Artificial Intelligence in Computer-Aided Drug Design (CADD) Tools for the Finding of Potent Biologically Active Small Molecules: Traditional to Modern Approach.

Computer-Aided Drug Design (CADD) entails designing molecules that could potentially interact with a specific biomolecular target and promising their potential binding. The stereo- arrangement and stereo-selectivity of small molecules (SMs)--based chemotherapeutic agents significantly influence their therapeutic potential and enhance their therapeutic advantages. CADD has been a well-established field for decades, but recent years have observed a significant shift toward acceptance of computational approaches in both academia and the pharmaceutical industry.

Mid-term Outcomes of Patella Resurfacing During Total Knee Arthroplasty (TKA): Clinical, Functional, and Radiographic Insights.

Aim The primary objective of the study was to evaluate the mid-term implant survivability, rate of revisions, and clinical and functional outcomes following patella resurfacing during total knee arthroplasty (TKA) utilizing posterior stabilized (PS) total knee system (TKS). Methods A prospective, single-arm, multi-center, post-marketing surveillance encompassed patients with end-stage primary knee osteoarthritis (OA) or inflammatory arthritis. The time points of the study included baseline, six weeks, six months, one year, and three years post-operatively.

Contribution of Travelers to Malaria in South West Delhi, India: Cross-Sectional Survey.

Background: India is committed to malaria elimination by the year 2030. According to the classification of malaria endemicity, the National Capital Territory of Delhi falls under category 1, with an annual parasite incidence of <1, and was targeted for elimination by 2022. Among others, population movement across states is one of the key challenges for malaria control, as it can result in imported malaria, thus introducing local transmission in an area nearing elimination.

BharatSim: An agent-based modelling framework for India.

BharatSim is an open-source agent-based modelling framework for the Indian population. It can simulate populations at multiple scales, from small communities to states. BharatSim uses a synthetic population created by applying statistical methods and machine learning algorithms to survey data from multiple sources, including the Census of India, the India Human Development Survey, the National Sample Survey, and the Gridded Population of the World.

Machine learning-enhanced detection of chlorpyrifos using molecularly imprinted polymer-coated optical fibers.

This paper explores the use of large core declad optical fibers coated with molecularly imprinted polymers for chlorpyrifos detection, a key marker of organophosphate pesticides. The performance of sensor is evaluated using artificial neural networks and principal component analysis. By varying the declad length, the performance of molecularly imprinted polymer-coated fibers is compared to uncoated fibers, and both are used to identify commercial and pure samples of chlorpyrifos pesticides.