Decoupled peak property learning for efficient and interpretable electronic circular dichroism spectrum prediction.

Electronic circular dichroism (ECD) spectra contain key information about molecular chirality by discriminating the absolute configurations of chiral molecules, which is crucial in asymmetric organic synthesis and the drug industry. However, existing predictive approaches lack the consideration of ECD spectra owing to the data scarcity and the limited interpretability to achieve trustworthy prediction. Here we establish a large-scale dataset for chiral molecular ECD spectra and propose ECDFormer for accurate and interpretable ECD spectrum prediction.

An Automatic Deep-Radiomics Framework for Prostate Cancer Diagnosis and Stratification in Patients with Serum Prostate-Specific Antigen of 4.0-10.0 ng/mL: A Multicenter Retrospective Study.

Rationale And Objectives: To develop an automatic deep-radiomics framework that diagnoses and stratifies prostate cancer in patients with prostate-specific antigen (PSA) levels between 4 and 10 ng/mL.

Materials And Methods: A total of 1124 patients with histological results and PSA levels between 4 and 10 ng/mL were enrolled from one public dataset and two local institutions. An nnUNet was trained for prostate masks, and a feature extraction module identified suspicious lesion masks.

The transcriptional repressor HEY2 regulates mitochondrial oxidative respiration to maintain cardiac homeostasis.

Energy deprivation and metabolic rewiring of cardiomyocytes are widely recognized hallmarks of heart failure. Here, we report that HEY2 (a Hairy/Enhancer-of-split-related transcriptional repressor) is upregulated in hearts of patients with dilated cardiomyopathy. Induced Hey2 expression in zebrafish hearts or mammalian cardiomyocytes impairs mitochondrial respiration, accompanied by elevated ROS, resulting in cardiomyocyte apoptosis and heart failure.

Deep Learning-Driven Optimization of Antihypertensive Properties from Whey Protein Hydrolysates: A Multienzyme Approach.

This study utilized deep learning to optimize antihypertensive peptides from whey protein hydrolysate. Using the Large Language Models (LLMs), we identified an optimal multienzyme combination (MC5) with an ACE inhibition rate of 89.08% at a concentration of 1 mg/mL, significantly higher than single-enzyme hydrolysis.

Four-Dimensional Data-Independent Acquisition-Based Proteomic Profiling Combined with Transcriptomic Analysis Reveals the Involvement of the Slym1-SlFHY3-CAB3C Module in Regulating Tomato Leaf Color.

In green plants, the chloroplast is responsible for light energy transition and organic assimilation. However, the molecular mechanisms underlying chloroplast development in horticultural crops remain unclear. Here, four-dimensional data-independent acquisition-based proteomic profiling identified 1,727 differentially expressed proteins between "Zhongshu 4" (ZS4) and () leaves, a considerable proportion of which were down-regulated chloroplast proteins.