Merging genes, models, and climate: a new approach to predicting rice flowering
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Jan-2026 16:11 ET (23-Jan-2026 21:11 GMT/UTC)
A research team used flowering data from 169 rice genotypes—each with over 700,000 SNP markers—across multiple environments to develop a robust framework for phenotypic prediction.
A research team has identified a key gene, CsCHLI, that plays a central role in chlorophyll biosynthesis and leaf coloration in tea plants.
In low-resource settings, babies born with gastroschisis — a congenital condition in which the developing intestines extend outside the body through a hole in the abdominal wall —face life-threatening challenges. While survival rates in high-income countries now exceed 90% thanks to advanced medical tools and neonatal care, infants in resource-constrained medical settings still face high mortality rates, partially because of a lack of access to the lifesaving equipment needed to treat the condition. A team of engineers and pediatric surgeons led by Rice University’s Rice360 Institute for Global Health Technologies is working to change that. Their innovation? A simple, low-cost and locally manufacturable medical device, known as the “SimpleSilo,” designed to provide lifesaving treatment for gastroschisis at a fraction of the current cost and made from locally available materials.
Researchers tested a large language model (LLM) on peer review tasks for cancer research papers. They found the AI could be abused to generate highly persuasive rejection letters and other fraudulent reviews, such as requests to cite unrelated papers. Crucially, current AI detection tools were largely unable to identify the AI-generated text, posing a significant, hidden threat to academic integrity.