that will increase both its accuracy and efficiency. STUDY DESIGN, SIZE, DURATION The study comprised two distinct components: a HT-COMET technical optimization section based on control versus DNAse treatment analyses (n = 3–5), and a cross-sectional study on 123 men presenting to a reproductive center with sperm concentrations categorized as severe oligozoospermia, oligozoospermia or normozoospermia. PARTICIPANTS/MATERIALS, SETTING, METHODS Sperm chromatin quality was measured using the comet assay: on classic 2-well slides for software comparison; on 96-well slides for HT-COMET optimization; after exposure to various concentrations of a damage-inducing agent, DNAse, using HT-COMET; on 123 subjects with different sperm concentrations using HT-COMET. Data from the 123 subjects were correlated to classic semen quality parameters and plotted as single-cell data in individual DNA damage profiles. MAIN RESULTS AND THE ROLE OF CHANCE We have developed a standard automated HT-COMET procedure for human sperm. It includes automated scoring of comets by a fully integrated high content screening setup that compares well with the most commonly used semi

Physics of automated driving in framework of three-phase traffic theory.

Science.gov (United States)

Kerner, Boris S

2018-04-01

We have revealed physical features of automated driving in the framework of the three-phase traffic theory for which there is no fixed time headway to the preceding vehicle. A comparison with the classical model approach to automated driving for which an automated driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that automated driving in the framework of the three-phase traffic theory can exhibit the following advantages in comparison with the classical model of automated driving: (i) The absence of string instability. (ii) Considerably smaller speed disturbances at road bottlenecks. (iii) Automated driving vehicles based on the three-phase theory can decrease the probability of traffic breakdown at the bottleneck in mixed traffic flow consisting of human driving and automated driving vehicles; on the contrary, even a single automated driving vehicle based on the classical approach can provoke traffic breakdown at the bottleneck in mixed traffic flow.

Physics of automated driving in framework of three-phase traffic theory

Science.gov (United States)

Kerner, Boris S.

2018-04-01

We have revealed physical features of automated driving in the framework of the three-phase traffic theory for which there is no fixed time headway to the preceding vehicle. A comparison with the classical model approach to automated driving for which an automated driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that automated driving in the framework of the three-phase traffic theory can exhibit the following advantages in comparison with the classical model of automated driving: (i) The absence of string instability. (ii) Considerably smaller speed disturbances at road bottlenecks. (iii) Automated driving vehicles based on the three-phase theory can decrease the probability of traffic breakdown at the bottleneck in mixed traffic flow consisting of human driving and automated driving vehicles; on the contrary, even a single automated driving vehicle based on the classical approach can provoke traffic breakdown at the bottleneck in mixed traffic flow.

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy.

Science.gov (United States)

Medyukhina, Anna; Meyer, Tobias; Schmitt, Michael; Romeike, Bernd F M; Dietzek, Benjamin; Popp, Jürgen

2012-11-01

Nonlinear optical (NLO) imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or two photon excited fluorescence (TPEF) show great potential for biomedical imaging. In order to facilitate the diagnostic process based on NLO imaging, there is need for an automated calculation of quantitative values such as cell density, nucleus-to-cytoplasm ratio, average nuclear size. Extraction of these parameters is helpful for the histological assessment in general and specifically e.g. for the determination of tumor grades. This requires an accurate image segmentation and detection of locations and boundaries of cells and nuclei. Here we present an image processing approach for the detection of nuclei and cells in co-registered TPEF and CARS images. The algorithm developed utilizes the gray-scale information for the detection of the nuclei locations and the gradient information for the delineation of the nuclear and cellular boundaries. The approach reported is capable for an automated segmentation of cells and nuclei in multimodal TPEF-CARS images of human brain tumor samples. The results are important for the development of NLO microscopy into a clinically relevant diagnostic tool. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Experimental determination of optimal clamping torque for AB-PEM Fuel cell

Directory of Open Access Journals (Sweden)

Noor Ul Hassan

2016-04-01

Full Text Available Polymer electrolyte Membrane (PEM fuel cell is an electrochemical device producing electricity by the reaction of hydrogen and oxygen without combustion. PEM fuel cell stack is provided with an appropriate clamping torque to prevent leakage of reactant gases and to minimize the contact resistance between gas diffusion media (GDL and bipolar plates. GDL porous structure and gas permeability is directly affected by the compaction pressure which, consequently, drastically change the fuel cell performance. Various efforts were made to determine the optimal compaction pressure and pressure distributions through simulations and experimentation. Lower compaction pressure results in increase of contact resistance and also chances of leakage. On the other hand, higher compaction pressure decreases the contact resistance but also narrows down the diffusion path for mass transfer from gas channels to the catalyst layers, consequently, lowering cell performance. The optimal cell performance is related to the gasket thickness and compression pressure on GDL. Every stack has a unique assembly pressure due to differences in fuel cell components material and stack design. Therefore, there is still need to determine the optimal torque value for getting the optimal cell performance. This study has been carried out in continuation of deve­lopment of Air breathing PEM fuel cell for small Unmanned Aerial Vehicle (UAV application. Compaction pressure at minimum contact resistance was determined and clamping torque value was calcu­la­ted accordingly. Single cell performance tests were performed at five different clamping torque values i.e 0.5, 1.0, 1.5, 2.0 and 2.5 N m, for achieving optimal cell per­formance. Clamping pressure distribution tests were also performed at these torque values to verify uniform pressure distribution at optimal torque value. Experimental and theoretical results were compared for making inferences about optimal cell perfor­man­ce. A

Plug-and-play monitoring and performance optimization for industrial automation processes

CERN Document Server

Luo, Hao

2017-01-01

Dr.-Ing. Hao Luo demonstrates the developments of advanced plug-and-play (PnP) process monitoring and control systems for industrial automation processes. With aid of the so-called Youla parameterization, a novel PnP process monitoring and control architecture (PnP-PMCA) with modularized components is proposed. To validate the developments, a case study on an industrial rolling mill benchmark is performed, and the real-time implementation on a laboratory brushless DC motor is presented. Contents PnP Process Monitoring and Control Architecture Real-Time Configuration Techniques for PnP Process Monitoring Real-Time Configuration Techniques for PnP Performance Optimization Benchmark Study and Real-Time Implementation Target Groups Researchers and students of Automation and Control Engineering Practitioners in the area of Industrial and Production Engineering The Author Hao Luo received the Ph.D. degree at the Institute for Automatic Control and Complex Systems (AKS) at the University of Duisburg-Essen, Germany, ...

Automated synthesis of photovoltaic-quality colloidal quantum dots using separate nucleation and growth stages

KAUST Repository

Pan, Jun

2013-11-26

As colloidal quantum dot (CQD) optoelectronic devices continue to improve, interest grows in the scaled-up and automated synthesis of high-quality materials. Unfortunately, all reports of record-performance CQD photovoltaics have been based on small-scale batch syntheses. Here we report a strategy for flow reactor synthesis of PbS CQDs and prove that it leads to solar cells having performance similar to that of comparable batch-synthesized nanoparticles. Specifically, we find that, only when using a dual-temperature-stage flow reactor synthesis reported herein, are the CQDs of sufficient quality to achieve high performance. We use a kinetic model to explain and optimize the nucleation and growth processes in the reactor. Compared to conventional single-stage flow-synthesized CQDs, we achieve superior quality nanocrystals via the optimized dual-stage reactor, with high photoluminescence quantum yield (50%) and narrow full width-half-maximum. The dual-stage flow reactor approach, with its versatility and rapid screening of multiple parameters, combined with its efficient materials utilization, offers an attractive path to automated synthesis of CQDs for photovoltaics and, more broadly, active optoelectronics. © 2013 American Chemical Society.

Single Cell Oncogenesis

Science.gov (United States)

Lu, Xin

It is believed that cancer originates from a single cell that has gone through generations of evolution of genetic and epigenetic changes that associate with the hallmarks of cancer. In some cancers such as various types of leukemia, cancer is clonal. Yet in other cancers like glioblastoma (GBM), there is tremendous tumor heterogeneity that is likely to be caused by simultaneous evolution of multiple subclones within the same tissue. It is obvious that understanding how a single cell develops into a clonal tumor upon genetic alterations, at molecular and cellular levels, holds the key to the real appreciation of tumor etiology and ultimate solution for therapeutics. Surprisingly very little is known about the process of spontaneous tumorigenesis from single cells in human or vertebrate animal models. The main reason is the lack of technology to track the natural process of single cell changes from a homeostatic state to a progressively cancerous state. Recently, we developed a patented compound, photoactivatable (''caged'') tamoxifen analogue 4-OHC and associated technique called optochemogenetic switch (OCG switch), which we believe opens the opportunity to address this urgent biological as well as clinical question about cancer. We propose to combine OCG switch with genetically engineered mouse models of head and neck squamous cell carcinoma and high grade astrocytoma (including GBM) to study how single cells, when transformed through acute loss of tumor suppressor genes PTEN and TP53 and gain of oncogenic KRAS, can develop into tumor colonies with cellular and molecular heterogeneity in these tissues. The abstract is for my invited talk in session ``Beyond Darwin: Evolution in Single Cells'' 3/18/2016 11:15 AM.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

Science.gov (United States)

Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

Directory of Open Access Journals (Sweden)

Jenny Jeong

Full Text Available Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

Science.gov (United States)

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image. Copyright © 2018 Elsevier B.V. All rights reserved.

Low-dose DNA damage and replication stress responses quantified by optimized automated single-cell image analysis

DEFF Research Database (Denmark)

Mistrik, Martin; Oplustilova, Lenka; Lukas, Jiri

2009-01-01

sensitive, quantitative, rapid and simple fluorescence image analysis in thousands of adherent cells per day. Sensitive DNA breakage estimation through analysis of phosphorylated histone H2AX (gamma-H2AX), and homologous recombination (HR) assessed by a new RPA/Rad51 dual-marker approach illustrate...

Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm

Directory of Open Access Journals (Sweden)

I. Hameem Shanavas

2014-01-01

Full Text Available In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.

Proposal for automated transformations on single-photon multipath qudits

Science.gov (United States)

Baldijão, R. D.; Borges, G. F.; Marques, B.; Solís-Prosser, M. A.; Neves, L.; Pádua, S.

2017-09-01

We propose a method for implementing automated state transformations on single-photon multipath qudits encoded in a one-dimensional transverse spatial domain. It relies on transferring the encoding from this domain to the orthogonal one by applying a spatial phase modulation with diffraction gratings, merging all the initial propagation paths by using a stable interferometric network, and filtering out the unwanted diffraction orders. The automation feature is attained by utilizing a programmable phase-only spatial light modulator (SLM) where properly designed diffraction gratings displayed on its screen will implement the desired transformations, including, among others, projections, permutations, and random operations. We discuss the losses in the process which is, in general, inherently nonunitary. Some examples of transformations are presented and, considering a realistic scenario, we analyze how they will be affected by the pixelated structure of the SLM screen. The method proposed here enables one to implement much more general transformations on multipath qudits than is possible with a SLM alone operating in the diagonal basis of which-path states. Therefore, it will extend the range of applicability for this encoding in high-dimensional quantum information and computing protocols as well as fundamental studies in quantum theory.

A novel method for detection of phosphorylation in single cells by surface enhanced Raman scattering (SERS using composite organic-inorganic nanoparticles (COINs.

Directory of Open Access Journals (Sweden)

Catherine M Shachaf

Full Text Available Detection of single cell epitopes has been a mainstay of immunophenotyping for over three decades, primarily using fluorescence techniques for quantitation. Fluorescence has broad overlapping spectra, limiting multiplexing abilities.To expand upon current detection systems, we developed a novel method for multi-color immuno-detection in single cells using "Composite Organic-Inorganic Nanoparticles" (COINs Raman nanoparticles. COINs are Surface-Enhanced Raman Scattering (SERS nanoparticles, with unique Raman spectra. To measure Raman spectra in single cells, we constructed an automated, compact, low noise and sensitive Raman microscopy device (Integrated Raman BioAnalyzer. Using this technology, we detected proteins expressed on the surface in single cells that distinguish T-cells among human blood cells. Finally, we measured intracellular phosphorylation of Stat1 (Y701 and Stat6 (Y641, with results comparable to flow cytometry.Thus, we have demonstrated the practicality of applying COIN nanoparticles for measuring intracellular phosphorylation, offering new possibilities to expand on the current fluorescent technology used for immunoassays in single cells.

A novel method for detection of phosphorylation in single cells by surface enhanced Raman scattering (SERS) using composite organic-inorganic nanoparticles (COINs).

Science.gov (United States)

Shachaf, Catherine M; Elchuri, Sailaja V; Koh, Ai Leen; Zhu, Jing; Nguyen, Lienchi N; Mitchell, Dennis J; Zhang, Jingwu; Swartz, Kenneth B; Sun, Lei; Chan, Selena; Sinclair, Robert; Nolan, Garry P

2009-01-01

Detection of single cell epitopes has been a mainstay of immunophenotyping for over three decades, primarily using fluorescence techniques for quantitation. Fluorescence has broad overlapping spectra, limiting multiplexing abilities. To expand upon current detection systems, we developed a novel method for multi-color immuno-detection in single cells using "Composite Organic-Inorganic Nanoparticles" (COINs) Raman nanoparticles. COINs are Surface-Enhanced Raman Scattering (SERS) nanoparticles, with unique Raman spectra. To measure Raman spectra in single cells, we constructed an automated, compact, low noise and sensitive Raman microscopy device (Integrated Raman BioAnalyzer). Using this technology, we detected proteins expressed on the surface in single cells that distinguish T-cells among human blood cells. Finally, we measured intracellular phosphorylation of Stat1 (Y701) and Stat6 (Y641), with results comparable to flow cytometry. Thus, we have demonstrated the practicality of applying COIN nanoparticles for measuring intracellular phosphorylation, offering new possibilities to expand on the current fluorescent technology used for immunoassays in single cells.

Single-cell sequencing in stem cell biology.

Science.gov (United States)

Wen, Lu; Tang, Fuchou

2016-04-15

Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of stem cell populations, but these differences are masked when bulk cells are used for omic analysis. Single-cell sequencing technologies serve as powerful tools to dissect cellular heterogeneity comprehensively and to identify distinct phenotypic cell types, even within a 'homogeneous' stem cell population. These technologies, including single-cell genome, epigenome, and transcriptome sequencing technologies, have been developing rapidly in recent years. The application of these methods to different types of stem cells, including pluripotent stem cells and tissue-specific stem cells, has led to exciting new findings in the stem cell field. In this review, we discuss the recent progress as well as future perspectives in the methodologies and applications of single-cell omic sequencing technologies.

Systems integration (automation system). System integration (automation system)

Energy Technology Data Exchange (ETDEWEB)

Fujii, K; Komori, T; Fukuma, Y; Oikawa, M [Nippon Steal Corp., Tokyo (Japan)

1991-09-26

This paper introduces business activities on an automation systems integration (SI) started by a company in July,1988, and describes the SI concepts. The business activities include, with the CIM (unified production carried out on computers) and AMENITY (living environment) as the mainstays, a single responsibility construction ranging from consultation on structuring optimal systems for processing and assembling industries and intelligent buildings to system design, installation and after-sales services. With an SI standing on users {prime} position taken most importantly, the business starts from a planning and consultation under close coordination. On the conceptual basis of structuring optimal systems using the ompany {prime}s affluent know-hows and tools and adapting and applying with multi-vendors, open networks, centralized and distributed systems, the business is promoted with the accumulated technologies capable of realizing artificial intelligence and neural networks in its background, and supported with highly valuable business results in the past. 10 figs., 1 tab.

Radial optimization of a BWR fuel cell using genetic algorithms

International Nuclear Information System (INIS)

Martin del Campo M, C.; Carmona H, R.; Oropeza C, I.P.

2006-01-01

The development of the application of the Genetic Algorithms (GA) to the optimization of the radial distribution of enrichment in a cell of fuel of a BWR (Boiling Water Reactor) is presented. The optimization process it was ties to the HELIOS simulator, which is a transport code of neutron simulation of fuel cells that has been validated for the calculation of nuclear banks for BWRs. With heterogeneous radial designs can improve the radial distribution of the power, for what the radial design of fuel has a strong influence in the global design of fuel recharges. The optimum radial distribution of fuel bars is looked for with different enrichments of U 235 and contents of consumable poison. For it is necessary to define the representation of the solution, the objective function and the implementation of the specific optimization process to the solution of the problem. The optimization process it was coded in 'C' language, it was automated the creation of the entrances to the simulator, the execution of the simulator and the extraction, in the exit of the simulator, of the parameters that intervene in the objective function. The objective function includes four parameters: average enrichment of the cell, average gadolinia concentration of the cell, peak factor of radial power and k-infinite multiplication factor. To be able to calculate the parameters that intervene in the objective function, the one evaluation process of GA was ties to the HELIOS code executed in a Compaq Alpha workstation. It was applied to the design of a fuel cell of 10 x 10 that it can be employee in the fuel assemble designs that are used at the moment in the Laguna Verde Nucleo electric Central. Its were considered 10 different fuel compositions which four contain gadolinia. Three heuristic rules that consist in prohibiting the placement of bars with gadolinia in the ends of the cell, to place the compositions with the smallest enrichment in the corners of the cell and to fix the placement of

Functions and Requirements for Automated Liquid Level Gauge Instruments in Single-Shell and Double-Shell Tank Farms

International Nuclear Information System (INIS)

CARPENTER, K.E.

1999-01-01

This functions and requirements document defines the baseline requirements and criteria for the design, purchase, fabrication, construction, installation, and operation of automated liquid level gauge instruments in the Tank Farms. This document is intended to become the technical baseline for current and future installation, operation and maintenance of automated liquid level gauges in single-shell and double-shell tank farms

Increasing efficiency of human mesenchymal stromal cell culture by optimization of microcarrier concentration and design of medium feed.

Science.gov (United States)

Chen, Allen Kuan-Liang; Chew, Yi Kong; Tan, Hong Yu; Reuveny, Shaul; Weng Oh, Steve Kah

2015-02-01

Large amounts of human mesenchymal stromal cells (MSCs) are needed for clinical cellular therapy. In a previous publication, we described a microcarrier-based process for expansion of MSCs. The present study optimized this process by selecting suitable basal media, microcarrier concentration and feeding regime to achieve higher cell yields and more efficient medium utilization. MSCs were expanded in stirred cultures on Cytodex 3 microcarriers with media containing 10% fetal bovine serum. Process optimization was carried out in spinner flasks. A 2-L bioreactor with an automated feeding system was used to validate the optimized parameters explored in spinner flask cultures. Minimum essential medium-α-based medium supported faster MSC growth on microcarriers than did Dulbecco's modified Eagle's medium (doubling time, 31.6 ± 1.4 vs 42 ± 1.7 h) and shortened the process time. At microcarrier concentration of 8 mg/mL, a high cell concentration of 1.08 × 10(6) cells/mL with confluent cell concentration of 4.7 × 10(4)cells/cm(2) was achieved. Instead of 50% medium exchange every 2 days, we have designed a full medium feed that is based on glucose consumption rate. The optimal medium feed that consisted of 1.5 g/L glucose supported MSC growth to full confluency while achieving the low medium usage efficiency of 3.29 mL/10(6)cells. Finally, a controlled bioreactor with the optimized parameters achieved maximal confluent cell concentration with 16-fold expansion and a further improved medium usage efficiency of 1.68 mL/10(6)cells. We have optimized the microcarrier-based platform for expansion of MSCs that generated high cell yields in a more efficient and cost-effective manner. This study highlighted the critical parameters in the optimization of MSC production process. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

An optimized routing algorithm for the automated assembly of standard multimode ribbon fibers in a full-mesh optical backplane

Science.gov (United States)

Basile, Vito; Guadagno, Gianluca; Ferrario, Maddalena; Fassi, Irene

2018-03-01

In this paper a parametric, modular and scalable algorithm allowing a fully automated assembly of a backplane fiber-optic interconnection circuit is presented. This approach guarantees the optimization of the optical fiber routing inside the backplane with respect to specific criteria (i.e. bending power losses), addressing both transmission performance and overall costs issues. Graph theory has been exploited to simplify the complexity of the NxN full-mesh backplane interconnection topology, firstly, into N independent sub-circuits and then, recursively, into a limited number of loops easier to be generated. Afterwards, the proposed algorithm selects a set of geometrical and architectural parameters whose optimization allows to identify the optimal fiber optic routing for each sub-circuit of the backplane. The topological and numerical information provided by the algorithm are then exploited to control a robot which performs the automated assembly of the backplane sub-circuits. The proposed routing algorithm can be extended to any array architecture and number of connections thanks to its modularity and scalability. Finally, the algorithm has been exploited for the automated assembly of an 8x8 optical backplane realized with standard multimode (MM) 12-fiber ribbons.

Automated Cache Performance Analysis And Optimization

Energy Technology Data Exchange (ETDEWEB)

Mohror, Kathryn [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2013-12-23

While there is no lack of performance counter tools for coarse-grained measurement of cache activity, there is a critical lack of tools for relating data layout to cache behavior to application performance. Generally, any nontrivial optimizations are either not done at all, or are done ”by hand” requiring significant time and expertise. To the best of our knowledge no tool available to users measures the latency of memory reference instructions for partic- ular addresses and makes this information available to users in an easy-to-use and intuitive way. In this project, we worked to enable the Open|SpeedShop performance analysis tool to gather memory reference latency information for specific instructions and memory ad- dresses, and to gather and display this information in an easy-to-use and intuitive way to aid performance analysts in identifying problematic data structures in their codes. This tool was primarily designed for use in the supercomputer domain as well as grid, cluster, cloud-based parallel e-commerce, and engineering systems and middleware. Ultimately, we envision a tool to automate optimization of application cache layout and utilization in the Open|SpeedShop performance analysis tool. To commercialize this soft- ware, we worked to develop core capabilities for gathering enhanced memory usage per- formance data from applications and create and apply novel methods for automatic data structure layout optimizations, tailoring the overall approach to support existing supercom- puter and cluster programming models and constraints. In this Phase I project, we focused on infrastructure necessary to gather performance data and present it in an intuitive way to users. With the advent of enhanced Precise Event-Based Sampling (PEBS) counters on recent Intel processor architectures and equivalent technology on AMD processors, we are now in a position to access memory reference information for particular addresses. Prior to the introduction of PEBS counters

Fabrication of Biomolecule Microarrays for Cell Immobilization Using Automated Microcontact Printing.

Science.gov (United States)

Foncy, Julie; Estève, Aurore; Degache, Amélie; Colin, Camille; Cau, Jean Christophe; Malaquin, Laurent; Vieu, Christophe; Trévisiol, Emmanuelle

2018-01-01

Biomolecule microarrays are generally produced by conventional microarrayer, i.e., by contact or inkjet printing. Microcontact printing represents an alternative way of deposition of biomolecules on solid supports but even if various biomolecules have been successfully microcontact printed, the production of biomolecule microarrays in routine by microcontact printing remains a challenging task and needs an effective, fast, robust, and low-cost automation process. Here, we describe the production of biomolecule microarrays composed of extracellular matrix protein for the fabrication of cell microarrays by using an automated microcontact printing device. Large scale cell microarrays can be reproducibly obtained by this method.

The Spiral Discovery Network as an Automated General-Purpose Optimization Tool

Directory of Open Access Journals (Sweden)

Adam B. Csapo

2018-01-01

Full Text Available The Spiral Discovery Method (SDM was originally proposed as a cognitive artifact for dealing with black-box models that are dependent on multiple inputs with nonlinear and/or multiplicative interaction effects. Besides directly helping to identify functional patterns in such systems, SDM also simplifies their control through its characteristic spiral structure. In this paper, a neural network-based formulation of SDM is proposed together with a set of automatic update rules that makes it suitable for both semiautomated and automated forms of optimization. The behavior of the generalized SDM model, referred to as the Spiral Discovery Network (SDN, and its applicability to nondifferentiable nonconvex optimization problems are elucidated through simulation. Based on the simulation, the case is made that its applicability would be worth investigating in all areas where the default approach of gradient-based backpropagation is used today.

Targeting population heterogeneity for optimal cell factories

DEFF Research Database (Denmark)

Heins, Anna-Lena; Carlqvist, Magnus; Helmark, S.

the heterogeneity level of the population. To further investigate these phenomena and gain a deeper understanding of population heterogeneity, Saccharomyces cerevisiae growth reporter strains based on the expression of green fluorescent protein (GFP) were constructed which enabled us to perform single cell level...... analysis, and thereby created the possibility to map population heterogeneity. A factorial design with pH, glucose concentration and oxygen level was performed in batch cultivations using the growth reporter strains to evaluate the effect of those environmental factors on heterogeneity level and amount......To achieve an efficient production process, it is essential to optimize both the strain and the cultivation conditions. Traditionally, a microbial population has been considered homogeneous in optimization studies of fermentation processes. However, research has shown that a typical microbial...

Automated structure solution, density modification and model building.

Science.gov (United States)

Terwilliger, Thomas C

2002-11-01

The approaches that form the basis of automated structure solution in SOLVE and RESOLVE are described. The use of a scoring scheme to convert decision making in macromolecular structure solution to an optimization problem has proven very useful and in many cases a single clear heavy-atom solution can be obtained and used for phasing. Statistical density modification is well suited to an automated approach to structure solution because the method is relatively insensitive to choices of numbers of cycles and solvent content. The detection of non-crystallographic symmetry (NCS) in heavy-atom sites and checking of potential NCS operations against the electron-density map has proven to be a reliable method for identification of NCS in most cases. Automated model building beginning with an FFT-based search for helices and sheets has been successful in automated model building for maps with resolutions as low as 3 A. The entire process can be carried out in a fully automatic fashion in many cases.

Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis

Energy Technology Data Exchange (ETDEWEB)

Lo, Andy; Tang, Yanan; Chen, Lu; Li, Liang, E-mail: Liang.Li@ualberta.ca

2013-07-25

Graphical abstract: -- Highlights: •Dimethylation after guanidination (2MEGA) uses inexpensive reagents for isotopic labeling of peptides. •2MEGA can be optimized and automated for labeling peptides with high efficiency. •2MEGA is compatible with several commonly used cell lysis and protein solubilization reagents. •The automated 2MEGA labeling method can be used to handle a variety of protein samples for relative proteome quantification. -- Abstract: Isotope labeling liquid chromatography–mass spectrometry (LC–MS) is a major analytical platform for quantitative proteome analysis. Incorporation of isotopes used to distinguish samples plays a critical role in the success of this strategy. In this work, we optimized and automated a chemical derivatization protocol (dimethylation after guanidination, 2MEGA) to increase the labeling reproducibility and reduce human intervention. We also evaluated the reagent compatibility of this protocol to handle biological samples in different types of buffers and surfactants. A commercially available liquid handler was used for reagent dispensation to minimize analyst intervention and at least twenty protein digest samples could be prepared in a single run. Different front-end sample preparation methods for protein solubilization (SDS, urea, Rapigest™, and ProteaseMAX™) and two commercially available cell lysis buffers were evaluated for compatibility with the automated protocol. It was found that better than 94% desired labeling could be obtained in all conditions studied except urea, where the rate was reduced to about 92% due to carbamylation on the peptide amines. This work illustrates the automated 2MEGA labeling process can be used to handle a wide range of protein samples containing various reagents that are often encountered in protein sample preparation for quantitative proteome analysis.

Automated detection of analyzable metaphase chromosome cells depicted on scanned digital microscopic images

Science.gov (United States)

Qiu, Yuchen; Wang, Xingwei; Chen, Xiaodong; Li, Yuhua; Liu, Hong; Li, Shibo; Zheng, Bin

2010-02-01

Visually searching for analyzable metaphase chromosome cells under microscopes is quite time-consuming and difficult. To improve detection efficiency, consistency, and diagnostic accuracy, an automated microscopic image scanning system was developed and tested to directly acquire digital images with sufficient spatial resolution for clinical diagnosis. A computer-aided detection (CAD) scheme was also developed and integrated into the image scanning system to search for and detect the regions of interest (ROI) that contain analyzable metaphase chromosome cells in the large volume of scanned images acquired from one specimen. Thus, the cytogeneticists only need to observe and interpret the limited number of ROIs. In this study, the high-resolution microscopic image scanning and CAD performance was investigated and evaluated using nine sets of images scanned from either bone marrow (three) or blood (six) specimens for diagnosis of leukemia. The automated CAD-selection results were compared with the visual selection. In the experiment, the cytogeneticists first visually searched for the analyzable metaphase chromosome cells from specimens under microscopes. The specimens were also automated scanned and followed by applying the CAD scheme to detect and save ROIs containing analyzable cells while deleting the others. The automated selected ROIs were then examined by a panel of three cytogeneticists. From the scanned images, CAD selected more analyzable cells than initially visual examinations of the cytogeneticists in both blood and bone marrow specimens. In general, CAD had higher performance in analyzing blood specimens. Even in three bone marrow specimens, CAD selected 50, 22, 9 ROIs, respectively. Except matching with the initially visual selection of 9, 7, and 5 analyzable cells in these three specimens, the cytogeneticists also selected 41, 15 and 4 new analyzable cells, which were missed in initially visual searching. This experiment showed the feasibility of

A versatile automated platform for micro-scale cell stimulation experiments.

Science.gov (United States)

Sinha, Anupama; Jebrail, Mais J; Kim, Hanyoup; Patel, Kamlesh D; Branda, Steven S

2013-08-06

Study of cells in culture (in vitro analysis) has provided important insight into complex biological systems. Conventional methods and equipment for in vitro analysis are well suited to study of large numbers of cells (≥ 10(5)) in milliliter-scale volumes (≥ 0.1 ml). However, there are many instances in which it is necessary or desirable to scale down culture size to reduce consumption of the cells of interest and/or reagents required for their culture, stimulation, or processing. Unfortunately, conventional approaches do not support precise and reproducible manipulation of micro-scale cultures, and the microfluidics-based automated systems currently available are too complex and specialized for routine use by most laboratories. To address this problem, we have developed a simple and versatile technology platform for automated culture, stimulation, and recovery of small populations of cells (100-2,000 cells) in micro-scale volumes (1-20 μl). The platform consists of a set of fibronectin-coated microcapillaries ("cell perfusion chambers"), within which micro-scale cultures are established, maintained, and stimulated; a digital microfluidics (DMF) device outfitted with "transfer" microcapillaries ("central hub"), which routes cells and reagents to and from the perfusion chambers; a high-precision syringe pump, which powers transport of materials between the perfusion chambers and the central hub; and an electronic interface that provides control over transport of materials, which is coordinated and automated via pre-determined scripts. As an example, we used the platform to facilitate study of transcriptional responses elicited in immune cells upon challenge with bacteria. Use of the platform enabled us to reduce consumption of cells and reagents, minimize experiment-to-experiment variability, and re-direct hands-on labor. Given the advantages that it confers, as well as its accessibility and versatility, our platform should find use in a wide variety of

Optimization of automation: I. Estimation method of cognitive automation rates reflecting the effects of automation on human operators in nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Min; Kim, Jong Hyun; Seong, Poong Hyun

2014-01-01

Highlights: • We propose an estimation method of the automation rate by taking the advantages of automation as the estimation measures. • We conduct the experiments to examine the validity of the suggested method. • The higher the cognitive automation rate is, the greater the decreased rate of the working time will be. • The usefulness of the suggested estimation method is proved by statistical analyses. - Abstract: Since automation was introduced in various industrial fields, the concept of the automation rate has been used to indicate the inclusion proportion of automation among all work processes or facilities. Expressions of the inclusion proportion of automation are predictable, as is the ability to express the degree of the enhancement of human performance. However, many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, this paper proposes a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs). Automation in NPPs can be divided into two types: system automation and cognitive automation. Some general descriptions and characteristics of each type of automation are provided, and the advantages of automation are investigated. The advantages of each type of automation are used as measures of the estimation method of the automation rate. One advantage was found to be a reduction in the number of tasks, and another was a reduction in human cognitive task loads. The system and the cognitive automation rate were proposed as quantitative measures by taking advantage of the aforementioned benefits. To quantify the required human cognitive task loads and thus suggest the cognitive automation rate, Conant’s information-theory-based model was applied. The validity of the suggested method, especially as regards the cognitive automation rate, was proven by conducting

Automated classification of cell morphology by coherence-controlled holographic microscopy

Science.gov (United States)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

Experimental optimization of a direct injection homogeneous charge compression ignition gasoline engine using split injections with fully automated microgenetic algorithms

Energy Technology Data Exchange (ETDEWEB)

Canakci, M. [Kocaeli Univ., Izmit (Turkey); Reitz, R.D. [Wisconsin Univ., Dept. of Mechanical Engineering, Madison, WI (United States)

2003-03-01

Homogeneous charge compression ignition (HCCI) is receiving attention as a new low-emission engine concept. Little is known about the optimal operating conditions for this engine operation mode. Combustion under homogeneous, low equivalence ratio conditions results in modest temperature combustion products, containing very low concentrations of NO{sub x} and particulate matter (PM) as well as providing high thermal efficiency. However, this combustion mode can produce higher HC and CO emissions than those of conventional engines. An electronically controlled Caterpillar single-cylinder oil test engine (SCOTE), originally designed for heavy-duty diesel applications, was converted to an HCCI direct injection (DI) gasoline engine. The engine features an electronically controlled low-pressure direct injection gasoline (DI-G) injector with a 60 deg spray angle that is capable of multiple injections. The use of double injection was explored for emission control and the engine was optimized using fully automated experiments and a microgenetic algorithm optimization code. The variables changed during the optimization include the intake air temperature, start of injection timing and the split injection parameters (per cent mass of fuel in each injection, dwell between the pulses). The engine performance and emissions were determined at 700 r/min with a constant fuel flowrate at 10 MPa fuel injection pressure. The results show that significant emissions reductions are possible with the use of optimal injection strategies. (Author)

Improving the automated optimization of profile extrusion dies by applying appropriate optimization areas and strategies

Science.gov (United States)

Hopmann, Ch.; Windeck, C.; Kurth, K.; Behr, M.; Siegbert, R.; Elgeti, S.

2014-05-01

The rheological design of profile extrusion dies is one of the most challenging tasks in die design. As no analytical solution is available, the quality and the development time for a new design highly depend on the empirical knowledge of the die manufacturer. Usually, prior to start production several time-consuming, iterative running-in trials need to be performed to check the profile accuracy and the die geometry is reworked. An alternative are numerical flow simulations. These simulations enable to calculate the melt flow through a die so that the quality of the flow distribution can be analyzed. The objective of a current research project is to improve the automated optimization of profile extrusion dies. Special emphasis is put on choosing a convenient starting geometry and parameterization, which enable for possible deformations. In this work, three commonly used design features are examined with regard to their influence on the optimization results. Based on the results, a strategy is derived to select the most relevant areas of the flow channels for the optimization. For these characteristic areas recommendations are given concerning an efficient parameterization setup that still enables adequate deformations of the flow channel geometry. Exemplarily, this approach is applied to a L-shaped profile with different wall thicknesses. The die is optimized automatically and simulation results are qualitatively compared with experimental results. Furthermore, the strategy is applied to a complex extrusion die of a floor skirting profile to prove the universal adaptability.

Automated single-trial assessment of laser-evoked potentials as an objective functional diagnostic tool for the nociceptive system.

Science.gov (United States)

Hatem, S M; Hu, L; Ragé, M; Gierasimowicz, A; Plaghki, L; Bouhassira, D; Attal, N; Iannetti, G D; Mouraux, A

2012-12-01

To assess the clinical usefulness of an automated analysis of event-related potentials (ERPs). Nociceptive laser-evoked potentials (LEPs) and non-nociceptive somatosensory electrically-evoked potentials (SEPs) were recorded in 37 patients with syringomyelia and 21 controls. LEP and SEP peak amplitudes and latencies were estimated using a single-trial automated approach based on time-frequency wavelet filtering and multiple linear regression, as well as a conventional approach based on visual inspection. The amplitudes and latencies of normal and abnormal LEP and SEP peaks were identified reliably using both approaches, with similar sensitivity and specificity. Because the automated approach provided an unbiased solution to account for average waveforms where no ERP could be identified visually, it revealed significant differences between patients and controls that were not revealed using the visual approach. The automated analysis of ERPs characterized reliably and objectively LEP and SEP waveforms in patients. The automated single-trial analysis can be used to characterize normal and abnormal ERPs with a similar sensitivity and specificity as visual inspection. While this does not justify its use in a routine clinical setting, the technique could be useful to avoid observer-dependent biases in clinical research. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Selection of an optimal neural network architecture for computer-aided detection of microcalcifications - Comparison of automated optimization techniques

International Nuclear Information System (INIS)

Gurcan, Metin N.; Sahiner, Berkman; Chan Heangping; Hadjiiski, Lubomir; Petrick, Nicholas

2001-01-01

Many computer-aided diagnosis (CAD) systems use neural networks (NNs) for either detection or classification of abnormalities. Currently, most NNs are 'optimized' by manual search in a very limited parameter space. In this work, we evaluated the use of automated optimization methods for selecting an optimal convolution neural network (CNN) architecture. Three automated methods, the steepest descent (SD), the simulated annealing (SA), and the genetic algorithm (GA), were compared. We used as an example the CNN that classifies true and false microcalcifications detected on digitized mammograms by a prescreening algorithm. Four parameters of the CNN architecture were considered for optimization, the numbers of node groups and the filter kernel sizes in the first and second hidden layers, resulting in a search space of 432 possible architectures. The area A z under the receiver operating characteristic (ROC) curve was used to design a cost function. The SA experiments were conducted with four different annealing schedules. Three different parent selection methods were compared for the GA experiments. An available data set was split into two groups with approximately equal number of samples. By using the two groups alternately for training and testing, two different cost surfaces were evaluated. For the first cost surface, the SD method was trapped in a local minimum 91% (392/432) of the time. The SA using the Boltzman schedule selected the best architecture after evaluating, on average, 167 architectures. The GA achieved its best performance with linearly scaled roulette-wheel parent selection; however, it evaluated 391 different architectures, on average, to find the best one. The second cost surface contained no local minimum. For this surface, a simple SD algorithm could quickly find the global minimum, but the SA with the very fast reannealing schedule was still the most efficient. The same SA scheme, however, was trapped in a local minimum on the first cost

Microfluidics for single cell analysis

DEFF Research Database (Denmark)

Jensen, Marie Pødenphant

Isolation and manipulation of single cells have gained an increasing interest from researchers because of the heterogeneity of cells from the same cell culture. Single cell analysis can ensure a better understanding of differences between individual cells and potentially solve a variety of clinical...... problems. In this thesis lab on a chip systems for rare single cell analysis are investigated. The focus was to develop a commercial, disposable device for circulating tumour cell (CTC) analysis. Such a device must be able to separate rare cells from blood samples and subsequently capture the specific...... cells, and simultaneously be fabricated and operated at low costs and be user-friendly. These challenges were addressed through development of two microfluidic devices, one for rare cell isolation based on pinched flow fractionation (PFF) and one for single cell capture based on hydrodynamic trapping...

Single Nanowire Probe for Single Cell Endoscopy and Sensing

Science.gov (United States)

Yan, Ruoxue

adaptable to average bio-lab environment. These probes are mechanically robust and flexible and can withstand repeated bending and deformation without significant deterioration in optical performance, which offers an ideal instrumental platform for out subsequent effort of using these nanoprobes in chemical sensing as well as single cell endoscopy and spot delivery. Parameters affecting the coupling efficiency and output power of the nanoprobe were studied and chemical etched of single mode fiber with small cone angle was established to be optimized for highly effective optical nanoprobes. The versatility of the nanoprobe design was first tested by transforming the nanowire probe into a pH sensor with near-field photopolymerization of a copolymer containing pH sensitive dye on the tip of the nanowire. The pH-sensitive nanoprobe was able to report the pH difference in micro-droplets containing buffer solution with the excitation of light waveguided on the nanoprobe with internal calibration, fast response time and good photostability and reversibility. Such nanoprobe sensors are ideal for high definition spatial and temporal sensing of concentration profile, especially for the kinetic processes in single cell studies for which chemical probes of minute sizes and fast response are desired. The nanoprobe was then applied into spot cargo delivery and in-situ single cell endoscopy. It was demonstrated that nanowire-based optical probe can deliver payloads into the cell with a high spatiotemporal precision, guide and confine visible light into intracellular compartments selectively and detect optical signals from the subcellular regions with high spatial resolution. The nanoprobe was proven to be biocompatible and non-invasive. The effective optical coupling between the fiber optics and the nanowire enables highly localized excitation and detection, limiting the probe volume to the close proximity of the nanowire. None the less, this versatile technique does not rely on any

Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology.

Science.gov (United States)

Annecchino, Luca A; Morris, Alexander R; Copeland, Caroline S; Agabi, Oshiorenoya E; Chadderton, Paul; Schultz, Simon R

2017-08-30

Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed "blind," meaning that throughput for sampling some genetically or morphologically defined cell types is unacceptably low. One solution to this problem is to use two-photon microscopy to target fluorescently labeled neurons. Combining this with robotic automation is difficult, however, as micropipette penetration induces tissue deformation, moving target cells from their initial location. Here we describe a platform for automated two-photon targeted patch-clamp recording, which solves this problem by making use of a closed loop visual servo algorithm. Our system keeps the target cell in focus while iteratively adjusting the pipette approach trajectory to compensate for tissue motion. We demonstrate platform validation with patch-clamp recordings from a variety of cells in the mouse neocortex and cerebellum. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Measuring single-cell density.

Science.gov (United States)

Grover, William H; Bryan, Andrea K; Diez-Silva, Monica; Suresh, Subra; Higgins, John M; Manalis, Scott R

2011-07-05

We have used a microfluidic mass sensor to measure the density of single living cells. By weighing each cell in two fluids of different densities, our technique measures the single-cell mass, volume, and density of approximately 500 cells per hour with a density precision of 0.001 g mL(-1). We observe that the intrinsic cell-to-cell variation in density is nearly 100-fold smaller than the mass or volume variation. As a result, we can measure changes in cell density indicative of cellular processes that would be otherwise undetectable by mass or volume measurements. Here, we demonstrate this with four examples: identifying Plasmodium falciparum malaria-infected erythrocytes in a culture, distinguishing transfused blood cells from a patient's own blood, identifying irreversibly sickled cells in a sickle cell patient, and identifying leukemia cells in the early stages of responding to a drug treatment. These demonstrations suggest that the ability to measure single-cell density will provide valuable insights into cell state for a wide range of biological processes.

Multi-objective optimization for an automated and simultaneous phase and baseline correction of NMR spectral data

Science.gov (United States)

Sawall, Mathias; von Harbou, Erik; Moog, Annekathrin; Behrens, Richard; Schröder, Henning; Simoneau, Joël; Steimers, Ellen; Neymeyr, Klaus

2018-04-01

Spectral data preprocessing is an integral and sometimes inevitable part of chemometric analyses. For Nuclear Magnetic Resonance (NMR) spectra a possible first preprocessing step is a phase correction which is applied to the Fourier transformed free induction decay (FID) signal. This preprocessing step can be followed by a separate baseline correction step. Especially if series of high-resolution spectra are considered, then automated and computationally fast preprocessing routines are desirable. A new method is suggested that applies the phase and the baseline corrections simultaneously in an automated form without manual input, which distinguishes this work from other approaches. The underlying multi-objective optimization or Pareto optimization provides improved results compared to consecutively applied correction steps. The optimization process uses an objective function which applies strong penalty constraints and weaker regularization conditions. The new method includes an approach for the detection of zero baseline regions. The baseline correction uses a modified Whittaker smoother. The functionality of the new method is demonstrated for experimental NMR spectra. The results are verified against gravimetric data. The method is compared to alternative preprocessing tools. Additionally, the simultaneous correction method is compared to a consecutive application of the two correction steps.

Single Cell Isolation and Analysis

Directory of Open Access Journals (Sweden)

Ping Hu

2016-10-01

Full Text Available Increasing evidence shows that the heterogeneity of individual cells within a genetically identical population can be critical to their peculiar function and fate. Conventional cell based assays mainly analysis the average responses from a population cells, while the difference within individual cells may often be masked. The cell size, RNA transcripts and protein expression level are quite different within individual cells and these variations are key point to answer the problems in cancer, neurobiology, stem cell biology, immunology and developmental biology. To better understand the cell-to-cell variations, the single cell analysis can provide much more detailed information which may be helpful for therapeutic decisions in an increasingly personalized medicine. In this review, we will focus on the recent development in single cell analysis, including methods used in single cell isolation, analysis and some application examples. The review provides the historical background to single cell analysis, discusses limitations, and current and future possibilities in this exciting field of research.

DESIGN OF SMALL AUTOMATION WORK CELL SYSTEM DEMONSTRATIONS

International Nuclear Information System (INIS)

TURNER, C.; PEHL, J.

2000-01-01

The introduction of automation systems into many of the facilities dealing with the production, use and disposition of nuclear materials has been an ongoing objective. Many previous attempts have been made, using a variety of monolithic and, in some cases, modular technologies. Many of these attempts were less than successful, owing to the difficulty of the problem, the lack of maturity of the technology, and over optimism about the capabilities of a particular system. Consequently, it is not surprising that suggestions that automation can reduce worker Occupational Radiation Exposure (ORE) levels are often met with skepticism and caution. The development of effective demonstrations of these technologies is of vital importance if automation is to become an acceptable option for nuclear material processing environments. The University of Texas Robotics Research Group (UTRRG) has been pursuing the development of technologies to support modular small automation systems (each of less than 5 degrees-of-freedom) and the design of those systems for more than two decades. Properly designed and implemented, these technologies have a potential to reduce the worker ORE associated with work in nuclear materials processing facilities. Successful development of systems for these applications requires the development of technologies that meet the requirements of the applications. These application requirements form a general set of rules that applicable technologies and approaches need to adhere to, but in and of themselves are generally insufficient for the design of a specific automation system. For the design of an appropriate system, the associated task specifications and relationships need to be defined. These task specifications also provide a means by which appropriate technology demonstrations can be defined. Based on the requirements and specifications of the operations of the Advanced Recovery and Integrated Extraction System (ARIES) pilot line at Los Alamos National

Automated Portfolio Optimization Based on a New Test for Structural Breaks

Directory of Open Access Journals (Sweden)

Tobias Berens

2014-04-01

Full Text Available We present a completely automated optimization strategy which combines the classical Markowitz mean-variance portfolio theory with a recently proposed test for structural breaks in covariance matrices. With respect to equity portfolios, global minimum-variance optimizations, which base solely on the covariance matrix, yield considerable results in previous studies. However, financial assets cannot be assumed to have a constant covariance matrix over longer periods of time. Hence, we estimate the covariance matrix of the assets by respecting potential change points. The resulting approach resolves the issue of determining a sample for parameter estimation. Moreover, we investigate if this approach is also appropriate for timing the reoptimizations. Finally, we apply the approach to two datasets and compare the results to relevant benchmark techniques by means of an out-of-sample study. It is shown that the new approach outperforms equally weighted portfolios and plain minimum-variance portfolios on average.

A NOVEL PIPELINE FOR DRUG DISCOVERY IN NEUROPSYCHIATRIC DISORDERS USING HIGH-CONTENT SINGLE-CELL SCREENING OF SIGNALLING NETWORK RESPONSES EX VIVO

OpenAIRE

Lago Cooke, Santiago Guillermo

2016-01-01

The current work entails the development of a novel high content platform for the measurement of kinetic ligand responses across cell signalling networks at the single-cell level in distinct PBMC subtypes ex vivo. Using automated sample preparation, fluorescent cellular barcoding and flow cytometry the platform is capable of detecting 21, 840 parallel cell signalling responses in each PBMC sample. We apply this platform to characterize the effects of neuropsychiatric treatments and CNS ligand...

High throughput automated microbial bioreactor system used for clone selection and rapid scale-down process optimization.

Science.gov (United States)

Velez-Suberbie, M Lourdes; Betts, John P J; Walker, Kelly L; Robinson, Colin; Zoro, Barney; Keshavarz-Moore, Eli

2018-01-01

High throughput automated fermentation systems have become a useful tool in early bioprocess development. In this study, we investigated a 24 x 15 mL single use microbioreactor system, ambr 15f, designed for microbial culture. We compared the fed-batch growth and production capabilities of this system for two Escherichia coli strains, BL21 (DE3) and MC4100, and two industrially relevant molecules, hGH and scFv. In addition, different carbon sources were tested using bolus, linear or exponential feeding strategies, showing the capacity of the ambr 15f system to handle automated feeding. We used power per unit volume (P/V) as a scale criterion to compare the ambr 15f with 1 L stirred bioreactors which were previously scaled-up to 20 L with a different biological system, thus showing a potential 1,300 fold scale comparability in terms of both growth and product yield. By exposing the cells grown in the ambr 15f system to a level of shear expected in an industrial centrifuge, we determined that the cells are as robust as those from a bench scale bioreactor. These results provide evidence that the ambr 15f system is an efficient high throughput microbial system that can be used for strain and molecule selection as well as rapid scale-up. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:58-68, 2018. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

Process development for automated solar cell and module production. Task 4. Automated array assembly. Quarterly report No. 1

Energy Technology Data Exchange (ETDEWEB)

Hagerty, J. J.

1980-10-15

Work has been divided into five phases. The first phase is to modify existing hardware and controlling computer software to: (1) improve cell-to-cell placement accuracy, (2) improve the solder joint while reducing the amount of solder and flux smear on the cell's surface, and (3) reduce the system cycle time to 10 seconds. The second phase involves expanding the existing system's capabilities to be able to reject broken cells and make post-solder electrical tests. Phase 3 involves developing new hardware to allow for the automated encapsulation of solar modules. This involves three discrete pieces of hardware: (1) a vacuum platen end effector for the robot which allows it to pick up the 1' x 4' array of 35 inter-connected cells. With this, it can also pick up the cover glass and completed module, (2) a lamination preparation station which cuts the various encapsulation components from roll storage and positions them for encapsulation, and (3) an automated encapsulation chamber which interfaces with the above two and applies the heat and vacuum to cure the encapsulants. Phase 4 involves the final assembly of the encapsulated array into a framed, edge-sealed module completed for installation. For this we are using MBA's Glass Reinforced Concrete (GRC) in panels such as those developed by MBA for JPL under contract No. 955281. The GRC panel plays the multiple role of edge frame, substrate and mounting structure. An automated method of applying the edge seal will also be developed. The final phase (5) is the fabrication of six 1' x 4' electrically active solar modules using the above developed equipment. Progress is reported. (WHK)

Optimization of an NLEO-based algorithm for automated detection of spontaneous activity transients in early preterm EEG

International Nuclear Information System (INIS)

Palmu, Kirsi; Vanhatalo, Sampsa; Stevenson, Nathan; Wikström, Sverre; Hellström-Westas, Lena; Palva, J Matias

2010-01-01

We propose here a simple algorithm for automated detection of spontaneous activity transients (SATs) in early preterm electroencephalography (EEG). The parameters of the algorithm were optimized by supervised learning using a gold standard created from visual classification data obtained from three human raters. The generalization performance of the algorithm was estimated by leave-one-out cross-validation. The mean sensitivity of the optimized algorithm was 97% (range 91–100%) and specificity 95% (76–100%). The optimized algorithm makes it possible to systematically study brain state fluctuations of preterm infants. (note)

Lab-on-a-Disc Platform for Automated Chemical Cell Lysis

Directory of Open Access Journals (Sweden)

Moo-Jung Seo

2018-02-01

Full Text Available Chemical cell lysis is an interesting topic in the research to Lab-on-a-Disc (LOD platforms on account of its perfect compatibility with the centrifugal spin column format. However, standard procedures followed in chemical cell lysis require sophisticated non-contact temperature control as well as the use of pressure resistant valves. These requirements pose a significant challenge thereby making the automation of chemical cell lysis on an LOD extremely difficult to achieve. In this study, an LOD capable of performing fully automated chemical cell lysis is proposed, where a combination of chemical and thermal methods has been used. It comprises a sample inlet, phase change material sheet (PCMS-based temperature sensor, heating chamber, and pressure resistant valves. The PCMS melts and solidifies at a certain temperature and thus is capable of indicating whether the heating chamber has reached a specific temperature. Compared to conventional cell lysis systems, the proposed system offers advantages of reduced manual labor and a compact structure that can be readily integrated onto an LOD. Experiments using Salmonella typhimurium strains were conducted to confirm the performance of the proposed cell lysis system. The experimental results demonstrate that the proposed system has great potential in realizing chemical cell lysis on an LOD whilst achieving higher throughput in terms of purity and yield of DNA thereby providing a good alternative to conventional cell lysis systems.

Lab-on-a-Disc Platform for Automated Chemical Cell Lysis.

Science.gov (United States)

Seo, Moo-Jung; Yoo, Jae-Chern

2018-02-26

Chemical cell lysis is an interesting topic in the research to Lab-on-a-Disc (LOD) platforms on account of its perfect compatibility with the centrifugal spin column format. However, standard procedures followed in chemical cell lysis require sophisticated non-contact temperature control as well as the use of pressure resistant valves. These requirements pose a significant challenge thereby making the automation of chemical cell lysis on an LOD extremely difficult to achieve. In this study, an LOD capable of performing fully automated chemical cell lysis is proposed, where a combination of chemical and thermal methods has been used. It comprises a sample inlet, phase change material sheet (PCMS)-based temperature sensor, heating chamber, and pressure resistant valves. The PCMS melts and solidifies at a certain temperature and thus is capable of indicating whether the heating chamber has reached a specific temperature. Compared to conventional cell lysis systems, the proposed system offers advantages of reduced manual labor and a compact structure that can be readily integrated onto an LOD. Experiments using Salmonella typhimurium strains were conducted to confirm the performance of the proposed cell lysis system. The experimental results demonstrate that the proposed system has great potential in realizing chemical cell lysis on an LOD whilst achieving higher throughput in terms of purity and yield of DNA thereby providing a good alternative to conventional cell lysis systems.

FogBank: a single cell segmentation across multiple cell lines and image modalities.

Science.gov (United States)

Chalfoun, Joe; Majurski, Michael; Dima, Alden; Stuelten, Christina; Peskin, Adele; Brady, Mary

2014-12-30

Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies. We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation. First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce. We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images. FogBank produces single cell segmentation from confluent cell

Flexible Measurement of Bioluminescent Reporters Using an Automated Longitudinal Luciferase Imaging Gas- and Temperature-optimized Recorder (ALLIGATOR).

Science.gov (United States)

Crosby, Priya; Hoyle, Nathaniel P; O'Neill, John S

2017-12-13

Luciferase-based reporters of cellular gene expression are in widespread use for both longitudinal and end-point assays of biological activity. In circadian rhythms research, for example, clock gene fusions with firefly luciferase give rise to robust rhythms in cellular bioluminescence that persist over many days. Technical limitations associated with photomultiplier tubes (PMT) or conventional microscopy-based methods for bioluminescence quantification have typically demanded that cells and tissues be maintained under quite non-physiological conditions during recording, with a trade-off between sensitivity and throughput. Here, we report a refinement of prior methods that allows long-term bioluminescence imaging with high sensitivity and throughput which supports a broad range of culture conditions, including variable gas and humidity control, and that accepts many different tissue culture plates and dishes. This automated longitudinal luciferase imaging gas- and temperature-optimized recorder (ALLIGATOR) also allows the observation of spatial variations in luciferase expression across a cell monolayer or tissue, which cannot readily be observed by traditional methods. We highlight how the ALLIGATOR provides vastly increased flexibility for the detection of luciferase activity when compared with existing methods.

Automated classification of cell morphology by coherence-controlled holographic microscopy.

Science.gov (United States)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Plutonium production in a remote automated cell

International Nuclear Information System (INIS)

Maddux, E.P.; Purcell, J.A.

1987-01-01

Production of 239 Pu metal has traditionally been carried out in glove box enclosures to protect operating personnel and the outside environment from the hazards of radiation. With the advent of more stringent federal regulations for protecting personnel, the environment, and security of special nuclear materials, it is proposed that plutonium be processed in a totally remote environment using automated work stations and robotic materials transfer and equipment maintenance. Investigators envision a facility where operations are carried out in two remotely operated cells. One cell will contain aqueous processing operations while the second will contain powder operations. Various processing steps will be carried out on modular frames of a standard configuration. The processing equipment on each frame will be completely automated and operated via computer. Nonaqueous materials will be transferred between frames by robots using closed-circuit television and computer control. Robots will be able to perform limited in-place maintenance of equipment on each frame for high-maintenance replaceable components. When major repair is required, the processing frame will be decoupled by the robot and moved to a decontamination and maintenance area by a conventional overhead bridge crane. The new design concept will provide for long-term goals, which include exposure reduction, near-real time accountability, safeguards, and waste reduction

Current automated 3D cell detection methods are not a suitable replacement for manual stereologic cell counting

Directory of Open Access Journals (Sweden)

Christoph eSchmitz

2014-05-01

Full Text Available Stereologic cell counting has had a major impact on the field of neuroscience. A major bottleneck in stereologic cell counting is that the user must manually decide whether or not each cell is counted according to three-dimensional (3D stereologic counting rules by visual inspection within hundreds of microscopic fields-of-view per investigated brain or brain region. Reliance on visual inspection forces stereologic cell counting to be very labor-intensive and time-consuming, and is the main reason why biased, non-stereologic two-dimensional (2D cell counting approaches have remained in widespread use. We present an evaluation of the performance of modern automated cell detection and segmentation algorithms as a potential alternative to the manual approach in stereologic cell counting. The image data used in this study were 3D microscopic images of thick brain tissue sections prepared with a variety of commonly used nuclear and cytoplasmic stains. The evaluation compared the numbers and locations of cells identified unambiguously and counted exhaustively by an expert observer with those found by three automated 3D cell detection algorithms: nuclei segmentation from the FARSIGHT toolkit, nuclei segmentation by 3D multiple level set methods, and the 3D object counter plug-in for ImageJ. Of these methods, FARSIGHT performed best, with true-positive detection rates between 38–99% and false-positive rates from 3.6–82%. The results demonstrate that the current automated methods suffer from lower detection rates and higher false-positive rates than are acceptable for obtaining valid estimates of cell numbers. Thus, at present, stereologic cell counting with manual decision for object inclusion according to unbiased stereologic counting rules remains the only adequate method for unbiased cell quantification in histologic tissue sections.

Automated high resolution full-field spatial coherence tomography for quantitative phase imaging of human red blood cells

Science.gov (United States)

Singla, Neeru; Dubey, Kavita; Srivastava, Vishal; Ahmad, Azeem; Mehta, D. S.

2018-02-01

We developed an automated high-resolution full-field spatial coherence tomography (FF-SCT) microscope for quantitative phase imaging that is based on the spatial, rather than the temporal, coherence gating. The Red and Green color laser light was used for finding the quantitative phase images of unstained human red blood cells (RBCs). This study uses morphological parameters of unstained RBCs phase images to distinguish between normal and infected cells. We recorded the single interferogram by a FF-SCT microscope for red and green color wavelength and average the two phase images to further reduced the noise artifacts. In order to characterize anemia infected from normal cells different morphological features were extracted and these features were used to train machine learning ensemble model to classify RBCs with high accuracy.

Computer-automated tuning of semiconductor double quantum dots into the single-electron regime

Energy Technology Data Exchange (ETDEWEB)

Baart, T. A.; Vandersypen, L. M. K. [QuTech, Delft University of Technology, P.O. Box 5046, 2600 GA Delft (Netherlands); Kavli Institute of Nanoscience, Delft University of Technology, P.O. Box 5046, 2600 GA Delft (Netherlands); Eendebak, P. T. [QuTech, Delft University of Technology, P.O. Box 5046, 2600 GA Delft (Netherlands); Netherlands Organisation for Applied Scientific Research (TNO), P.O. Box 155, 2600 AD Delft (Netherlands); Reichl, C.; Wegscheider, W. [Solid State Physics Laboratory, ETH Zürich, 8093 Zürich (Switzerland)

2016-05-23

We report the computer-automated tuning of gate-defined semiconductor double quantum dots in GaAs heterostructures. We benchmark the algorithm by creating three double quantum dots inside a linear array of four quantum dots. The algorithm sets the correct gate voltages for all the gates to tune the double quantum dots into the single-electron regime. The algorithm only requires (1) prior knowledge of the gate design and (2) the pinch-off value of the single gate T that is shared by all the quantum dots. This work significantly alleviates the user effort required to tune multiple quantum dot devices.

Economic Optimizing Control for Single-Cell Protein Production in a U-Loop Reactor

DEFF Research Database (Denmark)

Drejer, André; Ritschel, Tobias Kasper Skovborg; Jørgensen, Sten Bay

2017-01-01

The production of single-cell protein (SCP) in a U-loop reactor by a methanotroph is a cost efficient sustainable alternative to protein from fish meal obtained by over-fishing the oceans. SCP serves as animal feed. In this paper, we present a mathematical model that describes the dynamics of SCP...

Flow field optimization for proton exchange membrane fuel cells with varying channel heights and widths

International Nuclear Information System (INIS)

Wang Xiaodong; Huang Yuxian; Cheng, C.-H.; Jang, J.-Y.; Lee, D.-J.; Yan, W.-M.; Su Ay

2009-01-01

The optimal cathode flow field design of a single serpentine proton exchange membrane fuel cell is obtained by adopting a combined optimization procedure including a simplified conjugate-gradient method (SCGM) and a completely three-dimensional, two-phase, non-isothermal fuel cell model. The cell output power density P cell is the objective function to be maximized with channel heights, H 1 -H 5 , and channel widths, W 2 -W 5 as search variables. The optimal design has tapered channels 1, 3 and 4, and diverging channels 2 and 5, producing 22.51% increment compared with the basic design with all heights and widths setting as 1 mm. Reduced channel heights of channels 2-4 significantly enhance sub-rib convection to effectively transport oxygen to and liquid water out of diffusion layer. The final diverging channel prevents significant leakage of fuel to outlet via sub-rib convection from channel 4. Near-optimal design without huge loss in cell performance but is easily manufactured is discussed.

Nuclear protein accumulation in cellular senescence and organismal aging revealed with a novel single-cell resolution fluorescence microscopy assay.

Science.gov (United States)

De Cecco, Marco; Jeyapalan, Jessie; Zhao, Xiaoai; Tamamori-Adachi, Mimi; Sedivy, John M

2011-10-01

Replicative cellular senescence was discovered some 50 years ago. The phenotypes of senescent cells have been investigated extensively in cell culture, and found to affect essentially all aspects of cellular physiology. The relevance of cellular senescence in the context of age-associated pathologies as well as normal aging is a topic of active and ongoing interest. Considerable effort has been devoted to biomarker discovery to enable the microscopic detection of single senescent cells in tissues. One characteristic of senescent cells documented very early in cell culture studies was an increase in cell size and total protein content, but whether this occurs in vivo is not known. A limiting factor for studies of protein content and localization has been the lack of suitable fluorescence microscopy tools. We have developed an easy and flexible method, based on the merocyanine dye known as NanoOrange, to visualize and quantitatively measure total protein levels by high resolution fluorescence microscopy. NanoOrange staining can be combined with antibody-based immunofluorescence, thus providing both specific target and total protein information in the same specimen. These methods are optimally combined with automated image analysis platforms for high throughput analysis. We document here increasing protein content and density in nuclei of senescent human and mouse fibroblasts in vitro, and in liver nuclei of aged mice in vivo. Additionally, in aged liver nuclei NanoOrange revealed protein-dense foci that colocalize with centromeric heterochromatin.

Determination of the Optimized Automation Rate considering Effects of Automation on Human Operators in Nuclear Power Plants

International Nuclear Information System (INIS)

Lee, Seung Min; Seong, Poong Hyun; Kim, Jong Hyun; Kim, Man Cheol

2015-01-01

Automation refers to the use of a device or a system to perform a function previously performed by a human operator. It is introduced to reduce the human errors and to enhance the performance in various industrial fields, including the nuclear industry. However, these positive effects are not always achieved in complex systems such as nuclear power plants (NPPs). An excessive introduction of automation can generate new roles for human operators and change activities in unexpected ways. As more automation systems are accepted, the ability of human operators to detect automation failures and resume manual control is diminished. This disadvantage of automation is called the Out-of-the- Loop (OOTL) problem. We should consider the positive and negative effects of automation at the same time to determine the appropriate level of the introduction of automation. Thus, in this paper, we suggest an estimation method to consider the positive and negative effects of automation at the same time to determine the appropriate introduction of automation. This concept is limited in that it does not consider the effects of automation on human operators. Thus, a new estimation method for automation rate was suggested to overcome this problem

Optimized and Automated Radiosynthesis of [18F]DHMT for Translational Imaging of Reactive Oxygen Species with Positron Emission Tomography

Directory of Open Access Journals (Sweden)

Wenjie Zhang

2016-12-01

Full Text Available Reactive oxygen species (ROS play important roles in cell signaling and homeostasis. However, an abnormally high level of ROS is toxic, and is implicated in a number of diseases. Positron emission tomography (PET imaging of ROS can assist in the detection of these diseases. For the purpose of clinical translation of [18F]6-(4-((1-(2-fluoroethyl-1H-1,2,3-triazol-4-ylmethoxyphenyl-5-methyl-5,6-dihydrophenanthridine-3,8-diamine ([18F]DHMT, a promising ROS PET radiotracer, we first manually optimized the large-scale radiosynthesis conditions and then implemented them in an automated synthesis module. Our manual synthesis procedure afforded [18F]DHMT in 120 min with overall radiochemical yield (RCY of 31.6% ± 9.3% (n = 2, decay-uncorrected and specific activity of 426 ± 272 GBq/µmol (n = 2. Fully automated radiosynthesis of [18F]DHMT was achieved within 77 min with overall isolated RCY of 6.9% ± 2.8% (n = 7, decay-uncorrected and specific activity of 155 ± 153 GBq/µmol (n = 7 at the end of synthesis. This study is the first demonstration of producing 2-[18F]fluoroethyl azide by an automated module, which can be used for a variety of PET tracers through click chemistry. It is also the first time that [18F]DHMT was successfully tested for PET imaging in a healthy beagle dog.

Single-cell tracking reveals antibiotic-induced changes in mycobacterial energy metabolism.

Science.gov (United States)

Maglica, Željka; Özdemir, Emre; McKinney, John D

2015-02-17

method described here for single-cell tracking of intracellular ATP in live bacteria has many advantages compared to conventional ensemble-averaged assays. It provides a continuous real-time readout of bacterial ATP content, cell vitality, and antimicrobial mechanism of action with high temporal resolution at the single-cell level. In combination with high-throughput microfluidic devices and automated microscopy, this method also has the potential to serve as a novel screening tool in antimicrobial drug discovery. Copyright © 2015 Maglica et al.

The effect of increased centrifugation temperature on the quality of red-blood-cell concentrates of automated whole blood processing.

Science.gov (United States)

Weinigel, C; Rummler, S; Barz, D

2013-10-01

There are manual and automated methods to separate whole blood (WB) available. The Atreus whole blood processing system is an automated method, which combines centrifugation and expression of components into a single device. A major difference to conventional methods is that centrifugation temperature is not controlled at 22°C. The aim of this study was to examine the influence of increased centrifugation temperatures on the quality of red-blood-cell concentrates (RCC) after active cooling of WB prior to processing. A total of 28 WB were processed: 16 at centrifugation temperatures of up to 28°C (1st protocol) and 12 at 34°C (2nd protocol). RCC quality parameters were tested weekly for 42 days. Red-blood-cell concentrates (RCC) quality complied with the European and German guidelines. Haemolysis was not significantly different throughout storage. Significant statistical differences were detected between both protocols in potassium concentration at the end of storage and in ATP levels at the day of processing. Centrifugation temperatures of up to 34°C are well tolerated by the red blood cells with minimal interference with the RCC quality parameters. © 2013 International Society of Blood Transfusion.

An agar gel membrane-PDMS hybrid microfluidic device for long term single cell dynamic study.

Science.gov (United States)

Wong, Ieong; Atsumi, Shota; Huang, Wei-Chih; Wu, Tung-Yun; Hanai, Taizo; Lam, Miu-Ling; Tang, Ping; Yang, Jian; Liao, James C; Ho, Chih-Ming

2010-10-21

Significance of single cell measurements stems from the substantial temporal fluctuations and cell-cell variability possessed by individual cells. A major difficulty in monitoring surface non-adherent cells such as bacteria and yeast is that these cells tend to aggregate into clumps during growth, obstructing the tracking or identification of single-cells over long time periods. Here, we developed a microfluidic platform for long term single-cell tracking and cultivation with continuous media refreshing and dynamic chemical perturbation capability. The design highlights a simple device-assembly process between PDMS microchannel and agar membrane through conformal contact, and can be easily adapted by microbiologists for their routine laboratory use. The device confines cell growth in monolayer between an agar membrane and a glass surface. Efficient nutrient diffusion through the membrane and reliable temperature maintenance provide optimal growth condition for the cells, which exhibited fast exponential growth and constant distribution of cell sizes. More than 24 h of single-cell tracking was demonstrated on a transcription-metabolism integrated synthetic biological model, the gene-metabolic oscillator. Single cell morphology study under alcohol toxicity allowed us to discover and characterize cell filamentation exhibited by different E. coli isobutanol tolerant strains. We believe this novel device will bring new capabilities to quantitative microbiology, providing a versatile platform for single cell dynamic studies.

Microseismic event location using global optimization algorithms: An integrated and automated workflow

Science.gov (United States)

Lagos, Soledad R.; Velis, Danilo R.

2018-02-01

We perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing (VFSA) and Particle Swarm Optimization (PSO), and compare them against the classical grid search (GS). To this end, we present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data. First, we carry out the automatic detection, denoising and identification of the P- and S-waves. Secondly, we estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate. Finally, after taking proper care of the size of the search space using the backazimuth information, we perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes. We assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.

Technologies for Single-Cell Isolation

Science.gov (United States)

Gross, Andre; Schoendube, Jonas; Zimmermann, Stefan; Steeb, Maximilian; Zengerle, Roland; Koltay, Peter

2015-01-01

The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field. PMID:26213926

Technologies for Single-Cell Isolation

Directory of Open Access Journals (Sweden)

Andre Gross

2015-07-01

Full Text Available The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting respectively Flow cytometry (33% usage, laser microdissection (17%, manual cell picking (17%, random seeding/dilution (15%, and microfluidics/lab-on-a-chip devices (12% are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.

Technologies for Single-Cell Isolation.

Science.gov (United States)

Gross, Andre; Schoendube, Jonas; Zimmermann, Stefan; Steeb, Maximilian; Zengerle, Roland; Koltay, Peter

2015-07-24

The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.

Designing a fully automated multi-bioreactor plant for fast DoE optimization of pharmaceutical protein production.

Science.gov (United States)

Fricke, Jens; Pohlmann, Kristof; Jonescheit, Nils A; Ellert, Andree; Joksch, Burkhard; Luttmann, Reiner

2013-06-01

The identification of optimal expression conditions for state-of-the-art production of pharmaceutical proteins is a very time-consuming and expensive process. In this report a method for rapid and reproducible optimization of protein expression in an in-house designed small-scale BIOSTAT® multi-bioreactor plant is described. A newly developed BioPAT® MFCS/win Design of Experiments (DoE) module (Sartorius Stedim Systems, Germany) connects the process control system MFCS/win and the DoE software MODDE® (Umetrics AB, Sweden) and enables therefore the implementation of fully automated optimization procedures. As a proof of concept, a commercial Pichia pastoris strain KM71H has been transformed for the expression of potential malaria vaccines. This approach has allowed a doubling of intact protein secretion productivity due to the DoE optimization procedure compared to initial cultivation results. In a next step, robustness regarding the sensitivity to process parameter variability has been proven around the determined optimum. Thereby, a pharmaceutical production process that is significantly improved within seven 24-hour cultivation cycles was established. Specifically, regarding the regulatory demands pointed out in the process analytical technology (PAT) initiative of the United States Food and Drug Administration (FDA), the combination of a highly instrumented, fully automated multi-bioreactor platform with proper cultivation strategies and extended DoE software solutions opens up promising benefits and opportunities for pharmaceutical protein production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microfluidic cartridges for automated, point-of-care blood cell counting

CSIR Research Space (South Africa)

Smith, Suzanne

2016-11-01

Full Text Available Disposable, low-cost microfluidic cartridges for automated blood cell counting applications are presented in this article. The need for point-of-care medical diagnostic tools is evident, particularly in low-resource and rural settings, and a full...

Automated property optimization via ab initio O(N) elongation method: Application to (hyper-)polarizability in DNA

Energy Technology Data Exchange (ETDEWEB)

Orimoto, Yuuichi, E-mail: orimoto.yuuichi.888@m.kyushu-u.ac.jp [Department of Material Sciences, Faculty of Engineering Sciences, Kyushu University, 6-1 Kasuga-Park, Fukuoka 816-8580 (Japan); Aoki, Yuriko [Department of Material Sciences, Faculty of Engineering Sciences, Kyushu University, 6-1 Kasuga-Park, Fukuoka 816-8580 (Japan); Japan Science and Technology Agency, CREST, 4-1-8 Hon-chou, Kawaguchi, Saitama 332-0012 (Japan)

2016-07-14

An automated property optimization method was developed based on the ab initio O(N) elongation (ELG) method and applied to the optimization of nonlinear optical (NLO) properties in DNA as a first test. The ELG method mimics a polymerization reaction on a computer, and the reaction terminal of a starting cluster is attacked by monomers sequentially to elongate the electronic structure of the system by solving in each step a limited space including the terminal (localized molecular orbitals at the terminal) and monomer. The ELG-finite field (ELG-FF) method for calculating (hyper-)polarizabilities was used as the engine program of the optimization method, and it was found to show linear scaling efficiency while maintaining high computational accuracy for a random sequenced DNA model. Furthermore, the self-consistent field convergence was significantly improved by using the ELG-FF method compared with a conventional method, and it can lead to more feasible NLO property values in the FF treatment. The automated optimization method successfully chose an appropriate base pair from four base pairs (A, T, G, and C) for each elongation step according to an evaluation function. From test optimizations for the first order hyper-polarizability (β) in DNA, a substantial difference was observed depending on optimization conditions between “choose-maximum” (choose a base pair giving the maximum β for each step) and “choose-minimum” (choose a base pair giving the minimum β). In contrast, there was an ambiguous difference between these conditions for optimizing the second order hyper-polarizability (γ) because of the small absolute value of γ and the limitation of numerical differential calculations in the FF method. It can be concluded that the ab initio level property optimization method introduced here can be an effective step towards an advanced computer aided material design method as long as the numerical limitation of the FF method is taken into account.

Automated property optimization via ab initio O(N) elongation method: Application to (hyper-)polarizability in DNA

International Nuclear Information System (INIS)

Orimoto, Yuuichi; Aoki, Yuriko

2016-01-01

An automated property optimization method was developed based on the ab initio O(N) elongation (ELG) method and applied to the optimization of nonlinear optical (NLO) properties in DNA as a first test. The ELG method mimics a polymerization reaction on a computer, and the reaction terminal of a starting cluster is attacked by monomers sequentially to elongate the electronic structure of the system by solving in each step a limited space including the terminal (localized molecular orbitals at the terminal) and monomer. The ELG-finite field (ELG-FF) method for calculating (hyper-)polarizabilities was used as the engine program of the optimization method, and it was found to show linear scaling efficiency while maintaining high computational accuracy for a random sequenced DNA model. Furthermore, the self-consistent field convergence was significantly improved by using the ELG-FF method compared with a conventional method, and it can lead to more feasible NLO property values in the FF treatment. The automated optimization method successfully chose an appropriate base pair from four base pairs (A, T, G, and C) for each elongation step according to an evaluation function. From test optimizations for the first order hyper-polarizability (β) in DNA, a substantial difference was observed depending on optimization conditions between “choose-maximum” (choose a base pair giving the maximum β for each step) and “choose-minimum” (choose a base pair giving the minimum β). In contrast, there was an ambiguous difference between these conditions for optimizing the second order hyper-polarizability (γ) because of the small absolute value of γ and the limitation of numerical differential calculations in the FF method. It can be concluded that the ab initio level property optimization method introduced here can be an effective step towards an advanced computer aided material design method as long as the numerical limitation of the FF method is taken into account.

Titanium dioxide antireflection coating for silicon solar cells by spray deposition

Science.gov (United States)

Kern, W.; Tracy, E.

1980-01-01

A high-speed production process is described for depositing a single-layer, quarter-wavelength thick antireflection coating of titanium dioxide on metal-patterned single-crystal silicon solar cells for terrestrial applications. Controlled atomization spraying of an organotitanium solution was selected as the most cost-effective method of film deposition using commercial automated equipment. The optimal composition consists of titanium isopropoxide as the titanium source, n-butyl acetate as the diluent solvent, sec-butanol as the leveling agent, and 2-ethyl-1-hexanol to render the material uniformly depositable. Application of the process to the coating of circular, large-diameter solar cells with either screen-printed silver metallization or with vacuum-evaporated Ti/Pd/Ag metallization showed increases of over 40% in the electrical conversion efficiency. Optical characteristics, corrosion resistance, and several other important properties of the spray-deposited film are reported. Experimental evidence indicates a wide tolerance in the coating thickness upon the overall efficiency of the cell. Considerations pertaining to the optimization of AR coatings in general are discussed, and a comprehensive critical survey of the literature is presented.

Automation in nuclear hot cells (Paper No. 020)

International Nuclear Information System (INIS)

Pal, B.C.; Chougule, A.S.; Radke, M.G.; Ramaswamy, N.V.; Ramkumar, M.S.

1987-02-01

Bhabha Atomic Research Centre (BARC) in Trombay produces radioactive sources for a wide variety of uses in industry, agriculture and medicine, both within the country and abroad. The production and delivery of the radioactive sources in a form, ready for the end use, entails a number of operations, most of which are to be done with remote handling facilities, to maintain the prescribed biological shield to protect the operators. One of the repetitive operation among these which has to be done inside a concrete shielded hot-cell is the picking up of tiny radioactive wafers of iridium as small as 2.5mm dia., 0.3mm thick placing them in the required numbers to make up the total activity inside a capsule, closing the capsule with a top lid and finally welding the capsule. For doing this job remotely, recourse had to be taken to the use of master-slave manipulators (MSM), needing highly skilled operators to handle it for such delicate jobs repetitively. The operations for this repetitive job unlike most of other hot-cell operations, can be structured for machine operation and also fully automated. An automated system synthesising electromechanical, pneumatic and welding operations developed by the Division of Remote Handling and Robotics, BARC is described here. This relieves the operator of a number of jobs, to be repetitively done by MSM which would be strenous and taxing on account of the extremely small sizes of the pellets and wafers when they are to be handled, by remote indirect means with reliance on the master slave manipulators. A description of the automated system is given. (author). 3 figs

Autonomous guided vehicles methods and models for optimal path planning

CERN Document Server

Fazlollahtabar, Hamed

2015-01-01

  This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...

Automated Robust Maneuver Design and Optimization

Data.gov (United States)

National Aeronautics and Space Administration — NASA is seeking improvements to the current technologies related to Position, Navigation and Timing. In particular, it is desired to automate precise maneuver...

Optimal Design of Gradient Materials and Bi-Level Optimization of Topology Using Targets (BOTT)

Science.gov (United States)

Garland, Anthony

The objective of this research is to understand the fundamental relationships necessary to develop a method to optimize both the topology and the internal gradient material distribution of a single object while meeting constraints and conflicting objectives. Functionally gradient material (FGM) objects possess continuous varying material properties throughout the object, and they allow an engineer to tailor individual regions of an object to have specific mechanical properties by locally modifying the internal material composition. A variety of techniques exists for topology optimization, and several methods exist for FGM optimization, but combining the two together is difficult. Understanding the relationship between topology and material gradient optimization enables the selection of an appropriate model and the development of algorithms, which allow engineers to design high-performance parts that better meet design objectives than optimized homogeneous material objects. For this research effort, topology optimization means finding the optimal connected structure with an optimal shape. FGM optimization means finding the optimal macroscopic material properties within an object. Tailoring the material constitutive matrix as a function of position results in gradient properties. Once, the target macroscopic properties are known, a mesostructure or a particular material nanostructure can be found which gives the target material properties at each macroscopic point. This research demonstrates that topology and gradient materials can both be optimized together for a single part. The algorithms use a discretized model of the domain and gradient based optimization algorithms. In addition, when considering two conflicting objectives the algorithms in this research generate clear 'features' within a single part. This tailoring of material properties within different areas of a single part (automated design of 'features') using computational design tools is a novel benefit

Automated methods for single-stranded DNA isolation and dideoxynucleotide DNA sequencing reactions on a robotic workstation

International Nuclear Information System (INIS)

Mardis, E.R.; Roe, B.A.

1989-01-01

Automated procedures have been developed for both the simultaneous isolation of 96 single-stranded M13 chimeric template DNAs in less than two hours, and for simultaneously pipetting 24 dideoxynucleotide sequencing reactions on a commercially available laboratory workstation. The DNA sequencing results obtained by either radiolabeled or fluorescent methods are consistent with the premise that automation of these portions of DNA sequencing projects will improve the reproducibility of the DNA isolation and the procedures for these normally labor-intensive steps provides an approach for rapid acquisition of large amounts of high quality, reproducible DNA sequence data

Long-term live cell imaging and automated 4D analysis of drosophila neuroblast lineages.

Directory of Open Access Journals (Sweden)

Catarina C F Homem

Full Text Available The developing Drosophila brain is a well-studied model system for neurogenesis and stem cell biology. In the Drosophila central brain, around 200 neural stem cells called neuroblasts undergo repeated rounds of asymmetric cell division. These divisions typically generate a larger self-renewing neuroblast and a smaller ganglion mother cell that undergoes one terminal division to create two differentiating neurons. Although single mitotic divisions of neuroblasts can easily be imaged in real time, the lack of long term imaging procedures has limited the use of neuroblast live imaging for lineage analysis. Here we describe a method that allows live imaging of cultured Drosophila neuroblasts over multiple cell cycles for up to 24 hours. We describe a 4D image analysis protocol that can be used to extract cell cycle times and growth rates from the resulting movies in an automated manner. We use it to perform lineage analysis in type II neuroblasts where clonal analysis has indicated the presence of a transit-amplifying population that potentiates the number of neurons. Indeed, our experiments verify type II lineages and provide quantitative parameters for all cell types in those lineages. As defects in type II neuroblast lineages can result in brain tumor formation, our lineage analysis method will allow more detailed and quantitative analysis of tumorigenesis and asymmetric cell division in the Drosophila brain.

Qualification of academic facilities for small-scale automated manufacture of autologous cell-based products.

Science.gov (United States)

Hourd, Paul; Chandra, Amit; Alvey, David; Ginty, Patrick; McCall, Mark; Ratcliffe, Elizabeth; Rayment, Erin; Williams, David J

2014-01-01

Academic centers, hospitals and small companies, as typical development settings for UK regenerative medicine assets, are significant contributors to the development of autologous cell-based therapies. Often lacking the appropriate funding, quality assurance heritage or specialist regulatory expertise, qualifying aseptic cell processing facilities for GMP compliance is a significant challenge. The qualification of a new Cell Therapy Manufacturing Facility with automated processing capability, the first of its kind in a UK academic setting, provides a unique demonstrator for the qualification of small-scale, automated facilities for GMP-compliant manufacture of autologous cell-based products in these settings. This paper shares our experiences in qualifying the Cell Therapy Manufacturing Facility, focusing on our approach to streamlining the qualification effort, the challenges, project delays and inefficiencies we encountered, and the subsequent lessons learned.

A Miniature Probe for Ultrasonic Penetration of a Single Cell

Directory of Open Access Journals (Sweden)

Mingfei Xiao

2009-05-01

Full Text Available Although ultrasound cavitation must be avoided for safe diagnostic applications, the ability of ultrasound to disrupt cell membranes has taken on increasing significance as a method to facilitate drug and gene delivery. A new ultrasonic resonance driving method is introduced to penetrate rigid wall plant cells or oocytes with springy cell membranes. When a reasonable design is created, ultrasound can gather energy and increase the amplitude factor. Ultrasonic penetration enables exogenous materials to enter cells without damaging them by utilizing instant acceleration. This paper seeks to develop a miniature ultrasonic probe experiment system for cell penetration. A miniature ultrasonic probe is designed and optimized using the Precise Four Terminal Network Method and Finite Element Method (FEM and an ultrasonic generator to drive the probe is designed. The system was able to successfully puncture a single fish cell.

Automated flow cytometric analysis across large numbers of samples and cell types.

Science.gov (United States)

Chen, Xiaoyi; Hasan, Milena; Libri, Valentina; Urrutia, Alejandra; Beitz, Benoît; Rouilly, Vincent; Duffy, Darragh; Patin, Étienne; Chalmond, Bernard; Rogge, Lars; Quintana-Murci, Lluis; Albert, Matthew L; Schwikowski, Benno

2015-04-01

Multi-parametric flow cytometry is a key technology for characterization of immune cell phenotypes. However, robust high-dimensional post-analytic strategies for automated data analysis in large numbers of donors are still lacking. Here, we report a computational pipeline, called FlowGM, which minimizes operator input, is insensitive to compensation settings, and can be adapted to different analytic panels. A Gaussian Mixture Model (GMM)-based approach was utilized for initial clustering, with the number of clusters determined using Bayesian Information Criterion. Meta-clustering in a reference donor permitted automated identification of 24 cell types across four panels. Cluster labels were integrated into FCS files, thus permitting comparisons to manual gating. Cell numbers and coefficient of variation (CV) were similar between FlowGM and conventional gating for lymphocyte populations, but notably FlowGM provided improved discrimination of "hard-to-gate" monocyte and dendritic cell (DC) subsets. FlowGM thus provides rapid high-dimensional analysis of cell phenotypes and is amenable to cohort studies. Copyright © 2015. Published by Elsevier Inc.

Automated cell counts on CSF samples: A multicenter performance evaluation of the GloCyte system.

Science.gov (United States)

Hod, E A; Brugnara, C; Pilichowska, M; Sandhaus, L M; Luu, H S; Forest, S K; Netterwald, J C; Reynafarje, G M; Kratz, A

2018-02-01

Automated cell counters have replaced manual enumeration of cells in blood and most body fluids. However, due to the unreliability of automated methods at very low cell counts, most laboratories continue to perform labor-intensive manual counts on many or all cerebrospinal fluid (CSF) samples. This multicenter clinical trial investigated if the GloCyte System (Advanced Instruments, Norwood, MA), a recently FDA-approved automated cell counter, which concentrates and enumerates red blood cells (RBCs) and total nucleated cells (TNCs), is sufficiently accurate and precise at very low cell counts to replace all manual CSF counts. The GloCyte System concentrates CSF and stains RBCs with fluorochrome-labeled antibodies and TNCs with nucleic acid dyes. RBCs and TNCs are then counted by digital image analysis. Residual adult and pediatric CSF samples obtained for clinical analysis at five different medical centers were used for the study. Cell counts were performed by the manual hemocytometer method and with the GloCyte System following the same protocol at all sites. The limits of the blank, detection, and quantitation, as well as precision and accuracy of the GloCyte, were determined. The GloCyte detected as few as 1 TNC/μL and 1 RBC/μL, and reliably counted as low as 3 TNCs/μL and 2 RBCs/μL. The total coefficient of variation was less than 20%. Comparison with cell counts obtained with a hemocytometer showed good correlation (>97%) between the GloCyte and the hemocytometer, including at very low cell counts. The GloCyte instrument is a precise, accurate, and stable system to obtain red cell and nucleated cell counts in CSF samples. It allows for the automated enumeration of even very low cell numbers, which is crucial for CSF analysis. These results suggest that GloCyte is an acceptable alternative to the manual method for all CSF samples, including those with normal cell counts. © 2017 John Wiley & Sons Ltd.

Lessons from single-cell transcriptome analysis of oxygen-sensing cells.

Science.gov (United States)

Zhou, Ting; Matsunami, Hiroaki

2018-05-01

The advent of single-cell RNA-sequencing (RNA-Seq) technology has enabled transcriptome profiling of individual cells. Comprehensive gene expression analysis at the single-cell level has proven to be effective in characterizing the most fundamental aspects of cellular function and identity. This unbiased approach is revolutionary for small and/or heterogeneous tissues like oxygen-sensing cells in identifying key molecules. Here, we review the major methods of current single-cell RNA-Seq technology. We discuss how this technology has advanced the understanding of oxygen-sensing glomus cells in the carotid body and helped uncover novel oxygen-sensing cells and mechanisms in the mice olfactory system. We conclude by providing our perspective on future single-cell RNA-Seq research directed at oxygen-sensing cells.

Integrating Test-Form Formatting into Automated Test Assembly

Science.gov (United States)

Diao, Qi; van der Linden, Wim J.

2013-01-01

Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using…

Single-gene testing combined with single nucleotide polymorphism microarray preimplantation genetic diagnosis for aneuploidy: a novel approach in optimizing pregnancy outcome.

Science.gov (United States)

Brezina, Paul R; Benner, Andrew; Rechitsky, Svetlana; Kuliev, Anver; Pomerantseva, Ekaterina; Pauling, Dana; Kearns, William G

2011-04-01

To describe a method of amplifying DNA from blastocyst trophectoderm cells (two or three cells) and simultaneously performing 23-chromosome single nucleotide polymorphism microarrays and single-gene preimplantation genetic diagnosis. Case report. IVF clinic and preimplantation genetic diagnostic centers. A 36-year-old woman, gravida 2, para 1011, and her husband who both were carriers of GM(1) gangliosidosis. The couple wished to proceed with microarray analysis for aneuploidy detection coupled with DNA sequencing for GM(1) gangliosidosis. An IVF cycle was performed. Ten blastocyst-stage embryos underwent trophectoderm biopsy. Twenty-three-chromosome microarray analysis for aneuploidy and specific DNA sequencing for GM(1) gangliosidosis mutations were performed. Viable pregnancy. After testing, elective single embryo transfer was performed followed by an intrauterine pregnancy with documented fetal cardiac activity by ultrasound. Twenty-three-chromosome microarray analysis for aneuploidy detection and single-gene evaluation via specific DNA sequencing and linkage analysis are used for preimplantation diagnosis for single-gene disorders and aneuploidy. Because of the minimal amount of genetic material obtained from the day 3 to 5 embryos (up to 6 pg), these modalities have been used in isolation of each other. The use of preimplantation genetic diagnosis for aneuploidy coupled with testing for single-gene disorders via trophectoderm biopsy is a novel approach to maximize pregnancy outcomes. Although further investigation is warranted, preimplantation genetic diagnosis for aneuploidy and single-gene testing seem destined to be used increasingly to optimize ultimate pregnancy success. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Unravel lipid accumulation mechanism in oleaginous yeast through single cell systems biology study

Energy Technology Data Exchange (ETDEWEB)

Ding, Shiyou; Xiaoliang, Xie

2017-12-18

Replacement of petroleum with advanced biofuels is critical for environmental protection needs, sustainable and secure energy demands, and economic development. Bacteria, yeasts, and fungi can naturally synthesize fatty acids, isoprenoids, or polyalkanoates for energy storage, and therefore are currently explored for hydrocarbon fuel production. Oleaginous yeasts can accumulate high levels of lipids in the form of triacylglycerols (TAGs) when encountering stress conditions or imbalanced growth (e.g., growing under excess carbon sources and limited nitrogen conditions). Advantages of using oleaginous yeast as cell factories include short duplication time (< 1 hour), high yield of intracellular droplets, and easy scale-up for industrial production. Currently, various oleaginous yeasts (e.g., Yarrowia, Candida, Rhodotorulla, Rhodosporidium, Cryptococcus, Trichosporon, and Lipomyces) have been developed as potential advanced biofuel producers. Oleaginous yeast lipid production has two phases: 1) growth phase, where cells utilize the carbon and nitrogen source to build up biomass. And 2) lipid accumulation phase, where they convert carbon source in media into the storage lipid body. (i.e. a high carbon to nitrogen ratio leads to high lipid production). The lipid production varies dramatically when different sugar, e.g. glucose, xylose is used as carbon source. The efficient utilization of all monomeric sugars of hexoses and pentoses from various lignocellulosic biomass processing approaches is the key for economic lignocellulosic biofuel production. In this project, we explored lipid production in oleaginous yeast under different nitrogen and sugar conditions at the single-cell level. To understand the lipid production mechanism and identify genetic features responsive to lipid accumulation in the presence of pentose and nitrogen, we developed an automated chemical imaging and single-cell transcriptomics method to correlate the lipid accumulation with the

Automated quantification of epicardial adipose tissue using CT angiography: evaluation of a prototype software

International Nuclear Information System (INIS)

Spearman, James V.; Silverman, Justin R.; Krazinski, Aleksander W.; Costello, Philip; Meinel, Felix G.; Geyer, Lucas L.; Schoepf, U.J.; Apfaltrer, Paul; Canstein, Christian; De Cecco, Carlo Nicola

2014-01-01

This study evaluated the performance of a novel automated software tool for epicardial fat volume (EFV) quantification compared to a standard manual technique at coronary CT angiography (cCTA). cCTA data sets of 70 patients (58.6 ± 12.9 years, 33 men) were retrospectively analysed using two different post-processing software applications. Observer 1 performed a manual single-plane pericardial border definition and EFV M segmentation (manual approach). Two observers used a software program with fully automated 3D pericardial border definition and EFV A calculation (automated approach). EFV and time required for measuring EFV (including software processing time and manual optimization time) for each method were recorded. Intraobserver and interobserver reliability was assessed on the prototype software measurements. T test, Spearman's rho, and Bland-Altman plots were used for statistical analysis. The final EFV A (with manual border optimization) was strongly correlated with the manual axial segmentation measurement (60.9 ± 33.2 mL vs. 65.8 ± 37.0 mL, rho = 0.970, P 0.9). Automated EFV A quantification is an accurate and time-saving method for quantification of EFV compared to established manual axial segmentation methods. (orig.)

Optimal multi-photon phase sensing with a single interference fringe

Science.gov (United States)

Xiang, G. Y.; Hofmann, H. F.; Pryde, G. J.

2013-01-01

Quantum entanglement can help to increase the precision of optical phase measurements beyond the shot noise limit (SNL) to the ultimate Heisenberg limit. However, the N-photon parity measurements required to achieve this optimal sensitivity are extremely difficult to realize with current photon detection technologies, requiring high-fidelity resolution of N + 1 different photon distributions between the output ports. Recent experimental demonstrations of precision beyond the SNL have therefore used only one or two photon-number detection patterns instead of parity measurements. Here we investigate the achievable phase sensitivity of the simple and efficient single interference fringe detection technique. We show that the maximally-entangled “NOON” state does not achieve optimal phase sensitivity when N > 4, rather, we show that the Holland-Burnett state is optimal. We experimentally demonstrate this enhanced sensitivity using a single photon-counted fringe of the six-photon Holland-Burnett state. Specifically, our single-fringe six-photon measurement achieves a phase variance three times below the SNL. PMID:24067490

An automated single ion hit at JAERI heavy ion microbeam to observe individual radiation damage

International Nuclear Information System (INIS)

Kamiya, Tomihiro; Sakai, Takuro; Naitoh, Yutaka; Hamano, Tsuyoshi; Hirao, Toshio

1999-01-01

Microbeam scanning and a single ion hit technique have been combined to establish an automated beam positioning and single ion hit system at the JAERI Takasaki heavy ion microbeam system. Single ion irradiation on preset points of a sample in various patterns can be performed automatically in a short period. The reliability of the system was demonstrated using CR-39 nuclear track detectors. Single ion hit patterns were achieved with a positioning accuracy of 2 μm or less. In measurement of single event transient current using this system, the reduction of the pulse height by accumulation of radiation damages was observed by single ion injection to the same local areas. This technique showed a possibility to get some quantitative information about the lateral displacement of an individual radiation effect in silicon PIN photodiodes. This paper will give details of the irradiation system and present results from several experiments

Single-cell measurement of red blood cell oxygen affinity.

Science.gov (United States)

Di Caprio, Giuseppe; Stokes, Chris; Higgins, John M; Schonbrun, Ethan

2015-08-11

Oxygen is transported throughout the body by hemoglobin (Hb) in red blood cells (RBCs). Although the oxygen affinity of blood is well-understood and routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of RBC volume and Hb concentration are taken millions of times per day by clinical hematology analyzers, and they are important factors in determining the health of the hematologic system. To better understand the variability and determinants of oxygen affinity on a cellular level, we have developed a system that quantifies the oxygen saturation, cell volume, and Hb concentration for individual RBCs in high throughput. We find that the variability in single-cell saturation peaks at an oxygen partial pressure of 2.9%, which corresponds to the maximum slope of the oxygen-Hb dissociation curve. In addition, single-cell oxygen affinity is positively correlated with Hb concentration but independent of osmolarity, which suggests variation in the Hb to 2,3-diphosphoglycerate (2-3 DPG) ratio on a cellular level. By quantifying the functional behavior of a cellular population, our system adds a dimension to blood cell analysis and other measurements of single-cell variability.

Single-Cell RNA Sequencing of Glioblastoma Cells.

Science.gov (United States)

Sen, Rajeev; Dolgalev, Igor; Bayin, N Sumru; Heguy, Adriana; Tsirigos, Aris; Placantonakis, Dimitris G

2018-01-01

Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.

Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors.

Science.gov (United States)

Mitra, A K; Mukherjee, U K; Harding, T; Jang, J S; Stessman, H; Li, Y; Abyzov, A; Jen, J; Kumar, S; Rajkumar, V; Van Ness, B

2016-05-01

Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that have a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Although genome profiling studies have demonstrated heterogeneity in subclonal architecture that may ultimately lead to relapse, a gene expression-based prediction program that can identify, distinguish and quantify drug response in sub-populations within a bulk population of myeloma cells is lacking. In this study, we performed targeted transcriptome analysis on 528 pre-treatment single cells from 11 myeloma cell lines and 418 single cells from 8 drug-naïve MM patients, followed by intensive bioinformatics and statistical analysis for prediction of proteasome inhibitor sensitivity in individual cells. Using our previously reported drug response gene expression profile signature at the single-cell level, we developed an R Statistical analysis package available at https://github.com/bvnlabSCATTome, SCATTome (single-cell analysis of targeted transcriptome), that restructures the data obtained from Fluidigm single-cell quantitative real-time-PCR analysis run, filters missing data, performs scaling of filtered data, builds classification models and predicts drug response of individual cells based on targeted transcriptome using an assortment of machine learning methods. Application of SCATT should contribute to clinically relevant analysis of intratumor heterogeneity, and better inform drug choices based on subclonal cellular responses.

Epigenetics reloaded: the single-cell revolution.

Science.gov (United States)

Bheda, Poonam; Schneider, Robert

2014-11-01

Mechanistically, how epigenetic states are inherited through cellular divisions remains an important open question in the chromatin field and beyond. Defining the heritability of epigenetic states and the underlying chromatin-based mechanisms within a population of cells is complicated due to cell heterogeneity combined with varying levels of stability of these states; thus, efforts must be focused toward single-cell analyses. The approaches presented here constitute the forefront of epigenetics research at the single-cell level using classic and innovative methods to dissect epigenetics mechanisms from the limited material available in a single cell. This review further outlines exciting future avenues of research to address the significance of epigenetic heterogeneity and the contributions of microfluidics technologies to single-cell isolation and analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fully automated microchip system for the detection of quantal exocytosis from single and small ensembles of cells

DEFF Research Database (Denmark)

Spégel, Christer; Heiskanen, Arto; Pedersen, Simon

2008-01-01

A lab-on-a-chip device that enables positioning of single or small ensembles of cells on an aperture in close proximity to a mercaptopropionic acid (MPA) modified sensing electrode has been developed and characterized. The microchip was used for the detection of Ca2+-dependent quantal catecholamine...

Multiobjective Multifactorial Optimization in Evolutionary Multitasking.

Science.gov (United States)

Gupta, Abhishek; Ong, Yew-Soon; Feng, Liang; Tan, Kay Chen

2016-05-03

In recent decades, the field of multiobjective optimization has attracted considerable interest among evolutionary computation researchers. One of the main features that makes evolutionary methods particularly appealing for multiobjective problems is the implicit parallelism offered by a population, which enables simultaneous convergence toward the entire Pareto front. While a plethora of related algorithms have been proposed till date, a common attribute among them is that they focus on efficiently solving only a single optimization problem at a time. Despite the known power of implicit parallelism, seldom has an attempt been made to multitask, i.e., to solve multiple optimization problems simultaneously. It is contended that the notion of evolutionary multitasking leads to the possibility of automated transfer of information across different optimization exercises that may share underlying similarities, thereby facilitating improved convergence characteristics. In particular, the potential for automated transfer is deemed invaluable from the standpoint of engineering design exercises where manual knowledge adaptation and reuse are routine. Accordingly, in this paper, we present a realization of the evolutionary multitasking paradigm within the domain of multiobjective optimization. The efficacy of the associated evolutionary algorithm is demonstrated on some benchmark test functions as well as on a real-world manufacturing process design problem from the composites industry.

Application of evolution strategy algorithm for optimization of a single-layer sound absorber

Directory of Open Access Journals (Sweden)

Morteza Gholamipoor

2014-12-01

Full Text Available Depending on different design parameters and limitations, optimization of sound absorbers has always been a challenge in the field of acoustic engineering. Various methods of optimization have evolved in the past decades with innovative method of evolution strategy gaining more attention in the recent years. Based on their simplicity and straightforward mathematical representations, single-layer absorbers have been widely used in both engineering and industrial applications and an optimized design for these absorbers has become vital. In the present study, the method of evolution strategy algorithm is used for optimization of a single-layer absorber at both a particular frequency and an arbitrary frequency band. Results of the optimization have been compared against different methods of genetic algorithm and penalty functions which are proved to be favorable in both effectiveness and accuracy. Finally, a single-layer absorber is optimized in a desired range of frequencies that is the main goal of an industrial and engineering optimization process.

Operation optimization of distributed generation using artificial intelligent techniques

Directory of Open Access Journals (Sweden)

Mahmoud H. Elkazaz

2016-06-01

Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.

Novel diffusion cell for in vitro transdermal permeation, compatible with automated dynamic sampling

NARCIS (Netherlands)

Bosman, I.J; Lawant, A.L; Avegaart, S.R.; Ensing, K; de Zeeuw, R.A

The development of a new diffusion cell for in vitro transdermal permeation is described. The so-called Kelder cells were used in combination with the ASPEC system (Automatic Sample Preparation with Extraction Columns), which is designed for the automation of solid-phase extractions (SPE). Instead

Optimize Etching Based Single Mode Fiber Optic Temperature Sensor

OpenAIRE

Ajay Kumar; Dr. Pramod Kumar

2014-01-01

This paper presents a description of etching process for fabrication single mode optical fiber sensors. The process of fabrication demonstrates an optimized etching based method to fabricate single mode fiber (SMF) optic sensors in specified constant time and temperature. We propose a single mode optical fiber based temperature sensor, where the temperature sensing region is obtained by etching its cladding diameter over small length to a critical value. It is observed that th...

Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells

Directory of Open Access Journals (Sweden)

Amanda L. Peterson

2016-09-01

Full Text Available Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions.

Automated quantification of epicardial adipose tissue using CT angiography: evaluation of a prototype software

Energy Technology Data Exchange (ETDEWEB)

Spearman, James V.; Silverman, Justin R.; Krazinski, Aleksander W.; Costello, Philip [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); Meinel, Felix G.; Geyer, Lucas L. [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); Ludwig-Maximilians-University Hospital, Institute for Clinical Radiology, Munich (Germany); Schoepf, U.J. [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); Medical University of South Carolina, Division of Cardiology, Department of Medicine, Charleston, SC (United States); Apfaltrer, Paul [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); University Medical Center Mannheim, Medical Faculty Mannheim - Heidelberg University, Institute of Clinical Radiology and Nuclear Medicine, Mannheim (Germany); Canstein, Christian [Siemens Medical Solutions USA, Inc., Malvern, PA (United States); De Cecco, Carlo Nicola [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); University of Rome ' ' Sapienza' ' - Polo Pontino, Department of Radiological Sciences, Oncology and Pathology, Latina (Italy)

2014-02-15

This study evaluated the performance of a novel automated software tool for epicardial fat volume (EFV) quantification compared to a standard manual technique at coronary CT angiography (cCTA). cCTA data sets of 70 patients (58.6 ± 12.9 years, 33 men) were retrospectively analysed using two different post-processing software applications. Observer 1 performed a manual single-plane pericardial border definition and EFV{sub M} segmentation (manual approach). Two observers used a software program with fully automated 3D pericardial border definition and EFV{sub A} calculation (automated approach). EFV and time required for measuring EFV (including software processing time and manual optimization time) for each method were recorded. Intraobserver and interobserver reliability was assessed on the prototype software measurements. T test, Spearman's rho, and Bland-Altman plots were used for statistical analysis. The final EFV{sub A} (with manual border optimization) was strongly correlated with the manual axial segmentation measurement (60.9 ± 33.2 mL vs. 65.8 ± 37.0 mL, rho = 0.970, P < 0.001). A mean of 3.9 ± 1.9 manual border edits were performed to optimize the automated process. The software prototype required significantly less time to perform the measurements (135.6 ± 24.6 s vs. 314.3 ± 76.3 s, P < 0.001) and showed high reliability (ICC > 0.9). Automated EFV{sub A} quantification is an accurate and time-saving method for quantification of EFV compared to established manual axial segmentation methods. (orig.)

An automated three-dimensional detection and segmentation method for touching cells by integrating concave points clustering and random walker algorithm.

Directory of Open Access Journals (Sweden)

Yong He

Full Text Available Characterizing cytoarchitecture is crucial for understanding brain functions and neural diseases. In neuroanatomy, it is an important task to accurately extract cell populations' centroids and contours. Recent advances have permitted imaging at single cell resolution for an entire mouse brain using the Nissl staining method. However, it is difficult to precisely segment numerous cells, especially those cells touching each other. As presented herein, we have developed an automated three-dimensional detection and segmentation method applied to the Nissl staining data, with the following two key steps: 1 concave points clustering to determine the seed points of touching cells; and 2 random walker segmentation to obtain cell contours. Also, we have evaluated the performance of our proposed method with several mouse brain datasets, which were captured with the micro-optical sectioning tomography imaging system, and the datasets include closely touching cells. Comparing with traditional detection and segmentation methods, our approach shows promising detection accuracy and high robustness.

Optimal design of a hybridization scheme with a fuel cell using genetic optimization

Science.gov (United States)

Rodriguez, Marco A.

Fuel cell is one of the most dependable "green power" technologies, readily available for immediate application. It enables direct conversion of hydrogen and other gases into electric energy without any pollution of the environment. However, the efficient power generation is strictly stationary process that cannot operate under dynamic environment. Consequently, fuel cell becomes practical only within a specially designed hybridization scheme, capable of power storage and power management functions. The resultant technology could be utilized to its full potential only when both the fuel cell element and the entire hybridization scheme are optimally designed. The design optimization in engineering is among the most complex computational tasks due to its multidimensionality, nonlinearity, discontinuity and presence of constraints in the underlying optimization problem. this research aims at the optimal utilization of the fuel cell technology through the use of genetic optimization, and advance computing. This study implements genetic optimization in the definition of optimum hybridization rules for a PEM fuel cell/supercapacitor power system. PEM fuel cells exhibit high energy density but they are not intended for pulsating power draw applications. They work better in steady state operation and thus, are often hybridized. In a hybrid system, the fuel cell provides power during steady state operation while capacitors or batteries augment the power of the fuel cell during power surges. Capacitors and batteries can also be recharged when the motor is acting as a generator. Making analogies to driving cycles, three hybrid system operating modes are investigated: 'Flat' mode, 'Uphill' mode, and 'Downhill' mode. In the process of discovering the switching rules for these three modes, we also generate a model of a 30W PEM fuel cell. This study also proposes the optimum design of a 30W PEM fuel cell. The PEM fuel cell model and hybridization's switching rules are postulated

Bioreactor design for successive culture of anchorage-dependent cells operated in an automated manner.

Science.gov (United States)

Kino-Oka, Masahiro; Ogawa, Natsuki; Umegaki, Ryota; Taya, Masahito

2005-01-01

A novel bioreactor system was designed to perform a series of batchwise cultures of anchorage-dependent cells by means of automated operations of medium change and passage for cell transfer. The experimental data on contamination frequency ensured the biological cleanliness in the bioreactor system, which facilitated the operations in a closed environment, as compared with that in flask culture system with manual handlings. In addition, the tools for growth prediction (based on growth kinetics) and real-time growth monitoring by measurement of medium components (based on small-volume analyzing machinery) were installed into the bioreactor system to schedule the operations of medium change and passage and to confirm that culture proceeds as scheduled, respectively. The successive culture of anchorage-dependent cells was conducted with the bioreactor running in an automated way. The automated bioreactor gave a successful culture performance with fair accordance to preset scheduling based on the information in the latest subculture, realizing 79- fold cell expansion for 169 h. In addition, the correlation factor between experimental data and scheduled values through the bioreactor performance was 0.998. It was concluded that the proposed bioreactor with the integration of the prediction and monitoring tools could offer a feasible system for the manufacturing process of cultured tissue products.

Systematic optimization of human pluripotent stem cells media using Design of Experiments

Science.gov (United States)

Marinho, Paulo A.; Chailangkarn, Thanathom; Muotri, Alysson R.

2015-05-01

Human pluripotent stem cells (hPSC) are used to study the early stages of human development in vitro and, increasingly due to somatic cell reprogramming, cellular and molecular mechanisms of disease. Cell culture medium is a critical factor for hPSC to maintain pluripotency and self-renewal. Numerous defined culture media have been empirically developed but never systematically optimized for culturing hPSC. We applied design of experiments (DOE), a powerful statistical tool, to improve the medium formulation for hPSC. Using pluripotency and cell growth as read-outs, we determined the optimal concentration of both basic fibroblast growth factor (bFGF) and neuregulin-1 beta 1 (NRG1β1). The resulting formulation, named iDEAL, improved the maintenance and passage of hPSC in both normal and stressful conditions, and affected trimethylated histone 3 lysine 27 (H3K27me3) epigenetic status after genetic reprogramming. It also enhances efficient hPSC plating as single cells. Altogether, iDEAL potentially allows scalable and controllable hPSC culture routine in translational research. Our DOE strategy could also be applied to hPSC differentiation protocols, which often require numerous and complex cell culture media.

A cell-based high-throughput screening assay for radiation susceptibility using automated cell counting

International Nuclear Information System (INIS)

Hodzic, Jasmina; Dingjan, Ilse; Maas, Mariëlle JP; Meulen-Muileman, Ida H van der; Menezes, Renee X de; Heukelom, Stan; Verheij, Marcel; Gerritsen, Winald R; Geldof, Albert A; Triest, Baukelien van; Beusechem, Victor W van

2015-01-01

Radiotherapy is one of the mainstays in the treatment for cancer, but its success can be limited due to inherent or acquired resistance. Mechanisms underlying radioresistance in various cancers are poorly understood and available radiosensitizers have shown only modest clinical benefit. There is thus a need to identify new targets and drugs for more effective sensitization of cancer cells to irradiation. Compound and RNA interference high-throughput screening technologies allow comprehensive enterprises to identify new agents and targets for radiosensitization. However, the gold standard assay to investigate radiosensitivity of cancer cells in vitro, the colony formation assay (CFA), is unsuitable for high-throughput screening. We developed a new high-throughput screening method for determining radiation susceptibility. Fast and uniform irradiation of batches up to 30 microplates was achieved using a Perspex container and a clinically employed linear accelerator. The readout was done by automated counting of fluorescently stained nuclei using the Acumen eX3 laser scanning cytometer. Assay performance was compared to that of the CFA and the CellTiter-Blue homogeneous uniform-well cell viability assay. The assay was validated in a whole-genome siRNA library screening setting using PC-3 prostate cancer cells. On 4 different cancer cell lines, the automated cell counting assay produced radiation dose response curves that followed a linear-quadratic equation and that exhibited a better correlation to the results of the CFA than did the cell viability assay. Moreover, the cell counting assay could be used to detect radiosensitization by silencing DNA-PKcs or by adding caffeine. In a high-throughput screening setting, using 4 Gy irradiated and control PC-3 cells, the effects of DNA-PKcs siRNA and non-targeting control siRNA could be clearly discriminated. We developed a simple assay for radiation susceptibility that can be used for high-throughput screening. This will aid

Automated Image Analysis for Quantitative Fluorescence In Situ Hybridization with Environmental Samples▿ †

OpenAIRE

Zhou, Zhi; Pons, Marie Noëlle; Raskin, Lutgarde; Zilles, Julie L.

2007-01-01

When fluorescence in situ hybridization (FISH) analyses are performed with complex environmental samples, difficulties related to the presence of microbial cell aggregates and nonuniform background fluorescence are often encountered. The objective of this study was to develop a robust and automated quantitative FISH method for complex environmental samples, such as manure and soil. The method and duration of sample dispersion were optimized to reduce the interference of cell aggregates. An au...

Strategies to Optimize Adult Stem Cell Therapy for Tissue Regeneration

Directory of Open Access Journals (Sweden)

Shan Liu

2016-06-01

Full Text Available Stem cell therapy aims to replace damaged or aged cells with healthy functioning cells in congenital defects, tissue injuries, autoimmune disorders, and neurogenic degenerative diseases. Among various types of stem cells, adult stem cells (i.e., tissue-specific stem cells commit to becoming the functional cells from their tissue of origin. These cells are the most commonly used in cell-based therapy since they do not confer risk of teratomas, do not require fetal stem cell maneuvers and thus are free of ethical concerns, and they confer low immunogenicity (even if allogenous. The goal of this review is to summarize the current state of the art and advances in using stem cell therapy for tissue repair in solid organs. Here we address key factors in cell preparation, such as the source of adult stem cells, optimal cell types for implantation (universal mesenchymal stem cells vs. tissue-specific stem cells, or induced vs. non-induced stem cells, early or late passages of stem cells, stem cells with endogenous or exogenous growth factors, preconditioning of stem cells (hypoxia, growth factors, or conditioned medium, using various controlled release systems to deliver growth factors with hydrogels or microspheres to provide apposite interactions of stem cells and their niche. We also review several approaches of cell delivery that affect the outcomes of cell therapy, including the appropriate routes of cell administration (systemic, intravenous, or intraperitoneal vs. local administration, timing for cell therapy (immediate vs. a few days after injury, single injection of a large number of cells vs. multiple smaller injections, a single site for injection vs. multiple sites and use of rodents vs. larger animal models. Future directions of stem cell-based therapies are also discussed to guide potential clinical applications.

Assessment of Automated Analyses of Cell Migration on Flat and Nanostructured Surfaces

DEFF Research Database (Denmark)

Gradinaru, Cristian; Lopacinska, Joanna M.; Huth, Johannes

2012-01-01

Motility studies of cells often rely on computer software that analyzes time-lapse recorded movies and establishes cell trajectories fully automatically. This raises the question of reproducibility of results, since different programs could yield significantly different results of such automated ...... to different segmentation methods. Unfortunately, population averages based on such different cell populations, differ significantly in some cases. Thus, results obtained with one software package are not necessarily reproducible by other software....

Optimization of Critical Hairpin Features Allows miRNA-based Gene Knockdown Upon Single-copy Transduction

Directory of Open Access Journals (Sweden)

Renier Myburgh

2014-01-01

Full Text Available Gene knockdown using micro RNA (miRNA-based vector constructs is likely to become a prominent gene therapy approach. It was the aim of this study to improve the efficiency of gene knockdown through optimizing the structure of miRNA mimics. Knockdown of two target genes was analyzed: CCR5 and green fluorescent protein. We describe here a novel and optimized miRNA mimic design called mirGE comprising a lower stem length of 13 base pairs (bp, positioning of the targeting strand on the 5′ side of the miRNA, together with nucleotide mismatches in upper stem positions 1 and 12 placed on the passenger strand. Our mirGE proved superior to miR-30 in four aspects: yield of targeting strand incorporation into RNA-induced silencing complex (RISC; incorporation into RISC of correct targeting strand; precision of cleavage by Drosha; and ratio of targeting strand over passenger strand. A triple mirGE hairpin cassette targeting CCR5 was constructed. It allowed CCR5 knockdown with an efficiency of over 90% upon single-copy transduction. Importantly, single-copy expression of this construct rendered transduced target cells, including primary human macrophages, resistant to infection with a CCR5-tropic strain of HIV. Our results provide new insights for a better knockdown efficiency of constructs containing miRNA. Our results also provide the proof-of-principle that cells can be rendered HIV resistant through single-copy vector transduction, rendering this approach more compatible with clinical applications.

Automated Test-Form Generation

Science.gov (United States)

van der Linden, Wim J.; Diao, Qi

2011-01-01

In automated test assembly (ATA), the methodology of mixed-integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different…

Optimizing solar-cell grid geometry

Science.gov (United States)

Crossley, A. P.

1969-01-01

Trade-off analysis and mathematical expressions calculate optimum grid geometry in terms of various cell parameters. Determination of the grid geometry provides proper balance between grid resistance and cell output to optimize the energy conversion process.

Assessment of the Current Level of Automation in the Manufacture of Fuel Cell Systems for Combined Heat and Power Applications

Energy Technology Data Exchange (ETDEWEB)

Ulsh, M.; Wheeler, D.; Protopappas, P.

2011-08-01

The U.S. Department of Energy (DOE) is interested in supporting manufacturing research and development (R&D) for fuel cell systems in the 10-1,000 kilowatt (kW) power range relevant to stationary and distributed combined heat and power applications, with the intent to reduce manufacturing costs and increase production throughput. To assist in future decision-making, DOE requested that the National Renewable Energy Laboratory (NREL) provide a baseline understanding of the current levels of adoption of automation in manufacturing processes and flow, as well as of continuous processes. NREL identified and visited or interviewed key manufacturers, universities, and laboratories relevant to the study using a standard questionnaire. The questionnaire covered the current level of vertical integration, the importance of quality control developments for automation, the current level of automation and source of automation design, critical balance of plant issues, potential for continuous cell manufacturing, key manufacturing steps or processes that would benefit from DOE support for manufacturing R&D, the potential for cell or stack design changes to support automation, and the relationship between production volume and decisions on automation.

Application-Oriented Optimal Shift Schedule Extraction for a Dual-Motor Electric Bus with Automated Manual Transmission

Directory of Open Access Journals (Sweden)

Mingjie Zhao

2018-02-01

Full Text Available The conventional battery electric buses (BEBs have limited potential to optimize the energy consumption and reach a better dynamic performance. A practical dual-motor equipped with 4-speed Automated Manual Transmission (AMT propulsion system is proposed, which can eliminate the traction interruption in conventional AMT. A discrete model of the dual-motor-AMT electric bus (DMAEB is built and used to optimize the gear shift schedule. Dynamic programming (DP algorithm is applied to find the optimal results where the efficiency and shift time of each gear are considered to handle the application problem of global optimization. A rational penalty factor and a proper shift time delay based on bench test results are set to reduce the shift frequency by 82.5% in Chinese-World Transient Vehicle Cycle (C-WTVC. Two perspectives of applicable shift rule extraction methods, i.e., the classification method based on optimal operating points and clustering method based on optimal shifting points, are explored and compared. Eventually, the hardware-in-the-loop (HIL simulation results demonstrate that the proposed structure and extracted shift schedule can realize a significant improvement in reducing energy loss by 20.13% compared to traditional empirical strategies.

Optimization of the Single Staggered Wire and Tube Heat Exchanger

Directory of Open Access Journals (Sweden)

Arsana I Made

2016-01-01

Full Text Available Wire and tube heat exchanger consists of a coiled tube, and wire is welded on the two sides of it in normal direction of the tube. Generally,wire and tube heat exchanger uses inline wire arrangement between the two sides, whereas in this study, it used staggered wire arrangement that reduces the restriction of convection heat transfer. This study performed the optimization of single staggered wire and tube heat exchanger to increase the capacity and reduce the mass of the heat exchanger. Optimization was conducted with the Hooke-Jeeves method, which aims to optimize the geometry of the heat exchanger, especially on the diameter (dw and the distance between wires (pw. The model developed to present heat transfer correlations on single staggered wire and tube heat exchanger was valid. The maximum optimization factor obtained when the diameter wire was 0.9 mm and the distance between wires (pw was 11 mm with the fref value = 1.5837. It means that the optimized design only using mass of 59,10 % and could transfer heat about 98,5 % from the basis design.

Single-cell regulome data analysis by SCRAT.

Science.gov (United States)

Ji, Zhicheng; Zhou, Weiqiang; Ji, Hongkai

2017-09-15

Emerging single-cell technologies (e.g. single-cell ATAC-seq, DNase-seq or ChIP-seq) have made it possible to assay regulome of individual cells. Single-cell regulome data are highly sparse and discrete. Analyzing such data is challenging. User-friendly software tools are still lacking. We present SCRAT, a Single-Cell Regulome Analysis Toolbox with a graphical user interface, for studying cell heterogeneity using single-cell regulome data. SCRAT can be used to conveniently summarize regulatory activities according to different features (e.g. gene sets, transcription factor binding motif sites, etc.). Using these features, users can identify cell subpopulations in a heterogeneous biological sample, infer cell identities of each subpopulation, and discover distinguishing features such as gene sets and transcription factors that show different activities among subpopulations. SCRAT is freely available at https://zhiji.shinyapps.io/scrat as an online web service and at https://github.com/zji90/SCRAT as an R package. hji@jhu.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell.

Science.gov (United States)

Nagano, Takashi; Lubling, Yaniv; Yaffe, Eitan; Wingett, Steven W; Dean, Wendy; Tanay, Amos; Fraser, Peter

2015-12-01

Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C-ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.

The Celution® System: Automated Processing of Adipose-Derived Regenerative Cells in a Functionally Closed System.

Science.gov (United States)

Fraser, John K; Hicok, Kevin C; Shanahan, Rob; Zhu, Min; Miller, Scott; Arm, Douglas M

2014-01-01

Objective: To develop a closed, automated system that standardizes the processing of human adipose tissue to obtain and concentrate regenerative cells suitable for clinical treatment of thermal and radioactive burn wounds. Approach: A medical device was designed to automate processing of adipose tissue to obtain a clinical-grade cell output of stromal vascular cells that may be used immediately as a therapy for a number of conditions, including nonhealing wounds resulting from radiation damage. Results: The Celution ® System reliably and reproducibly generated adipose-derived regenerative cells (ADRCs) from tissue collected manually and from three commercial power-assisted liposuction devices. The entire process of introducing tissue into the system, tissue washing and proteolytic digestion, isolation and concentration of the nonadipocyte nucleated cell fraction, and return to the patient as a wound therapeutic, can be achieved in approximately 1.5 h. An alternative approach that applies ultrasound energy in place of enzymatic digestion demonstrates extremely poor efficiency cell extraction. Innovation: The Celution System is the first medical device validated and approved by multiple international regulatory authorities to generate autologous stromal vascular cells from adipose tissue that can be used in a real-time bedside manner. Conclusion: Initial preclinical and clinical studies using ADRCs obtained using the automated tissue processing Celution device described herein validate a safe and effective manner to obtain a promising novel cell-based treatment for wound healing.

An automated and fast approach to detect single-trial visual evoked potentials with application to brain-computer interface.

Science.gov (United States)

Tu, Yiheng; Hung, Yeung Sam; Hu, Li; Huang, Gan; Hu, Yong; Zhang, Zhiguo

2014-12-01

This study aims (1) to develop an automated and fast approach for detecting visual evoked potentials (VEPs) in single trials and (2) to apply the single-trial VEP detection approach in designing a real-time and high-performance brain-computer interface (BCI) system. The single-trial VEP detection approach uses common spatial pattern (CSP) as a spatial filter and wavelet filtering (WF) a temporal-spectral filter to jointly enhance the signal-to-noise ratio (SNR) of single-trial VEPs. The performance of the joint spatial-temporal-spectral filtering approach was assessed in a four-command VEP-based BCI system. The offline classification accuracy of the BCI system was significantly improved from 67.6±12.5% (raw data) to 97.3±2.1% (data filtered by CSP and WF). The proposed approach was successfully implemented in an online BCI system, where subjects could make 20 decisions in one minute with classification accuracy of 90%. The proposed single-trial detection approach is able to obtain robust and reliable VEP waveform in an automatic and fast way and it is applicable in VEP based online BCI systems. This approach provides a real-time and automated solution for single-trial detection of evoked potentials or event-related potentials (EPs/ERPs) in various paradigms, which could benefit many applications such as BCI and intraoperative monitoring. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Single-cell technologies in environmental omics

KAUST Repository

Kodzius, Rimantas

2015-10-22

Environmental studies are primarily done by culturing isolated microorganisms or by amplifying and sequencing conserved genes. Difficulties understanding the complexity of large numbers of various microorganisms in an environment led to the development of techniques to enrich specific microorganisms for upstream analysis, ultimately leading to single-cell isolation and analyses. We discuss the significance of single-cell technologies in omics studies with focus on metagenomics and metatranscriptomics. We propose that by reducing sample heterogeneity using single-cell genomics, metaomic studies can be simplified.

Single-cell technologies in environmental omics

KAUST Repository

Kodzius, Rimantas; Gojobori, Takashi

2015-01-01

Environmental studies are primarily done by culturing isolated microorganisms or by amplifying and sequencing conserved genes. Difficulties understanding the complexity of large numbers of various microorganisms in an environment led to the development of techniques to enrich specific microorganisms for upstream analysis, ultimately leading to single-cell isolation and analyses. We discuss the significance of single-cell technologies in omics studies with focus on metagenomics and metatranscriptomics. We propose that by reducing sample heterogeneity using single-cell genomics, metaomic studies can be simplified.

Single-cell measurement of red blood cell oxygen affinity

OpenAIRE

Caprio, Di; Stokes, Chris; Higgins, John M.; Schonbrun, Ethan

2015-01-01

Oxygen is transported throughout the body by hemoglobin in red blood cells. While the oxygen affinity of blood is well understood and is routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of red blood cell volume and hemoglobin concentration are taken millions of times per day by clinical hematology analyzers and are important factors in determining the health of the hematologic system....

TH-AB-BRA-02: Automated Triplet Beam Orientation Optimization for MRI-Guided Co-60 Radiotherapy

International Nuclear Information System (INIS)

Nguyen, D; Thomas, D; Cao, M; O’Connor, D; Lamb, J; Sheng, K

2016-01-01

Purpose: MRI guided Co-60 provides daily and intrafractional MRI soft tissue imaging for improved target tracking and adaptive radiotherapy. To remedy the low output limitation, the system uses three Co-60 sources at 120° apart, but using all three sources in planning is considerably unintuitive. We automate the beam orientation optimization using column generation, and then solve a novel fluence map optimization (FMO) problem while regularizing the number of MLC segments. Methods: Three patients—1 prostate (PRT), 1 lung (LNG), and 1 head-and-neck boost plan (H&NBoost)—were evaluated. The beamlet dose for 180 equally spaced coplanar beams under 0.35 T magnetic field was calculated using Monte Carlo. The 60 triplets were selected utilizing the column generation algorithm. The FMO problem was formulated using an L2-norm minimization with anisotropic total variation (TV) regularization term, which allows for control over the number of MLC segments. Our Fluence Regularized and Optimized Selection of Triplets (FROST) plans were compared against the clinical treatment plans (CLN) produced by an experienced dosimetrist. Results: The mean PTV D95, D98, and D99 differ by −0.02%, +0.12%, and +0.44% of the prescription dose between planning methods, showing same PTV dose coverage. The mean PTV homogeneity (D95/D5) was at 0.9360 (FROST) and 0.9356 (CLN). R50 decreased by 0.07 with FROST. On average, FROST reduced Dmax and Dmean of OARs by 6.56% and 5.86% of the prescription dose. The manual CLN planning required iterative trial and error runs which is very time consuming, while FROST required minimal human intervention. Conclusions: MRI guided Co-60 therapy needs the output of all sources yet suffers from unintuitive and laborious manual beam selection processes. Automated triplet orientation optimization is shown essential to overcome the difficulty and improves the dosimetry. A novel FMO with regularization provides additional controls over the number of MLC segments

TH-AB-BRA-02: Automated Triplet Beam Orientation Optimization for MRI-Guided Co-60 Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Nguyen, D; Thomas, D; Cao, M; O’Connor, D; Lamb, J; Sheng, K [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA (United States)

2016-06-15

Purpose: MRI guided Co-60 provides daily and intrafractional MRI soft tissue imaging for improved target tracking and adaptive radiotherapy. To remedy the low output limitation, the system uses three Co-60 sources at 120° apart, but using all three sources in planning is considerably unintuitive. We automate the beam orientation optimization using column generation, and then solve a novel fluence map optimization (FMO) problem while regularizing the number of MLC segments. Methods: Three patients—1 prostate (PRT), 1 lung (LNG), and 1 head-and-neck boost plan (H&NBoost)—were evaluated. The beamlet dose for 180 equally spaced coplanar beams under 0.35 T magnetic field was calculated using Monte Carlo. The 60 triplets were selected utilizing the column generation algorithm. The FMO problem was formulated using an L2-norm minimization with anisotropic total variation (TV) regularization term, which allows for control over the number of MLC segments. Our Fluence Regularized and Optimized Selection of Triplets (FROST) plans were compared against the clinical treatment plans (CLN) produced by an experienced dosimetrist. Results: The mean PTV D95, D98, and D99 differ by −0.02%, +0.12%, and +0.44% of the prescription dose between planning methods, showing same PTV dose coverage. The mean PTV homogeneity (D95/D5) was at 0.9360 (FROST) and 0.9356 (CLN). R50 decreased by 0.07 with FROST. On average, FROST reduced Dmax and Dmean of OARs by 6.56% and 5.86% of the prescription dose. The manual CLN planning required iterative trial and error runs which is very time consuming, while FROST required minimal human intervention. Conclusions: MRI guided Co-60 therapy needs the output of all sources yet suffers from unintuitive and laborious manual beam selection processes. Automated triplet orientation optimization is shown essential to overcome the difficulty and improves the dosimetry. A novel FMO with regularization provides additional controls over the number of MLC segments

Locating single-point sources from arrival times containing large picking errors (LPEs): the virtual field optimization method (VFOM)

Science.gov (United States)

Li, Xi-Bing; Wang, Ze-Wei; Dong, Long-Jun

2016-01-01

Microseismic monitoring systems using local location techniques tend to be timely, automatic and stable. One basic requirement of these systems is the automatic picking of arrival times. However, arrival times generated by automated techniques always contain large picking errors (LPEs), which may make the location solution unreliable and cause the integrated system to be unstable. To overcome the LPE issue, we propose the virtual field optimization method (VFOM) for locating single-point sources. In contrast to existing approaches, the VFOM optimizes a continuous and virtually established objective function to search the space for the common intersection of the hyperboloids, which is determined by sensor pairs other than the least residual between the model-calculated and measured arrivals. The results of numerical examples and in-site blasts show that the VFOM can obtain more precise and stable solutions than traditional methods when the input data contain LPEs. Furthermore, we discuss the impact of LPEs on objective functions to determine the LPE-tolerant mechanism, velocity sensitivity and stopping criteria of the VFOM. The proposed method is also capable of locating acoustic sources using passive techniques such as passive sonar detection and acoustic emission.

Lighting Automation - Flying an Earthlike Habit Project

Science.gov (United States)

Falker, Jay; Howard, Ricky; Culbert, Christopher; Clark, Toni Anne; Kolomenski, Andrei

2017-01-01

Our proposal will enable the development of automated spacecraft habitats for long duration missions. Majority of spacecraft lighting systems employ lamps or zone specific switches and dimmers. Automation is not in the "picture". If we are to build long duration environments, which provide earth-like habitats, minimize crew time, and optimize spacecraft power reserves, innovation in lighting automation is a must. To transform how spacecraft lighting environments are automated, we will provide performance data on a standard lighting communication protocol. We will investigate utilization and application of an industry accepted lighting control protocol, DMX512. We will demonstrate how lighting automation can conserve power, assist with lighting countermeasures, and utilize spatial body tracking. By using DMX512 we will prove the "wheel" does not need to be reinvented in terms of smart lighting and future spacecraft can use a standard lighting protocol to produce an effective, optimized and potentially earthlike habitat.

Single cell analysis of yeast replicative aging using a new generation of microfluidic device.

Directory of Open Access Journals (Sweden)

Yi Zhang

Full Text Available A major limitation to yeast aging study has been the inability to track mother cells and observe molecular markers during the aging process. The traditional lifespan assay relies on manual micro-manipulation to remove daughter cells from the mother, which is laborious, time consuming, and does not allow long term tracking with high resolution microscopy. Recently, we have developed a microfluidic system capable of retaining mother cells in the microfluidic chambers while removing daughter cells automatically, making it possible to observe fluorescent reporters in single cells throughout their lifespan. Here we report the development of a new generation of microfluidic device that overcomes several limitations of the previous system, making it easier to fabricate and operate, and allowing functions not possible with the previous design. The basic unit of the device consists of microfluidic channels with pensile columns that can physically trap the mother cells while allowing the removal of daughter cells automatically by the flow of the fresh media. The whole microfluidic device contains multiple independent units operating in parallel, allowing simultaneous analysis of multiple strains. Using this system, we have reproduced the lifespan curves for the known long and short-lived mutants, demonstrating the power of the device for automated lifespan measurement. Following fluorescent reporters in single mother cells throughout their lifespan, we discovered a surprising change of expression of the translation elongation factor TEF2 during aging, suggesting altered translational control in aged mother cells. Utilizing the capability of the new device to trap mother-daughter pairs, we analyzed mother-daughter inheritance and found age dependent asymmetric partitioning of a general stress response reporter between mother and daughter cells.

An objective method to optimize the MR sequence set for plaque classification in carotid vessel wall images using automated image segmentation.

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Ronald van 't Klooster

Full Text Available A typical MR imaging protocol to study the status of atherosclerosis in the carotid artery consists of the application of multiple MR sequences. Since scanner time is limited, a balance has to be reached between the duration of the applied MR protocol and the quantity and quality of the resulting images which are needed to assess the disease. In this study an objective method to optimize the MR sequence set for classification of soft plaque in vessel wall images of the carotid artery using automated image segmentation was developed. The automated method employs statistical pattern recognition techniques and was developed based on an extensive set of MR contrast weightings and corresponding manual segmentations of the vessel wall and soft plaque components, which were validated by histological sections. Evaluation of the results from nine contrast weightings showed the tradeoff between scan duration and automated image segmentation performance. For our dataset the best segmentation performance was achieved by selecting five contrast weightings. Similar performance was achieved with a set of three contrast weightings, which resulted in a reduction of scan time by more than 60%. The presented approach can help others to optimize MR imaging protocols by investigating the tradeoff between scan duration and automated image segmentation performance possibly leading to shorter scanning times and better image interpretation. This approach can potentially also be applied to other research fields focusing on different diseases and anatomical regions.

Automated Detection of Binucleated Cell and Micronuclei using CellProfiler 2.0 Software

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DWI RAMADHANI

2013-12-01

Full Text Available Micronucleus assay in human peripheral lymphocytes usually used to assess chromosomal damage. Manual scoring of micronuclei can be time consuming and large numbers of binucleated cells have to be analyzed to obtain statistically relevant data. Automation of the micronuclei analysis using image processing analysis software can provide a faster and more reliable analysis of micronucleus assay. Here the used of CellProfiler an open access cell image analysis software for automatic detection of binucleated cells and micronuclei were reported. We aimed to know whether there was a significant difference in the number of binucleated cells and micronuclei that obtained by manual and CellProfiler counting. Wilcoxon Rank test was used for statistical analysis to test H0 hypothesis that there was no significant difference in the number of binucleated cells and micronuclei that obtained by manual and CellProfiler counting. We analyzed 135 images for both manual and CellProfiler counting. Our results showed that there was no significant difference between manual and CellProfiler counting for binucleated cells (P = 0.851 and for micronuclei (P = 0.917. In conclusion, the binucleated cells and micronuclei counting using CellProfiler were comparable but not better than manual counting.

Automation of cell-based drug absorption assays in 96-well format using permeable support systems.

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Larson, Brad; Banks, Peter; Sherman, Hilary; Rothenberg, Mark

2012-06-01

Cell-based drug absorption assays, such as Caco-2 and MDCK-MDR1, are an essential component of lead compound ADME/Tox testing. The permeability and transport data they provide can determine whether a compound continues in the drug discovery process. Current methods typically incorporate 24-well microplates and are performed manually. Yet the need to generate absorption data earlier in the drug discovery process, on an increasing number of compounds, is driving the use of higher density plates. A simple, more efficient process that incorporates 96-well permeable supports and proper instrumentation in an automated process provides more reproducible data compared to manual methods. Here we demonstrate the ability to perform drug permeability and transport assays using Caco-2 or MDCKII-MDR1 cells. The assay procedure was automated in a 96-well format, including cell seeding, media and buffer exchanges, compound dispense, and sample removal using simple robotic instrumentation. Cell monolayer integrity was confirmed via transepithelial electrical resistance and Lucifer yellow measurements. Proper cell function was validated by analyzing apical-to-basolateral and basolateral-to-apical movement of rhodamine 123, a known P-glycoprotein substrate. Apparent permeability and efflux data demonstrate how the automated procedure provides a less variable method than manual processing, and delivers a more accurate assessment of a compound's absorption characteristics.

Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique

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Bandaru, Sunith; Deb, Kalyanmoy

2011-09-01

In this article, a methodology is proposed for automatically extracting innovative design principles which make a system or process (subject to conflicting objectives) optimal using its Pareto-optimal dataset. Such 'higher knowledge' would not only help designers to execute the system better, but also enable them to predict how changes in one variable would affect other variables if the system has to retain its optimal behaviour. This in turn would help solve other similar systems with different parameter settings easily without the need to perform a fresh optimization task. The proposed methodology uses a clustering-based optimization technique and is capable of discovering hidden functional relationships between the variables, objective and constraint functions and any other function that the designer wishes to include as a 'basis function'. A number of engineering design problems are considered for which the mathematical structure of these explicit relationships exists and has been revealed by a previous study. A comparison with the multivariate adaptive regression splines (MARS) approach reveals the practicality of the proposed approach due to its ability to find meaningful design principles. The success of this procedure for automated innovization is highly encouraging and indicates its suitability for further development in tackling more complex design scenarios.

Comparison of manual and automated cell counts in EDTA preserved synovial fluids. Storage has little influence on the results.

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Salinas, M; Rosas, J; Iborra, J; Manero, H; Pascual, E

1997-10-01

To determine the precision and agreement of synovial fluid (SF) cell counts done manually and with automated counters, and to determine the degree of variability of the counts in SF samples, kept in the tubes used for routine white blood cell (WBC) counts--which use liquid EDTA as anticoagulant--at 24 and 48 hours at 4 degrees C, and at room temperature. To determine precision, cell counts were repeated 10 times--both manually and by an automated counter--in a SF sample of low, medium, and high cellularity. The variances were calculated to determine the interobserver variation in two manual (M1,M2) and two automated cell counts (C1,C2). The agreement between a manual (M1) and automated counter (C1) results, was analysed by the Bland and Altman method and the difference against the mean of the two methods was plotted. Then, the mean difference between the two methods was estimated and the standard deviation of the difference. To determine the effects of storage, SF samples were kept in a refrigerator at 4 degrees C, and at room temperature; cell counts were done manually (M1) and automatically (C1) at 24 and 48 hours and the changes analysed by the Bland and Altman method. The variances were compared using an F test. (1) Precision. With the manual technique, the coefficients of variation were 27.9%, 14%, and 10.7% when used for counting the SF with low (270), medium (6200), and high cellularities (25,000). With the automated technique the coefficients of variation were 20%, 3.4%, and 2.9% in the same SF samples. In the fluids of medium and high cellularity, the variances of the automated cell counts were significatively lower (F test, p automated counter. (4) Influence of storage. The coulter counts of SF samples preserved at 4 degrees C showed less variance (F test, p Automated cell count of the SF offers advantages: it gives higher precision and consumes less time. The stability of the samples preserved in the EDTA tubes used for routine WBC counts is of

A Facile Droplet-Chip-Time-Resolved Inductively Coupled Plasma Mass Spectrometry Online System for Determination of Zinc in Single Cell.

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Wang, Han; Chen, Beibei; He, Man; Hu, Bin

2017-05-02

Single cell analysis is a significant research field in recent years reflecting the heterogeneity of cells in a biological system. In this work, a facile droplet chip was fabricated and online combined with time-resolved inductively coupled plasma mass spectrometry (ICPMS) via a microflow nebulizer for the determination of zinc in single HepG2 cells. On the focusing geometric designed PDMS microfluidic chip, the aqueous cell suspension was ejected and divided by hexanol to generate droplets. The droplets encapsulated single cells remain intact during the transportation into ICP for subsequent detection. Under the optimized conditions, the frequency of droplet generation is 3-6 × 10 6 min -1 , and the injected cell number is 2500 min -1 , which can ensure the single cell encapsulation. ZnO nanoparticles (NPs) were used for the quantification of zinc in single cells, and the accuracy was validated by conventional acid digestion-ICPMS method. The ZnO NPs incubated HepG2 cells were analyzed as model samples, and the results exhibit the heterogeneity of HepG2 cells in the uptake/adsorption of ZnO NPs. The developed online droplet-chip-ICPMS analysis system achieves stable single cell encapsulation and has high throughput for single cell analysis. It has the potential in monitoring the content as well as distribution of trace elements/NPs at the single cell level.

Probing bacterial adhesion at the single-cell level

DEFF Research Database (Denmark)

Zeng, Guanghong; Müller, Torsten; Meyer, Rikke Louise

be considered. We have developed a simple and versatile method to make single-cell bacterial probes for measuring single cell adhesion by force spectroscopy using atomic force microscopy (AFM). A single-cell probe was readily made by picking up a bacterial cell from a glass surface by approaching a tipless AFM...... cantilever coated with the commercial cell adhesive CellTakTM. We applied the method to study adhesion of living cells to abiotic surfaces at the single-cell level. Immobilisation of single bacterial cells to the cantilever was stable for several hours, and viability was confirmed by Live/Dead staining...... on the adhesion force, we explored the bond formation and adhesive strength of four different bacterial strains towards three abiotic substrates with variable hydrophobicity and surface roughness. The adhesion force and final rupture length were dependent on bacterial strains, surfaces properties, and time...

Performance evaluation of an automated single-channel sleep–wake detection algorithm

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Kaplan RF

2014-10-01

Full Text Available Richard F Kaplan,1 Ying Wang,1 Kenneth A Loparo,1,2 Monica R Kelly,3 Richard R Bootzin3 1General Sleep Corporation, Euclid, OH, USA; 2Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA; 3Department of Psychology, University of Arizona, Tucson, AZ, USA Background: A need exists, from both a clinical and a research standpoint, for objective sleep measurement systems that are both easy to use and can accurately assess sleep and wake. This study evaluates the output of an automated sleep–wake detection algorithm (Z-ALG used in the Zmachine (a portable, single-channel, electroencephalographic [EEG] acquisition and analysis system against laboratory polysomnography (PSG using a consensus of expert visual scorers. Methods: Overnight laboratory PSG studies from 99 subjects (52 females/47 males, 18–60 years, median age 32.7 years, including both normal sleepers and those with a variety of sleep disorders, were assessed. PSG data obtained from the differential mastoids (A1–A2 were assessed by Z-ALG, which determines sleep versus wake every 30 seconds using low-frequency, intermediate-frequency, and high-frequency and time domain EEG features. PSG data were independently scored by two to four certified PSG technologists, using standard Rechtschaffen and Kales guidelines, and these score files were combined on an epoch-by-epoch basis, using a majority voting rule, to generate a single score file per subject to compare against the Z-ALG output. Both epoch-by-epoch and standard sleep indices (eg, total sleep time, sleep efficiency, latency to persistent sleep, and wake after sleep onset were compared between the Z-ALG output and the technologist consensus score files. Results: Overall, the sensitivity and specificity for detecting sleep using the Z-ALG as compared to the technologist consensus are 95.5% and 92.5%, respectively, across all subjects, and the positive predictive value and the

Single cell enzyme diagnosis on the chip

DEFF Research Database (Denmark)

Jensen, Sissel Juul; Harmsen, Charlotte; Nielsen, Mette Juul

2013-01-01

Conventional diagnosis based on ensemble measurements often overlooks the variation among cells. Here, we present a droplet-microfluidics based platform to investigate single cell activities. Adopting a previously developed isothermal rolling circle amplification-based assay, we demonstrate...... detection of enzymatic activities down to the single cell level with small quantities of biological samples, which outcompetes existing techniques. Such a system, capable of resolving single cell activities, will ultimately have clinical applications in diagnosis, prediction of drug response and treatment...

A HUMAN AUTOMATION INTERACTION CONCEPT FOR A SMALL MODULAR REACTOR CONTROL ROOM

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Le Blanc, Katya; Spielman, Zach; Hill, Rachael

2017-06-01

Many advanced nuclear power plant (NPP) designs incorporate higher degrees of automation than the existing fleet of NPPs. Automation is being introduced or proposed in NPPs through a wide variety of systems and technologies, such as advanced displays, computer-based procedures, advanced alarm systems, and computerized operator support systems. Additionally, many new reactor concepts, both full scale and small modular reactors, are proposing increased automation and reduced staffing as part of their concept of operations. However, research consistently finds that there is a fundamental tradeoff between system performance with increased automation and reduced human performance. There is a need to address the question of how to achieve high performance and efficiency of high levels of automation without degrading human performance. One example of a new NPP concept that will utilize greater degrees of automation is the SMR concept from NuScale Power. The NuScale Power design requires 12 modular units to be operated in one single control room, which leads to a need for higher degrees of automation in the control room. Idaho National Laboratory (INL) researchers and NuScale Power human factors and operations staff are working on a collaborative project to address the human performance challenges of increased automation and to determine the principles that lead to optimal performance in highly automated systems. This paper will describe this concept in detail and will describe an experimental test of the concept. The benefits and challenges of the approach will be discussed.

ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.

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Gardeux, Vincent; David, Fabrice P A; Shajkofci, Adrian; Schwalie, Petra C; Deplancke, Bart

2017-10-01

Single-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet these groups often lack the expertise to handle complex scRNA-seq datasets. We developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types. The tool is freely available at asap.epfl.ch and R/Python scripts are available at github.com/DeplanckeLab/ASAP. bart.deplancke@epfl.ch. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

International Nuclear Information System (INIS)

Elsays, Mostafa A.; Naguib Aly, M; Badawi, Alya A.

2010-01-01

The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Mult-objective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem. (orig.)

Platforms for Single-Cell Collection and Analysis

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Lukas Valihrach

2018-03-01

Full Text Available Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS. In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments.

Platforms for Single-Cell Collection and Analysis.

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Valihrach, Lukas; Androvic, Peter; Kubista, Mikael

2018-03-11

Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS). In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments.

Single cell analysis of normal and leukemic hematopoiesis.

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Povinelli, Benjamin J; Rodriguez-Meira, Alba; Mead, Adam J

2018-02-01

The hematopoietic system is well established as a paradigm for the study of cellular hierarchies, their disruption in disease and therapeutic use in regenerative medicine. Traditional approaches to study hematopoiesis involve purification of cell populations based on a small number of surface markers. However, such population-based analysis obscures underlying heterogeneity contained within any phenotypically defined cell population. This heterogeneity can only be resolved through single cell analysis. Recent advances in single cell techniques allow analysis of the genome, transcriptome, epigenome and proteome in single cells at an unprecedented scale. The application of these new single cell methods to investigate the hematopoietic system has led to paradigm shifts in our understanding of cellular heterogeneity in hematopoiesis and how this is disrupted in disease. In this review, we summarize how single cell techniques have been applied to the analysis of hematopoietic stem/progenitor cells in normal and malignant hematopoiesis, with a particular focus on recent advances in single-cell genomics, including how these might be utilized for clinical application. Copyright © 2017. Published by Elsevier Ltd.

Fast and accurate automated cell boundary determination for fluorescence microscopy

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Arce, Stephen Hugo; Wu, Pei-Hsun; Tseng, Yiider

2013-07-01

Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

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Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without

QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform

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Sara Taylor

2018-04-01

Full Text Available Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific individual. A scientific way to find individualized recommendations and causal links is to conduct experiments using single-case experimental design; however, properly designed single-case experiments are not easy to conduct on oneself. We designed, developed, and evaluated a novel platform, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. We provide software for the platform that we used (available for free on GitHub, which provides the methodological elements to run many kinds of customized studies. In this work, we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We conducted a six-week pilot study (N = 13 to evaluate QuantifyMe. We describe the lessons learned developing the platform and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals, reducing the high administrative cost for advancing human health and wellbeing.

QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform.

Science.gov (United States)

Taylor, Sara; Sano, Akane; Ferguson, Craig; Mohan, Akshay; Picard, Rosalind W

2018-04-05

Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific individual. A scientific way to find individualized recommendations and causal links is to conduct experiments using single-case experimental design; however, properly designed single-case experiments are not easy to conduct on oneself. We designed, developed, and evaluated a novel platform, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. We provide software for the platform that we used (available for free on GitHub), which provides the methodological elements to run many kinds of customized studies. In this work, we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We conducted a six-week pilot study ( N = 13) to evaluate QuantifyMe. We describe the lessons learned developing the platform and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals, reducing the high administrative cost for advancing human health and wellbeing.

An automated analysis workflow for optimization of force-field parameters using neutron scattering data

Energy Technology Data Exchange (ETDEWEB)

Lynch, Vickie E.; Borreguero, Jose M. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Bhowmik, Debsindhu [Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Ganesh, Panchapakesan; Sumpter, Bobby G. [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Proffen, Thomas E. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Goswami, Monojoy, E-mail: goswamim@ornl.gov [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States)

2017-07-01

Graphical abstract: - Highlights: • An automated workflow to optimize force-field parameters. • Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA. • The mechanism relies on molecular dynamics simulation and neutron scattering experimental data. • The workflow can be generalized to any other experimental and simulation techniques. - Abstract: Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D{sub 2}O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.

Design Optimization of Internal Flow Devices

DEFF Research Database (Denmark)

Madsen, Jens Ingemann

The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies.......The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies....

Optimizing Grid Patterns on Photovoltaic Cells

Science.gov (United States)

Burger, D. R.

1984-01-01

CELCAL computer program helps in optimizing grid patterns for different photovoltaic cell geometries and metalization processes. Five different powerloss phenomena associated with front-surface metal grid pattern on photovoltaic cells.

Barcoding T Cell Calcium Response Diversity with Methods for Automated and Accurate Analysis of Cell Signals (MAAACS)

Science.gov (United States)

Sergé, Arnauld; Bernard, Anne-Marie; Phélipot, Marie-Claire; Bertaux, Nicolas; Fallet, Mathieu; Grenot, Pierre; Marguet, Didier; He, Hai-Tao; Hamon, Yannick

2013-01-01

We introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells. PMID:24086124

GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

Directory of Open Access Journals (Sweden)

Steffen C. Lott

2018-04-01

Full Text Available Bacterial small RNAs (sRNAs are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.

An automated high throughput screening-compatible assay to identify regulators of stem cell neural differentiation.

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Casalino, Laura; Magnani, Dario; De Falco, Sandro; Filosa, Stefania; Minchiotti, Gabriella; Patriarca, Eduardo J; De Cesare, Dario

2012-03-01

The use of Embryonic Stem Cells (ESCs) holds considerable promise both for drug discovery programs and the treatment of degenerative disorders in regenerative medicine approaches. Nevertheless, the successful use of ESCs is still limited by the lack of efficient control of ESC self-renewal and differentiation capabilities. In this context, the possibility to modulate ESC biological properties and to obtain homogenous populations of correctly specified cells will help developing physiologically relevant screens, designed for the identification of stem cell modulators. Here, we developed a high throughput screening-suitable ESC neural differentiation assay by exploiting the Cell(maker) robotic platform and demonstrated that neural progenies can be generated from ESCs in complete automation, with high standards of accuracy and reliability. Moreover, we performed a pilot screening providing proof of concept that this assay allows the identification of regulators of ESC neural differentiation in full automation.

Optimization of the temporal pattern of applied dose for a single fraction of radiation: Implications for radiation therapy

Science.gov (United States)

Altman, Michael B.

The increasing prevalence of intensity modulated radiation therapy (IMRT) as a treatment modality has led to a renewed interest in the potential for interaction between prolonged treatment time, as frequently associated with IMRT, and the underlying radiobiology of the irradiated tissue. A particularly relevant aspect of radiobiology is cell repair capacity, which influences cell survival, and thus directly relates to the ability to control tumors and spare normal tissues. For a single fraction of radiation, the linear quadratic (LQ) model is commonly used to relate the radiation dose to the fraction of cells surviving. The LQ model implies a dependence on two time-related factors which correlate to radiobiological effects: the duration of radiation application, and the functional form of how the dose is applied over that time (the "temporal pattern of applied dose"). Although the former has been well studied, the latter has not. Thus, the goal of this research is to investigate the impact of the temporal pattern of applied dose on the survival of human cells and to explore how the manipulation of this temporal dose pattern may be incorporated into an IMRT-based radiation therapy treatment planning scheme. The hypothesis is that the temporal pattern of applied dose in a single fraction of radiation can be optimized to maximize or minimize cell kill. Furthermore, techniques which utilize this effect could have clinical ramifications. In situations where increased cell kill is desirable, such as tumor control, or limiting the degree of cell kill is important, such as the sparing of normal tissue, temporal sequences of dose which maximize or minimize cell kill (temporally "optimized" sequences) may provide greater benefit than current clinically used radiation patterns. In the first part of this work, an LQ-based modeling analysis of effects of the temporal pattern of dose on cell kill is performed. Through this, patterns are identified for maximizing cell kill for a

Automated Solar Cell Assembly Teamed Process Research. Final subcontract report, 6 January 1993--31 October 1995

Energy Technology Data Exchange (ETDEWEB)

Nowlan, M. J.; Hogan, S. J.; Breen, W. F.; Murach, J. M.; Sutherland, S. F.; Patterson, J. S.; Darkazalli, G. [Spire Corp., Bedford, MA (US)

1996-02-01

This is the Final Technical Report for a program entitled ''Automated Solar Cell Assembly Teamed Process Research,'' funded by the US Department of Energy. This program was part of Phase 3A of the Photovoltaic Manufacturing Technology (PVMaT) project, which addressed the generic needs of the photovoltaic (PV) industry for improved quality, accelerated production scale-up, and substantially reduced manufacturing cost. Crystalline silicon solar cells (Czochralski monocrystalline, cast polycrystalline, and ribbon polycrystalline) are used in the great majority of PV modules produced in the US, accounting for 95% of all shipments in 1994. Spire's goal in this program was to reduce the cost of these modules by developing high throughput (5 MW per year) automated processes for interconnecting solar cells made from standard and thin silicon wafers. Spire achieved this goal by developing a completely new automated processing system, designated the SPI-ASSEMBLER{trademark} 5000, which is now offered as a commercial product to the PV industry. A discussion of the project and of the Assembler is provided.

Application of single-cell technology in cancer research.

Science.gov (United States)

Liang, Shao-Bo; Fu, Li-Wu

2017-07-01

In this review, we have outlined the application of single-cell technology in cancer research. Single-cell technology has made encouraging progress in recent years and now provides the means to detect rare cancer cells such as circulating tumor cells and cancer stem cells. We reveal how this technology has advanced the analysis of intratumor heterogeneity and tumor epigenetics, and guided individualized treatment strategies. The future prospects now are to bring single-cell technology into the clinical arena. We believe that the clinical application of single-cell technology will be beneficial in cancer diagnostics and treatment, and ultimately improve survival in cancer patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

GENPLAT: an automated platform for biomass enzyme discovery and cocktail optimization.

Science.gov (United States)

Walton, Jonathan; Banerjee, Goutami; Car, Suzana

2011-10-24

The high cost of enzymes for biomass deconstruction is a major impediment to the economic conversion of lignocellulosic feedstocks to liquid transportation fuels such as ethanol. We have developed an integrated high throughput platform, called GENPLAT, for the discovery and development of novel enzymes and enzyme cocktails for the release of sugars from diverse pretreatment/biomass combinations. GENPLAT comprises four elements: individual pure enzymes, statistical design of experiments, robotic pipeting of biomass slurries and enzymes, and automated colorimeteric determination of released Glc and Xyl. Individual enzymes are produced by expression in Pichia pastoris or Trichoderma reesei, or by chromatographic purification from commercial cocktails or from extracts of novel microorganisms. Simplex lattice (fractional factorial) mixture models are designed using commercial Design of Experiment statistical software. Enzyme mixtures of high complexity are constructed using robotic pipeting into a 96-well format. The measurement of released Glc and Xyl is automated using enzyme-linked colorimetric assays. Optimized enzyme mixtures containing as many as 16 components have been tested on a variety of feedstock and pretreatment combinations. GENPLAT is adaptable to mixtures of pure enzymes, mixtures of commercial products (e.g., Accellerase 1000 and Novozyme 188), extracts of novel microbes, or combinations thereof. To make and test mixtures of ˜10 pure enzymes requires less than 100 μg of each protein and fewer than 100 total reactions, when operated at a final total loading of 15 mg protein/g glucan. We use enzymes from several sources. Enzymes can be purified from natural sources such as fungal cultures (e.g., Aspergillus niger, Cochliobolus carbonum, and Galerina marginata), or they can be made by expression of the encoding genes (obtained from the increasing number of microbial genome sequences) in hosts such as E. coli, Pichia pastoris, or a filamentous fungus such

Electrochemical monitoring of intracellular enzyme activity of single living mammalian cells by using a double-mediator system

International Nuclear Information System (INIS)

Matsumae, Yoshiharu; Takahashi, Yasufumi; Ino, Kosuke; Shiku, Hitoshi; Matsue, Tomokazu

2014-01-01

Graphical abstract: NAD(P)H:quinone oxidoreductase (NQO) activity of single HeLa cells were evaluated by using the menadione–ferrocyanide double mediator system combined with scanning electrochemical microscopy (SECM). - Highlights: • NAD(P)H:quinone oxidoreductase activity of single cells were evaluated with SECM. • Fe(CN) 6 3− /menadione concentrations were optimized for long-term SECM monitoring. • Menadione affect the intracellular levels of reactive oxygen species and GSH. • At 100 μM menadione, the Fe(CN) 6 3− generation rate decreased rapidly within 30 min. - Abstract: We evaluated the intracellular NAD(P)H:quinone oxidoreductase (NQO) activity of single HeLa cells by using the menadione–ferrocyanide double-mediator system combined with scanning electrochemical microscopy (SECM). The double-mediator system was used to amplify the current response from the intracellular NQO activity and to reduce menadione-induced cell damage. The electron shuttle between the electrode and menadione was mediated by the ferrocyanide/ferricyanide redox couple. Generation of ferrocyanide was observed immediately after the addition of a lower concentration (10 μM) of menadione. The ferrocyanide generation rate was constant for 120 min. At a higher menadione concentration (100 μM), the ferrocyanide generation rate decreased within 30 min because of the cytotoxic effect of menadione. We also investigated the relationship between intracellular reactive oxygen species or glutathione levels and exposure to different menadione concentrations to determine the optimal condition for SECM with minimal invasiveness. The present study clearly demonstrates that SECM is useful for the analysis of intracellular enzymatic activities in single cells with a double-mediator system

Electrochemical monitoring of intracellular enzyme activity of single living mammalian cells by using a double-mediator system

Energy Technology Data Exchange (ETDEWEB)

Matsumae, Yoshiharu [Graduate School of Environmental Studies, Tohoku University, Aramaki 6-6-11-605, Aoba, Sendai 980-8579 (Japan); Takahashi, Yasufumi [Advanced Institute for Materials Research, Tohoku University, Katahira 2-1-1, Aoba, Sendai 980-8577 (Japan); Ino, Kosuke [Graduate School of Environmental Studies, Tohoku University, Aramaki 6-6-11-605, Aoba, Sendai 980-8579 (Japan); Shiku, Hitoshi, E-mail: shiku@bioinfo.che.tohoku.ac.jp [Graduate School of Environmental Studies, Tohoku University, Aramaki 6-6-11-605, Aoba, Sendai 980-8579 (Japan); Matsue, Tomokazu, E-mail: matsue@bioinfo.che.tohoku.ac.jp [Graduate School of Environmental Studies, Tohoku University, Aramaki 6-6-11-605, Aoba, Sendai 980-8579 (Japan); Advanced Institute for Materials Research, Tohoku University, Katahira 2-1-1, Aoba, Sendai 980-8577 (Japan)

2014-09-09

Graphical abstract: NAD(P)H:quinone oxidoreductase (NQO) activity of single HeLa cells were evaluated by using the menadione–ferrocyanide double mediator system combined with scanning electrochemical microscopy (SECM). - Highlights: • NAD(P)H:quinone oxidoreductase activity of single cells were evaluated with SECM. • Fe(CN){sub 6}{sup 3−}/menadione concentrations were optimized for long-term SECM monitoring. • Menadione affect the intracellular levels of reactive oxygen species and GSH. • At 100 μM menadione, the Fe(CN){sub 6}{sup 3−} generation rate decreased rapidly within 30 min. - Abstract: We evaluated the intracellular NAD(P)H:quinone oxidoreductase (NQO) activity of single HeLa cells by using the menadione–ferrocyanide double-mediator system combined with scanning electrochemical microscopy (SECM). The double-mediator system was used to amplify the current response from the intracellular NQO activity and to reduce menadione-induced cell damage. The electron shuttle between the electrode and menadione was mediated by the ferrocyanide/ferricyanide redox couple. Generation of ferrocyanide was observed immediately after the addition of a lower concentration (10 μM) of menadione. The ferrocyanide generation rate was constant for 120 min. At a higher menadione concentration (100 μM), the ferrocyanide generation rate decreased within 30 min because of the cytotoxic effect of menadione. We also investigated the relationship between intracellular reactive oxygen species or glutathione levels and exposure to different menadione concentrations to determine the optimal condition for SECM with minimal invasiveness. The present study clearly demonstrates that SECM is useful for the analysis of intracellular enzymatic activities in single cells with a double-mediator system.

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

International Nuclear Information System (INIS)

Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

2007-01-01

Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development

Single cell metabolomics

NARCIS (Netherlands)

Heinemann, Matthias; Zenobi, Renato

Recent discoveries suggest that cells of a clonal population often display multiple metabolic phenotypes at the same time. Motivated by the success of mass spectrometry (MS) in the investigation of population-level metabolomics, the analytical community has initiated efforts towards MS-based single

Single-cell intracellular nano-pH probes†

Science.gov (United States)

Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader

2016-01-01

Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution. PMID:27708772

Single-cell intracellular nano-pH probes.

Science.gov (United States)

Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader

2015-01-01

Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution.

Precision automation of cell type classification and sub-cellular fluorescence quantification from laser scanning confocal images

Directory of Open Access Journals (Sweden)

Hardy Craig Hall

2016-02-01

Full Text Available While novel whole-plant phenotyping technologies have been successfully implemented into functional genomics and breeding programs, the potential of automated phenotyping with cellular resolution is largely unexploited. Laser scanning confocal microscopy has the potential to close this gap by providing spatially highly resolved images containing anatomic as well as chemical information on a subcellular basis. However, in the absence of automated methods, the assessment of the spatial patterns and abundance of fluorescent markers with subcellular resolution is still largely qualitative and time-consuming. Recent advances in image acquisition and analysis, coupled with improvements in microprocessor performance, have brought such automated methods within reach, so that information from thousands of cells per image for hundreds of images may be derived in an experimentally convenient time-frame. Here, we present a MATLAB-based analytical pipeline to 1 segment radial plant organs into individual cells, 2 classify cells into cell type categories based upon random forest classification, 3 divide each cell into sub-regions, and 4 quantify fluorescence intensity to a subcellular degree of precision for a separate fluorescence channel. In this research advance, we demonstrate the precision of this analytical process for the relatively complex tissues of Arabidopsis hypocotyls at various stages of development. High speed and robustness make our approach suitable for phenotyping of large collections of stem-like material and other tissue types.

Video-rate confocal microscopy for single-molecule imaging in live cells and superresolution fluorescence imaging.

Science.gov (United States)

Lee, Jinwoo; Miyanaga, Yukihiro; Ueda, Masahiro; Hohng, Sungchul

2012-10-17

There is no confocal microscope optimized for single-molecule imaging in live cells and superresolution fluorescence imaging. By combining the swiftness of the line-scanning method and the high sensitivity of wide-field detection, we have developed a, to our knowledge, novel confocal fluorescence microscope with a good optical-sectioning capability (1.0 μm), fast frame rates (fluorescence detection efficiency. Full compatibility of the microscope with conventional cell-imaging techniques allowed us to do single-molecule imaging with a great ease at arbitrary depths of live cells. With the new microscope, we monitored diffusion motion of fluorescently labeled cAMP receptors of Dictyostelium discoideum at both the basal and apical surfaces and obtained superresolution fluorescence images of microtubules of COS-7 cells at depths in the range 0-85 μm from the surface of a coverglass. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A new framework for analysing automated acoustic species-detection data: occupancy estimation and optimization of recordings post-processing

Science.gov (United States)

Chambert, Thierry A.; Waddle, J. Hardin; Miller, David A.W.; Walls, Susan; Nichols, James D.

2018-01-01

The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors.We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation.Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders.When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated.Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

Bacterial growth on surfaces: Automated image analysis for quantification of growth rate-related parameters

DEFF Research Database (Denmark)

Møller, S.; Sternberg, Claus; Poulsen, L. K.

1995-01-01

species-specific hybridizations with fluorescence-labelled ribosomal probes to estimate the single-cell concentration of RNA. By automated analysis of digitized images of stained cells, we determined four independent growth rate-related parameters: cellular RNA and DNA contents, cell volume......, and the frequency of dividing cells in a cell population. These parameters were used to compare physiological states of liquid-suspended and surfacegrowing Pseudomonas putida KT2442 in chemostat cultures. The major finding is that the correlation between substrate availability and cellular growth rate found...

Evaluation of an automated knowledge based treatment planning system for head and neck

International Nuclear Information System (INIS)

Krayenbuehl, Jerome; Norton, Ian; Studer, Gabriela; Guckenberger, Matthias

2015-01-01

This study evaluated an automated inverse treatment planning algorithm, Pinnacle Auto-Planning (AP), and compared automatically generated plans with historical plans in a large cohort of head and neck cancer patients. Fifty consecutive patients treated with volumetric modulated arc therapy (Eclipse, Varian Medical System, Palo Alto, CA) for head and neck were re-planned with AP version 9.10. Only one single cycle of plan optimization using one single template was allowed for AP. The dose to the planning target volumes (PTV’s; 3–4 dose levels), the organs at risk (OAR’s) and the effective working time for planning was evaluated. Additionally, two experienced radiation oncologists blind-reviewed and ranked 10 plans. Dose coverage and dose homogeneity of the PTV were significantly improved with AP, however manually optimized plans showed significantly improved dose conformity. The mean dose to the parotid glands, oral mucosa, swallowing muscles, dorsal neck tissue and maximal dose to the spinal cord were significantly reduced with AP. In 64 % of the plans, the mean dose to any OAR (spinal cord excluded) was reduced by >20 % with AP in comparison to the manually optimized plans. In 12 % of the plans, the manually optimized plans showed reduced doses by >20 % in at least one OAR. The experienced radiation oncologists preferred the AP plan and the clinical plan in 80 and 20 % of the cases, respectively. The average effective working time was 3.8 min ± 1.1 min in comparison to 48.5 min ± 6.0 min using AP compared to the manually optimized plans, respectively. The evaluated automated planning algorithm achieved highly consistent and significantly improved treatment plans with potentially clinically relevant OAR sparing by >20 % in 64 % of the cases. The effective working time was substantially reduced with Auto-Planning

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

Science.gov (United States)

Teschendorff, Andrew E.; Enver, Tariq

2017-01-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836

Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm.

Science.gov (United States)

Yang, Qin; Zou, Hong-Yan; Zhang, Yan; Tang, Li-Juan; Shen, Guo-Li; Jiang, Jian-Hui; Yu, Ru-Qin

2016-01-15

Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is proposed for the first time upon protein pattern unmixing. Variable-weighted support vector machine (VW-SVM) is a demonstrated robust modeling technique with flexible and rational variable selection. As optimized by a global stochastic optimization technique, particle swarm optimization (PSO) algorithm, it makes VW-SVM to be an adaptive parameter-free method for automated unmixing of protein subcellular patterns. Results obtained by pattern unmixing of a set of fluorescence microscope images of cells indicate VW-SVM as optimized by PSO is able to extract useful pattern features by optimally rescaling each variable for non-linear SVM modeling, consequently leading to improved performances in multiplex protein pattern unmixing compared with conventional SVM and other exiting pattern unmixing methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Technical aspects and recommendations for single-cell qPCR.

Science.gov (United States)

Ståhlberg, Anders; Kubista, Mikael

2018-02-01

Single cells are basic physiological and biological units that can function individually as well as in groups in tissues and organs. It is central to identify, characterize and profile single cells at molecular level to be able to distinguish different kinds, to understand their functions and determine how they interact with each other. During the last decade several technologies for single-cell profiling have been developed and used in various applications, revealing many novel findings. Quantitative PCR (qPCR) is one of the most developed methods for single-cell profiling that can be used to interrogate several analytes, including DNA, RNA and protein. Single-cell qPCR has the potential to become routine methodology but the technique is still challenging, as it involves several experimental steps and few molecules are handled. Here, we discuss technical aspects and provide recommendation for single-cell qPCR analysis. The workflow includes experimental design, sample preparation, single-cell collection, direct lysis, reverse transcription, preamplification, qPCR and data analysis. Detailed reporting and sharing of experimental details and data will promote further development and make validation studies possible. Efforts aiming to standardize single-cell qPCR open up means to move single-cell analysis from specialized research settings to standard research laboratories. Copyright © 2017 Elsevier Ltd. All rights reserved.

Precise gene modification mediated by TALEN and single-stranded oligodeoxynucleotides in human cells.

Directory of Open Access Journals (Sweden)

Xiaoling Wang

Full Text Available The development of human embryonic stem cells (ESCs and induced pluripotent stem cells (iPSCs facilitates in vitro studies of human disease mechanisms, speeds up the process of drug screening, and raises the feasibility of using cell replacement therapy in clinics. However, the study of genotype-phenotype relationships in ESCs or iPSCs is hampered by the low efficiency of site-specific gene editing. Transcription activator-like effector nucleases (TALENs spurred interest due to the ease of assembly, high efficiency and faithful gene targeting. In this study, we optimized the TALEN design to maximize its genomic cutting efficiency. We showed that using optimized TALENs in conjunction with single-strand oligodeoxynucleotide (ssODN allowed efficient gene editing in human cells. Gene mutations and gene deletions for up to 7.8 kb can be accomplished at high efficiencies. We established human tumor cell lines and H9 ESC lines with homozygous deletion of the microRNA-21 (miR-21 gene and miR-9-2 gene. These cell lines provide a robust platform to dissect the roles these genes play during cell differentiation and tumorigenesis. We also observed that the endogenous homologous chromosome can serve as a donor template for gene editing. Overall, our studies demonstrate the versatility of using ssODN and TALEN to establish genetically modified cells for research and therapeutic application.

Deconstructing stem cell population heterogeneity: Single-cell analysis and modeling approaches

Science.gov (United States)

Wu, Jincheng; Tzanakakis, Emmanuel S.

2014-01-01

Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives. PMID:24035899

Incorporating single detector failure into the ROP detector layout optimization for CANDU reactors

Energy Technology Data Exchange (ETDEWEB)

Kastanya, Doddy, E-mail: Doddy.Kastanya@snclavalin.com

2015-12-15

Highlights: • ROP TSP value needs to be adjusted when any detector in the system fails. • Single detector failure criterion has been incorporated into the detector layout optimization as a constraint. • Results show that the optimized detector layout is more robust with respect to its vulnerability to a single detector failure. • An early rejection scheme has been introduced to speed-up the optimization process. - Abstract: In CANDU{sup ®} reactors, the regional overpower protection (ROP) systems are designed to protect the reactor against overpower in the fuel which could reduce the safety margin-to-dryout. In the CANDU{sup ®} 600 MW (CANDU 6) design, there are two ROP systems in the core, each of which is connected to a fast-acting shutdown system. Each ROP system consists of a number of fast-responding, self-powered flux detectors suitably distributed throughout the core within vertical and horizontal flux detector assemblies. The placement of these ROP detectors is a challenging discrete optimization problem. In the past few years, two algorithms, DETPLASA and ADORE, have been developed to optimize the detector layout for the ROP systems in CANDU reactors. These algorithms utilize the simulated annealing (SA) technique to optimize the placement of the detectors in the core. The objective of the optimization process is typically either to maximize the TSP value for a given number of detectors in the system or to minimize the number of detectors in the system to obtain a target TSP value. One measure to determine the robustness of the optimized detector layout is to evaluate the maximum decrease (penalty) in TSP value when any single detector in the system fails. The smaller the penalty, the more robust the design is. Therefore, in order to ensure that the optimized detector layout is robust, the single detector failure (SDF) criterion has been incorporated as an additional constraint into the ADORE algorithm. Results from this study indicate that there

Identification of innate lymphoid cells in single-cell RNA-Seq data.

Science.gov (United States)

Suffiotti, Madeleine; Carmona, Santiago J; Jandus, Camilla; Gfeller, David

2017-07-01

Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.

Objective automated quantification of fluorescence signal in histological sections of rat lens.

Science.gov (United States)

Talebizadeh, Nooshin; Hagström, Nanna Zhou; Yu, Zhaohua; Kronschläger, Martin; Söderberg, Per; Wählby, Carolina

2017-08-01

Visual quantification and classification of fluorescent signals is the gold standard in microscopy. The purpose of this study was to develop an automated method to delineate cells and to quantify expression of fluorescent signal of biomarkers in each nucleus and cytoplasm of lens epithelial cells in a histological section. A region of interest representing the lens epithelium was manually demarcated in each input image. Thereafter, individual cell nuclei within the region of interest were automatically delineated based on watershed segmentation and thresholding with an algorithm developed in Matlab™. Fluorescence signal was quantified within nuclei, cytoplasms and juxtaposed backgrounds. The classification of cells as labelled or not labelled was based on comparison of the fluorescence signal within cells with local background. The classification rule was thereafter optimized as compared with visual classification of a limited dataset. The performance of the automated classification was evaluated by asking 11 independent blinded observers to classify all cells (n = 395) in one lens image. Time consumed by the automatic algorithm and visual classification of cells was recorded. On an average, 77% of the cells were correctly classified as compared with the majority vote of the visual observers. The average agreement among visual observers was 83%. However, variation among visual observers was high, and agreement between two visual observers was as low as 71% in the worst case. Automated classification was on average 10 times faster than visual scoring. The presented method enables objective and fast detection of lens epithelial cells and quantification of expression of fluorescent signal with an accuracy comparable with the variability among visual observers. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Detection and capture of single circulating melanoma cells using photoacoustic flowmetry

Science.gov (United States)

O'Brien, Christine; Mosley, Jeffrey; Goldschmidt, Benjamin S.; Viator, John A.

2010-02-01

Photoacoustic flowmetry has been used to detect single circulating melanoma cells in vitro. Circulating melanoma cells are those cells that travel in the blood and lymph systems to create secondary tumors and are the hallmark of metastasis. This technique involves taking blood samples from patients, separating the white blood and melanoma cells from whole blood and irradiating them with a pulsed laser in a flowmetry set up. Rapid, visible wavelength laser pulses on the order of 5 ns can induce photoacoustic waves in melanoma cells due to their melanin content, while surrounding white blood cells remain acoustically passive. We have developed a system that identifies rare melanoma cells and captures them in 50 microliter volumes using suction applied near the photoacoustic detection chamber. The 50 microliter sample is then diluted and the experiment is repeated using the new sample until only a melanoma cell remains. We have tested this system on dyed microspheres ranging in size from 300 to 500 microns. Capture of circulating melanoma cells may provide the opportunity to study metastatic cells for basic understanding of the spread of cancer and to optimize patient specific therapies.

Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

Science.gov (United States)

Baran, Richard; Northen, Trent R

2013-10-15

Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

Single-cell analysis reveals a link between CD3- and CD59-mediated signaling pathways in Jurkat T cells

International Nuclear Information System (INIS)

Lipp, A. M.

2012-01-01

Elevation of intracellular free calcium concentration ([Ca2+]i) is a key signal during T cell activation and is commonly used as a read-out parameter for stimulation of T cell signaling. Upon T cell stimulation a variety of calcium signals is produced by individual cells of the T cell population and the type of calcium signal strongly influences cell fate decisions. The heterogeneous nature of T cells is masked in ensemble measurements, which highlights the need for single-cell measurements. In this study we used single-cell calcium measurements in Jurkat cells to investigate signaling pathways, which are triggered by different proteins, namely CD3 and CD59. By application of an automated cluster algorithm the presented assay provides unbiased analysis of a large data set of individual calcium time traces generated by the whole cell population. By using this method we could demonstrate that the Jurkat population generates heterogeneous calcium signals in a stimulus-dependent manner. Furthermore, our data revealed the existence of a link between CD3- and CD59-mediated signaling pathways. Single-cell calcium measurements in Jurkat cells expressing different levels of the T cell receptor (TCR) complex indicated that CD59-mediated calcium signaling is critically dependent on TCR surface expression levels. In addition, triggering CD59-mediated calcium signaling resulted in down-regulation of TCR surface expression levels, which is known to happen upon direct TCR triggering too. Moreover, by using siRNA-mediated protein knock-downs and protein knock-out Jurkat mutants we could show that CD3- and CD59-mediated calcium signaling require identical key proteins. We therefore explored by which mechanism CD59-mediated signaling couples into TCR-mediated signaling. Fluorescence recovery after photobleaching (FRAP) experiments and live-cell protein-protein interaction assays provided no evidence of a direct physical interaction between CD3- and CD59-mediated signaling pathways

Automated Photoreceptor Cell Identification on Nonconfocal Adaptive Optics Images Using Multiscale Circular Voting.

Science.gov (United States)

Liu, Jianfei; Jung, HaeWon; Dubra, Alfredo; Tam, Johnny

2017-09-01

Adaptive optics scanning light ophthalmoscopy (AOSLO) has enabled quantification of the photoreceptor mosaic in the living human eye using metrics such as cell density and average spacing. These rely on the identification of individual cells. Here, we demonstrate a novel approach for computer-aided identification of cone photoreceptors on nonconfocal split detection AOSLO images. Algorithms for identification of cone photoreceptors were developed, based on multiscale circular voting (MSCV) in combination with a priori knowledge that split detection images resemble Nomarski differential interference contrast images, in which dark and bright regions are present on the two sides of each cell. The proposed algorithm locates dark and bright region pairs, iteratively refining the identification across multiple scales. Identification accuracy was assessed in data from 10 subjects by comparing automated identifications with manual labeling, followed by computation of density and spacing metrics for comparison to histology and published data. There was good agreement between manual and automated cone identifications with overall recall, precision, and F1 score of 92.9%, 90.8%, and 91.8%, respectively. On average, computed density and spacing values using automated identification were within 10.7% and 11.2% of the expected histology values across eccentricities ranging from 0.5 to 6.2 mm. There was no statistically significant difference between MSCV-based and histology-based density measurements (P = 0.96, Kolmogorov-Smirnov 2-sample test). MSCV can accurately detect cone photoreceptors on split detection images across a range of eccentricities, enabling quick, objective estimation of photoreceptor mosaic metrics, which will be important for future clinical trials utilizing adaptive optics.

Automated Methods Of Corrosion Measurements

DEFF Research Database (Denmark)

Bech-Nielsen, Gregers; Andersen, Jens Enevold Thaulov; Reeve, John Ch

1997-01-01

The chapter describes the following automated measurements: Corrosion Measurements by Titration, Imaging Corrosion by Scanning Probe Microscopy, Critical Pitting Temperature and Application of the Electrochemical Hydrogen Permeation Cell.......The chapter describes the following automated measurements: Corrosion Measurements by Titration, Imaging Corrosion by Scanning Probe Microscopy, Critical Pitting Temperature and Application of the Electrochemical Hydrogen Permeation Cell....

Gravity-Assist Trajectories to the Ice Giants: An Automated Method to Catalog Mass-or Time-Optimal Solutions

Science.gov (United States)

Hughes, Kyle M.; Knittel, Jeremy M.; Englander, Jacob A.

2017-01-01

This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood---allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.

Automation model of sewerage rehabilitation planning.

Science.gov (United States)

Yang, M D; Su, T C

2006-01-01

The major steps of sewerage rehabilitation include inspection of sewerage, assessment of structural conditions, computation of structural condition grades, and determination of rehabilitation methods and materials. Conventionally, sewerage rehabilitation planning relies on experts with professional background that is tedious and time-consuming. This paper proposes an automation model of planning optimal sewerage rehabilitation strategies for the sewer system by integrating image process, clustering technology, optimization, and visualization display. Firstly, image processing techniques, such as wavelet transformation and co-occurrence features extraction, were employed to extract various characteristics of structural failures from CCTV inspection images. Secondly, a classification neural network was established to automatically interpret the structural conditions by comparing the extracted features with the typical failures in a databank. Then, to achieve optimal rehabilitation efficiency, a genetic algorithm was used to determine appropriate rehabilitation methods and substitution materials for the pipe sections with a risk of mal-function and even collapse. Finally, the result from the automation model can be visualized in a geographic information system in which essential information of the sewer system and sewerage rehabilitation plans are graphically displayed. For demonstration, the automation model of optimal sewerage rehabilitation planning was applied to a sewer system in east Taichung, Chinese Taiwan.

Design and optimization of the plasmonic graphene/InP thin-film solar-cell structure

Science.gov (United States)

Nematpour, Abedin; Nikoufard, Mahmoud; Mehragha, Rouholla

2018-06-01

In this paper, a graphene/InP thin-film Schottky-junction solar cell with a periodic array of plasmonic back-reflector is proposed. In this structure, a single-layer graphene sheet is deposited on the surface of the InP to form a Schottky junction. Then, the layer stack of the proposed solar-cell is optimized to have a maximum optical absorption of 〈A W〉  =  0.985 (98.5%) and short-circuit current density of J sc  =  33.01 mA cm‑2.

Nano-scale microfluidics to study 3D chemotaxis at the single cell level.

Directory of Open Access Journals (Sweden)

Corina Frick

Full Text Available Directed migration of cells relies on their ability to sense directional guidance cues and to interact with pericellular structures in order to transduce contractile cytoskeletal- into mechanical forces. These biomechanical processes depend highly on microenvironmental factors such as exposure to 2D surfaces or 3D matrices. In vivo, the majority of cells are exposed to 3D environments. Data on 3D cell migration are mostly derived from intravital microscopy or collagen-based in vitro assays. Both approaches offer only limited controllability of experimental conditions. Here, we developed an automated microfluidic system that allows positioning of cells in 3D microenvironments containing highly controlled diffusion-based chemokine gradients. Tracking migration in such gradients was feasible in real time at the single cell level. Moreover, the setup allowed on-chip immunocytochemistry and thus linking of functional with phenotypical properties in individual cells. Spatially defined retrieval of cells from the device allows down-stream off-chip analysis. Using dendritic cells as a model, our setup specifically allowed us for the first time to quantitate key migration characteristics of cells exposed to identical gradients of the chemokine CCL19 yet placed on 2D vs in 3D environments. Migration properties between 2D and 3D migration were distinct. Morphological features of cells migrating in an in vitro 3D environment were similar to those of cells migrating in animal tissues, but different from cells migrating on a surface. Our system thus offers a highly controllable in vitro-mimic of a 3D environment that cells traffic in vivo.

Automated MAD and MIR structure solution

International Nuclear Information System (INIS)

Terwilliger, Thomas C.; Berendzen, Joel

1999-01-01

A fully automated procedure for solving MIR and MAD structures has been developed using a scoring scheme to convert the structure-solution process into an optimization problem. Obtaining an electron-density map from X-ray diffraction data can be difficult and time-consuming even after the data have been collected, largely because MIR and MAD structure determinations currently require many subjective evaluations of the qualities of trial heavy-atom partial structures before a correct heavy-atom solution is obtained. A set of criteria for evaluating the quality of heavy-atom partial solutions in macromolecular crystallography have been developed. These have allowed the conversion of the crystal structure-solution process into an optimization problem and have allowed its automation. The SOLVE software has been used to solve MAD data sets with as many as 52 selenium sites in the asymmetric unit. The automated structure-solution process developed is a major step towards the fully automated structure-determination, model-building and refinement procedure which is needed for genomic scale structure determinations

Automated high-dose rate brachytherapy treatment planning for a single-channel vaginal cylinder applicator

Science.gov (United States)

Zhou, Yuhong; Klages, Peter; Tan, Jun; Chi, Yujie; Stojadinovic, Strahinja; Yang, Ming; Hrycushko, Brian; Medin, Paul; Pompos, Arnold; Jiang, Steve; Albuquerque, Kevin; Jia, Xun

2017-06-01

High dose rate (HDR) brachytherapy treatment planning is conventionally performed manually and/or with aids of preplanned templates. In general, the standard of care would be elevated by conducting an automated process to improve treatment planning efficiency, eliminate human error, and reduce plan quality variations. Thus, our group is developing AutoBrachy, an automated HDR brachytherapy planning suite of modules used to augment a clinical treatment planning system. This paper describes our proof-of-concept module for vaginal cylinder HDR planning that has been fully developed. After a patient CT scan is acquired, the cylinder applicator is automatically segmented using image-processing techniques. The target CTV is generated based on physician-specified treatment depth and length. Locations of the dose calculation point, apex point and vaginal surface point, as well as the central applicator channel coordinates, and the corresponding dwell positions are determined according to their geometric relationship with the applicator and written to a structure file. Dwell times are computed through iterative quadratic optimization techniques. The planning information is then transferred to the treatment planning system through a DICOM-RT interface. The entire process was tested for nine patients. The AutoBrachy cylindrical applicator module was able to generate treatment plans for these cases with clinical grade quality. Computation times varied between 1 and 3 min on an Intel Xeon CPU E3-1226 v3 processor. All geometric components in the automated treatment plans were generated accurately. The applicator channel tip positions agreed with the manually identified positions with submillimeter deviations and the channel orientations between the plans agreed within less than 1 degree. The automatically generated plans obtained clinically acceptable quality.

Laboratory automation: trajectory, technology, and tactics.

Science.gov (United States)

Markin, R S; Whalen, S A

2000-05-01

Laboratory automation is in its infancy, following a path parallel to the development of laboratory information systems in the late 1970s and early 1980s. Changes on the horizon in healthcare and clinical laboratory service that affect the delivery of laboratory results include the increasing age of the population in North America, the implementation of the Balanced Budget Act (1997), and the creation of disease management companies. Major technology drivers include outcomes optimization and phenotypically targeted drugs. Constant cost pressures in the clinical laboratory have forced diagnostic manufacturers into less than optimal profitability states. Laboratory automation can be a tool for the improvement of laboratory services and may decrease costs. The key to improvement of laboratory services is implementation of the correct automation technology. The design of this technology should be driven by required functionality. Automation design issues should be centered on the understanding of the laboratory and its relationship to healthcare delivery and the business and operational processes in the clinical laboratory. Automation design philosophy has evolved from a hardware-based approach to a software-based approach. Process control software to support repeat testing, reflex testing, and transportation management, and overall computer-integrated manufacturing approaches to laboratory automation implementation are rapidly expanding areas. It is clear that hardware and software are functionally interdependent and that the interface between the laboratory automation system and the laboratory information system is a key component. The cost-effectiveness of automation solutions suggested by vendors, however, has been difficult to evaluate because the number of automation installations are few and the precision with which operational data have been collected to determine payback is suboptimal. The trend in automation has moved from total laboratory automation to a

Single cell time-lapse analysis reveals that podoplanin enhances cell survival and colony formation capacity of squamous cell carcinoma cells.

Science.gov (United States)

Miyashita, Tomoyuki; Higuchi, Youichi; Kojima, Motohiro; Ochiai, Atsushi; Ishii, Genichiro

2017-01-06

Tumor initiating cells (TICs) are characterized by high clonal expansion capacity. We previously reported that podoplanin is a TIC-specific marker for the human squamous cell carcinoma cell line A431. The aim of this study is to explore the molecular mechanism underlying the high clonal expansion potential of podoplanin-positive A431cells using Fucci imaging. Single podoplanin-positive cells created large colonies at a significantly higher frequency than single podoplanin-negative cells, whereas no difference was observed between the two types of cells with respect to cell cycle status. Conversely, the cell death ratio of progenies derived from podoplanin-positive single cell was significantly lower than that of cells derived from podoplanin-negative cells. Single A431 cells, whose podoplanin expression was suppressed by RNA interference, exhibited increased cell death ratios and decreased frequency of large colony forming. Moreover, the frequency of large colony forming decreased significantly when podoplanin-positive single cells was treated with a ROCK (Rho-associated coiled-coil kinase) inhibitor, whereas no difference was observed in single podoplanin-negative cells. Our current study cleared that high clonal expansion capacity of podoplanin-positive TICs populations was the result of reduced cell death by podoplanin-mediated signaling. Therefore, podoplanin activity may be a therapeutic target in the treatment of squamous cell carcinomas.

PleurAlert: an augmented chest drainage system with electronic sensing, automated alerts and internet connectivity.

Science.gov (United States)

Leeson, Cory E; Weaver, Robert A; Bissell, Taylor; Hoyer, Rachel; McClain, Corinne; Nelson, Douglas A; Samosky, Joseph T

2012-01-01

We have enhanced a common medical device, the chest tube drainage container, with electronic sensing of fluid volume, automated detection of critical alarm conditions and the ability to automatically send alert text messages to a nurse's cell phone. The PleurAlert system provides a simple touch-screen interface and can graphically display chest tube output over time. Our design augments a device whose basic function dates back 50 years by adding technology to automate and optimize a monitoring process that can be time consuming and inconvenient for nurses. The system may also enhance detection of emergency conditions and speed response time.

FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis.

Directory of Open Access Journals (Sweden)

Alex D Herbert

Full Text Available Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ.

Automated computation of arbor densities: a step toward identifying neuronal cell types

Directory of Open Access Journals (Sweden)

Uygar eSümbül

2014-11-01

Full Text Available The shape and position of a neuron convey information regarding its molecular and functional identity. The identification of cell types from structure, a classic method, relies on the time-consuming step of arbor tracing. However, as genetic tools and imaging methods make data-driven approaches to neuronal circuit analysis feasible, the need for automated processing increases. Here, we first establish that mouse retinal ganglion cell types can be as precise about distributing their arbor volumes across the inner plexiform layer as they are about distributing the skeletons of the arbors. Then, we describe an automated approach to computing the spatial distribution of the dendritic arbors, or arbor density, with respect to a global depth coordinate based on this observation. Our method involves three-dimensional reconstruction of neuronal arbors by a supervised machine learning algorithm, post-processing of the enhanced stacks to remove somata and isolate the neuron of interest, and registration of neurons to each other using automatically detected arbors of the starburst amacrine interneurons as fiducial markers. In principle, this method could be generalizable to other structures of the CNS, provided that they allow sparse labeling of the cells and contain a reliable axis of spatial reference.

Single cell Hi-C reveals cell-to-cell variability in chromosome structure

Science.gov (United States)

Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter

2013-01-01

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610

Capturing Three-Dimensional Genome Organization in Individual Cells by Single-Cell Hi-C.

Science.gov (United States)

Nagano, Takashi; Wingett, Steven W; Fraser, Peter

2017-01-01

Hi-C is a powerful method to investigate genome-wide, higher-order chromatin and chromosome conformations averaged from a population of cells. To expand the potential of Hi-C for single-cell analysis, we developed single-cell Hi-C. Similar to the existing "ensemble" Hi-C method, single-cell Hi-C detects proximity-dependent ligation events between cross-linked and restriction-digested chromatin fragments in cells. A major difference between the single-cell Hi-C and ensemble Hi-C protocol is that the proximity-dependent ligation is carried out in the nucleus. This allows the isolation of individual cells in which nearly the entire Hi-C procedure has been carried out, enabling the production of a Hi-C library and data from individual cells. With this new method, we studied genome conformations and found evidence for conserved topological domain organization from cell to cell, but highly variable interdomain contacts and chromosome folding genome wide. In addition, we found that the single-cell Hi-C protocol provided cleaner results with less technical noise suggesting it could be used to improve the ensemble Hi-C technique.

Extraction of the number of peroxisomes in yeast cells by automated image analysis.

Science.gov (United States)

Niemistö, Antti; Selinummi, Jyrki; Saleem, Ramsey; Shmulevich, Ilya; Aitchison, John; Yli-Harja, Olli

2006-01-01

An automated image analysis method for extracting the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local mean-variance space. The watershed transformation is thereafter employed to separate cells that are clustered together. The peroxisomes are detected by thresholding the fluorescent image. The method is tested with several images of a budding yeast Saccharomyces cerevisiae population, and the results are compared with manually obtained results.

Replica Analysis for Portfolio Optimization with Single-Factor Model

Science.gov (United States)

Shinzato, Takashi

2017-06-01

In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

Automated patch clamp on mESC-derived cardiomyocytes for cardiotoxicity prediction.

Science.gov (United States)

Stoelzle, Sonja; Haythornthwaite, Alison; Kettenhofen, Ralf; Kolossov, Eugen; Bohlen, Heribert; George, Michael; Brüggemann, Andrea; Fertig, Niels

2011-09-01

Cardiovascular side effects are critical in drug development and have frequently led to late-stage project terminations or even drug withdrawal from the market. Physiologically relevant and predictive assays for cardiotoxicity are hence strongly demanded by the pharmaceutical industry. To identify a potential impact of test compounds on ventricular repolarization, typically a variety of ion channels in diverse heterologously expressing cells have to be investigated. Similar to primary cells, in vitro-generated stem cell-derived cardiomyocytes simultaneously express cardiac ion channels. Thus, they more accurately represent the native situation compared with cell lines overexpressing only a single type of ion channel. The aim of this study was to determine if stem cell-derived cardiomyocytes are suited for use in an automated patch clamp system. The authors show recordings of cardiac ion currents as well as action potential recordings in readily available stem cell-derived cardiomyocytes. Besides monitoring inhibitory effects of reference compounds on typical cardiac ion currents, the authors revealed for the first time drug-induced modulation of cardiac action potentials in an automated patch clamp system. The combination of an in vitro cardiac cell model with higher throughput patch clamp screening technology allows for a cost-effective cardiotoxicity prediction in a physiologically relevant cell system.

QuantifyMe: An Open-Source Automated Single-Case Experimental Design Platform †

Science.gov (United States)

Sano, Akane; Ferguson, Craig; Mohan, Akshay; Picard, Rosalind W.

2018-01-01

Smartphones and wearable sensors have enabled unprecedented data collection, with many products now providing feedback to users about recommended step counts or sleep durations. However, these recommendations do not provide personalized insights that have been shown to be best suited for a specific individual. A scientific way to find individualized recommendations and causal links is to conduct experiments using single-case experimental design; however, properly designed single-case experiments are not easy to conduct on oneself. We designed, developed, and evaluated a novel platform, QuantifyMe, for novice self-experimenters to conduct proper-methodology single-case self-experiments in an automated and scientific manner using their smartphones. We provide software for the platform that we used (available for free on GitHub), which provides the methodological elements to run many kinds of customized studies. In this work, we evaluate its use with four different kinds of personalized investigations, examining how variables such as sleep duration and regularity, activity, and leisure time affect personal happiness, stress, productivity, and sleep efficiency. We conducted a six-week pilot study (N = 13) to evaluate QuantifyMe. We describe the lessons learned developing the platform and recommendations for its improvement, as well as its potential for enabling personalized insights to be scientifically evaluated in many individuals, reducing the high administrative cost for advancing human health and wellbeing. PMID:29621133

Optimizing human-system interface automation design based on a skill-rule-knowledge framework

International Nuclear Information System (INIS)

Lin, Chiuhsiang Joe; Yenn, T.-C.; Yang, C.-W.

2010-01-01

This study considers the technological change that has occurred in complex systems within the past 30 years. The role of human operators in controlling and interacting with complex systems following the technological change was also investigated. Modernization of instrumentation and control systems and components leads to a new issue of human-automation interaction, in which human operational performance must be considered in automated systems. The human-automation interaction can differ in its types and levels. A system design issue is usually realized: given these technical capabilities, which system functions should be automated and to what extent? A good automation design can be achieved by making an appropriate human-automation function allocation. To our knowledge, only a few studies have been published on how to achieve appropriate automation design with a systematic procedure. Further, there is a surprising lack of information on examining and validating the influences of levels of automation (LOAs) on instrumentation and control systems in the advanced control room (ACR). The study we present in this paper proposed a systematic framework to help in making an appropriate decision towards types of automation (TOA) and LOAs based on a 'Skill-Rule-Knowledge' (SRK) model. From the evaluating results, it was shown that the use of either automatic mode or semiautomatic mode is insufficient to prevent human errors. For preventing the occurrences of human errors and ensuring the safety in ACR, the proposed framework can be valuable for making decisions in human-automation allocation.

Automated diagnostics scoping study. Final report

Energy Technology Data Exchange (ETDEWEB)

Quadrel, R.W.; Lash, T.A.

1994-06-01

The objective of the Automated Diagnostics Scoping Study was to investigate the needs for diagnostics in building operation and to examine some of the current technologies in automated diagnostics that can address these needs. The study was conducted in two parts. In the needs analysis, the authors interviewed facility managers and engineers at five building sites. In the technology survey, they collected published information on automated diagnostic technologies in commercial and military applications as well as on technologies currently under research. The following describe key areas that the authors identify for the research, development, and deployment of automated diagnostic technologies: tools and techniques to aid diagnosis during building commissioning, especially those that address issues arising from integrating building systems and diagnosing multiple simultaneous faults; technologies to aid diagnosis for systems and components that are unmonitored or unalarmed; automated capabilities to assist cause-and-effect exploration during diagnosis; inexpensive, reliable sensors, especially those that expand the current range of sensory input; technologies that aid predictive diagnosis through trend analysis; integration of simulation and optimization tools with building automation systems to optimize control strategies and energy performance; integration of diagnostic, control, and preventive maintenance technologies. By relating existing technologies to perceived and actual needs, the authors reached some conclusions about the opportunities for automated diagnostics in building operation. Some of a building operator`s needs can be satisfied by off-the-shelf hardware and software. Other needs are not so easily satisfied, suggesting directions for future research. Their conclusions and suggestions are offered in the final section of this study.

Single-cell photoacoustic thermometry

Science.gov (United States)

Gao, Liang; Wang, Lidai; Li, Chiye; Liu, Yan; Ke, Haixin; Zhang, Chi

2013-01-01

Abstract. A novel photoacoustic thermometric method is presented for simultaneously imaging cells and sensing their temperature. With three-seconds-per-frame imaging speed, a temperature resolution of 0.2°C was achieved in a photo-thermal cell heating experiment. Compared to other approaches, the photoacoustic thermometric method has the advantage of not requiring custom-developed temperature-sensitive biosensors. This feature should facilitate the conversion of single-cell thermometry into a routine lab tool and make it accessible to a much broader biological research community. PMID:23377004

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

Science.gov (United States)

Parks, Donovan H.; Imelfort, Michael; Skennerton, Connor T.; Hugenholtz, Philip; Tyson, Gene W.

2015-01-01

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities. PMID:25977477

Distinction of metaphases in the first cell cycle for automated system in radiation dosimetry

International Nuclear Information System (INIS)

Hayata, I.; Kajima, J.; Okabe, N.

1992-01-01

As part of the biological improvements for developing an automated scoring system of radiation induced chromosome aberrations for radiation dosimetry, we introduce a new method for identifying the metaphases in the first cell cycle. Differing from the conventional method with BrdUrd, it focuses on the difference of chromosome number to be induced by inhibiting the cytokinesis with Cytochalasin B. Majority of the cells with 46 chromosomes were in the first cell cycle, and the ratio of those with 46 chromosomes in the second division was less than one per cent both when Cytochalasin B of 1.5 μg/ml was added to the culture of irradiated lymphocytes and when that of 1.8 μg/ml was added to that of non-irradiated cells for one day, respectively. The ratio of metaphases with over-condensed chromosomes is reduced, the clear-cut image of chromosomes is obtained, culture and staining processes are simpler, and the device of UV irradiation is not necessary. Thus the present Cytochalasin B method offers more qualified input, data based on the numerical difference, than conventional image based recognition, and upgrades the quality of the scoring in the automated analysis system. (Author)

EVALUATION OF ANAEMIA USING RED CELL AND RETICULOCYTE PARAMETERS USING AUTOMATED HAEMATOLOGY ANALYSER

Directory of Open Access Journals (Sweden)

Vidyadhar Rao

2016-06-01

Full Text Available Use of current models of Automated Haematology Analysers help in calculating the haemoglobin contents of the mature Red cells, Reticulocytes and percentages of Microcytic and hypochromic Red cells. This has helped the clinician in reaching early diagnosis and management of Different haemopoietic disorders like Iron Deficiency Anaemia, Thalassaemia and anaemia of chronic diseases. AIM This study is conducted using an Automated Haematology Analyser to evaluate anaemia using the Red Cell and Reticulocyte parameters. Three types of anaemia were evaluated; iron deficiency anaemia, anaemia of long duration and anaemia associated with chronic disease and Iron deficiency. MATERIALS AND METHODS The blood samples were collected from 287 adult patients with anaemia differentiated depending upon their iron status, haemoglobinopathies and inflammatory activity. Iron deficiency anaemia (n=132, anaemia of long duration (ACD, (n=97 and anaemia associated with chronic disease with iron deficiency (ACD Combi, (n=58. Microcytic Red cells, hypochromic red cells percentage and levels of haemoglobin in reticulocytes and matured RBCs were calculated. The accuracy of the parameters was analysed using receiver operating characteristic analyser to differentiate between the types of anaemia. OBSERVATIONS AND RESULTS There was no difference in parameters between the iron deficiency group or anaemia associated with chronic disease and iron deficiency. The hypochromic red cells percentage was the best parameter in differentiating anaemia of chronic disease with or without absolute iron deficiency with a sensitivity of 72.7% and a specificity of 70.4%. CONCLUSIONS The parameters of red cells and reticulocytes were of reasonably good indicators in differentiating the absolute iron deficiency anaemia with chronic disease.

Cell type discovery using single-cell transcriptomics: implications for ontological representation.

Science.gov (United States)

Aevermann, Brian D; Novotny, Mark; Bakken, Trygve; Miller, Jeremy A; Diehl, Alexander D; Osumi-Sutherland, David; Lasken, Roger S; Lein, Ed S; Scheuermann, Richard H

2018-05-01

Cells are fundamental function units of multicellular organisms, with different cell types playing distinct physiological roles in the body. The recent advent of single-cell transcriptional profiling using RNA sequencing is producing 'big data', enabling the identification of novel human cell types at an unprecedented rate. In this review, we summarize recent work characterizing cell types in the human central nervous and immune systems using single-cell and single-nuclei RNA sequencing, and discuss the implications that these discoveries are having on the representation of cell types in the reference Cell Ontology (CL). We propose a method, based on random forest machine learning, for identifying sets of necessary and sufficient marker genes, which can be used to assemble consistent and reproducible cell type definitions for incorporation into the CL. The representation of defined cell type classes and their relationships in the CL using this strategy will make the cell type classes being identified by high-throughput/high-content technologies findable, accessible, interoperable and reusable (FAIR), allowing the CL to serve as a reference knowledgebase of information about the role that distinct cellular phenotypes play in human health and disease.

A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation.

Science.gov (United States)

Nestorowa, Sonia; Hamey, Fiona K; Pijuan Sala, Blanca; Diamanti, Evangelia; Shepherd, Mairi; Laurenti, Elisa; Wilson, Nicola K; Kent, David G; Göttgens, Berthold

2016-08-25

Maintenance of the blood system requires balanced cell fate decisions by hematopoietic stem and progenitor cells (HSPCs). Because cell fate choices are executed at the individual cell level, new single-cell profiling technologies offer exciting possibilities for mapping the dynamic molecular changes underlying HSPC differentiation. Here, we have used single-cell RNA sequencing to profile more than 1600 single HSPCs, and deep sequencing has enabled detection of an average of 6558 protein-coding genes per cell. Index sorting, in combination with broad sorting gates, allowed us to retrospectively assign cells to 12 commonly sorted HSPC phenotypes while also capturing intermediate cells typically excluded by conventional gating. We further show that independently generated single-cell data sets can be projected onto the single-cell resolution expression map to directly compare data from multiple groups and to build and refine new hypotheses. Reconstruction of differentiation trajectories reveals dynamic expression changes associated with early lymphoid, erythroid, and granulocyte-macrophage differentiation. The latter two trajectories were characterized by common upregulation of cell cycle and oxidative phosphorylation transcriptional programs. By using external spike-in controls, we estimate absolute messenger RNA (mRNA) levels per cell, showing for the first time that despite a general reduction in total mRNA, a subset of genes shows higher expression levels in immature stem cells consistent with active maintenance of the stem-cell state. Finally, we report the development of an intuitive Web interface as a new community resource to permit visualization of gene expression in HSPCs at single-cell resolution for any gene of choice. © 2016 by The American Society of Hematology.

Fast Filtration of Bacterial or Mammalian Suspension Cell Cultures for Optimal Metabolomics Results.

Directory of Open Access Journals (Sweden)

Natalie Bordag

Full Text Available The metabolome offers real time detection of the adaptive, multi-parametric response of the organisms to environmental changes, pathophysiological stimuli or genetic modifications and thus rationalizes the optimization of cell cultures in bioprocessing. In bioprocessing the measurement of physiological intracellular metabolite levels is imperative for successful applications. However, a sampling method applicable to all cell types with little to no validation effort which simultaneously offers high recovery rates, high metabolite coverage and sufficient removal of extracellular contaminations is still missing. Here, quenching, centrifugation and fast filtration were compared and fast filtration in combination with a stabilizing washing solution was identified as the most promising sampling method. Different influencing factors such as filter type, vacuum pressure, washing solutions were comprehensively tested. The improved fast filtration method (MxP® FastQuench followed by routine lipid/polar extraction delivers a broad metabolite coverage and recovery reflecting well physiological intracellular metabolite levels for different cell types, such as bacteria (Escherichia coli as well as mammalian cells chinese hamster ovary (CHO and mouse myeloma cells (NS0.The proposed MxP® FastQuench allows sampling, i.e. separation of cells from medium with washing and quenching, in less than 30 seconds and is robustly designed to be applicable to all cell types. The washing solution contains the carbon source respectively the 13C-labeled carbon source to avoid nutritional stress during sampling. This method is also compatible with automation which would further reduce sampling times and the variability of metabolite profiling data.

Cloning of Plasmodium falciparum by single-cell sorting.

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Miao, Jun; Li, Xiaolian; Cui, Liwang

2010-10-01

Malaria parasite cloning is traditionally carried out mainly by using the limiting dilution method, which is laborious, imprecise, and unable to distinguish multiply-infected RBCs. In this study, we used a parasite engineered to express green fluorescent protein (GFP) to evaluate a single-cell sorting method for rapidly cloning Plasmodium falciparum. By dividing a two-dimensional scattergram from a cell sorter into 17 gates, we determined the parameters for isolating singly-infected erythrocytes and sorted them into individual cultures. Pre-gating of the engineered parasites for GFP allowed the isolation of almost 100% GFP-positive clones. Compared with the limiting dilution method, the number of parasite clones obtained by single-cell sorting was much higher. Molecular analyses showed that parasite isolates obtained by single-cell sorting were highly homogenous. This highly efficient single-cell sorting method should prove very useful for cloning both P. falciparum laboratory populations from genetic manipulation experiments and clinical samples. Copyright 2010 Elsevier Inc. All rights reserved.

Cloning of Plasmodium falciparum by single-cell sorting

Science.gov (United States)

Miao, Jun; Li, Xiaolian; Cui, Liwang

2010-01-01

Malaria parasite cloning is traditionally carried out mainly by using the limiting dilution method, which is laborious, imprecise, and unable to distinguish multiply-infected RBCs. In this study, we used a parasite engineered to express green fluorescent protein (GFP) to evaluate a single-cell sorting method for rapidly cloning Plasmodium falciparum. By dividing a two dimensional scattergram from a cell sorter into 17 gates, we determined the parameters for isolating singly-infected erythrocytes and sorted them into individual cultures. Pre-gating of the engineered parasites for GFP allowed the isolation of almost 100% GFP-positive clones. Compared with the limiting dilution method, the number of parasite clones obtained by single-cell sorting was much higher. Molecular analyses showed that parasite isolates obtained by single-cell sorting were highly homogenous. This highly efficient single-cell sorting method should prove very useful for cloning both P. falciparum laboratory populations from genetic manipulation experiments and clinical samples. PMID:20435038

Process development for automated solar cell and module production. Task 4: automated array assembly. Quarterly report No. 5

Energy Technology Data Exchange (ETDEWEB)

Hagerty, J.J.

1980-01-31

Construction of an automated solar cell layup and interconnect system is now complete. This system incorporates a Unimate 2000 B industrial robot with an end effector consisting of a vacuum pick up and induction heating coil. The robot interfaces with a smart cell preparation station which correctly orients the cell, applies solder paste and forms and positions the correct lengths of interconnect lead. The system is controlled and monitored by a TRS-80 micro computer. The first operational tests of the fully integrated station have been run. These tests proved the soundness of the basic design concept but also pointed to areas in which modifications are necessary. These modifications are nearly complete and the improved parts are being integrated. Development of the controlling computer program is progressing to both reflect these changes and reduce operating time.

Single-Cell Quantitative PCR: Advances and Potential in Cancer Diagnostics.

Science.gov (United States)

Ok, Chi Young; Singh, Rajesh R; Salim, Alaa A

2016-01-01

Tissues are heterogeneous in their components. If cells of interest are a minor population of collected tissue, it would be difficult to obtain genetic or genomic information of the interested cell population with conventional genomic DNA extraction from the collected tissue. Single-cell DNA analysis is important in the analysis of genetics of cell clonality, genetic anticipation, and single-cell DNA polymorphisms. Single-cell PCR using Single Cell Ampligrid/GeXP platform is described in this chapter.

Automated tracking for advanced satellite laser ranging systems

Science.gov (United States)

McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

Evaluation of a Multi-Parameter Sensor for Automated, Continuous Cell Culture Monitoring in Bioreactors

Science.gov (United States)

Pappas, D.; Jeevarajan, A.; Anderson, M. M.

2004-01-01

offer automated, continuous monitoring of cell cultures with a temporal resolution of 1 minute, which is not attainable by sampling via handheld blood analyzer (i-STAT). Conclusion: The resulting bias and precision found in these cell culture-based studies is comparable to Paratrend sensor clinical results. Although the large error in p02 measurements (+/-18 mm Hg) may be acceptable for clinical applications, where Paratrend values are periodically adjusted to a BGA measurement, the O2 sensor in this bundle may not be reliable enough for the single-calibration requirement of sensors used in NASA's bioreactors. The pH and pC02 sensors in the bundle are reliable and stable over the measurement period, and can be used without recalibration to measure cell cultures in rn.jcrogravity biotechnology experiments. Future work will test additional Paratrend sensors to provide statistical assessment of sensor performance.

Optimization of single channel glazed photovoltaic thermal (PVT) array using Evolutionary Algorithm (EA) and carbon credit earned by the optimized array

International Nuclear Information System (INIS)

Singh, Sonveer; Agrawal, Sanjay; Gadh, Rajit

2015-01-01

Highlights: • Optimization of SCGPVT array using Evolutionary Algorithm. • The overall exergy gain is maximized with an Evolutionary Algorithm. • Annual Performance has been evaluated for New Delhi (India). • There are improvement in results than the model given in literature. • Carbon credit analysis has been done. - Abstract: In this paper, work is carried out in three steps. In the first step, optimization of single channel glazed photovoltaic thermal (SCGPVT) array has been done with an Evolutionary Algorithm (EA) keeping the overall exergy gain is an objective function of the SCGPVT array. For maximization of overall exergy gain, total seven design variables have been optimized such as length of the channel (L), mass flow rate of flowing fluid (m_F), velocity of flowing fluid (V_F), convective heat transfer coefficient through the tedlar (U_T), overall heat transfer coefficient between solar cell to ambient through glass cover (U_S_C_A_G), overall back loss heat transfer coefficient from flowing fluid to ambient (U_F_A) and convective heat transfer coefficient of tedlar (h_T). It has been observed that the instant overall exergy gain obtained from optimized system is 1.42 kW h, which is 87.86% more than the overall exergy gain of a un-optimized system given in literature. In the second step, overall exergy gain and overall thermal gain of SCGPVT array has been evaluated annually and there are 69.52% and 88.05% improvement in annual overall exergy gain and annual overall thermal gain respectively than the un-optimized system for the same input irradiance and ambient temperature. In the third step, carbon credit earned by the optimized SCGPVT array has also been evaluated as per norms of Kyoto Protocol Bangalore climatic conditions.

Microchip screening platform for single cell assessment of NK cell cytotoxicity

Directory of Open Access Journals (Sweden)

Karolin eGuldevall

2016-04-01

Full Text Available Here we report a screening platform for assessment of the cytotoxic potential of individual natural killer (NK cells within larger populations. Human primary NK cells were distributed across a silicon-glass microchip containing 32 400 individual microwells loaded with target cells. Through fluorescence screening and automated image analysis the numbers of NK and live or dead target cells in each well could be assessed at different time points after initial mixing. Cytotoxicity was also studied by time-lapse live-cell imaging in microwells quantifying the killing potential of individual NK cells. Although most resting NK cells (≈75% were non-cytotoxic against the leukemia cell line K562, some NK cells were able to kill several (≥3 target cells within the 12 hours long experiment. In addition, the screening approach was adapted to increase the chance to find and evaluate serial killing NK cells. Even if the cytotoxic potential varied between donors it was evident that a small fraction of highly cytotoxic NK cells were responsible for a substantial portion of the killing. We demonstrate multiple assays where our platform can be used to enumerate and characterize cytotoxic cells, such as NK or T cells. This approach could find use in clinical applications, e.g. in the selection of donors for stem cell transplantation or generation of highly specific and cytotoxic cells for adoptive immunotherapy.

Microchip Screening Platform for Single Cell Assessment of NK Cell Cytotoxicity

Science.gov (United States)

Guldevall, Karolin; Brandt, Ludwig; Forslund, Elin; Olofsson, Karl; Frisk, Thomas W.; Olofsson, Per E.; Gustafsson, Karin; Manneberg, Otto; Vanherberghen, Bruno; Brismar, Hjalmar; Kärre, Klas; Uhlin, Michael; Önfelt, Björn

2016-01-01

Here, we report a screening platform for assessment of the cytotoxic potential of individual natural killer (NK) cells within larger populations. Human primary NK cells were distributed across a silicon–glass microchip containing 32,400 individual microwells loaded with target cells. Through fluorescence screening and automated image analysis, the numbers of NK and live or dead target cells in each well could be assessed at different time points after initial mixing. Cytotoxicity was also studied by time-lapse live-cell imaging in microwells quantifying the killing potential of individual NK cells. Although most resting NK cells (≈75%) were non-cytotoxic against the leukemia cell line K562, some NK cells were able to kill several (≥3) target cells within the 12-h long experiment. In addition, the screening approach was adapted to increase the chance to find and evaluate serial killing NK cells. Even if the cytotoxic potential varied between donors, it was evident that a small fraction of highly cytotoxic NK cells were responsible for a substantial portion of the killing. We demonstrate multiple assays where our platform can be used to enumerate and characterize cytotoxic cells, such as NK or T cells. This approach could find use in clinical applications, e.g., in the selection of donors for stem cell transplantation or generation of highly specific and cytotoxic cells for adoptive immunotherapy. PMID:27092139

Predictions for optimal mitigation of paracrine inhibitory signalling in haemopoietic stem cell cultures.

Science.gov (United States)

Berry, Joseph D; Godara, Pankaj; Liovic, Petar; Haylock, David N

2015-04-16

Recent studies in the literature have highlighted the critical role played by cell signalling in determining haemopoietic stem cell (HSC) fate within ex vivo culture systems. Stimulatory signals can enhance proliferation and promote differentiation, whilst inhibitory signals can significantly limit culture output. Numerical models of various mitigation strategies are presented and applied to determine effectiveness of these strategies toward mitigation of paracrine inhibitory signalling inherent in these culture systems. The strategies assessed include mixing, media-exchange, fed-batch and perfusion. The models predict that significant spatial concentration gradients exist in typical cell cultures, with important consequences for subsequent cell expansion. Media exchange is shown to be the most effective mitigation strategy, but remains labour intensive and difficult to scale-up for large culture systems. The fed-batch strategy is only effective at very small Peclet number, and its effect is diminished as the cell culture volume grows. Conversely, mixing is effective at high Peclet number, and ineffective at low Peclet number. The models predict that cell expansion in fed-batch cultures becomes independent of increasing dilution rate, consistent with experimental results previously reported in the literature. In contrast, the models predict that increasing the flow rate in perfused cultures will lead to increased cell expansion, indicating the suitability of perfusion for use as an automated, tunable strategy. The effect of initial cell seeding density is also investigated, with the model showing that perfusion outperforms dilution for all densities considered. The models predict that the impact of inhibitory signalling in HSC cultures can be mitigated against using media manipulation strategies, with the optimal strategy dependent upon the protein diffusion time-scale relative to the media manipulation time-scale. The key messages from this study can be applied to

Automation in biological crystallization.

Science.gov (United States)

Stewart, Patrick Shaw; Mueller-Dieckmann, Jochen

2014-06-01

Crystallization remains the bottleneck in the crystallographic process leading from a gene to a three-dimensional model of the encoded protein or RNA. Automation of the individual steps of a crystallization experiment, from the preparation of crystallization cocktails for initial or optimization screens to the imaging of the experiments, has been the response to address this issue. Today, large high-throughput crystallization facilities, many of them open to the general user community, are capable of setting up thousands of crystallization trials per day. It is thus possible to test multiple constructs of each target for their ability to form crystals on a production-line basis. This has improved success rates and made crystallization much more convenient. High-throughput crystallization, however, cannot relieve users of the task of producing samples of high quality. Moreover, the time gained from eliminating manual preparations must now be invested in the careful evaluation of the increased number of experiments. The latter requires a sophisticated data and laboratory information-management system. A review of the current state of automation at the individual steps of crystallization with specific attention to the automation of optimization is given.

Closed-Loop Real-Time Imaging Enables Fully Automated Cell-Targeted Patch-Clamp Neural Recording In Vivo.

Science.gov (United States)

Suk, Ho-Jun; van Welie, Ingrid; Kodandaramaiah, Suhasa B; Allen, Brian; Forest, Craig R; Boyden, Edward S

2017-08-30

Targeted patch-clamp recording is a powerful method for characterizing visually identified cells in intact neural circuits, but it requires skill to perform. We previously developed an algorithm that automates "blind" patching in vivo, but full automation of visually guided, targeted in vivo patching has not been demonstrated, with currently available approaches requiring human intervention to compensate for cell movement as a patch pipette approaches a targeted neuron. Here we present a closed-loop real-time imaging strategy that automatically compensates for cell movement by tracking cell position and adjusting pipette motion while approaching a target. We demonstrate our system's ability to adaptively patch, under continuous two-photon imaging and real-time analysis, fluorophore-expressing neurons of multiple types in the living mouse cortex, without human intervention, with yields comparable to skilled human experimenters. Our "imagepatching" robot is easy to implement and will help enable scalable characterization of identified cell types in intact neural circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

Droplet Microfluidics for Compartmentalized Cell Lysis and Extension of DNA from Single-Cells

Science.gov (United States)

Zimny, Philip; Juncker, David; Reisner, Walter

Current single cell DNA analysis methods suffer from (i) bias introduced by the need for molecular amplification and (ii) limited ability to sequence repetitive elements, resulting in (iii) an inability to obtain information regarding long range genomic features. Recent efforts to circumvent these limitations rely on techniques for sensing single molecules of DNA extracted from single-cells. Here we demonstrate a droplet microfluidic approach for encapsulation and biochemical processing of single-cells inside alginate microparticles. In our approach, single-cells are first packaged inside the alginate microparticles followed by cell lysis, DNA purification, and labeling steps performed off-chip inside this microparticle system. The alginate microparticles are then introduced inside a micro/nanofluidic system where the alginate is broken down via a chelating buffer, releasing long DNA molecules which are then extended inside nanofluidic channels for analysis via standard mapping protocols.

Mapping Cellular Hierarchy by Single-Cell Analysis of the Cell Surface Repertoire

OpenAIRE

Guo, Guoji; Luc, Sidinh; Marco, Eugenio; Lin, Ta-Wei; Peng, Cong; Kerenyi, Marc A.; Beyaz, Semir; Kim, Woojin; Xu, Jian; Das, Partha Pratim; Neff, Tobias; Zou, Keyong; Yuan, Guo-Cheng; Orkin, Stuart H.

2013-01-01

Stem cell differentiation pathways are most often studied at the population level, whereas critical decisions are executed at the level of single cells. We have established a highly multiplexed, quantitative PCR assay to profile in an unbiased manner a panel of all commonly used cell surface markers (280 genes) from individual cells. With this method we analyzed over 1500 single cells throughout the mouse hematopoietic system, and illustrate its utility for revealing important biological insi...

Optimizing the balance between task automation and human manual control in simulated submarine track management.

Science.gov (United States)

Chen, Stephanie I; Visser, Troy A W; Huf, Samuel; Loft, Shayne

2017-09-01

Automation can improve operator performance and reduce workload, but can also degrade operator situation awareness (SA) and the ability to regain manual control. In 3 experiments, we examined the extent to which automation could be designed to benefit performance while ensuring that individuals maintained SA and could regain manual control. Participants completed a simulated submarine track management task under varying task load. The automation was designed to facilitate information acquisition and analysis, but did not make task decisions. Relative to a condition with no automation, the continuous use of automation improved performance and reduced subjective workload, but degraded SA. Automation that was engaged and disengaged by participants as required (adaptable automation) moderately improved performance and reduced workload relative to no automation, but degraded SA. Automation engaged and disengaged based on task load (adaptive automation) provided no benefit to performance or workload, and degraded SA relative to no automation. Automation never led to significant return-to-manual deficits. However, all types of automation led to degraded performance on a nonautomated task that shared information processing requirements with automated tasks. Given these outcomes, further research is urgently required to establish how to design automation to maximize performance while keeping operators cognitively engaged. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

Science.gov (United States)

Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

2018-05-01

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Genomic Sequencing of Single Microbial Cells from Environmental Samples

Energy Technology Data Exchange (ETDEWEB)

Ishoey, Thomas; Woyke, Tanja; Stepanauskas, Ramunas; Novotny, Mark; Lasken, Roger S.

2008-02-01

Recently developed techniques allow genomic DNA sequencing from single microbial cells [Lasken RS: Single-cell genomic sequencing using multiple displacement amplification, Curr Opin Microbiol 2007, 10:510-516]. Here, we focus on research strategies for putting these methods into practice in the laboratory setting. An immediate consequence of single-cell sequencing is that it provides an alternative to culturing organisms as a prerequisite for genomic sequencing. The microgram amounts of DNA required as template are amplified from a single bacterium by a method called multiple displacement amplification (MDA) avoiding the need to grow cells. The ability to sequence DNA from individual cells will likely have an immense impact on microbiology considering the vast numbers of novel organisms, which have been inaccessible unless culture-independent methods could be used. However, special approaches have been necessary to work with amplified DNA. MDA may not recover the entire genome from the single copy present in most bacteria. Also, some sequence rearrangements can occur during the DNA amplification reaction. Over the past two years many research groups have begun to use MDA, and some practical approaches to single-cell sequencing have been developed. We review the consensus that is emerging on optimum methods, reliability of amplified template, and the proper interpretation of 'composite' genomes which result from the necessity of combining data from several single-cell MDA reactions in order to complete the assembly. Preferred laboratory methods are considered on the basis of experience at several large sequencing centers where >70% of genomes are now often recovered from single cells. Methods are reviewed for preparation of bacterial fractions from environmental samples, single-cell isolation, DNA amplification by MDA, and DNA sequencing.

X-ray microanalysis of single and cultured cells

International Nuclear Information System (INIS)

Wroblewski, J.; Roomans, G.M.

1984-01-01

X-ray microanalysis of single or cultured cells is often a useful alternative or complement to the analysis of the corresponding tissue. It also allows the analysis of individual cells in a cell population. Preparation for X-ray microanalysis poses a number of typical problems. Suspensions of single cells can be prepared by either of two pathways: (1) washing - mounting - drying, or (2) centrifugation - freezing or fixation - sectioning. The washing step in the preparation of single or cultured cells presents the most severe problems. Cultured cells are generally grown on a substrate that is compatible with both the analysis and the culture, washed and dried. In some cases, sectioning of cultured cell monolayers has been performed. Special problems in quantitative analysis occur in those cases where the cells are analyzed on a thick substrate, since the substrate contributes to the spectral background

Fluorescence In Situ Hybridization (FISH Signal Analysis Using Automated Generated Projection Images

Directory of Open Access Journals (Sweden)

Xingwei Wang

2012-01-01

Full Text Available Fluorescence in situ hybridization (FISH tests provide promising molecular imaging biomarkers to more accurately and reliably detect and diagnose cancers and genetic disorders. Since current manual FISH signal analysis is low-efficient and inconsistent, which limits its clinical utility, developing automated FISH image scanning systems and computer-aided detection (CAD schemes has been attracting research interests. To acquire high-resolution FISH images in a multi-spectral scanning mode, a huge amount of image data with the stack of the multiple three-dimensional (3-D image slices is generated from a single specimen. Automated preprocessing these scanned images to eliminate the non-useful and redundant data is important to make the automated FISH tests acceptable in clinical applications. In this study, a dual-detector fluorescence image scanning system was applied to scan four specimen slides with FISH-probed chromosome X. A CAD scheme was developed to detect analyzable interphase cells and map the multiple imaging slices recorded FISH-probed signals into the 2-D projection images. CAD scheme was then applied to each projection image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm, identify FISH-probed signals using a top-hat transform, and compute the ratios between the normal and abnormal cells. To assess CAD performance, the FISH-probed signals were also independently visually detected by an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots in four testing samples. The study demonstrated the feasibility of automated FISH signal analysis that applying a CAD scheme to the automated generated 2-D projection images.

Programming cells by multiplex genome engineering and accelerated evolution.

Science.gov (United States)

Wang, Harris H; Isaacs, Farren J; Carr, Peter A; Sun, Zachary Z; Xu, George; Forest, Craig R; Church, George M

2009-08-13

The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales. Although in vitro and directed evolution methods have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-D-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.

Microprocessor-based integration of microfluidic control for the implementation of automated sensor monitoring and multithreaded optimization algorithms.

Science.gov (United States)

Ezra, Elishai; Maor, Idan; Bavli, Danny; Shalom, Itai; Levy, Gahl; Prill, Sebastian; Jaeger, Magnus S; Nahmias, Yaakov

2015-08-01

Microfluidic applications range from combinatorial synthesis to high throughput screening, with platforms integrating analog perfusion components, digitally controlled micro-valves and a range of sensors that demand a variety of communication protocols. Currently, discrete control units are used to regulate and monitor each component, resulting in scattered control interfaces that limit data integration and synchronization. Here, we present a microprocessor-based control unit, utilizing the MS Gadgeteer open framework that integrates all aspects of microfluidics through a high-current electronic circuit that supports and synchronizes digital and analog signals for perfusion components, pressure elements, and arbitrary sensor communication protocols using a plug-and-play interface. The control unit supports an integrated touch screen and TCP/IP interface that provides local and remote control of flow and data acquisition. To establish the ability of our control unit to integrate and synchronize complex microfluidic circuits we developed an equi-pressure combinatorial mixer. We demonstrate the generation of complex perfusion sequences, allowing the automated sampling, washing, and calibrating of an electrochemical lactate sensor continuously monitoring hepatocyte viability following exposure to the pesticide rotenone. Importantly, integration of an optical sensor allowed us to implement automated optimization protocols that require different computational challenges including: prioritized data structures in a genetic algorithm, distributed computational efforts in multiple-hill climbing searches and real-time realization of probabilistic models in simulated annealing. Our system offers a comprehensive solution for establishing optimization protocols and perfusion sequences in complex microfluidic circuits.

Single cell elemental analysis using nuclear microscopy

International Nuclear Information System (INIS)

Ren, M.Q.; Thong, P.S.P.; Kara, U.; Watt, F.

1999-01-01

The use of Particle Induced X-ray Emission (PIXE), Rutherford Backscattering Spectrometry (RBS) and Scanning Transmission Ion Microscopy (STIM) to provide quantitative elemental analysis of single cells is an area which has high potential, particularly when the trace elements such as Ca, Fe, Zn and Cu can be monitored. We describe the methodology of sample preparation for two cell types, the procedures of cell imaging using STIM, and the quantitative elemental analysis of single cells using RBS and PIXE. Recent work on single cells at the Nuclear Microscopy Research Centre,National University of Singapore has centred around two research areas: (a) Apoptosis (programmed cell death), which has been recently implicated in a wide range of pathological conditions such as cancer, Parkinson's disease etc, and (b) Malaria (infection of red blood cells by the malaria parasite). Firstly we present results on the elemental analysis of human Chang liver cells (ATTCC CCL 13) where vanadium ions were used to trigger apoptosis, and demonstrate that nuclear microscopy has the capability of monitoring vanadium loading within individual cells. Secondly we present the results of elemental changes taking place in individual mouse red blood cells which have been infected with the malaria parasite and treated with the anti-malaria drug Qinghaosu (QHS)