Multi-Institutional Analysis of Pancreatoduodenectomy for Nonfamilial Periampullary Adenoma: A Novel Risk Score to Guide Shared Decision-Making.

Introduction: Pancreatoduodenectomy (PD) may occasionally be indicated for complete removal of periampullary (duodenal and ampullary) adenomas (PAs). As compared with malignant indications, PD for benign or pre-malignant disease is often associated with increased morbidity. While the Spigelman classification assesses malignancy risk for familial adenomatous polyposis (FAP)-related duodenal adenomas, no malignancy risk score (MRS) exists for non-FAP related PAs.

BioMedGraphica: An All-in-One Platform for Biomedical Prior Knowledge and Omic Signaling Graph Generation.

Artificial intelligence (AI) is revolutionizing scientific discovery because of its super capability, following the neural scaling laws, to integrate and analyze large-scale datasets to mine knowledge. Foundation models, large language models (LLMs) and large vision models (LVMs), are among the most important foundations paving the way for general AI by pre-training on massive domain-specific datasets. Different from the well annotated, formatted and integrated large textual and image datasets for LLMs and LVMs, biomedical knowledge and datasets are fragmented with data scattered across publications and inconsistent databases that often use diverse nomenclature systems in the field of AI for Precision Health and Medicine (AI4PHM).

HMGA2 Expression Predicts Subtype, Survival, and Treatment Outcome in Pancreatic Ductal Adenocarcinoma.

Purpose: To establish HMGA2 as a marker of basal-like disease in pancreatic ductal adenocarcinoma (PDAC) and explore its use as a biomarker for prognosis and treatment resistance.

Experimental Design: We identified high expression of HMGA2 in basal PDAC cells in a scRNAseq Atlas of 172 patient samples. We then analyzed HMGA2 expression, along with expression of the classical marker GATA6, in a cohort of 580 PDAC samples with multiplex immunohistochemistry.

Nascent transcript O-MAP reveals the molecular architecture of a single-locus subnuclear compartment built by RBM20 and the RNA.

Eukaryotic nuclei adopt a highly compartmentalized architecture that influences nearly all genomic processes. Understanding how this architecture impacts gene expression has been hindered by a lack of tools for elucidating the molecular interactions at individual genomic loci. Here, we adapt oligonucleotide-mediated proximity-interactome mapping (O-MAP) to biochemically characterize discrete, micron-scale nuclear neighborhoods.