Association Between BMI and Neurocognitive Functions Among Middle-aged Obese Adults: Preliminary Findings Using Machine-learning (ML)-based Approach.

Background: Studies suggest that obesity predisposes individuals to developing cognitive dysfunction and an increased risk of dementia, but the nature of the relationship remains largely unexplored for better prognostic predictors.

Purpose: This study, the first of its kind in Indian participants with obesity, was intended to explore the use of quantification of different neurocognitive indices with increasing body mass index (BMI) among middle-aged participants with obesity. Additionally, machine-learning models were used to analyse the predictive performance of BMI for different cognitive functions.

Textural and geometric measures derived from digital tomosynthesis discriminate women with and without vertebral fracture.

Vertebral fractures are a common and debilitating consequence of osteoporosis. Bone mineral density (BMD), measured by dual energy x-ray absorptiometry (DXA), is the clinical standard for assessing overall bone quantity but falls short in accurately predicting vertebral fracture. Fracture risk prediction may be improved by incorporating metrics of microstructural organization from an appropriate imaging modality.

Smartphone Applications-Based Intervention to Reduce Body Mass Index and Improve Health-Related Behavior Among Children with Overweight/Obesity: A Pilot Clinical Trial.

Objectives: To assess changes in body mass index (BMI), diet and physical activity (PA) of 8-15-y-old children with overweight/ obesity, following a smartphone applications-based intervention; and to understand facilitators and barriers for BMI reduction.

Methods: Children were enrolled through online sessions on childhood obesity for students, parents and teachers at five private schools in Delhi, and requesting parents who perceived their children as having obesity to contact the study team. Eligibility was confirmed through home visit by a technician.

Structural-morphological insights into optimization of hydrothermally synthesized MoSe nanoflowers for improving supercapacitor applications.

The present work reports a clear and improved hydrothermal methodology for the synthesis of MoSe nanoflowers (MNFs) at 210 °C. To observe the effect of temperature on the fascinating properties, the process temperature was modified by ±10 °C. The as-prepared MNFs were found to consist of 2D nanosheets, which assembled into a 3D flower-like hierarchical morphology van der Waals forces.