Machine learning-enhanced detection of chlorpyrifos using molecularly imprinted polymer-coated optical fibers.

This paper explores the use of large core declad optical fibers coated with molecularly imprinted polymers for chlorpyrifos detection, a key marker of organophosphate pesticides. The performance of sensor is evaluated using artificial neural networks and principal component analysis. By varying the declad length, the performance of molecularly imprinted polymer-coated fibers is compared to uncoated fibers, and both are used to identify commercial and pure samples of chlorpyrifos pesticides.

Machine learning-based estimation of crude oil-nitrogen interfacial tension.

Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.

Application of Monte Carlo simulation and artificial neural network model to probabilistic health risk assessment in fluoride-endemic areas.

Groundwater contamination with fluoride is a considerable public health concern that affects millions of people worldwide. The rapid growth of urbanization has led to increase in groundwater contamination. The health risk assessment focuses on both acute and chronic health consequences as it investigates the extent and effects of fluoride exposure through contaminated groundwater.

Enantioselective Analysis and Separation of Two β-Blockers via Derivatization Approach.

Enantiomeric analysis of chiral drugs is very significant, as their enantiomers display different pharmacological or toxicological behavior towards living systems. Among these drugs, β-blockers are available as racemates, where their enantiomers display different pharmacological effects. Herein, we report enantioselective separation of two β-blockers, namely, atenolol and sotalol, using a derivatization approach.

Neuroactive Phytoconstituents of Glycyrrhiza glabra for the Treatment of Alzheimer's Disease.

Alzheimer's Disease (AD), a prevalent neurodegenerative disorder, poses a significant global health challenge with complicated pathogenesis. Pathological characteristics of AD include increasing loss of cholinergic neurons, oxidative stress, mitochondrial dysfunction, and amyloid beta accumulation. Due to the limited availability of effective therapeutic options with only symptomatic relief and their severe adverse effects, there is a significant need to search and explore new agents for the management of AD.

Bioinformatics Exploration of the Therapeutic Potential of Lotus Seed Compounds in Multiple Sclerosis: A Network Analysis of c-Jun Pathway.

The central nervous system is affected by multiple sclerosis (MS), a chronic autoimmune illness characterized by axonal destruction, demyelination, and inflammation. This article summarizes the state of the field, highlighting its complexity and significant influence on people's quality of life. The research employs a network pharmacological approach, integrating systems biology, bioinformatics, and pharmacology to identify biomarkers associated with MS.

Computational evaluation of micropores wetting effect on the removal process of CO through the membrane contactor.

In the current years, gas-liquid membrane contactors (GLMCs) have been introduced as a promising, versatile and easy-to-operate technology for mitigating the emission of major greenhouse contaminants (i.e., CO and HS) to the ecosystem.

Gait-based Parkinson's disease diagnosis and severity classification using force sensors and machine learning.

A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait signals using force sensors and machine learning approaches, is proposed in this study. Parkinson's disease is the primary neurodegenerative disorder that results in a gradual reduction in motor function. Early detection and monitoring of the disease progression is highly challenging due to the gradual progression of symptoms and the inadequacy of conventional methods in identifying subtle changes in mobility.

Eco-reliable operation based on clean environmental condition for the grid-connected renewable energy hubs with heat pump and hydrogen, thermal and compressed air storage systems.

Energy hubs, with their diverse regeneration and storage sources, can engage concurrently in energy transfer and storage. It is anticipated that managing the energy of these hubs within energy networks could enhance economic, environmental, and technical metrics. This article explains how electrical and thermal network hubs manage their energy consumption in the context of the multi-criteria objectives of efficiency, sustainability, reliability of the network operator, and operation.

Harnessing the potential of long non-coding RNAs in the pathophysiology of Alzheimer's disease.

Alzheimer's disease (AD), a diverse neurodegenerative disease, is the leading cause of dementia, accounting for 60-80 % of all cases. The pathophysiology of Alzheimer's disease is unknown, and there is no cure at this time. Recent developments in transcriptome-wide profiling have led to the identification of a number of non-coding RNAs (ncRNAs).

LC-MS profiling and cytotoxic activity of Angiopteris helferiana against HepG2 cell line: Molecular insight to investigate anticancer agent.

Liver cancer is one of the most prevalent malignant diseases in humans and the second leading cause of cancer-related mortality globally. Angiopteris helferiana was mentioned as a possible anticancer herb according to ethnomedicinal applications. However, the molecular docking and chemical profiling of the bioactive phytoconstituents accountable for the reported anticancer action still require research.

Enhancing the efficacy of zinc oxide nanoparticles by beta-carotene conjugation for improved anti-microbial and anti-tumor therapy for dental application.

Zinc oxide NPs (ZnO NPs) are notable in nanomedicine for their exceptional physicochemical and biological properties. This study synthesizes and characterizes beta-carotene-coated ZnO NPs (BT-ZnO NPs) for potential anti-cancer and antimicrobial applications, demonstrating significant efficacy against dental pathogens and oral cancer cells. Scanning Electron Microscopy, EDAX, UV, FTIR, XRD, and Zeta potential analysis of prepared BT-ZnO NPs revealed uniform flower-like crystalline structures with intricate morphology and an average particle size of 38.

Secure cloud computing: leveraging GNN and leader K-means for intrusion detection optimization.

Over the past two decades, cloud computing has experienced exponential growth, becoming a critical resource for organizations and individuals alike. However, this rapid adoption has introduced significant security challenges, particularly in intrusion detection, where traditional systems often struggle with low detection accuracy and high processing times. To address these limitations, this research proposes an optimized Intrusion Detection System (IDS) that leverages Graph Neural Networks and the Leader K-means clustering algorithm.

Chronic kidney disease and aging: dissecting the p53/p21 pathway as a therapeutic target.

Chronic kidney diseases (CKD) are a group of multi-factorial disorders that markedly impair kidney functions with progressive renal deterioration. Aging contributes to age-specific phenotypes in kidneys, which undergo several structural and functional alterations, such as a decline in regenerative capacity and increased fibrosis, inflammation, and tubular atrophy, all predisposing them to disease and increasing their susceptibility to injury while impeding their recovery. A central feature of these age-related processes is the activation of the p53/p21 pathway signaling.

Optimisation and evaluation of long circulating Ru-SLNs carrier for targeting melanoma cells.

The aim of study was to prepared and evaluated rutin-loaded solid-lipid-nanoparticles (Ru-SLNs) gel for treatment of melanoma cells. SLNs were prepared by ultrasonication method through optimisation and evaluated their mean-diameter, PDI, zeta-potential, morphology, entrapment-efficiency, drug-loading, interaction by FTIR, in vitro skin permeation, stability, antioxidant/MTT assay and fluorescence microscopic. Further developed Ru-SLNs was incorporated into gel and characterised their physicochemical properties, drug contents, in vitro diffusion, ex vivo permeation and retention studies in human cadaver skin.

Exosome-mediated delivery of CRISPR-Cas9: A revolutionary approach to cancer gene editing.

Several molecular strategies based on targeted gene delivery systems have been developed in recent years; however, the CRISPR-Cas9 technology introduced a new era of targeted gene editing, precisely modifying oncogenes, tumor suppressor genes, and other regulatory genes involved in carcinogenesis. However, efficiently and safely delivering CRISPR-Cas9 to cancer cells across the cell membrane and the nucleus is still challenging. Using viral vectors and nanoparticles presents issues of immunogenicity, off-target effects, and low targeting affinity.

Noise pollution mitigation and control in urban areas near international borders through 2D noise mapping.

Noise pollution is defined as any disturbing or unwanted sound that disrupts or harms human health or wildlife. Noise pollution can have profound effects on both human health and the environment. For humans, exposure to excessive noise levels has been linked to a range of health issues, including hearing damage, stress, and sleep disturbances.

Liquid biopsies and exosomal ncRNA: Transforming pancreatic cancer diagnostics and therapeutics.

Pancreatic cancer is a highly fatal malignancy due to poor early detection rate and resistance to conventional therapies. This review examines the potential for liquid biopsy as a transformative technology to identify diagnostic and therapeutic targets in pancreatic cancer. Specifically, we explore emerging biomarkers such as exosomal non-coding RNAs (ncRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs).

Recent Advances in 4D Printing: A Review of Current Smart Materials, Technologies, and Drug Delivery Systems.

Research on shape memory materials (SMM) or smart materials, along with advancements in printing technology, has transformed three-dimensional (3D) printing into what we now refer to as 4D printing. In this context, the addition of time as a fourth dimension enhances 3D printing. 4D printing involves the creation of 3D-printed objects that can change their shapes into complex geometries when influenced by external stimuli such as temperature, light, or pH over time.

Lead Phytomolecules for Treating Parkinson's Disease.

One percent of persons over 65 years of age suffer from Parkinson's disease, a neurological ailment marked by dopaminergic neurons in the nigrostriatal pathway gradually dying and being depleted in the striatum. Parkin and PINK1 gene mutations, which are essential for mitophagy and impair mitochondrial function, are the cause of it. Parkinson's disease is linked to a number of motor and impairment disorders, including bradykinesia, rigid muscles, tremor at rest, and imbalance.

Electroceuticals: Unlocking the promise of therapies.

Objectives: Electroceuticals refers to the constantly growing disciplines of bioelectric and bioelectronic medication. These include a broad variety of devices that have been invented and are now being utilized in medical implants, wearable medical electronics, and bioelectronics. The primary aim of this study is to encompass several facets of electroceuticals, their applications, and recent advancements in the field of medical challenges.

Targeting breast tumor extracellular matrix and stroma utilizing nanoparticles.

Breast cancer is a complicated malignancy and is known as the most common cancer in women. Considerable experiments have been devoted to explore the basic impacts of the tumor stroma, particularly the extracellular matrix (ECM) and stromal components, on tumor growth and resistance to treatment. ECM is made up of an intricate system of proteins, glycosaminoglycans, and proteoglycans, and maintains structural support and controls key signaling pathways involved in breast tumors.

Effect of soluble fiber supplementation on lipid parameters in subjects with type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials.

Background: There is no consensus in the existing literature regarding the effect of soluble fiber on the lipid profile of patients with type 2 diabetes mellitus (T2DM). This systematic review and meta-analysis of randomized controlled trials aimed to assess the effect of soluble fiber on triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in T2DM patients.

Methods: PubMed/MEDLINE, Scopus, and ISI Web of sciences were searched for RCTs up to 4 May 2024.

Metabolomics and network pharmacology-guided analysis of TNF-α expression by (Linn) targeting NF-kB the signalling pathway in cancer cell lines.

Introduction: Cancer has emerged as one of the leading causes of fatality all over the world. Phytoconstituents are being studied for their synergistic effects, which include disease prevention by altering molecular pathways and immunomodulation without side effects. The present experiment aims to explore the cancer preventive activities of Linn leaves extract in skin cancer cell lines (A431) and colon cancer cell lines (COLO 320DM)).