LONG-TERM PROGNOSIS OF NON-CELIAC ENTEROPATHIES AND A SCORE TO IDENTIFY PATIENTS WITH POOR OUTCOMES: A 30-YEAR MULTICENTER LONGITUDINAL STUDY.

Introduction: Long-term prognosis of non-celiac enteropathies (NCEs) is poorly understood. We aimed to evaluate long-term outcomes and develop a prognostic score for NCEs.

Methods: NCEs patients from an international multicenter cohort (4 Italian centers,1 UK, 1 French,1 Norwegian,1 USA,1 Indian) followed-up over 30 years were enrolled.

Trends in the incidence and mutational landscape of advanced uterine cancer.

Objective: The aim of this study was to examine disparities in 20-year incidence trends and mutations in advanced-stage uterine cancer in the United States, given poor survival rates.

Methods: Data were obtained from the United States Cancer Statistics for patients from 2001 to 2019 with International Federation of Gynecology and Obstetrics 2009 stage IVA and IVB uterine cancer. SEER∗Stat 8.

Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3.

Apical and basal dendrites of pyramidal neurons receive anatomically and functionally distinct inputs, implying compartment-level functional diversity during behavior. To test this, we imaged in vivo calcium signals from soma, apical dendrites, and basal dendrites in mouse hippocampal CA3 pyramidal neurons during head-fixed navigation. To capture compartment-specific population dynamics, we developed computational tools to automatically segment dendrites and extract accurate fluorescence traces from densely labeled neurons.

Enantioselective Borylcupration/Cyclization of Alkene-Tethered Oxime Esters.

A copper-catalyzed enantioselective synthesis of borylated 1-pyrrolines from γ,δ-unsaturated oxime esters is reported. Twenty-four novel 1-pyrroline derivatives are reported in yields ranging from 26% to 96% and enantioselectivities from 74.5:25.

Automatic speech recognition predicts contemporaneous earthquake fault displacement.

Significant progress has been made in probing the state of an earthquake fault by applying machine learning to continuous seismic waveforms. The breakthroughs were originally obtained from laboratory shear experiments and numerical simulations of fault shear, then successfully extended to slow-slipping faults. Here we apply the Wav2Vec-2.