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Introduction Glucose uptake and metabolism are the most physiologically important driver of insulin release from pancreatic islet [beta] cells, a highly specialized class of endocrine cells that secrete this hormone [...], Glucose plays a key role in shaping pancreatic [beta] cell function. Thus, deciphering the mechanisms by which this nutrient stimulates [beta] cells holds therapeutic promise for combating [beta] cell failure in type 2 diabetes (T2D). [beta] cells respond to hyperglycemia in part by rewiring their mRNA metabolism, yet the mechanisms governing these changes remain poorly understood. Here, we identify a requirement for the RNA-binding protein PCBP2 in maintaining [beta] cell function basally and during sustained hyperglycemic challenge. PCBP2 was induced in primary mouse islets incubated with elevated glucose and was required to adapt insulin secretion. Transcriptomic analysis of primary Pcbp2-deficient [beta] cells revealed impacts on basal and glucose-regulated mRNAs encoding core components of the insulin secretory pathway. Accordingly, Pcbp2-deficient [beta] cells exhibited defects in calcium flux, insulin granule ultrastructure and exocytosis, and the amplification pathway of insulin secretion. Further, PCBP2 was induced by glucose in primary human islets, was downregulated in islets from T2D donors, and impacted genes commonly altered in islets from donors with T2D and linked to single-nucleotide polymorphisms associated with T2D. Thus, these findings establish a paradigm for PCBP2 in governing basal and glucose-adaptive gene programs critical for shaping the functional state of [beta] cells.

Background and Aims Histological disease activity in inflammatory bowel disease [IBD] is associated with clinical outcomes and is an important endpoint in drug development. We developed deep learning models for automating histological assessments in IBD. Methods Histology images of intestinal mucosa from phase 2 and phase 3 clinical trials in Crohn's disease [CD] and ulcerative colitis [UC] were used to train artificial intelligence [AI] models to predict the Global Histology Activity Score [GHAS] for CD and Geboes histopathology score for UC. Three AI methods were compared. AI models were evaluated on held-back testing sets, and model predictions were compared against an expert central reader and five independent pathologists. Results The model based on multiple instance learning and the attention mechanism [SA-AbMILP] demonstrated the best performance among competing models. AI-modelled GHAS and Geboes subgrades matched central readings with moderate to substantial agreement, with accuracies ranging from 65% to 89%. Furthermore, the model was able to distinguish the presence and absence of pathology across four selected histological features, with accuracies for colon in both CD and UC ranging from 87% to 94% and for CD ileum ranging from 76% to 83%. For both CD and UC and across anatomical compartments [ileum and colon] in CD, comparable accuracies against central readings were found between the model-assigned scores and scores by an independent set of pathologists. Conclusions Deep learning models based upon GHAS and Geboes scoring systems were effective at distinguishing between the presence and absence of IBD microscopic disease activity. [ABSTRACT FROM AUTHOR]

We previously demonstrated that the two paralogous RNA-binding proteins PCBP1 and PCBP2 are individually essential for mouse development: Pcbp1-null embryos are peri-implantation lethal, while Pcbp2-null embryos lose viability at midgestation. Midgestation Pcbp22/2 embryos revealed a complex phenotype that included loss of certain hematopoietic determinants. Whether PCBP2 directly contributes to erythropoietic differentiation and whether PCBP1 has a role in this process remained undetermined. Here, we selectively inactivated the genes encoding these two RNA-binding proteins during differentiation of the erythroid lineage in the developing mouse embryo. Individual inactivation of either locus failed to impact viability or blood formation. However, combined inactivation of the two loci resulted in midgestational repression of erythroid/hematopoietic gene expression, loss of blood formation, and fetal demise. Orthogonal ex vivo analyses of primary erythroid progenitors selectively depleted of these two RNA-binding proteins revealed that they mediate a combination of overlapping and isoform-specific impacts on hematopoietic lineage transcriptome, impacting both mRNA representation and exon splicing. These data lead us to conclude that PCBP1 and PCBP2 mediate functions critical to differentiation of the erythroid lineage. [ABSTRACT FROM AUTHOR]

The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF , ADCY3 , TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.