Efficacy of hypertonic saline nasal irrigation in allergic rhinitis: A systematic review and meta-analysis.

Saline nasal irrigation provides symptom relief in allergic rhinitis (AR), but the optimal saline concentration remains uncertain. The comparative efficacy of 3% hypertonic saline nasal irrigation (HSNI) versus 0.9% isotonic saline is still debated.

Hybrid Convolutional Neural Network and Generative Adversarial Network Framework for Robust Deepfake Detection: Advancing Accuracy, Scalability, and Multimodal Integration.

Deepfakes pose critical threats to digital media integrity and societal trust. This paper presents a hybrid deepfake detection framework combining Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) to address challenges in scalability, generalizability, and adversarial robustness. The framework integrates adversarial training, a temporal decay analysis model, and multimodal detection across audio, video, and text domains.

Sunlight-Assisted Photodegradation of Tetracycline Using ZnS-Melamine-Formaldehyde Nanocomposites.

The degradation of colorless tetracycline hydrochloride (TCH), a widely used antibiotic, is a significant environmental concern due to its persistence in aquatic systems. The zinc sulfide (ZnS) nanoparticle fabricated melamine-formaldehyde polymer (MFP)-based nanocomposite (ZnS-MFP) was prepared via a hydrothermal polymerization method, followed by surface modification through a simple precipitation route. The degradation of TCH through photocatalysis adheres to pseudo-first-order kinetics with a significantly faster rate under natural sunlight than under artificial bulb light.

Involvement of lncRNA in cancer diagnosis and prognosis and clinical implications.

Long non-coding ribonucleic acids (lncRNAs) form a subclass of non-coding RNAs (ncRNAs), they are quite long and as their name non-coding suggests they do not have a role in protein coding. lncRNAs are vital in all the key steps of tumorigenesis, such as epithelial-mesenchymal transition, cancer stem cells formation, invasion, migration, and formation of the tumor vasculature. lncRNAs are classified into oncogenic or anti-tumor lncRNAs based on their functions.

GenoDense-Net: unraveling the genomic puzzle of the global pathogen.

The respiratory system of humans is impacted by infectious and deadly illnesses like COVID-19. Early identification and diagnosis of this type of illness is essential to stop the infection from spreading further. In the present research, we presented a technique for determining the condition using COVID-19's current genome sequences employing the DenseNet-16 framework.

Plastic pollution in the Ganga River: Modeling the town-level impact of population and waste management systems using region-specific parameters.

Plastic pollution in riverine environments poses a growing threat to ecosystems and human well-being, with the Ganga River emerging as a critical hotspot. This study introduces a novel town-level modeling framework that integrates population dynamics and heterogeneity in waste generation and management factors including collection, treatment, and recycling efficiencies, in the Ganga River basin to estimate riverine plastic waste (RPW). Model predictions were validated using the field data showing waste generation estimates within ±10 %.

Genetic and epigenetic landscape of O-methylguanine-DNA methyltransferase (MGMT): implications for DNA repair and cancer therapeutics.

O-Methylguanine-DNA methyltransferase (MGMT) acts as a genomic custodian, reversing alkylation damage to preserve DNA integrity. However, when its regulatory balance tips via promoter methylation, polymorphisms, or epigenetic silencing, MGMT can become a liability, fuelling cancer progression, treatment resistance, and poor outcomes across malignancies. This review uncovers the nuanced control of MGMT, revealing how its genetic and epigenetic shifts shape tumor behavior, therapeutic response, and risk stratification.

Phytochemical and pharmacoinformatics analysis of a traditional antipsoriatic oil formulation for its potential against proinflammatory cytokines TNF-α and IL-17A.

Psoriasis, a persistent inflammatory condition with a complex origin, lacks a definitive cure despite the availability of diverse treatments. Vetpalai thailam (VT), a Siddha formulation, is commonly used for addressing various skin ailments. Analysis via GC-MS of a sample of VT oil unveiled the existence of 65 compounds.

An insight review on the potential anti-hypertensive effects of Moringa oleifera.

Hypertension is a leading cause of cardiovascular-related morbidity and mortality worldwide. In recent years, there has been growing interest in exploring natural products for managing hypertension, with Moringa oleifera emerging as a promising natural candidate for blood pressure regulation. This review investigates the anti-hypertensive potential of M.

Machinability analysis in wire-EDM of cryogenically treated Ti6Al4V alloy and multi-objective optimization using MOAVOA and MOGA.

The performance of Ti6Al4V alloy in engineering and biomedical applications is often limited by its poor wear and abrasion resistance, especially when compared to conventional materials such as CoCr-based alloys and stainless steels. In biomedical implants, such as hip and knee joints, this limitation results in a typical service life of only 10-15 years. Cryogenic treatment has emerged as a potential method to enhance the wear resistance of Ti6Al4V.

Integrating physiological signals for enhanced sleep apnea diagnosis with SleepNet.

Sleep apnea, a prevalent respiratory disorder, poses significant health risks, including cardiovascular complications and behavioral issues, if left untreated. Traditional diagnostic methods like polysomnography, although effective, are often expensive and inconvenient. SleepNet addresses these issues by introducing a new multimodal approach tailored for precise sleep apnea detection.

Experimentally validated finite element model for mechanical and fracture characteristics of SiCN thin films under different loads.

In this work, SiCN thin films were deposited on p-Si (100) substrate using a thermal Chemical Vapor Deposition (CVD) process. The mechanical behavior of the thin film was characterized using the nanoindentation technique, where the load was varied from 1 to 4 mN, to understand the influence of load variation on the load-displacement response. Additionally, an experimentally validated FE model, incorporating an elast-plastic material response of the thin film, was developed to understand localized stress distribution and fracture behavior.

Optimization of SiO based water-diesel emulsified fuel for engine performance and emission characteristics using soft computing approaches.

The rising global energy demand strongly associates over global warming, and prompt environmental changes have determined researchers to investigate and identify alternative fuels as sustainable and eco-friendly solutions. The aim of the current study is to investigate the performance, and emission characteristics of an engine using water diesel emulsified fuel (WDEF) adopting SiO nanoparticle. The fuel blend D94W5S1-Si50, comprising of 94% diesel, 5% water, 1% SPAN 80, and 50 ppm silicon nanoparticles (SiNPs) is selected for test fuel and explored the simultaneous effects of different input parameters such as injection pressure, injection timing, and engine load on engine performance and emission attributes without engine modification or experiencing added costs.

Prediction of virulence factors in bacterial hypothetical proteins.

A large number of genes in bacterial genomes encode hypothetical proteins (HPs) with unknown functions that require annotation. These HPs have recently been linked to pathogenicity due to potential virulence factors. Understanding the key elements influencing their virulence is a crucial goal.

ASD-HybridNet: A hybrid deep learning framework for detection of autism spectrum disorder.

Current diagnostic methods for autism spectrum disorder (ASD) are based on subjective behavioral assessments, which present challenges to an accurate and early diagnosis. This paper proposes a hybrid deep learning framework, ASD-HybridNet, which integrates both region of interest (ROI) time series data and functional connectivity (FC) maps derived from functional magnetic resonance imaging (fMRI) data to improve ASD detection. Experiments on the ABIDE dataset demonstrate the effectiveness of the proposed method compared to existing approaches.

Optimization of friction stir welding parameters for enhanced mechanical properties of AISI 1018 carbon steel.

The present work aims to optimize the process parameters of friction stir welding (FSW) to improve the mechanical behavior of AISI 1018 carbon steel joints. The study explores the influence of welding speed, tool rotational speed, and shoulder diameter on ultimate tensile strength (UTS), percentage elongation (PE), percentage reduction in area (RA), and impact energy (IE). To achieve this, both single-response and multi-response optimization methods were applied.

AI-enhanced telemedicine: transforming resource allocation and cost-efficiency analysis via advanced queueing model.

The increasing demand for telemedicine makes conventional queueing approaches inadequate for meeting dynamic and priority-driven service needs. Therefore, a more advanced queueing mechanism is necessary to address these requirements. This paper integrates an advanced queueing model with AI-scheduling, implemented using deep reinforcement learning, to optimize digital healthcare by adjusting doctor availability dynamically and prioritizing patient care based on urgency and time of arrival.

Energy-efficient design of CNTFET-based quaternary arithmetic circuits.

The vast interconnection between digital logic blocks is the main challenge faced in chip designing, which leads to increased area overheads and average power consumption. One possible solution to overcome this challenge is to make use of multi-valued logic. However, for implementing multi-valued logic, new design techniques that deliver low-power and high-speed performance need to be explored.

Substance P mitigates lipopolysaccharide induced cognitive impairment in rats in a dose dependent manner.

Neuroinflammation contributes to cognitive decline in Alzheimer's disease (AD), and the neurokinin pathway has been implicated in the pathophysiology of AD. Although Substance P (SP), an endogenous ligand to the neurokinin 1 receptor (NK1R), is primarily known as a neurotransmitter, but emerging evidence indicates it has shown both pro and anti-inflammatory actions. However, the dose-dependent nature of the SP-NK1R axis's functional role remains to be fully elucidated.

Optimal selection of SiC and TiO reinforced ZA27 hybrid nanocomposite exercising PSI approach under fuzzy environment for bearing application.

The correct selection of material with adequate characteristics for bearing races has been troublesome owing to the wide availability of materials with different sets of characteristics. In the same context, the present work deals with selection of the best composite formulation using multi-criteria decision making (MCDM) method among the set of prepared composite alternatives. The preference selection index (PSI) method was utilized in ranking alternatives under uncertain (fuzzy) environment.

RNN-Bi-LSTM spectrum sensing algorithm for NOMA waveform with diverse channel conditions.

Non-Orthogonal Multiple Access (NOMA) has emerged as a prominent technique for enhancing spectral efficiency in beyond-fifth-generation (5G) and sixth-generation (6G) wireless systems. However, its performance is highly dependent on channel conditions, necessitating robust spectrum-sensing methods. This study proposes a novel Recurrent Neural Network (RNN)-based Bidirectional Long Short-Term Memory (RNN-Bi-LSTM) model to enhance the spectral performance of NOMA under various channel conditions, particularly the Rician and Rayleigh fading channels.

Improved photoinduced charge carrier separation through the built-in electric field in a rationally designed Ag-ZnMnO/exfoliated g-CN, a plasmonic p-n junction for solar-driven reduction of dissolved Cr(VI).

Sensitization of wide bandgap semiconductors by coupling with a low-band-gap semiconductor to improve photoinduced charge carrier separation by the built-in electric field is one of the attractive approaches to develop an efficient photocatalyst. Here we present the development of Ag-ZnMnO/exfoliated g-CN (Ag-ZMO/ECN), a novel photocatalyst designed to remove an inorganic pollutant Cr(VI) under direct solar light irradiation. The enhanced performance of Ag-ZMO/ECN is attributed to efficient charge separation, facilitated by the formation of a p-n junction at the interface of narrow-bandgap p-type ZMO and n-type ECN, and the localized surface plasmon resonance (LSPR) effect of the deposited Ag nanoparticles.

Hearing loss and hearing aid stigma in low- and middle-income settings: a scoping review.

Purpose: Stigma has been reported as a key barrier to hearing aid uptake. This scoping review explores evidence of reported stigma associated with hearing loss and hearing aids in low- and middle-income (LMI) settings.

Methods: Four databases were searched to identify studies published up to 6 November 2024.

A novel hybrid approach for thyroid disease detection: Integrating cuttlefish algorithm and simulated annealing for optimal feature selection.

Effective treatment relies on a timely diagnosis, which is critical in the case of thyroid disorder-one of the chronic endocrine disorders alongside diabetes and obesity-with profound health concerns. Thyroid disorders occur due to the malfunctioning of the thyroid gland, which may result in an imbalanced metabolic rate due to inappropriate hormone levels synthesis. An overactive gland results in hyperthyroidism, whereas an underactive or sluggish thyroid lead to hypothyroidism.

Dental Management for People With Congenital Haemophilia: A Systematic Review of the Existing Dental Recommendations.

Introduction: Haemophilia is the most common inherited bleeding disorder. Dental management for people with haemophilia (PwH) (both A and B) is challenging, as dental procedures may initiate bleeding episodes that may be difficult to control.

Objectives: This systematic review aimed to evaluate and summarize the existing dental guidelines that are proposed from various agencies/professional bodies, and so forth, for dental treatment procedures in PwH.