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HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates.
J Chem Inf Model
January 2025
State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, P.R. China.
The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective treatment. These mutations alter the drug-binding pocket of the protease and reduce the drug efficacy by disrupting interactions with inhibitors. Traditional methods, such as biochemical assays and structural biology, are crucial for studying enzyme function but are time-consuming and labor-intensive.
View Article and Find Full Text PDFInvestigating combined hypoxia and stemness indices for prognostic transcripts in gastric cancer: Machine learning and network analysis approaches.
Biochem Biophys Rep
March 2025
Department of Genetics and Molecular Biology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Introduction: Gastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including stemness mechanisms facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.
Materials And Methods: GC RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to compute hypoxia and stemness scores using Gene Set Variation Analysis (GSVA) and the mRNA expression-based stemness index (mRNAsi).
Effectiveness of a Fast- vs. Slow-Velocity Training on Load-Velocity Characteristics in Older Adults: A Pilot Study.
Int J Exerc Sci
December 2024
Department of Exercise Science and Pre-Health Professions, Creighton University, Omaha, NE, USA.
Resistance training at fast velocities is suggested to be more effective for improving muscular strength and movement speed compared to slow, heavy training. This study aimed to examine the effects of a fast-velocity (FVRT) compared to a slow-velocity (SVRT) resistance training program on maximal strength, maximal movement speed, and load-velocity characteristics in older adults. Nineteen community-dwelling older adults were randomly assigned to either the FVRT or SVRT group and completed a twice weekly, progressive resistance training protocol for 8-weeks.
View Article and Find Full Text PDFPredicting Color Development and Texture Changes in Tomatoes Treated With Hot Water and Exposed to High-Temperature Ethylene Using Support Vector Regression.
J Texture Stud
February 2025
Department of Mathematics, Aditya University, Surampalem, Andhra Pradesh, India.
This study investigated the impacts of hot water treatment (HWT) at 50°C or 25°C for 5 min and high-temperature ethylene (HTE) exposure at varying temperatures (20°C, 30°C, or 35°C) and durations (24, 48, or 72 h) on the postharvest quality and antioxidant properties of mature green tomatoes (MG). Color changes, physicochemical characteristics, antioxidant compounds, and overall antioxidant ability were assessed. HWT increased β-carotene levels and oxygen radical absorbance capacity (ORAC) while preserving color metrics, despite later HTE exposure.
View Article and Find Full Text PDFComparative analysis of regression algorithms for drug response prediction using GDSC dataset.
BMC Res Notes
January 2025
Department of Computer Engineering, Chungbuk National University, Chungdae-ro 1, Cheongju, 28644, Republic of Korea.
Background: Drug response prediction can infer the relationship between an individual's genetic profile and a drug, which can be used to determine the choice of treatment for an individual patient. Prediction of drug response is recently being performed using machine learning technology. However, high-throughput sequencing data produces thousands of features per patient.
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