9 results on '"M. Quinton"'
Search Results
2. WormBase 2024: status and transitioning to Alliance infrastructure.
- Author
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Sternberg PW, Van Auken K, Wang Q, Wright A, Yook K, Zarowiecki M, Arnaboldi V, Becerra A, Brown S, Cain S, Chan J, Chen WJ, Cho J, Davis P, Diamantakis S, Dyer S, Grigoriadis D, Grove CA, Harris T, Howe K, Kishore R, Lee R, Longden I, Luypaert M, Müller HM, Nuin P, Quinton-Tulloch M, Raciti D, Schedl T, Schindelman G, and Stein L
- Subjects
- Animals, Databases, Genetic, Genome, Helminth, Genomics methods, Caenorhabditis elegans genetics
- Abstract
WormBase has been the major repository and knowledgebase of information about the genome and genetics of Caenorhabditis elegans and other nematodes of experimental interest for over 2 decades. We have 3 goals: to keep current with the fast-paced C. elegans research, to provide better integration with other resources, and to be sustainable. Here, we discuss the current state of WormBase as well as progress and plans for moving core WormBase infrastructure to the Alliance of Genome Resources (the Alliance). As an Alliance member, WormBase will continue to interact with the C. elegans community, develop new features as needed, and curate key information from the literature and large-scale projects., Competing Interests: Conflicts of interest: The authors declare no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)
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- 2024
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3. Quality control data management with unity real-time in molecular virology.
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Quinton M, Newton DW, Neil B, Mitchell S, and Mostafa HH
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- Humans, Data Management, Herpesvirus 4, Human, Quality Control, Laboratories, Epstein-Barr Virus Infections
- Abstract
Introduction: Quality control (QC) is one component of an overarching quality management system (QMS) that aims at assuring laboratory quality and patient safety. QC data must be acceptable prior to reporting patients' results. Traditionally, QC statistics, records, and corrective actions were tracked at the Johns Hopkins Molecular Virology Laboratory using Microsoft Excel. Unity Real-Time (UnityRT), a QMS software (Bio-Rad Laboratories), which captures and analyzes QC data by instrument and control lot per assay, was implemented and its impact on the workflow was evaluated. The clinical utility of real-time QC monitoring using UnityRT is highlighted with a case of subtle QC trending of HIV-1 quantitative control results., Methods: A comprehensive workflow analysis was performed, with a focus on Epstein Barr Virus (EBV) and BKV quantitative viral load testing (Roche cobas 6800). The number of QC steps and time to complete each step were assessed before and after implementing UnityRT., Results: Our assessment of monthly QC data review revealed a total of 10 steps over 57 min when using Microsoft Excel, versus 6 steps over 11 min when using UnityRT. HIV-1 QC monitoring revealed subtle trending of the low positive control above the mean from November to December 2022, correlating with a change in the reagent kit lot. This associated with a shift in patients' results from positives below the lower limit of quantification to positives between 20 and 100 copies/mL., Conclusions: UnityRT consolidated QC analyses, monitoring, and tracking corrective actions. UnityRT was associated with significant time savings, which along with the interfaced feature of the QC capture and data analysis, have improved the workflow and reduced the risk of laboratory errors. The HIV-1 case revealed the value of the real-time monitoring of QC., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: HHM reports research collaborations with Bio-Rad, Qiagen, and Hologic, received honoraria from BD diagnostics and Bio-Rad, and serves on the advisory board for Seegene. BN is an employee of Bio-Rad Laboratories. At the time of the study, DN was an employee of Bio-Rad Laboratories., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
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- 2024
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4. A highly sensitive and quantitative assay for dystrophin protein using Single Molecule Count Technology.
- Author
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Ishii MN, Quinton M, and Kamiguchi H
- Subjects
- Humans, Reproducibility of Results, Muscles, Technology, Dystrophin genetics, Dystrophin metabolism, Muscular Dystrophy, Duchenne genetics
- Abstract
Duchenne muscular dystrophy (DMD) is a genetic disease characterized by progressive muscle loss caused by mutations in dystrophin, resulting in decreased dystrophin levels. Dystrophin protein expression is a biomarker used to evaluate treatments that restore patient dystrophin levels. Currently, a semiquantitative assay using western blotting, which normalizes dystrophin expression to that of a control population, is used for regulatory filing. However, the current methods are limited in terms of sensitivity, quantification, and reproducibility. To address this, a highly sensitive and quantitative sandwich immune assay using Single Molecule Counting technology was established, with recombinant dystrophin protein as the calibrator. Capture and detection antibodies were selected to detect full-length dystrophin. Using this optimized assay, dystrophin levels in muscle samples from Myotonic Dystrophy (n = 9) and DMD (n = 8) subjects were 93.2 ± 31.9 (range: 49.4-145.3) and 14.5 ± 6.8 (range: 6.18-22.6) fmol/total protein mg, respectively. The lowest concentration of dystrophin measured in the DMD samples was 5 times higher than that in the lower limit of quantitation, a level not detected by western blotting. These data indicate that this assay accurately and sensitively measured dystrophin protein and may be useful in clinical trials assessing dystrophin restoration therapies., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest associated with this manuscript. The authors have no conflicts of interest directly relevant to the content of this article., (Copyright © 2023 Elsevier B.V. All rights reserved.)
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- 2023
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5. Urine titin as a novel biomarker for Duchenne muscular dystrophy.
- Author
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Ishii MN, Nakashima M, Kamiguchi H, Zach N, Kuboki R, Baba R, Hirakawa T, Suzuki K, and Quinton M
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- Mice, Animals, Dystrophin genetics, Mice, Inbred mdx, Connectin urine, Muscle, Skeletal metabolism, Biomarkers metabolism, Disease Models, Animal, Protein Kinases metabolism, Muscular Dystrophy, Duchenne genetics
- Abstract
Duchenne muscular dystrophy (DMD) is the most severe form of muscular dystrophy that is caused by lack of dystrophin, a critical structural protein in skeletal muscle. DMD treatments, and quantitative biomarkers to assess the efficacy of potential treatments, are urgently needed. Previous evidence has shown that titin, a muscle cell protein, is increased in the urine of patients with DMD, suggesting its usefulness as a DMD biomarker. Here, we demonstrated that the elevated titin in urine is directly associated with the lack of dystrophin and urine titin responses to drug treatment. We performed a drug intervention study using mdx mice, a DMD mouse model. We showed that mdx mice, which lack dystrophin due to a mutation in exon 23 of the Dmd gene, have elevated urine titin. Treatment with an exon skipper that targets exon 23 rescued muscle dystrophin level and dramatically decreased urine titin in mdx mice and correlates with dystrophin expression. We also demonstrated that titin levels were significantly increased in the urine of patients with DMD. This suggests that elevated urine titin level might be a hallmark of DMD and a useful pharmacodynamic marker for therapies designed to restore dystrophin levels., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest associated with this manuscript. The authors have no conflicts of interest directly relevant to the content of this article., (Copyright © 2023 Elsevier B.V. All rights reserved.)
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- 2023
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6. Malignant transformation of mature cystic teratoma of the ovary.
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Atwi D, Kamal M, Quinton M, and Hassell LA
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- Female, Humans, Cell Transformation, Neoplastic pathology, Biomarkers, Tumor, Teratoma diagnosis, Teratoma therapy, Dermoid Cyst, Ovarian Neoplasms diagnosis, Ovarian Neoplasms therapy, Ovarian Neoplasms metabolism
- Abstract
Mature cystic teratoma is the most common ovarian germ cell neoplasm. Malignant transformation is a rare occurrence, accounting for 1.5%-2% of cases. Malignant changes can arise from any constituent tissue of a teratoma; however, squamous cell carcinoma is the most common histologic type seen, followed by adenocarcinoma and sarcoma respectively. Tumor marker concentration levels, age, and the tumor maximum diameter are predictive indicators for malignant transformation. Proper diagnosis includes recognizing the possibility of malignant transformation versus excluding other differential options, such as metastasis. Primary cytoreductive surgery, adjuvant chemotherapy, and radiotherapy are the current treatment methods. The aim of the review is to discuss the clinical and pathologic features of malignant transformation within mature cystic teratomas, while reviewing the reported malignant types, differential diagnoses, and treatment options. Data sources include review of pertinent peer-reviewed literature on malignant transformation of mature cystic teratoma and cases seen in authors' institutional practice. Mature cystic teratomas are a commonly encountered benign ovarian tumor. However, the possibility of malignant transformation should remain in consideration, especially with given clinical or pathologic features: increased patient age, tumor size, or tumor marker levels. Thorough sampling of solid tumor foci can help identify malignant components. Awareness and proper diagnosis, along with early detection and clinical management, shows improved patient outcomes., (© 2022 Japan Society of Obstetrics and Gynecology.)
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- 2022
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7. Evaluation of the respiratory NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage and Alinity m Resp-4-Plex assays.
- Author
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Quinton M, Geahr M, Gluck L, Jarrett J, and Mostafa HH
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- Humans, Influenza B virus, Nasopharynx, Respiratory Syncytial Viruses, SARS-CoV-2, Sensitivity and Specificity, COVID-19 diagnosis, Influenza, Human diagnosis, Respiratory Syncytial Virus Infections diagnosis
- Abstract
Background: December 2021 witnessed an unprecedented increase in SARS-CoV-2 infections in addition to the circulation of influenza A and respiratory syncytial viruses (RSV). Due to increased testing demands for SARS-CoV-2, influenza, and RSV associated with the overall increase in symptomatic respiratory infections, there is an urgent need for multiplex, automated, and high throughput assays in the diagnostic laboratories., Methods: We compared the performance of the NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage and the Alinity m Resp-4-Plex to the standard of care influenza A, B, RSV, and SARS-CoV-2 assays used at the Johns Hopkins Microbiology Laboratory. A total of 181 remnant nasopharyngeal swab (NPS) specimens positive for influenza A (n = 29), influenza B (n = 34), RSV (n = 40), SARS-CoV-2 (n = 33), influenza A/RSV (n = 1), and negatives (n = 44) were tested by either or both assays., Results: Both the NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage and the Alinity m Resp-4-Plex assays showed 100% total agreement for all the tested analytes. For samples with available cycle threshold (Ct) values, comparable ranges were noted for all targets between the two assays and to the standard of care Ct values as well., Conclusion: The NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage and the Alinity m Resp-4-Plex assays showed high sensitivity and accuracy for all the analytes included in both tests. Implementing these assays will assist the diagnostic laboratories with the surge of testing during the 2021-2022 influenza season., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2022
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8. WormBase in 2022-data, processes, and tools for analyzing Caenorhabditis elegans.
- Author
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Davis P, Zarowiecki M, Arnaboldi V, Becerra A, Cain S, Chan J, Chen WJ, Cho J, da Veiga Beltrame E, Diamantakis S, Gao S, Grigoriadis D, Grove CA, Harris TW, Kishore R, Le T, Lee RYN, Luypaert M, Müller HM, Nakamura C, Nuin P, Paulini M, Quinton-Tulloch M, Raciti D, Rodgers FH, Russell M, Schindelman G, Singh A, Stickland T, Van Auken K, Wang Q, Williams G, Wright AJ, Yook K, Berriman M, Howe KL, Schedl T, Stein L, and Sternberg PW
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- Animals, Caenorhabditis elegans genetics, Databases, Genetic, Genome, Genomics, Humans, Caenorhabditis genetics, Nematoda genetics
- Abstract
WormBase (www.wormbase.org) is the central repository for the genetics and genomics of the nematode Caenorhabditis elegans. We provide the research community with data and tools to facilitate the use of C. elegans and related nematodes as model organisms for studying human health, development, and many aspects of fundamental biology. Throughout our 22-year history, we have continued to evolve to reflect progress and innovation in the science and technologies involved in the study of C. elegans. We strive to incorporate new data types and richer data sets, and to provide integrated displays and services that avail the knowledge generated by the published nematode genetics literature. Here, we provide a broad overview of the current state of WormBase in terms of data type, curation workflows, analysis, and tools, including exciting new advances for analysis of single-cell data, text mining and visualization, and the new community collaboration forum. Concurrently, we continue the integration and harmonization of infrastructure, processes, and tools with the Alliance of Genome Resources, of which WormBase is a founding member., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)
- Published
- 2022
- Full Text
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9. Ensembl Genomes 2022: an expanding genome resource for non-vertebrates.
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Yates AD, Allen J, Amode RM, Azov AG, Barba M, Becerra A, Bhai J, Campbell LI, Carbajo Martinez M, Chakiachvili M, Chougule K, Christensen M, Contreras-Moreira B, Cuzick A, Da Rin Fioretto L, Davis P, De Silva NH, Diamantakis S, Dyer S, Elser J, Filippi CV, Gall A, Grigoriadis D, Guijarro-Clarke C, Gupta P, Hammond-Kosack KE, Howe KL, Jaiswal P, Kaikala V, Kumar V, Kumari S, Langridge N, Le T, Luypaert M, Maslen GL, Maurel T, Moore B, Muffato M, Mushtaq A, Naamati G, Naithani S, Olson A, Parker A, Paulini M, Pedro H, Perry E, Preece J, Quinton-Tulloch M, Rodgers F, Rosello M, Ruffier M, Seager J, Sitnik V, Szpak M, Tate J, Tello-Ruiz MK, Trevanion SJ, Urban M, Ware D, Wei S, Williams G, Winterbottom A, Zarowiecki M, Finn RD, and Flicek P
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- Animals, Computational Biology, Genome, Bacterial genetics, Genome, Fungal genetics, Genome, Plant genetics, Plants classification, Plants genetics, Vertebrates classification, Vertebrates genetics, Databases, Genetic, Genomics, Internet, Software
- Abstract
Ensembl Genomes (https://www.ensemblgenomes.org) provides access to non-vertebrate genomes and analysis complementing vertebrate resources developed by the Ensembl project (https://www.ensembl.org). The two resources collectively present genome annotation through a consistent set of interfaces spanning the tree of life presenting genome sequence, annotation, variation, transcriptomic data and comparative analysis. Here, we present our largest increase in plant, metazoan and fungal genomes since the project's inception creating one of the world's most comprehensive genomic resources and describe our efforts to reduce genome redundancy in our Bacteria portal. We detail our new efforts in gene annotation, our emerging support for pangenome analysis, our efforts to accelerate data dissemination through the Ensembl Rapid Release resource and our new AlphaFold visualization. Finally, we present details of our future plans including updates on our integration with Ensembl, and how we plan to improve our support for the microbial research community. Software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license). Data updates are synchronised with Ensembl's release cycle., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2022
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