Artificial intelligence: A new tool in the pathologist's armamentarium for the diagnosis of IBD.

Inflammatory bowel diseases (IBD) are classified into two entities, namely Crohn's disease (CD) and ulcerative colitis (UC), which differ in disease trajectories, genetics, epidemiological, clinical, endoscopic, and histopathological aspects. As no single golden standard modality for diagnosing IBD exists, the differential diagnosis among UC, CD, and non-IBD involves a multidisciplinary approach, considering professional groups that include gastroenterologists, endoscopists, radiologists, and pathologists. In this context, histological examination of endoscopic or surgical specimens plays a fundamental role.

Focus on Achalasia in the Omics Era.

Achalasia is a rare and complex esophageal disease of unknown etiology characterized by difficulty in swallowing due to the lack of opening of the lower esophageal sphincter and the absence of esophageal peristalsis. Recent advancements in technology for analyzing DNA, RNA and biomolecules in high-throughput techniques are offering new opportunities to better understand the etiology and the pathogenetic mechanisms underlying achalasia. Through this narrative review of the scientific literature, we aim to provide a comprehensive assessment of the state-of-the-art knowledge on omics of achalasia, with particular attention to those considered relevant to the pathogenesis of the disease.

Polymorphisms within autophagy-related genes as susceptibility biomarkers for pancreatic cancer: A meta-analysis of three large European cohorts and functional characterization.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with patients having unresectable or metastatic disease at diagnosis, with poor prognosis and very short survival. Given that genetic variation within autophagy-related genes influences autophagic flux and susceptibility to solid cancers, we decided to investigate whether 55,583 single nucleotide polymorphisms (SNPs) within 234 autophagy-related genes could influence the risk of developing PDAC in three large independent cohorts of European ancestry including 12,754 PDAC cases and 324,926 controls. The meta-analysis of these populations identified, for the first time, the association of the BID variant with an increased risk of developing the disease (OR = 1.

Inflammatory bowel disease genomics, transcriptomics, proteomics and metagenomics meet artificial intelligence.

Various extrinsic and intrinsic factors such as drug exposures, antibiotic treatments, smoking, lifestyle, genetics, immune responses, and the gut microbiome characterize ulcerative colitis and Crohn's disease, collectively called inflammatory bowel disease (IBD). All these factors contribute to the complexity and heterogeneity of the disease etiology and pathogenesis leading to major challenges for the scientific community in improving management, medical treatments, genetic risk, and exposome impact. Understanding the interaction(s) among these factors and their effects on the immune system in IBD patients has prompted advances in multi-omics research, the development of new tools as part of system biology, and more recently, artificial intelligence (AI) approaches.

Duodenal Fluid Analysis as a Rewarding Approach to Detect Low-Abundance Mutations in Biliopancreatic Cancers.

Diagnosis of biliopancreatic cancers by the available serum tumor markers, imaging, and histopathological tissue specimen examination remains a challenge. Circulating cell-free DNA derived from matched pairs of secretin-stimulated duodenal fluid (DF) and plasma from 10 patients with biliopancreatic diseases and 8 control subjects was analyzed using AmpliSeq™ HD technology for Ion Torrent Next-Generation Sequencing to evaluate the potential of liquid biopsy with DF in biliopancreatic cancers. The median cfDNA concentration was greater in DF-derived than in plasma-derived samples.