Integrating the Patient Perspective to Validate a Measure of Disease Severity in Inflammatory Bowel Disease: Online Survey of Patients and Their Physicians.

Background: The patient perspective is essential for assessing disease severity, but it is not always adequately considered. We describe how a comprehensive clinical disease severity index (DSI) for inflammatory bowel disease (IBD) correlates with patient global self-assessment (PGSA).

Methods: In an individually linked parallel online survey, physicians provided the DSI, and patients provided self-assessed severity using a global question and visual analog scale (0-100) (PGSA).

Gut microbiota predicts severity and reveals novel metabolic signatures in acute pancreatitis.

Objective: Early disease prediction is challenging in acute pancreatitis (AP). Here, we prospectively investigate whether the microbiome predicts severity of AP (Pancreatitis-Microbiome As Predictor of Severity; P-MAPS) early at hospital admission.

Design: Buccal and rectal microbial swabs were collected from 424 patients with AP within 72 hours of hospital admission in 15 European centres.

Cataloging SCN resistance loci in North American public soybean breeding programs.

Soybean cyst nematode (SCN) is a destructive pathogen of soybeans responsible for annual yield loss exceeding $1.5 billion in the United States. Here, we conducted a series of genome-wide association studies (GWASs) to understand the genetic landscape of SCN resistance in the University of Missouri soybean breeding programs (Missouri panel), as well as germplasm and cultivars within the United States Department of Agriculture (USDA) Uniform Soybean Tests-Northern Region (NUST).

Loss-of-function of an α-SNAP gene confers resistance to soybean cyst nematode.

Plant-parasitic nematodes are one of the most economically impactful pests in agriculture resulting in billions of dollars in realized annual losses worldwide. Soybean cyst nematode (SCN) is the number one biotic constraint on soybean production making it a priority for the discovery, validation and functional characterization of native plant resistance genes and genetic modes of action that can be deployed to improve soybean yield across the globe. Here, we present the discovery and functional characterization of a soybean resistance gene, GmSNAP02.