Performance of an Artificial Intelligence Model for Recognition and Quantitation of Histologic Features of Eosinophilic Esophagitis on Biopsy Samples.

We have developed an artificial intelligence (AI)-based digital pathology model for the evaluation of histologic features related to eosinophilic esophagitis (EoE). In this study, we evaluated the performance of our AI model in a cohort of pediatric and adult patients for histologic features included in the Eosinophilic Esophagitis Histologic Scoring System (EoEHSS). We collected a total of 203 esophageal biopsy samples from patients with mucosal eosinophilia of any degree (91 adult and 112 pediatric patients) and 10 normal controls from a prospectively maintained database.

Development and technical validation of an artificial intelligence model for quantitative analysis of histopathologic features of eosinophilic esophagitis.

Background: In an attempt to provide quantitative, reproducible, and standardized analyses in cases of eosinophilic esophagitis (EoE), we have developed an artificial intelligence (AI) digital pathology model for the evaluation of histologic features in the EoE/esophageal eosinophilia spectrum. Here, we describe the development and technical validation of this novel AI tool.

Methods: A total of 10 726 objects and 56.

The Use of Virtual Reality Echocardiography in Medical Education.

Virtual reality (VR) is a relatively new technology that allows an individual to experience a virtual world. This new immersive video type may be of particular usefulness in procedure-based healthcare settings. We hypothesized that VR echocardiography was non-inferior to live demonstration.

Medical school selection criteria as predictors of medical student empathy: a cross-sectional study of medical students, Ireland.

Objectives: To determine whether performance in any of the Health Professions Admissions Test (HPAT) sections, most specifically the interpersonal understanding section, correlates with self-reported empathy levels in medical students.

Setting: The study was conducted in University College Cork, Ireland.

Participants: 290 students participated in the study.

A Novel Selectable Islet 1 Positive Progenitor Cell Reprogrammed to Expandable and Functional Smooth Muscle Cells.

Disorders affecting smooth muscle structure/function may require technologies that can generate large scale, differentiated and contractile smooth muscle cells (SMC) suitable for cell therapy. To date no clonal precursor population that provides large numbers of differentiated SMC in culture has been identified in a rodent. Identification of such cells may also enhance insight into progenitor cell fate decisions and the relationship between smooth muscle precursors and disease states that implicate differentiated SMC.

Synthetic chemically modified mrna-based delivery of cytoprotective factor promotes early cardiomyocyte survival post-acute myocardial infarction.

To extend the temporal window for cytoprotection in cardiomyocytes undergoing apoptosis after hypoxia and myocardial infarction (MI), a synthetic chemically modified mRNA (modRNA) was used to drive delivery of insulin-like growth factor-1 (IGF1) within the area at risk in an in vivo murine model of MI. Delivery of IGF1 modRNA, with a polyethylenimine-based nanoparticle, augmented secreted and cell-associated IGF1, promoting cardiomyocyte survival and abrogating cell apoptosis under hypoxia-induced apoptosis conditions. Translation of modRNA-IGF1 was sufficient to induce downstream increases in the levels of Akt and Erk phosphorylation.