deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.

Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the misuse of antibiotics intensifies, the identification of AMPs as alternatives to antibiotics has become a hot topic. Accurately identifying AMPs using computational methods has been a key issue in the field of bioinformatics in recent years.

Exosome-equipped TNF antisense oligodeoxynucleotide or 2-deoxy-D-glucose ameliorated nonalcoholic steatohepatitis by modulating superoxide dismutase 1 in mice.

Inflammatory mediators tumor necrosis factor (TNF) and interleukin 1 beta (IL1β), primarily derived from hepatic macrophages in the liver, play a crucial role in the progression of nonalcoholic steatohepatitis (NASH). Meanwhile, intravenously injected exosomes are mainly distributed in the liver and predominantly taken up by hepatic macrophage. Herein, we aimed to evaluate the feasibility of targeted inhibition of TNF and IL1β expression in hepatic macrophages via exosomes as a potential therapeutic strategy for NASH.

Quantitative Study on the Charge-Dependent Uptake of Ultrasmall Fluorescent Gold Nanoclusters in 3D Spheroids of Cancer Cells.

Gold nanoclusters (AuNCs) have garnered significant attention in biomedical applications, particularly in biosensing, cancer therapy, and imaging, due to their unique optical property, good biocompatibility, and distinct bioactivity. Understanding the cellular uptake behavior of AuNCs is critical to improve the efficacy of their applications, whose mechanism has not been adequately validated. In this work, we synthesized AuNCs with varying surface modifications to quantify the exact law of surface charge on the cellular uptake of AuNCs in a multidimensional manner by using 3D multicellular tumor spheroids of both HeLa cells and MCF-7 cells as the model system.

An Elastic Filtering Algorithm with Visual Perception for Vehicle GNSS Navigation and Positioning.

Amidst the backdrop of the profound synergy between navigation and visual perception, there is an urgent demand for accurate real-time vehicle positioning in urban environments. However, the existing global navigation satellite system (GNSS) algorithms based on Kalman filters fall short of precision. In response, we introduce an elastic filtering algorithm with visual perception for vehicle GNSS navigation and positioning.

RiceSNP-ABST: a deep learning approach to identify abiotic stress-associated single nucleotide polymorphisms in rice.

Given the adverse effects faced by rice due to abiotic stresses, the precise and rapid identification of single nucleotide polymorphisms (SNPs) associated with abiotic stress traits (ABST-SNPs) in rice is crucial for developing resistant rice varieties. The scarcity of high-quality data related to abiotic stress in rice has hindered the development of computational models and constrained research efforts aimed at rice improvement and breeding. Genome-wide association studies provide a better statistical power to consider ABST-SNPs in rice.