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In this proof-of-concept study we demonstrate that in a binary system mass can be transferred toward an accreting compact object at an extremely high rate. If the transferred mass is efficiently converted to X-ray luminosity (with disregard of the classical Eddington limit) or if the X-rays are focused into a narrow beam, then binaries can form extreme ultraluminous X-ray (ULX) sources with an X-ray luminosity of . For example, Lasota and King argued that the brightest known ULX (HLX-1) is a regular binary system with a rather low-mass compact object (a stellar-origin black hole (BH) or a neutron star (NS)). The predicted formation efficiencies and lifetimes of binaries with the very high mass transfer rates are large enough to explain all observed systems with extreme X-ray luminosities. These systems are not only limited to binaries with stellar-origin BH accretors. Notably, we have also identified such objects with NSs. Typically, a BH is fed by a massive () Hertzsprung gap donor with Roche lobe overflow (RLOF) rate of ). For NS systems the typical donors are evolved low-mass () helium stars with RLOF rate of . Our study does not prove that any particular extreme ULX is a regular binary system, but it demonstrates that any ULX, including the most luminous ones, may potentially be a short-lived phase in the life of a binary star. [ABSTRACT FROM AUTHOR]

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.)

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills., Competing Interests: The authors have declared that no competing interests exist.

Background: Emerging reports indicate a high incidence of venous thromboembolism in patients hospitalised for SARS-CoV-2 pneumonia during the spring 2020 pandemic. The pronounced pulmonary and systemic inflammatory responses observed in these patients may contribute to a transient hypercoagulable state. In this setting, pulmonary embolism may cause further respiratory distress and clinical deterioration., Case Presentation: We describe the clinical course of three patients admitted with SARS-CoV-2 infection and respiratory distress, where pulmonary embolism was detected during the course of the hospitalisation. Two of the cases occurred despite early institution of standard dosage of low molecular weight heparin thromboprophylaxis, and in one case, pulmonary embolism was diagnosed during the convalescent phase of an otherwise benign COVID-19 disease course., Interpretation: These cases highlight the importance of awareness of the potentially increased incidence of venous thromboembolism in COVID-19 disease. Further research is required to establish appropriate clinical management guidelines for prevention of thromboembolic complications in COVID-19.

PortEco (http://porteco.org) aims to collect, curate and provide data and analysis tools to support basic biological research in Escherichia coli (and eventually other bacterial systems). PortEco is implemented as a 'virtual' model organism database that provides a single unified interface to the user, while integrating information from a variety of sources. The main focus of PortEco is to enable broad use of the growing number of high-throughput experiments available for E. coli, and to leverage community annotation through the EcoliWiki and GONUTS systems. Currently, PortEco includes curated data from hundreds of genome-wide RNA expression studies, from high-throughput phenotyping of single-gene knockouts under hundreds of annotated conditions, from chromatin immunoprecipitation experiments for tens of different DNA-binding factors and from ribosome profiling experiments that yield insights into protein expression. Conditions have been annotated with a consistent vocabulary, and data have been consistently normalized to enable users to find, compare and interpret relevant experiments. PortEco includes tools for data analysis, including clustering, enrichment analysis and exploration via genome browsers. PortEco search and data analysis tools are extensively linked to the curated gene, metabolic pathway and regulation content at its sister site, EcoCyc.