Mucosal Single-Cell Profiling of Crohn's-Like Disease of the Pouch Reveals Unique Pathogenesis and Therapeutic Targets.

Background & Aims: The pathophysiology of Crohn's-like disease of the pouch (CDP) in patients with a history of ulcerative colitis (UC) is unknown. We examined mucosal cells from patients with and without CDP using single-cell analyses.

Methods: Endoscopic samples were collected from pouch body and prepouch ileum (pouch/ileum) of 50 patients with an ileal pouch-anal anastomosis.

Corticosteroids Increase the Risk of Invasive Fungal Infections More Than Tumor Necrosis Factor-Alpha Inhibitors in Patients With Inflammatory Bowel Disease.

Background: Invasive fungal infections are a devastating complication of inflammatory bowel disease (IBD) treatment. We aimed to determine the incidence of fungal infections in IBD patients and examine the risk with tumor necrosis factor-alpha inhibitors (anti-TNF) compared with corticosteroids.

Methods: In a retrospective cohort study using the IBM MarketScan Commercial Database we identified US patients with IBD and at least 6 months enrollment from 2006 to 2018.

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations.

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions.

Evaluating the Appropriateness of Downscaled Climate Information for Projecting Risks of Salmonella.

Foodborne diseases have large economic and societal impacts worldwide. To evaluate how the risks of foodborne diseases might change in response to climate change, credible and usable climate information tailored to the specific application question is needed. Global Climate Model (GCM) data generally need to, both, be downscaled to the scales of the application to be usable, and represent, well, the key characteristics that inflict health impacts.

Using forecast and observed weather data to assess performance of forecast products in identifying heat waves and estimating heat wave effects on mortality.

Background: Heat wave and health warning systems are activated based on forecasts of health-threatening hot weather.

Objective: We estimated heat-mortality associations based on forecast and observed weather data in Detroit, Michigan, and compared the accuracy of forecast products for predicting heat waves.

Methods: We derived and compared apparent temperature (AT) and heat wave days (with heat waves defined as ≥ 2 days of daily mean AT ≥ 95th percentile of warm-season average) from weather observations and six different forecast products.

Comparing exposure metrics for classifying 'dangerous heat' in heat wave and health warning systems.

Heat waves have been linked to excess mortality and morbidity, and are projected to increase in frequency and intensity with a warming climate. This study compares exposure metrics to trigger heat wave and health warning systems (HHWS), and introduces a novel multi-level hybrid clustering method to identify potential dangerously hot days. Two-level and three-level hybrid clustering analysis as well as common indices used to trigger HHWS, including spatial synoptic classification (SSC), and the 90th, 95th, and 99th percentiles of minimum and relative minimum temperature (using a 10 day reference period), were calculated using a summertime weather dataset in Detroit from 1976 to 2006.

Geostatistical exploration of spatial variation of summertime temperatures in the Detroit metropolitan region.

Background: Because of the warming climate urban temperature patterns have been receiving increased attention. Temperature within urban areas can vary depending on land cover, meteorological and other factors. High resolution satellite data can be used to understand this intra-urban variability, although they have been primarily studied to characterize urban heat islands at a larger spatial scale.

Impacts of climate change on public health in India: future research directions.

Background: Climate change and associated increases in climate variability will likely further exacerbate global health disparities. More research is needed, particularly in developing countries, to accurately predict the anticipated impacts and inform effective interventions.

Objectives: Building on the information presented at the 2009 Joint Indo-U.