Long non-coding RNAs: Silent contributors to plant survival under abiotic stress.

Abiotic challenges have a major impact on plant growth and development. Recent research has highlighted the role of long non-coding RNAs in response to these environmental stressors. Long non-coding RNAs are transcripts that are usually longer than 200 nucleotides with no potential for coding proteins.

Polyherbal gel formulation with , , and : A preclinical evaluation for accelerated wound healing in diabetic foot ulcers.

A common and fatal consequence of diabetes, diabetic foot ulcers (DFU) are linked to an increased risk of mortality and amputation. The current study aimed to develop and evaluate a polyherbal gel formulation (PGF) employing hydro-alcoholic extracts of (fruits), (leaves), (fruits), and (bark) at different concentrations for the efficient treatment and management of DFU. The anti-oxidant, anti-diabetic, anti-inflammatory, anti-bacterial, and wound healing activities of PGFs were investigated using a range of cell-based assays and animal models.

Urban cooling through pavement innovation: a review of strategies and materials.

One of the major problems caused by the fast and unplanned growth of cities is the Urban Heat Island (UHI) effect. This happens when urban areas, especially pavements, become much hotter than the surrounding countryside, mainly during summer. The heat builds up on surfaces like roads and sidewalks because they absorb and store heat from the sun.

Biofuel production from starchy crops: advanced technology and current perspectives.

The sustainable replacement of conventional fossil fuels with bioethanol produced from starchy crops has garnered significant interest. This review paper provides current perspectives in the field and an overview of advanced technologies, emphasising the importance of efficient and environmentally friendly processes. Starchy crops such as wheat, barley, cassava, potato, and maize possess high starch content, which serves as a key feedstock for bioethanol production.

Transfer Learning for Automated Two-class Classification of Pulmonary Tuberculosis in Chest X-Ray Images.

Aim: Early and precise diagnosis is essential for effectively treating and managing pulmonary tuberculosis. The purpose of this research is to leverage artificial intelligence (AI), specifically convolutional neural networks (CNNs), to expedite the diagnosis of tuberculosis (TB) using chest X-ray (CXR) images.

Background: Mycobacterium tuberculosis, an aerobic bacterium, is the causative agent of TB.

Exploring novel green synthetic pathways and recent advances in pyrrole and its derivatives.

Pyrrole has fascinated scientists since its first isolation in the 19th century, particularly due to its importance in natural compounds such as heme and chlorophyll. Its unique aromatic structure and diverse reactivity have established it as a key building block in both organic and medicinal chemistry. Over the years, the interest in pyrrole derivatives has grown, especially as researchers seek greener and more sustainable synthesis methods.

A Deep Neural Network Framework for the Detection of Bacterial Diseases from Chest X-Ray Scans.

Aims: This research aims to develop an advanced deep-learning framework for detecting respiratory diseases, including COVID-19, pneumonia, and tuberculosis (TB), using chest X-ray scans.

Methods: A Deep Neural Network (DNN)-based system was developed to analyze medical images and extract key features from chest X-rays. The system leverages various DNN learning algorithms to study X-ray scan color, curve, and edge-based features.

Safety assessment of Detarium microcarpum Guil. & Perr. (Leguminosae) root bark extract in rats: Acute, sub-acute toxicity, ADMET, molecular docking, and molecular dynamics simulations approach.

Since the last decades, Detarium microcarpum have been used and studied due to the significant properties to threat various ailments. It is therefore crucial to ascertain the safety properties of is phytoconstituents. The present study was taken up to investigate the oral acute toxicity, 28 days repeated oral sub-acute toxicity study of D.

A Framework for Two-class Classification of Pulmonary Tuberculosis using Artificial Intelligence.

Aim: The study investigates the creation and assessment of Machine Learning (ML) models using different classifiers such as SVM (Support Vector Machine), logistic regression, decision tree, k-nearest neighbour (kNN), and Artificial Neural Network (ANN) for the automated identification of tuberculosis (TB) from chest X-ray(CXR) images.

Background: As a persistent worldwide health concern, TB requires early detection for effective treatment and control of the infection. The differential diagnosis of TB is a challenge, even for experienced radiologists.

Intronic region polymorphisms of autophagy gene ATG16L1 predispose individuals to Hepatitis B virus infection.

Intronic region polymorphisms, rs2241879 G/A, rs13005285 G/T, and rs7587633 C/T of ATG16L1 were analyzed in this case-control study in HBV-infected patients to find their role in HBV infection. The mutant alleles rs2241879A (OR = 1.57) and rs13005285T (OR = 1.

Almond consumption for 8 weeks differentially modulates metabolomic responses to an acute glucose challenge compared to crackers in young adults.

This study investigated the dynamic responses to an acute glucose challenge after 8 weeks of almond or cracker consumption (clinicaltrials.gov ID: NCT03084003). Young adults (n = 73, age: 18-19 years, BMI: 18-41 kg/m) participated in an 8-week randomized, controlled, parallel-arm intervention and were assigned to consume either almonds (2 oz/d, n = 38) or an isocaloric control snack of graham crackers (325 kcal/d, n = 35) daily.

Computational Model to Predict Potential Therapeutic Targets Employing Generative Adversarial Networks for Analysis of Proteins Involved in Mycobacterium fortuitum Biofilm Formation.

A planktonic population of bacteria can form a biofilm by adhesion and colonization. Proteins known as "adhesins" can bind to certain environmental structures, such as sugars, which will cause the bacteria to attach to the substrate. Quorum sensing is used to establish the population is dense enough to form a biofilm.

GTF2I acts as a novel tumor suppressor transcription factor and shows Favorable prognosis in renal cancer.

The role of GTF2I (General Transcription Factor2I) alteration has already been reported in thymic cancer as a valuable biomarker. However, the association of GTF2I mutation with renal cancer for prognosis of immunotherapy is not yet examined. The biologic and oncologic significance of GTF2I in renal cancer was examined at multiomics level such as mutation, copy number alteration, structural variants.

AlzGenPred - CatBoost-based gene classifier for predicting Alzheimer's disease using high-throughput sequencing data.

AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement in next-generation sequencing, an enormous amount of AD-associated genomics data is available. However, the information about the involvement of these genes in AD association is still a research topic.

Autophagy-related gene BECN1 single nucleotide polymorphisms in diseases.

Autophagy is a cytoprotective process that operates within a cell to maintain cellular homeostasis. An array of multiple proteins is involved to mediate this conserved cellular process. Among these, Beclin 1 protein encoded by BECN1 gene plays a crucial role during the initiation of autophagy.

Impact of Hydro-Alcoholic Bark Extract on Diabetic Wound Healing: A Topical Approach.

Purpose: The current study was aimed to evaluate the potential of against diabetic foot ulcer, where the wound healing is impaired and susceptible to infection.

Methods: The effects of hydroalcoholic bark extract (MOHE) on different parameters influencing diabetic wound healing were comprehensively investigated including: anti-inflammatory effects, antibacterial properties, antioxidant activity, anti-diabetic properties, and fibroblast proliferation and migration. Furthermore, in vivo studies were conducted in diabetic rats and Zebrafish to investigate the topical effects of MOHE on wound healing.

A semantic segmentation framework with UNet-pyramid for landslide prediction using remote sensing data.

Landslides are frequent all over the world, posing serious threats to human life, infrastructure, and economic operations, making them chronic disasters. This study proposes a novel landslide detection methodology that is automated and based on a hybrid deep learning approach. Currently, Deep Learning is constrained by the lack of applicability, lack of data, and low efficiency in landslide detection but with recent advancement in deep learning-based solutions for landslide detection has sparked considerable advantages over traditional techniques.

Proteogenomic Approaches for Diseasome Studies.

During the last three decades, technological advancements in high-throughput next-generation sequencing have resulted in an increased understanding of proteomic and genomic data, aptly termed proteogenomics. Efforts in developing such approaches have not only been limited but also focused on protein identification and subcellular localization. These approaches, however, have also been explored for their broad understanding of how genomics/transcriptomics data have yielded measures, for example, gene expression regulation/signal cascading and diseasome studies.

Unveiling the Self-assembly and Therapeutic Efficacy of Antimicrobial Peptides SA4 Against Multidrug-Resistant A. baumannii.

Infections linked to Acinetobacter baumannii are one of the main risks of modern medicine. Biofilms formed by A. baumannii due to a protective extracellular polysaccharide matrix make them highly tolerant to conventional antibiotics and raise the possibility of antibiotic resistance.

Simultaneous Production of Biogas and Electricity from Anaerobic Digestion of Pine Needles: Sustainable Energy and Waste Management.

Power scarcity and pollution can be overcome with the use of green energy forms like ethanol, biogas, electricity, hydrogen, etc., especially energy produced from renewable and industrial feedstocks. In hilly areas, pine needles are the most abundant biomass that has a low possibility of valorization due to high lignin content.

Identification of key genes and molecular pathways regulating heat stress tolerance in pearl millet to sustain productivity in challenging ecologies.

Pearl millet is a nutri-cereal that is mostly grown in harsh environments, making it an ideal crop to study heat tolerance mechanisms at the molecular level. Despite having a better-inbuilt tolerance to high temperatures than other crops, heat stress negatively affects the crop, posing a threat to productivity gain. Hence, to understand the heat-responsive genes, the leaf and root samples of two contrasting pearl millet inbreds, EGTB 1034 (heat tolerant) and EGTB 1091 (heat sensitive), were subjected to heat-treated conditions and generated genome-wide transcriptomes.

Vitamin K3 derivative inhibits androgen receptor signaling in targeting aggressive prostate cancer cells.

Prostate cancer (PCa) is the second critical cause of cancer-related deaths, with African Americans dying at higher rates in the U.S. The main reasons for the higher mortality rate are ethnic differences and lack of understanding of prostate cancer biology and affordable treatments, as well as the financial burden of African American men to obtain the most effective and safe treatments.

PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.

Protein methyltransferases (PMTs) are a group of enzymes that help catalyze the transfer of a methyl group to its substrates. These enzymes play an important role in epigenetic regulation and can methylate various substrates with DNA, RNA, protein, and small-molecule secondary metabolites. Dysregulation of methyltransferases is implicated in various human cancers.

Harnessing extracellular vesicles-mediated signaling for enhanced bone regeneration: novel insights into scaffold design.

The increasing prevalence of bone replacements and complications associated with bone replacement procedures underscores the need for innovative tissue restoration approaches. Existing synthetic grafts cannot fully replicate bone vascularization and mechanical characteristics. This study introduces a novel strategy utilizing pectin, chitosan, and polyvinyl alcohol to create interpenetrating polymeric network (IPN) scaffolds incorporated with extracellular vesicles (EVs) isolated from human mesenchymal stem cells (hMSCs).