Design and Development of Portable Body Composition Analyzer for Children.

Objectives: The aim of this study was (i) to design and develop a portable BCA device for measuring body composition parameters such as body weight, body fat (BF) %, total body water (TBW), fat-free mass (FFM), muscle mass (MM), and bone mass (BM); (ii) to validate the developed portable BCA with the Tanita MC 980 MA BCA device.

Methods: For this current study, two hundred healthy and obese subjects, whose ages ranged from 8 to 12 years (8.4 ± 1.

Dry LAMP: A point of care diagnostics for diagnosis of bovine tropical theileriosis.

Background Objectives: Theileriosis is an important tick-bome hemoprotozoan disease of cattle which causes severe economic loss due to morbidity and mortality. A diagnostic test having high sensitivity, specificity and easy application at the field level is the need of the hour. In this regard Loop-mediated isothermal amplification (LAMP) is proven to be a sensitive, easy and time efficient method.

Genetic variation drives cancer cell adaptation to ECM stiffness.

The progression of many solid tumors is accompanied by temporal and spatial changes in the stiffness of the extracellular matrix (ECM). Cancer cells adapt to soft and stiff ECM through mechanisms that are not fully understood. It is well known that there is significant genetic heterogeneity from cell to cell in tumors, but how ECM stiffness as a parameter might interact with that genetic variation is not known.

The Spectrum of Central Nervous System Tumors at a Tertiary Care Center Primarily Serving a Rural Population.

Background Central nervous system (CNS) tumors cause significant mortality and morbidity in all age groups. There was no data about the histological spectrum of all CNS tumors in the tertiary care center serving primarily the rural population of Uttar Pradesh. Aims and objectives The present study aimed to describe the histopathological spectrum of all CNS tumors reported in a rural tertiary care center at Saifai, Uttar Pradesh.

Many-body interactions and deep neural network potentials for water.

We present a detailed assessment of deep neural network potentials developed within the Deep Potential Molecular Dynamics (DeePMD) framework and trained on the MB-pol data-driven many-body potential energy function. Specific focus is directed at the ability of DeePMD-based potentials to correctly reproduce the accuracy of MB-pol across various water systems. Analyses of bulk and interfacial properties as well as many-body interactions characteristic of water elucidate inherent limitations in the transferability and predictive accuracy of DeePMD-based potentials.