Naphthalene -Diselenide-Based BODIPY Probe for the Detection of Hydrogen Peroxide, Butylhydroperoxide, Hydroxyl Radical, and Peroxynitrite Ion.

Dimethoxynaphthalene peri-diselenide-based BODIPY (4,4-difluoro-4-bora-3a,4a-diaza-s-indacene) probe has been synthesized. The probe demonstrated selectivity and sensitivity for hydrogen peroxide (HO) and butylhydroperoxide (BuOOH), hydroxyl radical (OH), and peroxynitrite ion (ONOO) detection and reversibility upon treatment with glutathione. The limits of detection of the probe were observed to be 0.

Crosstalk between cyclic-di-guanosine monophosphate and the sensor kinase MtrB regulates MtrA-dependent genes, bacterial growth, biofilm formation and lysosomal trafficking of .

Cyclic-di-guanosine monophosphate (c-di-GMP) plays an important role in bacterial signalling networks. C-di-GMP exerts a regulatory function through binding to diverse molecules that include transcription factors, riboswitches and sensor kinases (SKs), thereby regulating diverse processes. Here, we demonstrate the crosstalk between c-di-GMP and the SK MtrB of .

MitoEdit: a pipeline for optimizing mtDNA base editing and predicting bystander effects.

Motivation: Human mitochondrial DNA (mtDNA) mutations are causally implicated in maternally inherited mitochondrial respiratory disorders; however, the role of somatic mtDNA mutations in both late-onset chronic diseases and cancer remains less clear. Although recent advances in mtDNA base editing technology have the potential to model and characterize many of these mutations, current editing approaches are complicated by the potential for multiple unintentional edits (bystanders) that are only identifiable through empirical 'trial and error', thereby sacrificing valuable time and effort towards suboptimal construct development.

Results: We developed MitoEdit, a novel tool that incorporates empirical base editor patterns to facilitate identification of optimal target windows and potential bystander edits.

LipBengal: Pioneering Bengali lip-reading dataset for pronunciation mapping through lip gestures.

The dataset represents a significant advancement in Bengali lip-reading and visual speech recognition research, poised to drive future applications and technological progress. Despite Bengali's global status as the seventh most spoken language with approximately 265 million speakers, linguistically rich and widely spoken languages like Bengali have been largely overlooked by the research community. fills this gap by offering a pioneering dataset tailored for Bengali lip-reading, comprising visual data from 150 speakers across 54 classes, encompassing Bengali phonemes, alphabets, and symbols.