A three-layer perspective on miRNA regulation in β cell inflammation.

MicroRNAs (miRNAs) are noncoding RNA molecules that regulate gene expression post-transcriptionally and influence numerous biological processes. Aberrant miRNA expression is linked to diseases such as diabetes mellitus; indeed, miRNAs regulate pancreatic islet inflammation in both type 1 (T1D) and type 2 diabetes (T2D). Traditionally, miRNA research has focused on canonical sequences and offers a two-layer view - from expression to function.

Retrospective Study on the Features and Outcomes of a Tuscany COVID-19 Hospitalized Patients Cohort: Preliminary Results.

A few months after the COVID-19 pandemic onset, knowledge of SARS-CoV-2 infection and outcomes and treatments blew up. This paper aimed to evaluate the features of a Tuscany COVID-19 hospitalized cohort and to identify risk factors for COVID-19 severity. This retrospective observational COVID-19 cohort study (1 March 2020-1 March 2021) was conducted on patients ≥ 18 years old, admitted to Tuscany Hospital, and subjected to follow-up within 12 months after discharge.

Machine Learning Analysis in Diffusion Kurtosis Imaging for Discriminating Pediatric Posterior Fossa Tumors: A Repeatability and Accuracy Pilot Study.

: Differentiating pediatric posterior fossa (PF) tumors such as medulloblastoma (MB), ependymoma (EP), and pilocytic astrocytoma (PA) remains relevant, because of important treatment and prognostic implications. Diffusion kurtosis imaging (DKI) has not yet been investigated for discrimination of pediatric PF tumors. Estimating diffusion values from whole-tumor-based (VOI) segmentations may improve diffusion measurement repeatability compared to conventional region-of-interest (ROI) approaches.

Multi-omics analysis reveals drivers of loss of β-cell function after newly diagnosed autoimmune type 1 diabetes: An INNODIA multicenter study.

Aims: Heterogeneity in the rate of β-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of baseline multi-omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis.

Methods: We collected samples in a pan-European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients.