Patient ethnicity and three psychiatric intensive care units compared: the Tompkins Acute Ward Study

Background: Psychiatric Care Units provide care to disturbed patients in a context of higher security and staffing levels. Although such units are numerous, few systematic comparisons have been made, and there are indications that ethnic minority groups may be over-represented. Aim: To compare the rates of adverse incidents and patterns of usage of three Psychiatric Intensive Care Units. Method: The study used a triangulation or multi-method design, bringing together data from official statistics, local audit and interviews conducted with staff. Results: Intensive care patients were more likely to be young, male, and suffering a psychotic disorder, as compared to general acute ward patients. Caribbean patients were twice as likely, and Asian patients half as likely, to receive intensive care (age, gender and diagnosis controlled). There were large differences in service levels, staffing, team functioning and adverse incidents between the three units. Various aspects of physical security were important in preventing absconds. Conclusions: More evaluative research is required in order to define effective service levels, and to explore the nature of the interaction between ethnicity and inpatient care provision during acute illness

The Gene Ontology knowledgebase in 2023

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

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations

The Gene Ontology knowledgebase in 2023

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

Gut fermentation syndrome: A systematic review of case reports

BACKGROUND: The gut fermentation syndrome (GFS), also known as the endogenous alcohol fermentation syndrome or auto brewery syndrome, is a rare and underdiagnosed medical condition where consumed carbohydrates are converted to alcohol by the microbiota in the gastrointestinal or urinary tract. The symptoms of GFS can have severe impact on patients' wellbeing and can have social and legal consequences. Unfortunately, not much is reported about GFS. The aim of this systematic review was to assess the evidence for GFS, causal micro‐organisms, diagnostics, and possible treatments. METHODS: A protocol was developed prior to initiation of the systematic review (PROSPERO 207182). We performed a literature search for clinical studies on 1 September 2020 using PubMed and Embase. We included all clinical studies, including case reports that described the GFS. RESULTS: In total, 17 case reports were included, consisting of 20 patients diagnosed with GFS. The species that caused the GFS included Klebsiella pneumoniae, Candida albicans, C. glabrata, Saccharomyces cerevisiae, C. intermedia, C. parapsilosis, and C. kefyr. CONCLUSIONS: GFS is a rare but underdiagnosed disease in daily practice. The disease is mostly reported by Saccharomyces and Candida genera, and some cases were previously treated with antibiotics. Studies in Nonalcoholic Fatty Liver disease suggest a bacterial origin of endogenous alcohol‐production, which might also be causal micro‐organisms in GFS. Current treatments for GFS include antibiotics, antifungal medication, low carbohydrate diet, and probiotics. There might be a potential role of fecal microbiota transplant in the treatment of GFS

6th International Conference on Disaster Management and Human Health Risk: Reducing Risk, Improving Outcomes Disaster Management 2019

6th International Conference on Disaster Management and Human Health Risk: Reducing Risk, Improving Outcome