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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.

IntroductionDouble C2-like domain beta (DOC2B) is a vesicle priming protein critical for glucose-stimulated insulin secretion in β-cells. Individuals with type 1 diabetes (T1D) have lower levels of DOC2B in their residual functional β-cell mass and platelets, a phenotype also observed in a mouse model of T1D. Thus, DOC2B levels could provide important information on β-cell dys(function).ObjectiveOur objective was to evaluate the DOC2B secretome of β-cells. In addition to soluble extracellular protein, we assessed DOC2B localized within membrane-delimited nanoparticles – extracellular vesicles (EVs). Moreover, in rat clonal β-cells, we probed domains required for DOC2B sorting into EVs.MethodUsing Single Extracellular VEsicle Nanoscopy, we quantified EVs derived from clonal β-cells (human EndoC-βH1, rat INS-1 832/13, and mouse MIN6); two other cell types known to regulate glucose homeostasis and functionally utilize DOC2B (skeletal muscle rat myotube L6-GLUT4myc and human neuronal-like SH-SY5Y cells); and human islets sourced from individuals with no diabetes (ND). EVs derived from ND human plasma, ND human islets, and cell lines were isolated with either size exclusion chromatography or differential centrifugation. Isolated EVs were comprehensively characterized using dotblots, transmission electron microscopy, nanoparticle tracking analysis, and immunoblotting.ResultsDOC2B was present within EVs derived from ND human plasma, ND human islets, and INS-1 832/13 β-cells. Compared to neuronal-like SH-SY5Y cells and L6-GLUT4myc myotubes, clonal β-cells (EndoC-βH1, INS-1 832/13, and MIN6) produced significantly more EVs. DOC2B levels in EVs (over whole cell lysates) were higher in INS-1 832/13 β-cells compared to L6-GLUT4myc myotubes; SH-SY5Y neuronal-like cells did not release appreciable DOC2B. Mechanistically, we show that DOC2B was localized to the EV lumen; the tandem C2 domains were sufficient to confer sorting to INS-1 832/13 β-cell EVs.DiscussionClonal β-cells and ND human islets produce abundant EVs. In cell culture, appreciable DOC2B can be packaged into EVs, and a small fraction is excreted as a soluble protein. While DOC2B-laden EVs and soluble protein are present in ND plasma, further studies will be necessary to determine if DOC2B originating from β-cells significantly contributes to the plasma secretome.

Following state legislation mandating corequisite support in lieu of remedial prerequisites for underprepared students, this article tells the story of a specific corequisite program piloted in South Texas. Our model transformed certain sections of our institution's first-year seminar into corequisite courses, which were paired with required gateway classes. We argue, this model helped to extend existing networks of student support beyond classrooms and beyond advising.

Abstract Introduction Asthma is characterized by preventable morbidity, cost, and inequity. We sought to build an Asthma Learning Health System (ALHS) to coordinate regional pediatric asthma improvement activities. Methods We generated quantitative and qualitative insights pertinent to a better, more equitable care delivery system. We used electronic health record data to calculate asthma hospitalization rates for youth in our region. We completed an “environmental scan” to catalog the breadth of asthma‐related efforts occurring in our children's hospital and across the region. We supplemented the scan with group‐level assessments and focus groups with parents, clinicians, and community partners. We used insights from this descriptive epidemiology to inform the definition of shared aims, drivers, measures, and prototype interventions. Results Greater Cincinnati's youth are hospitalized for asthma at a rate three times greater than the U.S. average. Black youth are hospitalized at a rate five times greater than non‐Black youth. Certain neighborhoods bear the disproportionate burden of asthma morbidity. Across Cincinnati, there are many asthma‐relevant activities that seek to confront this morbidity; however, efforts are largely disconnected. Qualitative insights highlighted the importance of cross‐sector coordination, evidence‐based acute and preventive care, healthy homes and neighborhoods, and accountability. These insights also led to a shared, regional aim: to equitably reduce asthma‐related hospitalizations. Early interventions have included population‐level pattern recognition, multidisciplinary asthma action huddles, and enhanced social needs screening and response. Conclusion Learning health system methods are uniquely suited to asthma's complexity. Our nascent ALHS provides a scaffold atop which we can pursue better, more equitable regional asthma outcomes.

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.

Suppressing cellular signal transducers of transcription 2 (STAT2) is a common strategy that viruses use to establish infections, yet the detailed mechanism remains elusive, owing to a lack of structural information about the viral-cellular complex involved. Here, we report the cryo-EM and crystal structures of human STAT2 (hSTAT2) in complex with the non-structural protein 5 (NS5) of Zika virus (ZIKV) and dengue virus (DENV), revealing two-pronged interactions between NS5 and hSTAT2. First, the NS5 methyltransferase and RNA-dependent RNA polymerase (RdRP) domains form a conserved interdomain cleft harboring the coiled-coil domain of hSTAT2, thus preventing association of hSTAT2 with interferon regulatory factor 9. Second, the NS5 RdRP domain also binds the amino-terminal domain of hSTAT2. Disruption of these ZIKV NS5-hSTAT2 interactions compromised NS5-mediated hSTAT2 degradation and interferon suppression, and viral infection under interferon-competent conditions. Taken together, these results clarify the mechanism underlying the functional antagonism of STAT2 by both ZIKV and DENV.

Abstract Introduction A learning health network is a type of learning health system in which stakeholders use network organization to improve health and health care. Building on existing resources in the cystic fibrosis (CF) community, the Cystic Fibrosis Learning Network (CFLN) was designed to improve medical outcomes and quality of life through an intentional focus on achieving reliable evidence‐based chronic care delivery and creating a system for data‐driven collaborative learning. Methods We describe the development and growth of the CFLN considering six domains of a Network Maturity Grid: system leadership; governance and policy management; quality improvement (QI); engagement and community building; data and analytics; and research. We illustrate the impact of the CFLN experience on chronic care processes and indicators of collaborative infrastructure. Results The CFLN represents 36 accredited care centers in the CF Foundation Care Center Network caring for over 6300 patients. Of 6779 patient clinical care visits/quarter, 77% are entered into the CF Foundation Patient Registry within 30 days, providing timely means to track outcomes. Collaborative visit planning is occurring in 93% of clinical care visits to share agenda setting with patients and families. Almost all CFLN teams (94%, n = 34) have a patient/family partner (PFP), and 74% of PFPs indicate they are actively participating, taking ownership of, or leading QI initiatives with the interdisciplinary care team. In 2022, 97% of centers reported completing 1–13 improvement cycles per month, and 82% contributed to monthly QI progress reports to share learning. Conclusion The CFLN is a maturing, collaborative infrastructure. CFLN centers practice at an advanced level of coproduction. The CFLN fosters interdisciplinary and PFP leadership and the performance of consistent data‐driven improvement cycles. CFLN centers are positioned to respond to rapid changes in evidence‐based care and advance the practice of QI and implementation science on a broader scale.

Summary: Male mice lacking the androgen receptor (AR) in pancreatic β cells exhibit blunted glucose-stimulated insulin secretion (GSIS), leading to hyperglycemia. Testosterone activates an extranuclear AR in β cells to amplify glucagon-like peptide-1 (GLP-1) insulinotropic action. Here, we examined the architecture of AR targets that regulate GLP-1 insulinotropic action in male β cells. Testosterone cooperates with GLP-1 to enhance cAMP production at the plasma membrane and endosomes via: (1) increased mitochondrial production of CO2, activating the HCO3−-sensitive soluble adenylate cyclase; and (2) increased Gαs recruitment to GLP-1 receptor and AR complexes, activating transmembrane adenylate cyclase. Additionally, testosterone enhances GSIS in human islets via a focal adhesion kinase/SRC/phosphatidylinositol 3-kinase/mammalian target of rapamycin complex 2 actin remodeling cascade. We describe the testosterone-stimulated AR interactome, transcriptome, proteome, and metabolome that contribute to these effects. This study identifies AR genomic and non-genomic actions that enhance GLP-1-stimulated insulin exocytosis in male β cells.

Type 2 diabetes (T2D) is a heterogenous disease, and conventionally, peripheral insulin resistance (IR) was thought to precede islet β-cell dysfunction, promoting progression from prediabetes to T2D. New evidence suggests that T2D-lean individuals experience early β-cell dysfunction without significant IR. Regardless of the primary event (i.e., IR vs. β-cell dysfunction) that contributes to dysglycemia, significant early-onset oxidative damage and mitochondrial dysfunction in multiple metabolic tissues may be a driver of T2D onset and progression. Oxidative stress, defined as the generation of reactive oxygen species (ROS), is mediated by hyperglycemia alone or in combination with lipids. Physiological oxidative stress promotes inter-tissue communication, while pathological oxidative stress promotes inter-tissue mis-communication, and new evidence suggests that this is mediated via extracellular vesicles (EVs), including mitochondria containing EVs. Under metabolic-related stress conditions, EV-mediated cross-talk between β-cells and skeletal muscle likely trigger mitochondrial anomalies leading to prediabetes and T2D. This article reviews the underlying molecular mechanisms in ROS-related pathogenesis of prediabetes, including mitophagy and mitochondrial dynamics due to oxidative stress. Further, this review will describe the potential of various therapeutic avenues for attenuating oxidative damage, reversing prediabetes and preventing progression to T2D.