Development of deep learning-based mobile application for the identification of Coccidia species in pigs using microscopic images.

Coccidiosis is a gastrointestinal parasitic disease caused by different species of Eimeria and Isospora, poses a significant threat to pig farming, leading to substantial economic losses attributed to reduced growth rates, poor feed conversion, increased mortality rates, and the expense of treatment. Traditional methods for identifying Coccidia species in pigs rely on fecal examination and microscopic analysis, necessitating expert personnel for accurate species identification. To address this need, a deep learning-based mobile application capable of automatically identifying different species of Eimeria and Isospora was developed.

Computational analysis of MYC gene variants: structural and functional impact of non-synonymous SNPs.

The MYC proto-oncogene encodes a basic helix-loop-helix leucine zipper (HLH-LZ) transcription factor, acting as a master regulator of genes involved in cellular proliferation, differentiation, and immune surveillance. Dysregulation of MYC is implicated in over 70% of human cancers, driving oncogenic processes through altered gene expression and disrupted cellular functions. Non-synonymous single nucleotide polymorphisms (nsSNPs) within coding regions can significantly impact protein structure and function, leading to abnormal cellular behaviours.

Exploring the potential of diosgenin as a promising antitumor agent through comprehensive spectroscopic characterization, solvent-solute interactions, topological properties, Hirshfeld surface, and molecular docking interactions with 2NZT and 2I1V proteins.

This study characterizes the steroidal saponin diosgenin by theoretical and experimental spectroscopic techniques. Theoretical simulations were performed using the DFT/B3LYP/6-311++G(d,p) basis set to simulate spectroscopic, structural and other properties. Optimized geometries from simulations and experiments showed strong agreement, with R value of 0.

Excitation wavelength and time dependent colour tunable room temperature phosphorescence from boron doped carbon nanodots.

Developing metal free room temperature phosphorescence (RTP) materials have received tremendous attention due its potential application in various fields such as sensing, optoelectronics and anticounterfeiting. Herein, we have synthesized an excitation wavelength and time dependent phosphorescent boron doped carbon nanodots (BCNDs) by thermal treatment of ethanolamine and boric acid at 240 °C, where boric acid act as both doping and host agents. The obtained BCNDs display blue to orange fluorescence in both aqueous medium and solid state.