A Comprehensive Review on Exploring the Potential of Phytochemicals and Biogenic Nanoparticles for the Treatment of Antimicrobial-Resistant Pathogenic Bacteria.

Antimicrobial resistance (AMR) is an escalating global health concern that results in approximately 700,000 deaths annually owing to drug-resistant infections. It compromises the effectiveness of conventional antibiotics, as well as fundamental medical procedures, such as surgery and cancer treatment. Phytochemicals, natural plant constituents, and biogenic nanoparticles synthesized through biological processes are pharmacological alternatives for supplementing or replacing traditional antibiotics.

Bio-fabrication of chitosan-stabilized magnesium oxide nanomaterials: Investigation of photocatalytic, in vitro cytotoxicity activities and apoptosis in oral squamous carcinoma cells.

A bio-fabrication approach is a novel way to develop chitosan-stabilized magnesium oxide nanomaterials (cMgO-NMs). The process involves utilizing polymeric chitosan as the reducing and stabilizing agent. The characteristics of the developed cMgO-NMs were determined using various spectroscopical techniques.

TiO-sodium alginate core-shell nanosystem for higher antimicrobial wound healing application.

Wounds that are not properly managed can cause complications. Prompt and proper care is essential, to prevent microbial infection. Growing interest in metal oxide nanoparticles (NPs) for innovative wound treatments targeting healing and microbial infections.

Dynamics of pollution and trophic status in selected sub-tropical surface water bodies in Haridwar district, India.

This study provides a detailed approach to evaluating water quality in the Haridwar district, Uttarakhand, India, by integrating physicochemical and microbiological investigations. It employs multivariate analysis and applies water quality and trophic state indices to evaluate the current state of the water and identify potential sources of contamination. The results from the correlation matrix highlight the dynamic interactions between different water quality parameters.

Evaluating energy consumption patterns in novel foamed ternary alkali-activated masonry blocks.

This study endeavors to tackle the energy requirements of the building sector by employing passive design strategies. However, there exists a dearth of comprehension regarding the energy efficiency performance of foamed alkali-activated materials. To bridge this research gap, the study proposes a solution in the form of a thermally proficient wall material crafted from ceramic tile dust (CTD), class C fly ash (FA), and Ground Granulated Blast-Furnace Slag (GGBS), all of which are industrial by-products.

Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2.

The disease affects the optic nerve and represents the principle reasons of irreversible vision loss, mostly asymptomatic and uncontrolled. Consequently, early and accurate diagnosis is critical to prevent or reduce its effect, however, conventional diagnostic techniques often fail to provide concrete results. In this regard, we present a new approach built on Generative Adversarial Networks (GAN) and MobileNetV2 pretrained architecture for diagnosing glaucoma.

Bougainvillea glabra-mediated synthesis of Zr₃O and chitosan-coated zirconium oxide nanoparticles: Multifunctional antibacterial and anticancer agents with enhanced biocompatibility.

The effectiveness and safety of nanomaterials (NMs) are essential for their use in healthcare. This study focuses on creating NPs with multifunctional antibacterial and anticancer properties to combat bacterial infections and cancer disease more effectively than traditional antibiotics. This study investigates the synthesis of ZrO and chitosan (ch) coated zirconium oxide nanoparticles (chZrO NPs) using Bougainvillea glabra (B.

Analysis of RL electric circuits modeled by fractional Riccati IVP via Jacobi-Broyden Newton algorithm.

This paper focuses on modeling Resistor-Inductor (RL) electric circuits using a fractional Riccati initial value problem (IVP) framework. Conventional models frequently neglect the complex dynamics and memory effects intrinsic to actual RL circuits. This study aims to develop a more precise representation using a fractional-order Riccati model.

Predicting Color Development and Texture Changes in Tomatoes Treated With Hot Water and Exposed to High-Temperature Ethylene Using Support Vector Regression.

This study investigated the impacts of hot water treatment (HWT) at 50°C or 25°C for 5 min and high-temperature ethylene (HTE) exposure at varying temperatures (20°C, 30°C, or 35°C) and durations (24, 48, or 72 h) on the postharvest quality and antioxidant properties of mature green tomatoes (MG). Color changes, physicochemical characteristics, antioxidant compounds, and overall antioxidant ability were assessed. HWT increased β-carotene levels and oxygen radical absorbance capacity (ORAC) while preserving color metrics, despite later HTE exposure.

Apoptotic cell death of stomach cancer lines (AGS) induced by Co-NTB complex through cellular organelles and DNA damage.

Given that stomach cancer is the fourth leading cause of cancer-related death, there is a need to develop new drugs. Among various methods, metal-based coordination compounds are considered as an efficient strategy against this type of cancer. Similarly, the benzimidazole moiety plays a crucial role in biology; thus, various benzimidazole-based compounds have been found to be active as potential anticancer drugs and are currently used in clinical trials.

Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning.

Glaucoma, a severe eye disease leading to irreversible vision loss if untreated, remains a significant challenge in healthcare due to the complexity of its detection. Traditional methods rely on clinical examinations of fundus images, assessing features like optic cup and disc sizes, rim thickness, and other ocular deformities. Recent advancements in artificial intelligence have introduced new opportunities for enhancing glaucoma detection.

Cognitive neurodynamic approaches to adaptive signal processing in wireless sensor networks.

In recent years, Wireless Sensor Networks (WSN) have become vital because of their versatility in numerous applications. Nevertheless, the attain problems like inherent noise, and limited node computation capabilities, result in reduced sensor node lifespan as well as enhanced power consumption. To tackle such problems, this study develops a Modified-Distributed Arithmetic-Offset Binary Coding-based Adaptive Finite Impulse Response (MDA-OBC based AFIR) framework.

Limosilactobacillus reuteri fermented brown rice alleviates anxiety improves cognition and modulates gut microbiota in stressed mice.

Chronic stress disrupts gut microbiota homeostasis, contributing to anxiety and depression. This study explored the effects of Limosilactobacillus reuteri fermented brown rice (FBR) on anxiety using an ICR mouse chronic mild stress (CMS) model. Anxiety was assessed through body weight, corticosterone levels, neurotransmitter profiles, and behavioral tests.

Competitive Pasture Species to Suppress the Growth of Annual Riceflower ( Lindl.) at Different Planting Densities and Spatial Arrangements.

This study assessed the effectiveness of four competitive pasture species-Premier digit grass ( Steud. var. Premier), Rhodes grass ( Kunth.

A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells.

Electrochemical energy conversion technologies include proton exchange membrane fuel cells (PEMFCs) where proton interchange is an alternative to diesel distributed generation, and PEMFCs are considered as a promising backup power source and a tool to regulate power consumption. Some of the major benefits of these PEMFCs especially in power system applications include low emission of carbon, fast load following capability, no noise and high start-up reliability. It is challenging to find the best PEMFC parameters because the model is complex and the problem is nonlinear; not all optimization algorithms can solve this problem.

Bifunctional hierarchical WO nanorods@Br-doped g-CN Z-scheme heterojunctions for efficient tetracycline photodegradation: Optimization of key parameters, toxicological assessment, and electrocatalytic hydrogen evolution reaction.

In this study, graphitic carbon nitride (CN) and tungsten trioxide (WO) were successfully incorporated into bromine (Br)-doped graphitic carbon nitride (BCN) using an in-situ hydrothermal method. The photocatalytic efficiency of the resulting WO/Br-doped CN (WBCN) composites for the removal of tetracycline (TC) antibiotics under sunlight irradiation was evaluated. The mass ratio of WO to Br-doped CN (BCN) significantly influenced TC adsorption and photocatalytic degradation, with an optimal ratio of 9:1.

Advanced control parameter optimization in DC motors and liquid level systems.

In recent times, there has been notable progress in control systems across various industrial domains, necessitating effective management of dynamic systems for optimal functionality. A crucial research focus has emerged in optimizing control parameters to augment controller performance. Among the plethora of optimization algorithms, the mountain gazelle optimizer (MGO) stands out for its capacity to emulate the agile movements and behavioral strategies observed in mountain gazelles.

Reproductive toxicity of perfluorobutane sulfonate in zebrafish (Danio rerio): Impacts on oxidative stress, hormone disruption and HPGL axis dysregulation.

Per and polyfluoroalkyl substances (PFAS) are anthropogenic chemicals extensively used in consumer products. Perfluorobutane sulfonate (PFBS), a short-chain PFAS, has been introduced as an alternative to long-chain PFAS, but limited studies have investigated its reproductive toxicity in fish. In this study, adult zebrafish were exposed to PFBS at concentrations of 0.

Fluorescent N-Doped Carbon Dots as a Biocompatible Sensor for Thiophanate-Methyl Detection.

An eco-friendly nitrogen-passivated carbon dot (N-CDs)-based fluorescent sensor was designed for the selective and sensitive detection of thiophanate-methyl, a widely applied fungicide in agriculture. The synthesized N-CDs exhibited robust fluorescence and remarkable photostability, which contributed to the sensor's performance. Notably, the sensor achieved a detection limit as low as 4.

Phytochemical and Antioxidant Analysis of Bioactive Compound Extract from Nelumbo nucifera against Cancer Proteins: In Silico Spectroscopic Approach.

Nelumbo nucifera, an aquatic crop cultivated throughout Asian countries, belongs to the Nelumbonaceae family and has been widely used in traditional medicines with key pharmacological activities such as anti-viral, antipyretic, antioxidant, anti-steroid, anti-inflammatory, anti-arrhythmia, anti-obesity, and anti-aging properties. The present study aims to explore and assess the phytochemical composition, GC-MS profiling, antioxidant efficacy, and the major phytoconstituent phytol subjected to theoretical spectroscopic characterization using the DFT method. The phytochemical profiling of N.

A Carbazole Acrylonitrile Substituted Turn-On Fluorescence Chemosensors for Cyanide Ion and its Application to Real Sample Analysis.

An efficient probe (E)-2-(benzo[d]thiazol-2-yl)-3-(9-ethyl-9 H-carbazol-3-yl)acrylonitrile (CZ-BTZ) for selective fluorescence "turn-on" response with cyanide (CN) ion sensor was developed by simple Knoevenagel condensation of 9-ethyl-9 H carbazole-3-carbaldehyde with 2-(benzo[d]thiazol-2-yl) acetonitrile. The sensing ability of probe CZ-BTZ was tested with different inorganic anions through spectrophotometric and spectrofluorimetric methods. The UV-vis and fluorescence spectral studies show the formation of a new adduct between CZ-BTZ and CN by appearing with a new absorbance band at 350 nm and "turn-on" fluorescence at 535 nm in CHCN: HO (8:2, v/v, pH 7.

Insights into the photocatalytic removal of malachite green organic pollutant by highly efficient hard responsive BaCoDyFeO catalysts.

The widespread discharge of organic dyes into the wastewater from various industrial processes has develop a major environmental apprehension in the modern world. To tackle such environmental issues, we are synthesizing a novel catalyst of composition, BaCoDyFeO (x = y = 0.02-0.

Evaluation of antidiabetic and anti-inflammatory action of selenium nanoparticles mediated through aspalathus linearis - An in vitro study.

Introduction: Selenium nanoparticles (SeNPs) have drawn a lot of interest among researchers because of their distinct impact on antioxidant activity, anti-inflammatory tests, antibacterial activity, and in the treatment of various diseases. A. linearis has shown great findings in biomedical applications because of its physio-chemical compounds such as Aspalathin, orientin, and isoorientin.

Exploration of magnetic zeolite thin film derived from coal fly ash an efficient sorbent: Application to water treatment.

Fly ash, produced during coal combustion for energy making, which is recognized as an industrial by-product, could lead to environmental health hazards. Subsequently, fly ash found that an exceptional adsorption performance for the removal of various toxic pollutants, the adsorption capacity of fly ash might be altered by introducing physical/chemical stimulation. Successfully converting fly ash into zeolites not only recovers their disposal difficulties but also transforms unwanted materials into merchandisable products for various industrial applications.

Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries.

This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. The incorporation of nanotechnology, through the addition of nanoparticles to conventional fuels, improves fuel atomization, combustion efficiency, and emission control. Simultaneously, LSTM models are employed to analyze and predict the complex spray behavior under diverse operational and geometric conditions.