Two TAL Effectors of Xanthomonas citri pv. malvacearum Induce Water Soaking by Activating GhSWEET14 Genes in Cotton.

Bacterial blight of cotton (BBC) caused by Xanthomonas citri pv. malvacearum (Xcm) is an important and destructive disease affecting cotton plants. Transcription activator-like effectors (TALEs) released by the pathogen regulate cotton resistance to the susceptibility.

New opportunities in mechanistic and functional microbiome studies.

The field of microbiome research has experienced remarkable growth, leading to unprecedented discoveries of the molecular mechanisms that dictate host-microbiota interactions and their crucial roles in human health. In this "chemical biology of the microbiome" focus issue from Cell Chemical Biology, this Voices piece asks researchers from a range of backgrounds to share their insights on the most exciting recent developments in the microbiome field.

Risk factors for increased drain output after endoscopic thyroidectomy via areola approach: a retrospective cohort study.

Background: Endoscopic thyroidectomy (ET) offers superior cosmetic outcomes compared to traditional open thyroidectomy but is associated with higher postoperative drainage volumes (DV) and potential complications. Although ET via the areola approach (ETAA) has been used, the factors influencing DV after ETAA remain poorly understood. Therefore, this study aimed to identify clinical parameters that can objectively evaluate the factors influencing drainage volume after ETAA.

Control of water for high-yield and low-cost sustainable electrochemical synthesis of uniform monolayer graphene oxide.

With the rapid development of graphene industry, low-cost sustainable synthesis of monolayer graphene oxide (GO) has become more and more important for many applications such as water desalination, thermal management, energy storage and functional composites. Compared to the conventional chemical oxidation methods, water electrolytic oxidation of graphite-intercalation-compound (GIC) shows significant advantages in environmental-friendliness, safety and efficiency, but suffers from non-uniform oxidation, typically ~50 wt.% yield with ~50% monolayers.

Mitochondrial segmentation and function prediction in live-cell images with deep learning.

Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image segmentation and function prediction. Trained on a dataset of 20,000 manually labeled mitochondria from super-resolution (SR) images, MoDL achieves superior segmentation accuracy, enabling comprehensive morphological analysis.