Computational prediction of high-risk non-synonymous SNPs in human ApoE and their structural impact on amyloid-β interaction in Alzheimer's disease pathogenesis.

Apolipoprotein E (ApoE) plays a critical role in Alzheimer's disease (AD) by regulating amyloid beta (Aβ) clearance through direct interaction. Non-synonymous single nucleotide polymorphisms (nsSNPs) in ApoE alter its structure and impair function, contributing to disease progression. This study aimed to identify functionally damaging nsSNPs in the ApoE gene using in silico tools and to assess their structural and binding effects on Aβ in the context of AD progression.

Network and pharmacophore guided and BCL2 and HSP90AA1 targeted drug repurposable approaches against rheumatoid arthritis mediated diffuse large B-cell lymphoma.

Rheumatoid arthritis (RA) raises the incidence of Diffuse large B-cell lymphoma (DLBCL) development, presenting a critical clinical challenge due to the intersection of autoimmunity and malignancy. However, molecular mechanisms underlying RA-mediated DLBCL progression and therapeutic interventions remain poorly elucidated. To address this gap, we developed a novel GCNConv deep learning pipeline to predict key molecular hubs within shared genes of RA and DLBCL networks and validated them through literature mining.

Biodegradation of plastics and pesticides by soil bacteria in Bangladesh: Insights into antibiotic resistance and potential therapeutic targets.

Soil bacteria exhibit varying degrees of tolerance to different concentrations of pesticides and plastics, and some possess the ability to degrade them, which is crucial for bioremediation. However, the multidrug-resistant properties of these bacteria pose challenges for their potential applications. Hence, this study aims to separate and characterize plastics and pesticide-degrading bacteria fromnon-contaminated and contaminated sites in Bangladesh and evaluate their antibiotic-resistant patterns to identify safety issues and discover promising therapeutic targets for combating multidrug-resistant infections.

In-Silico discovery of novel cephalosporin antibiotic conformers via ligand-based pharmacophore modelling and de novo molecular design.

Antibiotic resistance poses a significant global challenge as bacteria evolve in response to antibiotic use, leading to prolonged hospitalizations, increased healthcare costs, and higher mortality rates. Cephalosporins, a class of beta-lactam antibiotics, are commonly employed to manage infections; however, their misuse and overuse have contributed to resistance development. In response, in silico methods have emerged as cost-effective and efficient tools for drug discovery.

Research experience and career factors in relation to mental health problems: Prevalence, risk factors, and machine learning-based predictive estimates.

Background: Mental health issues, including depression, anxiety, and insomnia, are increasingly prevalent among university students and graduates, especially those involved in academic research. The impact of research-related characteristics on mental health remains underexplored.

Aim: We examined this relationship using machine learning alongside traditional statistical analyses and GIS mapping.

Pretreatment of antioxidative Hodgsonia macrocarpa leaves attenuates anxiety, depression, inflammation, and pain: an in vitro, in vivo, and in silico study.

Ethnopharmacological Relevance: Hodgsonia macrocarpa (Blume) Cogn., known locally in Southeast Asia as bonyo kumra, is a climber traditionally used to treat a wide range of ailments, including headache, body pain, inflammation, fever, wounds, and ulcers. However, experimental assessments of these bioactivities are scarce.

Curcumin delivery and release by using a dual cooperative encapsulation system constructed with ZIF-8 MOFs and silk fibroin/polycaprolactone nanofibers for accelerated wound healing.

The development and design of novel nanofibrous dressings (NFDs) with biomimetic structure and multifunctional properties through electrospinning technique have aroused significant interest in the disciplines of wound treatment. In this study, curcumin (Cur) was firstly incorporated into zeolitic imidazolate framework-8 (ZIF-8), to generate Cur@ZIF-8 nanoparticles, which displayed a homogeneous, consistent, and nearly similar rhombic dodecahedral structure with the mean diameter of ~190 nm. Then the Cur@ZIF-8 was loaded into the silk fibroin (SF)/polycaprolactone (PCL) hybrid nanofibers to obtain a NFD through an electrospinning strategy.

Targeting MMP-7 in idiopathic pulmonary fibrosis: An integrative in vivo and in silico evaluation of the therapeutic potential of Tylophora indica.

Background: Idiopathic pulmonary fibrosis (IPF) is a degenerative pulmonary condition marked by a substantial accumulation of extracellular matrix and chronic inflammation. Matrix metalloproteinase-7 (MMP-7) is integral to fibrosis and likely a curative focus. This study investigates the therapeutic potential of Tylophora indica (T.

Oxidative Stress in DNA Damage and Neurodegenerative Diseases: Unveiling The Mechanisms and Therapeutic Opportunities.

Oxidative stress is marked by disproportionate levels of reactive oxygen species (ROS) and antioxidant defenses and is a key factor in initiating DNA damage and neurodegenerative diseases. Increased reactive oxygen species (ROS) levels can lead to oxidative DNA lesions, disrupting cellular function and contributing to genomic instability. Oxidative stress is linked to neuronal degeneration, particularly in conditions such as Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD), where DNA damage accelerates the progression of these disorders.

Functional Yogurt: Enhancing Color Stability, Functional Quality, and Storage Life With Malabar Spinach ( L.) Fruit.

Malabar spinach ( L.) is a leafy green vegetable rich in betalains, and is found in its fruit. It is also rich in bioactive and antioxidant compounds.

Analyzing the Challenges and Opportunities Associated With Harnessing New Antibiotics From the Fungal Microbiome.

The rapid rise in antibiotic resistance is a critical global health issue, and few new classes of antibiotics have been discovered since 1990 compared to the antibiotic's golden era between 1950 and 1970. However, developing new antimicrobial compounds faces many challenges, improvements in cultivation methods, genetic engineering, and advanced technologies are opening new paths for discovering and producing effective antibiotics. This study focuses on the fungal microbiome as a promising source of new antibiotics.

FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data.

Pneumonia, a severe lung infection caused by various viruses, presents significant challenges in diagnosis and treatment due to its similarities with other respiratory conditions. Additionally, the need to protect patient privacy complicates the sharing of sensitive clinical data. This study introduces FLPneXAINet, an effective framework that combines federated learning (FL) with deep learning (DL) and explainable AI (XAI) to securely and accurately predict pneumonia using chest X-ray (CXR) images.

An explainable and federated deep learning framework for skin cancer diagnosis.

Skin cancer (SC) is the most prominent form of cancer in humans, with over 1 million new cases reported worldwide each year. Early identification of SC plays a crucial role in effective treatment. However, protecting patient data privacy is a major concern in medical research.

Determinants of Modern Contraception Use Among Ever-Married Women in Bangladesh: A Nationwide Cross-Sectional Study.

Background And Aims: Contraception involves the deliberate prevention of conception through various methods, including mechanical devices, medications, behavioral strategies, or surgical techniques. This study aims to assess the socioeconomic and demographic determinants influencing the adoption of modern contraceptive methods among women.

Methods: A cross-sectional study design was employed, using data from the Bangladesh Demographic and Health Survey (BDHS) 2017-2018.

In silico evaluation and therapeutic targeting of LVDD9B protein for WSSV inhibition: molecular and ecological insights for aquaculture solutions.

Unlabelled: This study aimed to investigate structural dynamics, binding interactions, stability, pharmacokinetics, ecological risks, and bioactivity of shrimp receptor protein LVDD9B to identify potential therapeutic candidates against White Spot Syndrome Virus (WSSV). LVDD9B protein's 3D structure was predicted using SWISS-MODEL and validated with ProSA and Ramachandran plots. Protein-protein docking between LVDD9B and VP26 (WSSV protein) was performed using HADDOCK 2.

Joint modelling of anthropometric child undernutrition indicators to identify their risk factors in Bangladesh: evidence from the Multiple Indicator Cluster Survey (MICS) 2019.

Objective: Stunting, wasting and underweight are the three widely recognised indicators of child undernutrition. This study aimed to simultaneously model all indicators while accounting for their association using a joint modelling technique to identify their risk factors.

Design: This was a cross-sectional study design.

Insecticide susceptibility and knockdown resistance mutations in Aedes aegypti and Culex species in Bangladesh.

Insecticide resistance in mosquito populations remains a formidable challenge for the control of vector-borne diseases, especially in developing countries such as Bangladesh. This study investigates known knockdown resistance (kdr) mutations associated with pyrethroid resistance in Aedes aegypti and Culex species mosquitoes collected from Dhaka and Tangail cities. Deltamethrin-based CDC-bottle bioassays showed that Aedes aegypti had resistance rates of 39.

Modulating Ferroptosis in Aging: The Therapeutic Potential of Natural Products.

Aging is a multifactorial process driven by accumulating cellular damage. Ferroptosis-an iron-dependent, lipid peroxidation-mediated form of cell death-has emerged as a critical contributor to age-related tissue degeneration. This review synthesizes current evidence linking ferroptosis to key aging hallmarks, including oxidative stress, chronic inflammation, mitochondrial dysfunction, and dysregulated iron metabolism.

Effect of Degree of Milling (DOM) on Physicochemical and Nutritional Quality of Selected Rice Variety (BRRI dhan78).

Rice, a staple for over half the global population, undergoes milling that removes bran and germ, impacting its nutrient content, physical properties, and glycemic response. The study was conducted to estimate the effects of the degree of milling (DOM) on the physicochemical, nutritional quality, blood glucose response (GR) and glycemic index (GI) of the BRRI dhan78. Rice samples collected from BRRI were milled at 0% (brown rice), 5% (partial milled), and 10% (full milled).

Clinically proven natural products against breast cancer, with mechanistic insights.

Background: Breast cancer still stands to be the foremost contributor to cancer-related incidence and mortality in women globally accounting for about 14% of all female cancer-related deaths worldwide. This research seeks to illustrate the mechanisms and clinical findings of natural products against breast cancer treatment.

Methodology: Required data for this review article was retrieved employing several readily obtainable search databases, including Web of Science (Thomson Reuters, USA), PubMed (U.

Anemia diagnosis from clinical records leveraging tree-driven and XAI-enhanced machine learning.

South Asian countries are highly vulnerable to anemia- a condition affecting numerous children, women, and adolescents. Early detection and effective treatment of anemia could significantly reduce its prevalence. Therefore, in this study, we leveraged clinical records from a Bangladeshi Hospital to develop an adaptive machine learning framework designed to predict anemia by analyzing patients' hematological parameters.

Coumarin derivatives as anticancer agents targeting PI3K-AKT-mTOR pathway: a comprehensive literature review.

Coumarin is a natural benzopyrone compound known for its diverse pharmacological activities, including anticancer, anti-inflammatory, and antioxidant properties. But its derivatives' exploration in cancer, specially PI3K-AKT-mTOR pathways-based cancer activity not explored yet. This review aims to evaluate the anticancer potential of coumarin derivatives' by exploring their modulatory effects on the PI3K-AKT-mTOR signaling pathway across diverse cancer types.

Role of paternal Oryza sativa Baby Booms (OsBBMs) in initiating de novo gene expression and regulating early zygotic development in rice.

Oryza sativa BABY BOOM 1 (OsBBM1), a member of the AP2/ERF family of transcription factors, is expressed from paternal allele in rice zygote and plays a crucial role in initiating zygotic development. However, the mechanism how the paternal OsBBM1 drives this development remains unclear. Rice zygotes with four different gamete combinations with or without functional paternal OsBBMs were produced by electrofusion, using gametes isolated from bbms triple mutants and wild-type rice plants.

Anticancer potential of daidzin: a comprehensive literature review.

Daidzin (DZN), a naturally occurring isoflavone extracted from leguminous plants such as soybeans, has gained significant attention for its anticancer properties. This study provides a comprehensive overview of the pharmacokinetics (PKs), botanical sources, and therapeutic potentials of DZN, focusing on its mechanistic insights into cancer prevention and treatment. For the study, data were collected from databases such as PubMed, Google Scholar, Web of Science, and other reputable sources.

Probing the sensing potential of Nb- and Mo-based MXene nanosheets and their heterostructures for air pollutants: a DFT insight.

In this study, we utilized density functional theory (DFT) with plane-wave calculations to investigate the gas-sensing capabilities of Mo- and Nb-based MXene nanosheets, including NbC, NbN, MoC, and MoN, as well as their heterostructures (NbMoC and NbMoN). We focused on assessing their effectiveness in detecting hazardous airborne gases, such as carbon monoxide (CO) and nitrogen monoxide (NO). The adsorption energy, charge transfer, work function, and electronic properties of the nanosheets and their heterostructures were examined to understand their adsorption behavior.