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Journal articles on the topic 'Laboratory information management system (LIMS)'

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Published: 4 June 2021
Last updated: 4 February 2022

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1

Hu, Yu. "Development of Information Management System Used in Laboratory." Advanced Materials Research 605-607 (December 2012): 2518–21. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2518.

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The aim of this paper is to develop a Laboratory Information Management System (LIMS). The system will act as a secure repository for both public and proprietary data. The public repository will contain all the data from other public repositories as well as the data released by the researchers into the public domain. The secure repository will manage the data and maintain its privacy until the researcher who owns it shares it with the public. This secure repository needs login credentials that should be validated to access the system. It is this type of system that would be used to design the experiments that would be submitted to the LIMS system.
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2

Akhtyamov, Eldar R., Alexander Y. Dedyukhin, and Evgeny V. Koshkarov. "Organization of road quality control using the U-LAB laboratory information management system." Innotrans, no. 1 (2021): 55–62. http://dx.doi.org/10.20291/2311-164x-2021-1-55-62.

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The article discusses the results of implementation of the laboratory information management system (LIMS) U-LAB, developed by the UralNIIstrom Institute and tested in the regional road sector. The system of quality control of asphalt-concrete road surfaces, road pavement structures and road-building materials in the construction, repair and maintenance of highways is presented, the role of independent laboratory control, engineering and scientifictechnical support, supervision of design decisions is defined. The content and advantages of using the U-LAB LIMS for organizing and improving the efficiency of laboratory quality control of highways and building materials, improving interaction between road management bodies, contractors, design and scientific organizations involved in road works are described. The program interface is shown, the results and technical and economic indicators of the implementation and operation of LIMS in the UralNIIstrom test center in 2020 are presented.
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Varaksin, Konstantin S., Artem S. Makarov, and Alexander Y. Lyapin. "Competency management of laboratory personnel using LIMS." SCIENCE & TECHNOLOGIES OIL AND OIL PRODUCTS PIPELINE TRANSPORTATION 10, no. 6 (November 30, 2020): 636–41. http://dx.doi.org/10.28999/2541-9595-2020-10-6-636-641.

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The updated edition of the ISO/IEC 17025 standard introduced significant changes to the structure, terminology, resource requirements, processes, quality management system of testing and calibration laboratories. New requirements were established for the organization of laboratory activities – a process approach and risk-based thinking, which provides for a reduction in part of the prescriptive requirements and the introduction of requirements based on the analysis of the performance of actions. In accordance with GOST ISO IEC 17025-2019, the laboratory must authorize personnel to perform specific laboratory activities, as well as guarantee their competence. This article discusses the organization of the competence management system for the personnel of the laboratories of the organizations of Transneft system using the laboratory information management system (LIMS). The model of the process implementation has been described. It has been established that the competence test system allows you to regularly monitor the skills and knowledge of laboratory workers both in terms of the elements of the Quality Management System and in the applied measurement (test) methods. The personnel responsibility matrix implemented in LIMS regulates the powers and functionality of employees, ensuring that employees are allowed to perform work in accordance with their competence. The functions implemented in LIMS made it possible to automate the management of the competence of laboratory workers in accordance with the requirements of GOST ISO/IEC 17025-2019 and other regulatory documents.
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Craig, Thomas, Richard Holland, Rosalinda D’Amore, James R. Johnson, Hannah V. McCue, Anthony West, Valentin Zulkower, et al. "Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus." ACS Synthetic Biology 6, no. 12 (September 13, 2017): 2273–80. http://dx.doi.org/10.1021/acssynbio.7b00212.

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Clément, Sébastien, Joël Fillon, Jean Bousquet, and Jean Beaulieu. "TreeSNPs: a laboratory information management system (LIMS) dedicated to SNP discovery in trees." Tree Genetics & Genomes 6, no. 3 (January 13, 2010): 435–38. http://dx.doi.org/10.1007/s11295-009-0261-6.

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Saputra, Andika Bayu, and Ari Cahyono. "Analisis dan Perancangan Laboratory Information Management System (LIMS) Menggunakan Metode Total Architecture Synthesis (TAS)." JISKA (Jurnal Informatika Sunan Kalijaga) 5, no. 1 (May 19, 2020): 7. http://dx.doi.org/10.14421/jiska.2020.51-02.

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At present the laboratories in Colombo Yogyakarta High School have been utilized to the maximum but in the management process they are still using conventional methods and data that are not integrated either relating to administration of the laboratory, recording laboratory assets, scheduling and valuation. Recording that occurs at this time is done by using Microsoft Excel and only limited to be recorded without any synchronization and socialization to the teachers - so that it causes the use of laboratory space which is often a collision scheduling. The recording of laboratory assets is not neatly arranged so that the monitoring of assets both maintenance, replacement and repair of equipment is not well documented. This research implements the Total Architecture Synthesis (TAS) method. The total architecture synthesis method functions to determine the needs and design of business process architecture and system architecture.
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7

Turner, E. "Implementing a Laboratory Information Management System (LIMS) in an Army Corps of Engineers' Water Quality Testing Laboratory." Journal of the Association for Laboratory Automation 6, no. 5 (November 1, 2001): 60–63. http://dx.doi.org/10.1016/s1535-5535(04)00158-3.

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8

Turner, Elizabeth, Christine Paszko, and Don Kolva. "Implementing a Laboratory Information Management System (LIMS) in an Army Corps of Engineers' Water Quality Testing Laboratory." JALA: Journal of the Association for Laboratory Automation 6, no. 5 (October 2001): 60–63. http://dx.doi.org/10.1016/s1535-5535-04-00158-3.

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9

Droit, Arnaud, Joanna M. Hunter, Michèle Rouleau, Chantal Ethier, Aude Picard-Cloutier, David Bourgais, and Guy G. Poirier. "PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system." BMC Bioinformatics 8, no. 1 (2007): 483. http://dx.doi.org/10.1186/1471-2105-8-483.

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10

Hull, Carl. "Editorial [Hot Topic: Laboratory Information Management Systems (LIMS) (Guest Editor: Carl Hull)]." Combinatorial Chemistry & High Throughput Screening 14, no. 9 (November 1, 2011): 741. http://dx.doi.org/10.2174/138620711796957107.

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11

McDowall, R. D. "The role of laboratory information management systems (LIMS) in analytical method validation." Analytica Chimica Acta 391, no. 2 (May 1999): 149–58. http://dx.doi.org/10.1016/s0003-2670(99)00107-5.

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12

Çağındı, Özlem, and Semih Ötleş. "Importance of laboratory information management systems (LIMS) software for food processing factories." Journal of Food Engineering 65, no. 4 (December 2004): 565–68. http://dx.doi.org/10.1016/j.jfoodeng.2004.02.021.

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13

Prilusky, Jaime, Eric Oueillet, Nathalie Ulryck, Anne Pajon, Julie Bernauer, Isabelle Krimm, Sophie Quevillon-Cheruel, et al. "HalX: an open-source LIMS (Laboratory Information Management System) for small- to large-scale laboratories." Acta Crystallographica Section D Biological Crystallography 61, no. 6 (May 26, 2005): 671–78. http://dx.doi.org/10.1107/s0907444905001290.

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Schmieder, Florian, Christoph Polk, Felix Gottlöber, Patrick Schöps, Frank Sonntag, Ronny Deuse, Aline Jede, and Thomas Petzold. "Universal LIMS based platform for the automated processing of cell-based assays." Current Directions in Biomedical Engineering 5, no. 1 (September 1, 2019): 437–39. http://dx.doi.org/10.1515/cdbme-2019-0110.

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AbstractNowadays, cell-based assays are an elementary tool for diagnostics, animal-free substance testing and basic research. Depending on the application, the spectrum ranges from simple static cell cultures in microtiter plates to dynamic co-cultures in complex micro physiological systems (organ-on-a-chip). Depending on the complexity of the assay, numerous working steps have to be performed and the data from different analysis systems have to be processed, combined and documented. A universal platform has been developed for the automated handling of cell-based assays, which combines a laboratory information management system (LIMS) with a laboratory execution system (LES), a universal laboratory automation platform and established laboratory equipment. The LIMS handles the administration of all laboratory-relevant information, the planning, control and monitoring of laboratory processes, as well as the direct and qualified processing of raw data. Using a kidney-on-achip system as an example, the realization of complex cellbased assays for the animal-free characterization of the toxicity of different antibiotics will be demonstrated. In the kidney-on-a-chip system the artificial proximal tubular barrier was formed by seeding human immortalized proximal tubule cells (RPTEC) and human blood outgrowth endothelial cells (BOEC) on ThinCert™ membranes. Transepithelial electrical resistance (TEER) was measured daily to evaluate the barrier function of the cellular layers. Fluid handling and TEER measurements were performed using a laboratory automation platform that communicates directly with the LIMS. The LES supports laboratory assistants in executing the manual handling steps of the experiments.
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Ruf, M., and M. Adam. "Remote access and laboratory information management systems (LIMS) for single crystal diffraction experiments." Acta Crystallographica Section A Foundations of Crystallography 58, s1 (August 6, 2002): c368. http://dx.doi.org/10.1107/s0108767302099683.

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16

Wray, Bruce R. "Bar code sample identification: the key to laboratory information management systems (LIMS) productivity." TrAC Trends in Analytical Chemistry 7, no. 3 (March 1988): 88–93. http://dx.doi.org/10.1016/0165-9936(88)85027-1.

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17

Teuber, Markus, W. Andreas Koch, Carl Manaster, Stefan Wächter, Jochen Hampe, and Stefan Schreiber. "Improving Quality Control and Workflow Management in High- Throughput Single-Nucleotide Polymorphism Genotyping Environments." JALA: Journal of the Association for Laboratory Automation 10, no. 1 (February 2005): 43–47. http://dx.doi.org/10.1016/j.jala.2004.07.003.

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Single-nucleotide polymorphism (SNP) genotyping is a fundamental tool in the rapidly growing area of complex diseases and pharmacogenomics. SNP patterns that correlate with disease or response to treatment, respectively, are identified using bioinformatic techniques. We present an integrated laboratory information and management system (LIMS) for our high-throughput TaqMan™-based SNP genotyping platform. Three new client tools (ProjectManager, AssayManager, OrderTool) for our LIMS improve quality control and workflow management. The programs support organizing multiple genotyping experiments as projects, managing reagents with barcodes, and automation of assay ordering. The tools are freely available at our homepage.
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18

Goodblatt, Avrum. "Fostering LIMS Development Through Open Standards." Microscopy Today 13, no. 6 (November 2005): 44–45. http://dx.doi.org/10.1017/s1551929500054006.

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At the Microscopy and Microanalysis conference in Honolulu this last August a small meeting was convened to share information and knowledge about implementing LIMS (Laboratory Information Management Systems). The meeting took place at the end of the session on Core Facility Management, through the efforts of Debby Sherman, who is coordinator of the Core Facility Managers Focused Interest Group (http://microscopy.org/MSAUnits/Committees/ Facilities.html). In addition to the meeting, I spoke with several vendors (focusing on those vendors we use here at PathBioResource), as well as others who have made some progress in developing and/or installing LIMS.
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19

Crossett, Don. "Managing data: LIMS implementation in drug discovery." Biochemist 27, no. 6 (December 1, 2005): 27–29. http://dx.doi.org/10.1042/bio02706027.

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It is estimated that it takes approximately $1.25 billion1 and more than 10 years for the drug discovery and development process to be completed and a new drug to be brought to market. During all of this long process, from pre-clinical testing to product development and approval from the FDA (Federal Drug Administration), a wealth of data from a wide variety of bioinformatic tools are collected, integrated and analysed in order to lead to the next big discovery. This is why there are many analysts who believe that an effective Laboratory Information Management System (LIMS) to collect and manage laboratory data can save millions of dollars from the overall associated costs.
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20

Jin, Hee-Jeong, Jeong-Won Lee, and Hwan-Gue Cho. "A Reliable and Distributed LIMS for Efficient Management of the Microarray Experiment Environment." Journal of Integrative Bioinformatics 4, no. 1 (March 1, 2007): 115–31. http://dx.doi.org/10.1515/jib-2007-57.

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Summary A microarray is a principal technology in molecular biology. It generates thousands of expressions of genotypes at once. Typically, a microarray experiment contains many kinds of information, such as gene names, sequences, expression profiles, scanned images, and annotation. So, the organization and analysis of vast amounts of data are required. Microarray LIMS (Laboratory Information Management System) provides data management, search, and basic analysis. Recently, microarray joint researches, such as the skeletal system disease and anti-cancer medicine have been widely conducted. This research requires data sharing among laboratories within the joint research group. In this paper, we introduce a web based microarray LIMS, SMILE (Small and solid MIcroarray Lims for Experimenters), especially for shared data management. The data sharing function of SMILE is based on Friend-to-Friend (F2F), which is based on anonymous P2P (Peer-to-Peer), in which people connect directly with their “friends”. It only allows its friends to exchange data directly using IP addresses or digital signatures you trust. In SMILE, there are two types of friends: “service provider”, which provides data, and “client”, which is provided with data. So, the service provider provides shared data only to its clients. SMILE provides useful functions for microarray experiments, such as variant data management, image analysis, normalization, system management, project schedule management, and shared data management. Moreover, it connections with two systems: ArrayMall for analyzing microarray images and GENAW for constructing a genetic network. SMILE is available on http://neobio.cs.pusan.ac.kr:8080/smile.
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21

Merrer, Robert J. "Information management systems in the undergraduate instrumental analysis laboratory. Part I: Introduction to LIMS." Journal of Chemical Education 62, no. 5 (May 1985): A149. http://dx.doi.org/10.1021/ed062pa149.

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Merrer, Robert J. "Information management systems in the undergraduate instrumental analysis laboratory. Part II: Applications of LIMS." Journal of Chemical Education 62, no. 6 (June 1985): A173. http://dx.doi.org/10.1021/ed062pa173.

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23

Graves, Sean. "An Automated System for Processing Sample Vials Stored at Ultra-Low Temperatures." JALA: Journal of the Association for Laboratory Automation 7, no. 6 (December 2002): 32–35. http://dx.doi.org/10.1016/s1535-5535-04-00223-0.

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The BIOPHILE Individual Vial Retriever (IVR) system has been developed to provide automated access to vials stored at ultra-low temperatures. The IVR performs storage, retrieval, sorting, cataloging, volume estimation (weighing), barcode reading, and re-racking. All racking operations are performed in an environment designed to keep samples frozen at their optimal temperature. Operating temperatures are −80°C, −40°C, −20°C, and room temperature. Laboratory Information Management System (LIMS) integration, automation integration, chain of custody tracking, and FDA 21CFR Part 11 compliance are supported. This article introduces the IVR and provides information on its characteristics.
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Byrnes, Robert W., Eoin Fahy, and Shankar Subramaniam. "A Laboratory Information Management System for High-Throughput Experimental Lipidomics: Minimal Information Required for the Analysis of Lipidomics Experiments (MIALE)." JALA: Journal of the Association for Laboratory Automation 12, no. 4 (August 2007): 230–38. http://dx.doi.org/10.1016/j.jala.2007.04.002.

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Sequencing of the human genome has opened the way and provided the impetus for building a comprehensive picture of a mammalian cell. Significant efforts are underway in the fields of genomics and proteomics to identify all genes and proteins in a given organism. The goal is a complete map of the genes, gene products, and their interaction networks in a functioning cell. The next step in establishing a comprehensive picture of a cell will be to integrate the cell's metabolome with the rapidly developing genomic and proteomic maps. A cell's metabolome, however, is such an enormous and complex entity that characterizing it can only be approached in sections. Our group of laboratories, the LIPID MAPS consortium, has focused on the lipid section of the metabolome. We have implemented a Lipid Metabolites and Pathways Strategy, termed LIPID MAPS, that applies a global integrated approach to the study of lipidomics in cells and tissues. This paper describes key aspects of the design, implementation, and accessibility features of a Laboratory Information Management System (LIMS) which serves the LIPID MAPS consortium. This software serves as a model system for integrating experimental information obtained by laboratories participating in metabolomics studies. (JALA 2007;12:230–8)
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Voegele, C., S. V. Tavtigian, D. de Silva, S. Cuber, A. Thomas, and F. Le Calvez-Kelm. "A Laboratory Information Management System (LIMS) for a high throughput genetic platform aimed at candidate gene mutation screening." Bioinformatics 23, no. 18 (August 20, 2007): 2504–6. http://dx.doi.org/10.1093/bioinformatics/btm365.

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Vullo, S., G. Purpari, G. Chiarenza, M. T. Mercante, A. Guercio, G. Tumino, and P. Colangeli. "A Laboratory Information Management System (LIMS) for animal health: Experiences of the Istituto Zooprofilattico Sperimentale of Sicily (Italy)." International Journal of Infectious Diseases 45 (April 2016): 297. http://dx.doi.org/10.1016/j.ijid.2016.02.654.

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27

Lana-Peixoto, Marco A., Lívia Edwiges Talim, Alessandra C. Faria-Campos, Sérgio V. A. Campos, Cristiane F. Rocha, Lucas A. Hanke, Natália Talim, Paulo Henrique Batista, Carolina R. Araujo, and Rodrigo Kleinpaul. "NMO-DBr: the Brazilian Neuromyelitis Optica Database System." Arquivos de Neuro-Psiquiatria 69, no. 4 (August 2011): 687–92. http://dx.doi.org/10.1590/s0004-282x2011000500021.

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OBJECTIVE: To present the Brazilian Neuromyelitis Optica Database System (NMO-DBr), a database system which collects, stores, retrieves, and analyzes information from patients with NMO and NMO-related disorders. METHOD: NMO-DBr uses Flux, a LIMS (Laboratory Information Management Systems) for data management. We used information from medical records of patients with NMO spectrum disorders, and NMO variants, the latter defined by the presence of neurological symptoms associated with typical lesions on brain magnetic resonance imaging (MRI) or aquaporin-4 antibody seropositivity. RESULTS: NMO-DBr contains data related to patient's identification, symptoms, associated conditions, index events, recurrences, family history, visual and spinal cord evaluation, disability, cerebrospinal fluid and blood tests, MRI, optic coherence tomography, diagnosis and treatment. It guarantees confidentiality, performs cross-checking and statistical analysis. CONCLUSION: NMO-DBr is a tool which guides professionals to take the history, record and analyze information making medical practice more consistent and improving research in the area.
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Goodblatt, Avrum. "Fostering LIMS Development Through Open Standards Part II - Ontologies and Business Process." Microscopy Today 14, no. 1 (January 2006): 46–47. http://dx.doi.org/10.1017/s1551929500055206.

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This is the second in the series of short articles about Laboratory Information Management Systems (LIMS). This installment will focus on two issues - looking at ontologies and at business process design. The goal is to demonstrate how LIMS is really a combination of several capabilities, and that although each capability should be looked at separately, they ultimately must all work together as seamlessly as possible.Before diving in, I would like to thank Dr. Q. C. Yu, the director of our Biomedical Imaging Facility here in Pathology and Laboratory Medicine at Penn http://www.med.upenn.edu/bmcrc/morph/?morph for his assistance, encouragement, and sponsorship of my participation in the Honolulu conference.
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Salinas, Maria, Maite López-Garrigós, Emilio Flores, and Carlos Leiva-Salinas. "Automated Requests for Thyroid-Stimulating Hormone and Ferretin Tests in Young Primary Care Patients with Anorexia as an Intervention to Improve Detection of Underlying Conditions." Laboratory Medicine 50, no. 3 (January 7, 2019): 268–72. http://dx.doi.org/10.1093/labmed/lmy076.

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Abstract Objective To improve clinical laboratory contribution to the treatment of primary care patients with anorexia through automated computerized strategies. Methods We recorded the number of laboratory requests due to anorexia; the demographic data, laboratory values, and presence of pathological values for the applicable patients. In a prospective study, the laboratory information management system (LIMS) automatically added thyroid-stimulating hormone (TSH) and/or ferritin testing when it was not requested by general practitioners for all primary care patients with anorexia who were younger than 16 years. Results A total of 3562 patients underwent laboratory testing due to anorexia, of whom 47% were younger than 16 years. The tests in which the results most frequently were abnormal were hemoglobin, ferritin, and TSH. TSH results were abnormal in 20% of patients younger than 16 years. Through the intervention, we detected 3 low ferritin values and 7 cases of pathological TSH levels. Conclusions The LIMS required TSH and ferritin testing in young patients even when not requested, potentially avoiding the adverse effects of iron deficiency and thyroid disorders on neurological development and cognition in those patients.
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Zimmerman, Matthew, David Cooper, Marcin Cymborowski, Krzysztof Konina, Marek Grabowski, Elizabeth MacLean, and Wladek Minor. "Transforming biomedical and structural data into information and knowledge." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C492. http://dx.doi.org/10.1107/s2053273314095072.

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The LabDB laboratory information management system (LIMS) tracks, organizes and analyzes data from chemical and solution management, protein production, crystallization, diffraction, structure solution, and in vitro biochemical and biophysical experiments. The system is comprised of multiple modules specialized for different tasks, such as the Xtaldb system for crystallization or the hkldb module of the HKL-3000 suite for diffraction data collection and structure solution. The biochemical/biophysical experiments tracked by LabDB include spectrophotometric binding and kinetics, thermal shift binding, isothermal titration calorimetry (ITC) and protein quantitation. These tools associate functional and structural experiments, for example, for selecting likely substrates for co-crystallization and soaking experiments. Whenever possible, the system harvests data with no or minimal user intervention from laboratory hardware. Devices that may connect to or import data into LabDB include crystal observation (Rigaku Minstrel HT and Formulatrix Rock Imager), liquid handling (Formulatrix Rock Maker and Emerald Opti-Matrix Maker), chromatography (GE Healthcare AKTA), quantitation (Caliper LabChip GX II and Bio-Rad Gel Doc EZ), RT-PCR (Applied Biosystems 7900HT and Bio-Rad C1000/CFX96) and ITC (MicroCal iTC-200) systems. LabDB is used by two high-throughput PSI:Biology centers (MCSG and NYSGRC) as well as other major NIH consortia (the Center for Structural Genomics of Infectious Diseases and the Enzyme Function Initiative), and track millions of experiments on tens of thousands of targets.[1] The system also provides extensive data mining and analysis tools for translating raw experimental data into information and knowledge. We present examples of analyses generated by the system useful in designing new experiments.
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Shaban-Nejad, Arash, Olga Ormandjieva, Mohamad Kassab, and Volker Haarslev. "Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory." International Journal of Telemedicine and Applications 2009 (2009): 1–14. http://dx.doi.org/10.1155/2009/917826.

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Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.
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Rodriguez-Borja, Enrique, Macarena Díaz-Gimenez, Arturo Carratala Calvo, Inmaculada Vinyals-Bellido, Africa Corchon-Peyrallo, Ausias Hervas-Romero, and Adela Pozo-Giraldez. "Decision support system through automatic algorithms and electronic request in diagnosis of anaemia for primary care patients." Biochemia medica 31, no. 2 (June 15, 2021): 250–57. http://dx.doi.org/10.11613/bm.2021.020702.

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An appropriate management of anaemia laboratory tests is crucial for a correct diagnosis and treatment. A non-sequential “shotgun” approach (where every anaemia related test is ordered) causes workload and cost increases and could be potentially harmful. We have implemented a Decision Support System through our laboratory information system (LIMS) based on reflexive algorithms and automatic generation of interpretative reports specifically in diagnosis of anaemia for primary care patients. When a request contained an “Anaemia Suspicion Study” profile, more than twenty automatic reflexive rules were activated in our LIMS based upon laboratory results. These rules normally involved the addition of reflexive tests. A final report was automatically generated for each interpretation which was always reviewed for their validity by two staff pathologists. We measured the impact of this system in the ordering of most common anaemia related tests and if a proper treatment was established based on the interpretive report. From all the studies performed, only 12% were positive being “iron deficiency” and “anaemia of chronic disease” the most frequent causes, 62% and 17%, respectively. Proper treatment was established in 88% of these anaemic patients. Total iron, transferrin, ferritin, folate and vitamin B12 demand decreased substantially after implementation representing a cost reduction of 40% only for these five tests. Our system has easily improved patient outcomes, advising on individual clinical cases. We have also noticeably reduced the number of over-requested tests and laboratory costs.
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Kldiashvili, Ekaterine, and Nikoloz Shakulashvili. "Digital Cytology as the Tool for Organization of Cytology Online Quality Assurance Programs." International Journal of Reliable and Quality E-Healthcare 7, no. 1 (January 2018): 31–39. http://dx.doi.org/10.4018/ijrqeh.2018010103.

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The article aims at evaluating the use of telecytology and laboratory information management system (LIMS) as tools for the implementation of online cytology quality assurance programs under the conditions of Georgia. Five hundred gynecological cytology cases (benign – 350; atypical squamous cells of undetermined significance (ASCUS) – 80; low-grade squamous intraepithelial lesion (LSIL) – 35; high-grade squamous intraepithelial lesion (HSIL) - 35) were randomly selected. The randomization has been done by using the Research Randomizer. Digital images were obtained in all cases at a maximum resolution of 2048x1536 pixels. Then, all 500 cases (medical data and images) were uploaded to the LIMS and were labelled “QA”. Diagnosis of glass slides and digital images were made independently in a double-blind manner by three certified cytologists, commencing with the diagnosis of “QA” cases followed by a diagnosis of glass slides four months later. It was found that the diagnoses of “QA” cases correspond with initial diagnoses.
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de Sanctis, Daniele, and Stephanie Monaco. "The MxCuBE2/ISPyB environment for remote data collection at the ESRF." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C786. http://dx.doi.org/10.1107/s2053273314092134.

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MxCuBE, is a beamline control graphical user interface (GUI) for macromolecular crystallography (MX) experiments that was developed by the ESRF and has been in use since 2005. The GUI provides the user with a friendly interface to electronic devices, permitting to carry out experiments in a intuitive environment while benefiting from the increasing automation. Since its release, MxCuBE has become the preferred MX data acquisition software, also installed at other European synchrotron sites [SOLEIL, EMBL@PETRAIII, BESSY and MAXLAB].In September 2013, after intense recoding, experiment design and testing, the ESRF has deployed MxCuBE2 on all the ESRF's MX beamlines. This new generation of GUI is capable of interfacing with a variety of low level control systems. MxCuBE2, written in the Python programming language, has a radical new appearance and provides an updated environment for performing complicated multi-crystal/multi-position MX experiments in a modular, logical and automatic fashion. ISPyB is a Laboratory Information Management System (LIMS) conceived to record experimental parameters and basic reporting of the data obtained. Since 2009 ISPyB has been a collaboration between ESRF and Diamond Light Source (DLS) and the LIMS is now a multi-site, generic system for synchrotron-based (MX) experiments. The current version allows users to track their sample location (to/from & at the synchrotron), facilitates transmission of information from and to other LIMS, records experiment details, and provides the results - including reflection files - of automatic data processing protocols. Indeed as experiments have become more complex and automated ISPyB has become more than just a repository for project histories - it has become a support for rapid decision making during experiments. The combination of these two indispensable tools in every day users life at the European Synchrotron Radiation Facility will be presented and discussed.
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Croft, MG, GC Fraser, and WN Gaul. "Role of the New South Wales Department of Primary Industries' Laboratory Information Management System (LIMS) in the 2007 equine influenza emergency animal disease response." Australian Veterinary Journal 89 (June 29, 2011): 47–49. http://dx.doi.org/10.1111/j.1751-0813.2011.00745.x.

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Carter, Craig N., and Jacqueline L. Smith. "A proposal to leverage high-quality veterinary diagnostic laboratory large data streams for animal health, public health, and One Health." Journal of Veterinary Diagnostic Investigation 33, no. 3 (March 26, 2021): 399–409. http://dx.doi.org/10.1177/10406387211003088.

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Test data generated by ~60 accredited member laboratories of the American Association of Veterinary Laboratory Diagnosticians (AAVLD) is of exceptional quality. These data are captured by 1 of 13 laboratory information management systems (LIMSs) developed specifically for veterinary diagnostic laboratories (VDLs). Beginning ~2000, the National Animal Health Laboratory Network (NAHLN) developed an electronic messaging system for LIMS to automatically send standardized data streams for 14 select agents to a national repository. This messaging enables the U.S. Department of Agriculture to track and respond to high-consequence animal disease outbreaks such as highly pathogenic avian influenza. Because of the lack of standardized data collection in the LIMSs used at VDLs, there is, to date, no means of summarizing VDL large data streams for multi-state and national animal health studies or for providing near-real-time tracking for hundreds of other important animal diseases in the United States that are detected routinely by VDLs. Further, VDLs are the only state and federal resources that can provide early detection and identification of endemic and emerging zoonotic diseases. Zoonotic diseases are estimated to be responsible for 2.5 billion cases of human illness and 2.7 million deaths worldwide every year. The economic and health impact of the SARS-CoV-2 pandemic is self-evident. We review here the history and progress of data management in VDLs and discuss ways of seizing unexplored opportunities to advance data leveraging to better serve animal health, public health, and One Health.
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Дмитриева, Е. Ю., В. А. Терещенко, and А. С. Шляхтун. "Experience and prospects of using the laboratory information system in testing laboratories of municipal water utilities." Vodosnabzhenie i sanitarnaia tehnika, no. 1 (January 18, 2021): 12–20. http://dx.doi.org/10.35776/vst.2021.01.02.

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Задача подтверждения высокого уровня качества проводимых исследований ставит аналитические лаборатории водоканалов перед необходимостью прохождения периодических аттестаций на соответствие требованиям государственных и международных стандартов (обновленный ГОСТ ИСО/МЭК 17025-2019 и др.), предполагающих внедрение в аналитическую практику внутрилабораторного контроля (ВЛК), системы менеджмента качества (СМК), прохождение процедур межлабораторных сличительных испытаний (МСИ). Как следствие, существенно увеличивается нагрузка на персонал лаборатории, снижается эффективность труда инженеров и лаборантов, возрастают затраты на лабораторную деятельность. В качестве пути оптимизации деятельности лаборатории рассматривается использование лабораторных информационных систем (ЛИС, ЛИМС) – программных средств автоматизации бизнес-процессов, позволяющих комплексно решать задачи аккредитованных лабораторий и повышать эффективность их работы просто и прозрачно. Примером таких информационных систем является ЛИС «Химик-Аналитик», уже более 20 лет успешно применяемая в лабораториях водоканалов по всей России. На сегодняшний день ЛИС удовлетворяет практически все потребности аккредитованных лабораторий: внесение результатов анализа (в том числе напрямую с оборудования) и их метрологическая обработка в соответствии с требованиями нормативной документации, формирование отчетных документов, учет товарно-материальных ценностей с возможностью интеграции с бухгалтерскими системами учета, ведение журналов СМК, составление рабочих планов и формирование заданий. Доступ к документам ЛИС и построение градуировочных характеристик возможен через web-сервисы. ЛИС доступна в различных вариантах комплектации, минимальным из которых является программный продукт «ЛИС для ВЛК». The task of confirming the high level of quality of the conducted research places analytical laboratories of water utilities before the need of being certified for compliance with the requirements of the state and international standards (updated GOST ISO/IEC 17025-2019, etc.), involving the introduction of an intralaboratory control (IC), a quality management system (QMS), passing the procedures of interlaboratory comparative tests (ICT). As a result, the workload on the laboratory personnel significantly increases, the efficiency of the work of engineers and laboratory assistants declines, the costs of the laboratory activities increase. The use of laboratory information systems (LIS, LIMS), i. e. software tools for the automation of business processes that provide for the comprehensive solution of the tasks of accredited laboratories is considered as a way to optimize the laboratory's activities; and it is simple and transparent to increase the efficiency of their activities. An example of such information systems is LIS «Khimik-Analitik» that has been successfully cooperating with the laboratories of water utilities throughout Russia for more than 20 years. Today, LIS meets almost all the requirements to the accredited laboratories, i. e. entering the results of analysis (including directly from the equipment) and their metrological processing in accordance with the requirements of the regulatory documents, compiling report documents, accounting of inventory items with possible integration with accounting systems, maintaining QMS journals, drawing up route plans and job setup. The access to LIS documents and development of calibration characteristics is possible through web services. LIS is available in various configuration options, the minimum of which is LIS for IC software product.
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Correia, Damien, Olivia Doppelt-Azeroual, Jean-Baptiste Denis, Mathias Vandenbogaert, and Valérie Caro. "MetaGenSense : A web application for analysis and visualization of high throughput sequencing metagenomic data." F1000Research 4 (April 2, 2015): 86. http://dx.doi.org/10.12688/f1000research.6139.1.

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The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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39

Correia, Damien, Olivia Doppelt-Azeroual, Jean-Baptiste Denis, Mathias Vandenbogaert, and Valérie Caro. "MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data." F1000Research 4 (August 22, 2016): 86. http://dx.doi.org/10.12688/f1000research.6139.2.

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The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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40

Correia, Damien, Olivia Doppelt-Azeroual, Jean-Baptiste Denis, Mathias Vandenbogaert, and Valérie Caro. "MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data." F1000Research 4 (December 1, 2016): 86. http://dx.doi.org/10.12688/f1000research.6139.3.

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The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.
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41

Trevisan, Giovani, Leticia C. M. Linhares, Kent J. Schwartz, Eric R. Burrough, Edison de S. Magalhães, Bret Crim, Poonam Dubey, et al. "Data standardization implementation and applications within and among diagnostic laboratories: integrating and monitoring enteric coronaviruses." Journal of Veterinary Diagnostic Investigation 33, no. 3 (March 19, 2021): 457–68. http://dx.doi.org/10.1177/10406387211002163.

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Every day, thousands of samples from diverse populations of animals are submitted to veterinary diagnostic laboratories (VDLs) for testing. Each VDL has its own laboratory information management system (LIMS), with processes and procedures to capture submission information, perform laboratory tests, define the boundaries of test results (i.e., positive or negative), and report results, in addition to internal business and accounting applications. Enormous quantities of data are accumulated and stored within VDL LIMSs. There is a need for platforms that allow VDLs to exchange and share portions of laboratory data using standardized, reliable, and sustainable information technology processes. Here we report concepts and applications for standardization and aggregation of data from swine submissions to multiple VDLs to detect and monitor porcine enteric coronaviruses by RT-PCR. Oral fluids, feces, and fecal swabs were the specimens submitted most frequently for enteric coronavirus testing. Statistical algorithms were used successfully to scan and monitor the overall and state-specific percentage of positive submissions. Major findings revealed a consistently recurrent seasonal pattern, with the highest percentage of positive submissions detected during December–February for porcine epidemic diarrhea virus, porcine deltacoronavirus, and transmissible gastroenteritis virus (TGEV). After 2014, very few submissions tested positive for TGEV. Monitoring VDL data proactively has the potential to signal and alert stakeholders early of significant changes from expected detection. We demonstrate the importance of, and applications for, data organized and aggregated by using LOINC and SNOMED CTs, as well as the use of customized messaging to allow inter-VDL exchange of information.
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42

Suberi, Radhika S. "Situation analysis of medical laboratories in primary health centres." International Journal Of Community Medicine And Public Health 8, no. 5 (April 27, 2021): 2304. http://dx.doi.org/10.18203/2394-6040.ijcmph20211750.

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Background: This study was conducted with the objective to assess the medical laboratories attached with primary health centres (PHCs) focusing on the current needs, gaps and to understand the utilization pattern of the laboratory services. There are hardly any relevant studies that are known to have investigated the functioning of laboratories attached with PHCs based on quality of service they are providing.Methods: This study was a cross sectional study based on observations and assessment made at 33 randomly selected medical laboratories attached with PHCs in Ahmedabad district, Gujarat. Checklist adapted from National Quality Assurance Standards (NQAS) and Indian Public Health Standards (IPHS) were used as a tool for data collection.Results: Though all the laboratories have been found to be functioning effectively based on the indicators in this study, some of the laboratories were not performing basic important tests like rapid plasma reagin (RPR) (18%) and hepatitis B surface antigen (HbSAg) (21%). None of the laboratories attached to the PHCs under study performed Widal test. There was very low utilization of urinary pregnancy test (UPT) (1.81%) in the first quarter of the year.Conclusions: Although most of the indicators reflect satisfactory performance of the laboratories, there exists certain gaps and needs that are essential in provision of quality laboratory services in the primary level of health care. The laboratory information management system (LIMS) was the major issue in the laboratories.
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43

Albano, Maria S., William Rothman, Chiseko Watanabe, Anna Gora, Andromachi Scaradavou, and Pablo Rubinstein. "Hematopoietic Colony Forming Unit: Development of a High-Throughput CFU Assay Strategy by the Use of High-Resolution Digital Images Stored in a Laboratory Information System." Blood 112, no. 11 (November 16, 2008): 2306. http://dx.doi.org/10.1182/blood.v112.11.2306.2306.

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Abstract Background: Umbilical Cord Blood (CB) is an increasingly accepted graft source for patients lacking related donors. Graft characteristics currently used as determinants of quality and engraftment potential of CB units include the enumeration of Total Nucleated Cell (TNC), CD34+ and Colony Forming Units (CFU). Among those, the 14 day-CFU assay is the only one that determines the functional state as well as the number of hematopoietic progenitor cells. Thus, CFU in pre and post cryopreservation/thawing specimens are strong independent predictors of CB graft engraftment. Traditionally, evaluation of CFU growth is performed by light microscopy (traditional classification), is time consuming, subjective and difficult to standardize. Aims: A) To evaluate whether the incorporation of high-resolution digital imaging and colony staining could make reading the traditional CFU assay objective and readily standardizable. B) To validate the new strategy vs traditional classification. C) To develop a computer based laboratory information management system (LIMS) to support high-throughput CFU assay. Methods and Results: After 14 days of CB culture (CFU assay-Stem Cell Technologies), an image of the 35 mm culture dishes was captured using a high-resolution photographic camera based digital imaging system, which achieves a resolution of 7.6 μM per pixel and thus, allows a clear view of all colonies in the dish with their barcoded IDs. A short one-step staining with MTT (3-[4,5-dimethylthiazol-2yl]-2,5-diphenyltetrazolium bromide) allows an even better definition of CFU-GM/E; CFU-GM and CFU-E by bestowing a specific color on each type (dark purple, purple and red respectively) against a uniformly clear background. A good correlation was observed after comparison of the new strategy against traditional enumeration (R2 linear= 0.95; n= 122 culture dishes evaluated). Low variation was observed after 151 cultures were independently classified and enumerated by three different operators (CV%= 8.9; range 1–27%). Sample plating introduced variation of the CFU assay, in an experiment where nine CB samples were evaluated by multiple plating (Intra-assay CV%= 21.9 %; range 3.4–34.5% and Inter-assay CV%= 23.3%; range 12.6–35%). A computer based laboratory information (LIMS) was developed to store all culture dishes, linked by unique barcoded ID labels to a specific CB unit, and including CB image, incubator location, plating and counting dates, as well as detailed colony enumeration. This system has been used for 5 months in our laboratory and more than 3,000 CB units have been tested in duplicate (average: 30 CB/day). Images of an average of 60 culture dishes and MTT staining can be performed in less than two hours. The specific coloration of CFU colonies allows faster classification and enumeration and thus, permits a more precise analysis of CFU colonies and its relation with CD34+ cell content and post-transplant engraftment. Summary: With this new strategy, CFU can be objectively visualized, differentiated and counted; the digital images can be stored for future review and refined classification. The described system provides computerized information on optical assay parameters and has become an invaluable tool supporting high-throughput implementation. Thus, the combination of high resolution imaging, one-step staining and the traditional CFU assay overcome most technical challenges of the conventional method, supporting standardization and yielding high reproducibility to the assay which can be easily implemented in CB banks where large numbers of samples need to be tested daily.
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44

De Massis, Fabrizio, Carla Ippoliti, Simona Iannetti, Manuela Tittarelli, Sandro Pelini, Daniele Giansante, and Aurora Ciarrocchi. "Canine Leishmaniasis: Serological Results in Private and Kennel Dogs Tested over a Six-Year Period (2009–2014) in Abruzzo and Molise Regions, Italy." Microorganisms 8, no. 12 (December 1, 2020): 1915. http://dx.doi.org/10.3390/microorganisms8121915.

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This paper reports the results of serological tests for the detection of antibodies against Leishmania spp. in Abruzzo and Molise regions from 2009 to 2014, with the aim of evaluating the presence and distribution of canine leishmaniasis. Data were extracted from the Laboratory Information Management System (LIMS) of the Istituto Zooprofilattico Sperimentale of Abruzzo and Molise, and then the dog identification numbers were matched with those stored in the Canine Registries of the two regions to get information about the age of dogs at time of testing. Dogs were considered positive when having an IFAT (Indirect Fluorescent Antibody Test) titer ≥1:80. In total, 41,631 dogs were tested, 85.3% from Abruzzo and 14.7% from Molise. At the provincial level, the percentage of positive dogs ranged from 5.2% (L’Aquila, Abruzzo region) to 21.8% (Campobasso, Molise region). Findings are consistent with the hypothesis that in the coastal areas, the relationships between the host, the vector, and the agent are more favorable for the spreading of CanL, and it seems that densely populated urban internal areas have less favorable conditions. Being a dog hosted in a kennel seems not to be a factor increasing the probability that dogs show positivity, even in long-term sheltering conditions.
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45

Chung, Jo L., Jian Sun, John Sidney, Alessandro Sette, and Bjoern Peters. "IMMUNOCAT—A Data Management System for Epitope Mapping Studies." Journal of Biomedicine and Biotechnology 2010 (2010): 1–8. http://dx.doi.org/10.1155/2010/856842.

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To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established “IMMUNOCAT”, an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.
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Kueffner, Robert, Hui Li, Kakit Cheung, Marc Fink, Zachry Soens, Jinlian Wang, Osman Siddiqui, et al. "VONC: A solution for the clinical assessment of somatic genomic alterations." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e13155-e13155. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e13155.

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e13155 Background: Next generation sequencing (NGS) technology is transforming the diagnosis and treatment of cancer. However, the massive scale of data has overwhelmed pathologists who need streamlined tools to process this data, automate report generation and minimize human errors. Methods: We developed the Variant interpretation station for ONCology, VONC, as an end-to-end solution for moving from NGS whole exome and transcriptome data to actionable clinical reports that support cancer diagnosis, prognosis, and personalized treatment strategies for solid and hematologic malignancies. Results: VONC integrates all steps for moving from raw NGS data, variant calling and LIMS, to comprehensive annotation of variants. The main functional feature of VONC is a transparent process that effectively combines automated and expert curation to identify clinically relevant and actionable driver variants. VONC also enables efficient management of multi-group, -role, -system and -site curation processes. In contrast to current tools, VONC handles all somatic and constitutional genomic alterations including SNV, indel, CNV, fusion, splicing, and gene expression. Key data sources include 1) 350,000 variants for 50 tumor types across 57,000 sequenced cancer patients; 2) variant frequencies estimated from 1.5M cancer patients; 3) expert curated literature evidence from 16,818 papers covering 26,496 alterations spanning 2,448 cancer driver genes; and 4) curated database of FDA-approved drugs and recruiting clinical trials. VONC presents a prioritized list of variants in oncogenes and tumor suppressors through functional (literature-based) and structure-based (hotspots) algorithms. This is coupled to all supporting information necessary for clinical decision making. Curators can quickly screen variant type, QC metrics, and frequency in sequencing cohorts of cancer patients as well as healthy subjects. Within minutes, variants can be triaged and annotated with FDA approved, NCCN guidelines reported, or literature supported therapeutics, including resistance and contraindicated. Conclusions: VONC is a clinically-ready tool with an intuitive end-user interface tailored for the rapid assessment of variants in cancer patients, to facilitate personalized cancer medicine in a high-throughput laboratory.
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Pradella, Marco, Romolo Dorizzi, and Angelo Burlina. "Immunoassay data management and LIMS: a PC-based system in a clinical laboratory." Chemometrics and Intelligent Laboratory Systems 17, no. 2 (November 1992): 187–91. http://dx.doi.org/10.1016/0169-7439(92)90045-h.

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48

Alvarnas, Joseph, Amira Ahmed, Nancy Gonzalez, Eileen Smith, Diana Russom, Larry Couture, Stephen J. Forman, and David DiGiusto. "Purity, Potency and Safety: Quality Management Reports (QMR) as the Basis for An Effective Continuous Process Improvement System in An Academic Gene Therapy Program." Blood 114, no. 22 (November 20, 2009): 1417. http://dx.doi.org/10.1182/blood.v114.22.1417.1417.

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Abstract Abstract 1417 Poster Board I-440 Gene-modified cellular products (GMCP) hold great promise for the management of numerous disease indications but are considered high-risk biological agents and are derived through extremely complex design and manufacturing processes. Thus, a robust Quality Management System (QMS) is essential for safe production of GMCP for clinical investigation. Development of a QMS that ensures compliance with current Good Manufacturing Practices (cGMP) and current Good Tissue Practices (cGTP) is particularly challenging in an academic setting where basic researchers, clinical investigators, regulatory, administrative, facilities and manufacturing personnel are all involved in the realization of a single GMCP. Following an ISO9001-based gap analysis of the Cellular Therapeutics program at the City of Hope, we implemented Quality Management Reports (QMR) as a tool for capturing data related to GMCP manufacturing. The QMR system was used to document and facilitate corrective and preventative actions (CAPA) as required following protocol deviation and/or Out of Specification (OOS) analyses. QMR data is captured in real-time and includes a detailed description of the event, impact analysis, root cause investigation, action plan and effectiveness analysis for resulting interventions. QMRs are documented using the Labware® (Wilmington, DE) Laboratory Information Management System (LIMS) that is available in real-time to authorized participants in GMCP production. A key aspect in the development of this on-line system was creation of links between the QMRs, OOS and CAPA documentation and investigation. The investigation database contains a series of templates: CAPA, SOP deviations, OOS and QMR that are designed to fully capture any events that impact or have the potential to impact quality, safety or efficient realization of a GMCP. The QMR process was applied to 2 manufacturing campaigns: a lentiviral vector-transfected CD34 GMCP for autologous transplantation in patients with AIDS lymphoma and a Master Cell Bank that was created for the treatment of patients with recurrent Glioblastoma Multiforme based upon an oligoclonal allogeneic T-cell product that contained both a chimeric antigen T-cell receptor and a zinc finger disrupted glucocorticoid receptor genomic sequence. Between May 2008-June 2009, 22 QMRs were generated related to product/reagent transfer, reagent quality/storage, equipment malfunction/OOS, product/environmental sterility, biological reagent OOS and Quality Control specifications for product release. Seventeen of 22 QMRs were resolved and closed. The average time to closing a QMR was 82 days (range 4-198 days). QMR findings lead to a revision of the program organizational chart, lead to the development and implementation of a new standard operating procedure (SOP) for Root Cause Analysis (RCA) investigations, development of new forms (GMP Equipment Approval Forms, a Quality Systems Project Proposal Form and Quality Assurance Customer Satisfactions Survey Forms), revisions to the SOP for CAPA and retraining of manufacturing staff as part of the resultant CAPA investigations to prevent repeat occurrences. Based upon QMR findings, 2 multidisciplinary RCAs were performed and resulted in revisions to documentation for CD34-cell selection and a major revision to the use of RODI water and manufacturing flow during GMCP production campaigns. Only 1 of 22 QMR-captured events has recurred (failure of an equipment monitoring system) and no events have re-occurred that might have had an impact upon product quality or safety. User satisfaction surveys performed by QA following the completion of a multidisciplinary RCA investigation indicate that the QMR process was viewed as fair, unbiased and transparent by a majority of the users (86% were either “Extremely Satisfied” or “Satisfied” with the experience). The QMR process is a powerful tool for the safe realization of GMCP and allows for real-time capture and multidisciplinary communication of complex events, including OOS that either individually or in aggregate may impact the purity, potency or safety of manufactured GMCP. These are often events that would not be routinely captured either as part of a batch record or merit CAPA. Because effectiveness analysis is included as part of the QMR process, it provides a key mechanism for continuous process improvement. Disclosures: Alvarnas: Novartis: Speakers Bureau.
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Riswanto, Nyoto Suseno, Partono, Purwiro Harjati, and HA Dedy. "School Laboratory Management Information System." Journal of Physics: Conference Series 1361 (November 2019): 012068. http://dx.doi.org/10.1088/1742-6596/1361/1/012068.

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50

Fushshilat, I., A. Rahmat, Y. Somantri, and E. Haritman. "Laboratory management: digital laboratory information system (DLIS) concept." IOP Conference Series: Materials Science and Engineering 434 (December 3, 2018): 012286. http://dx.doi.org/10.1088/1757-899x/434/1/012286.

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