Proteomic analysis reveals anticancer mechanisms of Bhallataka taila in inhibiting lung cancer progression and metastasis.

Lung cancer remains the leading cause of cancer-related deaths worldwide due to its poor prognosis. Despite significant advancements in the understanding of cancer development, improvements in diagnostic methods, and multimodal therapeutic regimens, the prognosis of lung cancer has still not improved. Therefore, it is reasonable to look for newer and alternative medicines for treatment.

Selection of alkaliphilic Bacillus pectate lyases based on reactivity and pH-dependent stability in simulated environment for industrial applications.

Pectate lyases, known for their alkaliphilic nature, are ideal for industrial applications that require specific pH conditions, particularly in industries such as textiles and pulp extraction. These enzymes, primarily from the polysaccharide lyase family 1 (PL1) of different microbial sources, play a vital role in polysaccharide degradation. Given the potent pectinolytic activity of Bacillus pectate lyases, targeting these enzymes is crucial for identifying the most effective candidates.

Zingerone effect against Candida albicans growth and biofilm production.

Background: The increasing resistance of Candida albicans biofilms underscores the urgent need for effective antifungals. This study evaluated the efficacy of zingerone and elucidated its mode of action against C. albicans ATCC 90028 and clinical isolate C1.

An Artificial Intelligence-Based Non-Invasive Approach for Cardiovascular Disease Risk Stratification in Obstructive Sleep Apnea Patients: A Narrative Review.

Background: Obstructive sleep apnea (OSA) is a severe condition associated with numerous cardiovascular complications, including heart failure. The complex biological and morphological relationship between OSA and atherosclerotic cardiovascular disease (ASCVD) poses challenges in predicting adverse cardiovascular outcomes. While artificial intelligence (AI) has shown potential for predicting cardiovascular disease (CVD) and stroke risks in other conditions, there is a lack of detailed, bias-free, and compressed AI models for ASCVD and stroke risk stratification in OSA patients.

Impact of Rhenium(I)-Diselenoether Compound on Cell Adhesion, Migration, Invasion Capacities, and MMP-2 Release in MDA-MB-231 Breast Cancer Cells.

Background/aim: Organometallic complexes can decrease adhesion, migration, invasion of cancer cells, mainly through regulation of the extracellular matrix and therefore act against metastases. The aim was to investigate the anti-invasive properties of a rhenium-based metal compound, rhenium(I)-diselenoether (Re-diSe) and its effects on matrix metalloproteinase MMP-2, a key player in metastatic processes, in cultured MDA-MB231 triple-negative breast cancer cells.

Materials And Methods: Matrigel was utilized to assess cancer cell adhesion to the extracellular matrix.

Exploring the role of exosomal lncRNA in cancer immunopathogenesis: Unraveling the immune response and EMT pathways.

Exosomes are membrane-bound vesicles secreted by diverse cell types, serving as crucial mediators in intercellular communication and significantly influencing cancer development. Exosomes facilitate complex signaling processes in the tumor microenvironment for immunomodulation, metastasis, angiogenesis, and treatment resistance. Notably, long non-coding RNAs (lncRNAs), a class of non-coding RNAs, engage with mRNA, DNA, proteins, and miRNAs to modulate gene expression through multiple mechanisms, including transcriptional, post-transcriptional, translational, and epigenetic pathways.

Zinc-doped hydroxyapatite loaded chitosan gelatin nanocomposite scaffolds as a promising platform for bone regeneration.

The advancement in the arena of bone tissue engineering persuades us to develop novel nanocomposite scaffolds in order to improve antibacterial, osteogenic, and angiogenic properties that show resemblance to natural bone extracellular matrix. Here, we focused on the development of novel zinc-doped hydroxyapatite (ZnHAP) nanoparticles (1, 2 and 3 wt%; size: 50-60 nm) incorporated chitosan-gelatin nanocomposite scaffold, with an interconnected porous structure. The addition of ZnHAP nanoparticles decreases the pore size (~30 µm) of the chitosan gelatin scaffold.

3-Hydroxybenzoic acid inhibits the virulence attributes and disrupts biofilm production in clinical isolates of Acinetobacter baumannii.

Purpose: Acinetobacter baumannii (A. baumannii) is an emerging global public health threat owing to its ability to form biofilms. Here, we evaluated 3-hydroxybenzoic acid (3-HBA), a promising organic compound, for its ability to disrupt biofilm formation and virulence attributes in clinical isolates of A.

Identification of blast resistant finger millet (Eleusine coracana L.) genotype through phenotypic screening and molecular profiling.

Finger millet blast caused by Pyricularia grisea hinders crop's growth and is a serious threat to economic yield. It can lead to massive yield losses i.e.

Effect of Virtual Reality Distraction Method on the Level of Salivary Cortisol in Children With Autism Spectrum Disorder During Dental Treatment.

To examine the effect of using Virtual Reality distraction on salivary cortisol levels in children with Autism Spectrum Disorders (ASD) during routine dental treatments. A randomized cross-over study was designed and children with a known diagnosis of ASD, between 8 and 15 years of age, requiring routine, non-invasive dental treatments, were recruited. They were divided into 2 groups (group 1 and group 2) and scheduled for dental treatments using conventional behavior management and/or VR distraction techniques in their first and second dental visit, accordingly.

A novel adaptive FOCV algorithm with robust IMRAC control for sustainable and high-efficiency MPPT in standalone PV systems: experimental validation and performance assessment.

This paper introduces an innovative, adaptive Fractional Open-Circuit Voltage (FOCV) algorithm combined with a robust Improved Model Reference Adaptive Controller (IMRAC) for Maximum Power Point Tracking (MPPT) in standalone photovoltaic (PV) systems. The proposed two-stage control strategy enhances energy efficiency, simplifies system operation, and addresses limitations in conventional MPPT methods, such as slow convergence, high oscillations, and susceptibility to environmental fluctuations. The first stage dynamically estimates the Maximum Power Point (MPP) voltage using a novel adaptive FOCV method, which eliminates the need for irradiance sensors or physical disconnection of PV modules.

Optimal design of a novel modified electric eel foraging optimization (MEEFO) based super twisting sliding mode controller for controlling the speed of a switched reluctance motor.

Switched Reluctance Motor (SRM) has a very high potential for adjustable speed drive operation due to their cost-effectiveness, high efficiency, robustness, simplicity, etc. Now a days SRMs are widely used in automotive industries as traction motors in electric vehicles and hybrid electric vehicles, air-conditioning compressors, and for other auxiliary services. In this article, a novel super twisting sliding mode controller (STSMC) is proposed to improve the performance of an SRM for reducing the ripple in speed and torque.

Exploring purine analogues as inhibitors against Katanin, a microtubule severing enzyme using molecular modeling approach.

Katanin, a key protein in cellular architecture, plays a crucial role in severing microtubules, which are vital components of the cytoskeleton. Given its central involvement in cell division and proliferation, katanin represents a promising target for therapeutic intervention, particularly in cancer treatment. Inhibiting katanin's function could potentially hinder the uncontrolled growth of cancerous cells, making it an attractive target for novel anti-cancer therapies.

Coordinated charging of EV fleets in community parking lots to maximize benefits using a three-stage energy management system.

The rapid global adoption of electric vehicles (EVs) necessitates the development of advanced EV charging infrastructure to meet rising energy demands. In particular, community parking lots (CPLs) offer significant opportunities for coordinating EVs' charging. By integrating energy storage systems (ESSs), renewable energy sources (RESs), and building prosumers, substantial reductions in peak load and electricity costs can be achieved, while simultaneously promoting environmental sustainability.

Development of a high-performance pseudocapacitive composite via electroless deposition of silver nanoparticles on micro-sized silicon.

An energy material has been developed using a one-step chemical reduction method, incorporating silver nanoparticles (AgNPs) that encapsulate micro-sized silicon (mSi) flakes. SEM investigation revealed complete encapsulation of silicon flakes by AgNP's dendritic structure, EDX confirmed the deposition of Ag on Si flakes. Raman spectroscopy confirmed the formation of silver and silicon oxides.

A new band selection framework for hyperspectral remote sensing image classification.

Dimensionality Reduction (DR) is an indispensable step to enhance classifier accuracy with data redundancy in hyperspectral images (HSI). This paper proposes a framework for DR that combines band selection (BS) and effective spatial features. The conventional clustering methods for BS typically face hard encounters when we have a less data items matched to the dimensionality of the accompanying feature space.

Optimizing demand response and load balancing in smart EV charging networks using AI integrated blockchain framework.

The integration of Electric Vehicles (EVs) into power grids introduces several critical challenges, such as limited scalability, inefficiencies in real-time demand management, and significant data privacy and security vulnerabilities within centralized architectures. Furthermore, the increasing demand for decentralized systems necessitates robust solutions to handle the growing volume of EVs while ensuring grid stability and optimizing energy utilization. To address these challenges, this paper presents the Demand Response and Load Balancing using Artificial intelligence (DR-LB-AI) framework.

Synthesis of gum acacia-cl-acrylic acid-co-itaconic acid hydrogels for efficient removal of toxic dye rhodamine-B: A step for sustainable environment.

In the present study, we prepared Gum Acacia-cl-Acrylic acid-co-itaconic acid (GA-cl-AA-co-IA) hydrogels by free radical crosslink polymerization method for the efficient removal of Rhodamine-B (RhB) dye. The hydrogels were further characterized by different characterization techniques: Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), Atomic force microscopy (AFM), Brunuer-Emmett-Teller (BET) and field emission scanning electron microscopy (FE-SEM) to confirm synthesis. The synthesis parameters were optimized by swelling studies, which were performed by gravimetric analysis method.

Exploration of the Reasons for Poor Adherence Among Metabolic Syndrome Patients Attending a Tertiary Care Hospital in Tamil Nadu, India: A Mixed Method Study.

Background A major challenge in the treatment of MetS is the prevalence of low rates of adherence to the treatment regimen for individual components by the affected persons. This study aimed to estimate the medication adherence level among those with metabolic syndrome, determine the factors significantly associated with low adherence to medication, and explore the reasons for poor adherence to medication Materials and methods This sequential explanatory type of mixed method study was conducted among the metabolic syndrome patients attending the lifestyle clinic of a tertiary care hospital in the Salem district of Tamil Nadu, India. For the quantitative component, 210 was the sample size and for the qualitative component, the sample size was six.