PINK1 modulates Prdx2 to reduce lipotoxicity-induced apoptosis and attenuate cardiac dysfunction in heart failure mice with a preserved ejection fraction.

Introduction: Heart failure with preserved ejection fraction (HFpEF) is a complex condition characterized by metabolic dysfunction and myocardial lipotoxicity. The roles of PTEN-induced kinase 1 (PINK1) and peroxiredoxin-2 (Prdx2) in HFpEF pathogenesis remain unclear.

Objective: This study aimed to investigate the interaction between PINK1 and Prdx2 to mitigate cardiac diastolic dysfunction in HFpEF.

Comparative analysis of mitochondrial genomes of Stemona tuberosa lour. reveals heterogeneity in structure, synteny, intercellular gene transfer, and RNA editing.

Background: Stemona tuberosa, a vital species in traditional Chinese medicine, has been extensively cultivated and utilized within its natural distribution over the past decades. While the chloroplast genome of S. tuberosa has been characterized, its mitochondrial genome (mitogenome) remains unexplored.

Synergistic Remediation of Cadmium Pollution in Saline-Alkali Soil by Hydrogel and .

The cadmium (Cd) in saline-alkali soil poses a serious threat to the ecological environment and human health. , as a hyperaccumulator plant, can remediate Cd in saline-alkali soil, but the efficiency of phytoremediation is low. To improve the remediation effect of Cd pollution in saline-alkali soil, this study for the first time uses the synergy of hydrogel and for the remediation of Cd in saline-alkali soil.

Facile Synthesis of Flower-cluster ZIF Nanocarriers: Performance in Controlled Release of Thiamethoxam and Insecticidal Activity.

At present, it is highly important to develop nanopesticide, which can improve the effect of pesticides and reduce the risks of environmental. Zeolitic imidazolate framework (ZIF) is usually used as a nanocarrier of nanopesticide, which has a porous structure and stimuli-responsive properties. However, the drug loading performance and stability of ZIF are poor.

PPI-CoAttNet: A Web Server for Protein-Protein Interaction Tasks Using a Coattention Model.

Predicting protein-protein interactions (PPIs) is crucial for advancing drug discovery. Despite the proposal of numerous advanced computational methods, these approaches often suffer from poor usability for biologists and lack generalization. In this study, we designed a deep learning model based on a coattention mechanism that was capable of both PPI and site prediction and used this model as the foundation for PPI-CoAttNet, a user-friendly, multifunctional web server for PPI prediction.