The value of open-source clinical science in pandemic response: lessons from ISARIC.
Ontology highlight
ABSTRACT:
SUBMITTER: ISARIC Clinical Characterisation Group
PROVIDER: S-EPMC8489876 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Despite the increased access to scientific publications and data as a result of open science initiatives, access to scientific tools remains limited. Uncrewed aerial vehicles (UAVs, or drones) can be a powerful tool for research in disciplines such as agriculture and environmental sciences, but their use in research is currently dominated by proprietary, closed source tools. The objective of this work was to collect, curate, organize and test a set of open source tools for aerial data capture for research purposes. The Open Science Drone Toolkit was built through a collaborative and iterative process by more than 100 people in five countries, and comprises an open-hardware autonomous drone and off-the-shelf hardware, open-source software, and guides and protocols that enable the user to perform all the necessary tasks to obtain aerial data. Data obtained with this toolkit over a wheat field was compared to data from satellite imagery and a commercial hand-held sensor, finding a high correlation for both instruments. Our results demonstrate the possibility of capturing research-grade aerial data using affordable, accessible, and customizable open source software and hardware, and using open workflows.
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Project description:Chemical matter is needed to target the divergent biology associated with the different life cycle stages of Plasmodium. Here, we report the parallel de novo screening of the Medicines for Malaria Venture (MMV) Pandemic Response Box against Plasmodium asexual and liver stage parasites, stage IV/V gametocytes, gametes, oocysts and as endectocides. Unique chemotypes were identified with both multistage activity or stage-specific activity, including structurally diverse gametocyte-targeted compounds with potent transmission-blocking activity, such as the JmjC inhibitor ML324 and the antitubercular clinical candidate SQ109. Mechanistic investigations prove that ML324 prevents histone demethylation, resulting in aberrant gene expression and death in gametocytes. Moreover, the selection of parasites resistant to SQ109 implicates the druggable V-type H+-ATPase for the reduced sensitivity. Our data therefore provides an expansive dataset of compounds that could be redirected for antimalarial development and also point towards proteins that can be targeted in multiple parasite life cycle stages.
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Project description:BackgroundThe increasing access to autonomously-operated technologies offer vast opportunities to sample large volumes of biological data. However, these technologies also impose novel demands on ecologists who need to apply tools for data management and processing that are efficient, publicly available and easy to use. Such tools are starting to be developed for a wider community and here we present an approach to combine essential analytical functions for analysing large volumes of image data in marine ecological research.New informationThis paper describes the Koster Seafloor Observatory, an open-source approach to analysing large amounts of subsea movie data for marine ecological research. The approach incorporates three distinct modules to: manage and archive the subsea movies, involve citizen scientists to accurately classify the footage and, finally, train and test machine learning algorithms for detection of biological objects. This modular approach is based on open-source code and allows researchers to customise and further develop the presented functionalities to various types of data and questions related to analysis of marine imagery. We tested our approach for monitoring cold water corals in a Marine Protected Area in Sweden using videos from remotely-operated vehicles (ROVs). Our study resulted in a machine learning model with an adequate performance, which was entirely trained with classifications provided by citizen scientists. We illustrate the application of machine learning models for automated inventories and monitoring of cold water corals. Our approach shows how citizen science can be used to effectively extract occurrence and abundance data for key ecological species and habitats from underwater footage. We conclude that the combination of open-source tools, citizen science systems, machine learning and high performance computational resources are key to successfully analyse large amounts of underwater imagery in the future.
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Project description:PurposeThe global coronavirus disease 2019 (COVID-19) pandemic and the search for ways in which to provide the best available care have created unprecedented times in terms of rapidly evolving reports of available treatment options. The primary objective of our analysis was to categorize online, open-source guidance to determine how US institutions approached their recommendations for management of patients with COVID-19 in the early weeks of the pandemic.MethodsA search for open-source, online institutional guidelines for the treatment of COVID-19 was conducted using predefined criteria. The search was limited to the United States and conducted from April 12 through 14, 2020, and again on April 22, 2020. Searches were conducted at 2 points in time in order to identify changes in treatment recommendations due to evolving literature or institutional experience. Treatment recommendations, including guidance on antiviral therapy, corticosteroid and interleukin-6 inhibitor use, and nutritional supplementation were compared.ResultsOf the 105 institutions that met initial screening criteria, 14 institutions (13.3%) had online COVID-19 guidance available. Supportive care and clinical trial enrollment were the primary recommendations in all evaluated guidance. Recommendations to consider antimicrobial and adjunctive therapy varied. Eighty-six percent of guidelines contained recommendations for use, or consideration of use, of hydroxychloroquine. Guidance from 2 institutions mentioned use of hydroxychloroquine and azithromycin in combination. Of the 13 institutions listing hydroxychloroquine dosing recommendations, 62% recommended maintenance dosing of 200 mg twice daily. Infectious diseases or other specialty consultation was required by 89% of institutions using interleukin-6 inhibitors for COVID-19 management.ConclusionOverall, the analysis revealed variability in treatment or supplemental pharmacologic therapy for the management of COVID-19.
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