Formulation development, characterization, and optimization of Eudragit-cinnamon essential oil-based nanoplatform and its efficacy against resistant bacteria.

Introduction: Microbial resistance is a growing global concern, necessitating the development of novel drug delivery system to combat the resistant bacterial strains. We aimed to formulate Eudragit based cinnamon essential oil loaded nanoplatform against resistant microbial strain.

Methods: Nanoparticles were characterized for zeta potential, PDI, particle size, SEM, FTIR, entrapment efficiency and drug release kinetic.

Potential of syringol and guaiacol in mitigating hyperglycemia associated dicarbonyl stress in rats subjected to high-fat high-fructose diet.

Objective: The current study assessed the pharmacological potential of syringol and guaiacol, both separately and in combination, in hyperglycemia linked to dicarbonyl stress (DS).

Methods: The control group (n = 5) received a standard diet with Tween 20 and disease group received high-fat high-fructose diet. The remaining four groups received metformin, syringol (100 μg/kg), guaiacol (100 μg/kg), or a combination of both (50 + 50 μg/kg) starting on the 29th day and lasting 30 days.

Biochemical and thermodynamic characterization of a novel α-amylase from Avena fatua for biotechnological applications.

This study reports the production, purification, and characterization of a thermostable, raw starch-hydrolysing α-amylase from Avena fatua seeds. The enzyme was purified to a 16.5-fold increase in purity through a series of steps, including pH adjustment, lyophilization, PEG precipitation, and multiple chromatographic techniques, ultimately achieving a specific activity of 90 U/mg.

Phytochemical Profiling and Dual In Vitro In Vivo Antidiabetic Assessment of Ethyl Acetate Fraction and Essential Oil From Allium ascalonicum.

Allium ascalonicum (shallot) is a traditional medicinal plant recognized for its rich phytochemical content and therapeutic potential. This study aimed to evaluate the phytochemical composition, antidiabetic activity, and toxicity profile of the ethyl acetate fraction and essential oil. GC-MS analysis identified 34 compounds in the ethyl acetate fraction, with major constituents including phenol, 2-methoxy-4-vinyl- (17.

Transcriptome characterisation and population genetics of Hayata - An endangered gymnosperm and implication for its conservation in Vietnam.

Biodiversity loss and degradation activities have a significant impact and devastating consequences on the ecosystem, eventually posing a major threat to many plant species, including . Deforestation and the growth of settlements are the main factors that affect the biodiversity hotspots in Vietnam such as Northwest, Northeast, North Central and Central Highlands regions. This has led to a decline of the species, so effective conservation strategies are urgently required.

Applications of benchtop and portable spectroscopy techniques for food quality monitoring.

Food safety and quality have become major worldwide issues. Because of their quickness, effectiveness, and non-destructive nature, spectroscopy methods are essential for guaranteeing the safety and quality of food items. These techniques include Fourier transform infrared (FTIR), Infrared (IR), Raman spectroscopy, near-infrared (NIR), and Fluorescence spectroscopies, which can be used to evaluate food composition analysis, food adulteration, spoilage indicators, and various levels of contamination.

Spatial distribution of potentially toxic elements and ecological-health risks in a wastewater-irrigated peri-urban agroecosystem: a multi-matrix assessment from Muzaffargarh, Pakistan.

Peri-urban vegetable growing areas are vital for food security but are increasingly threatened by contamination from nearby industrial sites. This study examined potentially toxic element spatial distribution, bioaccumulation, and associated ecological-health risks in vegetables cultivated with wastewater-irrigated soil for over 30 years in southern Punjab, Pakistan. A total of 540 samples of drinking water, soil, and vegetables were collected from three sectors (X, Y, and Z) for comparative analysis.

Discussing the epidemiology of COVID-19 model with the effective numerical scheme.

COVID-19 is a contagion that's container lead to lung difficulties such as pneumonia and, in the greatest severe circumstances, serious respirational disease. In response to these challenges, the present research proposes and analyses an SEIQR model with a nonlinear recovery and incidence rate. The appearance aimed at fundamental threshold quantity [Formula: see text] is established, which is critical to the stability of disease-free and endemic equilibria.

Network-based intrusion detection using deep learning technique.

A high growth rate in network traffic and the complexity of cyber threats have made it necessary to create more effective and flexible intrusion detection systems. Most traditional Network-based Intrusion Detection Systems (NIDS) can become weak at detecting new patterns of attacks due to the use of obsolete data or traditional machine learning models. To overcome the mentioned constraints, the current research presents a new deep learning solution that combines Sequential Deep Neural Networks (DNN) and Rectified Linear Unit (ReLU) activation unit with an Extra Tree Classifier feature selection procedure.

Multi-stage ESO-ADRC for frequency stabilization in off-grid systems with high renewable energy and EV penetration.

Urban hybrid off-grid power systems (UHOGPS) face critical frequency stabilization challenges as renewable energy sources (RES) and electric vehicles (EVs) dominate modern grids, introducing complex nonlinearities, stochastic disturbances, and dynamic uncertainties. To address these limitations, this paper proposes a multi-stage extended state observer with generalized active disturbance rejection control (MSESO-GADRC), a novel framework that hierarchically decomposes disturbances into targeted frequency bands for precise mitigation. The key contribution lies in its multi-stage ESO architecture, which uniquely integrates two-, three-, and four-stage observer configurations with adaptive bandwidth tuning to isolate and suppress low-, medium-, and high-frequency disturbances while compensating for unmodeled dynamics.

Thermostable and solvent-tolerant alkaline protease from Galium aparine: Purification and industrial applications.

A thermostable extracellular alkaline protease was isolated and purified 7.1-fold from Galium aparine using a sequential four-step procedure comprising ammonium sulfate precipitation, ion-exchange chromatography, ultrafiltration, and gel filtration. The purified enzyme, with a monomeric molecular mass of approximately ∼30 kDa as determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), exhibited optimal catalytic activity at pH 8.

Immobilization of -Derived Phytase on Novel Carriers: A Sustainable Approach to Enhance Nutrient Bioavailability in Cereal-Based Foods.

This study investigates the immobilization of phytase onto three solid carriers─sodium alginate/poly(vinyl alcohol) (AlgNa/PVA) beads, glass microspheres, and cellulose beads─for the purpose of phytic acid hydrolysis in food matrices. Phytase was either entrapped within the matrix (AlgNa/PVA, cellulose) or covalently bonded (glass microspheres) for enhanced stability and reusability. Glass microspheres demonstrated superior catalytic performance with higher activity retention and reusability and were thus selected for optimization.

Evaluating the understanding and perception of final-year pharmacy and medical students regarding generic medicines: a cross-sectional study in Abbottabad, Pakistan.

Background: Generic medicines reduce the cost and improve affordability. Having precise knowledge of generic medicine consideration among senior pharmacy and medical students will enhance the impact of generic substitution. The study was conducted to evaluate the understanding and perception of generic medicines among future practitioners (FP, final year pharmacy, and medical students) in Abbottabad, Pakistan.

Fabrication and evaluation of solidified nanoemulsion designs for systemic delivery of atorvastatin through the lung.

To improve the solubility of atorvastatin and overcome the stability issues of liquid nanoemulsion, the current study aimed to synthesize solidified SNEDDS particles with aerodynamic diameter of ≤ 3 μm. The simple and chitosan-decorated liquid SNEDDS were dried by spray drying method and evaluated for their physicochemical properties, release characteristics and aerodynamic performance. A single dose pharmacokinetic study was performed in rabbits to establish the therapeutic performance of solidified nanoemulsion with respect to LIPITOR.

Synthesis of new nicotintaldehyde derivatives via Pd(0) catalyzed suzuki coupling with structural characterization and co-combined computational-experimental evaluation against oral pathogens.

A highly efficient Pd-built catalytic system for the Suzuki Miyaura coupling of nicotinaldehyde was developed under gentle reaction conditions. Analytical techniques included FTIR, Uv-Visible, H NMR, and C NMR, whereas computational analysis used during the investigation involved DFT (density functional theory), Molecular docking, PASS, ADMET and drug likeness. In the current investigation, new nicotinaldehyde derivatives were synthesized via a Pd(0)-catalyzed Suzuki coupling reaction.

End-to-end feature fusion for jointly optimized speech enhancement and automatic speech recognition.

Speech enhancement (SE) and automatic speech recognition (ASR) in real-time processing involve improving the quality and intelligibility of speech signals on the fly, ensuring accurate transcription as the speech unfolds. SE eliminates unwanted background noise from target speech in environments with high background noise levels, which is crucial in real-time ASR. This study first proposes a speech enhancement network based on an attentional-codec model.

Classifying kidney disease using a dense layers deep learning model.

Early diagnosis and thorough management techniques are crucial for people with chronic kidney disease (CKD), a crippling and potentially fatal condition. Research has focused a lot on machine learning and deep learning systems for the detection of kidney diseases. Deep learning platforms like hidden layers, activation functions, optimizers, and epochs are also necessary for the automatic detection of these diseases.

Overcoming Multidrug Resistance in E. coli and Salmonella Isolates from Nile Tilapia: Synergistic Effects of Novel Antibiotic Combinations.

Escherichia coli and Salmonella are significant foodborne zoonotic pathogens, causing serious human illness. The rising global prevalence of antimicrobial resistance (AMR) in these species exacerbates their public health risk, complicating the treatment of bacterial infection. This study investigates its prevalence, resistant genes, and treatment strategy against antibiotic-resistant bacteria, focusing on E.

Demystifying diagnosis: an efficient deep learning technique with explainable AI to improve breast cancer detection.

As per a WHO survey conducted in 2023, more than 2.3 million breast cancer (BC) cases are reported every year. In nearly 95% of countries, the second leading cause of death for females is BC.

Multimodal hate speech detection: a novel deep learning framework for multilingual text and images.

The rapid proliferation of social media platforms has facilitated the expression of opinions but also enabled the spread of hate speech. Detecting multimodal hate speech in low-resource multilingual contexts poses significant challenges. This study presents a deep learning framework that integrates bidirectional long short-term memory (BiLSTM) and EfficientNetB1 to classify hate speech in Urdu-English tweets, leveraging both text and image modalities.

Determination of risk factors for foot and mouth disease emergence in East Java, Indonesia.

Background: Foot and mouth disease (FMD) is a highly infectious disease, affecting animals with divided hooves. FMD has seen significant outbreaks in East Java, Indonesia, highlighting the urgent need to understand the risk factors contributing to its emergence in this region. FMD spreads easily across borders and leads to significant economic losses due to illness, death, and trade limitations.

Molecular detection of blaSHV gene in multidrug resistance of isolated from chicken egg shell swab from a traditional market in Surabaya.

Background: Contamination with food ingredients, including eggs, causes various dangers because it threatens public health, because it acts as a multidrug resistance (MDR) bacteria, especially the extended-spectrum beta-lactamase (ESBL) strain. The ESBL SHV gene is part of a broad-spectrum ESBL that is often found in Gram-negative bacteria.

Aim: This study aimed to identify the ESBL SHV gene in MDR from chicken eggshells.

Nephroprotective Effects of Fraxinus Hookeri Wenz. Against Renal Toxicity and DNA Oxidative Damages Induced by CCl in Rats.

Recognizing the therapeutic value of the Genus Fraxinus worldwide, this study evaluates the antioxidant potential of Fraxinus hookeri Wenz. (F. hookeri) against CCl-induced nephrotoxicity in rats.

Functionalized chitosan as nano-delivery platform for CRISPR-Cas9 in cancer treatment.

CRISPR-Cas system permanently deletes any harmful gene-of-interest to combat cancer growth. Chitosan (CS) is a potential cancer therapeutic that mediates via PI3K/Akt/mTOR, MAPK and NF-kβ signaling pathway modulation. CS and its covalent derivatives have been designed as nanocarrier of CRISPR-Cas9 alone (plasmid or ribonucleoprotein) or in combination with chemical drug for cancer treatment.