Draft genome sequence of strain YAFMF0618, isolated from Gaoligong Mountain.

The genus is an important Chinese medicinal fungus. Here, we present a draft genome sequence of strain YAFMF0618. The genome resource will support subsequent research into the potential secondary metabolite diversity of .

A green and environmentally benign route to synthesizing Z-scheme BiS-TCN photocatalyst for efficient hydrogen production.

Designing and developing photocatalysts with excellent performance in order to achieve efficient hydrogen production is an important strategy for addressing future energy and environmental challenges. Traditional single-phase photocatalytic materials either have a large bandgap and low visible light response or experience rapid recombination of the photogenerated carriers with low quantum efficiency, seriously hindering their photocatalytic applications. To solve these issues, an important solution is to construct well-matched heterojunctions with highly efficient charge separation capabilities.

Creation of Interfacial S-Sn-N Electron Pathways for Efficient Light-Driven Hydrogen Evolution.

Establishing effective charge transfer channels between two semiconductors is key to improving photocatalytic activity. However, controlling hetero-structures in situ and designing binding modes pose significant challenges. Herein, hydrolytic SnCl·2HO is selected as the metal source and loaded in situ onto a layered carbon nitriden supramolecular precursor.

Genetic expression profile-based screening of genes and pathways associated with papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer; however, the specific genes and signaling pathways involved in this cancer remain largely unclear. The present study analyzed three profile datasets, GSE6004, GSE29265 and GSE60542, which were comprised of 47 PTC and 41 normal thyroid tissue samples, to identify key genes and pathways associated with PTC. Initially, differentially-expressed genes (DEGs) between PTC and normal thyroid tissue were screened using R 3.

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA).