MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

Directory of Open Access Journals (Sweden)

Kuczmarski Thomas A

2006-10-01

Full Text Available Abstract Background MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. Description MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. Conclusion MannDB comprises a large number of genomes and comprehensive protein

Integrated Automation of High-Throughput Screening and Reverse Phase Protein Array Sample Preparation

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

into automated robotic high-throughput screens, which allows subsequent protein quantification. In this integrated solution, samples are directly forwarded to automated cell lysate preparation and preparation of dilution series, including reformatting to a protein spotter-compatible format after the high......-throughput screening. Tracking of huge sample numbers and data analysis from a high-content screen to RPPAs is accomplished via MIRACLE, a custom made software suite developed by us. To this end, we demonstrate that the RPPAs generated in this manner deliver reliable protein readouts and that GAPDH and TFR levels can...

The Protein Maker: an automated system for high-throughput parallel purification

International Nuclear Information System (INIS)

Smith, Eric R.; Begley, Darren W.; Anderson, Vanessa; Raymond, Amy C.; Haffner, Taryn E.; Robinson, John I.; Edwards, Thomas E.; Duncan, Natalie; Gerdts, Cory J.; Mixon, Mark B.; Nollert, Peter; Staker, Bart L.; Stewart, Lance J.

2011-01-01

The Protein Maker instrument addresses a critical bottleneck in structural genomics by allowing automated purification and buffer testing of multiple protein targets in parallel with a single instrument. Here, the use of this instrument to (i) purify multiple influenza-virus proteins in parallel for crystallization trials and (ii) identify optimal lysis-buffer conditions prior to large-scale protein purification is described. The Protein Maker is an automated purification system developed by Emerald BioSystems for high-throughput parallel purification of proteins and antibodies. This instrument allows multiple load, wash and elution buffers to be used in parallel along independent lines for up to 24 individual samples. To demonstrate its utility, its use in the purification of five recombinant PB2 C-terminal domains from various subtypes of the influenza A virus is described. Three of these constructs crystallized and one diffracted X-rays to sufficient resolution for structure determination and deposition in the Protein Data Bank. Methods for screening lysis buffers for a cytochrome P450 from a pathogenic fungus prior to upscaling expression and purification are also described. The Protein Maker has become a valuable asset within the Seattle Structural Genomics Center for Infectious Disease (SSGCID) and hence is a potentially valuable tool for a variety of high-throughput protein-purification applications

Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal

OpenAIRE

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of appl...

Non-Uniform Sampling and J-UNIO Automation for Efficient Protein NMR Structure Determination.

Science.gov (United States)

Didenko, Tatiana; Proudfoot, Andrew; Dutta, Samit Kumar; Serrano, Pedro; Wüthrich, Kurt

2015-08-24

High-resolution structure determination of small proteins in solution is one of the big assets of NMR spectroscopy in structural biology. Improvements in the efficiency of NMR structure determination by advances in NMR experiments and automation of data handling therefore attracts continued interest. Here, non-uniform sampling (NUS) of 3D heteronuclear-resolved [(1)H,(1)H]-NOESY data yielded two- to three-fold savings of instrument time for structure determinations of soluble proteins. With the 152-residue protein NP_372339.1 from Staphylococcus aureus and the 71-residue protein NP_346341.1 from Streptococcus pneumonia we show that high-quality structures can be obtained with NUS NMR data, which are equally well amenable to robust automated analysis as the corresponding uniformly sampled data. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fully automated laboratory and field-portable goniometer used for performing accurate and precise multiangular reflectance measurements

Science.gov (United States)

Harms, Justin D.; Bachmann, Charles M.; Ambeau, Brittany L.; Faulring, Jason W.; Ruiz Torres, Andres J.; Badura, Gregory; Myers, Emily

2017-10-01

Field-portable goniometers are created for a wide variety of applications. Many of these applications require specific types of instruments and measurement schemes and must operate in challenging environments. Therefore, designs are based on the requirements that are specific to the application. We present a field-portable goniometer that was designed for measuring the hemispherical-conical reflectance factor (HCRF) of various soils and low-growing vegetation in austere coastal and desert environments and biconical reflectance factors in laboratory settings. Unlike some goniometers, this system features a requirement for "target-plane tracking" to ensure that measurements can be collected on sloped surfaces, without compromising angular accuracy. The system also features a second upward-looking spectrometer to measure the spatially dependent incoming illumination, an integrated software package to provide full automation, an automated leveling system to ensure a standard frame of reference, a design that minimizes the obscuration due to self-shading to measure the opposition effect, and the ability to record a digital elevation model of the target region. This fully automated and highly mobile system obtains accurate and precise measurements of HCRF in a wide variety of terrain and in less time than most other systems while not sacrificing consistency or repeatability in laboratory environments.

Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH

International Nuclear Information System (INIS)

Volk, Jochen; Herrmann, Torsten; Wuethrich, Kurt

2008-01-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness

Accurate protein structure modeling using sparse NMR data and homologous structure information.

Science.gov (United States)

Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

2012-06-19

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Quantification of Eosinophilic Granule Protein Deposition in Biopsies of Inflammatory Skin Diseases by Automated Image Analysis of Highly Sensitive Immunostaining

Directory of Open Access Journals (Sweden)

Peter Kiehl

1999-01-01

Full Text Available Eosinophilic granulocytes are major effector cells in inflammation. Extracellular deposition of toxic eosinophilic granule proteins (EGPs, but not the presence of intact eosinophils, is crucial for their functional effect in situ. As even recent morphometric approaches to quantify the involvement of eosinophils in inflammation have been only based on cell counting, we developed a new method for the cell‐independent quantification of EGPs by image analysis of immunostaining. Highly sensitive, automated immunohistochemistry was done on paraffin sections of inflammatory skin diseases with 4 different primary antibodies against EGPs. Image analysis of immunostaining was performed by colour translation, linear combination and automated thresholding. Using strictly standardized protocols, the assay was proven to be specific and accurate concerning segmentation in 8916 fields of 520 sections, well reproducible in repeated measurements and reliable over 16 weeks observation time. The method may be valuable for the cell‐independent segmentation of immunostaining in other applications as well.

FireProt: web server for automated design of thermostable proteins

Science.gov (United States)

Musil, Milos; Stourac, Jan; Brezovsky, Jan; Prokop, Zbynek; Zendulka, Jaroslav; Martinek, Tomas

2017-01-01

Abstract There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot. PMID:28449074

Automated design evolution of stereochemically randomized protein foldamers

Science.gov (United States)

Ranbhor, Ranjit; Kumar, Anil; Patel, Kirti; Ramakrishnan, Vibin; Durani, Susheel

2018-05-01

Diversification of chain stereochemistry opens up the possibilities of an ‘in principle’ increase in the design space of proteins. This huge increase in the sequence and consequent structural variation is aimed at the generation of smart materials. To diversify protein structure stereochemically, we introduced L- and D-α-amino acids as the design alphabet. With a sequence design algorithm, we explored the usage of specific variables such as chirality and the sequence of this alphabet in independent steps. With molecular dynamics, we folded stereochemically diverse homopolypeptides and evaluated their ‘fitness’ for possible design as protein-like foldamers. We propose a fitness function to prune the most optimal fold among 1000 structures simulated with an automated repetitive simulated annealing molecular dynamics (AR-SAMD) approach. The highly scored poly-leucine fold with sequence lengths of 24 and 30 amino acids were later sequence-optimized using a Dead End Elimination cum Monte Carlo based optimization tool. This paper demonstrates a novel approach for the de novo design of protein-like foldamers.

Rapid detection, classification and accurate alignment of up to a million or more related protein sequences.

Science.gov (United States)

Neuwald, Andrew F

2009-08-01

The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical. This problem is addressed using Multiply-Aligned Profiles for Global Alignment of Protein Sequences (MAPGAPS). The MAPGAPS program uses a set of multiply-aligned profiles both as a query to detect and classify related sequences and as a template to multiply-align the sequences. It relies on Karlin-Altschul statistics for sensitivity and on PSI-BLAST (and other) heuristics for speed. Using as input a carefully curated multiple-profile alignment for P-loop GTPases, MAPGAPS correctly aligned weakly conserved sequence motifs within 33 distantly related GTPases of known structure. By comparison, the sequence- and structurally based alignment methods hmmalign and PROMALS3D misaligned at least 11 and 23 of these regions, respectively. When applied to a dataset of 65 million protein sequences, MAPGAPS identified, classified and aligned (with comparable accuracy) nearly half a million putative P-loop GTPase sequences. A C++ implementation of MAPGAPS is available at http://mapgaps.igs.umaryland.edu. Supplementary data are available at Bioinformatics online.

Automating the application of smart materials for protein crystallization

International Nuclear Information System (INIS)

Khurshid, Sahir; Govada, Lata; EL-Sharif, Hazim F.; Reddy, Subrayal M.; Chayen, Naomi E.

2015-01-01

The first semi-liquid, non-protein nucleating agent for automated protein crystallization trials is described. This ‘smart material’ is demonstrated to induce crystal growth and will provide a simple, cost-effective tool for scientists in academia and industry. The fabrication and validation of the first semi-liquid nonprotein nucleating agent to be administered automatically to crystallization trials is reported. This research builds upon prior demonstration of the suitability of molecularly imprinted polymers (MIPs; known as ‘smart materials’) for inducing protein crystal growth. Modified MIPs of altered texture suitable for high-throughput trials are demonstrated to improve crystal quality and to increase the probability of success when screening for suitable crystallization conditions. The application of these materials is simple, time-efficient and will provide a potent tool for structural biologists embarking on crystallization trials

Automated mass correction and data interpretation for protein open-access liquid chromatography-mass spectrometry.

Science.gov (United States)

Wagner, Craig D; Hall, John T; White, Wendy L; Miller, Luke A D; Williams, Jon D

2007-02-01

Characterization of recombinant protein purification fractions and final products by liquid chromatography-mass spectrometry (LC/MS) are requested more frequently each year. A protein open-access (OA) LC/MS system was developed in our laboratory to meet this demand. This paper compares the system that we originally implemented in our facilities in 2003 to the one now in use, and discusses, in more detail, recent enhancements that have improved its robustness, reliability, and data reporting capabilities. The system utilizes instruments equipped with reversed-phase chromatography and an orthogonal accelerated time-of-flight mass spectrometer fitted with an electrospray source. Sample analysis requests are accomplished using a simple form on a web-enabled laboratory information management system (LIMS). This distributed form is accessible from any intranet-connected company desktop computer. Automated data acquisition and processing are performed using a combination of in-house (OA-Self Service, OA-Monitor, and OA-Analysis Engine) and vendor-supplied programs (AutoLynx, and OpenLynx) located on acquisition computers and off-line processing workstations. Analysis results are then reported via the same web-based LIMS. Also presented are solutions to problems not addressed on commercially available, small-molecule OA-LC/MS systems. These include automated transforming of mass-to-charge (m/z) spectra to mass spectra and automated data interpretation that considers minor variants to the protein sequence-such as common post-translational modifications (PTMs). Currently, our protein OA-LC/MS platform runs on five LC/MS instruments located in three separate GlaxoSmithKline R&D sites in the US and UK. To date, more than 8000 protein OA-LC/MS samples have been analyzed. With these user friendly and highly automated OA systems in place, mass spectrometry plays a key role in assessing the quality of recombinant proteins, either produced at our facilities or bought from external

Rapid and accurate processing method for amide proton exchange rate measurement in proteins

International Nuclear Information System (INIS)

Koskela, Harri; Heikkinen, Outi; Kilpelaeinen, Ilkka; Heikkinen, Sami

2007-01-01

Exchange between protein backbone amide hydrogen and water gives relevant information about solvent accessibility and protein secondary structure stability. NMR spectroscopy provides a convenient tool to study these dynamic processes with saturation transfer experiments. Processing of this type of NMR spectra has traditionally required peak integration followed by exponential fitting, which can be tedious with large data sets. We propose here a computer-aided method that applies inverse Laplace transform in the exchange rate measurement. With this approach, the determination of exchange rates can be automated, and reliable results can be acquired rapidly without a need for manual processing

CASA: An Efficient Automated Assignment of Protein Mainchain NMR Data Using an Ordered Tree Search Algorithm

International Nuclear Information System (INIS)

Wang Jianyong; Wang Tianzhi; Zuiderweg, Erik R. P.; Crippen, Gordon M.

2005-01-01

Rapid analysis of protein structure, interaction, and dynamics requires fast and automated assignments of 3D protein backbone triple-resonance NMR spectra. We introduce a new depth-first ordered tree search method of automated assignment, CASA, which uses hand-edited peak-pick lists of a flexible number of triple resonance experiments. The computer program was tested on 13 artificially simulated peak lists for proteins up to 723 residues, as well as on the experimental data for four proteins. Under reasonable tolerances, it generated assignments that correspond to the ones reported in the literature within a few minutes of CPU time. The program was also tested on the proteins analyzed by other methods, with both simulated and experimental peaklists, and it could generate good assignments in all relevant cases. The robustness was further tested under various situations

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

Science.gov (United States)

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

A new software routine that automates the fitting of protein X-ray crystallographic electron-density maps.

Science.gov (United States)

Levitt, D G

2001-07-01

The classical approach to building the amino-acid residues into the initial electron-density map requires days to weeks of a skilled investigator's time. Automating this procedure should not only save time, but has the potential to provide a more accurate starting model for input to refinement programs. The new software routine MAID builds the protein structure into the electron-density map in a series of sequential steps. The first step is the fitting of the secondary alpha-helix and beta-sheet structures. These 'fits' are then used to determine the local amino-acid sequence assignment. These assigned fits are then extended through the loop regions and fused with the neighboring sheet or helix. The program was tested on the unaveraged 2.5 A selenomethionine multiple-wavelength anomalous dispersion (SMAD) electron-density map that was originally used to solve the structure of the 291-residue protein human heart short-chain L-3-hydroxyacyl-CoA dehydrogenase (SHAD). Inputting just the map density and the amino-acid sequence, MAID fitted 80% of the residues with an r.m.s.d. error of 0.43 A for the main-chain atoms and 1.0 A for all atoms without any user intervention. When tested on a higher quality 1.9 A SMAD map, MAID correctly fitted 100% (418) of the residues. A major advantage of the MAID fitting procedure is that it maintains ideal bond lengths and angles and constrains phi/psi angles to the appropriate Ramachandran regions. Recycling the output of this new routine through a partial structure-refinement program may have the potential to completely automate the fitting of electron-density maps.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

Energy Technology Data Exchange (ETDEWEB)

Lee, Woonghee, E-mail: whlee@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States); Petit, Chad M. [University of Alabama at Birmingham, Department of Biochemistry and Molecular Genetics (United States); Cornilescu, Gabriel; Stark, Jaime L.; Markley, John L., E-mail: markley@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States)

2016-06-15

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27–98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

International Nuclear Information System (INIS)

Lee, Woonghee; Petit, Chad M.; Cornilescu, Gabriel; Stark, Jaime L.; Markley, John L.

2016-01-01

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27–98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

Automated 3D-Printed Unibody Immunoarray for Chemiluminescence Detection of Cancer Biomarker Proteins

Science.gov (United States)

Tang, C. K.; Vaze, A.; Rusling, J. F.

2017-01-01

A low cost three-dimensional (3D) printed clear plastic microfluidic device was fabricated for fast, low cost automated protein detection. The unibody device features three reagent reservoirs, an efficient 3D network for passive mixing, and an optically transparent detection chamber housing a glass capture antibody array for measuring chemiluminescence output with a CCD camera. Sandwich type assays were built onto the glass arrays using a multi-labeled detection antibody-polyHRP (HRP = horseradish peroxidase). Total assay time was ~30 min in a complete automated assay employing a programmable syringe pump so that the protocol required minimal operator intervention. The device was used for multiplexed detection of prostate cancer biomarker proteins prostate specific antigen (PSA) and platelet factor 4 (PF-4). Detection limits of 0.5 pg mL−1 were achieved for these proteins in diluted serum with log dynamic ranges of four orders of magnitude. Good accuracy vs ELISA was validated by analyzing human serum samples. This prototype device holds good promise for further development as a point-of-care cancer diagnostics tool. PMID:28067370

PONDEROSA, an automated 3D-NOESY peak picking program, enables automated protein structure determination.

Science.gov (United States)

Lee, Woonghee; Kim, Jin Hae; Westler, William M; Markley, John L

2011-06-15

PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY ((13)C-edited and/or (15)N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means. The program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/.

PASA - A Program for Automated Protein NMR Backbone Signal Assignment by Pattern-Filtering Approach

International Nuclear Information System (INIS)

Xu Yizhuang; Wang Xiaoxia; Yang Jun; Vaynberg, Julia; Qin Jun

2006-01-01

We present a new program, PASA (Program for Automated Sequential Assignment), for assigning protein backbone resonances based on multidimensional heteronuclear NMR data. Distinct from existing programs, PASA emphasizes a per-residue-based pattern-filtering approach during the initial stage of the automated 13 C α and/or 13 C β chemical shift matching. The pattern filter employs one or multiple constraints such as 13 C α /C β chemical shift ranges for different amino acid types and side-chain spin systems, which helps to rule out, in a stepwise fashion, improbable assignments as resulted from resonance degeneracy or missing signals. Such stepwise filtering approach substantially minimizes early false linkage problems that often propagate, amplify, and ultimately cause complication or combinatorial explosion of the automation process. Our program (http://www.lerner.ccf.org/moleccard/qin/) was tested on four representative small-large sized proteins with various degrees of resonance degeneracy and missing signals, and we show that PASA achieved the assignments efficiently and rapidly that are fully consistent with those obtained by laborious manual protocols. The results demonstrate that PASA may be a valuable tool for NMR-based structural analyses, genomics, and proteomics

Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

Directory of Open Access Journals (Sweden)

Stovgaard Kasper

2010-08-01

Full Text Available Abstract Background Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference. Results We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids the computationally costly iteration over all atoms. We estimated the form factors using generated data from a set of high quality protein structures. No ad hoc scaling or correction factors are applied in the calculation of the curves. Two coarse-grained representations of protein structure were investigated; two scattering bodies per amino acid led to significantly better results than a single scattering body. Conclusion We show that the obtained point estimates allow the calculation of accurate SAXS curves from coarse-grained protein models. The resulting curves are on par with the current state-of-the-art program CRYSOL, which requires full atomic detail. Our method was also comparable to CRYSOL in recognizing native structures among native-like decoys. As a proof-of-concept, we combined the coarse-grained Debye calculation with a previously described probabilistic model of protein structure, TorusDBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for

Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification

Science.gov (United States)

Murphy, Patrick J. M.; Stone, Orrin J.; Anderson, Michelle E.

2011-01-01

In contrast to other chromatographic methods for purifying proteins (e.g. gel filtration, affinity, and ion exchange), hydrophobic interaction chromatography (HIC) commonly requires experimental determination (referred to as screening or "scouting") in order to select the most suitable chromatographic medium for purifying a given protein 1. The method presented here describes an automated approach to scouting for an optimal HIC media to be used in protein purification. HIC separates proteins and other biomolecules from a crude lysate based on differences in hydrophobicity. Similar to affinity chromatography (AC) and ion exchange chromatography (IEX), HIC is capable of concentrating the protein of interest as it progresses through the chromatographic process. Proteins best suited for purification by HIC include those with hydrophobic surface regions and able to withstand exposure to salt concentrations in excess of 2 M ammonium sulfate ((NH4)2SO4). HIC is often chosen as a purification method for proteins lacking an affinity tag, and thus unsuitable for AC, and when IEX fails to provide adequate purification. Hydrophobic moieties on the protein surface temporarily bind to a nonpolar ligand coupled to an inert, immobile matrix. The interaction between protein and ligand are highly dependent on the salt concentration of the buffer flowing through the chromatography column, with high ionic concentrations strengthening the protein-ligand interaction and making the protein immobile (i.e. bound inside the column) 2. As salt concentrations decrease, the protein-ligand interaction dissipates, the protein again becomes mobile and elutes from the column. Several HIC media are commercially available in pre-packed columns, each containing one of several hydrophobic ligands (e.g. S-butyl, butyl, octyl, and phenyl) cross-linked at varying densities to agarose beads of a specific diameter 3. Automated column scouting allows for an efficient approach for determining which HIC media

Robotic liquid handling and automation in epigenetics.

Science.gov (United States)

Gaisford, Wendy

2012-10-01

Automated liquid-handling robots and high-throughput screening (HTS) are widely used in the pharmaceutical industry for the screening of large compound libraries, small molecules for activity against disease-relevant target pathways, or proteins. HTS robots capable of low-volume dispensing reduce assay setup times and provide highly accurate and reproducible dispensing, minimizing variation between sample replicates and eliminating the potential for manual error. Low-volume automated nanoliter dispensers ensure accuracy of pipetting within volume ranges that are difficult to achieve manually. In addition, they have the ability to potentially expand the range of screening conditions from often limited amounts of valuable sample, as well as reduce the usage of expensive reagents. The ability to accurately dispense lower volumes provides the potential to achieve a greater amount of information than could be otherwise achieved using manual dispensing technology. With the emergence of the field of epigenetics, an increasing number of drug discovery companies are beginning to screen compound libraries against a range of epigenetic targets. This review discusses the potential for the use of low-volume liquid handling robots, for molecular biological applications such as quantitative PCR and epigenetics.

Improved protein hydrogen/deuterium exchange mass spectrometry platform with fully automated data processing.

Science.gov (United States)

Zhang, Zhongqi; Zhang, Aming; Xiao, Gang

2012-06-05

Protein hydrogen/deuterium exchange (HDX) followed by protease digestion and mass spectrometric (MS) analysis is accepted as a standard method for studying protein conformation and conformational dynamics. In this article, an improved HDX MS platform with fully automated data processing is described. The platform significantly reduces systematic and random errors in the measurement by introducing two types of corrections in HDX data analysis. First, a mixture of short peptides with fast HDX rates is introduced as internal standards to adjust the variations in the extent of back exchange from run to run. Second, a designed unique peptide (PPPI) with slow intrinsic HDX rate is employed as another internal standard to reflect the possible differences in protein intrinsic HDX rates when protein conformations at different solution conditions are compared. HDX data processing is achieved with a comprehensive HDX model to simulate the deuterium labeling and back exchange process. The HDX model is implemented into the in-house developed software MassAnalyzer and enables fully unattended analysis of the entire protein HDX MS data set starting from ion detection and peptide identification to final processed HDX output, typically within 1 day. The final output of the automated data processing is a set (or the average) of the most possible protection factors for each backbone amide hydrogen. The utility of the HDX MS platform is demonstrated by exploring the conformational transition of a monoclonal antibody by increasing concentrations of guanidine.

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

An automated A-value measurement tool for accurate cochlear duct length estimation.

Science.gov (United States)

Iyaniwura, John E; Elfarnawany, Mai; Ladak, Hanif M; Agrawal, Sumit K

2018-01-22

There has been renewed interest in the cochlear duct length (CDL) for preoperative cochlear implant electrode selection and postoperative generation of patient-specific frequency maps. The CDL can be estimated by measuring the A-value, which is defined as the length between the round window and the furthest point on the basal turn. Unfortunately, there is significant intra- and inter-observer variability when these measurements are made clinically. The objective of this study was to develop an automated A-value measurement algorithm to improve accuracy and eliminate observer variability. Clinical and micro-CT images of 20 cadaveric cochleae specimens were acquired. The micro-CT of one sample was chosen as the atlas, and A-value fiducials were placed onto that image. Image registration (rigid affine and non-rigid B-spline) was applied between the atlas and the 19 remaining clinical CT images. The registration transform was applied to the A-value fiducials, and the A-value was then automatically calculated for each specimen. High resolution micro-CT images of the same 19 specimens were used to measure the gold standard A-values for comparison against the manual and automated methods. The registration algorithm had excellent qualitative overlap between the atlas and target images. The automated method eliminated the observer variability and the systematic underestimation by experts. Manual measurement of the A-value on clinical CT had a mean error of 9.5 ± 4.3% compared to micro-CT, and this improved to an error of 2.7 ± 2.1% using the automated algorithm. Both the automated and manual methods correlated significantly with the gold standard micro-CT A-values (r = 0.70, p value measurement tool using atlas-based registration methods was successfully developed and validated. The automated method eliminated the observer variability and improved accuracy as compared to manual measurements by experts. This open-source tool has the potential to benefit

Automation systems for radioimmunoassay

International Nuclear Information System (INIS)

Yamasaki, Paul

1974-01-01

The application of automation systems for radioimmunoassay (RIA) was discussed. Automated systems could be useful in the second step, of the four basic processes in the course of RIA, i.e., preparation of sample for reaction. There were two types of instrumentation, a semi-automatic pipete, and a fully automated pipete station, both providing for fast and accurate dispensing of the reagent or for the diluting of sample with reagent. Illustrations of the instruments were shown. (Mukohata, S.)

Complacency and Automation Bias in the Use of Imperfect Automation.

Science.gov (United States)

Wickens, Christopher D; Clegg, Benjamin A; Vieane, Alex Z; Sebok, Angelia L

2015-08-01

We examine the effects of two different kinds of decision-aiding automation errors on human-automation interaction (HAI), occurring at the first failure following repeated exposure to correctly functioning automation. The two errors are incorrect advice, triggering the automation bias, and missing advice, reflecting complacency. Contrasts between analogous automation errors in alerting systems, rather than decision aiding, have revealed that alerting false alarms are more problematic to HAI than alerting misses are. Prior research in decision aiding, although contrasting the two aiding errors (incorrect vs. missing), has confounded error expectancy. Participants performed an environmental process control simulation with and without decision aiding. For those with the aid, automation dependence was created through several trials of perfect aiding performance, and an unexpected automation error was then imposed in which automation was either gone (one group) or wrong (a second group). A control group received no automation support. The correct aid supported faster and more accurate diagnosis and lower workload. The aid failure degraded all three variables, but "automation wrong" had a much greater effect on accuracy, reflecting the automation bias, than did "automation gone," reflecting the impact of complacency. Some complacency was manifested for automation gone, by a longer latency and more modest reduction in accuracy. Automation wrong, creating the automation bias, appears to be a more problematic form of automation error than automation gone, reflecting complacency. Decision-aiding automation should indicate its lower degree of confidence in uncertain environments to avoid the automation bias. © 2015, Human Factors and Ergonomics Society.

Automated protein identification by the combination of MALDI MS and MS/MS spectra from different instruments.

Science.gov (United States)

Levander, Fredrik; James, Peter

2005-01-01

The identification of proteins separated on two-dimensional gels is most commonly performed by trypsin digestion and subsequent matrix-assisted laser desorption ionization (MALDI) with time-of-flight (TOF). Recently, atmospheric pressure (AP) MALDI coupled to an ion trap (IT) has emerged as a convenient method to obtain tandem mass spectra (MS/MS) from samples on MALDI target plates. In the present work, we investigated the feasibility of using the two methodologies in line as a standard method for protein identification. In this setup, the high mass accuracy MALDI-TOF spectra are used to calibrate the peptide precursor masses in the lower mass accuracy AP-MALDI-IT MS/MS spectra. Several software tools were developed to automate the analysis process. Two sets of MALDI samples, consisting of 142 and 421 gel spots, respectively, were analyzed in a highly automated manner. In the first set, the protein identification rate increased from 61% for MALDI-TOF only to 85% for MALDI-TOF combined with AP-MALDI-IT. In the second data set the increase in protein identification rate was from 44% to 58%. AP-MALDI-IT MS/MS spectra were in general less effective than the MALDI-TOF spectra for protein identification, but the combination of the two methods clearly enhanced the confidence in protein identification.

Active learning of neuron morphology for accurate automated tracing of neurites

Science.gov (United States)

Gala, Rohan; Chapeton, Julio; Jitesh, Jayant; Bhavsar, Chintan; Stepanyants, Armen

2014-01-01

Automating the process of neurite tracing from light microscopy stacks of images is essential for large-scale or high-throughput quantitative studies of neural circuits. While the general layout of labeled neurites can be captured by many automated tracing algorithms, it is often not possible to differentiate reliably between the processes belonging to different cells. The reason is that some neurites in the stack may appear broken due to imperfect labeling, while others may appear fused due to the limited resolution of optical microscopy. Trained neuroanatomists routinely resolve such topological ambiguities during manual tracing tasks by combining information about distances between branches, branch orientations, intensities, calibers, tortuosities, colors, as well as the presence of spines or boutons. Likewise, to evaluate different topological scenarios automatically, we developed a machine learning approach that combines many of the above mentioned features. A specifically designed confidence measure was used to actively train the algorithm during user-assisted tracing procedure. Active learning significantly reduces the training time and makes it possible to obtain less than 1% generalization error rates by providing few training examples. To evaluate the overall performance of the algorithm a number of image stacks were reconstructed automatically, as well as manually by several trained users, making it possible to compare the automated traces to the baseline inter-user variability. Several geometrical and topological features of the traces were selected for the comparisons. These features include the total trace length, the total numbers of branch and terminal points, the affinity of corresponding traces, and the distances between corresponding branch and terminal points. Our results show that when the density of labeled neurites is sufficiently low, automated traces are not significantly different from manual reconstructions obtained by trained users. PMID

Active learning of neuron morphology for accurate automated tracing of neurites

Directory of Open Access Journals (Sweden)

Rohan eGala

2014-05-01

Full Text Available Automating the process of neurite tracing from light microscopy stacks of images is essential for large-scale or high-throughput quantitative studies of neural circuits. While the general layout of labeled neurites can be captured by many automated tracing algorithms, it is often not possible to differentiate reliably between the processes belonging to different cells. The reason is that some neurites in the stack may appear broken due to imperfect labeling, while others may appear fused due to the limited resolution of optical microscopy. Trained neuroanatomists routinely resolve such topological ambiguities during manual tracing tasks by combining information about distances between branches, branch orientations, intensities, calibers, tortuosities, colors, as well as the presence of spines or boutons. Likewise, to evaluate different topological scenarios automatically, we developed a machine learning approach that combines many of the above mentioned features. A specifically designed confidence measure was used to actively train the algorithm during user-assisted tracing procedure. Active learning significantly reduces the training time and makes it possible to obtain less than 1% generalization error rates by providing few training examples. To evaluate the overall performance of the algorithm a number of image stacks were reconstructed automatically, as well as manually by several trained users, making it possible to compare the automated traces to the baseline inter-user variability. Several geometrical and topological features of the traces were selected for the comparisons. These features include the total trace length, the total numbers of branch and terminal points, the affinity of corresponding traces, and the distances between corresponding branch and terminal points. Our results show that when the density of labeled neurites is sufficiently low, automated traces are not significantly different from manual reconstructions obtained by

Full automation and validation of a flexible ELISA platform for host cell protein and protein A impurity detection in biopharmaceuticals.

Science.gov (United States)

Rey, Guillaume; Wendeler, Markus W

2012-11-01

Monitoring host cell protein (HCP) and protein A impurities is important to ensure successful development of recombinant antibody drugs. Here, we report the full automation and validation of an ELISA platform on a robotic system that allows the detection of Chinese hamster ovary (CHO) HCPs and residual protein A of in-process control samples and final drug substance. The ELISA setup is designed to serve three main goals: high sample throughput, high quality of results, and sample handling flexibility. The processing of analysis requests, determination of optimal sample dilutions, and calculation of impurity content is performed automatically by a spreadsheet. Up to 48 samples in three unspiked and spiked dilutions each are processed within 24 h. The dilution of each sample is individually prepared based on the drug concentration and the expected impurity content. Adaptable dilution protocols allow the analysis of sample dilutions ranging from 1:2 to 1:2×10(7). The validity of results is assessed by automatic testing for dilutional linearity and spike recovery for each sample. This automated impurity ELISA facilitates multi-project process development, is easily adaptable to other impurity ELISA formats, and increases analytical capacity by combining flexible sample handling with high data quality. Copyright © 2012 Elsevier B.V. All rights reserved.

FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

J. Wohlfeil

2012-07-01

Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.

Fast and accurate protein substructure searching with simulated annealing and GPUs

Directory of Open Access Journals (Sweden)

Stivala Alex D

2010-09-01

Full Text Available Abstract Background Searching a database of protein structures for matches to a query structure, or occurrences of a structural motif, is an important task in structural biology and bioinformatics. While there are many existing methods for structural similarity searching, faster and more accurate approaches are still required, and few current methods are capable of substructure (motif searching. Results We developed an improved heuristic for tableau-based protein structure and substructure searching using simulated annealing, that is as fast or faster and comparable in accuracy, with some widely used existing methods. Furthermore, we created a parallel implementation on a modern graphics processing unit (GPU. Conclusions The GPU implementation achieves up to 34 times speedup over the CPU implementation of tableau-based structure search with simulated annealing, making it one of the fastest available methods. To the best of our knowledge, this is the first application of a GPU to the protein structural search problem.

The Buccaneer software for automated model building. 1. Tracing protein chains.

Science.gov (United States)

Cowtan, Kevin

2006-09-01

A new technique for the automated tracing of protein chains in experimental electron-density maps is described. The technique relies on the repeated application of an oriented electron-density likelihood target function to identify likely C(alpha) positions. This function is applied both in the location of a few promising ;seed' positions in the map and to grow those initial C(alpha) positions into extended chain fragments. Techniques for assembling the chain fragments into an initial chain trace are discussed.

Contaminant analysis automation, an overview

International Nuclear Information System (INIS)

Hollen, R.; Ramos, O. Jr.

1996-01-01

To meet the environmental restoration and waste minimization goals of government and industry, several government laboratories, universities, and private companies have formed the Contaminant Analysis Automation (CAA) team. The goal of this consortium is to design and fabricate robotics systems that standardize and automate the hardware and software of the most common environmental chemical methods. In essence, the CAA team takes conventional, regulatory- approved (EPA Methods) chemical analysis processes and automates them. The automation consists of standard laboratory modules (SLMs) that perform the work in a much more efficient, accurate, and cost- effective manner

Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling

DEFF Research Database (Denmark)

Simonsen, Martin; Maetschke, S.R.; Ragan, M.A.

2012-01-01

Motivation: Phylogenetic profiling methods can achieve good accuracy in predicting protein–protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa (RT) is critical for accurate prediction, but with more than 2500 fully sequenced taxa publicly......: We present three novel methods for automating the selection of RT, using machine learning based on known protein–protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting...... phylogenetic profiles often require very different RT sets to support high prediction accuracy....

CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

Directory of Open Access Journals (Sweden)

Li Gong-Hua

2010-08-01

Full Text Available Abstract Background The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB, thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm, has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods. Results The evaluation of CMASA shows that the CMASA is highly accurate (0.96, sensitive (0.86, and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function and SPASM (a local structure alignment method; and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods. The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA. Conclusions The CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the

A geometrical approach for semi-automated crystal centering and in situ X-ray diffraction data collection

International Nuclear Information System (INIS)

Mohammad Yaser Heidari Khajepour; Ferrer, Jean-Luc; Lebrette, Hugo; Vernede, Xavier; Rogues, Pierrick

2013-01-01

High-throughput protein crystallography projects pushed forward the development of automated crystallization platforms that are now commonly used. This created an urgent need for adapted and automated equipment for crystal analysis. However, first these crystals have to be harvested, cryo-protected and flash-cooled, operations that can fail or negatively impact on the crystal. In situ X-ray diffraction analysis has become a valid alternative to these operations, and a growing number of users apply it for crystal screening and to solve structures. Nevertheless, even this shortcut may require a significant amount of beam time. In this in situ high-throughput approach, the centering of crystals relative to the beam represents the bottleneck in the analysis process. In this article, a new method to accelerate this process, by recording accurately the local geometry coordinates for each crystal in the crystallization plate, is presented. Subsequently, the crystallization plate can be presented to the X-ray beam by an automated plate-handling device, such as a six-axis robot arm, for an automated crystal centering in the beam, in situ screening or data collection. Here the preliminary results of such a semi-automated pipeline are reported for two distinct test proteins. (authors)

HIPPI: highly accurate protein family classification with ensembles of HMMs

Directory of Open Access Journals (Sweden)

Nam-phuong Nguyen

2016-11-01

Full Text Available Abstract Background Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. Results We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification. HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. Conclusion HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Automation of C-terminal sequence analysis of 2D-PAGE separated proteins

Directory of Open Access Journals (Sweden)

P.P. Moerman

2014-06-01

Full Text Available Experimental assignment of the protein termini remains essential to define the functional protein structure. Here, we report on the improvement of a proteomic C-terminal sequence analysis method. The approach aims to discriminate the C-terminal peptide in a CNBr-digest where Met-Xxx peptide bonds are cleaved in internal peptides ending at a homoserine lactone (hsl-derivative. pH-dependent partial opening of the lactone ring results in the formation of doublets for all internal peptides. C-terminal peptides are distinguished as singlet peaks by MALDI-TOF MS and MS/MS is then used for their identification. We present a fully automated protocol established on a robotic liquid-handling station.

RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database.

Science.gov (United States)

Field, Helen I; Fenyö, David; Beavis, Ronald C

2002-01-01

RADARS, a rapid, automated, data archiving and retrieval software system for high-throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close-to-expert accuracy and brings robust data analysis to the non-expert user.

Validation of commercially available automated canine-specific immunoturbidimetric method for measuring canine C-reactive protein

DEFF Research Database (Denmark)

Hillström, Anna; Hagman, Ragnvi; Tvedten, Harold

2014-01-01

BACKGROUND: Measurement of C-reactive protein (CRP) is used for diagnosing and monitoring systemic inflammatory disease in canine patients. An automated human immunoturbidimetric assay has been validated for measuring canine CRP, but cross-reactivity with canine CRP is unpredictable. OBJECTIVE......: The purpose of the study was to validate a new automated canine-specific immunoturbidimetric CRP method (Gentian cCRP). METHODS: Studies of imprecision, accuracy, prozone effect, interference, limit of quantification, and stability under different storage conditions were performed. The new method was compared...... with a human CRP assay previously validated for canine CRP determination. Samples from 40 healthy dogs were analyzed to establish a reference interval. RESULTS: Total imprecision was

Automating tasks in protein structure determination with the clipper python module.

Science.gov (United States)

McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M; Hoh, Soon Wen; Jenkins, Huw T; Dodson, Eleanor; Cowtan, Kevin; Agirre, Jon

2018-01-01

Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine-independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo-microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Laser guided automated calibrating system for accurate bracket ...

African Journals Online (AJOL)

It is widely recognized that accurate bracket placement is of critical importance in the efficient application of biomechanics and in realizing the full potential of a preadjusted edgewise appliance. Aim: The purpose of ... placement. Keywords: Hough transforms, Indirect bonding technique, Laser, Orthodontic bracket placement ...

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

International Nuclear Information System (INIS)

Thompson, A.P.; Swiler, L.P.; Trott, C.R.; Foiles, S.M.; Tucker, G.J.

2015-01-01

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

Energy Technology Data Exchange (ETDEWEB)

Thompson, Aidan P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Multiscale Science Dept.; Swiler, Laura P. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Optimization and Uncertainty Quantification Dept.; Trott, Christian R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Scalable Algorithms Dept.; Foiles, Stephen M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science Dept.; Tucker, Garritt J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science Dept.; Drexel Univ., Philadelphia, PA (United States). Dept. of Materials Science and Engineering

2015-03-15

Here, we present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

Energy Technology Data Exchange (ETDEWEB)

Thompson, A.P., E-mail: athomps@sandia.gov [Multiscale Science Department, Sandia National Laboratories, PO Box 5800, MS 1322, Albuquerque, NM 87185 (United States); Swiler, L.P., E-mail: lpswile@sandia.gov [Optimization and Uncertainty Quantification Department, Sandia National Laboratories, PO Box 5800, MS 1318, Albuquerque, NM 87185 (United States); Trott, C.R., E-mail: crtrott@sandia.gov [Scalable Algorithms Department, Sandia National Laboratories, PO Box 5800, MS 1322, Albuquerque, NM 87185 (United States); Foiles, S.M., E-mail: foiles@sandia.gov [Computational Materials and Data Science Department, Sandia National Laboratories, PO Box 5800, MS 1411, Albuquerque, NM 87185 (United States); Tucker, G.J., E-mail: gtucker@coe.drexel.edu [Computational Materials and Data Science Department, Sandia National Laboratories, PO Box 5800, MS 1411, Albuquerque, NM 87185 (United States); Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104 (United States)

2015-03-15

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

Devices used by automated milking systems are similarly accurate in estimating milk yield and in collecting a representative milk sample compared with devices used by farms with conventional milk recording

NARCIS (Netherlands)

Kamphuis, Claudia; Dela Rue, B.; Turner, S.A.; Petch, S.

2015-01-01

Information on accuracy of milk-sampling devices used on farms with automated milking systems (AMS) is essential for development of milk recording protocols. The hypotheses of this study were (1) devices used by AMS units are similarly accurate in estimating milk yield and in collecting

A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

Science.gov (United States)

Ross, James D.; Cullen, D. Kacy; Harris, James P.; LaPlaca, Michelle C.; DeWeerth, Stephen P.

2015-01-01

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions. PMID

PINE-SPARKY.2 for automated NMR-based protein structure research.

Science.gov (United States)

Lee, Woonghee; Markley, John L

2018-05-01

Nuclear magnetic resonance (NMR) spectroscopy, along with X-ray crystallography and cryoelectron microscopy, is one of the three major tools that enable the determination of atomic-level structural models of biological macromolecules. Of these, NMR has the unique ability to follow important processes in solution, including conformational changes, internal dynamics and protein-ligand interactions. As a means for facilitating the handling and analysis of spectra involved in these types of NMR studies, we have developed PINE-SPARKY.2, a software package that integrates and automates discrete tasks that previously required interaction with separate software packages. The graphical user interface of PINE-SPARKY.2 simplifies chemical shift assignment and verification, automated detection of secondary structural elements, predictions of flexibility and hydrophobic cores, and calculation of three-dimensional structural models. PINE-SPARKY.2 is available in the latest version of NMRFAM-SPARKY from the National Magnetic Resonance Facility at Madison (http://pine.nmrfam.wisc.edu/download_packages.html), the NMRbox Project (https://nmrbox.org) and to subscribers to the SBGrid (https://sbgrid.org). For a detailed description of the program, see http://www.nmrfam.wisc.edu/pine-sparky2.htm. whlee@nmrfam.wisc.edu or markley@nmrfam.wisc.edu. Supplementary data are available at Bioinformatics online.

Assay of mouse-cell clones for retrovirus p30 protein by use of an automated solid-state radioimmunoassay

International Nuclear Information System (INIS)

Kennel, S.J.; Tnnant, R.W.

1979-01-01

A solid-state radioimmunoassay system has been developed that is useful for automated analysis of samples in microtiter plates. Assays for interspecies and type-specific antigenic determinants of the C-type retrovirus protein, p30, have been used to identify clones of cells producing this protein. This method allows testing of at least 1000 clones a day, making it useful for studies of frequencies of virus protein induction, defective virus production, and formation of recombinant viruses

MIEC-SVM: automated pipeline for protein peptide/ligand interaction prediction.

Science.gov (United States)

Li, Nan; Ainsworth, Richard I; Wu, Meixin; Ding, Bo; Wang, Wei

2016-03-15

MIEC-SVM is a structure-based method for predicting protein recognition specificity. Here, we present an automated MIEC-SVM pipeline providing an integrated and user-friendly workflow for construction and application of the MIEC-SVM models. This pipeline can handle standard amino acids and those with post-translational modifications (PTMs) or small molecules. Moreover, multi-threading and support to Sun Grid Engine (SGE) are implemented to significantly boost the computational efficiency. The program is available at http://wanglab.ucsd.edu/MIEC-SVM CONTACT: : wei-wang@ucsd.edu Supplementary data available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Laser Guided Automated Calibrating System for Accurate Bracket ...

African Journals Online (AJOL)

Background: The basic premise of preadjusted bracket system is accurate bracket positioning. ... using MATLAB ver. 7 software (The MathWorks Inc.). These images are in the form of matrices of size 640 × 480. 650 nm (red light) type III diode laser is used as ... motion control and Pitch, Yaw, Roll degrees of freedom (DOF).

Automated measurement of serum thyroxine with the ''AIRA II,'' as compared with competitive protein binding and radioimmunoassay

International Nuclear Information System (INIS)

Reese, M.G.; Johnson, L.V.R.

1978-01-01

Two conventional serum thyroxine assays, run in separate laboratories, one by competitive protein binding and one by radioimmunoassay, were used to evaluate the automated ARIA II (Becton Dickinson Immunodiagnostics) serum thyroxine assay. Competitive protein binding as compared to ARIA II with 111 clinical serum samples gave a slope of 1.04 and a correlation coefficient of 0.94. The radioimmunoassay comparison to ARIA II with 53 clinical serum samples gave a slope of 1.05 and a correlation coefficient of 0.92. The ARIA II inter-assay coefficient of variation for 10 replicates of low, medium, and high thyroxine serum samples was 6.2, 6.0, and 2.9%, respectively, with an inter-assay coefficient of variation among 15 different assays of 15.5, 10.1, and 7.9%. The automated ARIA II, with a 2.2-min cycle per sample, gives results that compare well with those by manual methodology

Automated Analysis of Protein Expression and Gene Amplification within the Same Cells of Paraffin-Embedded Tumour Tissue

Directory of Open Access Journals (Sweden)

Timo Gaiser

2010-01-01

Full Text Available Background: The simultaneous detection of protein expression and gene copy number changes in patient samples, like paraffin-embedded tissue sections, is challenging since the procedures of immunohistochemistry (IHC and Fluorescence in situ Hybridization (FISH negatively influence each other which often results in suboptimal staining. Therefore, we developed a novel automated algorithm based on relocation which allows subsequent detection of protein content and gene copy number changes within the same cell.

Fast and accurate semi-automated segmentation method of spinal cord MR images at 3T applied to the construction of a cervical spinal cord template.

Directory of Open Access Journals (Sweden)

Mohamed-Mounir El Mendili

Full Text Available To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord.A semi-automated double threshold-based method (DTbM was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM, threshold-based method (TbM and manual outlining (ground truth. Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59, a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map.Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction.A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

Fast and accurate semi-automated segmentation method of spinal cord MR images at 3T applied to the construction of a cervical spinal cord template.

Science.gov (United States)

El Mendili, Mohamed-Mounir; Chen, Raphaël; Tiret, Brice; Villard, Noémie; Trunet, Stéphanie; Pélégrini-Issac, Mélanie; Lehéricy, Stéphane; Pradat, Pierre-François; Benali, Habib

2015-01-01

To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord. A semi-automated double threshold-based method (DTbM) was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM), threshold-based method (TbM) and manual outlining (ground truth). Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59), a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map. Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC) was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction. A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

Rapid and accurate prediction and scoring of water molecules in protein binding sites.

Directory of Open Access Journals (Sweden)

Gregory A Ross

Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

PONDEROSA-C/S: client-server based software package for automated protein 3D structure determination.

Science.gov (United States)

Lee, Woonghee; Stark, Jaime L; Markley, John L

2014-11-01

Peak-picking Of Noe Data Enabled by Restriction Of Shift Assignments-Client Server (PONDEROSA-C/S) builds on the original PONDEROSA software (Lee et al. in Bioinformatics 27:1727-1728. doi: 10.1093/bioinformatics/btr200, 2011) and includes improved features for structure calculation and refinement. PONDEROSA-C/S consists of three programs: Ponderosa Server, Ponderosa Client, and Ponderosa Analyzer. PONDEROSA-C/S takes as input the protein sequence, a list of assigned chemical shifts, and nuclear Overhauser data sets ((13)C- and/or (15)N-NOESY). The output is a set of assigned NOEs and 3D structural models for the protein. Ponderosa Analyzer supports the visualization, validation, and refinement of the results from Ponderosa Server. These tools enable semi-automated NMR-based structure determination of proteins in a rapid and robust fashion. We present examples showing the use of PONDEROSA-C/S in solving structures of four proteins: two that enable comparison with the original PONDEROSA package, and two from the Critical Assessment of automated Structure Determination by NMR (Rosato et al. in Nat Methods 6:625-626. doi: 10.1038/nmeth0909-625 , 2009) competition. The software package can be downloaded freely in binary format from http://pine.nmrfam.wisc.edu/download_packages.html. Registered users of the National Magnetic Resonance Facility at Madison can submit jobs to the PONDEROSA-C/S server at http://ponderosa.nmrfam.wisc.edu, where instructions, tutorials, and instructions can be found. Structures are normally returned within 1-2 days.

A scalable and accurate method for classifying protein-ligand binding geometries using a MapReduce approach.

Science.gov (United States)

Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M

2012-07-01

We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Automated microfluidic sample-preparation platform for high-throughput structural investigation of proteins by small-angle X-ray scattering

DEFF Research Database (Denmark)

Lafleur, Josiane P.; Snakenborg, Detlef; Nielsen, Søren Skou

2011-01-01

A new microfluidic sample-preparation system is presented for the structural investigation of proteins using small-angle X-ray scattering (SAXS) at synchrotrons. The system includes hardware and software features for precise fluidic control, sample mixing by diffusion, automated X-ray exposure...... control, UV absorbance measurements and automated data analysis. As little as 15 l of sample is required to perform a complete analysis cycle, including sample mixing, SAXS measurement, continuous UV absorbance measurements, and cleaning of the channels and X-ray cell with buffer. The complete analysis...

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.

Automated de novo phasing and model building of coiled-coil proteins.

Science.gov (United States)

Rämisch, Sebastian; Lizatović, Robert; André, Ingemar

2015-03-01

Models generated by de novo structure prediction can be very useful starting points for molecular replacement for systems where suitable structural homologues cannot be readily identified. Protein-protein complexes and de novo-designed proteins are examples of systems that can be challenging to phase. In this study, the potential of de novo models of protein complexes for use as starting points for molecular replacement is investigated. The approach is demonstrated using homomeric coiled-coil proteins, which are excellent model systems for oligomeric systems. Despite the stereotypical fold of coiled coils, initial phase estimation can be difficult and many structures have to be solved with experimental phasing. A method was developed for automatic structure determination of homomeric coiled coils from X-ray diffraction data. In a benchmark set of 24 coiled coils, ranging from dimers to pentamers with resolutions down to 2.5 Å, 22 systems were automatically solved, 11 of which had previously been solved by experimental phasing. The generated models contained 71-103% of the residues present in the deposited structures, had the correct sequence and had free R values that deviated on average by 0.01 from those of the respective reference structures. The electron-density maps were of sufficient quality that only minor manual editing was necessary to produce final structures. The method, named CCsolve, combines methods for de novo structure prediction, initial phase estimation and automated model building into one pipeline. CCsolve is robust against errors in the initial models and can readily be modified to make use of alternative crystallographic software. The results demonstrate the feasibility of de novo phasing of protein-protein complexes, an approach that could also be employed for other small systems beyond coiled coils.

ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

International Nuclear Information System (INIS)

Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

2007-01-01

The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors

Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

OpenAIRE

Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

2016-01-01

C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1?3?mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammator...

The Stanford Automated Mounter: Enabling High-Throughput Protein Crystal Screening at SSRL

International Nuclear Information System (INIS)

Smith, C.A.; Cohen, A.E.

2009-01-01

The macromolecular crystallography experiment lends itself perfectly to high-throughput technologies. The initial steps including the expression, purification, and crystallization of protein crystals, along with some of the later steps involving data processing and structure determination have all been automated to the point where some of the last remaining bottlenecks in the process have been crystal mounting, crystal screening, and data collection. At the Stanford Synchrotron Radiation Laboratory, a National User Facility that provides extremely brilliant X-ray photon beams for use in materials science, environmental science, and structural biology research, the incorporation of advanced robotics has enabled crystals to be screened in a true high-throughput fashion, thus dramatically accelerating the final steps. Up to 288 frozen crystals can be mounted by the beamline robot (the Stanford Auto-Mounting System) and screened for diffraction quality in a matter of hours without intervention. The best quality crystals can then be remounted for the collection of complete X-ray diffraction data sets. Furthermore, the entire screening and data collection experiment can be controlled from the experimenter's home laboratory by means of advanced software tools that enable network-based control of the highly automated beamlines.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions.

Science.gov (United States)

Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

2015-07-07

Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

Directory of Open Access Journals (Sweden)

Xin Deng

2015-07-01

Full Text Available Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach.

Directory of Open Access Journals (Sweden)

Zhiheng Wang

Full Text Available The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database.The DisoMCS is available at http://cal.tongji.edu.cn/disorder/.

Improvement of an automated protein crystal exchange system PAM for high-throughput data collection

International Nuclear Information System (INIS)

Hiraki, Masahiko; Yamada, Yusuke; Chavas, Leonard M. G.; Wakatsuki, Soichi; Matsugaki, Naohiro

2013-01-01

A special liquid-nitrogen Dewar with double capacity for the sample-exchange robot has been created at AR-NE3A at the Photon Factory, allowing continuous fully automated data collection. In this work, this new system is described and the stability of its calibration is discussed. Photon Factory Automated Mounting system (PAM) protein crystal exchange systems are available at the following Photon Factory macromolecular beamlines: BL-1A, BL-5A, BL-17A, AR-NW12A and AR-NE3A. The beamline AR-NE3A has been constructed for high-throughput macromolecular crystallography and is dedicated to structure-based drug design. The PAM liquid-nitrogen Dewar can store a maximum of three SSRL cassettes. Therefore, users have to interrupt their experiments and replace the cassettes when using four or more of them during their beam time. As a result of investigation, four or more cassettes were used in AR-NE3A alone. For continuous automated data collection, the size of the liquid-nitrogen Dewar for the AR-NE3A PAM was increased, doubling the capacity. In order to check the calibration with the new Dewar and the cassette stand, calibration experiments were repeatedly performed. Compared with the current system, the parameters of the novel system are shown to be stable

Improvement of an automated protein crystal exchange system PAM for high-throughput data collection

Energy Technology Data Exchange (ETDEWEB)

Hiraki, Masahiko, E-mail: masahiko.hiraki@kek.jp; Yamada, Yusuke; Chavas, Leonard M. G. [High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan); Wakatsuki, Soichi [High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan); SLAC National Accelerator Laboratory, 2575 Sand Hill Road, MS 69, Menlo Park, CA 94025-7015 (United States); Stanford University, Beckman Center B105, Stanford, CA 94305-5126 (United States); Matsugaki, Naohiro [High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan)

2013-11-01

A special liquid-nitrogen Dewar with double capacity for the sample-exchange robot has been created at AR-NE3A at the Photon Factory, allowing continuous fully automated data collection. In this work, this new system is described and the stability of its calibration is discussed. Photon Factory Automated Mounting system (PAM) protein crystal exchange systems are available at the following Photon Factory macromolecular beamlines: BL-1A, BL-5A, BL-17A, AR-NW12A and AR-NE3A. The beamline AR-NE3A has been constructed for high-throughput macromolecular crystallography and is dedicated to structure-based drug design. The PAM liquid-nitrogen Dewar can store a maximum of three SSRL cassettes. Therefore, users have to interrupt their experiments and replace the cassettes when using four or more of them during their beam time. As a result of investigation, four or more cassettes were used in AR-NE3A alone. For continuous automated data collection, the size of the liquid-nitrogen Dewar for the AR-NE3A PAM was increased, doubling the capacity. In order to check the calibration with the new Dewar and the cassette stand, calibration experiments were repeatedly performed. Compared with the current system, the parameters of the novel system are shown to be stable.

Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

DEFF Research Database (Denmark)

Stovgaard, Kasper; Andreetta, Christian; Ferkinghoff-Borg, Jesper

2010-01-01

, which is paramount for structure determination based on statistical inference. Results: We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids......DBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for use in statistical inference of protein structures from SAXS data....

Automated builder and database of protein/membrane complexes for molecular dynamics simulations.

Directory of Open Access Journals (Sweden)

Sunhwan Jo

2007-09-01

Full Text Available Molecular dynamics simulations of membrane proteins have provided deeper insights into their functions and interactions with surrounding environments at the atomic level. However, compared to solvation of globular proteins, building a realistic protein/membrane complex is still challenging and requires considerable experience with simulation software. Membrane Builder in the CHARMM-GUI website (http://www.charmm-gui.org helps users to build such a complex system using a web browser with a graphical user interface. Through a generalized and automated building process including system size determination as well as generation of lipid bilayer, pore water, bulk water, and ions, a realistic membrane system with virtually any kinds and shapes of membrane proteins can be generated in 5 minutes to 2 hours depending on the system size. Default values that were elaborated and tested extensively are given in each step to provide reasonable options and starting points for both non-expert and expert users. The efficacy of Membrane Builder is illustrated by its applications to 12 transmembrane and 3 interfacial membrane proteins, whose fully equilibrated systems with three different types of lipid molecules (DMPC, DPPC, and POPC and two types of system shapes (rectangular and hexagonal are freely available on the CHARMM-GUI website. One of the most significant advantages of using the web environment is that, if a problem is found, users can go back and re-generate the whole system again before quitting the browser. Therefore, Membrane Builder provides the intuitive and easy way to build and simulate the biologically important membrane system.

Development of a method for the accurate measurement of protein turnover in neoplastic cells grown in culture

International Nuclear Information System (INIS)

Silverman, J.A.

1984-01-01

In this study, it was shown that standard techniques for cell recovery and sample preparation for liquid scintillation counting led to underestimation of the radioactivity present in cell proteins by 20-40%. These techniques involved labeling with 3 He leucine or 14 C leucine, scraping the cells from the dish in a buffer, TCA precipitation of the cell proteins, solubilization in NaOH and counting in a liquid scintillation counter. Hydrolysis of the proteins with HCl or Pronase significantly increased the recovery of the labeled proteins. Also, solubilization in situ with NaOH or hydrolysis in situ with Pronase recovered 5-10% additional labeled proteins. The techniques developed here allow the accurate measurement of radioactivity in cell proteins. In addition, these techniques were used to study protein turnover in rat hepatoma cells grown in culture. These cells regulated their growth rate through changes in the protein synthesis rate as opposed to changes in the protein degradation rate. These data support the hypothesis that neoplastic cells, unlike normal cells, do not regulate proteolysis in growth control; normal cells under similar conditions have been shown to activate lysosomal proteolysis as they reach confluence. The physiologic implications of this observation are discussed

BRAIN initiative: transcranial magnetic stimulation automation and calibration.

Science.gov (United States)

Todd, Garth D; Abdellatif, Ahmed; Sabouni, Abas

2014-01-01

In this paper, we introduced an automated TMS system with robot control and optical sensor combined with neuronavigation software. By using the robot, the TMS coil can be accurately positioned over any preselected brain region. The neuronavigation system provides an accurate positioning of a magnetic coil in order to induce a specific cortical excitation. An infrared optical measurement device is also used in order to detect and compensate for head movements of the patient. This procedure was simulated using a PC based robotic simulation program. The proposed automated robot system is integrated with TMS numerical solver and allows users to actually see the depth, location, and shape of the induced eddy current on the computer monitor.

An automated blood sampling system used in positron emission tomography

International Nuclear Information System (INIS)

Eriksson, L.; Bohm, C.; Kesselberg, M.

1988-01-01

Fast dynamic function studies with positron emission tomography (PET), has the potential to give accurate information of physiological functions of the brain. This capability can be realised if the positron camera system accurately quantitates the tracer uptake in the brain with sufficiently high efficiency and in sufficiently short time intervals. However, in addition, the tracer concentration in blood, as a function of time, must be accurately determined. This paper describes and evaluates an automated blood sampling system. Two different detector units are compared. The use of the automated blood sampling system is demonstrated in studies of cerebral blood flow, in studies of the blood-brain barrier transfer of amino acids and of the cerebral oxygen consumption. 5 refs.; 7 figs

Accurate, fully-automated NMR spectral profiling for metabolomics.

Directory of Open Access Journals (Sweden)

Siamak Ravanbakhsh

Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

A Chip-Capillary Hybrid Device for Automated Transfer of Sample Pre-Separated by Capillary Isoelectric Focusing to Parallel Capillary Gel Electrophoresis for Two-Dimensional Protein Separation

Science.gov (United States)

Lu, Joann J.; Wang, Shili; Li, Guanbin; Wang, Wei; Pu, Qiaosheng; Liu, Shaorong

2012-01-01

In this report, we introduce a chip-capillary hybrid device to integrate capillary isoelectric focusing (CIEF) with parallel capillary sodium dodecyl sulfate – polyacrylamide gel electrophoresis (SDS-PAGE) or capillary gel electrophoresis (CGE) toward automating two-dimensional (2D) protein separations. The hybrid device consists of three chips that are butted together. The middle chip can be moved between two positions to re-route the fluidic paths, which enables the performance of CIEF and injection of proteins partially resolved by CIEF to CGE capillaries for parallel CGE separations in a continuous and automated fashion. Capillaries are attached to the other two chips to facilitate CIEF and CGE separations and to extend the effective lengths of CGE columns. Specifically, we illustrate the working principle of the hybrid device, develop protocols for producing and preparing the hybrid device, and demonstrate the feasibility of using this hybrid device for automated injection of CIEF-separated sample to parallel CGE for 2D protein separations. Potentials and problems associated with the hybrid device are also discussed. PMID:22830584

Accurate identification of ALK positive lung carcinoma patients: novel FDA-cleared automated fluorescence in situ hybridization scanning system and ultrasensitive immunohistochemistry.

Directory of Open Access Journals (Sweden)

Esther Conde

Full Text Available BACKGROUND: Based on the excellent results of the clinical trials with ALK-inhibitors, the importance of accurately identifying ALK positive lung cancer has never been greater. However, there are increasing number of recent publications addressing discordances between FISH and IHC. The controversy is further fuelled by the different regulatory approvals. This situation prompted us to investigate two ALK IHC antibodies (using a novel ultrasensitive detection-amplification kit and an automated ALK FISH scanning system (FDA-cleared in a series of non-small cell lung cancer tumor samples. METHODS: Forty-seven ALK FISH-positive and 56 ALK FISH-negative NSCLC samples were studied. All specimens were screened for ALK expression by two IHC antibodies (clone 5A4 from Novocastra and clone D5F3 from Ventana and for ALK rearrangement by FISH (Vysis ALK FISH break-apart kit, which was automatically captured and scored by using Bioview's automated scanning system. RESULTS: All positive cases with the IHC antibodies were FISH-positive. There was only one IHC-negative case with both antibodies which showed a FISH-positive result. The overall sensitivity and specificity of the IHC in comparison with FISH were 98% and 100%, respectively. CONCLUSIONS: The specificity of these ultrasensitive IHC assays may obviate the need for FISH confirmation in positive IHC cases. However, the likelihood of false negative IHC results strengthens the case for FISH testing, at least in some situations.

Monte Carlo shielding analyses using an automated biasing procedure

International Nuclear Information System (INIS)

Tang, J.S.; Hoffman, T.J.

1988-01-01

A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost

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.

Automated Feature Extraction from Hyperspectral Imagery, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The proposed activities will result in the development of a novel hyperspectral feature-extraction toolkit that will provide a simple, automated, and accurate...

Automated Image Analysis Corrosion Working Group Update: February 1, 2018

Energy Technology Data Exchange (ETDEWEB)

Wendelberger, James G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2018-02-01

These are slides for the automated image analysis corrosion working group update. The overall goals were: automate the detection and quantification of features in images (faster, more accurate), how to do this (obtain data, analyze data), focus on Laser Scanning Confocal Microscope (LCM) data (laser intensity, laser height/depth, optical RGB, optical plus laser RGB).

Electrostatics of proteins in dielectric solvent continua. I. An accurate and efficient reaction field description.

Science.gov (United States)

Bauer, Sebastian; Mathias, Gerald; Tavan, Paul

2014-03-14

We present a reaction field (RF) method which accurately solves the Poisson equation for proteins embedded in dielectric solvent continua at a computational effort comparable to that of an electrostatics calculation with polarizable molecular mechanics (MM) force fields. The method combines an approach originally suggested by Egwolf and Tavan [J. Chem. Phys. 118, 2039 (2003)] with concepts generalizing the Born solution [Z. Phys. 1, 45 (1920)] for a solvated ion. First, we derive an exact representation according to which the sources of the RF potential and energy are inducible atomic anti-polarization densities and atomic shielding charge distributions. Modeling these atomic densities by Gaussians leads to an approximate representation. Here, the strengths of the Gaussian shielding charge distributions are directly given in terms of the static partial charges as defined, e.g., by standard MM force fields for the various atom types, whereas the strengths of the Gaussian anti-polarization densities are calculated by a self-consistency iteration. The atomic volumes are also described by Gaussians. To account for covalently overlapping atoms, their effective volumes are calculated by another self-consistency procedure, which guarantees that the dielectric function ε(r) is close to one everywhere inside the protein. The Gaussian widths σ(i) of the atoms i are parameters of the RF approximation. The remarkable accuracy of the method is demonstrated by comparison with Kirkwood's analytical solution for a spherical protein [J. Chem. Phys. 2, 351 (1934)] and with computationally expensive grid-based numerical solutions for simple model systems in dielectric continua including a di-peptide (Ac-Ala-NHMe) as modeled by a standard MM force field. The latter example shows how weakly the RF conformational free energy landscape depends on the parameters σ(i). A summarizing discussion highlights the achievements of the new theory and of its approximate solution particularly by

Electrostatics of proteins in dielectric solvent continua. I. An accurate and efficient reaction field description

Energy Technology Data Exchange (ETDEWEB)

Bauer, Sebastian; Mathias, Gerald; Tavan, Paul, E-mail: paul.tavan@physik.uni-muenchen.de [Lehrstuhl für BioMolekulare Optik, Ludwig–Maximilians Universität München, Oettingenstr. 67, 80538 München (Germany)

2014-03-14

We present a reaction field (RF) method which accurately solves the Poisson equation for proteins embedded in dielectric solvent continua at a computational effort comparable to that of an electrostatics calculation with polarizable molecular mechanics (MM) force fields. The method combines an approach originally suggested by Egwolf and Tavan [J. Chem. Phys. 118, 2039 (2003)] with concepts generalizing the Born solution [Z. Phys. 1, 45 (1920)] for a solvated ion. First, we derive an exact representation according to which the sources of the RF potential and energy are inducible atomic anti-polarization densities and atomic shielding charge distributions. Modeling these atomic densities by Gaussians leads to an approximate representation. Here, the strengths of the Gaussian shielding charge distributions are directly given in terms of the static partial charges as defined, e.g., by standard MM force fields for the various atom types, whereas the strengths of the Gaussian anti-polarization densities are calculated by a self-consistency iteration. The atomic volumes are also described by Gaussians. To account for covalently overlapping atoms, their effective volumes are calculated by another self-consistency procedure, which guarantees that the dielectric function ε(r) is close to one everywhere inside the protein. The Gaussian widths σ{sub i} of the atoms i are parameters of the RF approximation. The remarkable accuracy of the method is demonstrated by comparison with Kirkwood's analytical solution for a spherical protein [J. Chem. Phys. 2, 351 (1934)] and with computationally expensive grid-based numerical solutions for simple model systems in dielectric continua including a di-peptide (Ac-Ala-NHMe) as modeled by a standard MM force field. The latter example shows how weakly the RF conformational free energy landscape depends on the parameters σ{sub i}. A summarizing discussion highlights the achievements of the new theory and of its approximate solution

Comparison of automated and manual shielding block fabrication

International Nuclear Information System (INIS)

Weeks, K.J.; Fraass, B.A.; McShan, D.L.; Hardybala, S.S.; Hargreaves, E.A.; Lichter, A.S.

1989-01-01

This work reports the results of a study comparing computer controlled and manual shielding block cutting. The general problems inherent in automated block cutting have been identified and minimized. A system whose accuracy is sufficient for clinical applications has been developed. The relative accuracy of our automated system versus experienced technician controlled cutting was investigated. In general, it is found that automated cutting is somewhat faster and more accurate than manual cutting for very large fields, but that the reverse is true for most smaller fields. The relative cost effectiveness of automated cutting is dependent on the percentage of computer designed blocks which are generated in the clinical setting. At the present time, the traditional manual method is still favored

Dried Blood Spot Proteomics: Surface Extraction of Endogenous Proteins Coupled with Automated Sample Preparation and Mass Spectrometry Analysis

Science.gov (United States)

Martin, Nicholas J.; Bunch, Josephine; Cooper, Helen J.

2013-08-01

Dried blood spots offer many advantages as a sample format including ease and safety of transport and handling. To date, the majority of mass spectrometry analyses of dried blood spots have focused on small molecules or hemoglobin. However, dried blood spots are a potentially rich source of protein biomarkers, an area that has been overlooked. To address this issue, we have applied an untargeted bottom-up proteomics approach to the analysis of dried blood spots. We present an automated and integrated method for extraction of endogenous proteins from the surface of dried blood spots and sample preparation via trypsin digestion by use of the Advion Biosciences Triversa Nanomate robotic platform. Liquid chromatography tandem mass spectrometry of the resulting digests enabled identification of 120 proteins from a single dried blood spot. The proteins identified cross a concentration range of four orders of magnitude. The method is evaluated and the results discussed in terms of the proteins identified and their potential use as biomarkers in screening programs.

I trust it, but I don't know why: effects of implicit attitudes toward automation on trust in an automated system.

Science.gov (United States)

Merritt, Stephanie M; Heimbaugh, Heather; LaChapell, Jennifer; Lee, Deborah

2013-06-01

This study is the first to examine the influence of implicit attitudes toward automation on users' trust in automation. Past empirical work has examined explicit (conscious) influences on user level of trust in automation but has not yet measured implicit influences. We examine concurrent effects of explicit propensity to trust machines and implicit attitudes toward automation on trust in an automated system. We examine differential impacts of each under varying automation performance conditions (clearly good, ambiguous, clearly poor). Participants completed both a self-report measure of propensity to trust and an Implicit Association Test measuring implicit attitude toward automation, then performed an X-ray screening task. Automation performance was manipulated within-subjects by varying the number and obviousness of errors. Explicit propensity to trust and implicit attitude toward automation did not significantly correlate. When the automation's performance was ambiguous, implicit attitude significantly affected automation trust, and its relationship with propensity to trust was additive: Increments in either were related to increases in trust. When errors were obvious, a significant interaction between the implicit and explicit measures was found, with those high in both having higher trust. Implicit attitudes have important implications for automation trust. Users may not be able to accurately report why they experience a given level of trust. To understand why users trust or fail to trust automation, measurements of implicit and explicit predictors may be necessary. Furthermore, implicit attitude toward automation might be used as a lever to effectively calibrate trust.

Automated MRI segmentation for individualized modeling of current flow in the human head.

Science.gov (United States)

Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

2013-12-01

High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible

Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies.

Science.gov (United States)

Surinova, Silvia; Hüttenhain, Ruth; Chang, Ching-Yun; Espona, Lucia; Vitek, Olga; Aebersold, Ruedi

2013-08-01

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope-labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1-2 weeks, depending on the number of replicates used in the experiment.

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera

OpenAIRE

Thuy Tuong Nguyen; David C. Slaughter; Bradley D. Hanson; Andrew Barber; Amy Freitas; Daniel Robles; Erin Whelan

2015-01-01

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a t...

SU-D-16A-02: A Novel Methodology for Accurate, Semi-Automated Delineation of Oral Mucosa for Radiation Therapy Dose-Response Studies

International Nuclear Information System (INIS)

Dean, J; Welsh, L; Gulliford, S; Harrington, K; Nutting, C

2014-01-01

Purpose: The significant morbidity caused by radiation-induced acute oral mucositis means that studies aiming to elucidate dose-response relationships in this tissue are a high priority. However, there is currently no standardized method for delineating the mucosal structures within the oral cavity. This report describes the development of a methodology to delineate the oral mucosa accurately on CT scans in a semi-automated manner. Methods: An oral mucosa atlas for automated segmentation was constructed using the RayStation Atlas-Based Segmentation (ABS) module. A radiation oncologist manually delineated the full surface of the oral mucosa on a planning CT scan of a patient receiving radiotherapy (RT) to the head and neck region. A 3mm fixed annulus was added to incorporate the mucosal wall thickness. This structure was saved as an atlas template. ABS followed by model-based segmentation was performed on four further patients sequentially, adding each patient to the atlas. Manual editing of the automatically segmented structure was performed. A dose comparison between these contours and previously used oral cavity volume contours was performed. Results: The new approach was successful in delineating the mucosa, as assessed by an experienced radiation oncologist, when applied to a new series of patients receiving head and neck RT. Reductions in the mean doses obtained when using the new delineation approach, compared with the previously used technique, were demonstrated for all patients (median: 36.0%, range: 25.6% – 39.6%) and were of a magnitude that might be expected to be clinically significant. Differences in the maximum dose that might reasonably be expected to be clinically significant were observed for two patients. Conclusion: The method developed provides a means of obtaining the dose distribution delivered to the oral mucosa more accurately than has previously been achieved. This will enable the acquisition of high quality dosimetric data for use in

Optimization of the GBMV2 implicit solvent force field for accurate simulation of protein conformational equilibria.

Science.gov (United States)

Lee, Kuo Hao; Chen, Jianhan

2017-06-15

Accurate treatment of solvent environment is critical for reliable simulations of protein conformational equilibria. Implicit treatment of solvation, such as using the generalized Born (GB) class of models arguably provides an optimal balance between computational efficiency and physical accuracy. Yet, GB models are frequently plagued by a tendency to generate overly compact structures. The physical origins of this drawback are relatively well understood, and the key to a balanced implicit solvent protein force field is careful optimization of physical parameters to achieve a sufficient level of cancellation of errors. The latter has been hampered by the difficulty of generating converged conformational ensembles of non-trivial model proteins using the popular replica exchange sampling technique. Here, we leverage improved sampling efficiency of a newly developed multi-scale enhanced sampling technique to re-optimize the generalized-Born with molecular volume (GBMV2) implicit solvent model with the CHARMM36 protein force field. Recursive optimization of key GBMV2 parameters (such as input radii) and protein torsion profiles (via the CMAP torsion cross terms) has led to a more balanced GBMV2 protein force field that recapitulates the structures and stabilities of both helical and β-hairpin model peptides. Importantly, this force field appears to be free of the over-compaction bias, and can generate structural ensembles of several intrinsically disordered proteins of various lengths that seem highly consistent with available experimental data. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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

Can a semi-automated surface matching and principal axis-based algorithm accurately quantify femoral shaft fracture alignment in six degrees of freedom?

Science.gov (United States)

Crookshank, Meghan C; Beek, Maarten; Singh, Devin; Schemitsch, Emil H; Whyne, Cari M

2013-07-01

Accurate alignment of femoral shaft fractures treated with intramedullary nailing remains a challenge for orthopaedic surgeons. The aim of this study is to develop and validate a cone-beam CT-based, semi-automated algorithm to quantify the malalignment in six degrees of freedom (6DOF) using a surface matching and principal axes-based approach. Complex comminuted diaphyseal fractures were created in nine cadaveric femora and cone-beam CT images were acquired (27 cases total). Scans were cropped and segmented using intensity-based thresholding, producing superior, inferior and comminution volumes. Cylinders were fit to estimate the long axes of the superior and inferior fragments. The angle and distance between the two cylindrical axes were calculated to determine flexion/extension and varus/valgus angulation and medial/lateral and anterior/posterior translations, respectively. Both surfaces were unwrapped about the cylindrical axes. Three methods of matching the unwrapped surface for determination of periaxial rotation were compared based on minimizing the distance between features. The calculated corrections were compared to the input malalignment conditions. All 6DOF were calculated to within current clinical tolerances for all but two cases. This algorithm yielded accurate quantification of malalignment of femoral shaft fractures for fracture gaps up to 60 mm, based on a single CBCT image of the fractured limb. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.

Science.gov (United States)

A Santos, Jose C; Nassif, Houssam; Page, David; Muggleton, Stephen H; E Sternberg, Michael J

2012-07-11

There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. In addition to confirming literature results, ProGolem's model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners.

Zero in on Key Open Problems in Automated NMR Protein Structure Determination

KAUST Repository

Abbas, Ahmed

2015-11-12

Nuclear magnetic resonance (NMR) is one of the main approaches for protein struc- ture determination. The biggest advantage of this approach is that it can determine the three-dimensional structure of the protein in the solution phase. Thus, the natural dynamics of the protein can be studied. However, NMR protein structure determina- tion is an expertise intensive and time-consuming process. If the structure determi- nation process can be accelerated or even automated by computational methods, that will significantly advance the structural biology field. Our goal in this dissertation is to propose highly efficient and error tolerant methods that can work well on real and noisy data sets of NMR. Our first contribution in this dissertation is the development of a novel peak pick- ing method (WaVPeak). First, WaVPeak denoises the NMR spectra using wavelet smoothing. A brute force method is then used to identify all the candidate peaks. Af- ter that, the volume of each candidate peak is estimated. Finally, the peaks are sorted according to their volumes. WaVPeak is tested on the same benchmark data set that was used to test the state-of-the-art method, PICKY. WaVPeak shows significantly better performance than PICKY in terms of recall and precision. Our second contribution is to propose an automatic method to select peaks pro- duced by peak picking methods. This automatic method is used to overcome the limitations of fixed number-based methods. Our method is based on the Benjamini- Hochberg (B-H) algorithm. The method is used with both WaVPeak and PICKY to automatically select the number of peaks to return from out of hundreds of candidate peaks. The volume (in WaVPeak) and the intensity (in PICKY) are converted into p-values. Peaks that have p-values below some certain threshold are selected. Ex- perimental results show that the new method is better than the fixed number-based method in terms of recall. To improve precision, we tried to eliminate false peaks using

Automated Quality Control for Ortholmages and DEMs

DEFF Research Database (Denmark)

Höhle, Joachim; Potucková, Marketa

2005-01-01

The checking of geometric accurancy of orthoimages and digital elevation models (DEMs) is discussed. As a reference, an existing orthoimage and a second orthoimage derived from an overlapping aerial image, are used. The proposed automated procedures for checking the orthoimages and DEMs are based...

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

International Nuclear Information System (INIS)

Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

2015-01-01

Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

Energy Technology Data Exchange (ETDEWEB)

Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke, E-mail: ksheng@mednet.ucla.edu [Department of Radiation Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90024 (United States)

2015-11-15

Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery.

Science.gov (United States)

Yu, Victoria Y; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A; Sheng, Ke

2015-11-01

Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was attributed to phantom setup

Automated design of degenerate codon libraries.

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Mena, Marco A; Daugherty, Patrick S

2005-12-01

Degenerate codon libraries are frequently used in protein engineering and evolution studies but are often limited to targeting a small number of positions to adequately limit the search space. To mitigate this, codon degeneracy can be limited using heuristics or previous knowledge of the targeted positions. To automate design of libraries given a set of amino acid sequences, an algorithm (LibDesign) was developed that generates a set of possible degenerate codon libraries, their resulting size, and their score relative to a user-defined scoring function. A gene library of a specified size can then be constructed that is representative of the given amino acid distribution or that includes specific sequences or combinations thereof. LibDesign provides a new tool for automated design of high-quality protein libraries that more effectively harness existing sequence-structure information derived from multiple sequence alignment or computational protein design data.

AUTOMATED PROCESS MONITORING: APPLYING PROVEN AUTOMATION TECHNIQUES TO INTERNATIONAL SAFEGUARDS NEEDS

International Nuclear Information System (INIS)

O'Hara, Matthew J.; Durst, Philip C.; Grate, Jay W.; Devol, Timothy A.; Egorov, Oleg; Clements, John P.

2008-01-01

Identification and quantification of specific alpha- and beta-emitting radionuclides in complex liquid matrices is highly challenging, and is typically accomplished through laborious wet chemical sample preparation and separations followed by analysis using a variety of detection methodologies (e.g., liquid scintillation, gas proportional counting, alpha energy analysis, mass spectrometry). Analytical results may take days or weeks to report. Chains of custody and sample security measures may also complicate or slow the analytical process. When an industrial process-scale plant requires the monitoring of specific radionuclides as an indication of the composition of its feed stream or of plant performance, radiochemical measurements must be fast, accurate, and reliable. Scientists at Pacific Northwest National Laboratory have assembled a fully automated prototype Process Monitor instrument capable of a variety of tasks: automated sampling directly from a feed stream, sample digestion/analyte redox adjustment, chemical separations, radiochemical detection and data analysis/reporting. The system is compact, its components are fluidically inter-linked, and analytical results could be immediately transmitted to on- or off-site locations. The development of a rapid radiochemical Process Monitor for 99Tc in Hanford tank waste processing streams, capable of performing several measurements per hour, will be discussed in detail. More recently, the automated platform was modified to perform measurements of 90Sr in Hanford tank waste stimulant. The system exemplifies how automation could be integrated into reprocessing facilities to support international nuclear safeguards needs

Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

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Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

2013-01-01

The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many

Automated classification of immunostaining patterns in breast tissue from the human protein Atlas

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Issac Niwas Swamidoss

2013-01-01

Full Text Available Background: The Human Protein Atlas (HPA is an effort to map the location of all human proteins (http://www.proteinatlas.org/. It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. Materials and Methods: The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM features, complex wavelet co-occurrence matrix (CWCM features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM and linear discriminant analysis (LDA classifier. Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. Results: We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Conclusions: Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for

Validation of the Automated Method VIENA: An Accurate, Precise, and Robust Measure of Ventricular Enlargement

NARCIS (Netherlands)

Vrenken, H.; Vos, E.K.; van der Flier, W.M.; Sluimer, I.C.; Cover, K.S.; Knol, D.L.; Barkhof, F.

2014-01-01

Background: In many retrospective studies and large clinical trials, high-resolution, good-contrast 3DT1 images are unavailable, hampering detailed analysis of brain atrophy. Ventricular enlargement then provides a sensitive indirect measure of ongoing central brain atrophy. Validated automated

Decision peptide-driven: a free software tool for accurate protein quantification using gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry.

Science.gov (United States)

Santos, Hugo M; Reboiro-Jato, Miguel; Glez-Peña, Daniel; Nunes-Miranda, J D; Fdez-Riverola, Florentino; Carvallo, R; Capelo, J L

2010-09-15

The decision peptide-driven tool implements a software application for assisting the user in a protocol for accurate protein quantification based on the following steps: (1) protein separation through gel electrophoresis; (2) in-gel protein digestion; (3) direct and inverse (18)O-labeling and (4) matrix assisted laser desorption ionization time of flight mass spectrometry, MALDI analysis. The DPD software compares the MALDI results of the direct and inverse (18)O-labeling experiments and quickly identifies those peptides with paralleled loses in different sets of a typical proteomic workflow. Those peptides are used for subsequent accurate protein quantification. The interpretation of the MALDI data from direct and inverse labeling experiments is time-consuming requiring a significant amount of time to do all comparisons manually. The DPD software shortens and simplifies the searching of the peptides that must be used for quantification from a week to just some minutes. To do so, it takes as input several MALDI spectra and aids the researcher in an automatic mode (i) to compare data from direct and inverse (18)O-labeling experiments, calculating the corresponding ratios to determine those peptides with paralleled losses throughout different sets of experiments; and (ii) allow to use those peptides as internal standards for subsequent accurate protein quantification using (18)O-labeling. In this work the DPD software is presented and explained with the quantification of protein carbonic anhydrase. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis.

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Masso, Majid; Vaisman, Iosif I

2008-09-15

Accurate predictive models for the impact of single amino acid substitutions on protein stability provide insight into protein structure and function. Such models are also valuable for the design and engineering of new proteins. Previously described methods have utilized properties of protein sequence or structure to predict the free energy change of mutants due to thermal (DeltaDeltaG) and denaturant (DeltaDeltaG(H2O)) denaturations, as well as mutant thermal stability (DeltaT(m)), through the application of either computational energy-based approaches or machine learning techniques. However, accuracy associated with applying these methods separately is frequently far from optimal. We detail a computational mutagenesis technique based on a four-body, knowledge-based, statistical contact potential. For any mutation due to a single amino acid replacement in a protein, the method provides an empirical normalized measure of the ensuing environmental perturbation occurring at every residue position. A feature vector is generated for the mutant by considering perturbations at the mutated position and it's ordered six nearest neighbors in the 3-dimensional (3D) protein structure. These predictors of stability change are evaluated by applying machine learning tools to large training sets of mutants derived from diverse proteins that have been experimentally studied and described. Predictive models based on our combined approach are either comparable to, or in many cases significantly outperform, previously published results. A web server with supporting documentation is available at http://proteins.gmu.edu/automute.

4D experiments measured with APSY for automated backbone resonance assignments of large proteins

International Nuclear Information System (INIS)

Krähenbühl, Barbara; Boudet, Julien; Wider, Gerhard

2013-01-01

Detailed structural and functional characterization of proteins by solution NMR requires sequence-specific resonance assignment. We present a set of transverse relaxation optimization (TROSY) based four-dimensional automated projection spectroscopy (APSY) experiments which are designed for resonance assignments of proteins with a size up to 40 kDa, namely HNCACO, HNCOCA, HNCACB and HN(CO)CACB. These higher-dimensional experiments include several sensitivity-optimizing features such as multiple quantum parallel evolution in a ‘just-in-time’ manner, aliased off-resonance evolution, evolution-time optimized APSY acquisition, selective water-handling and TROSY. The experiments were acquired within the concept of APSY, but they can also be used within the framework of sparsely sampled experiments. The multidimensional peak lists derived with APSY provided chemical shifts with an approximately 20 times higher precision than conventional methods usually do, and allowed the assignment of 90 % of the backbone resonances of the perdeuterated primase-polymerase ORF904, which contains 331 amino acid residues and has a molecular weight of 38.4 kDa.

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics.

Science.gov (United States)

Chepelev, Leonid L; Riazanov, Alexandre; Kouznetsov, Alexandre; Low, Hong Sang; Dumontier, Michel; Baker, Christopher J O

2011-07-26

The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics

Directory of Open Access Journals (Sweden)

Dumontier Michel

2011-07-01

Full Text Available Abstract Background The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. Results As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of

An Immune-inspired Adaptive Automated Intrusion Response System Model

Directory of Open Access Journals (Sweden)

Ling-xi Peng

2012-09-01

Full Text Available An immune-inspired adaptive automated intrusion response system model, named as , is proposed. The descriptions of self, non-self, immunocyte, memory detector, mature detector and immature detector of the network transactions, and the realtime network danger evaluation equations are given. Then, the automated response polices are adaptively performed or adjusted according to the realtime network danger. Thus, not only accurately evaluates the network attacks, but also greatly reduces the response times and response costs.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

Science.gov (United States)

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the

Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules.

Directory of Open Access Journals (Sweden)

Gregory R Johnson

2015-12-01

Full Text Available Characterizing the spatial distribution of proteins directly from microscopy images is a difficult problem with numerous applications in cell biology (e.g. identifying motor-related proteins and clinical research (e.g. identification of cancer biomarkers. Here we describe the design of a system that provides automated analysis of punctate protein patterns in microscope images, including quantification of their relationships to microtubules. We constructed the system using confocal immunofluorescence microscopy images from the Human Protein Atlas project for 11 punctate proteins in three cultured cell lines. These proteins have previously been characterized as being primarily located in punctate structures, but their images had all been annotated by visual examination as being simply "vesicular". We were able to show that these patterns could be distinguished from each other with high accuracy, and we were able to assign to one of these subclasses hundreds of proteins whose subcellular localization had not previously been well defined. In addition to providing these novel annotations, we built a generative approach to modeling of punctate distributions that captures the essential characteristics of the distinct patterns. Such models are expected to be valuable for representing and summarizing each pattern and for constructing systems biology simulations of cell behaviors.

An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

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Albert-Baskar Arul

2013-06-01

Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

Exploring the relationship between sequence similarity and accurate phylogenetic trees.

Science.gov (United States)

Cantarel, Brandi L; Morrison, Hilary G; Pearson, William

2006-11-01

We have characterized the relationship between accurate phylogenetic reconstruction and sequence similarity, testing whether high levels of sequence similarity can consistently produce accurate evolutionary trees. We generated protein families with known phylogenies using a modified version of the PAML/EVOLVER program that produces insertions and deletions as well as substitutions. Protein families were evolved over a range of 100-400 point accepted mutations; at these distances 63% of the families shared significant sequence similarity. Protein families were evolved using balanced and unbalanced trees, with ancient or recent radiations. In families sharing statistically significant similarity, about 60% of multiple sequence alignments were 95% identical to true alignments. To compare recovered topologies with true topologies, we used a score that reflects the fraction of clades that were correctly clustered. As expected, the accuracy of the phylogenies was greatest in the least divergent families. About 88% of phylogenies clustered over 80% of clades in families that shared significant sequence similarity, using Bayesian, parsimony, distance, and maximum likelihood methods. However, for protein families with short ancient branches (ancient radiation), only 30% of the most divergent (but statistically significant) families produced accurate phylogenies, and only about 70% of the second most highly conserved families, with median expectation values better than 10(-60), produced accurate trees. These values represent upper bounds on expected tree accuracy for sequences with a simple divergence history; proteins from 700 Giardia families, with a similar range of sequence similarities but considerably more gaps, produced much less accurate trees. For our simulated insertions and deletions, correct multiple sequence alignments did not perform much better than those produced by T-COFFEE, and including sequences with expressed sequence tag-like sequencing errors did not

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

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A Santos Jose C

2012-07-01

Full Text Available Abstract Background There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP, which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. Results The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. Conclusions In addition to confirming literature results, ProGolem’s model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners.

Integrating protein structures and precomputed genealogies in the Magnum database: Examples with cellular retinoid binding proteins

Directory of Open Access Journals (Sweden)

Bradley Michael E

2006-02-01

Full Text Available Abstract Background When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use. Results The precomputed Magnum database offers a solution to this problem for ca. 1,800 full-length protein families with at least one crystal structure. The Magnum deliverables include 1 multiple sequence alignments, 2 mapping of alignment sites to crystal structure sites, 3 phylogenetic trees, 4 inferred ancestral sequences at internal tree nodes, and 5 amino acid replacements along tree branches. Comprehensive evaluations revealed that the automated procedures used to construct Magnum produced accurate models of how proteins divergently evolve, or genealogies, and correctly integrated these with the structural data. To demonstrate Magnum's capabilities, we asked for amino acid replacements requiring three nucleotide substitutions, located at internal protein structure sites, and occurring on short phylogenetic tree branches. In the cellular retinoid binding protein family a site that potentially modulates ligand binding affinity was discovered. Recruitment of cellular retinol binding protein to function as a lens crystallin in the diurnal gecko afforded another opportunity to showcase the predictive value of a browsable database containing branch replacement patterns integrated with protein structures. Conclusion We integrated two areas of protein science, evolution and structure, on a large scale and created a precomputed database, known as Magnum, which is the first freely available resource of its kind. Magnum provides evolutionary and structural

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

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Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Automated image analysis of cyclin D1 protein expression in invasive lobular breast carcinoma provides independent prognostic information.

Science.gov (United States)

Tobin, Nicholas P; Lundgren, Katja L; Conway, Catherine; Anagnostaki, Lola; Costello, Sean; Landberg, Göran

2012-11-01

The emergence of automated image analysis algorithms has aided the enumeration, quantification, and immunohistochemical analyses of tumor cells in both whole section and tissue microarray samples. To date, the focus of such algorithms in the breast cancer setting has been on traditional markers in the common invasive ductal carcinoma subtype. Here, we aimed to optimize and validate an automated analysis of the cell cycle regulator cyclin D1 in a large collection of invasive lobular carcinoma and relate its expression to clinicopathologic data. The image analysis algorithm was trained to optimally match manual scoring of cyclin D1 protein expression in a subset of invasive lobular carcinoma tissue microarray cores. The algorithm was capable of distinguishing cyclin D1-positive cells and illustrated high correlation with traditional manual scoring (κ=0.63). It was then applied to our entire cohort of 483 patients, with subsequent statistical comparisons to clinical data. We found no correlation between cyclin D1 expression and tumor size, grade, and lymph node status. However, overexpression of the protein was associated with reduced recurrence-free survival (P=.029), as was positive nodal status (Pinvasive lobular carcinoma. Finally, high cyclin D1 expression was associated with increased hazard ratio in multivariate analysis (hazard ratio, 1.75; 95% confidence interval, 1.05-2.89). In conclusion, we describe an image analysis algorithm capable of reliably analyzing cyclin D1 staining in invasive lobular carcinoma and have linked overexpression of the protein to increased recurrence risk. Our findings support the use of cyclin D1 as a clinically informative biomarker for invasive lobular breast cancer. Copyright © 2012 Elsevier Inc. All rights reserved.

Accurate Quantification of Cardiovascular Biomarkers in Serum Using Protein Standard Absolute Quantification (PSAQ™) and Selected Reaction Monitoring*

Science.gov (United States)

Huillet, Céline; Adrait, Annie; Lebert, Dorothée; Picard, Guillaume; Trauchessec, Mathieu; Louwagie, Mathilde; Dupuis, Alain; Hittinger, Luc; Ghaleh, Bijan; Le Corvoisier, Philippe; Jaquinod, Michel; Garin, Jérôme; Bruley, Christophe; Brun, Virginie

2012-01-01

Development of new biomarkers needs to be significantly accelerated to improve diagnostic, prognostic, and toxicity monitoring as well as therapeutic follow-up. Biomarker evaluation is the main bottleneck in this development process. Selected Reaction Monitoring (SRM) combined with stable isotope dilution has emerged as a promising option to speed this step, particularly because of its multiplexing capacities. However, analytical variabilities because of upstream sample handling or incomplete trypsin digestion still need to be resolved. In 2007, we developed the PSAQ™ method (Protein Standard Absolute Quantification), which uses full-length isotope-labeled protein standards to quantify target proteins. In the present study we used clinically validated cardiovascular biomarkers (LDH-B, CKMB, myoglobin, and troponin I) to demonstrate that the combination of PSAQ and SRM (PSAQ-SRM) allows highly accurate biomarker quantification in serum samples. A multiplex PSAQ-SRM assay was used to quantify these biomarkers in clinical samples from myocardial infarction patients. Good correlation between PSAQ-SRM and ELISA assay results was found and demonstrated the consistency between these analytical approaches. Thus, PSAQ-SRM has the capacity to improve both accuracy and reproducibility in protein analysis. This will be a major contribution to efficient biomarker development strategies. PMID:22080464

Computerized automated remote inspection system

International Nuclear Information System (INIS)

The automated inspection system utilizes a computer to control the location of the ultrasonic transducer, the actual inspection process, the display of the data, and the storage of the data on IBM magnetic tape. This automated inspection equipment provides two major advantages. First, it provides a cost savings, because of the reduced inspection time, made possible by the automation of the data acquisition, processing, and storage equipment. This reduced inspection time is also made possible by a computerized data evaluation aid which speeds data interpretation. In addition, the computer control of the transducer location drive allows the exact duplication of a previously located position or flaw. The second major advantage is that the use of automated inspection equipment also allows a higher-quality inspection, because of the automated data acquisition, processing, and storage. This storage of data, in accurate digital form on IBM magnetic tape, for example, facilitates retrieval for comparison with previous inspection data. The equipment provides a multiplicity of scan data which will provide statistical information on any questionable volume or flaw. An automatic alarm for location of all reportable flaws reduces the probability of operator error. This system has the ability to present data on a cathode ray tube as numerical information, a three-dimensional picture, or ''hard-copy'' sheet. One important advantage of this system is the ability to store large amounts of data in compact magnetic tape reels

Using Modeling and Simulation to Predict Operator Performance and Automation-Induced Complacency With Robotic Automation: A Case Study and Empirical Validation.

Science.gov (United States)

Wickens, Christopher D; Sebok, Angelia; Li, Huiyang; Sarter, Nadine; Gacy, Andrew M

2015-09-01

The aim of this study was to develop and validate a computational model of the automation complacency effect, as operators work on a robotic arm task, supported by three different degrees of automation. Some computational models of complacency in human-automation interaction exist, but those are formed and validated within the context of fairly simplified monitoring failures. This research extends model validation to a much more complex task, so that system designers can establish, without need for human-in-the-loop (HITL) experimentation, merits and shortcomings of different automation degrees. We developed a realistic simulation of a space-based robotic arm task that could be carried out with three different levels of trajectory visualization and execution automation support. Using this simulation, we performed HITL testing. Complacency was induced via several trials of correctly performing automation and then was assessed on trials when automation failed. Following a cognitive task analysis of the robotic arm operation, we developed a multicomponent model of the robotic operator and his or her reliance on automation, based in part on visual scanning. The comparison of model predictions with empirical results revealed that the model accurately predicted routine performance and predicted the responses to these failures after complacency developed. However, the scanning models do not account for the entire attention allocation effects of complacency. Complacency modeling can provide a useful tool for predicting the effects of different types of imperfect automation. The results from this research suggest that focus should be given to supporting situation awareness in automation development. © 2015, Human Factors and Ergonomics Society.

Future of Automated Insulin Delivery Systems.

Science.gov (United States)

Castle, Jessica R; DeVries, J Hans; Kovatchev, Boris

2017-06-01

Advances in continuous glucose monitoring (CGM) have brought on a paradigm shift in the management of type 1 diabetes. These advances have enabled the automation of insulin delivery, where an algorithm determines the insulin delivery rate in response to the CGM values. There are multiple automated insulin delivery (AID) systems in development. A system that automates basal insulin delivery has already received Food and Drug Administration approval, and more systems are likely to follow. As the field of AID matures, future systems may incorporate additional hormones and/or multiple inputs, such as activity level. All AID systems are impacted by CGM accuracy and future CGM devices must be shown to be sufficiently accurate to be safely incorporated into AID. In this article, we summarize recent achievements in AID development, with a special emphasis on CGM sensor performance, and discuss the future of AID systems from the point of view of their input-output characteristics, form factor, and adaptability.

Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype

International Nuclear Information System (INIS)

Knowles, David; Sudar, Damir; Bator, Carol; Bissell, Mina

2006-01-01

The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, the distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is an increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype, and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently-stained nuclear protein NuMA in different mammary phenotypes obtained using three-dimensional cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from three-dimensional confocal images. Prominent features of fluorescently-stained NuMA were detected using a novel local bright feature analysis technique, and their normalized spatial density calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features as non-neoplastic cells underwent phenotypically normal acinar morphogenesis. In contrast, we did not detect any reorganization of NuMA during the formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating non-neoplastic cells from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues

Automating CPM-GOMS

Science.gov (United States)

John, Bonnie; Vera, Alonso; Matessa, Michael; Freed, Michael; Remington, Roger

2002-01-01

CPM-GOMS is a modeling method that combines the task decomposition of a GOMS analysis with a model of human resource usage at the level of cognitive, perceptual, and motor operations. CPM-GOMS models have made accurate predictions about skilled user behavior in routine tasks, but developing such models is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the

Automated longitudinal intra-subject analysis (ALISA) for diffusion MRI tractography

DEFF Research Database (Denmark)

Aarnink, Saskia H; Vos, Sjoerd B; Leemans, Alexander

2014-01-01

the inter-subject and intra-subject automation in this situation are intended for subjects without gross pathology. In this work, we propose such an automated longitudinal intra-subject analysis (dubbed ALISA) approach, and assessed whether ALISA could preserve the same level of reliability as obtained....... The major disadvantage of manual FT segmentations, unfortunately, is that placing regions-of-interest for tract selection can be very labor-intensive and time-consuming. Although there are several methods that can identify specific WM fiber bundles in an automated way, manual FT segmentations across...... multiple subjects performed by a trained rater with neuroanatomical expertise are generally assumed to be more accurate. However, for longitudinal DTI analyses it may still be beneficial to automate the FT segmentation across multiple time points, but then for each individual subject separately. Both...

LC-MS/MS Peptide Mapping with Automated Data Processing for Routine Profiling of N-Glycans in Immunoglobulins

Science.gov (United States)

Shah, Bhavana; Jiang, Xinzhao Grace; Chen, Louise; Zhang, Zhongqi

2014-06-01

Protein N-Glycan analysis is traditionally performed by high pH anion exchange chromatography (HPAEC), reversed phase liquid chromatography (RPLC), or hydrophilic interaction liquid chromatography (HILIC) on fluorescence-labeled glycans enzymatically released from the glycoprotein. These methods require time-consuming sample preparations and do not provide site-specific glycosylation information. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) peptide mapping is frequently used for protein structural characterization and, as a bonus, can potentially provide glycan profile on each individual glycosylation site. In this work, a recently developed glycopeptide fragmentation model was used for automated identification, based on their MS/MS, of N-glycopeptides from proteolytic digestion of monoclonal antibodies (mAbs). Experimental conditions were optimized to achieve accurate profiling of glycoforms. Glycan profiles obtained from LC-MS/MS peptide mapping were compared with those obtained from HPAEC, RPLC, and HILIC analyses of released glycans for several mAb molecules. Accuracy, reproducibility, and linearity of the LC-MS/MS peptide mapping method for glycan profiling were evaluated. The LC-MS/MS peptide mapping method with fully automated data analysis requires less sample preparation, provides site-specific information, and may serve as an alternative method for routine profiling of N-glycans on immunoglobulins as well as other glycoproteins with simple N-glycans.

Fast automated placement of polar hydrogen atoms in protein-ligand complexes

Directory of Open Access Journals (Sweden)

Lippert Tobias

2009-08-01

Full Text Available Abstract Background Hydrogen bonds play a major role in the stabilization of protein-ligand complexes. The ability of a functional group to form them depends on the position of its hydrogen atoms. An accurate knowledge of the positions of hydrogen atoms in proteins is therefore important to correctly identify hydrogen bonds and their properties. The high mobility of hydrogen atoms introduces several degrees of freedom: Tautomeric states, where a hydrogen atom alters its binding partner, torsional changes where the position of the hydrogen atom is rotated around the last heavy-atom bond in a residue, and protonation states, where the number of hydrogen atoms at a functional group may change. Also, side-chain flips in glutamine and asparagine and histidine residues, which are common crystallographic ambiguities must be identified before structure-based calculations can be conducted. Results We have implemented a method to determine the most probable hydrogen atom positions in a given protein-ligand complex. Optimality of hydrogen bond geometries is determined by an empirical scoring function which is used in molecular docking. This allows to evaluate protein-ligand interactions with an established model. Also, our method allows to resolve common crystallographic ambiguities such as as flipped amide groups and histidine residues. To ensure high speed, we make use of a dynamic programming approach. Conclusion Our results were checked against selected high-resolution structures from an external dataset, for which the positions of the hydrogen atoms have been validated manually. The quality of our results is comparable to that of other programs, with the advantage of being fast enough to be applied on-the-fly for interactive usage or during score evaluation.

Fast and accurate non-sequential protein structure alignment using a new asymmetric linear sum assignment heuristic.

Science.gov (United States)

Brown, Peter; Pullan, Wayne; Yang, Yuedong; Zhou, Yaoqi

2016-02-01

The three dimensional tertiary structure of a protein at near atomic level resolution provides insight alluding to its function and evolution. As protein structure decides its functionality, similarity in structure usually implies similarity in function. As such, structure alignment techniques are often useful in the classifications of protein function. Given the rapidly growing rate of new, experimentally determined structures being made available from repositories such as the Protein Data Bank, fast and accurate computational structure comparison tools are required. This paper presents SPalignNS, a non-sequential protein structure alignment tool using a novel asymmetrical greedy search technique. The performance of SPalignNS was evaluated against existing sequential and non-sequential structure alignment methods by performing trials with commonly used datasets. These benchmark datasets used to gauge alignment accuracy include (i) 9538 pairwise alignments implied by the HOMSTRAD database of homologous proteins; (ii) a subset of 64 difficult alignments from set (i) that have low structure similarity; (iii) 199 pairwise alignments of proteins with similar structure but different topology; and (iv) a subset of 20 pairwise alignments from the RIPC set. SPalignNS is shown to achieve greater alignment accuracy (lower or comparable root-mean squared distance with increased structure overlap coverage) for all datasets, and the highest agreement with reference alignments from the challenging dataset (iv) above, when compared with both sequentially constrained alignments and other non-sequential alignments. SPalignNS was implemented in C++. The source code, binary executable, and a web server version is freely available at: http://sparks-lab.org yaoqi.zhou@griffith.edu.au. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Serum protein profile at remission can accurately assess therapeutic outcomes and survival for serous ovarian cancer.

Directory of Open Access Journals (Sweden)

Jinhua Wang

Full Text Available BACKGROUND: Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer. EXPERIMENTAL DESIGN: Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD, remission (RM and recurrence (RC. The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis. RESULTS: Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC have individually good area-under-the-curve (AUC values (AUC = 0.69-0.86 and more than 10 three-marker combinations have excellent AUC values (0.91-0.93 in distinguishing active cancer samples (PD & RC from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC. Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1 measured at remission can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p<10(-3. CONCLUSION: We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.

An automated method for the layup of fiberglass fabric

Science.gov (United States)

Zhu, Siqi

This dissertation presents an automated composite fabric layup solution based on a new method to deform fiberglass fabric referred to as shifting. A layup system was designed and implemented using a large robotic gantry and custom end-effector for shifting. Layup tests proved that the system can deposit fabric onto two-dimensional and three-dimensional tooling surfaces accurately and repeatedly while avoiding out-of-plane deformation. A process planning method was developed to generate tool paths for the layup system based on a geometric model of the tooling surface. The approach is analogous to Computer Numerical Controlled (CNC) machining, where Numerical Control (NC) code from a Computer-Aided Design (CAD) model is generated to drive the milling machine. Layup experiments utilizing the proposed method were conducted to validate the performance. The results show that the process planning software requires minimal time or human intervention and can generate tool paths leading to accurate composite fabric layups. Fiberglass fabric samples processed with shifting deformation were observed for meso-scale deformation. Tow thinning, bending and spacing was observed and measured. Overall, shifting did not create flaws in amounts that would disqualify the method from use in industry. This suggests that shifting is a viable method for use in automated manufacturing. The work of this dissertation provides a new method for the automated layup of broad width composite fabric that is not possible with any available composite automation systems to date.

Automated imaging system for single molecules

Science.gov (United States)

Schwartz, David Charles; Runnheim, Rodney; Forrest, Daniel

2012-09-18

There is provided a high throughput automated single molecule image collection and processing system that requires minimal initial user input. The unique features embodied in the present disclosure allow automated collection and initial processing of optical images of single molecules and their assemblies. Correct focus may be automatically maintained while images are collected. Uneven illumination in fluorescence microscopy is accounted for, and an overall robust imaging operation is provided yielding individual images prepared for further processing in external systems. Embodiments described herein are useful in studies of any macromolecules such as DNA, RNA, peptides and proteins. The automated image collection and processing system and method of same may be implemented and deployed over a computer network, and may be ergonomically optimized to facilitate user interaction.

A novel nano-immunoassay method for quantification of proteins from CD138-purified myeloma cells: biological and clinical utility.

Science.gov (United States)

Misiewicz-Krzeminska, Irena; Corchete, Luis Antonio; Rojas, Elizabeta A; Martínez-López, Joaquín; García-Sanz, Ramón; Oriol, Albert; Bladé, Joan; Lahuerta, Juan-José; Miguel, Jesús San; Mateos, María-Victoria; Gutiérrez, Norma C

2018-05-01

Protein analysis in bone marrow samples from patients with multiple myeloma has been limited by the low concentration of proteins obtained after CD138 + cell selection. A novel approach based on capillary nano-immunoassay could make it possible to quantify dozens of proteins from each myeloma sample in an automated manner. Here we present a method for the accurate and robust quantification of the expression of multiple proteins extracted from CD138-purified multiple myeloma samples frozen in RLT Plus buffer, which is commonly used for nucleic acid preservation and isolation. Additionally, the biological and clinical value of this analysis for a panel of 12 proteins essential to the pathogenesis of multiple myeloma was evaluated in 63 patients with newly diagnosed multiple myeloma. The analysis of the prognostic impact of CRBN /Cereblon and IKZF1 /Ikaros mRNA/protein showed that only the protein levels were able to predict progression-free survival of patients; mRNA levels were not associated with prognosis. Interestingly, high levels of Cereblon and Ikaros proteins were associated with longer progression-free survival only in patients who received immunomodulatory drugs and not in those treated with other drugs. In conclusion, the capillary nano-immunoassay platform provides a novel opportunity for automated quantification of the expression of more than 20 proteins in CD138 + primary multiple myeloma samples. Copyright © 2018 Ferrata Storti Foundation.

Automated procedure for performing computer security risk analysis

International Nuclear Information System (INIS)

Smith, S.T.; Lim, J.J.

1984-05-01

Computers, the invisible backbone of nuclear safeguards, monitor and control plant operations and support many materials accounting systems. Our automated procedure to assess computer security effectiveness differs from traditional risk analysis methods. The system is modeled as an interactive questionnaire, fully automated on a portable microcomputer. A set of modular event trees links the questionnaire to the risk assessment. Qualitative scores are obtained for target vulnerability, and qualitative impact measures are evaluated for a spectrum of threat-target pairs. These are then combined by a linguistic algebra to provide an accurate and meaningful risk measure. 12 references, 7 figures

Accurate cytogenetic biodosimetry through automated dicentric chromosome curation and metaphase cell selection [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Jin Liu

2017-08-01

Full Text Available Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs arising primarily from sister chromatid separation, chromosome fragmentation, and cellular debris. This reduced FPs by an average of 55% and was highly specific to these abnormal structures (≥97.7% in three samples. Additional filters selectively removed images with incomplete, highly overlapped, or missing metaphase cells, or with poor overall chromosome morphologies that increased FP rates. Image selection is optimized and FP DCs are minimized by combining multiple feature based segmentation filters and a novel image sorting procedure based on the known distribution of chromosome lengths. Applying the same image segmentation filtering procedures to both calibration and test samples reduced the average dose estimation error from 0.4 Gy to <0.2 Gy, obviating the need to first manually review these images. This reliable and scalable solution enables batch processing for multiple samples of unknown dose, and meets current requirements for triage radiation biodosimetry of high quality metaphase cell preparations.

Designing an automated blood fractionation system.

Science.gov (United States)

McQuillan, Adrian C; Sales, Sean D

2008-04-01

UK Biobank will be collecting blood samples from a cohort of 500 000 volunteers and it is expected that the rate of collection will peak at approximately 3000 blood collection tubes per day. These samples need to be prepared for long-term storage. It is not considered practical to manually process this quantity of samples so an automated blood fractionation system is required. Principles of industrial automation were applied to the blood fractionation process leading to the requirement of developing a vision system to identify the blood fractions within the blood collection tube so that the fractions can be accurately aspirated and dispensed into micro-tubes. A prototype was manufactured and tested on a range of human blood samples collected in different tube types. A specially designed vision system was capable of accurately measuring the position of the plasma meniscus, plasma/buffy coat interface and the red cells/buffy coat interface within a vacutainer. A rack of 24 vacutainers could be processed in blood fractionation system offers a solution to the problem of processing human blood samples collected in vacutainers in a consistent manner and provides a means of ensuring data and sample integrity.

Technology demonstration of space intravehicular automation and robotics

Science.gov (United States)

Morris, A. Terry; Barker, L. Keith

1994-01-01

Automation and robotic technologies are being developed and capabilities demonstrated which would increase the productivity of microgravity science and materials processing in the space station laboratory module, especially when the crew is not present. The Automation Technology Branch at NASA Langley has been working in the area of intravehicular automation and robotics (IVAR) to provide a user-friendly development facility, to determine customer requirements for automated laboratory systems, and to improve the quality and efficiency of commercial production and scientific experimentation in space. This paper will describe the IVAR facility and present the results of a demonstration using a simulated protein crystal growth experiment inside a full-scale mockup of the space station laboratory module using a unique seven-degree-of-freedom robot.

Automation, parallelism, and robotics for proteomics.

Science.gov (United States)

Alterovitz, Gil; Liu, Jonathan; Chow, Jijun; Ramoni, Marco F

2006-07-01

The speed of the human genome project (Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C. et al., Nature 2001, 409, 860-921) was made possible, in part, by developments in automation of sequencing technologies. Before these technologies, sequencing was a laborious, expensive, and personnel-intensive task. Similarly, automation and robotics are changing the field of proteomics today. Proteomics is defined as the effort to understand and characterize proteins in the categories of structure, function and interaction (Englbrecht, C. C., Facius, A., Comb. Chem. High Throughput Screen. 2005, 8, 705-715). As such, this field nicely lends itself to automation technologies since these methods often require large economies of scale in order to achieve cost and time-saving benefits. This article describes some of the technologies and methods being applied in proteomics in order to facilitate automation within the field as well as in linking proteomics-based information with other related research areas.

ImaEdge - a platform for quantitative analysis of the spatiotemporal dynamics of cortical proteins during cell polarization.

Science.gov (United States)

Zhang, Zhen; Lim, Yen Wei; Zhao, Peng; Kanchanawong, Pakorn; Motegi, Fumio

2017-12-15

Cell polarity involves the compartmentalization of the cell cortex. The establishment of cortical compartments arises from the spatial bias in the activity and concentration of cortical proteins. The mechanistic dissection of cell polarity requires the accurate detection of dynamic changes in cortical proteins, but the fluctuations of cell shape and the inhomogeneous distributions of cortical proteins greatly complicate the quantitative extraction of their global and local changes during cell polarization. To address these problems, we introduce an open-source software package, ImaEdge, which automates the segmentation of the cortex from time-lapse movies, and enables quantitative extraction of cortical protein intensities. We demonstrate that ImaEdge enables efficient and rigorous analysis of the dynamic evolution of cortical PAR proteins during Caenorhabditis elegans embryogenesis. It is also capable of accurate tracking of varying levels of transgene expression and discontinuous signals of the actomyosin cytoskeleton during multiple rounds of cell division. ImaEdge provides a unique resource for quantitative studies of cortical polarization, with the potential for application to many types of polarized cells.This article has an associated First Person interview with the first authors of the paper. © 2017. Published by The Company of Biologists Ltd.

Refuelling: Swiss station will be semi-automated

International Nuclear Information System (INIS)

Fontaine, B.; Ribaux, P.

1981-01-01

The first semi-automated LWR refuelling machine in Europe has been supplied to the Leibstadt General Electric BWR in Switzerland. The system relieves operators of the boring and repetitive job of moving and accurately positioning the refuelling machine during fuelling operations and will thus contribute to plant safety. The machine and its mode of operation are described. (author)

Automated Normalized Cut Segmentation of Aortic Root in CT Angiography

NARCIS (Netherlands)

Elattar, Mustafa; Wiegerinck, Esther; Planken, Nils; VanBavel, Ed; van Assen, Hans; Baan, Jan Jr; Marquering, Henk

2014-01-01

Transcatheter Aortic Valve Implantation (TAVI) is a new minimal-invasive intervention for implanting prosthetic valves in patients with aortic stenosis. This procedure is associated with adverse effects like paravalvular leakage, stroke, and coronary obstruction. Accurate automated sizing for

AUTOMATED TECHNIQUE FOR FLOW MEASUREMENTS FROM MARIOTTE RESERVOIRS.

Science.gov (United States)

Constantz, Jim; Murphy, Fred

1987-01-01

The mariotte reservoir supplies water at a constant hydraulic pressure by self-regulation of its internal gas pressure. Automated outflow measurements from mariotte reservoirs are generally difficult because of the reservoir's self-regulation mechanism. This paper describes an automated flow meter specifically designed for use with mariotte reservoirs. The flow meter monitors changes in the mariotte reservoir's gas pressure during outflow to determine changes in the reservoir's water level. The flow measurement is performed by attaching a pressure transducer to the top of a mariotte reservoir and monitoring gas pressure changes during outflow with a programmable data logger. The advantages of the new automated flow measurement techniques include: (i) the ability to rapidly record a large range of fluxes without restricting outflow, and (ii) the ability to accurately average the pulsing flow, which commonly occurs during outflow from the mariotte reservoir.

Development of a fully automated online mixing system for SAXS protein structure analysis

DEFF Research Database (Denmark)

Nielsen, Søren Skou; Arleth, Lise

2010-01-01

This thesis presents the development of an automated high-throughput mixing and exposure system for Small-Angle Scattering analysis on a synchrotron using polymer microfluidics. Software and hardware for both automated mixing, exposure control on a beamline and automated data reduction...... and preliminary analysis is presented. Three mixing systems that have been the corner stones of the development process are presented including a fully functioning high-throughput microfluidic system that is able to produce and expose 36 mixed samples per hour using 30 μL of sample volume. The system is tested...

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.

Automated microscopy for high-content RNAi screening

Science.gov (United States)

2010-01-01

Fluorescence microscopy is one of the most powerful tools to investigate complex cellular processes such as cell division, cell motility, or intracellular trafficking. The availability of RNA interference (RNAi) technology and automated microscopy has opened the possibility to perform cellular imaging in functional genomics and other large-scale applications. Although imaging often dramatically increases the content of a screening assay, it poses new challenges to achieve accurate quantitative annotation and therefore needs to be carefully adjusted to the specific needs of individual screening applications. In this review, we discuss principles of assay design, large-scale RNAi, microscope automation, and computational data analysis. We highlight strategies for imaging-based RNAi screening adapted to different library and assay designs. PMID:20176920

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

Sub-micron accurate track navigation method ''Navi'' for the analysis of Nuclear Emulsion

International Nuclear Information System (INIS)

Yoshioka, T; Yoshida, J; Kodama, K

2011-01-01

Sub-micron accurate track navigation in Nuclear Emulsion is realized by using low energy signals detected by automated Nuclear Emulsion read-out systems. Using those much dense ''noise'', about 10 4 times larger than the real tracks, the accuracy of the track position navigation reaches to be sub micron only by using the information of a microscope field of view, 200 micron times 200 micron. This method is applied to OPERA analysis in Japan, i.e. support of human eye checks of the candidate tracks, confirmation of neutrino interaction vertexes and to embed missing track segments to the track data read-out by automated systems.

Sub-micron accurate track navigation method ``Navi'' for the analysis of Nuclear Emulsion

Science.gov (United States)

Yoshioka, T.; Yoshida, J.; Kodama, K.

2011-03-01

Sub-micron accurate track navigation in Nuclear Emulsion is realized by using low energy signals detected by automated Nuclear Emulsion read-out systems. Using those much dense ``noise'', about 104 times larger than the real tracks, the accuracy of the track position navigation reaches to be sub micron only by using the information of a microscope field of view, 200 micron times 200 micron. This method is applied to OPERA analysis in Japan, i.e. support of human eye checks of the candidate tracks, confirmation of neutrino interaction vertexes and to embed missing track segments to the track data read-out by automated systems.

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

Science.gov (United States)

Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-03-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein

Identification of Success Criteria for Automated Function Using Feed and Bleed Operation

International Nuclear Information System (INIS)

Kim, Bo Gyung; Kim, Sang Ho; Kang, Hyun Gook; Yoon, Ho Joon

2013-01-01

Since NPP has lots of functions and systems, operated procedure is much complicated and the chance of human error to operate the safety systems is quite high. In the case of large break loss of coolant accident (LBLOCA) and station black out (SBO), the dependency of operator is very low. However, when many mitigation systems are still available, operators have several choices to mitigate the accident and the human error can be increased more. To reduce the operator's workload and perform the operation accurate after the accident, automated function for safe cooldown based on the feed and bleed (F and B) operation was suggested. The automated function can predict whether the plant will be safe after the automated function is initiated, and perform the safety functions automatically. To expect the success of cooldown, success criteria should be identified. To perform the operation accurately after the accident, the automated function for safe cooldown based on the F and B operation is suggested. To expect the success of cooldown, sequence of RCS situation when heat removal by secondary system fails is identified. Based on the sequence of RCS situation, four levels of necessity of F and B operation are classified. To obtain the boundary of levels, the TH analysis will be performed

Automated DNA extraction from genetically modified maize using aminosilane-modified bacterial magnetic particles.

Science.gov (United States)

Ota, Hiroyuki; Lim, Tae-Kyu; Tanaka, Tsuyoshi; Yoshino, Tomoko; Harada, Manabu; Matsunaga, Tadashi

2006-09-18

A novel, automated system, PNE-1080, equipped with eight automated pestle units and a spectrophotometer was developed for genomic DNA extraction from maize using aminosilane-modified bacterial magnetic particles (BMPs). The use of aminosilane-modified BMPs allowed highly accurate DNA recovery. The (A(260)-A(320)):(A(280)-A(320)) ratio of the extracted DNA was 1.9+/-0.1. The DNA quality was sufficiently pure for PCR analysis. The PNE-1080 offered rapid assay completion (30 min) with high accuracy. Furthermore, the results of real-time PCR confirmed that our proposed method permitted the accurate determination of genetically modified DNA composition and correlated well with results obtained by conventional cetyltrimethylammonium bromide (CTAB)-based methods.

Automated high-throughput protein purification using an ÄKTApurifier and a CETAC autosampler.

Science.gov (United States)

Yoo, Daniel; Provchy, Justin; Park, Cynthia; Schulz, Craig; Walker, Kenneth

2014-05-30

As the pace of drug discovery accelerates there is an increased focus on screening larger numbers of protein therapeutic candidates to identify those that are functionally superior and to assess manufacturability earlier in the process. Although there have been advances toward high throughput (HT) cloning and expression, protein purification is still an area where improvements can be made to conventional techniques. Current methodologies for purification often involve a tradeoff between HT automation or capacity and quality. We present an ÄKTA combined with an autosampler, the ÄKTA-AS, which has the capability of purifying up to 240 samples in two chromatographic dimensions without the need for user intervention. The ÄKTA-AS has been shown to be reliable with sample volumes between 0.5 mL and 100 mL, and the innovative use of a uniquely configured loading valve ensures reliability by efficiently removing air from the system as well as preventing sample cross contamination. Incorporation of a sample pump flush minimizes sample loss and enables recoveries ranging from the low tens of micrograms to milligram quantities of protein. In addition, when used in an affinity capture-buffer exchange format the final samples are formulated in a buffer compatible with most assays without requirement of additional downstream processing. The system is designed to capture samples in 96-well microplate format allowing for seamless integration of downstream HT analytic processes such as microfluidic or HPLC analysis. Most notably, there is minimal operator intervention to operate this system, thereby increasing efficiency, sample consistency and reducing the risk of human error. Copyright © 2014 Elsevier B.V. All rights reserved.

Automation for Accommodating Fuel-Efficient Descents in Constrained Airspace

Science.gov (United States)

Coopenbarger, Richard A.

2010-01-01

Continuous descents at low engine power are desired to reduce fuel consumption, emissions and noise during arrival operations. The challenge is to allow airplanes to fly these types of efficient descents without interruption during busy traffic conditions. During busy conditions today, airplanes are commonly forced to fly inefficient, step-down descents as airtraffic controllers work to ensure separation and maximize throughput. NASA in collaboration with government and industry partners is developing new automation to help controllers accommodate continuous descents in the presence of complex traffic and airspace constraints. This automation relies on accurate trajectory predictions to compute strategic maneuver advisories. The talk will describe the concept behind this new automation and provide an overview of the simulations and flight testing used to develop and refine its underlying technology.

Towards Automated Binding Affinity Prediction Using an Iterative Linear Interaction Energy Approach

Directory of Open Access Journals (Sweden)

C. Ruben Vosmeer

2014-01-01

Full Text Available Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.

AuTom: a novel automatic platform for electron tomography reconstruction

KAUST Repository

Han, Renmin

2017-07-26

We have developed a software package towards automatic electron tomography (ET): Automatic Tomography (AuTom). The presented package has the following characteristics: accurate alignment modules for marker-free datasets containing substantial biological structures; fully automatic alignment modules for datasets with fiducial markers; wide coverage of reconstruction methods including a new iterative method based on the compressed-sensing theory that suppresses the “missing wedge” effect; and multi-platform acceleration solutions that support faster iterative algebraic reconstruction. AuTom aims to achieve fully automatic alignment and reconstruction for electron tomography and has already been successful for a variety of datasets. AuTom also offers user-friendly interface and auxiliary designs for file management and workflow management, in which fiducial marker-based datasets and marker-free datasets are addressed with totally different subprocesses. With all of these features, AuTom can serve as a convenient and effective tool for processing in electron tomography.

Automated side-chain model building and sequence assignment by template matching

International Nuclear Information System (INIS)

Terwilliger, Thomas C.

2002-01-01

A method for automated macromolecular side-chain model building and for aligning the sequence to the map is described. An algorithm is described for automated building of side chains in an electron-density map once a main-chain model is built and for alignment of the protein sequence to the map. The procedure is based on a comparison of electron density at the expected side-chain positions with electron-density templates. The templates are constructed from average amino-acid side-chain densities in 574 refined protein structures. For each contiguous segment of main chain, a matrix with entries corresponding to an estimate of the probability that each of the 20 amino acids is located at each position of the main-chain model is obtained. The probability that this segment corresponds to each possible alignment with the sequence of the protein is estimated using a Bayesian approach and high-confidence matches are kept. Once side-chain identities are determined, the most probable rotamer for each side chain is built into the model. The automated procedure has been implemented in the RESOLVE software. Combined with automated main-chain model building, the procedure produces a preliminary model suitable for refinement and extension by an experienced crystallographer

Automated fault-management in a simulated spaceflight micro-world

Science.gov (United States)

Lorenz, Bernd; Di Nocera, Francesco; Rottger, Stefan; Parasuraman, Raja

2002-01-01

BACKGROUND: As human spaceflight missions extend in duration and distance from Earth, a self-sufficient crew will bear far greater onboard responsibility and authority for mission success. This will increase the need for automated fault management (FM). Human factors issues in the use of such systems include maintenance of cognitive skill, situational awareness (SA), trust in automation, and workload. This study examine the human performance consequences of operator use of intelligent FM support in interaction with an autonomous, space-related, atmospheric control system. METHODS: An expert system representing a model-base reasoning agent supported operators at a low level of automation (LOA) by a computerized fault finding guide, at a medium LOA by an automated diagnosis and recovery advisory, and at a high LOA by automate diagnosis and recovery implementation, subject to operator approval or veto. Ten percent of the experimental trials involved complete failure of FM support. RESULTS: Benefits of automation were reflected in more accurate diagnoses, shorter fault identification time, and reduced subjective operator workload. Unexpectedly, fault identification times deteriorated more at the medium than at the high LOA during automation failure. Analyses of information sampling behavior showed that offloading operators from recovery implementation during reliable automation enabled operators at high LOA to engage in fault assessment activities CONCLUSIONS: The potential threat to SA imposed by high-level automation, in which decision advisories are automatically generated, need not inevitably be counteracted by choosing a lower LOA. Instead, freeing operator cognitive resources by automatic implementation of recover plans at a higher LOA can promote better fault comprehension, so long as the automation interface is designed to support efficient information sampling.

Completion of autobuilt protein models using a database of protein fragments

International Nuclear Information System (INIS)

Cowtan, Kevin

2012-01-01

Two developments in the process of automated protein model building in the Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules. Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature

Accurate determination of interfacial protein secondary structure by combining interfacial-sensitive amide I and amide III spectral signals.

Science.gov (United States)

Ye, Shuji; Li, Hongchun; Yang, Weilai; Luo, Yi

2014-01-29

Accurate determination of protein structures at the interface is essential to understand the nature of interfacial protein interactions, but it can only be done with a few, very limited experimental methods. Here, we demonstrate for the first time that sum frequency generation vibrational spectroscopy can unambiguously differentiate the interfacial protein secondary structures by combining surface-sensitive amide I and amide III spectral signals. This combination offers a powerful tool to directly distinguish random-coil (disordered) and α-helical structures in proteins. From a systematic study on the interactions between several antimicrobial peptides (including LKα14, mastoparan X, cecropin P1, melittin, and pardaxin) and lipid bilayers, it is found that the spectral profiles of the random-coil and α-helical structures are well separated in the amide III spectra, appearing below and above 1260 cm(-1), respectively. For the peptides with a straight backbone chain, the strength ratio for the peaks of the random-coil and α-helical structures shows a distinct linear relationship with the fraction of the disordered structure deduced from independent NMR experiments reported in the literature. It is revealed that increasing the fraction of negatively charged lipids can induce a conformational change of pardaxin from random-coil to α-helical structures. This experimental protocol can be employed for determining the interfacial protein secondary structures and dynamics in situ and in real time without extraneous labels.

Large scale identification and categorization of protein sequences using structured logistic regression

DEFF Research Database (Denmark)

Pedersen, Bjørn Panella; Ifrim, Georgiana; Liboriussen, Poul

2014-01-01

Abstract Background Structured Logistic Regression (SLR) is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well...... problem. Results Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known...... for further biochemical characterization and structural analysis....

Automated tool for virtual screening and pharmacology-based pathway prediction and analysis

Directory of Open Access Journals (Sweden)

Sugandh Kumar

2017-10-01

Full Text Available The virtual screening is an effective tool for the lead identification in drug discovery. However, there are limited numbers of crystal structures available as compared to the number of biological sequences which makes (Structure Based Drug Discovery SBDD a difficult choice. The current tool is an attempt to automate the protein structure modelling and automatic virtual screening followed by pharmacology-based prediction and analysis. Starting from sequence(s, this tool automates protein structure modelling, binding site identification, automated docking, ligand preparation, post docking analysis and identification of hits in the biological pathways that can be modulated by a group of ligands. This automation helps in the characterization of ligands selectivity and action of ligands on a complex biological molecular network as well as on individual receptor. The judicial combination of the ligands binding different receptors can be used to inhibit selective biological pathways in a disease. This tool also allows the user to systemically investigate network-dependent effects of a drug or drug candidate.

Cellular-automation fluids: A model for flow in porous media

International Nuclear Information System (INIS)

Rothman, D.H.

1987-01-01

Because the intrinsic inhomogeneity of porous media makes the application of proper boundary conditions difficult, fluid flow through microgeometric models has typically been achieved with idealized arrays of geometrically simple pores, throats, and cracks. The author proposes here an attractive alternative, capable of freely and accurately modeling fluid flow in grossly irregular geometries. This new method numerically solves the Navier-Stokes equations using the cellular-automation fluid model introduced by Frisch, Hasslacher, and Pomeau. The cellular-automation fluid is extraordinarily simple - particles of unit mass traveling with unit velocity reside on a triangular lattice and obey elementary collisions rules - but capable of modeling much of the rich complexity of real fluid flow. The author shows how cellular-automation fluids are applied to the study of porous media. In particular, he discusses issues of scale on the cellular-automation lattice and present the results of 2-D simulations, including numerical estimation of permeability and verification of Darcy's law

Automated extraction of radiation dose information from CT dose report images.

Science.gov (United States)

Li, Xinhua; Zhang, Da; Liu, Bob

2011-06-01

The purpose of this article is to describe the development of an automated tool for retrieving texts from CT dose report images. Optical character recognition was adopted to perform text recognitions of CT dose report images. The developed tool is able to automate the process of analyzing multiple CT examinations, including text recognition, parsing, error correction, and exporting data to spreadsheets. The results were precise for total dose-length product (DLP) and were about 95% accurate for CT dose index and DLP of scanned series.

Comparison of known food weights with image-based portion-size automated estimation and adolescents' self-reported portion size.

Science.gov (United States)

Lee, Christina D; Chae, Junghoon; Schap, TusaRebecca E; Kerr, Deborah A; Delp, Edward J; Ebert, David S; Boushey, Carol J

2012-03-01

Diet is a critical element of diabetes self-management. An emerging area of research is the use of images for dietary records using mobile telephones with embedded cameras. These tools are being designed to reduce user burden and to improve accuracy of portion-size estimation through automation. The objectives of this study were to (1) assess the error of automatically determined portion weights compared to known portion weights of foods and (2) to compare the error between automation and human. Adolescents (n = 15) captured images of their eating occasions over a 24 h period. All foods and beverages served were weighed. Adolescents self-reported portion sizes for one meal. Image analysis was used to estimate portion weights. Data analysis compared known weights, automated weights, and self-reported portions. For the 19 foods, the mean ratio of automated weight estimate to known weight ranged from 0.89 to 4.61, and 9 foods were within 0.80 to 1.20. The largest error was for lettuce and the most accurate was strawberry jam. The children were fairly accurate with portion estimates for two foods (sausage links, toast) using one type of estimation aid and two foods (sausage links, scrambled eggs) using another aid. The automated method was fairly accurate for two foods (sausage links, jam); however, the 95% confidence intervals for the automated estimates were consistently narrower than human estimates. The ability of humans to estimate portion sizes of foods remains a problem and a perceived burden. Errors in automated portion-size estimation can be systematically addressed while minimizing the burden on people. Future applications that take over the burden of these processes may translate to better diabetes self-management. © 2012 Diabetes Technology Society.

Construct validity and reliability of automated body reaction test ...

African Journals Online (AJOL)

Automated Body Reaction Test (ABRT) is a new device for skills and physical assessment instrument to measure ability on react, move quickly and accurately in accordance with stimulus. A total of 474 subjects aged 7-17 years old were randomly selected for the construct validity (n=330) and reliability (n=144). The ABRT ...

Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR).

Science.gov (United States)

Beller, Elaine; Clark, Justin; Tsafnat, Guy; Adams, Clive; Diehl, Heinz; Lund, Hans; Ouzzani, Mourad; Thayer, Kristina; Thomas, James; Turner, Tari; Xia, Jun; Robinson, Karen; Glasziou, Paul

2018-05-19

Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need to be able to work together, to exchange data and results. Therefore, we initiated the International Collaboration for the Automation of Systematic Reviews (ICASR), to successfully put all the parts of automation of systematic review production together. The first meeting was held in Vienna in October 2015. We established a set of principles to enable tools to be developed and integrated into toolkits.This paper sets out the principles devised at that meeting, which cover the need for improvement in efficiency of SR tasks, automation across the spectrum of SR tasks, continuous improvement, adherence to high quality standards, flexibility of use and combining components, the need for a collaboration and varied skills, the desire for open source, shared code and evaluation, and a requirement for replicability through rigorous and open evaluation.Automation has a great potential to improve the speed of systematic reviews. Considerable work is already being done on many of the steps involved in a review. The 'Vienna Principles' set out in this paper aim to guide a more coordinated effort which will allow the integration of work by separate teams and build on the experience, code and evaluations done by the many teams working across the globe.

Automated medical image segmentation techniques

Directory of Open Access Journals (Sweden)

Sharma Neeraj

2010-01-01

Full Text Available Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

Strep-Tagged Protein Purification.

Science.gov (United States)

Maertens, Barbara; Spriestersbach, Anne; Kubicek, Jan; Schäfer, Frank

2015-01-01

The Strep-tag system can be used to purify recombinant proteins from any expression system. Here, protocols for lysis and affinity purification of Strep-tagged proteins from E. coli, baculovirus-infected insect cells, and transfected mammalian cells are given. Depending on the amount of Strep-tagged protein in the lysate, a protocol for batch binding and subsequent washing and eluting by gravity flow can be used. Agarose-based matrices with the coupled Strep-Tactin ligand are the resins of choice, with a binding capacity of up to 9 mg ml(-1). For purification of lower amounts of Strep-tagged proteins, the use of Strep-Tactin magnetic beads is suitable. In addition, Strep-tagged protein purification can also be automated using prepacked columns for FPLC or other liquid-handling chromatography instrumentation, but automated purification is not discussed in this protocol. The protocols described here can be regarded as an update of the Strep-Tag Protein Handbook (Qiagen, 2009). © 2015 Elsevier Inc. All rights reserved.

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.

An automated approach to network features of protein structure ensembles

Science.gov (United States)

Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi

2013-01-01

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html. PMID:23934896

[Research and Design of a System for Detecting Automated External Defbrillator Performance Parameters].

Science.gov (United States)

Wang, Kewu; Xiao, Shengxiang; Jiang, Lina; Hu, Jingkai

2017-09-30

In order to regularly detect the performance parameters of automated external defibrillator (AED), to make sure it is safe before using the instrument, research and design of a system for detecting automated external defibrillator performance parameters. According to the research of the characteristics of its performance parameters, combing the STM32's stability and high speed with PWM modulation control, the system produces a variety of ECG normal and abnormal signals through the digital sampling methods. Completed the design of the hardware and software, formed a prototype. This system can accurate detect automated external defibrillator discharge energy, synchronous defibrillation time, charging time and other key performance parameters.

Serum protein concentrations from clinically healthy horses determined by agarose gel electrophoresis.

Science.gov (United States)

Riond, Barbara; Wenger-Riggenbach, Bettina; Hofmann-Lehmann, Regina; Lutz, Hans

2009-03-01

Serum protein electrophoresis is a useful screening test in equine laboratory medicine. The method can provide valuable information about changes in the concentrations of albumin and alpha-, beta-, and gamma-globulins and thereby help characterize dysproteinemias in equine patients. Reference values for horses using agarose gel as a support medium have not been reported. The purpose of this study was to establish reference intervals for serum protein concentrations in adult horses using agarose gel electrophoresis and to assess differences between warm-blooded and heavy draught horses. In addition, the precision of electrophoresis for determining fraction percentages and the detection limit were determined. Blood samples were obtained from 126 clinically healthy horses, including 105 Thoroughbreds and 21 heavy draught horses of both sexes and ranging from 2 to 20 years of age. The total protein concentration was determined by an automated biuret method. Serum protein electrophoresis was performed using a semi-automated agarose gel electrophoresis system. Coefficients of variation (CVs) were calculated for within-run and within-assay precision. Data from warm-blooded and draught horses were compared using the Mann-Whitney U test. Within-run and within-assay CVs were draught horses and so combined reference intervals (2.5-97.5%) were calculated for total protein (51.0-72.0 g/L), albumin (29.6-38.5 g/L), alpha(1)-globulin (1.9-3.1 g/L), alpha(2)-globulin (5.3-8.7 g/L), beta(1)-globulin (2.8-7.3g/L), beta(2)-globulin (2.2-6.0 g/L), and gamma-globulin (5.8-12.7 g/L) concentrations, and albumin/globulin ratio (0.93-1.65). Using agarose gel as the supporting matrix for serum protein electrophoresis in horses resulted in excellent resolution and accurate results that facilitated standardization into 6 protein fractions.

Comparison between manual and automated techniques for assessment of data from dynamic antral scintigraphy

International Nuclear Information System (INIS)

Misiara, Gustavo P.; Troncon, Luiz E.A.; Secaf, Marie; Moraes, Eder R.

2008-01-01

This work aimed at determining whether data from dynamic antral scintigraphy (DAS) yielded by a simple, manual technique are as accurate as those generated by a conventional automated technique (fast Fourier transform) for assessing gastric contractility. Seventy-one stretches (4 min) of 'activity versus time' curves obtained by DAS from 10 healthy volunteers and 11 functional dyspepsia patients, after ingesting a liquid meal (320 ml, 437 kcal) labeled with technetium-99m ( 99m Tc)-phytate, were independently analyzed by manual and automated techniques. Data obtained by both techniques for the frequency of antral contractions were similar. Contraction amplitude determined by the manual technique was significantly higher than that estimated by the automated method, in both patients and controls. The contraction frequency 30 min post-meal was significantly lower in patients than in controls, which was correctly shown by both techniques. A manual technique using ordinary resources of the gamma camera workstation, despite yielding higher figures for the amplitude of gastric contractions, is as accurate as the conventional automated technique of DAS analysis. These findings may favor a more intensive use of DAS coupled to gastric emptying studies, which would provide a more comprehensive assessment of gastric motor function in disease. (author)

Automated side-chain model building and sequence assignment by template matching.

Science.gov (United States)

Terwilliger, Thomas C

2003-01-01

An algorithm is described for automated building of side chains in an electron-density map once a main-chain model is built and for alignment of the protein sequence to the map. The procedure is based on a comparison of electron density at the expected side-chain positions with electron-density templates. The templates are constructed from average amino-acid side-chain densities in 574 refined protein structures. For each contiguous segment of main chain, a matrix with entries corresponding to an estimate of the probability that each of the 20 amino acids is located at each position of the main-chain model is obtained. The probability that this segment corresponds to each possible alignment with the sequence of the protein is estimated using a Bayesian approach and high-confidence matches are kept. Once side-chain identities are determined, the most probable rotamer for each side chain is built into the model. The automated procedure has been implemented in the RESOLVE software. Combined with automated main-chain model building, the procedure produces a preliminary model suitable for refinement and extension by an experienced crystallographer.

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.

Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

Directory of Open Access Journals (Sweden)

Niklas Berliner

Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.

Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images

NARCIS (Netherlands)

Lee, K.; Buitendijk, G.H.; Bogunovic, H.; Springelkamp, H.; Hofman, A.; Wahle, A.; Sonka, M.; Vingerling, J.R.; Klaver, C.C.W.; Abramoff, M.D.

2016-01-01

PURPOSE: To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies. METHODS: Six hundred ninety macular SD-OCT image volumes (6.0 x 6.0 x 2.3 mm3)

Is automated kinetic measurement superior to end-point for advanced oxidation protein product?

Science.gov (United States)

Oguz, Osman; Inal, Berrin Bercik; Emre, Turker; Ozcan, Oguzhan; Altunoglu, Esma; Oguz, Gokce; Topkaya, Cigdem; Guvenen, Guvenc

2014-01-01

Advanced oxidation protein product (AOPP) was first described as an oxidative protein marker in chronic uremic patients and measured with a semi-automatic end-point method. Subsequently, the kinetic method was introduced for AOPP assay. We aimed to compare these two methods by adapting them to a chemistry analyzer and to investigate the correlation between AOPP and fibrinogen, the key molecule responsible for human plasma AOPP reactivity, microalbumin, and HbA1c in patients with type II diabetes mellitus (DM II). The effects of EDTA and citrate-anticogulated tubes on these two methods were incorporated into the study. This study included 93 DM II patients (36 women, 57 men) with HbA1c levels > or = 7%, who were admitted to the diabetes and nephrology clinics. The samples were collected in EDTA and in citrate-anticoagulated tubes. Both methods were adapted to a chemistry analyzer and the samples were studied in parallel. In both types of samples, we found a moderate correlation between the kinetic and the endpoint methods (r = 0.611 for citrate-anticoagulated, r = 0.636 for EDTA-anticoagulated, p = 0.0001 for both). We found a moderate correlation between fibrinogen-AOPP and microalbumin-AOPP levels only in the kinetic method (r = 0.644 and 0.520 for citrate-anticoagulated; r = 0.581 and 0.490 for EDTA-anticoagulated, p = 0.0001). We conclude that adaptation of the end-point method to automation is more difficult and it has higher between-run CV% while application of the kinetic method is easier and it may be used in oxidative stress studies.

Automated measurement of office, home and ambulatory blood pressure in atrial fibrillation.

Science.gov (United States)

Kollias, Anastasios; Stergiou, George S

2014-01-01

1. Hypertension and atrial fibrillation (AF) often coexist and are strong risk factors for stroke. Current guidelines for blood pressure (BP) measurement in AF recommend repeated measurements using the auscultatory method, whereas the accuracy of the automated devices is regarded as questionable. This review presents the current evidence on the feasibility and accuracy of automated BP measurement in the presence of AF and the potential for automated detection of undiagnosed AF during such measurements. 2. Studies evaluating the use of automated BP monitors in AF are limited and have significant heterogeneity in methodology and protocols. Overall, the oscillometric method is feasible for static (office or home) and ambulatory use and appears to be more accurate for systolic than diastolic BP measurement. 3. Given that systolic hypertension is particularly common and important in the elderly, the automated BP measurement method may be acceptable for self-home and ambulatory monitoring, but not for professional office or clinic measurement. 4. An embedded algorithm for the detection of asymptomatic AF during routine automated BP measurement with high diagnostic accuracy has been developed and appears to be a useful screening tool for elderly hypertensives. © 2013 Wiley Publishing Asia Pty Ltd.

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions.

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Saha, Tanumoy; Rathmann, Isabel; Galic, Milos

2017-07-11

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

Use of refractometry for determination of psittacine plasma protein concentration.

Science.gov (United States)

Cray, Carolyn; Rodriguez, Marilyn; Arheart, Kristopher L

2008-12-01

Previous studies have demonstrated both poor and good correlation of total protein concentrations in various avian species using refractometry and biuret methodologies. The purpose of the current study was to compare these 2 techniques of total protein determination using plasma samples from several psittacine species and to determine the effect of cholesterol and other solutes on refractometry results. Total protein concentration in heparinized plasma samples without visible lipemia was analyzed by refractometry and an automated biuret method on a dry reagent analyzer (Ortho 250). Cholesterol, glucose, and uric acid concentrations were measured using the same analyzer. Results were compared using Deming regression analysis, Bland-Altman bias plots, and Spearman's rank correlation. Correlation coefficients (r) for total protein results by refractometry and biuret methods were 0.49 in African grey parrots (n=28), 0.77 in Amazon parrots (20), 0.57 in cockatiels (20), 0.73 in cockatoos (36), 0.86 in conures (20), and 0.93 in macaws (38) (Prefractometry in Amazon parrots, conures, and macaws (n=25 each, PRefractometry can be used to accurately measure total protein concentration in nonlipemic plasma samples from some psittacine species. Method and species-specific reference intervals should be used in the interpretation of total protein values.

Altering user' acceptance of automation through prior automation exposure.

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Bekier, Marek; Molesworth, Brett R C

2017-06-01

Air navigation service providers worldwide see increased use of automation as one solution to overcome the capacity constraints imbedded in the present air traffic management (ATM) system. However, increased use of automation within any system is dependent on user acceptance. The present research sought to determine if the point at which an individual is no longer willing to accept or cooperate with automation can be manipulated. Forty participants underwent training on a computer-based air traffic control programme, followed by two ATM exercises (order counterbalanced), one with and one without the aid of automation. Results revealed after exposure to a task with automation assistance, user acceptance of high(er) levels of automation ('tipping point') decreased; suggesting it is indeed possible to alter automation acceptance. Practitioner Summary: This paper investigates whether the point at which a user of automation rejects automation (i.e. 'tipping point') is constant or can be manipulated. The results revealed after exposure to a task with automation assistance, user acceptance of high(er) levels of automation decreased; suggesting it is possible to alter automation acceptance.

IMAGE CONSTRUCTION TO AUTOMATION OF PROJECTIVE TECHNIQUES FOR PSYCHOPHYSIOLOGICAL ANALYSIS

Directory of Open Access Journals (Sweden)

Natalia Pavlova

2018-04-01

Full Text Available The search for a solution of automation of the process of assessment of a psychological analysis of the person drawings created by it from an available set of some templates are presented at this article. It will allow to reveal more effectively infringements of persons mentality. In particular, such decision can be used for work with children who possess the developed figurative thinking, but are not yet capable of an accurate statement of the thoughts and experiences. For automation of testing by using a projective method, we construct interactive environment for visualization of compositions of the several images and then analyse

Automated brain structure segmentation based on atlas registration and appearance models

DEFF Research Database (Denmark)

van der Lijn, Fedde; de Bruijne, Marleen; Klein, Stefan

2012-01-01

Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic resonance images that combines information about a structure’s location and appearance. The spatial...... with different magnetic resonance sequences, in which the hippocampus and cerebellum were segmented by an expert. Furthermore, the method is compared to two other segmentation techniques that were applied to the same data. Results show that the atlas- and appearance-based method produces accurate results...

Development of an automated asbestos counting software based on fluorescence microscopy.

Science.gov (United States)

Alexandrov, Maxym; Ichida, Etsuko; Nishimura, Tomoki; Aoki, Kousuke; Ishida, Takenori; Hirota, Ryuichi; Ikeda, Takeshi; Kawasaki, Tetsuo; Kuroda, Akio

2015-01-01

An emerging alternative to the commonly used analytical methods for asbestos analysis is fluorescence microscopy (FM), which relies on highly specific asbestos-binding probes to distinguish asbestos from interfering non-asbestos fibers. However, all types of microscopic asbestos analysis require laborious examination of large number of fields of view and are prone to subjective errors and large variability between asbestos counts by different analysts and laboratories. A possible solution to these problems is automated counting of asbestos fibers by image analysis software, which would lower the cost and increase the reliability of asbestos testing. This study seeks to develop a fiber recognition and counting software for FM-based asbestos analysis. We discuss the main features of the developed software and the results of its testing. Software testing showed good correlation between automated and manual counts for the samples with medium and high fiber concentrations. At low fiber concentrations, the automated counts were less accurate, leading us to implement correction mode for automated counts. While the full automation of asbestos analysis would require further improvements in accuracy of fiber identification, the developed software could already assist professional asbestos analysts and record detailed fiber dimensions for the use in epidemiological research.

ProDaMa: an open source Python library to generate protein structure datasets.

Science.gov (United States)

Armano, Giuliano; Manconi, Andrea

2009-10-02

The huge difference between the number of known sequences and known tertiary structures has justified the use of automated methods for protein analysis. Although a general methodology to solve these problems has not been yet devised, researchers are engaged in developing more accurate techniques and algorithms whose training plays a relevant role in determining their performance. From this perspective, particular importance is given to the training data used in experiments, and researchers are often engaged in the generation of specialized datasets that meet their requirements. To facilitate the task of generating specialized datasets we devised and implemented ProDaMa, an open source Python library than provides classes for retrieving, organizing, updating, analyzing, and filtering protein data. ProDaMa has been used to generate specialized datasets useful for secondary structure prediction and to develop a collaborative web application aimed at generating and sharing protein structure datasets. The library, the related database, and the documentation are freely available at the URL http://iasc.diee.unica.it/prodama.

Fast and Accurate Approaches for Large-Scale, Automated Mapping of Food Diaries on Food Composition Tables

Directory of Open Access Journals (Sweden)

Marc Lamarine

2018-05-01

Full Text Available Aim of Study: The use of weighed food diaries in nutritional studies provides a powerful method to quantify food and nutrient intakes. Yet, mapping these records onto food composition tables (FCTs is a challenging, time-consuming and error-prone process. Experts make this effort manually and no automation has been previously proposed. Our study aimed to assess automated approaches to map food items onto FCTs.Methods: We used food diaries (~170,000 records pertaining to 4,200 unique food items from the DiOGenes randomized clinical trial. We attempted to map these items onto six FCTs available from the EuroFIR resource. Two approaches were tested: the first was based solely on food name similarity (fuzzy matching. The second used a machine learning approach (C5.0 classifier combining both fuzzy matching and food energy. We tested mapping food items using their original names and also an English-translation. Top matching pairs were reviewed manually to derive performance metrics: precision (the percentage of correctly mapped items and recall (percentage of mapped items.Results: The simpler approach: fuzzy matching, provided very good performance. Under a relaxed threshold (score > 50%, this approach enabled to remap 99.49% of the items with a precision of 88.75%. With a slightly more stringent threshold (score > 63%, the precision could be significantly improved to 96.81% while keeping a recall rate > 95% (i.e., only 5% of the queried items would not be mapped. The machine learning approach did not lead to any improvements compared to the fuzzy matching. However, it could increase substantially the recall rate for food items without any clear equivalent in the FCTs (+7 and +20% when mapping items using their original or English-translated names. Our approaches have been implemented as R packages and are freely available from GitHub.Conclusion: This study is the first to provide automated approaches for large-scale food item mapping onto FCTs. We

Automated smartphone audiometry: Validation of a word recognition test app.

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Dewyer, Nicholas A; Jiradejvong, Patpong; Henderson Sabes, Jennifer; Limb, Charles J

2018-03-01

Develop and validate an automated smartphone word recognition test. Cross-sectional case-control diagnostic test comparison. An automated word recognition test was developed as an app for a smartphone with earphones. English-speaking adults with recent audiograms and various levels of hearing loss were recruited from an audiology clinic and were administered the smartphone word recognition test. Word recognition scores determined by the smartphone app and the gold standard speech audiometry test performed by an audiologist were compared. Test scores for 37 ears were analyzed. Word recognition scores determined by the smartphone app and audiologist testing were in agreement, with 86% of the data points within a clinically acceptable margin of error and a linear correlation value between test scores of 0.89. The WordRec automated smartphone app accurately determines word recognition scores. 3b. Laryngoscope, 128:707-712, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Automated quantitative assessment of proteins' biological function in protein knowledge bases.

Science.gov (United States)

Mayr, Gabriele; Lepperdinger, Günter; Lackner, Peter

2008-01-01

Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Automated Quantitative Assessment of Proteins' Biological Function in Protein Knowledge Bases

Directory of Open Access Journals (Sweden)

Gabriele Mayr

2008-01-01

Full Text Available Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Automated kidney morphology measurements from ultrasound images using texture and edge analysis

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Ravishankar, Hariharan; Annangi, Pavan; Washburn, Michael; Lanning, Justin

2016-04-01

In a typical ultrasound scan, a sonographer measures Kidney morphology to assess renal abnormalities. Kidney morphology can also help to discriminate between chronic and acute kidney failure. The caliper placements and volume measurements are often time consuming and an automated solution will help to improve accuracy, repeatability and throughput. In this work, we developed an automated Kidney morphology measurement solution from long axis Ultrasound scans. Automated kidney segmentation is challenging due to wide variability in kidney shape, size, weak contrast of the kidney boundaries and presence of strong edges like diaphragm, fat layers. To address the challenges and be able to accurately localize and detect kidney regions, we present a two-step algorithm that makes use of edge and texture information in combination with anatomical cues. First, we use an edge analysis technique to localize kidney region by matching the edge map with predefined templates. To accurately estimate the kidney morphology, we use textural information in a machine learning algorithm framework using Haar features and Gradient boosting classifier. We have tested the algorithm on 45 unseen cases and the performance against ground truth is measured by computing Dice overlap, % error in major and minor axis of kidney. The algorithm shows successful performance on 80% cases.

Automated analysis of high-content microscopy data with deep learning.

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Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins.

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Reddy, Jithender G; Kumar, Dinesh; Hosur, Ramakrishna V

2015-02-01

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.

Toward fully automated genotyping: Genotyping microsatellite markers by deconvolution

Energy Technology Data Exchange (ETDEWEB)

Perlin, M.W.; Lancia, G.; See-Kiong, Ng [Carnegie Mellon Univ., Pittsburgh, PA (United States)

1995-11-01

Dense genetic linkage maps have been constructed for the human and mouse genomes, with average densities of 2.9 cM and 0.35 cM, respectively. These genetic maps are crucial for mapping both Mendelian and complex traits and are useful in clinical genetic diagnosis. Current maps are largely comprised of abundant, easily assayed, and highly polymorphic PCR-based microsatellite markers, primarily dinucleotide (CA){sub n} repeats. One key limitation of these length polymorphisms is the PCR stutter (or slippage) artifact that introduces additional stutter bands. With two (or more) closely spaced alleles, the stutter bands overlap, and it is difficult to accurately determine the correct alleles; this stutter phenomenon has all but precluded full automation, since a human must visually inspect the allele data. We describe here novel deconvolution methods for accurate genotyping that mathematically remove PCR stutter artifact from microsatellite markers. These methods overcome the manual interpretation bottleneck and thereby enable full automation of genetic map construction and use. New functionalities, including the pooling of DNAs and the pooling of markers, are described that may greatly reduce the associated experimentation requirements. 32 refs., 5 figs., 3 tabs.

Automated Localization of Multiple Pelvic Bone Structures on MRI.

Science.gov (United States)

Onal, Sinan; Lai-Yuen, Susana; Bao, Paul; Weitzenfeld, Alfredo; Hart, Stuart

2016-01-01

In this paper, we present a fully automated localization method for multiple pelvic bone structures on magnetic resonance images (MRI). Pelvic bone structures are at present identified manually on MRI to locate reference points for measurement and evaluation of pelvic organ prolapse (POP). Given that this is a time-consuming and subjective procedure, there is a need to localize pelvic bone structures automatically. However, bone structures are not easily differentiable from soft tissue on MRI as their pixel intensities tend to be very similar. In this paper, we present a model that combines support vector machines and nonlinear regression capturing global and local information to automatically identify the bounding boxes of bone structures on MRI. The model identifies the location of the pelvic bone structures by establishing the association between their relative locations and using local information such as texture features. Results show that the proposed method is able to locate the bone structures of interest accurately (dice similarity index >0.75) in 87-91% of the images. This research aims to enable accurate, consistent, and fully automated localization of bone structures on MRI to facilitate and improve the diagnosis of health conditions such as female POP.

G2S: A web-service for annotating genomic variants on 3D protein structures.

Science.gov (United States)

Wang, Juexin; Sheridan, Robert; Sumer, S Onur; Schultz, Nikolaus; Xu, Dong; Gao, Jianjiong

2018-01-27

Accurately mapping and annotating genomic locations on 3D protein structures is a key step in structure-based analysis of genomic variants detected by recent large-scale sequencing efforts. There are several mapping resources currently available, but none of them provides a web API (Application Programming Interface) that support programmatic access. We present G2S, a real-time web API that provides automated mapping of genomic variants on 3D protein structures. G2S can align genomic locations of variants, protein locations, or protein sequences to protein structures and retrieve the mapped residues from structures. G2S API uses REST-inspired design conception and it can be used by various clients such as web browsers, command terminals, programming languages and other bioinformatics tools for bringing 3D structures into genomic variant analysis. The webserver and source codes are freely available at https://g2s.genomenexus.org. g2s@genomenexus.org. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Importance of molecular diagnosis in the accurate diagnosis of ...

Indian Academy of Sciences (India)

1Department of Health and Environmental Sciences, Kyoto University Graduate School of Medicine, Yoshida Konoecho, ... of molecular diagnosis in the accurate diagnosis of systemic carnitine deficiency. .... 'affecting protein function' by SIFT.

Current status and future prospects of an automated sample exchange system PAM for protein crystallography

Science.gov (United States)

Hiraki, M.; Yamada, Y.; Chavas, L. M. G.; Matsugaki, N.; Igarashi, N.; Wakatsuki, S.

2013-03-01

To achieve fully-automated and/or remote data collection in high-throughput X-ray experiments, the Structural Biology Research Centre at the Photon Factory (PF) has installed PF automated mounting system (PAM) for sample exchange robots at PF macromolecular crystallography beamlines BL-1A, BL-5A, BL-17A, AR-NW12A and AR-NE3A. We are upgrading the experimental systems, including the PAM for stable and efficient operation. To prevent human error in automated data collection, we installed a two-dimensional barcode reader for identification of the cassettes and sample pins. Because no liquid nitrogen pipeline in the PF experimental hutch is installed, the users commonly add liquid nitrogen using a small Dewar. To address this issue, an automated liquid nitrogen filling system that links a 100-liter tank to the robot Dewar has been installed on the PF macromolecular beamline. Here we describe this new implementation, as well as future prospects.

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

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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

Accurate predictions for the LHC made easy

CERN Multimedia

CERN. Geneva

2014-01-01

The data recorded by the LHC experiments is of a very high quality. To get the most out of the data, precise theory predictions, including uncertainty estimates, are needed to reduce as much as possible theoretical bias in the experimental analyses. Recently, significant progress has been made in computing Next-to-Leading Order (NLO) computations, including matching to the parton shower, that allow for these accurate, hadron-level predictions. I shall discuss one of these efforts, the MadGraph5_aMC@NLO program, that aims at the complete automation of predictions at the NLO accuracy within the SM as well as New Physics theories. I’ll illustrate some of the theoretical ideas behind this program, show some selected applications to LHC physics, as well as describe the future plans.

An OGA-Resistant Probe Allows Specific Visualization and Accurate Identification of O-GlcNAc-Modified Proteins in Cells.

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Li, Jing; Wang, Jiajia; Wen, Liuqing; Zhu, He; Li, Shanshan; Huang, Kenneth; Jiang, Kuan; Li, Xu; Ma, Cheng; Qu, Jingyao; Parameswaran, Aishwarya; Song, Jing; Zhao, Wei; Wang, Peng George

2016-11-18

O-linked β-N-acetyl-glucosamine (O-GlcNAc) is an essential and ubiquitous post-translational modification present in nucleic and cytoplasmic proteins of multicellular eukaryotes. The metabolic chemical probes such as GlcNAc or GalNAc analogues bearing ketone or azide handles, in conjunction with bioorthogonal reactions, provide a powerful approach for detecting and identifying this modification. However, these chemical probes either enter multiple glycosylation pathways or have low labeling efficiency. Therefore, selective and potent probes are needed to assess this modification. We report here the development of a novel probe, 1,3,6-tri-O-acetyl-2-azidoacetamido-2,4-dideoxy-d-glucopyranose (Ac 3 4dGlcNAz), that can be processed by the GalNAc salvage pathway and transferred by O-GlcNAc transferase (OGT) to O-GlcNAc proteins. Due to the absence of a hydroxyl group at C4, this probe is less incorporated into α/β 4-GlcNAc or GalNAc containing glycoconjugates. Furthermore, the O-4dGlcNAz modification was resistant to the hydrolysis of O-GlcNAcase (OGA), which greatly enhanced the efficiency of incorporation for O-GlcNAcylation. Combined with a click reaction, Ac 3 4dGlcNAz allowed the selective visualization of O-GlcNAc in cells and accurate identification of O-GlcNAc-modified proteins with LC-MS/MS. This probe represents a more potent and selective tool in tracking, capturing, and identifying O-GlcNAc-modified proteins in cells and cell lysates.

Improving the driver-automation interaction: an approach using automation uncertainty.

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Beller, Johannes; Heesen, Matthias; Vollrath, Mark

2013-12-01

The aim of this study was to evaluate whether communicating automation uncertainty improves the driver-automation interaction. A false system understanding of infallibility may provoke automation misuse and can lead to severe consequences in case of automation failure. The presentation of automation uncertainty may prevent this false system understanding and, as was shown by previous studies, may have numerous benefits. Few studies, however, have clearly shown the potential of communicating uncertainty information in driving. The current study fills this gap. We conducted a driving simulator experiment, varying the presented uncertainty information between participants (no uncertainty information vs. uncertainty information) and the automation reliability (high vs.low) within participants. Participants interacted with a highly automated driving system while engaging in secondary tasks and were required to cooperate with the automation to drive safely. Quantile regressions and multilevel modeling showed that the presentation of uncertainty information increases the time to collision in the case of automation failure. Furthermore, the data indicated improved situation awareness and better knowledge of fallibility for the experimental group. Consequently, the automation with the uncertainty symbol received higher trust ratings and increased acceptance. The presentation of automation uncertaintythrough a symbol improves overall driver-automation cooperation. Most automated systems in driving could benefit from displaying reliability information. This display might improve the acceptance of fallible systems and further enhances driver-automation cooperation.

Photogrammetric approach to automated checking of DTMs

DEFF Research Database (Denmark)

Potucková, Marketa

2005-01-01

Geometrically accurate digital terrain models (DTMs) are essential for orthoimage production and many other applications. Collecting reference data or visual inspection are reliable but time consuming and therefore expensive methods for finding errors in DTMs. In this paper, a photogrammetric...... approach to automated checking and improving of DTMs is evaluated. Corresponding points in two overlapping orthoimages are found by means of area based matching. Provided the image orientation is correct, discovered displacements correspond to DTM errors. Improvements of the method regarding its...

EpHLA software: a timesaving and accurate tool for improving identification of acceptable mismatches for clinical purposes.

Science.gov (United States)

Filho, Herton Luiz Alves Sales; da Mata Sousa, Luiz Claudio Demes; von Glehn, Cristina de Queiroz Carrascosa; da Silva, Adalberto Socorro; dos Santos Neto, Pedro de Alcântara; do Nascimento, Ferraz; de Castro, Adail Fonseca; do Nascimento, Liliane Machado; Kneib, Carolina; Bianchi Cazarote, Helena; Mayumi Kitamura, Daniele; Torres, Juliane Roberta Dias; da Cruz Lopes, Laiane; Barros, Aryela Loureiro; da Silva Edlin, Evelin Nildiane; de Moura, Fernanda Sá Leal; Watanabe, Janine Midori Figueiredo; do Monte, Semiramis Jamil Hadad

2012-06-01

The HLAMatchmaker algorithm, which allows the identification of “safe” acceptable mismatches (AMMs) for recipients of solid organ and cell allografts, is rarely used in part due to the difficulty in using it in the current Excel format. The automation of this algorithm may universalize its use to benefit the allocation of allografts. Recently, we have developed a new software called EpHLA, which is the first computer program automating the use of the HLAMatchmaker algorithm. Herein, we present the experimental validation of the EpHLA program by showing the time efficiency and the quality of operation. The same results, obtained by a single antigen bead assay with sera from 10 sensitized patients waiting for kidney transplants, were analyzed either by conventional HLAMatchmaker or by automated EpHLA method. Users testing these two methods were asked to record: (i) time required for completion of the analysis (in minutes); (ii) number of eplets obtained for class I and class II HLA molecules; (iii) categorization of eplets as reactive or non-reactive based on the MFI cutoff value; and (iv) determination of AMMs based on eplets' reactivities. We showed that although both methods had similar accuracy, the automated EpHLA method was over 8 times faster in comparison to the conventional HLAMatchmaker method. In particular the EpHLA software was faster and more reliable but equally accurate as the conventional method to define AMMs for allografts. The EpHLA software is an accurate and quick method for the identification of AMMs and thus it may be a very useful tool in the decision-making process of organ allocation for highly sensitized patients as well as in many other applications.

Designing of smart home automation system based on Raspberry Pi

Science.gov (United States)

Saini, Ravi Prakash; Singh, Bhanu Pratap; Sharma, Mahesh Kumar; Wattanawisuth, Nattapol; Leeprechanon, Nopbhorn

2016-03-01

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning "on" and "off" of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

Towards an Automated Acoustic Detection System for Free Ranging Elephants.

Science.gov (United States)

Zeppelzauer, Matthias; Hensman, Sean; Stoeger, Angela S

The human-elephant conflict is one of the most serious conservation problems in Asia and Africa today. The involuntary confrontation of humans and elephants claims the lives of many animals and humans every year. A promising approach to alleviate this conflict is the development of an acoustic early warning system. Such a system requires the robust automated detection of elephant vocalizations under unconstrained field conditions. Today, no system exists that fulfills these requirements. In this paper, we present a method for the automated detection of elephant vocalizations that is robust to the diverse noise sources present in the field. We evaluate the method on a dataset recorded under natural field conditions to simulate a real-world scenario. The proposed method outperformed existing approaches and robustly and accurately detected elephants. It thus can form the basis for a future automated early warning system for elephants. Furthermore, the method may be a useful tool for scientists in bioacoustics for the study of wildlife recordings.

Active machine learning-driven experimentation to determine compound effects on protein patterns.

Science.gov (United States)

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-02-03

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.

Transitioning to future air traffic management: effects of imperfect automation on controller attention and performance.

Science.gov (United States)

Rovira, Ericka; Parasuraman, Raja

2010-06-01

This study examined whether benefits of conflict probe automation would occur in a future air traffic scenario in which air traffic service providers (ATSPs) are not directly responsible for freely maneuvering aircraft but are controlling other nonequipped aircraft (mixed-equipage environment). The objective was to examine how the type of automation imperfection (miss vs. false alarm) affects ATSP performance and attention allocation. Research has shown that the type of automation imperfection leads to differential human performance costs. Participating in four 30-min scenarios were 12 full-performance-level ATSPs. Dependent variables included conflict detection and resolution performance, eye movements, and subjective ratings of trust and self confidence. ATSPs detected conflicts faster and more accurately with reliable automation, as compared with manual performance. When the conflict probe automation was unreliable, conflict detection performance declined with both miss (25% conflicts detected) and false alarm automation (50% conflicts detected). When the primary task of conflict detection was automated, even highly reliable yet imperfect automation (miss or false alarm) resulted in serious negative effects on operator performance. The further in advance that conflict probe automation predicts a conflict, the greater the uncertainty of prediction; thus, designers should provide users with feedback on the state of the automation or other tools that allow for inspection and analysis of the data underlying the conflict probe algorithm.

Automated hardwood lumber grading utilizing a multiple sensor machine vision technology

Science.gov (United States)

D. Earl Kline; Chris Surak; Philip A. Araman

2003-01-01

Over the last 10 years, scientists at the Thomas M. Brooks Forest Products Center, the Bradley Department of Electrical and Computer Engineering, and the USDA Forest Service have been working on lumber scanning systems that can accurately locate and identify defects in hardwood lumber. Current R&D efforts are targeted toward developing automated lumber grading...

Automated Selection of Hotspots (ASH): enhanced automated segmentation and adaptive step finding for Ki67 hotspot detection in adrenal cortical cancer.

Science.gov (United States)

Lu, Hao; Papathomas, Thomas G; van Zessen, David; Palli, Ivo; de Krijger, Ronald R; van der Spek, Peter J; Dinjens, Winand N M; Stubbs, Andrew P

2014-11-25

In prognosis and therapeutics of adrenal cortical carcinoma (ACC), the selection of the most active areas in proliferative rate (hotspots) within a slide and objective quantification of immunohistochemical Ki67 Labelling Index (LI) are of critical importance. In addition to intratumoral heterogeneity in proliferative rate i.e. levels of Ki67 expression within a given ACC, lack of uniformity and reproducibility in the method of quantification of Ki67 LI may confound an accurate assessment of Ki67 LI. We have implemented an open source toolset, Automated Selection of Hotspots (ASH), for automated hotspot detection and quantification of Ki67 LI. ASH utilizes NanoZoomer Digital Pathology Image (NDPI) splitter to convert the specific NDPI format digital slide scanned from the Hamamatsu instrument into a conventional tiff or jpeg format image for automated segmentation and adaptive step finding hotspots detection algorithm. Quantitative hotspot ranking is provided by the functionality from the open source application ImmunoRatio as part of the ASH protocol. The output is a ranked set of hotspots with concomitant quantitative values based on whole slide ranking. We have implemented an open source automated detection quantitative ranking of hotspots to support histopathologists in selecting the 'hottest' hotspot areas in adrenocortical carcinoma. To provide wider community easy access to ASH we implemented a Galaxy virtual machine (VM) of ASH which is available from http://bioinformatics.erasmusmc.nl/wiki/Automated_Selection_of_Hotspots . The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_216.

A study on an automated computerized differential diagnosis of diffuse liver diseases, based only on hepatic scintigrams using sup(99m)Tc-Sn-colloid

International Nuclear Information System (INIS)

Matsuo, Michimasa; Fujii, Susumu; Kaneda, Yukio

1980-01-01

Hepatic scintigrams using sup(99m)Tc-compounds are now routinely performed. In this study, automated computerized pattern characterizations of right lateral hepatic scintigrams using sup(99m)Tc-Sn colloid were studied to extract characteristic indicators, which are effective for an automated computerized differential diagnosis. The program, developed by us, of the automated computerized pattern characterization and the automated computerized differential diagnosis can be performed without the aid of professional doctors' ability of pattern recognition. The right lateral hepatic scintigrams of fifty one cases, which are accurately diagnosed by biopsy, are applied as the training group. The results of the automated computerized differential diagnosis were as follows: Three cases were accurately diagnosed among 3 normal cases; Three among 3 acute hepatitis; Seven among 7 chronic inactive hepatitis; Twenty among 22 chronic active hepatitis; Sixteen among 16 liver cirrhosis. Only two cases of chronic active hepatitis are falsely-diagnosed as chronic inactive hepatitis and as liver cirrhosis respectively. The over all accuracy rate was 96% in the training group. With this result, the automated computerized differential diagnosis of diffuse liver diseases is suggested to be possible, based on the hepatic scintigram. (author)

Automated Classification of Consumer Health Information Needs in Patient Portal Messages.

Science.gov (United States)

Cronin, Robert M; Fabbri, Daniel; Denny, Joshua C; Jackson, Gretchen Purcell

2015-01-01

Patients have diverse health information needs, and secure messaging through patient portals is an emerging means by which such needs are expressed and met. As patient portal adoption increases, growing volumes of secure messages may burden healthcare providers. Automated classification could expedite portal message triage and answering. We created four automated classifiers based on word content and natural language processing techniques to identify health information needs in 1000 patient-generated portal messages. Logistic regression and random forest classifiers detected single information needs well, with area under the curves of 0.804-0.914. A logistic regression classifier accurately found the set of needs within a message, with a Jaccard index of 0.859 (95% Confidence Interval: (0.847, 0.871)). Automated classification of consumer health information needs expressed in patient portal messages is feasible and may allow direct linking to relevant resources or creation of institutional resources for commonly expressed needs.

Development and application of the automated Monte Carlo biasing procedure in SAS4

International Nuclear Information System (INIS)

Tang, J.S.; Broadhead, B.L.

1993-01-01

An automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete-ordinates calculation are used to generate biasing parameters for a three-dimensional Monte Carlo calculation. The automated procedure consisting of cross-section processing, adjoint flux determination, biasing parameter generation, and the initiation of a MORSE-SGC/S Monte Carlo calculation has been implemented in the SAS4 module of the SCALE computer code system. The automated procedure has been used extensively in the investigation of both computational and experimental benchmarks for the NEACRP working group on shielding assessment of transportation packages. The results of these studies indicate that with the automated biasing procedure, Monte Carlo shielding calculations of spent fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost. The systematic biasing approach described in this paper can also be applied to other similar shielding problems

Usefulness of automated biopsy guns in image-guided biopsy

International Nuclear Information System (INIS)

Lee, Jung Hyung; Rhee, Chang Soo; Lee, Sung Moon; Kim, Hong; Woo, Sung Ku; Suh, Soo Jhi

1994-01-01

To evaluate the usefulness of automated biopsy guns in image-guided biopsy of lung, liver, pancreas and other organs. Using automated biopsy devices, 160 biopsies of variable anatomic sites were performed: Biopsies were performed under ultrasonographic(US) guidance in 95 and computed tomographic (CT) guidance in 65. We retrospectively analyzed histologic results and complications. Specimens were adequate for histopathologic diagnosis in 143 of the 160 patients(89.4%)-Diagnostic tissue was obtained in 130 (81.3%), suggestive tissue obtained in 13(8.1%), and non-diagnostic tissue was obtained in 14(8.7%). Inadequate tissue was obtained in only 3(1.9%). There was no statistically significant difference between US-guided and CT-guided percutaneous biopsy. There was no occurrence of significant complication. We have experienced mild complications in only 5 patients-2 hematuria and 2 hematochezia in transrectal prostatic biopsy, and 1 minimal pneumothorax in CT-guided percutaneous lung biopsy. All of them were resolved spontaneously. The image-guided biopsy using the automated biopsy gun was a simple, safe and accurate method of obtaining adequate specimen for the histopathologic diagnosis

Usefulness of automated biopsy guns in image-guided biopsy

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Hyung; Rhee, Chang Soo; Lee, Sung Moon; Kim, Hong; Woo, Sung Ku; Suh, Soo Jhi [School of Medicine, Keimyung University, Daegu (Korea, Republic of)

1994-12-15

To evaluate the usefulness of automated biopsy guns in image-guided biopsy of lung, liver, pancreas and other organs. Using automated biopsy devices, 160 biopsies of variable anatomic sites were performed: Biopsies were performed under ultrasonographic(US) guidance in 95 and computed tomographic (CT) guidance in 65. We retrospectively analyzed histologic results and complications. Specimens were adequate for histopathologic diagnosis in 143 of the 160 patients(89.4%)-Diagnostic tissue was obtained in 130 (81.3%), suggestive tissue obtained in 13(8.1%), and non-diagnostic tissue was obtained in 14(8.7%). Inadequate tissue was obtained in only 3(1.9%). There was no statistically significant difference between US-guided and CT-guided percutaneous biopsy. There was no occurrence of significant complication. We have experienced mild complications in only 5 patients-2 hematuria and 2 hematochezia in transrectal prostatic biopsy, and 1 minimal pneumothorax in CT-guided percutaneous lung biopsy. All of them were resolved spontaneously. The image-guided biopsy using the automated biopsy gun was a simple, safe and accurate method of obtaining adequate specimen for the histopathologic diagnosis.

Automated quality control in a file-based broadcasting workflow

Science.gov (United States)

Zhang, Lina

2014-04-01

Benefit from the development of information and internet technologies, television broadcasting is transforming from inefficient tape-based production and distribution to integrated file-based workflows. However, no matter how many changes have took place, successful broadcasting still depends on the ability to deliver a consistent high quality signal to the audiences. After the transition from tape to file, traditional methods of manual quality control (QC) become inadequate, subjective, and inefficient. Based on China Central Television's full file-based workflow in the new site, this paper introduces an automated quality control test system for accurate detection of hidden troubles in media contents. It discusses the system framework and workflow control when the automated QC is added. It puts forward a QC criterion and brings forth a QC software followed this criterion. It also does some experiments on QC speed by adopting parallel processing and distributed computing. The performance of the test system shows that the adoption of automated QC can make the production effective and efficient, and help the station to achieve a competitive advantage in the media market.

Automated data processing and radioassays.

Science.gov (United States)

Samols, E; Barrows, G H

1978-04-01

Radioassays include (1) radioimmunoassays, (2) competitive protein-binding assays based on competition for limited antibody or specific binding protein, (3) immunoradiometric assay, based on competition for excess labeled antibody, and (4) radioreceptor assays. Most mathematical models describing the relationship between labeled ligand binding and unlabeled ligand concentration have been based on the law of mass action or the isotope dilution principle. These models provide useful data reduction programs, but are theoretically unfactory because competitive radioassay usually is not based on classical dilution principles, labeled and unlabeled ligand do not have to be identical, antibodies (or receptors) are frequently heterogenous, equilibrium usually is not reached, and there is probably steric and cooperative influence on binding. An alternative, more flexible mathematical model based on the probability or binding collisions being restricted by the surface area of reactive divalent sites on antibody and on univalent antigen has been derived. Application of these models to automated data reduction allows standard curves to be fitted by a mathematical expression, and unknown values are calculated from binding data. The vitrues and pitfalls are presented of point-to-point data reduction, linear transformations, and curvilinear fitting approaches. A third-order polynomial using the square root of concentration closely approximates the mathematical model based on probability, and in our experience this method provides the most acceptable results with all varieties of radioassays. With this curvilinear system, linear point connection should be used between the zero standard and the beginning of significant dose response, and also towards saturation. The importance is stressed of limiting the range of reported automated assay results to that portion of the standard curve that delivers optimal sensitivity. Published methods for automated data reduction of Scatchard plots

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera.

Science.gov (United States)

Nguyen, Thuy Tuong; Slaughter, David C; Hanson, Bradley D; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

2015-07-28

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

Increasing the accuracy and automation of fractional vegetation cover estimation from digital photographs

Science.gov (United States)

The use of automated methods to estimate canopy cover (CC) from digital photographs has increased in recent years given its potential to produce accurate, fast and inexpensive CC measurements. Wide acceptance has been delayed because of the limitations of these methods. This work introduces a novel ...

Flexible automated approach for quantitative liquid handling of complex biological samples.

Science.gov (United States)

Palandra, Joe; Weller, David; Hudson, Gary; Li, Jeff; Osgood, Sarah; Hudson, Emily; Zhong, Min; Buchholz, Lisa; Cohen, Lucinda H

2007-11-01

A fully automated protein precipitation technique for biological sample preparation has been developed for the quantitation of drugs in various biological matrixes. All liquid handling during sample preparation was automated using a Hamilton MicroLab Star Robotic workstation, which included the preparation of standards and controls from a Watson laboratory information management system generated work list, shaking of 96-well plates, and vacuum application. Processing time is less than 30 s per sample or approximately 45 min per 96-well plate, which is then immediately ready for injection onto an LC-MS/MS system. An overview of the process workflow is discussed, including the software development. Validation data are also provided, including specific liquid class data as well as comparative data of automated vs manual preparation using both quality controls and actual sample data. The efficiencies gained from this automated approach are described.

Quantitative radiology: automated CT liver volumetry compared with interactive volumetry and manual volumetry.

Science.gov (United States)

Suzuki, Kenji; Epstein, Mark L; Kohlbrenner, Ryan; Garg, Shailesh; Hori, Masatoshi; Oto, Aytekin; Baron, Richard L

2011-10-01

The purpose of this study was to evaluate automated CT volumetry in the assessment of living-donor livers for transplant and to compare this technique with software-aided interactive volumetry and manual volumetry. Hepatic CT scans of 18 consecutively registered prospective liver donors were obtained under a liver transplant protocol. Automated liver volumetry was developed on the basis of 3D active-contour segmentation. To establish reference standard liver volumes, a radiologist manually traced the contour of the liver on each CT slice. We compared the results obtained with automated and interactive volumetry with those obtained with the reference standard for this study, manual volumetry. The average interactive liver volume was 1553 ± 343 cm(3), and the average automated liver volume was 1520 ± 378 cm(3). The average manual volume was 1486 ± 343 cm(3). Both interactive and automated volumetric results had excellent agreement with manual volumetric results (intraclass correlation coefficients, 0.96 and 0.94). The average user time for automated volumetry was 0.57 ± 0.06 min/case, whereas those for interactive and manual volumetry were 27.3 ± 4.6 and 39.4 ± 5.5 min/case, the difference being statistically significant (p volumetry are accurate for measuring liver volume with CT, but automated volumetry is substantially more efficient.

Decision Making In A High-Tech World: Automation Bias and Countermeasures

Science.gov (United States)

Mosier, Kathleen L.; Skitka, Linda J.; Burdick, Mark R.; Heers, Susan T.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

Automated dental identification system: An aid to forensic odontology

Directory of Open Access Journals (Sweden)

Parvathi Devi

2011-01-01

Full Text Available Automated dental identification system is computer-aided software for the postmortem identification of deceased individuals based on dental characteristics specifically radiographs. This system is receiving increased attention because of the large number of victims encountered in the mass disasters and it is 90% more time saving and accurate than the conventional radiographic methods. This technique is based on the intensity of the overall region of tooth image and therefore it does not necessitate the presence of sharp boundary between the teeth. It provides automated search and matching capabilities for digitized radiographs and photographic dental images and compares the teeth present in multiple digitized dental records in order to access their similarity. This paper highlights the functionality of its components and techniques used in realizing these components.

Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing.

Science.gov (United States)

Wu, Lingling; Wen, Guojun; Wang, Yudan; Huang, Lei; Zhou, Jiang

2018-02-15

Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED light target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, direction location algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system.

Automated-immunosensor with centrifugal fluid valves for salivary cortisol measurement

Directory of Open Access Journals (Sweden)

Masaki Yamaguchi

2014-08-01

Full Text Available Point-of-care measurement of the stress hormone cortisol will greatly facilitate the timely diagnosis and management of stress-related disorders. We describe an automated salivary cortisol immunosensor, incorporating centrifugal fluid valves and a disposable disc-chip that allows for truncated reporting of cortisol levels (<15 min. The performance characteristics of the immunosensor are optimized through select blocking agents to prevent the non-specific adsorption of proteins; immunoglobulin G (IgG polymer for the pad and milk protein for the reservoirs and the flow channels. Incorporated centrifugal fluid valves allow for rapid and repeat washings to remove impurities from the saliva samples. An optical reader and laptop computer automate the immunoassay processes and provide easily accessible digital readouts of salivary cortisol measurements. Linear regression analysis of the calibration curve for the cortisol immunosensor showed 0.92 of coefficient of multiple determination, R2, and 38.7% of coefficient of variation, CV, for a range of salivary cortisol concentrations between 0.4 and 11.3 ng/mL. The receiver operating characteristic (ROC curve analysis of human saliva samples indicate potential utility for discriminating stress disorders and underscore potential application of the biosensor in stress disorders. The performance of our salivary cortisol immunosensor approaches laboratory based tests and allows noninvasive, quantitative, and automated analysis of human salivary cortisol levels with reporting times compatible with point-of-care applications. Keywords: Immunosensor, Centrifugal fluid valve, Automation, Cortisol, Saliva

Streamlined sign-out of capillary protein electrophoresis using middleware and an open-source macro application.

Science.gov (United States)

Mathur, Gagan; Haugen, Thomas H; Davis, Scott L; Krasowski, Matthew D

2014-01-01

Interfacing of clinical laboratory instruments with the laboratory information system (LIS) via "middleware" software is increasingly common. Our clinical laboratory implemented capillary electrophoresis using a Sebia(®) Capillarys-2™ (Norcross, GA, USA) instrument for serum and urine protein electrophoresis. Using Data Innovations Instrument Manager, an interface was established with the LIS (Cerner) that allowed for bi-directional transmission of numeric data. However, the text of the interpretive pathology report was not properly transferred. To reduce manual effort and possibility for error in text data transfer, we developed scripts in AutoHotkey, a free, open-source macro-creation and automation software utility. Scripts were written to create macros that automated mouse and key strokes. The scripts retrieve the specimen accession number, capture user input text, and insert the text interpretation in the correct patient record in the desired format. The scripts accurately and precisely transfer narrative interpretation into the LIS. Combined with bar-code reading by the electrophoresis instrument, the scripts transfer data efficiently to the correct patient record. In addition, the AutoHotKey script automated repetitive key strokes required for manual entry into the LIS, making protein electrophoresis sign-out easier to learn and faster to use by the pathology residents. Scripts allow for either preliminary verification by residents or final sign-out by the attending pathologist. Using the open-source AutoHotKey software, we successfully improved the transfer of text data between capillary electrophoresis software and the LIS. The use of open-source software tools should not be overlooked as tools to improve interfacing of laboratory instruments.

Assessing drivers' response during automated driver support system failures with non-driving tasks.

Science.gov (United States)

Shen, Sijun; Neyens, David M

2017-06-01

With the increase in automated driver support systems, drivers are shifting from operating their vehicles to supervising their automation. As a result, it is important to understand how drivers interact with these automated systems and evaluate their effect on driver responses to safety critical events. This study aimed to identify how drivers responded when experiencing a safety critical event in automated vehicles while also engaged in non-driving tasks. In total 48 participants were included in this driving simulator study with two levels of automated driving: (a) driving with no automation and (b) driving with adaptive cruise control (ACC) and lane keeping (LK) systems engaged; and also two levels of a non-driving task (a) watching a movie or (b) no non-driving task. In addition to driving performance measures, non-driving task performance and the mean glance duration for the non-driving task were compared between the two levels of automated driving. Drivers using the automated systems responded worse than those manually driving in terms of reaction time, lane departure duration, and maximum steering wheel angle to an induced lane departure event. These results also found that non-driving tasks further impaired driver responses to a safety critical event in the automated system condition. In the automated driving condition, driver responses to the safety critical events were slower, especially when engaged in a non-driving task. Traditional driver performance variables may not necessarily effectively and accurately evaluate driver responses to events when supervising autonomous vehicle systems. Thus, it is important to develop and use appropriate variables to quantify drivers' performance under these conditions. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Implementation and design of a communication system of an agent-based automated substation

Institute of Scientific and Technical Information of China (English)

LIN Yong-jun; LIU Yu-tao; ZHANG Dan-hui

2006-01-01

A substation system requires that communication be transmitted reliably,accurately and in real-time.Aimed at solving problems,e.g.,flow confliction and sensitive data transmission,a model of the communication system of an agent-based automated substation is introduced.The running principle is discussed in detail and each type of agent is discussed further.At the end,the realization of the agent system applied to the substation is presented.The outcome shows that the communication system of an agent-based automated substation improves the accuracy and reliability of the data transfer and presents it in realtime.

Exploiting street-level panoramic images for large-scale automated surveying of traffic sign

NARCIS (Netherlands)

Hazelhoff, L.; Creusen, I.M.; With, de P.H.N.

2014-01-01

Accurate and up-to-date inventories of traffic signs contribute to efficient road maintenance and a high road safety. This paper describes a system for the automated surveying of road signs from street-level images. This is an extremely challenging task, as the involved capturings are non-densely

Low cost automation

International Nuclear Information System (INIS)

1987-03-01

This book indicates method of building of automation plan, design of automation facilities, automation and CHIP process like basics of cutting, NC processing machine and CHIP handling, automation unit, such as drilling unit, tapping unit, boring unit, milling unit and slide unit, application of oil pressure on characteristics and basic oil pressure circuit, application of pneumatic, automation kinds and application of process, assembly, transportation, automatic machine and factory automation.

Automated Classification of Consumer Health Information Needs in Patient Portal Messages

Science.gov (United States)

Cronin, Robert M.; Fabbri, Daniel; Denny, Joshua C.; Jackson, Gretchen Purcell

2015-01-01

Patients have diverse health information needs, and secure messaging through patient portals is an emerging means by which such needs are expressed and met. As patient portal adoption increases, growing volumes of secure messages may burden healthcare providers. Automated classification could expedite portal message triage and answering. We created four automated classifiers based on word content and natural language processing techniques to identify health information needs in 1000 patient-generated portal messages. Logistic regression and random forest classifiers detected single information needs well, with area under the curves of 0.804–0.914. A logistic regression classifier accurately found the set of needs within a message, with a Jaccard index of 0.859 (95% Confidence Interval: (0.847, 0.871)). Automated classification of consumer health information needs expressed in patient portal messages is feasible and may allow direct linking to relevant resources or creation of institutional resources for commonly expressed needs. PMID:26958285

Computational methods for protein identification from mass spectrometry data.

Directory of Open Access Journals (Sweden)

Leo McHugh

2008-02-01

Full Text Available Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.

Automated Sample Exchange Robots for the Structural Biology Beam Lines at the Photon Factory

International Nuclear Information System (INIS)

Hiraki, Masahiko; Watanabe, Shokei; Yamada, Yusuke; Matsugaki, Naohiro; Igarashi, Noriyuki; Gaponov, Yurii; Wakatsuki, Soichi

2007-01-01

We are now developing automated sample exchange robots for high-throughput protein crystallographic experiments for onsite use at synchrotron beam lines. It is part of the fully automated robotics systems being developed at the Photon Factory, for the purposes of protein crystallization, monitoring crystal growth, harvesting and freezing crystals, mounting the crystals inside a hutch and for data collection. We have already installed the sample exchange robots based on the SSRL automated mounting system at our insertion device beam lines BL-5A and AR-NW12A at the Photon Factory. In order to reduce the time required for sample exchange further, a prototype of a double-tonged system was developed. As a result of preliminary experiments with double-tonged robots, the sample exchange time was successfully reduced from 70 seconds to 10 seconds with the exception of the time required for pre-cooling and warming up the tongs

Possible Computer Vision Systems and Automated or Computer-Aided Edging and Trimming

Science.gov (United States)

Philip A. Araman

1990-01-01

This paper discusses research which is underway to help our industry reduce costs, increase product volume and value recovery, and market more accurately graded and described products. The research is part of a team effort to help the hardwood sawmill industry automate with computer vision systems, and computer-aided or computer controlled processing. This paper...

The Manchester Acute Coronary Syndromes (MACS) decision rule: validation with a new automated assay for heart-type fatty acid binding protein.

Science.gov (United States)

Body, Richard; Burrows, Gillian; Carley, Simon; Lewis, Philip S

2015-10-01

The Manchester Acute Coronary Syndromes (MACS) decision rule may enable acute coronary syndromes to be immediately 'ruled in' or 'ruled out' in the emergency department. The rule incorporates heart-type fatty acid binding protein (h-FABP) and high sensitivity troponin T levels. The rule was previously validated using a semiautomated h-FABP assay that was not practical for clinical implementation. We aimed to validate the rule with an automated h-FABP assay that could be used clinically. In this prospective diagnostic cohort study we included patients presenting to the emergency department with suspected cardiac chest pain. Serum drawn on arrival was tested for h-FABP using an automated immunoturbidimetric assay (Randox) and high sensitivity troponin T (Roche). The primary outcome, a diagnosis of acute myocardial infarction (AMI), was adjudicated based on 12 h troponin testing. A secondary outcome, major adverse cardiac events (MACE; death, AMI, revascularisation or new coronary stenosis), was determined at 30 days. Of the 456 patients included, 78 (17.1%) had AMI and 97 (21.3%) developed MACE. Using the automated h-FABP assay, the MACS rule had the same C-statistic for MACE as the original rule (0.91; 95% CI 0.88 to 0.92). 18.9% of patients were identified as 'very low risk' and thus eligible for immediate discharge with no missed AMIs and a 2.3% incidence of MACE (n=2, both coronary stenoses). 11.1% of patients were classed as 'high-risk' and had a 92.0% incidence of MACE. Our findings validate the performance of a refined MACS rule incorporating an automated h-FABP assay, facilitating use in clinical settings. The effectiveness of this refined rule should be verified in an interventional trial prior to implementation. UK CRN 8376. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

The second round of Critical Assessment of Automated Structure Determination of Proteins by NMR: CASD-NMR-2013

Energy Technology Data Exchange (ETDEWEB)

Rosato, Antonio [University of Florence, Department of Chemistry and Magnetic Resonance Center (Italy); Vranken, Wim [Vrije Universiteit Brussel, Structural Biology Brussels (Belgium); Fogh, Rasmus H.; Ragan, Timothy J. [University of Leicester, Department of Biochemistry, School of Biological Sciences (United Kingdom); Tejero, Roberto [Universidad de Valencia, Departamento de Química Física (Spain); Pederson, Kari; Lee, Hsiau-Wei; Prestegard, James H. [University of Georgia, Complex Carbohydrate Research Center and Northeast Structural Genomics Consortium (United States); Yee, Adelinda; Wu, Bin; Lemak, Alexander; Houliston, Scott; Arrowsmith, Cheryl H. [University of Toronto, Department of Medical Biophysics, Cancer Genomics and Proteomics, Ontario Cancer Institute, Northeast Structural Genomics Consortium (Canada); Kennedy, Michael [Miami University, Department of Chemistry and Biochemistry, Northeast Structural Genomics Consortium (United States); Acton, Thomas B.; Xiao, Rong; Liu, Gaohua; Montelione, Gaetano T., E-mail: guy@cabm.rutgers.edu [The State University of New Jersey, Department of Molecular Biology and Biochemistry, Center for Advanced Biotechnology and Medicine, Northeast Structural Genomics Consortium, Rutgers (United States); Vuister, Geerten W., E-mail: gv29@le.ac.uk [University of Leicester, Department of Biochemistry, School of Biological Sciences (United Kingdom)

2015-08-15

The second round of the community-wide initiative Critical Assessment of automated Structure Determination of Proteins by NMR (CASD-NMR-2013) comprised ten blind target datasets, consisting of unprocessed spectral data, assigned chemical shift lists and unassigned NOESY peak and RDC lists, that were made available in both curated (i.e. manually refined) or un-curated (i.e. automatically generated) form. Ten structure calculation programs, using fully automated protocols only, generated a total of 164 three-dimensional structures (entries) for the ten targets, sometimes using both curated and un-curated lists to generate multiple entries for a single target. The accuracy of the entries could be established by comparing them to the corresponding manually solved structure of each target, which was not available at the time the data were provided. Across the entire data set, 71 % of all entries submitted achieved an accuracy relative to the reference NMR structure better than 1.5 Å. Methods based on NOESY peak lists achieved even better results with up to 100 % of the entries within the 1.5 Å threshold for some programs. However, some methods did not converge for some targets using un-curated NOESY peak lists. Over 90 % of the entries achieved an accuracy better than the more relaxed threshold of 2.5 Å that was used in the previous CASD-NMR-2010 round. Comparisons between entries generated with un-curated versus curated peaks show only marginal improvements for the latter in those cases where both calculations converged.

The second round of Critical Assessment of Automated Structure Determination of Proteins by NMR: CASD-NMR-2013

International Nuclear Information System (INIS)

Rosato, Antonio; Vranken, Wim; Fogh, Rasmus H.; Ragan, Timothy J.; Tejero, Roberto; Pederson, Kari; Lee, Hsiau-Wei; Prestegard, James H.; Yee, Adelinda; Wu, Bin; Lemak, Alexander; Houliston, Scott; Arrowsmith, Cheryl H.; Kennedy, Michael; Acton, Thomas B.; Xiao, Rong; Liu, Gaohua; Montelione, Gaetano T.; Vuister, Geerten W.

2015-01-01

The second round of the community-wide initiative Critical Assessment of automated Structure Determination of Proteins by NMR (CASD-NMR-2013) comprised ten blind target datasets, consisting of unprocessed spectral data, assigned chemical shift lists and unassigned NOESY peak and RDC lists, that were made available in both curated (i.e. manually refined) or un-curated (i.e. automatically generated) form. Ten structure calculation programs, using fully automated protocols only, generated a total of 164 three-dimensional structures (entries) for the ten targets, sometimes using both curated and un-curated lists to generate multiple entries for a single target. The accuracy of the entries could be established by comparing them to the corresponding manually solved structure of each target, which was not available at the time the data were provided. Across the entire data set, 71 % of all entries submitted achieved an accuracy relative to the reference NMR structure better than 1.5 Å. Methods based on NOESY peak lists achieved even better results with up to 100 % of the entries within the 1.5 Å threshold for some programs. However, some methods did not converge for some targets using un-curated NOESY peak lists. Over 90 % of the entries achieved an accuracy better than the more relaxed threshold of 2.5 Å that was used in the previous CASD-NMR-2010 round. Comparisons between entries generated with un-curated versus curated peaks show only marginal improvements for the latter in those cases where both calculations converged

Automated dried blood spots standard and QC sample preparation using a robotic liquid handler.

Science.gov (United States)

Yuan, Long; Zhang, Duxi; Aubry, Anne-Francoise; Arnold, Mark E

2012-12-01

A dried blood spot (DBS) bioanalysis assay involves many steps, such as the preparation of standard (STD) and QC samples in blood, the spotting onto DBS cards, and the cutting-out of the spots. These steps are labor intensive and time consuming if done manually, which, therefore, makes automation very desirable in DBS bioanalysis. A robotic liquid handler was successfully applied to the preparation of STD and QC samples in blood and to spot the blood samples onto DBS cards using buspirone as the model compound. This automated preparation was demonstrated to be accurate and consistent. However the accuracy and precision of automated preparation were similar to those from manual preparation. The effect of spotting volume on accuracy was evaluated and a trend of increasing concentrations of buspirone with increasing spotting volumes was observed. The automated STD and QC sample preparation process significantly improved the efficiency, robustness and safety of DBS bioanalysis.

Quantitative analysis and prediction of curvature in leucine-rich repeat proteins.

Science.gov (United States)

Hindle, K Lauren; Bella, Jordi; Lovell, Simon C

2009-11-01

Leucine-rich repeat (LRR) proteins form a large and diverse family. They have a wide range of functions most of which involve the formation of protein-protein interactions. All known LRR structures form curved solenoids, although there is large variation in their curvature. It is this curvature that determines the shape and dimensions of the inner space available for ligand binding. Unfortunately, large-scale parameters such as the overall curvature of a protein domain are extremely difficult to predict. Here, we present a quantitative analysis of determinants of curvature of this family. Individual repeats typically range in length between 20 and 30 residues and have a variety of secondary structures on their convex side. The observed curvature of the LRR domains correlates poorly with the lengths of their individual repeats. We have, therefore, developed a scoring function based on the secondary structure of the convex side of the protein that allows prediction of the overall curvature with a high degree of accuracy. We also demonstrate the effectiveness of this method in selecting a suitable template for comparative modeling. We have developed an automated, quantitative protocol that can be used to predict accurately the curvature of leucine-rich repeat proteins of unknown structure from sequence alone. This protocol is available as an online resource at http://www.bioinf.manchester.ac.uk/curlrr/.

The Atmospheric Data Acquisition And Interpolation Process For Center-TRACON Automation System

Science.gov (United States)

Jardin, M. R.; Erzberger, H.; Denery, Dallas G. (Technical Monitor)

1995-01-01

The Center-TRACON Automation System (CTAS), an advanced new air traffic automation program, requires knowledge of spatial and temporal atmospheric conditions such as the wind speed and direction, the temperature and the pressure in order to accurately predict aircraft trajectories. Real-time atmospheric data is available in a grid format so that CTAS must interpolate between the grid points to estimate the atmospheric parameter values. The atmospheric data grid is generally not in the same coordinate system as that used by CTAS so that coordinate conversions are required. Both the interpolation and coordinate conversion processes can introduce errors into the atmospheric data and reduce interpolation accuracy. More accurate algorithms may be computationally expensive or may require a prohibitively large amount of data storage capacity so that trade-offs must be made between accuracy and the available computational and data storage resources. The atmospheric data acquisition and processing employed by CTAS will be outlined in this report. The effects of atmospheric data processing on CTAS trajectory prediction will also be analyzed, and several examples of the trajectory prediction process will be given.

ProDaMa: an open source Python library to generate protein structure datasets

Directory of Open Access Journals (Sweden)

Manconi Andrea

2009-10-01

Full Text Available Abstract Background The huge difference between the number of known sequences and known tertiary structures has justified the use of automated methods for protein analysis. Although a general methodology to solve these problems has not been yet devised, researchers are engaged in developing more accurate techniques and algorithms whose training plays a relevant role in determining their performance. From this perspective, particular importance is given to the training data used in experiments, and researchers are often engaged in the generation of specialized datasets that meet their requirements. Findings To facilitate the task of generating specialized datasets we devised and implemented ProDaMa, an open source Python library than provides classes for retrieving, organizing, updating, analyzing, and filtering protein data. Conclusion ProDaMa has been used to generate specialized datasets useful for secondary structure prediction and to develop a collaborative web application aimed at generating and sharing protein structure datasets. The library, the related database, and the documentation are freely available at the URL http://iasc.diee.unica.it/prodama.

Cardiac imaging: working towards fully-automated machine analysis & interpretation.

Science.gov (United States)

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-03-01

Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

Automated classification of Acid Rock Drainage potential from Corescan drill core imagery

Science.gov (United States)

Cracknell, M. J.; Jackson, L.; Parbhakar-Fox, A.; Savinova, K.

2017-12-01

Classification of the acid forming potential of waste rock is important for managing environmental hazards associated with mining operations. Current methods for the classification of acid rock drainage (ARD) potential usually involve labour intensive and subjective assessment of drill core and/or hand specimens. Manual methods are subject to operator bias, human error and the amount of material that can be assessed within a given time frame is limited. The automated classification of ARD potential documented here is based on the ARD Index developed by Parbhakar-Fox et al. (2011). This ARD Index involves the combination of five indicators: A - sulphide content; B - sulphide alteration; C - sulphide morphology; D - primary neutraliser content; and E - sulphide mineral association. Several components of the ARD Index require accurate identification of sulphide minerals. This is achieved by classifying Corescan Red-Green-Blue true colour images into the presence or absence of sulphide minerals using supervised classification. Subsequently, sulphide classification images are processed and combined with Corescan SWIR-based mineral classifications to obtain information on sulphide content, indices representing sulphide textures (disseminated versus massive and degree of veining), and spatially associated minerals. This information is combined to calculate ARD Index indicator values that feed into the classification of ARD potential. Automated ARD potential classifications of drill core samples associated with a porphyry Cu-Au deposit are compared to manually derived classifications and those obtained by standard static geochemical testing and X-ray diffractometry analyses. Results indicate a high degree of similarity between automated and manual ARD potential classifications. Major differences between approaches are observed in sulphide and neutraliser mineral percentages, likely due to the subjective nature of manual estimates of mineral content. The automated approach

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera

Directory of Open Access Journals (Sweden)

Thuy Tuong Nguyen

2015-07-01

Full Text Available This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1 an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2 a plant counting method based on projection histograms; and (3 a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

Automated method for measuring the extent of selective logging damage with airborne LiDAR data

Science.gov (United States)

Melendy, L.; Hagen, S. C.; Sullivan, F. B.; Pearson, T. R. H.; Walker, S. M.; Ellis, P.; Kustiyo; Sambodo, Ari Katmoko; Roswintiarti, O.; Hanson, M. A.; Klassen, A. W.; Palace, M. W.; Braswell, B. H.; Delgado, G. M.

2018-05-01

Selective logging has an impact on the global carbon cycle, as well as on the forest micro-climate, and longer-term changes in erosion, soil and nutrient cycling, and fire susceptibility. Our ability to quantify these impacts is dependent on methods and tools that accurately identify the extent and features of logging activity. LiDAR-based measurements of these features offers significant promise. Here, we present a set of algorithms for automated detection and mapping of critical features associated with logging - roads/decks, skid trails, and gaps - using commercial airborne LiDAR data as input. The automated algorithm was applied to commercial LiDAR data collected over two logging concessions in Kalimantan, Indonesia in 2014. The algorithm results were compared to measurements of the logging features collected in the field soon after logging was complete. The automated algorithm-mapped road/deck and skid trail features match closely with features measured in the field, with agreement levels ranging from 69% to 99% when adjusting for GPS location error. The algorithm performed most poorly with gaps, which, by their nature, are variable due to the unpredictable impact of tree fall versus the linear and regular features directly created by mechanical means. Overall, the automated algorithm performs well and offers significant promise as a generalizable tool useful to efficiently and accurately capture the effects of selective logging, including the potential to distinguish reduced impact logging from conventional logging.

Implementation of a fully automated process purge-and-trap gas chromatograph at an environmental remediation site

International Nuclear Information System (INIS)

Blair, D.S.; Morrison, D.J.

1997-01-01

The AQUASCAN, a commercially available, fully automated purge-and-trap gas chromatograph from Sentex Systems Inc., was implemented and evaluated as an in-field, automated monitoring system of contaminated groundwater at an active DOE remediation site in Pinellas, FL. Though the AQUASCAN is designed as a stand alone process analytical unit, implementation at this site required additional hardware. The hardware included a sample dilution system and a method for delivering standard solution to the gas chromatograph for automated calibration. As a result of the evaluation the system was determined to be a reliable and accurate instrument. The AQUASCAN reported concentration values for methylene chloride, trichloroethylene, and toluene in the Pinellas ground water were within 20% of reference laboratory values

Autonomy and Automation

Science.gov (United States)

Shively, Jay

2017-01-01

A significant level of debate and confusion has surrounded the meaning of the terms autonomy and automation. Automation is a multi-dimensional concept, and we propose that Remotely Piloted Aircraft Systems (RPAS) automation should be described with reference to the specific system and task that has been automated, the context in which the automation functions, and other relevant dimensions. In this paper, we present definitions of automation, pilot in the loop, pilot on the loop and pilot out of the loop. We further propose that in future, the International Civil Aviation Organization (ICAO) RPAS Panel avoids the use of the terms autonomy and autonomous when referring to automated systems on board RPA. Work Group 7 proposes to develop, in consultation with other workgroups, a taxonomy of Levels of Automation for RPAS.

Designing of smart home automation system based on Raspberry Pi

International Nuclear Information System (INIS)

Saini, Ravi Prakash; Singh, Bhanu Pratap; Sharma, Mahesh Kumar; Wattanawisuth, Nattapol; Leeprechanon, Nopbhorn

2016-01-01

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning “on” and “off” of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

Designing of smart home automation system based on Raspberry Pi

Energy Technology Data Exchange (ETDEWEB)

Saini, Ravi Prakash; Singh, Bhanu Pratap [B K Birla Institute of Engineering & Technology, Pilani, Rajasthan (India); Sharma, Mahesh Kumar; Wattanawisuth, Nattapol; Leeprechanon, Nopbhorn, E-mail: Dr.N.L@ieee.org [Thammasat University, Rangsit Campus, Pathum Thani (Thailand)

2016-03-09

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning “on” and “off” of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

Production and quality assurance automation in the Goddard Space Flight Center Flight Dynamics Facility

Science.gov (United States)

Chapman, K. B.; Cox, C. M.; Thomas, C. W.; Cuevas, O. O.; Beckman, R. M.

1994-01-01

The Flight Dynamics Facility (FDF) at the NASA Goddard Space Flight Center (GSFC) generates numerous products for NASA-supported spacecraft, including the Tracking and Data Relay Satellites (TDRS's), the Hubble Space Telescope (HST), the Extreme Ultraviolet Explorer (EUVE), and the space shuttle. These products include orbit determination data, acquisition data, event scheduling data, and attitude data. In most cases, product generation involves repetitive execution of many programs. The increasing number of missions supported by the FDF has necessitated the use of automated systems to schedule, execute, and quality assure these products. This automation allows the delivery of accurate products in a timely and cost-efficient manner. To be effective, these systems must automate as many repetitive operations as possible and must be flexible enough to meet changing support requirements. The FDF Orbit Determination Task (ODT) has implemented several systems that automate product generation and quality assurance (QA). These systems include the Orbit Production Automation System (OPAS), the New Enhanced Operations Log (NEOLOG), and the Quality Assurance Automation Software (QA Tool). Implementation of these systems has resulted in a significant reduction in required manpower, elimination of shift work and most weekend support, and improved support quality, while incurring minimal development cost. This paper will present an overview of the concepts used and experiences gained from the implementation of these automation systems.

Automated genotyping of dinucleotide repeat markers

Energy Technology Data Exchange (ETDEWEB)

Perlin, M.W.; Hoffman, E.P. [Carnegie Mellon Univ., Pittsburgh, PA (United States)]|[Univ. of Pittsburgh, PA (United States)

1994-09-01

The dinucleotide repeats (i.e., microsatellites) such as CA-repeats are a highly polymorphic, highly abundant class of PCR-amplifiable markers that have greatly streamlined genetic mapping experimentation. It is expected that over 30,000 such markers (including tri- and tetranucleotide repeats) will be characterized for routine use in the next few years. Since only size determination, and not sequencing, is required to determine alleles, in principle, dinucleotide repeat genotyping is easily performed on electrophoretic gels, and can be automated using DNA sequencers. Unfortunately, PCR stuttering with these markers generates not one band for each allele, but a pattern of bands. Since closely spaced alleles must be disambiguated by human scoring, this poses a key obstacle to full automation. We have developed methods that overcome this obstacle. Our model is that the observed data is generated by arithmetic superposition (i.e., convolution) of multiple allele patterns. By quantitatively measuring the size of each component band, and exploiting the unique stutter pattern associated with each marker, closely spaced alleles can be deconvolved; this unambiguously reconstructs the {open_quotes}true{close_quotes} allele bands, with stutter artifact removed. We used this approach in a system for automated diagnosis of (X-linked) Duchenne muscular dystrophy; four multiplexed CA-repeats within the dystrophin gene were assayed on a DNA sequencer. Our method accurately detected small variations in gel migration that shifted the allele size estimate. In 167 nonmutated alleles, 89% (149/167) showed no size variation, 9% (15/167) showed 1 bp variation, and 2% (3/167) showed 2 bp variation. We are currently developing a library of dinucleotide repeat patterns; together with our deconvolution methods, this library will enable fully automated genotyping of dinucleotide repeats from sizing data.

AUTOBA: automation of backbone assignment from HN(C)N suite of experiments.

Science.gov (United States)

Borkar, Aditi; Kumar, Dinesh; Hosur, Ramakrishna V

2011-07-01

Development of efficient strategies and automation represent important milestones of progress in rapid structure determination efforts in proteomics research. In this context, we present here an efficient algorithm named as AUTOBA (Automatic Backbone Assignment) designed to automate the assignment protocol based on HN(C)N suite of experiments. Depending upon the spectral dispersion, the user can record 2D or 3D versions of the experiments for assignment. The algorithm uses as inputs: (i) protein primary sequence and (ii) peak-lists from user defined HN(C)N suite of experiments. In the end, one gets H(N), (15)N, C(α) and C' assignments (in common BMRB format) for the individual residues along the polypeptide chain. The success of the algorithm has been demonstrated, not only with experimental spectra recorded on two small globular proteins: ubiquitin (76 aa) and M-crystallin (85 aa), but also with simulated spectra of 27 other proteins using assignment data from the BMRB.

Automating Ontological Annotation with WordNet

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

2006-01-22

Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach.

Directory of Open Access Journals (Sweden)

Andre F Marquand

Full Text Available Progressive supranuclear palsy (PSP, multiple system atrophy (MSA and idiopathic Parkinson's disease (IPD can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs. An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i a subcortical motor network; (ii each of its component regions and (iii the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.

Launch Control System Software Development System Automation Testing

Science.gov (United States)

Hwang, Andrew

2017-01-01

) tool to Brandon Echols, a fellow intern, and I. The purpose of the OCR tool is to analyze an image and find the coordinates of any group of text. Some issues that arose while installing the OCR tool included the absence of certain libraries needed to train the tool and an outdated software version. We eventually resolved the issues and successfully installed the OCR tool. Training the tool required many images and different fonts and sizes, but in the end the tool learned to accurately decipher the text in the images and their coordinates. The OCR tool produced a file that contained significant metadata for each section of text, but only the text and coordinates of the text was required for our purpose. The team made a script to parse the information we wanted from the OCR file to a different file that would be used by automation functions within the automated framework. Since a majority of development and testing for the automated test cases for the GUI in question has been done using live simulated data on the workstations at the Launch Control Center (LCC), a large amount of progress has been made. As of this writing, about 60% of all of automated testing has been implemented. Additionally, the OCR tool will help make our automated tests more robust due to the tool's text recognition being highly scalable to different text fonts and text sizes. Soon we will have the whole test system automated, allowing for more full-time engineers working on development projects.

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

Bayesian automated cortical segmentation for neonatal MRI

Science.gov (United States)

Chou, Zane; Paquette, Natacha; Ganesh, Bhavana; Wang, Yalin; Ceschin, Rafael; Nelson, Marvin D.; Macyszyn, Luke; Gaonkar, Bilwaj; Panigrahy, Ashok; Lepore, Natasha

2017-11-01

Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 fullterm and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

Fully automated laboratory for the assay of plutonium in wastes and recoverable scraps

International Nuclear Information System (INIS)

Guiberteau, P.; Michaut, F.; Bergey, C.; Debruyne, T.

1990-01-01

To determine the plutonium content of wastes and recoverable scraps in intermediate size containers (ten liters) an automated laboratory has been carried out. Two passive methods of measurement are used. Gamma ray spectrometry allows plutonium isotopic analysis, americium determination and plutonium assay in wastes and poor scraps. Calorimetry is used for accurate (± 3%) plutonium determination in rich scraps. A full automation was realized with a barcode management and a supply robot to feed the eight assay set-ups. The laboratory works on a 24 hours per day and 365 days per year basis and has a capacity of 8,000 assays per year

webPOISONCONTROL: can poison control be automated?

Science.gov (United States)

Litovitz, Toby; Benson, Blaine E; Smolinske, Susan

2016-08-01

A free webPOISONCONTROL app allows the public to determine the appropriate triage of poison ingestions without calling poison control. If accepted and safe, this alternative expands access to reliable poison control services to those who prefer the Internet over the telephone. This study assesses feasibility, safety, and user-acceptance of automated online triage of asymptomatic, nonsuicidal poison ingestion cases. The user provides substance name, amount, age, and weight in an automated online tool or downloadable app, and is given a specific triage recommendation to stay home, go to the emergency department, or call poison control for further guidance. Safety was determined by assessing outcomes of consecutive home-triaged cases with follow-up and by confirming the correct application of algorithms. Case completion times and user perceptions of speed and ease of use were measures of user-acceptance. Of 9256 cases, 73.3% were triaged to home, 2.1% to an emergency department, and 24.5% directed to call poison control. Children younger than 6 years were involved in 75.2% of cases. Automated follow-up was done in 31.2% of home-triaged cases; 82.3% of these had no effect. No major or fatal outcomes were reported. More than 91% of survey respondents found the tool quick and easy to use. Median case completion time was 4.1 minutes. webPOISONCONTROL augments traditional poison control services by providing automated, accurate online access to case-specific triage and first aid guidance for poison ingestions. It is safe, quick, and easy to use. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment.

Science.gov (United States)

Jiang, Hui; Hanna, Eriny; Gatto, Cheryl L; Page, Terry L; Bhuva, Bharat; Broadie, Kendal

2016-03-01

Aversive olfactory classical conditioning has been the standard method to assess Drosophila learning and memory behavior for decades, yet training and testing are conducted manually under exceedingly labor-intensive conditions. To overcome this severe limitation, a fully automated, inexpensive system has been developed, which allows accurate and efficient Pavlovian associative learning/memory analyses for high-throughput pharmacological and genetic studies. The automated system employs a linear actuator coupled to an odorant T-maze with airflow-mediated transfer of animals between training and testing stages. Odorant, airflow and electrical shock delivery are automatically administered and monitored during training trials. Control software allows operator-input variables to define parameters of Drosophila learning, short-term memory and long-term memory assays. The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24h) are comparable to traditional manual experiments, while minimizing experimenter involvement. The automated system provides vast improvements over labor-intensive manual approaches with no experimenter involvement required during either training or testing phases. It provides quality control tracking of airflow rates, odorant delivery and electrical shock treatments, and an expanded platform for high-throughput studies of combinational drug tests and genetic screens. The design uses inexpensive hardware and software for a total cost of ∼$500US, making it affordable to a wide range of investigators. This study demonstrates the design, construction and testing of a fully automated Drosophila olfactory classical association apparatus to provide low-labor, high-fidelity, quality-monitored, high-throughput and inexpensive learning and memory behavioral assays. Copyright © 2015 Elsevier B.V. All rights reserved.

Proteogenomics of rare taxonomic phyla: A prospective treasure trove of protein coding genes.

Science.gov (United States)

Kumar, Dhirendra; Mondal, Anupam Kumar; Kutum, Rintu; Dash, Debasis

2016-01-01

Sustainable innovations in sequencing technologies have resulted in a torrent of microbial genome sequencing projects. However, the prokaryotic genomes sequenced so far are unequally distributed along their phylogenetic tree; few phyla contain the majority, the rest only a few representatives. Accurate genome annotation lags far behind genome sequencing. While automated computational prediction, aided by comparative genomics, remains a popular choice for genome annotation, substantial fraction of these annotations are erroneous. Proteogenomics utilizes protein level experimental observations to annotate protein coding genes on a genome wide scale. Benefits of proteogenomics include discovery and correction of gene annotations regardless of their phylogenetic conservation. This not only allows detection of common, conserved proteins but also the discovery of protein products of rare genes that may be horizontally transferred or taxonomy specific. Chances of encountering such genes are more in rare phyla that comprise a small number of complete genome sequences. We collated all bacterial and archaeal proteogenomic studies carried out to date and reviewed them in the context of genome sequencing projects. Here, we present a comprehensive list of microbial proteogenomic studies, their taxonomic distribution, and also urge for targeted proteogenomics of underexplored taxa to build an extensive reference of protein coding genes. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Stepwise Fitting Procedure for automated fitting of Ecopath with Ecosim models

Directory of Open Access Journals (Sweden)

Erin Scott

2016-01-01

Full Text Available The Stepwise Fitting Procedure automates testing of alternative hypotheses used for fitting Ecopath with Ecosim (EwE models to observation reference data (Mackinson et al. 2009. The calibration of EwE model predictions to observed data is important to evaluate any model that will be used for ecosystem based management. Thus far, the model fitting procedure in EwE has been carried out manually: a repetitive task involving setting >1000 specific individual searches to find the statistically ‘best fit’ model. The novel fitting procedure automates the manual procedure therefore producing accurate results and lets the modeller concentrate on investigating the ‘best fit’ model for ecological accuracy.

Load Segmentation for Convergence of Distribution Automation and Advanced Metering Infrastructure Systems

Science.gov (United States)

Pamulaparthy, Balakrishna; KS, Swarup; Kommu, Rajagopal

2014-12-01

Distribution automation (DA) applications are limited to feeder level today and have zero visibility outside of the substation feeder and reaching down to the low-voltage distribution network level. This has become a major obstacle in realizing many automated functions and enhancing existing DA capabilities. Advanced metering infrastructure (AMI) systems are being widely deployed by utilities across the world creating system-wide communications access to every monitoring and service point, which collects data from smart meters and sensors in short time intervals, in response to utility needs. DA and AMI systems convergence provides unique opportunities and capabilities for distribution grid modernization with the DA system acting as a controller and AMI system acting as feedback to DA system, for which DA applications have to understand and use the AMI data selectively and effectively. In this paper, we propose a load segmentation method that helps the DA system to accurately understand and use the AMI data for various automation applications with a suitable case study on power restoration.

Automated Passive Capillary Lysimeters for Estimating Water Drainage in the Vadose Zone

Science.gov (United States)

Jabro, J.; Evans, R.

2009-04-01

In this study, we demonstrated and evaluated the performance and accuracy of an automated PCAP lysimeters that we designed for in-situ continuous measuring and estimating of drainage water below the rootzone of a sugarbeet-potato-barley rotation under two irrigation frequencies. Twelve automated PCAPs with sampling surface dimensions of 31 cm width * 91 cm long and 87 cm in height were placed 90 cm below the soil surface in a Lihen sandy loam. Our state-of-the-art design incorporated Bluetooth wireless technology to enable an automated datalogger to transmit drainage water data simultaneously every 15 minutes to a remote host and had a greater efficiency than other types of lysimeters. It also offered a significantly larger coverage area (2700 cm2) than similarly designed vadose zone lysimeters. The cumulative manually extracted drainage water was compared with the cumulative volume of drainage water recorded by the datalogger from the tipping bucket using several statistical methods. Our results indicated that our automated PCAPs are accurate and provided convenient means for estimating water drainage in the vadose zone without the need for costly and manually time-consuming supportive systems.

Home Automation

OpenAIRE

Ahmed, Zeeshan

2010-01-01

In this paper I briefly discuss the importance of home automation system. Going in to the details I briefly present a real time designed and implemented software and hardware oriented house automation research project, capable of automating house's electricity and providing a security system to detect the presence of unexpected behavior.

Automated Diagnosis of Otitis Media: Vocabulary and Grammar

Science.gov (United States)

Kuruvilla, Anupama; Hoberman, Alejandro; Kovačević, Jelena

2013-01-01

We propose a novel automated algorithm for classifying diagnostic categories of otitis media: acute otitis media, otitis media with effusion, and no effusion. Acute otitis media represents a bacterial superinfection of the middle ear fluid, while otitis media with effusion represents a sterile effusion that tends to subside spontaneously. Diagnosing children with acute otitis media is difficult, often leading to overprescription of antibiotics as they are beneficial only for children with acute otitis media. This underscores the need for an accurate and automated diagnostic algorithm. To that end, we design a feature set understood by both otoscopists and engineers based on the actual visual cues used by otoscopists; we term this the otitis media vocabulary. We also design a process to combine the vocabulary terms based on the decision process used by otoscopists; we term this the otitis media grammar. The algorithm achieves 89.9% classification accuracy, outperforming both clinicians who did not receive special training and state-of-the-art classifiers. PMID:23997759

Lexical evolution rates derived from automated stability measures

Science.gov (United States)

Petroni, Filippo; Serva, Maurizio

2010-03-01

Phylogenetic trees can be reconstructed from the matrix which contains the distances between all pairs of languages in a family. Recently, we proposed a new method which uses normalized Levenshtein distances among words with the same meaning and averages over all the items of a given list. Decisions about the number of items in the input lists for language comparison have been debated since the beginning of glottochronology. The point is that words associated with some of the meanings have a rapid lexical evolution. Therefore, a large vocabulary comparison is only apparently more accurate than a smaller one, since many of the words do not carry any useful information. In principle, one should find the optimal length of the input lists, studying the stability of the different items. In this paper we tackle the problem with an automated methodology based only on our normalized Levenshtein distance. With this approach, the program of an automated reconstruction of language relationships is completed.

RCrane: semi-automated RNA model building.

Science.gov (United States)

Keating, Kevin S; Pyle, Anna Marie

2012-08-01

RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems.

Negative chemical ionization gas chromatography coupled to hybrid quadrupole time-of-flight mass spectrometry and automated accurate mass data processing for determination of pesticides in fruit and vegetables.

Science.gov (United States)

Besil, Natalia; Uclés, Samanta; Mezcúa, Milagros; Heinzen, Horacio; Fernández-Alba, Amadeo R

2015-08-01

Gas chromatography coupled to high resolution hybrid quadrupole time-of-flight mass spectrometry (GC-QTOF MS), operating in negative chemical ionization (NCI) mode and combining full scan with MSMS experiments using accurate mass analysis, has been explored for the automated determination of pesticide residues in fruit and vegetables. Seventy compounds were included in this approach where 50 % of them are not approved by the EU legislation. A global 76 % of the analytes could be identified at 1 μg kg(-1). Recovery studies were developed at three concentration levels (1, 5, and 10 μg kg(-1)). Seventy-seven percent of the detected pesticides at the lowest level yielded recoveries within the 70 %-120 % range, whereas 94 % could be quantified at 5 μg kg(-1), and the 100 % were determined at 10 μg kg(-1). Good repeatability, expressed as relative standard deviation (RSD home-made database was developed and applied to an automatic accurate mass data processing. Measured mass accuracies of the generated ions were mainly less than 5 ppm for at least one diagnostic ion. When only one ion was obtained in the single-stage NCI-MS, a representative product ion from MSMS experiments was used as identification criterion. A total of 30 real samples were analyzed and 67 % of the samples were positive for 12 different pesticides in the range 1.0-1321.3 μg kg(-1).

Snow-covered Landsat time series stacks improve automated disturbance mapping accuracy in forested landscapes

Science.gov (United States)

Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy B. Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

2011-01-01

Accurate landscape-scale maps of forests and associated disturbances are critical to augment studies on biodiversity, ecosystem services, and the carbon cycle, especially in terms of understanding how the spatial and temporal complexities of damage sustained from disturbances influence forest structure and function. Vegetation change tracker (VCT) is a highly automated...

Mass spectrometry for protein quantification in biomarker discovery.

Science.gov (United States)

Wang, Mu; You, Jinsam

2012-01-01

Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

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

RCrane: semi-automated RNA model building

International Nuclear Information System (INIS)

Keating, Kevin S.; Pyle, Anna Marie

2012-01-01

RCrane is a new tool for the partially automated building of RNA crystallographic models into electron-density maps of low or intermediate resolution. This tool helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems

APSY-NMR for protein backbone assignment in high-throughput structural biology

Energy Technology Data Exchange (ETDEWEB)

Dutta, Samit Kumar; Serrano, Pedro; Proudfoot, Andrew; Geralt, Michael [The Scripps Research Institute, Department of Integrative Structural and Computational Biology (United States); Pedrini, Bill [Paul Scherrer Institute (PSI), SwissFEL Project (Switzerland); Herrmann, Torsten [Université de Lyon, Institut des Sciences Analytiques, Centre de RMN à Très Hauts Champs, UMR 5280 CNRS, ENS Lyon, UCB Lyon 1 (France); Wüthrich, Kurt, E-mail: wuthrich@scripps.edu [The Scripps Research Institute, Department of Integrative Structural and Computational Biology (United States)

2015-01-15

A standard set of three APSY-NMR experiments has been used in daily practice to obtain polypeptide backbone NMR assignments in globular proteins with sizes up to about 150 residues, which had been identified as targets for structure determination by the Joint Center for Structural Genomics (JCSG) under the auspices of the Protein Structure Initiative (PSI). In a representative sample of 30 proteins, initial fully automated data analysis with the software UNIO-MATCH-2014 yielded complete or partial assignments for over 90 % of the residues. For most proteins the APSY data acquisition was completed in less than 30 h. The results of the automated procedure provided a basis for efficient interactive validation and extension to near-completion of the assignments by reference to the same 3D heteronuclear-resolved [{sup 1}H,{sup 1}H]-NOESY spectra that were subsequently used for the collection of conformational constraints. High-quality structures were obtained for all 30 proteins, using the J-UNIO protocol, which includes extensive automation of NMR structure determination.

Accurate and sensitive quantification of protein-DNA binding affinity.

Science.gov (United States)

Rastogi, Chaitanya; Rube, H Tomas; Kribelbauer, Judith F; Crocker, Justin; Loker, Ryan E; Martini, Gabriella D; Laptenko, Oleg; Freed-Pastor, William A; Prives, Carol; Stern, David L; Mann, Richard S; Bussemaker, Harmen J

2018-04-17

Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes. Copyright © 2018 the Author(s). Published by PNAS.

How Accurately Can the Google Web Speech API Recognize and Transcribe Japanese L2 English Learners' Oral Production?

Science.gov (United States)

Ashwell, Tim; Elam, Jesse R.

2017-01-01

The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…

VALIDATING the Accuracy of Sighten's Automated Shading Tool

Energy Technology Data Exchange (ETDEWEB)

2018-05-04

Solar companies - including installers, financiers, and distributors - leverage Sighten software to deliver accurate shading calculations and solar proposals. Sighten recently partnered with Google Project Sunroof to provide automated remote shading analysis directly within the Sighten platform. The National Renewable Energy Laboratory (NREL), in partnership with Sighten, independently verified the accuracy of Sighten's remote-shading solar access values (SAVs) on an annual basis for locations in Los Angeles, California, and Denver, Colorado.

Automated immunohistochemical method to analyze large areas of the human cortex.

Science.gov (United States)

Abbass, Mohamad; Trought, Kathleen; Long, David; Semechko, Anton; Wong, Albert H C

2018-01-15

There have been inconsistencies in the histological abnormalities found in the cerebral cortex from patients with schizophrenia, bipolar disorder and major depression. Discrepancies in previously published reports may arise from small sample sizes, inconsistent methodology and biased cell counting. We applied automated quantification of neuron density, neuron size and cortical layer thickness in large regions of the cerebral cortex in psychiatric patients. This method accurately segments DAPI positive cells that are also stained with CUX2 and FEZF2. Cortical layer thickness, neuron density and neuron size were automatically computed for each cortical layer in numerous Brodmann areas. We did not find pronounced cytoarchitectural abnormalities in the anterior cingulate cortex or orbitofrontal cortex in patients with schizophrenia, bipolar disorder or major depressive disorder. There were no significant differences in layer thickness measured in immunohistochemically stained slides compared with traditional Nissl stained slides. Automated cell counts were correlated, reliable and consistent with manual counts, while being much less time-consuming. We demonstrate the validity of using a novel automated analysis approach to post-mortem brain tissue. We were able to analyze large cortical areas and quantify specific cell populations using immunohistochemical markers. Future analyses could benefit from efficient automated analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Semi-Automated Hydrophobic Interaction Chromatography Column Scouting Used in the Two-Step Purification of Recombinant Green Fluorescent Protein

Science.gov (United States)

Murphy, Patrick J. M.

2014-01-01

Background Hydrophobic interaction chromatography (HIC) most commonly requires experimental determination (i.e., scouting) in order to select an optimal chromatographic medium for purifying a given target protein. Neither a two-step purification of untagged green fluorescent protein (GFP) from crude bacterial lysate using sequential HIC and size exclusion chromatography (SEC), nor HIC column scouting elution profiles of GFP, have been previously reported. Methods and Results Bacterial lysate expressing recombinant GFP was sequentially adsorbed to commercially available HIC columns containing butyl, octyl, and phenyl-based HIC ligands coupled to matrices of varying bead size. The lysate was fractionated using a linear ammonium phosphate salt gradient at constant pH. Collected HIC eluate fractions containing retained GFP were then pooled and further purified using high-resolution preparative SEC. Significant differences in presumptive GFP elution profiles were observed using in-line absorption spectrophotometry (A395) and post-run fluorimetry. SDS-PAGE and western blot demonstrated that fluorometric detection was the more accurate indicator of GFP elution in both HIC and SEC purification steps. Comparison of composite HIC column scouting data indicated that a phenyl ligand coupled to a 34 µm matrix produced the highest degree of target protein capture and separation. Conclusions Conducting two-step protein purification using the preferred HIC medium followed by SEC resulted in a final, concentrated product with >98% protein purity. In-line absorbance spectrophotometry was not as precise of an indicator of GFP elution as post-run fluorimetry. These findings demonstrate the importance of utilizing a combination of detection methods when evaluating purification strategies. GFP is a well-characterized model protein, used heavily in educational settings and by researchers with limited protein purification experience, and the data and strategies presented here may aid in

Streamlined sign-out of capillary protein electrophoresis using middleware and an open-source macro application

Directory of Open Access Journals (Sweden)

Gagan Mathur

2014-01-01

Full Text Available Background: Interfacing of clinical laboratory instruments with the laboratory information system (LIS via "middleware" software is increasingly common. Our clinical laboratory implemented capillary electrophoresis using a Sebia; Capillarys-2™ (Norcross, GA, USA instrument for serum and urine protein electrophoresis. Using Data Innovations Instrument Manager, an interface was established with the LIS (Cerner that allowed for bi-directional transmission of numeric data. However, the text of the interpretive pathology report was not properly transferred. To reduce manual effort and possibility for error in text data transfer, we developed scripts in AutoHotkey, a free, open-source macro-creation and automation software utility. Materials and Methods: Scripts were written to create macros that automated mouse and key strokes. The scripts retrieve the specimen accession number, capture user input text, and insert the text interpretation in the correct patient record in the desired format. Results: The scripts accurately and precisely transfer narrative interpretation into the LIS. Combined with bar-code reading by the electrophoresis instrument, the scripts transfer data efficiently to the correct patient record. In addition, the AutoHotKey script automated repetitive key strokes required for manual entry into the LIS, making protein electrophoresis sign-out easier to learn and faster to use by the pathology residents. Scripts allow for either preliminary verification by residents or final sign-out by the attending pathologist. Conclusions: Using the open-source AutoHotKey software, we successfully improved the transfer of text data between capillary electrophoresis software and the LIS. The use of open-source software tools should not be overlooked as tools to improve interfacing of laboratory instruments.

Automated NMR structure determination of stereo-array isotope labeled ubiquitin from minimal sets of spectra using the SAIL-FLYA system

Energy Technology Data Exchange (ETDEWEB)

Ikeya, Teppei [Goethe University Frankfurt am Main, Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance (Germany); Takeda, Mitsuhiro; Yoshida, Hitoshi; Terauchi, Tsutomu; Jee, Jun-Goo; Kainosho, Masatsune [Tokyo Metropolitan University, Graduate School of Science (Japan)], E-mail: kainosho@nmr.chem.metro-u.ac.jp; Guentert, Peter [Goethe University Frankfurt am Main, Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance (Germany)], E-mail: guentert@em.uni-frankfurt.de

2009-08-15

Stereo-array isotope labeling (SAIL) has been combined with the fully automated NMR structure determination algorithm FLYA to determine the three-dimensional structure of the protein ubiquitin from different sets of input NMR spectra. SAIL provides a complete stereo- and regio-specific pattern of stable isotopes that results in sharper resonance lines and reduced signal overlap, without information loss. Here we show that as a result of the superior quality of the SAIL NMR spectra, reliable, fully automated analyses of the NMR spectra and structure calculations are possible using fewer input spectra than with conventional uniformly {sup 13}C/{sup 15}N-labeled proteins. FLYA calculations with SAIL ubiquitin, using a single three-dimensional 'through-bond' spectrum (and 2D HSQC spectra) in addition to the {sup 13}C-edited and {sup 15}N-edited NOESY spectra for conformational restraints, yielded structures with an accuracy of 0.83-1.15 A for the backbone RMSD to the conventionally determined solution structure of SAIL ubiquitin. NMR structures can thus be determined almost exclusively from the NOESY spectra that yield the conformational restraints, without the need to record many spectra only for determining intermediate, auxiliary data of the chemical shift assignments. The FLYA calculations for this report resulted in 252 ubiquitin structure bundles, obtained with different input data but identical structure calculation and refinement methods. These structures cover the entire range from highly accurate structures to seriously, but not trivially, wrong structures, and thus constitute a valuable database for the substantiation of structure validation methods.

Automated NMR structure determination of stereo-array isotope labeled ubiquitin from minimal sets of spectra using the SAIL-FLYA system

International Nuclear Information System (INIS)

Ikeya, Teppei; Takeda, Mitsuhiro; Yoshida, Hitoshi; Terauchi, Tsutomu; Jee, Jun-Goo; Kainosho, Masatsune; Guentert, Peter

2009-01-01

Stereo-array isotope labeling (SAIL) has been combined with the fully automated NMR structure determination algorithm FLYA to determine the three-dimensional structure of the protein ubiquitin from different sets of input NMR spectra. SAIL provides a complete stereo- and regio-specific pattern of stable isotopes that results in sharper resonance lines and reduced signal overlap, without information loss. Here we show that as a result of the superior quality of the SAIL NMR spectra, reliable, fully automated analyses of the NMR spectra and structure calculations are possible using fewer input spectra than with conventional uniformly 13 C/ 15 N-labeled proteins. FLYA calculations with SAIL ubiquitin, using a single three-dimensional 'through-bond' spectrum (and 2D HSQC spectra) in addition to the 13 C-edited and 15 N-edited NOESY spectra for conformational restraints, yielded structures with an accuracy of 0.83-1.15 A for the backbone RMSD to the conventionally determined solution structure of SAIL ubiquitin. NMR structures can thus be determined almost exclusively from the NOESY spectra that yield the conformational restraints, without the need to record many spectra only for determining intermediate, auxiliary data of the chemical shift assignments. The FLYA calculations for this report resulted in 252 ubiquitin structure bundles, obtained with different input data but identical structure calculation and refinement methods. These structures cover the entire range from highly accurate structures to seriously, but not trivially, wrong structures, and thus constitute a valuable database for the substantiation of structure validation methods

Automated NMR structure determination of stereo-array isotope labeled ubiquitin from minimal sets of spectra using the SAIL-FLYA system.

Science.gov (United States)

Ikeya, Teppei; Takeda, Mitsuhiro; Yoshida, Hitoshi; Terauchi, Tsutomu; Jee, Jun-Goo; Kainosho, Masatsune; Güntert, Peter

2009-08-01

Stereo-array isotope labeling (SAIL) has been combined with the fully automated NMR structure determination algorithm FLYA to determine the three-dimensional structure of the protein ubiquitin from different sets of input NMR spectra. SAIL provides a complete stereo- and regio-specific pattern of stable isotopes that results in sharper resonance lines and reduced signal overlap, without information loss. Here we show that as a result of the superior quality of the SAIL NMR spectra, reliable, fully automated analyses of the NMR spectra and structure calculations are possible using fewer input spectra than with conventional uniformly 13C/15N-labeled proteins. FLYA calculations with SAIL ubiquitin, using a single three-dimensional "through-bond" spectrum (and 2D HSQC spectra) in addition to the 13C-edited and 15N-edited NOESY spectra for conformational restraints, yielded structures with an accuracy of 0.83-1.15 A for the backbone RMSD to the conventionally determined solution structure of SAIL ubiquitin. NMR structures can thus be determined almost exclusively from the NOESY spectra that yield the conformational restraints, without the need to record many spectra only for determining intermediate, auxiliary data of the chemical shift assignments. The FLYA calculations for this report resulted in 252 ubiquitin structure bundles, obtained with different input data but identical structure calculation and refinement methods. These structures cover the entire range from highly accurate structures to seriously, but not trivially, wrong structures, and thus constitute a valuable database for the substantiation of structure validation methods.

SURF'S UP! – Protein classification by surface comparisons

Indian Academy of Sciences (India)

Prakash

encounter large protein families with only a few members of ... server for analysis of functional relationships in protein families, as inferred from protein surface maps comparison ... features, SURF'S UP! can work with models obtained from comparative modelling. ... 1997) or, if the user is confident in the quality of automated.

Solid-phase synthesis of protein-polymers on reversible immobilization supports.

Science.gov (United States)

Murata, Hironobu; Carmali, Sheiliza; Baker, Stefanie L; Matyjaszewski, Krzysztof; Russell, Alan J

2018-02-27

Facile automated biomacromolecule synthesis is at the heart of blending synthetic and biologic worlds. Full access to abiotic/biotic synthetic diversity first occurred when chemistry was developed to grow nucleic acids and peptides from reversibly immobilized precursors. Protein-polymer conjugates, however, have always been synthesized in solution in multi-step, multi-day processes that couple innovative chemistry with challenging purification. Here we report the generation of protein-polymer hybrids synthesized by protein-ATRP on reversible immobilization supports (PARIS). We utilized modified agarose beads to covalently and reversibly couple to proteins in amino-specific reactions. We then modified reversibly immobilized proteins with protein-reactive ATRP initiators and, after ATRP, we released and analyzed the protein polymers. The activity and stability of PARIS-synthesized and solution-synthesized conjugates demonstrated that PARIS was an effective, rapid, and simple method to generate protein-polymer conjugates. Automation of PARIS significantly reduced synthesis/purification timelines, thereby opening a path to changing how to generate protein-polymer conjugates.

Automated main-chain model building by template matching and iterative fragment extension

International Nuclear Information System (INIS)

Terwilliger, Thomas C.

2003-01-01

A method for automated macromolecular main-chain model building is described. An algorithm for the automated macromolecular model building of polypeptide backbones is described. The procedure is hierarchical. In the initial stages, many overlapping polypeptide fragments are built. In subsequent stages, the fragments are extended and then connected. Identification of the locations of helical and β-strand regions is carried out by FFT-based template matching. Fragment libraries of helices and β-strands from refined protein structures are then positioned at the potential locations of helices and strands and the longest segments that fit the electron-density map are chosen. The helices and strands are then extended using fragment libraries consisting of sequences three amino acids long derived from refined protein structures. The resulting segments of polypeptide chain are then connected by choosing those which overlap at two or more C α positions. The fully automated procedure has been implemented in RESOLVE and is capable of model building at resolutions as low as 3.5 Å. The algorithm is useful for building a preliminary main-chain model that can serve as a basis for refinement and side-chain addition

Protein structural similarity search by Ramachandran codes

Directory of Open Access Journals (Sweden)

Chang Chih-Hung

2007-08-01

Full Text Available Abstract Background Protein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed, several methods have been designed to reduce three-dimensional protein structures to one-dimensional text strings that are then analyzed by traditional sequence alignment methods; however, the accuracy is usually sacrificed and the speed is still unable to match sequence similarity search tools. Here, we aimed to improve the linear encoding methodology and develop efficient search tools that can rapidly retrieve structural homologs from large protein databases. Results We propose a new linear encoding method, SARST (Structural similarity search Aided by Ramachandran Sequential Transformation. SARST transforms protein structures into text strings through a Ramachandran map organized by nearest-neighbor clustering and uses a regenerative approach to produce substitution matrices. Then, classical sequence similarity search methods can be applied to the structural similarity search. Its accuracy is similar to Combinatorial Extension (CE and works over 243,000 times faster, searching 34,000 proteins in 0.34 sec with a 3.2-GHz CPU. SARST provides statistically meaningful expectation values to assess the retrieved information. It has been implemented into a web service and a stand-alone Java program that is able to run on many different platforms. Conclusion As a database search method, SARST can rapidly distinguish high from low similarities and efficiently retrieve homologous structures. It demonstrates that the easily accessible linear encoding methodology has the potential to serve as a foundation for efficient protein structural similarity search tools. These search tools are supposed applicable to automated and high-throughput functional annotations or predictions for the ever increasing number of published protein structures in this post-genomic era.

Automated titration method for use on blended asphalts

Science.gov (United States)

Pauli, Adam T [Cheyenne, WY; Robertson, Raymond E [Laramie, WY; Branthaver, Jan F [Chatham, IL; Schabron, John F [Laramie, WY

2012-08-07

A system for determining parameters and compatibility of a substance such as an asphalt or other petroleum substance uses titration to highly accurately determine one or more flocculation occurrences and is especially applicable to the determination or use of Heithaus parameters and optimal mixing of various asphalt stocks. In a preferred embodiment, automated titration in an oxygen gas exclusive system and further using spectrophotometric analysis (2-8) of solution turbidity is presented. A reversible titration technique enabling in-situ titration measurement of various solution concentrations is also presented.

Moving toward the automation of the systematic review process: a summary of discussions at the second meeting of International Collaboration for the Automation of Systematic Reviews (ICASR).

Science.gov (United States)

O'Connor, Annette M; Tsafnat, Guy; Gilbert, Stephen B; Thayer, Kristina A; Wolfe, Mary S

2018-01-09

The second meeting of the International Collaboration for Automation of Systematic Reviews (ICASR) was held 3-4 October 2016 in Philadelphia, Pennsylvania, USA. ICASR is an interdisciplinary group whose aim is to maximize the use of technology for conducting rapid, accurate, and efficient systematic reviews of scientific evidence. Having automated tools for systematic review should enable more transparent and timely review, maximizing the potential for identifying and translating research findings to practical application. The meeting brought together multiple stakeholder groups including users of summarized research, methodologists who explore production processes and systematic review quality, and technologists such as software developers, statisticians, and vendors. This diversity of participants was intended to ensure effective communication with numerous stakeholders about progress toward automation of systematic reviews and stimulate discussion about potential solutions to identified challenges. The meeting highlighted challenges, both simple and complex, and raised awareness among participants about ongoing efforts by various stakeholders. An outcome of this forum was to identify several short-term projects that participants felt would advance the automation of tasks in the systematic review workflow including (1) fostering better understanding about available tools, (2) developing validated datasets for testing new tools, (3) determining a standard method to facilitate interoperability of tools such as through an application programming interface or API, and (4) establishing criteria to evaluate the quality of tools' output. ICASR 2016 provided a beneficial forum to foster focused discussion about tool development and resources and reconfirm ICASR members' commitment toward systematic reviews' automation.

PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases.

Science.gov (United States)

Floden, Evan W; Tommaso, Paolo D; Chatzou, Maria; Magis, Cedrik; Notredame, Cedric; Chang, Jia-Ming

2016-07-08

The PSI/TM-Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non-redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. The web server is available at http://tcoffee.crg.cat/tmcoffee. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Process automation

International Nuclear Information System (INIS)

Moser, D.R.

1986-01-01

Process automation technology has been pursued in the chemical processing industries and to a very limited extent in nuclear fuel reprocessing. Its effective use has been restricted in the past by the lack of diverse and reliable process instrumentation and the unavailability of sophisticated software designed for process control. The Integrated Equipment Test (IET) facility was developed by the Consolidated Fuel Reprocessing Program (CFRP) in part to demonstrate new concepts for control of advanced nuclear fuel reprocessing plants. A demonstration of fuel reprocessing equipment automation using advanced instrumentation and a modern, microprocessor-based control system is nearing completion in the facility. This facility provides for the synergistic testing of all chemical process features of a prototypical fuel reprocessing plant that can be attained with unirradiated uranium-bearing feed materials. The unique equipment and mission of the IET facility make it an ideal test bed for automation studies. This effort will provide for the demonstration of the plant automation concept and for the development of techniques for similar applications in a full-scale plant. A set of preliminary recommendations for implementing process automation has been compiled. Some of these concepts are not generally recognized or accepted. The automation work now under way in the IET facility should be useful to others in helping avoid costly mistakes because of the underutilization or misapplication of process automation. 6 figs

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.

Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles.

Science.gov (United States)

Zheng, Wu; Blake, Catherine

2015-10-01

Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts. Copyright © 2015 Elsevier Inc. All rights reserved.

High-throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

International Nuclear Information System (INIS)

Sloane, A.J.; Duff, J.L.; Hopwood, F.G.; Wilson, N.L.; Smith, P.E.; Hill, C.J.; Packer, N.H.; Williams, K.L.; Gooley, A.A.; Cole, R.A.; Cooley, P.W.; Wallace, D.B.

2001-01-01

We describe a 'chemical printer' that uses piezoelectric pulsing for rapid and accurate microdispensing of picolitre volumes of fluid for proteomic analysis of 'protein macroarrays'. Unlike positive transfer and pin transfer systems, our printer dispenses fluid in a non-contact process that ensures that the fluid source cannot be contaminated by substrate during a printing event. We demonstrate automated delivery of enzyme and matrix solutions for on-membrane protein digestion and subsequent peptide mass fingerprinting (pmf) analysis directly from the membrane surface using matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). This approach bypasses the more commonly used multi-step procedures, thereby permitting a more rapid procedure for protein identification. We also highlight the advantage of printing different chemistries onto an individual protein spot for multiple microscale analyses. This ability is particularly useful when detailed characterisation of rare and valuable sample is required. Using a combination of PNGase F and trypsin we have mapped sites of N-glycosylation using on-membrane digestion strategies. We also demonstrate the ability to print multiple serum samples in a micro-ELISA format and rapidly screen a protein macroarray of human blood plasma for pathogen-derived antigens. We anticipate that the 'chemical printer' will be a major component of proteomic platforms for high-throughput protein identification and characterisation with widespread applications in biomedical and diagnostic discovery

High throughput protein production screening

Science.gov (United States)

Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

2009-09-08

Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

Human/Automation Trade Methodology for the Moon, Mars and Beyond

Science.gov (United States)

Korsmeyer, David J.

2009-01-01

It is possible to create a consistent trade methodology that can characterize operations model alternatives for crewed exploration missions. For example, a trade-space that is organized around the objective of maximizing Crew Exploration Vehicle (CEV) independence would have the input as a classification of the category of analysis to be conducted or decision to be made, and a commitment to a detailed point in a mission profile during which the analysis or decision is to be made. For example, does the decision have to do with crew activity planning, or life support? Is the mission phase trans-Earth injection, cruise, or lunar descent? Different kinds of decision analysis of the trade-space between human and automated decisions will occurs at different points in a mission's profile. The necessary objectives at a given point in time during a mission will call for different kinds of response with respect to where and how computers and automation are expected to help provide an accurate, safe, and timely response. In this paper, a consistent methodology for assessing the trades between human and automated decisions on-board will be presented and various examples discussed.

A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

NARCIS (Netherlands)

Melo, Rita; Fieldhouse, Robert; Melo, André; Correia, João D G; Cordeiro, Maria Natália D S; Gümüş, Zeynep H; Costa, Joaquim; Bonvin, Alexandre M J J; de Sousa Moreira, Irina

2016-01-01

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model

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.

Reverse Phase Protein Arrays for High-throughput Toxicity Screening

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

High-throughput screening is extensively applied for identification of drug targets and drug discovery and recently it found entry into toxicity testing. Reverse phase protein arrays (RPPAs) are used widespread for quantification of protein markers. We reasoned that RPPAs also can be utilized...... beneficially in automated high-throughput toxicity testing. An advantage of using RPPAs is that, in addition to the baseline toxicity readout, they allow testing of multiple markers of toxicity, such as inflammatory responses, which do not necessarily cumulate in cell death. We used transfection of si......RNAs with known killing effects as a model system to demonstrate that RPPA-based protein quantification can serve as substitute readout of cell viability, hereby reliably reflecting toxicity. In terms of automation, cell exposure, protein harvest, serial dilution and sample reformatting were performed using...

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

Science.gov (United States)

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

Directory of Open Access Journals (Sweden)

Marlies Verschuuren

Full Text Available A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND, which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

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.

Fully automated MRI-guided robotics for prostate brachytherapy

International Nuclear Information System (INIS)

Stoianovici, D.; Vigaru, B.; Petrisor, D.; Muntener, M.; Patriciu, A.; Song, D.

2008-01-01

The uncertainties encountered in the deployment of brachytherapy seeds are related to the commonly used ultrasound imager and the basic instrumentation used for the implant. An alternative solution is under development in which a fully automated robot is used to place the seeds according to the dosimetry plan under direct MRI-guidance. Incorporation of MRI-guidance creates potential for physiological and molecular image-guided therapies. Moreover, MRI-guided brachytherapy is also enabling for re-estimating dosimetry during the procedure, because with the MRI the seeds already implanted can be localised. An MRI compatible robot (MrBot) was developed. The robot is designed for transperineal percutaneous prostate interventions, and customised for fully automated MRI-guided brachytherapy. With different end-effectors, the robot applies to other image-guided interventions of the prostate. The robot is constructed of non-magnetic and dielectric materials and is electricity free using pneumatic actuation and optic sensing. A new motor (PneuStep) was purposely developed to set this robot in motion. The robot fits alongside the patient in closed-bore MRI scanners. It is able to stay fully operational during MR imaging without deteriorating the quality of the scan. In vitro, cadaver, and animal tests showed millimetre needle targeting accuracy, and very precise seed placement. The robot tested without any interference up to 7T. The robot is the first fully automated robot to function in MRI scanners. Its first application is MRI-guided seed brachytherapy. It is capable of automated, highly accurate needle placement. Extensive testing is in progress prior to clinical trials. Preliminary results show that the robot may become a useful image-guided intervention instrument. (author)

A Droplet Microfluidic Platform for Automating Genetic Engineering.

Science.gov (United States)

Gach, Philip C; Shih, Steve C C; Sustarich, Jess; Keasling, Jay D; Hillson, Nathan J; Adams, Paul D; Singh, Anup K

2016-05-20

We present a water-in-oil droplet microfluidic platform for transformation, culture and expression of recombinant proteins in multiple host organisms including bacteria, yeast and fungi. The platform consists of a hybrid digital microfluidic/channel-based droplet chip with integrated temperature control to allow complete automation and integration of plasmid addition, heat-shock transformation, addition of selection medium, culture, and protein expression. The microfluidic format permitted significant reduction in consumption (100-fold) of expensive reagents such as DNA and enzymes compared to the benchtop method. The chip contains a channel to continuously replenish oil to the culture chamber to provide a fresh supply of oxygen to the cells for long-term (∼5 days) cell culture. The flow channel also replenished oil lost to evaporation and increased the number of droplets that could be processed and cultured. The platform was validated by transforming several plasmids into Escherichia coli including plasmids containing genes for fluorescent proteins GFP, BFP and RFP; plasmids with selectable markers for ampicillin or kanamycin resistance; and a Golden Gate DNA assembly reaction. We also demonstrate the applicability of this platform for transformation in widely used eukaryotic organisms such as Saccharomyces cerevisiae and Aspergillus niger. Duration and temperatures of the microfluidic heat-shock procedures were optimized to yield transformation efficiencies comparable to those obtained by benchtop methods with a throughput up to 6 droplets/min. The proposed platform offers potential for automation of molecular biology experiments significantly reducing cost, time and variability while improving throughput.

Automated SmartPrep tracker positioning in liver MRI scans

International Nuclear Information System (INIS)

Goto, Takao; Kabasawa, Hiroyuki

2013-01-01

This paper presents a new method for automated SmartPrep tracker positioning in liver MRI scans. SmartPrep is used to monitor the contrast bolus signal in order to detect the arrival time of the bolus. Accurately placing the tracker in the aorta while viewing three planar scout images is a difficult task for the operator and is an important problem from the workflow standpoint. The development of an automated SmartPrep tracker would therefore help to improve workflow in liver MRI scans. In our proposed method, the aorta is detected using AdaBoost (which is a machine learning technique) by searching around the cerebral spinal fluid (CSF) in the spinal cord. Analysis of scout scan images showed that our detection method functioned properly for a variety of axial MR images without intensity correction. A total of 234 images reconstructed from the datasets of 64 volunteers were analyzed, and the results showed that the detection error for the aorta was approximately 3 mm. (author)

Automated building of organometallic complexes from 3D fragments.

Science.gov (United States)

Foscato, Marco; Venkatraman, Vishwesh; Occhipinti, Giovanni; Alsberg, Bjørn K; Jensen, Vidar R

2014-07-28

A method for the automated construction of three-dimensional (3D) molecular models of organometallic species in design studies is described. Molecular structure fragments derived from crystallographic structures and accurate molecular-level calculations are used as 3D building blocks in the construction of multiple molecular models of analogous compounds. The method allows for precise control of stereochemistry and geometrical features that may otherwise be very challenging, or even impossible, to achieve with commonly available generators of 3D chemical structures. The new method was tested in the construction of three sets of active or metastable organometallic species of catalytic reactions in the homogeneous phase. The performance of the method was compared with those of commonly available methods for automated generation of 3D models, demonstrating higher accuracy of the prepared 3D models in general, and, in particular, a much wider range with respect to the kind of chemical structures that can be built automatically, with capabilities far beyond standard organic and main-group chemistry.

EDM-DEDM and protein crystal structure solution.

Science.gov (United States)

Caliandro, Rocco; Carrozzini, Benedetta; Cascarano, Giovanni Luca; Giacovazzo, Carmelo; Mazzone, Anna Maria; Siliqi, Dritan

2009-05-01

Electron-density modification (EDM) procedures are the classical tool for driving model phases closer to those of the target structure. They are often combined with automated model-building programs to provide a correct protein model. The task is not always performed, mostly because of the large initial phase error. A recently proposed procedure combined EDM with DEDM (difference electron-density modification); the method was applied to the refinement of phases obtained by molecular replacement, ab initio or SAD phasing [Caliandro, Carrozzini, Cascarano, Giacovazzo, Mazzone & Siliqi (2009), Acta Cryst. D65, 249-256] and was more effective in improving phases than EDM alone. In this paper, a novel fully automated protocol for protein structure refinement based on the iterative application of automated model-building programs combined with the additional power derived from the EDM-DEDM algorithm is presented. The cyclic procedure was successfully tested on challenging cases for which all other approaches had failed.

A rapid and accurate method for determining protein content in dairy products based on asynchronous-injection alternating merging zone flow-injection spectrophotometry.

Science.gov (United States)

Liang, Qin-Qin; Li, Yong-Sheng

2013-12-01

An accurate and rapid method and a system to determine protein content using asynchronous-injection alternating merging zone flow-injection spectrophotometry based on reaction between coomassie brilliant blue G250 (CBBG) and protein was established. Main merit of our approach is that it can avoid interferences of other nitric-compounds in samples, such as melamine and urea. Optimized conditions are as follows: Concentrations of CBBG, polyvinyl alcohol (PVA), NaCl and HCl are 150 mg/l, 30 mg/l, 0.1 mol/l and 1.0% (v/v), respectively; volumes of the sample and reagent are 150 μl and 30 μl, respectively; length of a reaction coil is 200 cm; total flow rate is 2.65 ml/min. The linear range of the method is 0.5-15 mg/l (BSA), its detection limit is 0.05 mg/l, relative standard deviation is less than 1.87% (n=11), and analytical speed is 60 samples per hour. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prevalence of discordant microscopic changes with automated CBC analysis

Directory of Open Access Journals (Sweden)

Fabiano de Jesus Santos

2014-12-01

Full Text Available Introduction:The most common cause of diagnostic error is related to errors in laboratory tests as well as errors of results interpretation. In order to reduce them, the laboratory currently has modern equipment which provides accurate and reliable results. The development of automation has revolutionized the laboratory procedures in Brazil and worldwide.Objective:To determine the prevalence of microscopic changes present in blood slides concordant and discordant with results obtained using fully automated procedures.Materials and method:From January to July 2013, 1,000 hematological parameters slides were analyzed. Automated analysis was performed on last generation equipment, which methodology is based on electrical impedance, and is able to quantify all the figurative elements of the blood in a universe of 22 parameters. The microscopy was performed by two experts in microscopy simultaneously.Results:The data showed that only 42.70% were concordant, comparing with 57.30% discordant. The main findings among discordant were: Changes in red blood cells 43.70% (n = 250, white blood cells 38.46% (n = 220, and number of platelet 17.80% (n = 102.Discussion:The data show that some results are not consistent with clinical or physiological state of an individual, and cannot be explained because they have not been investigated, which may compromise the final diagnosis.Conclusion:It was observed that it is of fundamental importance that the microscopy qualitative analysis must be performed in parallel with automated analysis in order to obtain reliable results, causing a positive impact on the prevention, diagnosis, prognosis, and therapeutic follow-up.

PSAIA – Protein Structure and Interaction Analyzer

Directory of Open Access Journals (Sweden)

Vlahoviček Kristian

2008-04-01

Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

Developing effective automated feedback in temporal bone surgery simulation.

Science.gov (United States)

Wijewickrema, Sudanthi; Piromchai, Patorn; Zhou, Yun; Ioannou, Ioanna; Bailey, James; Kennedy, Gregor; O'Leary, Stephen

2015-06-01

We aim to test the effectiveness, accuracy, and usefulness of an automated feedback system in facilitating skill acquisition in virtual reality surgery. We evaluate the performance of the feedback system through a randomized controlled trial of 24 students allocated to feedback and nonfeedback groups. The feedback system was based on the Melbourne University temporal bone surgery simulator. The study was conducted at the simulation laboratory of the Royal Victorian Eye and Ear Hospital, Melbourne. The study participants were medical students from the University of Melbourne, who were asked to perform virtual cortical mastoidectomy on the simulator. The extent to which the drilling behavior of the feedback and nonfeedback groups differed was used to evaluate the effectiveness of the system. Its accuracy was determined through a postexperiment observational assessment of recordings made during the experiment by an expert surgeon. Its usability was evaluated using students' self-reports of their impressions of the system. A Friedman's test showed that there was a significant improvement in the drilling performance of the feedback group, χ(2)(1) = 14.450, P feedback (when trainee behavior was detected) 88.6% of the time and appropriate feedback (accurate advice) 84.2% of the time. Participants' opinions about the usefulness of the system were highly positive. The automated feedback system was observed to be effective in improving surgical technique, and the provided feedback was found to be accurate and useful. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images.

Science.gov (United States)

Wang, Kang; Jayadev, Chaitra; Nittala, Muneeswar G; Velaga, Swetha B; Ramachandra, Chaithanya A; Bhaskaranand, Malavika; Bhat, Sandeep; Solanki, Kaushal; Sadda, SriniVas R

2018-03-01

We examined the sensitivity and specificity of an automated algorithm for detecting referral-warranted diabetic retinopathy (DR) on Optos ultrawidefield (UWF) pseudocolour images. Patients with diabetes were recruited for UWF imaging. A total of 383 subjects (754 eyes) were enrolled. Nonproliferative DR graded to be moderate or higher on the 5-level International Clinical Diabetic Retinopathy (ICDR) severity scale was considered as grounds for referral. The software automatically detected DR lesions using the previously trained classifiers and classified each image in the test set as referral-warranted or not warranted. Sensitivity, specificity and the area under the receiver operating curve (AUROC) of the algorithm were computed. The automated algorithm achieved a 91.7%/90.3% sensitivity (95% CI 90.1-93.9/80.4-89.4) with a 50.0%/53.6% specificity (95% CI 31.7-72.8/36.5-71.4) for detecting referral-warranted retinopathy at the patient/eye levels, respectively; the AUROC was 0.873/0.851 (95% CI 0.819-0.922/0.804-0.894). Diabetic retinopathy (DR) lesions were detected from Optos pseudocolour UWF images using an automated algorithm. Images were classified as referral-warranted DR with a high degree of sensitivity and moderate specificity. Automated analysis of UWF images could be of value in DR screening programmes and could allow for more complete and accurate disease staging. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Lean automation development : applying lean principles to the automation development process

OpenAIRE

Granlund, Anna; Wiktorsson, Magnus; Grahn, Sten; Friedler, Niklas

2014-01-01

By a broad empirical study it is indicated that automation development show potential of improvement. In the paper, 13 lean product development principles are contrasted to the automation development process and it is suggested why and how these principles can facilitate, support and improve the automation development process. The paper summarises a description of what characterises a lean automation development process and what consequences it entails. Main differences compared to current pr...

Automated path length and M56 measurements at Jefferson Lab

International Nuclear Information System (INIS)

Hardy, D.; Tang, J.; Legg, R.

1997-01-01

Accurate measurement of path length and path length changes versus momentum (M 56 ) are critical for maintaining minimum beam energy spread in the CEBAF (Continuous Electron Beam Accelerator Facility) accelerator at the Thomas Jefferson National Accelerator Facility (Jefferson Lab). The relative path length for each circuit of the beam (1256m) must be equal within 1.5 degrees of 1497 MHz RF phase. A relative path length measurement is made by measuring the relative phases of RF signals from a cavity that is separately excited for each pass of a 4.2 μs pulsed beam. This method distinguishes the path length to less than 0.5 path length error. The development of a VME based automated measurement system for path length and M 56 has contributed to faster machine setup time and has the potential for use as a feedback parameter for automated control

Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

Energy Technology Data Exchange (ETDEWEB)

Haas, B J; Salzberg, S L; Zhu, W; Pertea, M; Allen, J E; Orvis, J; White, O; Buell, C R; Wortman, J R

2007-12-10

EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics

DEFF Research Database (Denmark)

Ong, S.E.; Blagoev, B.; Kratchmarova, I.

2002-01-01

Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. H...

Automated Classification of Asteroids into Families at Work

Science.gov (United States)

Knežević, Zoran; Milani, Andrea; Cellino, Alberto; Novaković, Bojan; Spoto, Federica; Paolicchi, Paolo

2014-07-01

We have recently proposed a new approach to the asteroid family classification by combining the classical HCM method with an automated procedure to add newly discovered members to existing families. This approach is specifically intended to cope with ever increasing asteroid data sets, and consists of several steps to segment the problem and handle the very large amount of data in an efficient and accurate manner. We briefly present all these steps and show the results from three subsequent updates making use of only the automated step of attributing the newly numbered asteroids to the known families. We describe the changes of the individual families membership, as well as the evolution of the classification due to the newly added intersections between the families, resolved candidate family mergers, and emergence of the new candidates for the mergers. We thus demonstrate how by the new approach the asteroid family classification becomes stable in general terms (converging towards a permanent list of confirmed families), and in the same time evolving in details (to account for the newly discovered asteroids) at each update.

Both Automation and Paper.

Science.gov (United States)

Purcell, Royal

1988-01-01

Discusses the concept of a paperless society and the current situation in library automation. Various applications of automation and telecommunications are addressed, and future library automation is considered. Automation at the Monroe County Public Library in Bloomington, Indiana, is described as an example. (MES)

Automated Groundwater Screening

International Nuclear Information System (INIS)

Taylor, Glenn A.; Collard, Leonard B.

2005-01-01

The Automated Intruder Analysis has been extended to include an Automated Ground Water Screening option. This option screens 825 radionuclides while rigorously applying the National Council on Radiation Protection (NCRP) methodology. An extension to that methodology is presented to give a more realistic screening factor for those radionuclides which have significant daughters. The extension has the promise of reducing the number of radionuclides which must be tracked by the customer. By combining the Automated Intruder Analysis with the Automated Groundwater Screening a consistent set of assumptions and databases is used. A method is proposed to eliminate trigger values by performing rigorous calculation of the screening factor thereby reducing the number of radionuclides sent to further analysis. Using the same problem definitions as in previous groundwater screenings, the automated groundwater screening found one additional nuclide, Ge-68, which failed the screening. It also found that 18 of the 57 radionuclides contained in NCRP Table 3.1 failed the screening. This report describes the automated groundwater screening computer application

Automation of BESSY scanning tables

International Nuclear Information System (INIS)

Hanton, J.; Kesteman, J.

1981-01-01

A micro processor M6800 is used for the automation of scanning and premeasuring BESSY tables. The tasks achieved by the micro processor are: 1. control of spooling of the four asynchronous film winding devices and switching on and off the 4 projections lamps, 2. pre-processing of the data coming from a bi-polar coordinates measuring device, 3. bi-directional interchange of informations between the operator, the BESSY table and the DEC PDP 11/34 mini computer controling the scanning operations, 4. control of the magnification on the table by swapping the projection lenses of appropriate focal lengths and the associated light boxes (under development). In connection with point 4, study is being made for the use of BESSY tables for accurate measurements (+/-5 microns), by encoding the displacements of the projections lenses. (orig.)

Steam generator automated eddy current data analysis: A benchmarking study. Final report

International Nuclear Information System (INIS)

Brown, S.D.

1998-12-01

The eddy current examination of steam generator tubes is a very demanding process. Challenges include: complex signal analysis, massive amount of data to be reviewed quickly with extreme precision and accuracy, shortages of data analysts during peak periods, and the desire to reduce examination costs. One method to address these challenges is by incorporating automation into the data analysis process. Specific advantages, which automated data analysis has the potential to provide, include the ability to analyze data more quickly, consistently and accurately than can be performed manually. Also, automated data analysis can potentially perform the data analysis function with significantly smaller levels of analyst staffing. Despite the clear advantages that an automated data analysis system has the potential to provide, no automated system has been produced and qualified that can perform all of the functions that utility engineers demand. This report investigates the current status of automated data analysis, both at the commercial and developmental level. A summary of the various commercial and developmental data analysis systems is provided which includes the signal processing methodologies used and, where available, the performance data obtained for each system. Also, included in this report is input from seventeen research organizations regarding the actions required and obstacles to be overcome in order to bring automatic data analysis from the laboratory into the field environment. In order to provide assistance with ongoing and future research efforts in the automated data analysis arena, the most promising approaches to signal processing are described in this report. These approaches include: wavelet applications, pattern recognition, template matching, expert systems, artificial neural networks, fuzzy logic, case based reasoning and genetic algorithms. Utility engineers and NDE researchers can use this information to assist in developing automated data

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.)

Accurate and Reliable Prediction of the Binding Affinities of Macrocycles to Their Protein Targets.

Science.gov (United States)

Yu, Haoyu S; Deng, Yuqing; Wu, Yujie; Sindhikara, Dan; Rask, Amy R; Kimura, Takayuki; Abel, Robert; Wang, Lingle

2017-12-12

Macrocycles have been emerging as a very important drug class in the past few decades largely due to their expanded chemical diversity benefiting from advances in synthetic methods. Macrocyclization has been recognized as an effective way to restrict the conformational space of acyclic small molecule inhibitors with the hope of improving potency, selectivity, and metabolic stability. Because of their relatively larger size as compared to typical small molecule drugs and the complexity of the structures, efficient sampling of the accessible macrocycle conformational space and accurate prediction of their binding affinities to their target protein receptors poses a great challenge of central importance in computational macrocycle drug design. In this article, we present a novel method for relative binding free energy calculations between macrocycles with different ring sizes and between the macrocycles and their corresponding acyclic counterparts. We have applied the method to seven pharmaceutically interesting data sets taken from recent drug discovery projects including 33 macrocyclic ligands covering a diverse chemical space. The predicted binding free energies are in good agreement with experimental data with an overall root-mean-square error (RMSE) of 0.94 kcal/mol. This is to our knowledge the first time where the free energy of the macrocyclization of linear molecules has been directly calculated with rigorous physics-based free energy calculation methods, and we anticipate the outstanding accuracy demonstrated here across a broad range of target classes may have significant implications for macrocycle drug discovery.

Fragment-based quantum mechanical calculation of protein-protein binding affinities.

Science.gov (United States)

Wang, Yaqian; Liu, Jinfeng; Li, Jinjin; He, Xiao

2018-04-29

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

A robust computational solution for automated quantification of a specific binding ratio based on [123I]FP-CIT SPECT images

International Nuclear Information System (INIS)

Oliveira, F. P. M.; Tavares, J. M. R. S.; Borges, Faria D.; Campos, Costa D.

2014-01-01

The purpose of the current paper is to present a computational solution to accurately quantify a specific to a non-specific uptake ratio in [ 123 I]fP-CIT single photon emission computed tomography (SPECT) images and simultaneously measure the spatial dimensions of the basal ganglia, also known as basal nuclei. A statistical analysis based on a reference dataset selected by the user is also automatically performed. The quantification of the specific to non-specific uptake ratio here is based on regions of interest defined after the registration of the image under study with a template image. The computational solution was tested on a dataset of 38 [ 123 I]FP-CIT SPECT images: 28 images were from patients with Parkinson’s disease and the remainder from normal patients, and the results of the automated quantification were compared to the ones obtained by three well-known semi-automated quantification methods. The results revealed a high correlation coefficient between the developed automated method and the three semi-automated methods used for comparison (r ≥0.975). The solution also showed good robustness against different positions of the patient, as an almost perfect agreement between the specific to non-specific uptake ratio was found (ICC=1.000). The mean processing time was around 6 seconds per study using a common notebook PC. The solution developed can be useful for clinicians to evaluate [ 123 I]FP-CIT SPECT images due to its accuracy, robustness and speed. Also, the comparison between case studies and the follow-up of patients can be done more accurately and proficiently since the intra- and inter-observer variability of the semi-automated calculation does not exist in automated solutions. The dimensions of the basal ganglia and their automatic comparison with the values of the population selected as reference are also important for professionals in this area.

Are current atomistic force fields accurate enough to study proteins in crowded environments?

Directory of Open Access Journals (Sweden)

Drazen Petrov

2014-05-01

Full Text Available The high concentration of macromolecules in the crowded cellular interior influences different thermodynamic and kinetic properties of proteins, including their structural stabilities, intermolecular binding affinities and enzymatic rates. Moreover, various structural biology methods, such as NMR or different spectroscopies, typically involve samples with relatively high protein concentration. Due to large sampling requirements, however, the accuracy of classical molecular dynamics (MD simulations in capturing protein behavior at high concentration still remains largely untested. Here, we use explicit-solvent MD simulations and a total of 6.4 µs of simulated time to study wild-type (folded and oxidatively damaged (unfolded forms of villin headpiece at 6 mM and 9.2 mM protein concentration. We first perform an exhaustive set of simulations with multiple protein molecules in the simulation box using GROMOS 45a3 and 54a7 force fields together with different types of electrostatics treatment and solution ionic strengths. Surprisingly, the two villin headpiece variants exhibit similar aggregation behavior, despite the fact that their estimated aggregation propensities markedly differ. Importantly, regardless of the simulation protocol applied, wild-type villin headpiece consistently aggregates even under conditions at which it is experimentally known to be soluble. We demonstrate that aggregation is accompanied by a large decrease in the total potential energy, with not only hydrophobic, but also polar residues and backbone contributing substantially. The same effect is directly observed for two other major atomistic force fields (AMBER99SB-ILDN and CHARMM22-CMAP as well as indirectly shown for additional two (AMBER94, OPLS-AAL, and is possibly due to a general overestimation of the potential energy of protein-protein interactions at the expense of water-water and water-protein interactions. Overall, our results suggest that current MD force fields

A fully automated microfluidic femtosecond laser axotomy platform for nerve regeneration studies in C. elegans.

Science.gov (United States)

Gokce, Sertan Kutal; Guo, Samuel X; Ghorashian, Navid; Everett, W Neil; Jarrell, Travis; Kottek, Aubri; Bovik, Alan C; Ben-Yakar, Adela

2014-01-01

Femtosecond laser nanosurgery has been widely accepted as an axonal injury model, enabling nerve regeneration studies in the small model organism, Caenorhabditis elegans. To overcome the time limitations of manual worm handling techniques, automation and new immobilization technologies must be adopted to improve throughput in these studies. While new microfluidic immobilization techniques have been developed that promise to reduce the time required for axotomies, there is a need for automated procedures to minimize the required amount of human intervention and accelerate the axotomy processes crucial for high-throughput. Here, we report a fully automated microfluidic platform for performing laser axotomies of fluorescently tagged neurons in living Caenorhabditis elegans. The presented automation process reduces the time required to perform axotomies within individual worms to ∼17 s/worm, at least one order of magnitude faster than manual approaches. The full automation is achieved with a unique chip design and an operation sequence that is fully computer controlled and synchronized with efficient and accurate image processing algorithms. The microfluidic device includes a T-shaped architecture and three-dimensional microfluidic interconnects to serially transport, position, and immobilize worms. The image processing algorithms can identify and precisely position axons targeted for ablation. There were no statistically significant differences observed in reconnection probabilities between axotomies carried out with the automated system and those performed manually with anesthetics. The overall success rate of automated axotomies was 67.4±3.2% of the cases (236/350) at an average processing rate of 17.0±2.4 s. This fully automated platform establishes a promising methodology for prospective genome-wide screening of nerve regeneration in C. elegans in a truly high-throughput manner.

Protein Crystal Growth

Science.gov (United States)

2003-01-01

In order to rapidly and efficiently grow crystals, tools were needed to automatically identify and analyze the growing process of protein crystals. To meet this need, Diversified Scientific, Inc. (DSI), with the support of a Small Business Innovation Research (SBIR) contract from NASA s Marshall Space Flight Center, developed CrystalScore(trademark), the first automated image acquisition, analysis, and archiving system designed specifically for the macromolecular crystal growing community. It offers automated hardware control, image and data archiving, image processing, a searchable database, and surface plotting of experimental data. CrystalScore is currently being used by numerous pharmaceutical companies and academic and nonprofit research centers. DSI, located in Birmingham, Alabama, was awarded the patent Method for acquiring, storing, and analyzing crystal images on March 4, 2003. Another DSI product made possible by Marshall SBIR funding is VaporPro(trademark), a unique, comprehensive system that allows for the automated control of vapor diffusion for crystallization experiments.

Automated Peak Picking and Peak Integration in Macromolecular NMR Spectra Using AUTOPSY

Science.gov (United States)

Koradi, Reto; Billeter, Martin; Engeli, Max; Güntert, Peter; Wüthrich, Kurt

1998-12-01

A new approach for automated peak picking of multidimensional protein NMR spectra with strong overlap is introduced, which makes use of the program AUTOPSY (automatedpeak picking for NMRspectroscopy). The main elements of this program are a novel function for local noise level calculation, the use of symmetry considerations, and the use of lineshapes extracted from well-separated peaks for resolving groups of strongly overlapping peaks. The algorithm generates peak lists with precise chemical shift and integral intensities, and a reliability measure for the recognition of each peak. The results of automated peak picking of NOESY spectra with AUTOPSY were tested in combination with the combined automated NOESY cross peak assignment and structure calculation routine NOAH implemented in the program DYANA. The quality of the resulting structures was found to be comparable with those from corresponding data obtained with manual peak picking.

Automated model building

CERN Document Server

Caferra, Ricardo; Peltier, Nicholas

2004-01-01

This is the first book on automated model building, a discipline of automated deduction that is of growing importance Although models and their construction are important per se, automated model building has appeared as a natural enrichment of automated deduction, especially in the attempt to capture the human way of reasoning The book provides an historical overview of the field of automated deduction, and presents the foundations of different existing approaches to model construction, in particular those developed by the authors Finite and infinite model building techniques are presented The main emphasis is on calculi-based methods, and relevant practical results are provided The book is of interest to researchers and graduate students in computer science, computational logic and artificial intelligence It can also be used as a textbook in advanced undergraduate courses

Performance of optimized McRAPD in identification of 9 yeast species frequently isolated from patient samples: potential for automation.

Science.gov (United States)

Trtkova, Jitka; Pavlicek, Petr; Ruskova, Lenka; Hamal, Petr; Koukalova, Dagmar; Raclavsky, Vladislav

2009-11-10

Rapid, easy, economical and accurate species identification of yeasts isolated from clinical samples remains an important challenge for routine microbiological laboratories, because susceptibility to antifungal agents, probability to develop resistance and ability to cause disease vary in different species. To overcome the drawbacks of the currently available techniques we have recently proposed an innovative approach to yeast species identification based on RAPD genotyping and termed McRAPD (Melting curve of RAPD). Here we have evaluated its performance on a broader spectrum of clinically relevant yeast species and also examined the potential of automated and semi-automated interpretation of McRAPD data for yeast species identification. A simple fully automated algorithm based on normalized melting data identified 80% of the isolates correctly. When this algorithm was supplemented by semi-automated matching of decisive peaks in first derivative plots, 87% of the isolates were identified correctly. However, a computer-aided visual matching of derivative plots showed the best performance with average 98.3% of the accurately identified isolates, almost matching the 99.4% performance of traditional RAPD fingerprinting. Since McRAPD technique omits gel electrophoresis and can be performed in a rapid, economical and convenient way, we believe that it can find its place in routine identification of medically important yeasts in advanced diagnostic laboratories that are able to adopt this technique. It can also serve as a broad-range high-throughput technique for epidemiological surveillance.

Validating automated kidney stone volumetry in computed tomography and mathematical correlation with estimated stone volume based on diameter.

Science.gov (United States)

Wilhelm, Konrad; Miernik, Arkadiusz; Hein, Simon; Schlager, Daniel; Adams, Fabian; Benndorf, Matthias; Fritz, Benjamin; Langer, Mathias; Hesse, Albrecht; Schoenthaler, Martin; Neubauer, Jakob

2018-06-02

To validate AutoMated UroLithiasis Evaluation Tool (AMULET) software for kidney stone volumetry and compare its performance to standard clinical practice. Maximum diameter and volume of 96 urinary stones were measured as reference standard by three independent urologists. The same stones were positioned in an anthropomorphic phantom and CT scans acquired in standard settings. Three independent radiologists blinded to the reference values took manual measurements of the maximum diameter and automatic measurements of maximum diameter and volume. An "expected volume" was calculated based on manual diameter measurements using the formula: V=4/3 πr³. 96 stones were analyzed in the study. We had initially aimed to assess 100. Nine were replaced during data acquisition due of crumbling and 4 had to be excluded because the automated measurement did not work. Mean reference maximum diameter was 13.3 mm (5.2-32.1 mm). Correlation coefficients among all measured outcomes were compared. The correlation between the manual and automatic diameter measurements to the reference was 0.98 and 0.91, respectively (pvolumetry is possible and significantly more accurate than diameter-based volumetric calculations. To avoid bias in clinical trials, size should be measured as volume. However, automated diameter measurements are not as accurate as manual measurements.

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.

Comparison of three flaw-location methods for automated ultrasonic testing

International Nuclear Information System (INIS)

Seiger, H.

1982-01-01

Two well-known methods for locating flaws by measurement of the transit time of ultrasonic pulses are examined theoretically. It is shown that neither is sufficiently reliable for use in automated ultrasonic testing. A third method, which takes into account the shape of the sound field from the probe and the uncertainty in measurement of probe-flaw distance and probe position, is introduced. An experimental comparison of the three methods indicates that use of the advanced method results in more accurate location of flaws. (author)

Quantum-Chemical Electron Densities of Proteins and of Selected Protein Sites from Subsystem Density Functional Theory

NARCIS (Netherlands)

Kiewisch, K.; Jacob, C.R.; Visscher, L.

2013-01-01

The ability to calculate accurate electron densities of full proteins or of selected sites in proteins is a prerequisite for a fully quantum-mechanical calculation of protein-protein and protein-ligand interaction energies. Quantum-chemical subsystem methods capable of treating proteins and other

Automated delineation of stroke lesions using brain CT images

Directory of Open Access Journals (Sweden)

Céline R. Gillebert

2014-01-01

Full Text Available Computed tomographic (CT images are widely used for the identification of abnormal brain tissue following infarct and hemorrhage in stroke. Manual lesion delineation is currently the standard approach, but is both time-consuming and operator-dependent. To address these issues, we present a method that can automatically delineate infarct and hemorrhage in stroke CT images. The key elements of this method are the accurate normalization of CT images from stroke patients into template space and the subsequent voxelwise comparison with a group of control CT images for defining areas with hypo- or hyper-intense signals. Our validation, using simulated and actual lesions, shows that our approach is effective in reconstructing lesions resulting from both infarct and hemorrhage and yields lesion maps spatially consistent with those produced manually by expert operators. A limitation is that, relative to manual delineation, there is reduced sensitivity of the automated method in regions close to the ventricles and the brain contours. However, the automated method presents a number of benefits in terms of offering significant time savings and the elimination of the inter-operator differences inherent to manual tracing approaches. These factors are relevant for the creation of large-scale lesion databases for neuropsychological research. The automated delineation of stroke lesions from CT scans may also enable longitudinal studies to quantify changes in damaged tissue in an objective and reproducible manner.

Bayesian ISOLA: new tool for automated centroid moment tensor inversion

Science.gov (United States)

Vackář, Jiří; Burjánek, Jan; Gallovič, František; Zahradník, Jiří; Clinton, John

2017-04-01

Focal mechanisms are important for understanding seismotectonics of a region, and they serve as a basic input for seismic hazard assessment. Usually, the point source approximation and the moment tensor (MT) are used. We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances and high signal-to-noise are rejected, and full-waveform inversion in a space-time grid around a provided hypocenter. The method is innovative in the following aspects: (i) The CMT inversion is fully automated, no user interaction is required, although the details of the process can be visually inspected latter on many figures which are automatically plotted.(ii) The automated process includes detection of disturbances based on MouseTrap code, so disturbed recordings do not affect inversion.(iii) A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequencies.(iv) Bayesian approach is used, so not only the best solution is obtained, but also the posterior probability density function.(v) A space-time grid search effectively combined with the least-squares inversion of moment tensor components speeds up the inversion and allows to obtain more accurate results compared to stochastic methods. The method has been tested on synthetic and observed data. It has been tested by comparison with manually processed moment tensors of all events greater than M≥3 in the Swiss catalogue over 16 years using data available at the Swiss data center (http://arclink.ethz.ch). The quality of the results of the presented automated process is comparable with careful manual processing of data. The software package programmed in Python has been designed to be as versatile as possible in

Automation in structural biology beamlines of the Photon Factory

International Nuclear Information System (INIS)

Igarashi, Noriyuki; Hiraki, Masahiko; Matsugaki, Naohiro; Yamada, Yusuke; Wakatsuki, Soichi

2007-01-01

The Photon Factory currently operates four synchrotron beamlines for protein crystallography and two more beamlines are scheduled to be constructed in the next years. Over the last years these beamlines have been upgraded and equipped with a fully automated beamline control system based on a robotic sample changer. The current system allows for remote operation, controlled from the user's area, of sample mounting, centering and data collection of pre-frozen crystals mounted in Hampton-type cryo-loops on goniometer head. New intuitive graphical user interfaces have been developed so as to control the complete beamline operation. Furthermore, algorithms for automatic sample centering based on pattern matching and X-ray beam scanning are being developed and combined with newly developed diffraction evaluation programs in order to complete entire automation of the data collection. (author)

Automation on an Open-Access Platform of Alzheimer's Disease Biomarker Immunoassays.

Science.gov (United States)

Gille, Benjamin; Dedeene, Lieselot; Stoops, Erik; Demeyer, Leentje; Francois, Cindy; Lefever, Stefanie; De Schaepdryver, Maxim; Brix, Britta; Vandenberghe, Rik; Tournoy, Jos; Vanderstichele, Hugo; Poesen, Koen

2018-04-01

The lack of (inter-)laboratory standardization has hampered the application of universal cutoff values for Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers and their transfer to general clinical practice. The automation of the AD biomarker immunoassays is suggested to generate more robust results than using manual testing. Open-access platforms will facilitate the integration of automation for novel biomarkers, allowing the introduction of the protein profiling concept. A feasibility study was performed on an automated open-access platform of the commercial immunoassays for the 42-amino-acid isoform of amyloid-β (Aβ 1-42 ), Aβ 1-40 , and total tau in CSF. Automated Aβ 1-42 , Aβ 1-40 , and tau immunoassays were performed within predefined acceptance criteria for bias and imprecision. Similar accuracy was obtained for ready-to-use calibrators as for reconstituted lyophilized kit calibrators. When compared with the addition of a standard curve in each test run, the use of a master calibrator curve, determined before and applied to each batch analysis as the standard curve, yielded an acceptable overall bias of -2.6% and -0.9% for Aβ 1-42 and Aβ 1-40 , respectively, with an imprecision profile of 6.2% and 8.4%, respectively. Our findings show that transfer of commercial manual immunoassays to fully automated open-access platforms is feasible, as it performs according to universal acceptance criteria.

Automated detection of geomagnetic storms with heightened risk of GIC

Science.gov (United States)

Bailey, Rachel L.; Leonhardt, Roman

2016-06-01

Automated detection of geomagnetic storms is of growing importance to operators of technical infrastructure (e.g., power grids, satellites), which is susceptible to damage caused by the consequences of geomagnetic storms. In this study, we compare three methods for automated geomagnetic storm detection: a method analyzing the first derivative of the geomagnetic variations, another looking at the Akaike information criterion, and a third using multi-resolution analysis of the maximal overlap discrete wavelet transform of the variations. These detection methods are used in combination with an algorithm for the detection of coronal mass ejection shock fronts in ACE solar wind data prior to the storm arrival on Earth as an additional constraint for possible storm detection. The maximal overlap discrete wavelet transform is found to be the most accurate of the detection methods. The final storm detection software, implementing analysis of both satellite solar wind and geomagnetic ground data, detects 14 of 15 more powerful geomagnetic storms over a period of 2 years.

Automated road network extraction from high spatial resolution multi-spectral imagery

Science.gov (United States)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

78 FR 53466 - Modification of Two National Customs Automation Program (NCAP) Tests Concerning Automated...

Science.gov (United States)

2013-08-29

... Customs Automation Program (NCAP) Tests Concerning Automated Commercial Environment (ACE) Document Image... National Customs Automation Program (NCAP) tests concerning document imaging, known as the Document Image... the National Customs Automation Program (NCAP) tests concerning document imaging, known as the...

Fast and accurate approaches for large-scale, automated mapping of food diaries on food composition tables

DEFF Research Database (Denmark)

Lamarine, Marc; Hager, Jörg; Saris, Wim H M

2018-01-01

the EuroFIR resource. Two approaches were tested: the first was based solely on food name similarity (fuzzy matching). The second used a machine learning approach (C5.0 classifier) combining both fuzzy matching and food energy. We tested mapping food items using their original names and also an English...... not lead to any improvements compared to the fuzzy matching. However, it could increase substantially the recall rate for food items without any clear equivalent in the FCTs (+7 and +20% when mapping items using their original or English-translated names). Our approaches have been implemented as R packages...... and are freely available from GitHub. Conclusion: This study is the first to provide automated approaches for large-scale food item mapping onto FCTs. We demonstrate that both high precision and recall can be achieved. Our solutions can be used with any FCT and do not require any programming background...

Design of a novel automated methanol feed system for pilot-scale fermentation of Pichia pastoris.

Science.gov (United States)

Hamaker, Kent H; Johnson, Daniel C; Bellucci, Joseph J; Apgar, Kristie R; Soslow, Sherry; Gercke, John C; Menzo, Darrin J; Ton, Christopher

2011-01-01

Large-scale fermentation of Pichia pastoris requires a large volume of methanol feed during the induction phase. However, a large volume of methanol feed is difficult to use in the processing suite because of the inconvenience of constant monitoring, manual manipulation steps, and fire and explosion hazards. To optimize and improve safety of the methanol feed process, a novel automated methanol feed system has been designed and implemented for industrial fermentation of P. pastoris. Details of the design of the methanol feed system are described. The main goals of the design were to automate the methanol feed process and to minimize the hazardous risks associated with storing and handling large quantities of methanol in the processing area. The methanol feed system is composed of two main components: a bulk feed (BF) system and up to three portable process feed (PF) systems. The BF system automatically delivers methanol from a central location to the portable PF system. The PF system provides precise flow control of linear, step, or exponential feed of methanol to the fermenter. Pilot-scale fermentations with linear and exponential methanol feeds were conducted using two Mut(+) (methanol utilization plus) strains, one expressing a recombinant therapeutic protein and the other a monoclonal antibody. Results show that the methanol feed system is accurate, safe, and efficient. The feed rates for both linear and exponential feed methods were within ± 5% of the set points, and the total amount of methanol fed was within 1% of the targeted volume. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

Automated Detection of HONcode Website Conformity Compared to Manual Detection: An Evaluation.

Science.gov (United States)

Boyer, Célia; Dolamic, Ljiljana

2015-06-02

To earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website's HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the current time-consuming tasks of HONcode certification and ongoing surveillance. Additionally, an automated tool used as a plugin to a general search engine might help to detect health websites that respect HONcode principles but have not yet been certified. The goal of this study was to determine whether the automated system is capable of performing as good as human experts for the task of identifying HONcode principles on health websites. Using manual evaluation by HONcode senior experts as a baseline, this study compared the capability of the automated HONcode detection system to that of the HONcode senior experts. A set of 27 health-related websites were manually assessed for compliance to each of the 8 HONcode principles by senior HONcode experts. The same set of websites were processed by the automated system for HONcode compliance detection based on supervised machine learning. The results obtained by these two methods were then compared. For the privacy criterion, the automated system obtained the same results as the human expert for 17 of 27 sites (14 true positives and 3 true negatives) without noise (0 false positives). The remaining 10 false negative instances for the privacy criterion represented tolerable behavior because it is important that all automatically detected principle conformities are accurate (ie, specificity [100%] is preferred over sensitivity [58%] for the privacy criterion). In addition, the automated system had precision of at least 75%, with a recall of more

Optimization of automation: III. Development of optimization method for determining automation rate in nuclear power plants

International Nuclear Information System (INIS)

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

2016-01-01

Highlights: • We propose an appropriate automation rate that enables the best human performance. • We analyze the shortest working time considering Situation Awareness Recovery (SAR). • The optimized automation rate is estimated by integrating the automation and ostracism rate estimation methods. • The process to derive the optimized automation rate is demonstrated through case studies. - Abstract: Automation has been introduced in various industries, including the nuclear field, because it is commonly believed that automation promises greater efficiency, lower workloads, and fewer operator errors through reducing operator errors and enhancing operator and system performance. However, the excessive introduction of automation has deteriorated operator performance due to the side effects of automation, which are referred to as Out-of-the-Loop (OOTL), and this is critical issue that must be resolved. Thus, in order to determine the optimal level of automation introduction that assures the best human operator performance, a quantitative method of optimizing the automation is proposed in this paper. In order to propose the optimization method for determining appropriate automation levels that enable the best human performance, the automation rate and ostracism rate, which are estimation methods that quantitatively analyze the positive and negative effects of automation, respectively, are integrated. The integration was conducted in order to derive the shortest working time through considering the concept of situation awareness recovery (SAR), which states that the automation rate with the shortest working time assures the best human performance. The process to derive the optimized automation rate is demonstrated through an emergency operation scenario-based case study. In this case study, four types of procedures are assumed through redesigning the original emergency operating procedure according to the introduced automation and ostracism levels. Using the

Development of Fully Automated Low-Cost Immunoassay System for Research Applications.

Science.gov (United States)

Wang, Guochun; Das, Champak; Ledden, Bradley; Sun, Qian; Nguyen, Chien

2017-10-01

Enzyme-linked immunosorbent assay (ELISA) automation for routine operation in a small research environment would be very attractive. A portable fully automated low-cost immunoassay system was designed, developed, and evaluated with several protein analytes. It features disposable capillary columns as the reaction sites and uses real-time calibration for improved accuracy. It reduces the overall assay time to less than 75 min with the ability of easy adaptation of new testing targets. The running cost is extremely low due to the nature of automation, as well as reduced material requirements. Details about system configuration, components selection, disposable fabrication, system assembly, and operation are reported. The performance of the system was initially established with a rabbit immunoglobulin G (IgG) assay, and an example of assay adaptation with an interleukin 6 (IL6) assay is shown. This system is ideal for research use, but could work for broader testing applications with further optimization.

Automated bone segmentation from large field of view 3D MR images of the hip joint

International Nuclear Information System (INIS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-01-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head–neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone–cartilage interfaces for potential cartilage segmentation. (paper)

Automated bone segmentation from large field of view 3D MR images of the hip joint

Science.gov (United States)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

A novel strategy for NMR resonance assignment and protein structure determination

International Nuclear Information System (INIS)

Lemak, Alexander; Gutmanas, Aleksandras; Chitayat, Seth; Karra, Murthy; Farès, Christophe; Sunnerhagen, Maria; Arrowsmith, Cheryl H.

2011-01-01

The quality of protein structures determined by nuclear magnetic resonance (NMR) spectroscopy is contingent on the number and quality of experimentally-derived resonance assignments, distance and angular restraints. Two key features of protein NMR data have posed challenges for the routine and automated structure determination of small to medium sized proteins; (1) spectral resolution – especially of crowded nuclear Overhauser effect spectroscopy (NOESY) spectra, and (2) the reliance on a continuous network of weak scalar couplings as part of most common assignment protocols. In order to facilitate NMR structure determination, we developed a semi-automated strategy that utilizes non-uniform sampling (NUS) and multidimensional decomposition (MDD) for optimal data collection and processing of selected, high resolution multidimensional NMR experiments, combined it with an ABACUS protocol for sequential and side chain resonance assignments, and streamlined this procedure to execute structure and refinement calculations in CYANA and CNS, respectively. Two graphical user interfaces (GUIs) were developed to facilitate efficient analysis and compilation of the data and to guide automated structure determination. This integrated method was implemented and refined on over 30 high quality structures of proteins ranging from 5.5 to 16.5 kDa in size.

Template-based protein-protein docking exploiting pairwise interfacial residue restraints

NARCIS (Netherlands)

Xue, Li C; Garcia Lopes Maia Rodrigues, João; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2016-01-01

Although many advanced and sophisticatedab initioapproaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to

World-wide distribution automation systems

International Nuclear Information System (INIS)

Devaney, T.M.

1994-01-01

A worldwide power distribution automation system is outlined. Distribution automation is defined and the status of utility automation is discussed. Other topics discussed include a distribution management system, substation feeder, and customer functions, potential benefits, automation costs, planning and engineering considerations, automation trends, databases, system operation, computer modeling of system, and distribution management systems

A new automated colorimetric method for measuring total oxidant status.

Science.gov (United States)

Erel, Ozcan

2005-12-01

To develop a new, colorimetric and automated method for measuring total oxidation status (TOS). The assay is based on the oxidation of ferrous ion to ferric ion in the presence of various oxidant species in acidic medium and the measurement of the ferric ion by xylenol orange. The oxidation reaction of the assay was enhanced and precipitation of proteins was prevented. In addition, autoxidation of ferrous ion present in the reagent was prevented during storage. The method was applied to an automated analyzer, which was calibrated with hydrogen peroxide and the analytical performance characteristics of the assay were determined. There were important correlations with hydrogen peroxide, tert-butyl hydroperoxide and cumene hydroperoxide solutions (r=0.99, Ptotal antioxidant capacity (TAC) (r=-0.66 Ptotal oxidant status.

WIDAFELS flexible automation systems

International Nuclear Information System (INIS)

Shende, P.S.; Chander, K.P.; Ramadas, P.

1990-01-01

After discussing the various aspects of automation, some typical examples of various levels of automation are given. One of the examples is of automated production line for ceramic fuel pellets. (M.G.B.)

Semi-continuous protein fractionating using affinity cross-flow filtration

NARCIS (Netherlands)

Borneman, Zandrie; Zhang, W.; van den Boomgaard, Anthonie; Smolders, C.A.

2002-01-01

Protein purification by means of downstream processing is increasingly important. At the University of Twente a semi-continuous process is developed for the isolation of BSA out of crude protein mixtures. For this purpose an automated Affinity Cross-Flow Filtration, ACFF, process is developed. This

A large-scale evaluation of computational protein function prediction

NARCIS (Netherlands)

Radivojac, P.; Clark, W.T.; Oron, T.R.; Schnoes, A.M.; Wittkop, T.; Kourmpetis, Y.A.I.; Dijk, van A.D.J.; Friedberg, I.

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be

Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI

International Nuclear Information System (INIS)

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Filgueiras-Rama, David; Pizarro, Gonzalo; Ibañez, Borja; Berenfeld, Omer; Boyers, Pamela; Gold, Jeffrey

2012-01-01

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning. (paper)

Parameters Investigation of Mathematical Model of Productivity for Automated Line with Availability by DMAIC Methodology

Directory of Open Access Journals (Sweden)

Tan Chan Sin

2014-01-01

Full Text Available Automated line is widely applied in industry especially for mass production with less variety product. Productivity is one of the important criteria in automated line as well as industry which directly present the outputs and profits. Forecast of productivity in industry accurately in order to achieve the customer demand and the forecast result is calculated by using mathematical model. Mathematical model of productivity with availability for automated line has been introduced to express the productivity in terms of single level of reliability for stations and mechanisms. Since this mathematical model of productivity with availability cannot achieve close enough productivity compared to actual one due to lack of parameters consideration, the enhancement of mathematical model is required to consider and add the loss parameters that is not considered in current model. This paper presents the investigation parameters of productivity losses investigated by using DMAIC (Define, Measure, Analyze, Improve, and Control concept and PACE Prioritization Matrix (Priority, Action, Consider, and Eliminate. The investigated parameters are important for further improvement of mathematical model of productivity with availability to develop robust mathematical model of productivity in automated line.

Automation in Clinical Microbiology

Science.gov (United States)

Ledeboer, Nathan A.

2013-01-01

Historically, the trend toward automation in clinical pathology laboratories has largely bypassed the clinical microbiology laboratory. In this article, we review the historical impediments to automation in the microbiology laboratory and offer insight into the reasons why we believe that we are on the cusp of a dramatic change that will sweep a wave of automation into clinical microbiology laboratories. We review the currently available specimen-processing instruments as well as the total laboratory automation solutions. Lastly, we outline the types of studies that will need to be performed to fully assess the benefits of automation in microbiology laboratories. PMID:23515547

Virtual automation.

Science.gov (United States)

Casis, E; Garrido, A; Uranga, B; Vives, A; Zufiaurre, C

2001-01-01

Total laboratory automation (TLA) can be substituted in mid-size laboratories by a computer sample workflow control (virtual automation). Such a solution has been implemented in our laboratory using PSM, software developed in cooperation with Roche Diagnostics (Barcelona, Spain), to this purpose. This software is connected to the online analyzers and to the laboratory information system and is able to control and direct the samples working as an intermediate station. The only difference with TLA is the replacement of transport belts by personnel of the laboratory. The implementation of this virtual automation system has allowed us the achievement of the main advantages of TLA: workload increase (64%) with reduction in the cost per test (43%), significant reduction in the number of biochemistry primary tubes (from 8 to 2), less aliquoting (from 600 to 100 samples/day), automation of functional testing, drastic reduction of preanalytical errors (from 11.7 to 0.4% of the tubes) and better total response time for both inpatients (from up to 48 hours to up to 4 hours) and outpatients (from up to 10 days to up to 48 hours). As an additional advantage, virtual automation could be implemented without hardware investment and significant headcount reduction (15% in our lab).

A Container Horizontal Positioning Method with Image Sensors for Cranes in Automated Container Terminals

Directory of Open Access Journals (Sweden)

FU Yonghua

2014-03-01

Full Text Available Automation is a trend for large container terminals nowadays, and container positioning techniques are key factor in the automating process. Vision based positioning techniques are inexpensive and rather accurate in nature, while the effect with insufficient illumination is left in question. This paper proposed a vision-based procedure with image sensors to determine the position of one container in the horizontal plane. The points found by the edge detection operator are clustered, and only the peak points in the parameter space of the Hough transformation is selected, in order that the effect of noises could be much decreased. The effectiveness of our procedure is verified in experiments, in which the efficiency of the procedure is also investigated.

Automation of Test Cases for Web Applications : Automation of CRM Test Cases

OpenAIRE

Seyoum, Alazar

2012-01-01

The main theme of this project was to design a test automation framework for automating web related test cases. Automating test cases designed for testing a web interface provide a means of improving a software development process by shortening the testing phase in the software development life cycle. In this project an existing AutoTester framework and iMacros test automation tools were used. CRM Test Agent was developed to integrate AutoTester to iMacros and to enable the AutoTester,...

Automated Processing of Plasma Samples for Lipoprotein Separation by Rate-Zonal Ultracentrifugation.

Science.gov (United States)

Peters, Carl N; Evans, Iain E J

2016-12-01

Plasma lipoproteins are the primary means of lipid transport among tissues. Defining alterations in lipid metabolism is critical to our understanding of disease processes. However, lipoprotein measurement is limited to specialized centers. Preparation for ultracentrifugation involves the formation of complex density gradients that is both laborious and subject to handling errors. We created a fully automated device capable of forming the required gradient. The design has been made freely available for download by the authors. It is inexpensive relative to commercial density gradient formers, which generally create linear gradients unsuitable for rate-zonal ultracentrifugation. The design can easily be modified to suit user requirements and any potential future improvements. Evaluation of the device showed reliable peristaltic pump accuracy and precision for fluid delivery. We also demonstrate accurate fluid layering with reduced mixing at the gradient layers when compared to usual practice by experienced laboratory personnel. Reduction in layer mixing is of critical importance, as it is crucial for reliable lipoprotein separation. The automated device significantly reduces laboratory staff input and reduces the likelihood of error. Overall, this device creates a simple and effective solution to formation of complex density gradients. © 2015 Society for Laboratory Automation and Screening.

Design and Achievement of User Interface Automation Testing of Linux Based on Element Tree of DogTail

Directory of Open Access Journals (Sweden)

Yuan Wen-Chao

2017-01-01

Full Text Available As Linux gets more popular around the world, the advantage of the open source on software makes people do automated UI test by unified testing framework. UI software testing can guarantee the rationality of User Interface of Linux and accuracy of the UI’s widgets. In order to set free from fuzzy and repeated manual testing, and improve efficiency, this paper achieves automation testing of UI under Linux, and proposes a method to identify and test UI widgets under Linux, which is according to element tree of DogTail automaton testing framework. It achieves automation test of UI under Linux. According to this method, Aiming at the product of Red Hat Subscription Manager under Red Hat Enterprise Linux, it designs the automation test plan of this series of product’s dialogs. After many tests, it is indicated that this plan can identify UI widgets accurately and rationally, describe the structure of software clearly, avoid software errors and improve efficiency of the software. Simultaneously, it also can be used in the internationalization testing for checking translation during software internationalization.

Automated Office Blood Pressure Measurement.

Science.gov (United States)

Myers, Martin G

2018-04-01

Manual blood pressure (BP) recorded in routine clinical practice is relatively inaccurate and associated with higher readings compared to BP measured in research studies in accordance with standardized measurement guidelines. The increase in routine office BP is the result of several factors, especially the presence of office staff, which tends to make patients nervous and also allows for conversation to occur. With the disappearance of the mercury sphygmomanometer because of environmental concerns, there is greater use of oscillometric BP recorders, both in the office setting and elsewhere. Although oscillometric devices may reduce some aspects of observer BP measurement error in the clinical setting, they are still associated with higher BP readings, known as white coat hypertension (for diagnosis) or white coat effect (with treated hypertension). Now that fully automated sphygmomanometers are available which are capable of recording several readings with the patient resting quietly, there is no longer any need to have office staff present when BP is being recorded. Such readings are called automated office blood pressure (AOBP) and they are both more accurate than conventional manual office BP and not associated with the white coat phenomena. AOBP readings are also similar to the awake ambulatory BP and home BP, both of which are relatively good predictors of cardiovascular risk. The available evidence suggests that AOBP should now replace manual or electronic office BP readings when screening patients for hypertension and also after antihypertensive drug therapy is initiated. Copyright © 2018. The Korean Society of Cardiology.

An Automation Planning Primer.

Science.gov (United States)

Paynter, Marion

1988-01-01

This brief planning guide for library automation incorporates needs assessment and evaluation of options to meet those needs. A bibliography of materials on automation planning and software reviews, library software directories, and library automation journals is included. (CLB)

The Automated Assessment of Postural Stability: Balance Detection Algorithm.

Science.gov (United States)

Napoli, Alessandro; Glass, Stephen M; Tucker, Carole; Obeid, Iyad

2017-12-01

Impaired balance is a common indicator of mild traumatic brain injury, concussion and musculoskeletal injury. Given the clinical relevance of such injuries, especially in military settings, it is paramount to develop more accurate and reliable on-field evaluation tools. This work presents the design and implementation of the automated assessment of postural stability (AAPS) system, for on-field evaluations following concussion. The AAPS is a computer system, based on inexpensive off-the-shelf components and custom software, that aims to automatically and reliably evaluate balance deficits, by replicating a known on-field clinical test, namely, the Balance Error Scoring System (BESS). The AAPS main innovation is its balance error detection algorithm that has been designed to acquire data from a Microsoft Kinect ® sensor and convert them into clinically-relevant BESS scores, using the same detection criteria defined by the original BESS test. In order to assess the AAPS balance evaluation capability, a total of 15 healthy subjects (7 male, 8 female) were required to perform the BESS test, while simultaneously being tracked by a Kinect 2.0 sensor and a professional-grade motion capture system (Qualisys AB, Gothenburg, Sweden). High definition videos with BESS trials were scored off-line by three experienced observers for reference scores. AAPS performance was assessed by comparing the AAPS automated scores to those derived by three experienced observers. Our results show that the AAPS error detection algorithm presented here can accurately and precisely detect balance deficits with performance levels that are comparable to those of experienced medical personnel. Specifically, agreement levels between the AAPS algorithm and the human average BESS scores ranging between 87.9% (single-leg on foam) and 99.8% (double-leg on firm ground) were detected. Moreover, statistically significant differences in balance scores were not detected by an ANOVA test with alpha equal to 0

RAPID AUTOMATED RADIOCHEMICAL ANALYZER FOR DETERMINATION OF TARGETED RADIONUCLIDES IN NUCLEAR PROCESS STREAMS

International Nuclear Information System (INIS)

O'Hara, Matthew J.; Durst, Philip C.; Grate, Jay W.; Egorov, Oleg; Devol, Timothy A.

2008-01-01

Some industrial process-scale plants require the monitoring of specific radionuclides as an indication of the composition of their feed streams or as indicators of plant performance. In this process environment, radiochemical measurements must be fast, accurate, and reliable. Manual sampling, sample preparation, and analysis of process fluids are highly precise and accurate, but tend to be expensive and slow. Scientists at Pacific Northwest National Laboratory (PNNL) have assembled and characterized a fully automated prototype Process Monitor instrument which was originally designed to rapidly measure Tc-99 in the effluent streams of the Waste Treatment Plant at Hanford, WA. The system is capable of a variety of tasks: extraction of a precise volume of sample, sample digestion/analyte redox adjustment, column-based chemical separations, flow-through radiochemical detection and data analysis/reporting. The system is compact, its components are fluidically inter-linked, and analytical results can be immediately calculated and electronically reported. It is capable of performing a complete analytical cycle in less than 15 minutes. The system is highly modular and can be adapted to a variety of sample types and analytical requirements. It exemplifies how automation could be integrated into reprocessing facilities to support international nuclear safeguards needs

Automation in Immunohematology

Directory of Open Access Journals (Sweden)

Meenu Bajpai

2012-01-01

Full Text Available There have been rapid technological advances in blood banking in South Asian region over the past decade with an increasing emphasis on quality and safety of blood products. The conventional test tube technique has given way to newer techniques such as column agglutination technique, solid phase red cell adherence assay, and erythrocyte-magnetized technique. These new technologies are adaptable to automation and major manufacturers in this field have come up with semi and fully automated equipments for immunohematology tests in the blood bank. Automation improves the objectivity and reproducibility of tests. It reduces human errors in patient identification and transcription errors. Documentation and traceability of tests, reagents and processes and archiving of results is another major advantage of automation. Shifting from manual methods to automation is a major undertaking for any transfusion service to provide quality patient care with lesser turnaround time for their ever increasing workload. This article discusses the various issues involved in the process.

Fully automated laser ray tracing system to measure changes in the crystalline lens GRIN profile.

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Qiu, Chen; Maceo Heilman, Bianca; Kaipio, Jari; Donaldson, Paul; Vaghefi, Ehsan

2017-11-01

Measuring the lens gradient refractive index (GRIN) accurately and reliably has proven an extremely challenging technical problem. A fully automated laser ray tracing (LRT) system was built to address this issue. The LRT system captures images of multiple laser projections before and after traversing through an ex vivo lens. These LRT images, combined with accurate measurements of the lens geometry, are used to calculate the lens GRIN profile. Mathematically, this is an ill-conditioned problem; hence, it is essential to apply biologically relevant constraints to produce a feasible solution. The lens GRIN measurements were compared with previously published data. Our GRIN retrieval algorithm produces fast and accurate measurements of the lens GRIN profile. Experiments to study the optics of physiologically perturbed lenses are the future direction of this research.

Semi-automated digital image analysis of patellofemoral joint space width from lateral knee radiographs

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Grochowski, S.J. [Mayo Clinic, Department of Orthopedic Surgery, Rochester (United States); Amrami, K.K. [Mayo Clinic, Department of Radiology, Rochester (United States); Kaufman, K. [Mayo Clinic, Department of Orthopedic Surgery, Rochester (United States); Mayo Clinic/Foundation, Biomechanics Laboratory, Department of Orthopedic Surgery, Charlton North L-110L, Rochester (United States)

2005-10-01

To design a semi-automated program to measure minimum patellofemoral joint space width (JSW) using standing lateral view radiographs. Lateral patellofemoral knee radiographs were obtained from 35 asymptomatic subjects. The radiographs were analyzed to report both the repeatability of the image analysis program and the reproducibility of JSW measurements within a 2 week period. The results were also compared with manual measurements done by an experienced musculoskeletal radiologist. The image analysis program was shown to have an excellent coefficient of repeatability of 0.18 and 0.23 mm for intra- and inter-observer measurements respectively. The manual method measured a greater minimum JSW than the automated method. Reproducibility between days was comparable to other published results, but was less satisfactory for both manual and semi-automated measurements. The image analysis program had an inter-day coefficient of repeatability of 1.24 mm, which was lower than 1.66 mm for the manual method. A repeatable semi-automated method for measurement of the patellofemoral JSW from radiographs has been developed. The method is more accurate than manual measurements. However, the between-day reproducibility is higher than the intra-day reproducibility. Further investigation of the protocol for obtaining sequential lateral knee radiographs is needed in order to reduce the between-day variability. (orig.)

Automated segmentation of ventricles from serial brain MRI for the quantification of volumetric changes associated with communicating hydrocephalus in patients with brain tumor

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Pura, John A.; Hamilton, Allison M.; Vargish, Geoffrey A.; Butman, John A.; Linguraru, Marius George

2011-03-01

Accurate ventricle volume estimates could improve the understanding and diagnosis of postoperative communicating hydrocephalus. For this category of patients, associated changes in ventricle volume can be difficult to identify, particularly over short time intervals. We present an automated segmentation algorithm that evaluates ventricle size from serial brain MRI examination. The technique combines serial T1- weighted images to increase SNR and segments the means image to generate a ventricle template. After pre-processing, the segmentation is initiated by a fuzzy c-means clustering algorithm to find the seeds used in a combination of fast marching methods and geodesic active contours. Finally, the ventricle template is propagated onto the serial data via non-linear registration. Serial volume estimates were obtained in an automated robust and accurate manner from difficult data.

Towards automated diffraction tomography: Part I-Data acquisition

International Nuclear Information System (INIS)

Kolb, U.; Gorelik, T.; Kuebel, C.; Otten, M.T.; Hubert, D.

2007-01-01

The ultimate aim of electron diffraction data collection for structure analysis is to sample the reciprocal space as accurately as possible to obtain a high-quality data set for crystal structure determination. Besides a more precise lattice parameter determination, fine sampling is expected to deliver superior data on reflection intensities, which is crucial for subsequent structure analysis. Traditionally, three-dimensional (3D) diffraction data are collected by manually tilting a crystal around a selected crystallographic axis and recording a set of diffraction patterns (a tilt series) at various crystallographic zones. In a second step, diffraction data from these zones are combined into a 3D data set and analyzed to yield the desired structure information. Data collection can also be performed automatically, with the recent advances in tomography acquisition providing a suitable basis. An experimental software module has been developed for the Tecnai microscope for such an automated diffraction pattern collection while tilting around the goniometer axis. The module combines STEM imaging with diffraction pattern acquisition in nanodiffraction mode. It allows automated recording of diffraction tilt series from nanoparticles with a size down to 5 nm

Automated Budget System -

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Department of Transportation — The Automated Budget System (ABS) automates management and planning of the Mike Monroney Aeronautical Center (MMAC) budget by providing enhanced capability to plan,...

Bioprocessing automation in cell therapy manufacturing: Outcomes of special interest group automation workshop.

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Ball, Oliver; Robinson, Sarah; Bure, Kim; Brindley, David A; Mccall, David

2018-04-01

Phacilitate held a Special Interest Group workshop event in Edinburgh, UK, in May 2017. The event brought together leading stakeholders in the cell therapy bioprocessing field to identify present and future challenges and propose potential solutions to automation in cell therapy bioprocessing. Here, we review and summarize discussions from the event. Deep biological understanding of a product, its mechanism of action and indication pathogenesis underpin many factors relating to bioprocessing and automation. To fully exploit the opportunities of bioprocess automation, therapeutics developers must closely consider whether an automation strategy is applicable, how to design an 'automatable' bioprocess and how to implement process modifications with minimal disruption. Major decisions around bioprocess automation strategy should involve all relevant stakeholders; communication between technical and business strategy decision-makers is of particular importance. Developers should leverage automation to implement in-process testing, in turn applicable to process optimization, quality assurance (QA)/ quality control (QC), batch failure control, adaptive manufacturing and regulatory demands, but a lack of precedent and technical opportunities can complicate such efforts. Sparse standardization across product characterization, hardware components and software platforms is perceived to complicate efforts to implement automation. The use of advanced algorithmic approaches such as machine learning may have application to bioprocess and supply chain optimization. Automation can substantially de-risk the wider supply chain, including tracking and traceability, cryopreservation and thawing and logistics. The regulatory implications of automation are currently unclear because few hardware options exist and novel solutions require case-by-case validation, but automation can present attractive regulatory incentives. Copyright © 2018 International Society for Cellular Therapy

Fully automated radiosynthesis of [11C]PBR28, a radiopharmaceutical for the translocator protein (TSPO) 18 kDa, using a GE TRACERlab FXC-Pro

International Nuclear Information System (INIS)

Hoareau, Raphaël; Shao, Xia; Henderson, Bradford D.; Scott, Peter J.H.

2012-01-01

In order to image the translocator protein (TSPO) 18 kDa in the clinic using positron emission tomography (PET) imaging, we had a cause to prepare [ 11 C]PBR28. In this communication we highlight our novel, recently developed, one-pot synthesis of the desmethyl-PBR28 precursor, as well as present an optimized fully automated preparation of [ 11 C]PBR28 using a GE TRACERlab FX C-Pro . Following radiolabelling, purification is achieved by HPLC and, to the best of our knowledge, the first reported example of reconstituting [ 11 C]PBR28 into ethanolic saline using solid-phase extraction (SPE). This procedure is operationally simple, and provides high quality doses of [ 11 C]PBR28 suitable for use in clinical PET imaging studies. Typical radiochemical yield using the optimized method is 3.6% yield (EOS, n=3), radiochemical and chemical purity are consistently >99%, and specific activities are 14,523 Ci/mmol. Highlights: ► This paper reports a fully automated synthesis of [ 11 C]PBR28 using a TRACERlab FXc-pro. ► We report a solid-phase extraction technique for the reconstitution of [ 11 C]PBR28. ► ICP-MS data for PBR28 precursor is reported confirming suitability for clinical use.

Solution structure and dynamics of melanoma inhibitory activity protein

International Nuclear Information System (INIS)

Lougheed, Julie C.; Domaille, Peter J.; Handel, Tracy M.

2002-01-01

Melanoma inhibitory activity (MIA) is a small secreted protein that is implicated in cartilage cell maintenance and melanoma metastasis. It is representative of a recently discovered family of proteins that contain a Src Homologous 3 (SH3) subdomain. While SH3 domains are normally found in intracellular proteins and mediate protein-protein interactions via recognition of polyproline helices, MIA is single-domain extracellular protein, and it probably binds to a different class of ligands.Here we report the assignments, solution structure, and dynamics of human MIA determined by heteronuclear NMR methods. The structures were calculated in a semi-automated manner without manual assignment of NOE crosspeaks, and have a backbone rmsd of 0.38 A over the ordered regions of the protein. The structure consists of an SH3-like subdomain with N- and C-terminal extensions of approximately 20 amino acids each that together form a novel fold. The rmsd between the solution structure and our recently reported crystal structure is 0.86 A over the ordered regions of the backbone, and the main differences are localized to the most dynamic regions of the protein. The similarity between the NMR and crystal structures supports the use of automated NOE assignments and ambiguous restraints to accelerate the calculation of NMR structures

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

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Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E; Blais, Jaime D; Czerwiec, Frank S; Harris, Peter C; King, Bernard F; Torres, Vicente E; Erickson, Bradley J

2017-08-01

Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

Increased Automation in Stereo Camera Calibration Techniques

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Brandi House

2006-08-01

Full Text Available Robotic vision has become a very popular field in recent years due to the numerous promising applications it may enhance. However, errors within the cameras and in their perception of their environment can cause applications in robotics to fail. To help correct these internal and external imperfections, stereo camera calibrations are performed. There are currently many accurate methods of camera calibration available; however, most or all of them are time consuming and labor intensive. This research seeks to automate the most labor intensive aspects of a popular calibration technique developed by Jean-Yves Bouguet. His process requires manual selection of the extreme corners of a checkerboard pattern. The modified process uses embedded LEDs in the checkerboard pattern to act as active fiducials. Images are captured of the checkerboard with the LEDs on and off in rapid succession. The difference of the two images automatically highlights the location of the four extreme corners, and these corner locations take the place of the manual selections. With this modification to the calibration routine, upwards of eighty mouse clicks are eliminated per stereo calibration. Preliminary test results indicate that accuracy is not substantially affected by the modified procedure. Improved automation to camera calibration procedures may finally penetrate the barriers to the use of calibration in practice.

Robotic automation of medication-use management.

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Enright, S M

1993-11-01

In the October 1993 issue of Physician Assistant, we published "Robots for Health Care," the first of two articles on the medical applications of robotics. That article discussed ways in which robots could help patients with manipulative disabilities to perform activities of daily living and hold paid employment; transfer patients from bed to chair and back again; add precision to the most exacting surgical procedures; and someday carry out diagnostic and therapeutic techniques from within the human body. This month, we are pleased to offer an article by Sharon Enright, an authority on pharmacy operations, who considers how an automated medication-management system that makes use of bar-code technology is capable of streamlining drug dispensing, controlling safety, increasing cost-effectiveness, and ensuring accurate and complete record-keeping.

Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement

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Hakan Kartal

2018-06-01

Full Text Available Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

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Hong, Weizhe; Kennedy, Ann; Burgos-Artizzu, Xavier P; Zelikowsky, Moriel; Navonne, Santiago G; Perona, Pietro; Anderson, David J

2015-09-22

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body "pose" of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.

Impact of protein and ligand impurities on ITC-derived protein-ligand thermodynamics.

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Grüner, Stefan; Neeb, Manuel; Barandun, Luzi Jakob; Sielaff, Frank; Hohn, Christoph; Kojima, Shun; Steinmetzer, Torsten; Diederich, François; Klebe, Gerhard

2014-09-01

The thermodynamic characterization of protein-ligand interactions by isothermal titration calorimetry (ITC) is a powerful tool in drug design, giving valuable insight into the interaction driving forces. ITC is thought to require protein and ligand solutions of high quality, meaning both the absence of contaminants as well as accurately determined concentrations. Ligands synthesized to deviating purity and protein of different pureness were titrated by ITC. Data curation was attempted also considering information from analytical techniques to correct stoichiometry. We used trypsin and tRNA-guanine transglycosylase (TGT), together with high affinity ligands to investigate the effect of errors in protein concentration as well as the impact of ligand impurities on the apparent thermodynamics. We found that errors in protein concentration did not change the thermodynamic properties obtained significantly. However, most ligand impurities led to pronounced changes in binding enthalpy. If protein binding of the respective impurity is not expected, the actual ligand concentration was corrected for and the thus revised data compared to thermodynamic properties obtained with the respective pure ligand. Even in these cases, we observed differences in binding enthalpy of about 4kJ⋅mol(-1), which is considered significant. Our results indicate that ligand purity is the critical parameter to monitor if accurate thermodynamic data of a protein-ligand complex are to be recorded. Furthermore, artificially changing fitting parameters to obtain a sound interaction stoichiometry in the presence of uncharacterized ligand impurities may lead to thermodynamic parameters significantly deviating from the accurate thermodynamic signature. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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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.

Chest wall segmentation in automated 3D breast ultrasound scans.

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Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

2013-12-01

In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. Copyright © 2012 Elsevier B.V. All rights reserved.

Improvements in the automated radioimmunoassay for cAMP or cGMP

International Nuclear Information System (INIS)

Brooker, G.

1988-01-01

The work others in developing antibodies and the original radioimmunoassay for cyclic nucleotides provides the basis for these sensitive assays. The acetylation radioimmunoassay for cyclic nucleotides has enabled the measurement of cyclic AMP and cyclic GMP in very small biological samples. This is because accurate determinations can be made in samples containing less than 1 fmol of cyclic AMP or cyclic GMP. The Gamma-Flo automated radioimmunoassay system has been adapted to these assays such that cyclic nucleotides can be automatically measured at a rate of about 60 samples/hr. The Gamma-Flo instrument provides high-precision assays and eliminates human intervention in all steps of the radioimmunoassay. The automated assay has been in continuous operation in our laboratory over the last 10 years and this chapter summarizes the methodology and delineates improvements which have occurred over that time frame. Details for the preparation of the radioligands apply also to the manual acetylated radioimmunoassay for cyclic nucleotides

Towards protein-crystal centering using second-harmonic generation (SHG) microscopy

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Kissick, David J.; Dettmar, Christopher M. [Purdue University, West Lafayette, IN 47907 (United States); Becker, Michael [Argonne National Laboratory, Argonne, IL 60439 (United States); Mulichak, Anne M. [Hauptman–Woodward Medical Research Institute, Argonne, IL 60439 (United States); Cherezov, Vadim [The Scripps Research Institute, La Jolla, CA 92037 (United States); Ginell, Stephan L. [Argonne National Laboratory, Argonne, IL 60439 (United States); Battaile, Kevin P.; Keefe, Lisa J. [Hauptman–Woodward Medical Research Institute, Argonne, IL 60439 (United States); Fischetti, Robert F. [Argonne National Laboratory, Argonne, IL 60439 (United States); Simpson, Garth J., E-mail: gsimpson@purdue.edu [Purdue University, West Lafayette, IN 47907 (United States)

2013-05-01

The potential of second-harmonic generation (SHG) microscopy for automated crystal centering to guide synchrotron X-ray diffraction of protein crystals has been explored. The potential of second-harmonic generation (SHG) microscopy for automated crystal centering to guide synchrotron X-ray diffraction of protein crystals was explored. These studies included (i) comparison of microcrystal positions in cryoloops as determined by SHG imaging and by X-ray diffraction rastering and (ii) X-ray structure determinations of selected proteins to investigate the potential for laser-induced damage from SHG imaging. In studies using β{sub 2} adrenergic receptor membrane-protein crystals prepared in lipidic mesophase, the crystal locations identified by SHG images obtained in transmission mode were found to correlate well with the crystal locations identified by raster scanning using an X-ray minibeam. SHG imaging was found to provide about 2 µm spatial resolution and shorter image-acquisition times. The general insensitivity of SHG images to optical scatter enabled the reliable identification of microcrystals within opaque cryocooled lipidic mesophases that were not identified by conventional bright-field imaging. The potential impact of extended exposure of protein crystals to five times a typical imaging dose from an ultrafast laser source was also assessed. Measurements of myoglobin and thaumatin crystals resulted in no statistically significant differences between structures obtained from diffraction data acquired from exposed and unexposed regions of single crystals. Practical constraints for integrating SHG imaging into an active beamline for routine automated crystal centering are discussed.

Towards protein-crystal centering using second-harmonic generation (SHG) microscopy

International Nuclear Information System (INIS)

Kissick, David J.; Dettmar, Christopher M.; Becker, Michael; Mulichak, Anne M.; Cherezov, Vadim; Ginell, Stephan L.; Battaile, Kevin P.; Keefe, Lisa J.; Fischetti, Robert F.; Simpson, Garth J.

2013-01-01

The potential of second-harmonic generation (SHG) microscopy for automated crystal centering to guide synchrotron X-ray diffraction of protein crystals has been explored. The potential of second-harmonic generation (SHG) microscopy for automated crystal centering to guide synchrotron X-ray diffraction of protein crystals was explored. These studies included (i) comparison of microcrystal positions in cryoloops as determined by SHG imaging and by X-ray diffraction rastering and (ii) X-ray structure determinations of selected proteins to investigate the potential for laser-induced damage from SHG imaging. In studies using β 2 adrenergic receptor membrane-protein crystals prepared in lipidic mesophase, the crystal locations identified by SHG images obtained in transmission mode were found to correlate well with the crystal locations identified by raster scanning using an X-ray minibeam. SHG imaging was found to provide about 2 µm spatial resolution and shorter image-acquisition times. The general insensitivity of SHG images to optical scatter enabled the reliable identification of microcrystals within opaque cryocooled lipidic mesophases that were not identified by conventional bright-field imaging. The potential impact of extended exposure of protein crystals to five times a typical imaging dose from an ultrafast laser source was also assessed. Measurements of myoglobin and thaumatin crystals resulted in no statistically significant differences between structures obtained from diffraction data acquired from exposed and unexposed regions of single crystals. Practical constraints for integrating SHG imaging into an active beamline for routine automated crystal centering are discussed

Complex Genetics of Behavior: BXDs in the Automated Home-Cage.

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Loos, Maarten; Verhage, Matthijs; Spijker, Sabine; Smit, August B

2017-01-01

This chapter describes a use case for the genetic dissection and automated analysis of complex behavioral traits using the genetically diverse panel of BXD mouse recombinant inbred strains. Strains of the BXD resource differ widely in terms of gene and protein expression in the brain, as well as in their behavioral repertoire. A large mouse resource opens the possibility for gene finding studies underlying distinct behavioral phenotypes, however, such a resource poses a challenge in behavioral phenotyping. To address the specifics of large-scale screening we describe how to investigate: (1) how to assess mouse behavior systematically in addressing a large genetic cohort, (2) how to dissect automation-derived longitudinal mouse behavior into quantitative parameters, and (3) how to map these quantitative traits to the genome, deriving loci underlying aspects of behavior.

Semi-automated scoring of triple-probe FISH in human sperm using confocal microscopy.

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Branch, Francesca; Nguyen, GiaLinh; Porter, Nicholas; Young, Heather A; Martenies, Sheena E; McCray, Nathan; Deloid, Glen; Popratiloff, Anastas; Perry, Melissa J

2017-09-01

Structural and numerical sperm chromosomal aberrations result from abnormal meiosis and are directly linked to infertility. Any live births that arise from aneuploid conceptuses can result in syndromes such as Kleinfelter, Turners, XYY and Edwards. Multi-probe fluorescence in situ hybridization (FISH) is commonly used to study sperm aneuploidy, however manual FISH scoring in sperm samples is labor-intensive and introduces errors. Automated scoring methods are continuously evolving. One challenging aspect for optimizing automated sperm FISH scoring has been the overlap in excitation and emission of the fluorescent probes used to enumerate the chromosomes of interest. Our objective was to demonstrate the feasibility of combining confocal microscopy and spectral imaging with high-throughput methods for accurately measuring sperm aneuploidy. Our approach used confocal microscopy to analyze numerical chromosomal abnormalities in human sperm using enhanced slide preparation and rigorous semi-automated scoring methods. FISH for chromosomes X, Y, and 18 was conducted to determine sex chromosome disomy in sperm nuclei. Application of online spectral linear unmixing was used for effective separation of four fluorochromes while decreasing data acquisition time. Semi-automated image processing, segmentation, classification, and scoring were performed on 10 slides using custom image processing and analysis software and results were compared with manual methods. No significant differences in disomy frequencies were seen between the semi automated and manual methods. Samples treated with pepsin were observed to have reduced background autofluorescence and more uniform distribution of cells. These results demonstrate that semi-automated methods using spectral imaging on a confocal platform are a feasible approach for analyzing numerical chromosomal aberrations in sperm, and are comparable to manual methods. © 2017 International Society for Advancement of Cytometry. © 2017

78 FR 66039 - Modification of National Customs Automation Program Test Concerning Automated Commercial...

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2013-11-04

... Customs Automation Program Test Concerning Automated Commercial Environment (ACE) Cargo Release (Formerly...) plan to both rename and modify the National Customs Automation Program (NCAP) test concerning the... data elements required to obtain release for cargo transported by air. The test will now be known as...

A novel method for the accurate evaluation of Poisson's ratio of soft polymer materials.

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Lee, Jae-Hoon; Lee, Sang-Soo; Chang, Jun-Dong; Thompson, Mark S; Kang, Dong-Joong; Park, Sungchan; Park, Seonghun

2013-01-01

A new method with a simple algorithm was developed to accurately measure Poisson's ratio of soft materials such as polyvinyl alcohol hydrogel (PVA-H) with a custom experimental apparatus consisting of a tension device, a micro X-Y stage, an optical microscope, and a charge-coupled device camera. In the proposed method, the initial positions of the four vertices of an arbitrarily selected quadrilateral from the sample surface were first measured to generate a 2D 1st-order 4-node quadrilateral element for finite element numerical analysis. Next, minimum and maximum principal strains were calculated from differences between the initial and deformed shapes of the quadrilateral under tension. Finally, Poisson's ratio of PVA-H was determined by the ratio of minimum principal strain to maximum principal strain. This novel method has an advantage in the accurate evaluation of Poisson's ratio despite misalignment between specimens and experimental devices. In this study, Poisson's ratio of PVA-H was 0.44 ± 0.025 (n = 6) for 2.6-47.0% elongations with a tendency to decrease with increasing elongation. The current evaluation method of Poisson's ratio with a simple measurement system can be employed to a real-time automated vision-tracking system which is used to accurately evaluate the material properties of various soft materials.

An investigation of highly accurate and precise robotic hole measurements using non-contact devices

Directory of Open Access Journals (Sweden)

Usman Zahid

2016-01-01

Full Text Available Industrial robots arms are widely used in manufacturing industry because of their support for automation. However, in metrology, robots have had limited application due to their insufficient accuracy. Even using error compensation and calibration methods, robots are not effective for micrometre (μm level metrology. Non-contact measurement devices can potentially enable the use of robots for highly accurate metrology. However, the use of such devices on robots has not been investigated. The research work reported in this paper explores the use of different non-contact measurement devices on an industrial robot. The aim is to experimentally investigate the effects of robot movements on the accuracy and precision of measurements. The focus has been on assessing the ability to accurately measure various geometric and surface parameters of holes despite the inherent inaccuracies of industrial robot. This involves the measurement of diameter, roundness and surface roughness. The study also includes scanning of holes for measuring internal features such as start and end point of a taper. Two different non-contact measurement devices based on different technologies are investigated. Furthermore, effects of eccentricity, vibrations and thermal variations are also assessed. The research contributes towards the use of robots for highly accurate and precise robotic metrology.

Application of bar codes to the automation of analytical sample data collection

International Nuclear Information System (INIS)

Jurgensen, H.A.

1986-01-01

The Health Protection Department at the Savannah River Plant collects 500 urine samples per day for tritium analyses. Prior to automation, all sample information was compiled manually. Bar code technology was chosen for automating this program because it provides a more accurate, efficient, and inexpensive method for data entry. The system has three major functions: sample labeling is accomplished at remote bar code label stations composed of an Intermec 8220 (Intermec Corp.) interfaced to an IBM-PC, data collection is done on a central VAX 11/730 (Digital Equipment Corp.). Bar code readers are used to log-in samples to be analyzed on liquid scintillation counters. The VAX 11/730 processes the data and generates reports, data storage is on the VAX 11/730 and backed up on the plant's central computer. A brief description of several other bar code applications at the Savannah River Plant is also presented

Automation-aided Task Loads Index based on the Automation Rate Reflecting the Effects on Human Operators in NPPs

International Nuclear Information System (INIS)

Lee, Seungmin; Seong, Poonghyun; Kim, Jonghyun

2013-01-01

Many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs) was suggested. These suggested measures express how much automation support human operators but it cannot express the change of human operators' workload, whether the human operators' workload is increased or decreased. Before considering automation rates, whether the adopted automation is good or bad might be estimated in advance. In this study, to estimate the appropriateness of automation according to the change of the human operators' task loads, automation-aided task loads index is suggested based on the concept of the suggested automation rate. To insure plant safety and efficiency on behalf of human operators, various automation systems have been installed in NPPs, and many works which were previously conducted by human operators can now be supported by computer-based operator aids. According to the characteristics of the automation types, the estimation method of the system automation and the cognitive automation rate were suggested. The proposed estimation method concentrates on the effects of introducing automation, so it directly express how much the automated system support human operators. Based on the suggested automation rates, the way to estimate how much the automated system can affect the human operators' cognitive task load is suggested in this study. When there is no automation, the calculated index is 1, and it means there is no change of human operators' task load

Verification of Single-Peptide Protein Identifications by the Application of Complementary Database Search Algorithms

National Research Council Canada - National Science Library

Rohrbough, James G; Breci, Linda; Merchant, Nirav; Miller, Susan; Haynes, Paul A

2005-01-01

.... One such technique, known as the Multi-Dimensional Protein Identification Technique, or MudPIT, involves the use of computer search algorithms that automate the process of identifying proteins...

Integrated Markov-neural reliability computation method: A case for multiple automated guided vehicle system

International Nuclear Information System (INIS)

Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep

2015-01-01

This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks

Asleep at the automated wheel-Sleepiness and fatigue during highly automated driving.

Science.gov (United States)

Vogelpohl, Tobias; Kühn, Matthias; Hummel, Thomas; Vollrath, Mark

2018-03-20

Due to the lack of active involvement in the driving situation and due to monotonous driving environments drivers with automation may be prone to become fatigued faster than manual drivers (e.g. Schömig et al., 2015). However, little is known about the progression of fatigue during automated driving and its effects on the ability to take back manual control after a take-over request. In this driving simulator study with Nö=ö60 drivers we used a three factorial 2ö×ö2ö×ö12 mixed design to analyze the progression (12ö×ö5ömin; within subjects) of driver fatigue in drivers with automation compared to manual drivers (between subjects). Driver fatigue was induced as either mainly sleep related or mainly task related fatigue (between subjects). Additionally, we investigated the drivers' reactions to a take-over request in a critical driving scenario to gain insights into the ability of fatigued drivers to regain manual control and situation awareness after automated driving. Drivers in the automated driving condition exhibited facial indicators of fatigue after 15 to 35ömin of driving. Manual drivers only showed similar indicators of fatigue if they suffered from a lack of sleep and then only after a longer period of driving (approx. 40ömin). Several drivers in the automated condition closed their eyes for extended periods of time. In the driving with automation condition mean automation deactivation times after a take-over request were slower for a certain percentage (about 30%) of the drivers with a lack of sleep (Mö=ö3.2; SDö=ö2.1ös) compared to the reaction times after a long drive (Mö=ö2.4; SDö=ö0.9ös). Drivers with automation also took longer than manual drivers to first glance at the speed display after a take-over request and were more likely to stay behind a braking lead vehicle instead of overtaking it. Drivers are unable to stay alert during extended periods of automated driving without non-driving related tasks. Fatigued drivers could

Automated docking screens: a feasibility study.

Science.gov (United States)

Irwin, John J; Shoichet, Brian K; Mysinger, Michael M; Huang, Niu; Colizzi, Francesco; Wassam, Pascal; Cao, Yiqun

2009-09-24

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 A rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 A rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org .

Procedure automation: the effect of automated procedure execution on situation awareness and human performance

International Nuclear Information System (INIS)

Andresen, Gisle; Svengren, Haakan; Heimdal, Jan O.; Nilsen, Svein; Hulsund, John-Einar; Bisio, Rossella; Debroise, Xavier

2004-04-01

As advised by the procedure workshop convened in Halden in 2000, the Halden Project conducted an experiment on the effect of automation of Computerised Procedure Systems (CPS) on situation awareness and human performance. The expected outcome of the study was to provide input for guidance on CPS design, and to support the Halden Project's ongoing research on human reliability analysis. The experiment was performed in HAMMLAB using the HAMBO BWR simulator and the COPMA-III CPS. Eight crews of operators from Forsmark 3 and Oskarshamn 3 participated. Three research questions were investigated: 1) Does procedure automation create Out-Of-The-Loop (OOTL) performance problems? 2) Does procedure automation affect situation awareness? 3) Does procedure automation affect crew performance? The independent variable, 'procedure configuration', had four levels: paper procedures, manual CPS, automation with breaks, and full automation. The results showed that the operators experienced OOTL problems in full automation, but that situation awareness and crew performance (response time) were not affected. One possible explanation for this is that the operators monitored the automated procedure execution conscientiously, something which may have prevented the OOTL problems from having negative effects on situation awareness and crew performance. In a debriefing session, the operators clearly expressed their dislike for the full automation condition, but that automation with breaks could be suitable for some tasks. The main reason why the operators did not like the full automation was that they did not feel being in control. A qualitative analysis addressing factors contributing to response time delays revealed that OOTL problems did not seem to cause delays, but that some delays could be explained by the operators having problems with the freeze function of the CPS. Also other factors such as teamwork and operator tendencies were of importance. Several design implications were drawn

Total Protein Content Determination of Microalgal Biomass by Elemental Nitrogen Analysis and a Dedicated Nitrogen-to-Protein Conversion Factor

Energy Technology Data Exchange (ETDEWEB)

Laurens, Lieve M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Olstad-Thompson, Jessica L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Templeton, David W [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-04-02

Accurately determining protein content is important in the valorization of algal biomass in food, feed, and fuel markets, where these values are used for component balance calculations. Conversion of elemental nitrogen to protein is a well-accepted and widely practiced method, but depends on developing an applicable nitrogen-to-protein conversion factor. The methodology reported here covers the quantitative assessment of the total nitrogen content of algal biomass and a description of the methodology that underpins the accurate de novo calculation of a dedicated nitrogen-to-protein conversion factor.

Automated main-chain model building by template matching and iterative fragment extension.

Science.gov (United States)

Terwilliger, Thomas C

2003-01-01

An algorithm for the automated macromolecular model building of polypeptide backbones is described. The procedure is hierarchical. In the initial stages, many overlapping polypeptide fragments are built. In subsequent stages, the fragments are extended and then connected. Identification of the locations of helical and beta-strand regions is carried out by FFT-based template matching. Fragment libraries of helices and beta-strands from refined protein structures are then positioned at the potential locations of helices and strands and the longest segments that fit the electron-density map are chosen. The helices and strands are then extended using fragment libraries consisting of sequences three amino acids long derived from refined protein structures. The resulting segments of polypeptide chain are then connected by choosing those which overlap at two or more C(alpha) positions. The fully automated procedure has been implemented in RESOLVE and is capable of model building at resolutions as low as 3.5 A. The algorithm is useful for building a preliminary main-chain model that can serve as a basis for refinement and side-chain addition.

Automated robust generation of compact 3D statistical shape models

Science.gov (United States)

Vrtovec, Tomaz; Likar, Bostjan; Tomazevic, Dejan; Pernus, Franjo

2004-05-01

Ascertaining the detailed shape and spatial arrangement of anatomical structures is important not only within diagnostic settings but also in the areas of planning, simulation, intraoperative navigation, and tracking of pathology. Robust, accurate and efficient automated segmentation of anatomical structures is difficult because of their complexity and inter-patient variability. Furthermore, the position of the patient during image acquisition, the imaging device and protocol, image resolution, and other factors induce additional variations in shape and appearance. Statistical shape models (SSMs) have proven quite successful in capturing structural variability. A possible approach to obtain a 3D SSM is to extract reference voxels by precisely segmenting the structure in one, reference image. The corresponding voxels in other images are determined by registering the reference image to each other image. The SSM obtained in this way describes statistically plausible shape variations over the given population as well as variations due to imperfect registration. In this paper, we present a completely automated method that significantly reduces shape variations induced by imperfect registration, thus allowing a more accurate description of variations. At each iteration, the derived SSM is used for coarse registration, which is further improved by describing finer variations of the structure. The method was tested on 64 lumbar spinal column CT scans, from which 23, 38, 45, 46 and 42 volumes of interest containing vertebra L1, L2, L3, L4 and L5, respectively, were extracted. Separate SSMs were generated for each vertebra. The results show that the method is capable of reducing the variations induced by registration errors.

Automated Cross-Sectional Measurement Method of Intracranial Dural Venous Sinuses.

Science.gov (United States)

Lublinsky, S; Friedman, A; Kesler, A; Zur, D; Anconina, R; Shelef, I

2016-03-01

MRV is an important blood vessel imaging and diagnostic tool for the evaluation of stenosis, occlusions, or aneurysms. However, an accurate image-processing tool for vessel comparison is unavailable. The purpose of this study was to develop and test an automated technique for vessel cross-sectional analysis. An algorithm for vessel cross-sectional analysis was developed that included 7 main steps: 1) image registration, 2) masking, 3) segmentation, 4) skeletonization, 5) cross-sectional planes, 6) clustering, and 7) cross-sectional analysis. Phantom models were used to validate the technique. The method was also tested on a control subject and a patient with idiopathic intracranial hypertension (4 large sinuses tested: right and left transverse sinuses, superior sagittal sinus, and straight sinus). The cross-sectional area and shape measurements were evaluated before and after lumbar puncture in patients with idiopathic intracranial hypertension. The vessel-analysis algorithm had a high degree of stability with <3% of cross-sections manually corrected. All investigated principal cranial blood sinuses had a significant cross-sectional area increase after lumbar puncture (P ≤ .05). The average triangularity of the transverse sinuses was increased, and the mean circularity of the sinuses was decreased by 6% ± 12% after lumbar puncture. Comparison of phantom and real data showed that all computed errors were <1 voxel unit, which confirmed that the method provided a very accurate solution. In this article, we present a novel automated imaging method for cross-sectional vessels analysis. The method can provide an efficient quantitative detection of abnormalities in the dural sinuses. © 2016 by American Journal of Neuroradiology.

Validity of automated measurement of left ventricular ejection fraction and volume using the Philips EPIQ system.

Science.gov (United States)

Hovnanians, Ninel; Win, Theresa; Makkiya, Mohammed; Zheng, Qi; Taub, Cynthia

2017-11-01

To assess the efficiency and reproducibility of automated measurements of left ventricular (LV) volumes and LV ejection fraction (LVEF) in comparison to manually traced biplane Simpson's method. This is a single-center prospective study. Apical four- and two-chamber views were acquired in patients in sinus rhythm. Two operators independently measured LV volumes and LVEF using biplane Simpson's method. In addition, the image analysis software a2DQ on the Philips EPIQ system was applied to automatically assess the LV volumes and LVEF. Time spent on each analysis, using both methods, was documented. Concordance of echocardiographic measures was evaluated using intraclass correlation (ICC) and Bland-Altman analysis. Manual tracing and automated measurement of LV volumes and LVEF were performed in 184 patients with a mean age of 67.3 ± 17.3 years and BMI 28.0 ± 6.8 kg/m 2 . ICC and Bland-Altman analysis showed good agreements between manual and automated methods measuring LVEF, end-systolic, and end-diastolic volumes. The average analysis time was significantly less using the automated method than manual tracing (116 vs 217 seconds/patient, P Automated measurement using the novel image analysis software a2DQ on the Philips EPIQ system produced accurate, efficient, and reproducible assessment of LV volumes and LVEF compared with manual measurement. © 2017, Wiley Periodicals, Inc.

Automation-aided Task Loads Index based on the Automation Rate Reflecting the Effects on Human Operators in NPPs

Energy Technology Data Exchange (ETDEWEB)

Lee, Seungmin; Seong, Poonghyun [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Kim, Jonghyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2013-05-15

Many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs) was suggested. These suggested measures express how much automation support human operators but it cannot express the change of human operators' workload, whether the human operators' workload is increased or decreased. Before considering automation rates, whether the adopted automation is good or bad might be estimated in advance. In this study, to estimate the appropriateness of automation according to the change of the human operators' task loads, automation-aided task loads index is suggested based on the concept of the suggested automation rate. To insure plant safety and efficiency on behalf of human operators, various automation systems have been installed in NPPs, and many works which were previously conducted by human operators can now be supported by computer-based operator aids. According to the characteristics of the automation types, the estimation method of the system automation and the cognitive automation rate were suggested. The proposed estimation method concentrates on the effects of introducing automation, so it directly express how much the automated system support human operators. Based on the suggested automation rates, the way to estimate how much the automated system can affect the human operators' cognitive task load is suggested in this study. When there is no automation, the calculated index is 1, and it means there is no change of human operators' task load.

Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease

Directory of Open Access Journals (Sweden)

Jing Wu

2016-01-01

Full Text Available In macular spectral domain optical coherence tomography (SD-OCT volumes, detection of the foveal center is required for accurate and reproducible follow-up studies, structure function correlation, and measurement grid positioning. However, disease can cause severe obscuring or deformation of the fovea, thus presenting a major challenge in automated detection. We propose a fully automated fovea detection algorithm to extract the fovea position in SD-OCT volumes of eyes with exudative maculopathy. The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity. Based on foveal type classification, the fovea position is computed based on retinal nerve fiber layer thickness. Mean absolute distance between system and clinical expert annotated fovea positions from a dataset comprised of 240 SD-OCT volumes was 162.3 µm in cystoid macular edema and 262 µm in nAMD. The presented method has cross-vendor functionality, while demonstrating accurate and reliable performance close to typical expert interobserver agreement. The automatically detected fovea positions may be used as landmarks for intra- and cross-patient registration and to create a joint reference frame for extraction of spatiotemporal features in “big data.” Furthermore, reliable analyses of retinal thickness, as well as retinal structure function correlation, may be facilitated.

Automated extinction monitor for the NLOT site survey

Science.gov (United States)

Kumar Sharma, Tarun

In order to search a few potential sites for the National Large Optical Telescope (NLOT) project, we have initiated a site survey program. Since, most of instruments used for the site survey are custom made, we also started developing our own site characterization instruments. In this process we have designed and developed a device called Automated Extinction Monitor (AEM) and installed the same at IAO, Hanle. The AEM is a small wide field robotic telescope, dedicated to record atmospheric extinction in one or more photometric bands. It gives very accurate statistics of the distribution of photometric nights. In addition to this, instrument also provides the measurement of sky brightness. Here we briefly describe overall instrument and initial results obtained.

Automation of radioimmunoassay

International Nuclear Information System (INIS)

Yamaguchi, Chisato; Yamada, Hideo; Iio, Masahiro

1974-01-01

Automation systems for measuring Australian antigen by radioimmunoassay under development were discussed. Samples were processed as follows: blood serum being dispensed by automated sampler to the test tube, and then incubated under controlled time and temperature; first counting being omitted; labelled antibody being dispensed to the serum after washing; samples being incubated and then centrifuged; radioactivities in the precipitate being counted by auto-well counter; measurements being tabulated by automated typewriter. Not only well-type counter but also position counter was studied. (Kanao, N.)

77 FR 48527 - National Customs Automation Program (NCAP) Test Concerning Automated Commercial Environment (ACE...

Science.gov (United States)

2012-08-14

... National Customs Automation Program (NCAP) test concerning the simplified entry functionality in the... DEPARTMENT OF HOMELAND SECURITY U.S. Customs and Border Protection National Customs Automation Program (NCAP) Test Concerning Automated Commercial Environment (ACE) Simplified Entry: Modification of...

Ultrasound-guided renal biopsy: experience using an automated core biopsy system.

Science.gov (United States)

Chan, R; Common, A A; Marcuzzi, D

2000-04-01

To assess the safety and efficacy of ultrasound-guided percutaneous renal biopsy using an automated core biopsy system, and to determine radiologists' accuracy in predicting sample adequacy. Ninety-five biopsies were performed on 25 native kidneys and 70 renal allografts using a 16-gauge automated, spring-loaded core biopsy device under real-time sonographic guidance. Radiologists performing the biopsy estimated the number of core samples needed to obtain an adequate specimen, based on visual inspection of each core. The final determination of the number of samples was made by a pathology technologist who attended each biopsy, based on preliminary microscopic examination of tissue cores. After each biopsy, an ultrasonographic examination was performed to search for biopsy-related hemorrhage, and a questionnaire was given to the patient to determine biopsy-related complications, which were categorized as either minor or major. The main indication for biopsy was acute renal failure (in 43.2% of biopsies). An average of 3 tissue cores per biopsy were obtained. Of the 94 patients in whom a biopsy was conducted to exclude diffuse renal disease, a mean of 12.5 glomeruli were present in each specimen. Overall, adequate tissue for diagnosis was obtained in 98.9% of cases. The radiologists' estimate of the number of core samples needed concurred with the pathology technologists' determination of sample adequacy in 88.4% of cases. A total of 26 complications occurred (in 27.4% of biopsies), consisting of 23 minor (24.2%) and 3 major (3.2%) complications. Real-time sonographic guidance in conjunction with an automated core biopsy system is a safe and accurate method of performing percutaneous renal biopsy. Routine use of sonographic examinations to search for biopsy-related complications is not indicated. Radiologists are accurate in estimating sample adequacy in most cases; however, the presence of a pathology technologist at the biopsy procedure virtually eliminates the

The comparison of automated urine analyzers with manual microscopic examination for urinalysis automated urine analyzers and manual urinalysis.

Science.gov (United States)

İnce, Fatma Demet; Ellidağ, Hamit Yaşar; Koseoğlu, Mehmet; Şimşek, Neşe; Yalçın, Hülya; Zengin, Mustafa Osman

2016-08-01

Urinalysis is one of the most commonly performed tests in the clinical laboratory. However, manual microscopic sediment examination is labor-intensive, time-consuming, and lacks standardization in high-volume laboratories. In this study, the concordance of analyses between manual microscopic examination and two different automatic urine sediment analyzers has been evaluated. 209 urine samples were analyzed by the Iris iQ200 ELITE (İris Diagnostics, USA), Dirui FUS-200 (DIRUI Industrial Co., China) automatic urine sediment analyzers and by manual microscopic examination. The degree of concordance (Kappa coefficient) and the rates within the same grading were evaluated. For erythrocytes, leukocytes, epithelial cells, bacteria, crystals and yeasts, the degree of concordance between the two instruments was better than the degree of concordance between the manual microscopic method and the individual devices. There was no concordance between all methods for casts. The results from the automated analyzers for erythrocytes, leukocytes and epithelial cells were similar to the result of microscopic examination. However, in order to avoid any error or uncertainty, some images (particularly: dysmorphic cells, bacteria, yeasts, casts and crystals) have to be analyzed by manual microscopic examination by trained staff. Therefore, the software programs which are used in automatic urine sediment analysers need further development to recognize urinary shaped elements more accurately. Automated systems are important in terms of time saving and standardization.

Building biochips: a protein production pipeline

Science.gov (United States)

de Carvalho-Kavanagh, Marianne G. S.; Albala, Joanna S.

2004-06-01

Protein arrays are emerging as a practical format in which to study proteins in high-throughput using many of the same techniques as that of the DNA microarray. The key advantage to array-based methods for protein study is the potential for parallel analysis of thousands of samples in an automated, high-throughput fashion. Building protein arrays capable of this analysis capacity requires a robust expression and purification system capable of generating hundreds to thousands of purified recombinant proteins. We have developed a method to utilize LLNL-I.M.A.G.E. cDNAs to generate recombinant protein libraries using a baculovirus-insect cell expression system. We have used this strategy to produce proteins for analysis of protein/DNA and protein/protein interactions using protein microarrays in order to understand the complex interactions of proteins involved in homologous recombination and DNA repair. Using protein array techniques, a novel interaction between the DNA repair protein, Rad51B, and histones has been identified.

Application of an Automated Discharge Imaging System and LSPIV during Typhoon Events in Taiwan

OpenAIRE

Wei-Che Huang; Chih-Chieh Young; Wen-Cheng Liu

2018-01-01

An automated discharge imaging system (ADIS), which is a non-intrusive and safe approach, was developed for measuring river flows during flash flood events. ADIS consists of dual cameras to capture complete surface images in the near and far fields. Surface velocities are accurately measured using the Large Scale Particle Image Velocimetry (LSPIV) technique. The stream discharges are then obtained from the depth-averaged velocity (based upon an empirical velocity-index relationship) and cross...

Laboratory Automation and Middleware.

Science.gov (United States)

Riben, Michael

2015-06-01

The practice of surgical pathology is under constant pressure to deliver the highest quality of service, reduce errors, increase throughput, and decrease turnaround time while at the same time dealing with an aging workforce, increasing financial constraints, and economic uncertainty. Although not able to implement total laboratory automation, great progress continues to be made in workstation automation in all areas of the pathology laboratory. This report highlights the benefits and challenges of pathology automation, reviews middleware and its use to facilitate automation, and reviews the progress so far in the anatomic pathology laboratory. Copyright © 2015 Elsevier Inc. All rights reserved.

Managing laboratory automation.

Science.gov (United States)

Saboe, T J

1995-01-01

This paper discusses the process of managing automated systems through their life cycles within the quality-control (QC) laboratory environment. The focus is on the process of directing and managing the evolving automation of a laboratory; system examples are given. The author shows how both task and data systems have evolved, and how they interrelate. A BIG picture, or continuum view, is presented and some of the reasons for success or failure of the various examples cited are explored. Finally, some comments on future automation need are discussed.

Unified Brake Service by a Hierarchical Controller for Active Deceleration Control in an Electric and Automated Vehicle

Directory of Open Access Journals (Sweden)

Yuliang Nie

2017-12-01

Full Text Available Unified brake service is a universal service for generating certain brake force to meet the demand deceleration and is essential for an automated driving system. However, it is rather difficult to control the pressure in the wheel cylinders to reach the target deceleration of the automated vehicle, which is the key issue of the active deceleration control system (ADC. This paper proposes a hierarchical control method to actively control vehicle deceleration with active-brake actuators. In the upper hierarchical, the target pressure of wheel cylinders is obtained by dynamic equations of a pure electric vehicle. In the lower hierarchical, the solenoid valve instructions and the pump speed of hydraulic control unit (HCU are determined to satisfy the desired pressure with the feedback of measured wheel cylinder pressure by pressure sensors. Results of road experiments of a pure electric and automated vehicle indicate that the proposed method realizes the target deceleration accurately and efficiently.

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

A Fully Automated Penumbra Segmentation Tool

DEFF Research Database (Denmark)

Nagenthiraja, Kartheeban; Ribe, Lars Riisgaard; Hougaard, Kristina Dupont

2012-01-01

Introduction: Perfusion- and diffusion weighted MRI (PWI/DWI) is widely used to select patients who are likely to benefit from recanalization therapy. The visual identification of PWI-DWI-mismatch tissue depends strongly on the observer, prompting a need for software, which estimates potentially...... salavageable tissue, quickly and accurately. We present a fully Automated Penumbra Segmentation (APS) algorithm using PWI and DWI images. We compare automatically generated PWI-DWI mismatch mask to mask outlined manually by experts, in 168 patients. Method: The algorithm initially identifies PWI lesions......) at 600∙10-6 mm2/sec. Due to the nature of thresholding, the ADC mask overestimates the DWI lesion volume and consequently we initialized level-set algorithm on DWI image with ADC mask as prior knowledge. Combining the PWI and inverted DWI mask then yield the PWI-DWI mismatch mask. Four expert raters...

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.)

78 FR 44142 - Modification of Two National Customs Automation Program (NCAP) Tests Concerning Automated...

Science.gov (United States)

2013-07-23

... Customs Automation Program (NCAP) Tests Concerning Automated Commercial Environment (ACE) Document Image... (CBP's) plan to modify the National Customs Automation Program (NCAP) tests concerning document imaging... entry process by reducing the number of data elements required to obtain release for cargo transported...

The Science of Home Automation

Science.gov (United States)

Thomas, Brian Louis

Smart home technologies and the concept of home automation have become more popular in recent years. This popularity has been accompanied by social acceptance of passive sensors installed throughout the home. The subsequent increase in smart homes facilitates the creation of home automation strategies. We believe that home automation strategies can be generated intelligently by utilizing smart home sensors and activity learning. In this dissertation, we hypothesize that home automation can benefit from activity awareness. To test this, we develop our activity-aware smart automation system, CARL (CASAS Activity-aware Resource Learning). CARL learns the associations between activities and device usage from historical data and utilizes the activity-aware capabilities to control the devices. To help validate CARL we deploy and test three different versions of the automation system in a real-world smart environment. To provide a foundation of activity learning, we integrate existing activity recognition and activity forecasting into CARL home automation. We also explore two alternatives to using human-labeled data to train the activity learning models. The first unsupervised method is Activity Detection, and the second is a modified DBSCAN algorithm that utilizes Dynamic Time Warping (DTW) as a distance metric. We compare the performance of activity learning with human-defined labels and with automatically-discovered activity categories. To provide evidence in support of our hypothesis, we evaluate CARL automation in a smart home testbed. Our results indicate that home automation can be boosted through activity awareness. We also find that the resulting automation has a high degree of usability and comfort for the smart home resident.

Adaptive Automation Design and Implementation

Science.gov (United States)

2015-09-17

with an automated system to a real-world adaptive au- tomation system implementation. There have been plenty of adaptive automation 17 Adaptive...of systems without increasing manpower requirements by allocating routine tasks to automated aids, improving safety through the use of au- tomated ...between intermediate levels of au- tomation , explicitly defining which human task a given level automates. Each model aids the creation and classification

Layered distributed architecture for plant automation

International Nuclear Information System (INIS)

Aravamuthan, G.; Verma, Yachika; Ranjan, Jyoti; Chachondia, Alka S.; Ganesh, G.

2005-01-01

The development of plant automation system and associated software remains one of the greatest challenges to the widespread implementation of highly adaptive re-configurable automation technology. This paper presents a layered distributed architecture for a plant automation system designed to support rapid reconfiguration and redeployment of automation components. The paper first presents evolution of automation architecture and their associated environment in the past few decades and then presents the concept of layered system architecture and the use of automation components to support the construction of a wide variety of automation system. It also highlights the role of standards and technology, which can be used in the development of automation components. We have attempted to adhere to open standards and technology for the development of automation component at a various layers. It also highlights the application of this concept in the development of an Operator Information System (OIS) for Advanced Heavy Water Reactor (AHWR). (author)