Lipoxygenase Inhibitor From Endophytic Fungus Cladosporium ramotenellum Associated With Argemone mexicana L.

Argemone mexicana is one of the known herbaceous plants hosting bioactive isoquinoline alkaloids. In the current study, an endophytic fungal isolate was studied for anti-inflammatory potential and the identification of its bioactive molecule. An endophytic fungus AMEF-14 was obtained from this plant and identified as Cladosporium ramotenellum based on microscopy and molecular tools.

Impact of acid and alkali treatments on the nutritional, functional, and structural properties of hull-less barley flour.

Barley is an underutilized crop with considerable potential for enhancing food security and sustainability. Hull-less barley is a nutrient-dense cereal grain rich in β-glucan and dietary fiber; however, its broader application in food systems is constrained by the presence of antinutritional factors and certain functional limitations that affect processing and bioavailability. This study investigated the effects of acid (1% HCl) and alkali (1% NaOH) treatments on two hull-less barley varieties (PL 891 and BHS 352), with emphasis on nutritional composition, antinutrient reduction, functional behavior, thermal transitions, and microstructural attributes.

Ligand-based virtual screening to discover potential inhibitors of SARS-CoV-2 main protease.

The main protease (M, also known as 3CL), a pivotal enzyme of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been considered a prime target for drug development due to its crucial role in viral replication and transcription. Importantly, a high degree of conservation in more than 13 million SARS-CoV-2 sequences affords M as a promising target for antiviral therapy to impede the genetic evolution of SARS-CoV-2. In this work, ∼16 million compounds from various small molecule databases were screened using ligand-based virtual screening (LBVS) with boceprevir as the reference compound to identify new small molecule inhibitors of M.

An intelligent fault detection (IFD) system for lithium-ion battery using machine learning approach.

In recent years, electric vehicles (EVs) have become increasingly popular, driven by advancements in battery technology, growing environmental awareness, and the demand for sustainable transportation. Compared to internal combustion engines, EVs not only produce fewer emissions but also offer greater energy efficiency, leading to reduced operating costs. Despite these advantages, concerns about battery failures have been a significant safety issue for EVs.

A Deep Learning and Explainable Artificial Intelligence based Scheme for Breast Cancer Detection.

Incorporating Artificial Intelligence (AI) presents significant potential for transforming multiple aspects of the healthcare sector, encompassing administration, medical prediction, decision-making, and diagnostics. However, its often perceived enigmatic nature is a significant barrier to the widespread use of AI in the medical field. AI systems, specifically deep learning models, have demonstrated exceptional performance, often comparable to that of humans.

Machine Learning Prediction of 3D Domain Swapping Proteins in Medicinal Plants.

3D domain swapping is a protein structural phenomenon in which two or more protein subunits exchange identical structural subunits and form oligomers. Proteins that exhibit 3D domain swapping play a crucial role in various biological functions, such as secondary metabolite biosynthesis, and in coping with several biotic and abiotic stresses in medicinal plants. This study investigates the ability to predict 3D domain swapping patterns among the genomes of medicinal plants using random forest and K-nearest neighbor classifiers models, demonstrating accuracies of 91.

Unmasking anti-forensic techniques: A DCNN-driven approach to uncover contrast enhancement and median filtering detection.

A forensic analyst must utilize a variety of artifacts in order to create a potent forensic method. By eliminating these artifacts, anti-forensic approaches seek to elude forensic detectors. The field of digital image forensics has many difficulties due to the growing sophistication of anti-forensic tactics.

The lipid partners of plant membrane transporters in salinity stress response.

Plant membrane transporters are essential for perceiving salinity stress, transducing signals, and mitigating stress during salt exposure. These proteins reside in the membrane and are modulated by various cellular components, including membrane lipids. Certain specific lipids are known to modulate the activity of plant membrane transporters, influencing their structure, function, and distribution within the membrane.

Period-doubling cascade to chaos and optimal quadratic harvesting in a prey-predator-scavenger model using Crowley-Martin functional response.

In the present article, a prey-predator-scavenger model is proposed and investigated with quadratic harvesting of predator and scavenger populations. The system is assumed to follow the Crowley-Martin functional response to describe the interaction between prey and predator populations. The positivity and boundedness of the system with respect to positive initial conditions are established.

Enhancing Early GI Disease Detection with Spectral Visualization and Deep Learning.

Timely and accurate diagnosis of gastrointestinal diseases (GIDs) remains a critical bottleneck in clinical endoscopy, particularly due to the limited contrast and sensitivity of conventional white light imaging (WLI) in detecting early-stage mucosal abnormalities. To overcome this, this research presents Spectrum Aided Vision Enhancer (SAVE), an innovative, software-driven framework that transforms standard WLI into high-fidelity hyperspectral imaging (HSI) and simulated narrow-band imaging (NBI) without any hardware modification. SAVE leverages advanced spectral reconstruction techniques, including Macbeth Color Checker-based calibration, principal component analysis (PCA), and multivariate polynomial regression, achieving a root mean square error (RMSE) of 0.

Imipenem-induced outer membrane vesicles from Elizabethkingia anophelis inhibit biofilm formation and shift nosocomial pathogen dynamics.

Elizabethkingia anophelis is an emerging multidrug-resistant Gram-negative pathogen that can cause severe nosocomial infections. Although multidrug resistance complicates the clinical management of E. anophelis, the ecological impact of stress responses, including antibiotic pressure, is unclear.

Molecularly Imprinted Magnetic Fluorescent Carbon Dots Using Polydopamine with Dual Functionality as a Monomer and Cross-Linking Agent for Selective Mefenamic Acid Detection.

This research presents a sustainable and efficient method for synthesizing polydopamine imprinted magnetic carbon dots (MCDs@PI), which were synthesized from wheat straw via hydrothermal carbonization. The carbon dots were magnetically functionalized using iron salts and coated with a polydopamine layer, where dopamine acted as a functional monomer as well as a cross-linker. The sensor demonstrated high selectivity and sensitivity for mefenamic acid, achieving a limit of detection of 2.

Comparative analysis of three-pillared and four-pillared synthetic glucose receptor using molecular dynamics simulations: a case study.

The advancement of computational molecular modeling has significantly enhanced the development of synthetic glucose receptors, addressing one of the most challenging problems in glucose recognition. This study explores the design and analysis of both three-pillared and four-pillared synthetic glucose receptors. Using polar (1,2-Bis(3-methylureido)benzene) pillars combined with benzene, biphenyl, and phenanthrene fragments as apolar surfaces, we have designed novel receptors.

RetinoDeep: Leveraging Deep Learning Models for Advanced Retinopathy Diagnostics.

Diabetic retinopathy (DR), a leading cause of vision loss worldwide, poses a critical challenge to healthcare systems due to its silent progression and the reliance on labor-intensive, subjective manual screening by ophthalmologists, especially amid a global shortage of eye care specialists. Addressing the pressing need for scalable, objective, and interpretable diagnostic tools, this work introduces RetinoDeep-deep learning frameworks integrating hybrid architectures and explainable AI to enhance the automated detection and classification of DR across seven severity levels. Specifically, we propose four novel models: an EfficientNetB0 combined with an SPCL transformer for robust global feature extraction; a ResNet50 ensembled with Bi-LSTM to synergize spatial and sequential learning; a Bi-LSTM optimized through genetic algorithms for hyperparameter tuning; and a Bi-LSTM with SHAP explainability to enhance model transparency and clinical trustworthiness.

A Light-Up Fluorescent Probe for Detection of Reactive Oxygen Species and a Nerve Gas Simulant: Applications in Environmental, Cellular, and Vapor Phases.

A turn-on fluorescent probe, TPIHB, featuring a hydrazinobenzothiazole-appended phenanthroimidazole core, was developed for dual-channel sensing of reactive oxygen species, hypochlorite, and nerve agent simulant diethyl chlorophosphate (DCP), through two distinct mechanistic pathways in biological settings and vapor-phase applications. The probe lighted up with a strong blue signal at 437 nm due to the formation of triazole TPITT through the hypochlorite-induced intramolecular oxidative cyclization. In contrast, DCP-triggered protonation of the secondary nitrogen led to the formation of ICT-enabled TPIHB-DH, resulting in a bright cyan emission at 458 nm in an aqueous THF medium.

Application of stubble waste biochar in cementitious composites: the impact of pyrolysis temperature on its characteristics and cementitious performance.

This study investigates the impact of biochar production temperature on its physicochemical properties and performance as a partial replacement ofcementin mortar mixes. Rice stubble biochar was produced at 450 °C (BC) and 550 °C (BC) with consistent pyrolysis conditions of 120-minute residence time and 10 °C/min heating rate. The produced biochar's were characterized for various physiochemical characteristics using Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Fluorescence (XRF), proximate analysis, pH, and water retention capacity assessments.

Ruthenium(II)-catalyzed C-2 alkenylation of indole with olefins a quinazolin-4(3)-one directing group: a platform for selective fluorescent anion sensors.

We report a ruthenium(II)-catalyzed C-H alkenylation of 2-(1-indol-3-yl)quinazolin-4(3)-one with various alkenes. The reaction proceeds selectively at the C2 position of the indole moiety, facilitated by a cyclic amide as the directing group. Furthermore, the synthesized compounds were evaluated for their photophysical properties, revealing intriguing fluorescence characteristics that highlight their potential as promising fluorescent probes.

DeepHybrid-CNN: A hybrid approach for pre-processing of skin cancer images.

In the current technological era, digital imaging is ubiquitous, and it serves a crucial purpose in the realm of medical research. Skin cancer is one of the most common types of cancer, and its early diagnosis is essential to reduce the mortality rates. An impediment that must be overcome to identify essential image details for computerized cancer segmentation effectively and classification is the presence of a variety of noise types, as well as hair in the acquired skin lesion images.

Assessment of the Efficiency of Vaccination and Short-term Isolation in Lowering the Disease Load in Koalas Population.

Koala populations in some regions of eastern Australia are in critical condition. Our research aims to develop effective conservation strategies for these declining koalas threatened by chlamydia infection, predation, and climate change. To achieve this, we developed a mathematical model that includes populations of dingoes and koalas categorized as susceptible, infected, and confined.

The interplay of ferroptosis and oxidative stress mechanisms: a critical contributor to chronic obstructive pulmonary disease pathophysiology.

Ferroptosis, a recently discovered iron-dependent regulated form of cell death, is characterised by lipid peroxidation and oxidative stress. Recent studies suggested that ferroptosis plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD), a progressive and irreversible lung disorder, marked by airflow limitation, emphysema, and chronic bronchitis. Cigarette smoke (CS), one of the prominent risk factors for COPD, is known to induce ferroptosis by generating reactive oxygen species (ROS), depleting antioxidant defences, such as glutathione and glutathione peroxidase 4, and disrupting iron homeostasis.

Alarming implications: severe fever with thrombocytopenia syndrome and its biological vectors in the context of climate change.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne zoonotic disease. Since its identification in China in 2009, reports of SFTS cases have steadily increased, posing a significant threat to public health. This review summarizes the epidemiological characteristics of SFTS and its biological vectors, with a particular emphasis on the role of the tick vector in disease transmission.

Effect of rGO synthesized from different precursors on the enhancement in mechanical properties of GFRPs.

This study investigates and compares the impact of various precursor-based reduced graphene oxide (rGO) nanofillers, prepared through chemical and thermal reduction methods on the mechanical properties of E-glass fiber-reinforced epoxy resin composites (GFRPs). Varying amounts of rGO derived from semi-anthracite coal-based graphene oxide (AC-rGO) and graphite-based graphene oxide (Gr-rGO), synthesized via thermal reduction and chemical reduction (AC-GT, Gr-GT, AC-GC, and Gr-GC) into an epoxy resin matrix were dispersed into an epoxy resin matrix. The resulting mixture was infused into E-glass fiber mats to fabricate multiscale composites using vacuum-assisted resin infusion molding technique.

Algae-based nanoparticles for enhancing sustainable applications in integrated food-water ecosystem.

Over the past decade with the ever-increasing population growth, the concurrent demands for food and water have risen, thus significantly affecting sustainability. Recently, biogenic nanoparticles produced from algal biomass inherently rich in secondary metabolites have garnered huge attention to sort the complexities related to food-water nexus. This critical review aims to explore recent advancements in the synthesis, characterization, and functional properties of algae-based nanoparticles (ANPs), highlighting their role in supporting sustainable solutions across the food and water sectors.

Genomic Analysis and Biomineralization Efficacy of Bacillus megaterium SS3 for Improving Durability Properties of Building Material.

Urease-producing microorganisms play an important role in biomineralization through microbially induced calcium carbonate precipitation (MICCP), contributing to enhanced durability and extended lifespan of construction materials in civil engineering. This study investigates the MICCP capabilities of a ureolytic strain, Bacillus megaterium SS3, isolated from alkaline calcareous soil, which showed native adaptation to high-pH environments typical of cementitious materials. Bacillus megaterium exhibited maximum urease activity (625 U/mL) and promoted CaCO precipitation up to 177.