Quality of Life in Children With Chronic Health Conditions and Its Contribution to Unmet Supportive Care Needs of Families.

BACKGROUND: While theoretical models have established the bidirectional relationship between health and wellbeing of parents and children with chronic health conditions (CHCs), previous work has predominantly emphasised the impact of parent functioning on child outcomes. This study examines how quality of life (QoL) domains in children with CHCs are associated with unmet supportive care needs (SCN) of their parents and explores whether these associations vary by health condition. METHOD: Parents of children with congenital heart disease (CHD), type 1 diabetes (T1D) and cancer diagnosed before the age of 12 years and receiving treatment within the last 5 years were eligible. Parents recruited through charity organisations and social media platforms completed a secure, online survey via Qualtrics. The PedsQL examined child QoL across four dimensions: physical, emotional, social and school functioning. A 34-item survey assessed parents' unmet SCN in the previous month across six need domains (e.g., care and informational). Linear regressions examined associations between child QoL and unmet SCN domains and moderation analyses determined whether associations varied as a function of CHC. RESULTS: The study included 186 parents (age range 25-56 years) of children diagnosed with various CHCs (52% CHD; 27% T1D, 21% cancer). The child's emotional functioning was inversely related to all unmet SCN domains, social functioning was inversely related to three domains (physical and social; support; financial), school functioning was inversely related to two domains (physical and social; care), and child's physical functioning was not associated with any SCN domains. Only the association between child school functioning and unmet care needs was significantly moderated by CHC type (p < 0.05). CONCLUSION: Poorer emotional functioning in children with a CHC is a key factor in determining parents unmet SCN. Larger studies are required to replicate these findings and inform design of interventions addressing QoL and unmet SCN in families of children with common CHCs.

Autologous Conditioned Serum in Knee Osteoarthritis: A Systematic Review of Current Clinical Evidence.

Knee osteoarthritis (OA) significantly impacts global health, causing pain, disability, and socioeconomic burden. Traditional treatments often provide only temporary relief and can have adverse effects. Autologous conditioned serum (ACS) therapy, which enriches a patient's own blood with growth factors and anti-inflammatory cytokines, has emerged as a promising approach to manage knee OA, potentially offering pain reduction, improved function, and tissue regeneration. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched databases such as PubMed, Web of Science, and Cochrane using terms like "Autologous Conditioned Serum" and "knee osteoarthritis." Clinical studies were selected based on their focus on ACS's efficacy in knee OA, assessing outcomes like pain relief, functional improvement, and adverse events. Eighteen studies met the inclusion criteria, including randomized controlled trials, observational studies, and comparative analyses. The review included a wide range of study designs and outcomes, highlighting ACS's efficacy in reducing pain and enhancing knee function as evidenced by various patient-reported outcome measures Visual Analog Scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Injury and Osteoarthritis Outcome Score (KOOS), Knee Society Clinical Rating Score (KSCRS) with a follow-up of up to 11 years (range: 2-11 years). Comparative studies showed ACS to be as effective or superior to conventional treatments such as platelet-rich plasma, steroids, and hyaluronic acid, especially in cases of moderate synovitis. Minimal adverse effects such as peri-injection pain, rigidity, synovitis, transient sensation of redness/heat, and numbness in the knee/leg/toes were reported, underscoring ACS's safety. Some studies suggested ACS might also have disease-modifying effects, contributing to tissue repair and integrity. ACS therapy offers a promising alternative for knee OA management, demonstrating potential benefits in symptom alleviation, functional improvement, and safety. Indications of disease-modifying properties further highlight its therapeutic value. However, the need for standardized formulations and treatment protocols, long-term studies, and mechanistic understanding remain. Future research should focus on addressing these gaps to fully elucidate ACS's role in the treatment landscape of knee OA.

The Science of Solid Lipid Nanoparticles: From Fundamentals to Applications.

Solid lipid nanoparticles (SLNs) play a crucial role in drug delivery, offering benefits such as enhanced bioavailability, targeted distribution, and reduced toxicity. This article provides a comprehensive overview of SLN formulation, development, and advancement in pharmaceutical research, examining their characteristics, classifications, and significance. The review also delves into the real-world applicability of various SLN formulations across different routes of administration, discussing their advantages, disadvantages, and challenges of scalability, along with strategies for efficient implementation. Furthermore, it explores the diverse applications of SLNs through various delivery methods, addressing the obstacles and potential solutions. By highlighting the critical role of SLNs in improving treatment outcomes, this review underscores their importance in modern drug delivery systems.

Blood flow modulation to improve motor and neurophysiological outcomes in individuals with stroke: a scoping review.

Ischemic Conditioning (IC) is a procedure involving brief periods of occlusion followed by reperfusion in stationary limbs. Blood Flow Restriction with Exercise (BFR-E) is a technique comprising blood flow restriction during aerobic or resistance exercise. Both IC and BFR-E are Blood Flow Modulation (BFM) strategies that have shown promise across various health domains and are clinically relevant for stroke rehabilitation. Despite their potential benefits, our knowledge on the application and efficacy of either intervention in stroke is limited. This scoping review aims to synthesize the existing literature on the impact of IC and BFR-E on motor and neurophysiological outcomes in individuals post-stroke. Evidence from five studies displayed enhancements in paretic leg strength, gait speed, and paretic leg fatiguability after IC. Additionally, BFR-E led to improvements in clinical performance, gait parameters, and serum lactate levels. While trends toward motor function improvement were observed post-intervention, statistically significant differences were limited. Neurophysiological changes showed inconclusive results. Our review suggests that IC and BFR-E are promising clinical approaches in stroke, however high-quality studies focusing on neurophysiological mechanisms are required to establish the efficacy and underlying mechanisms of both in stroke. Recommendations regarding future directions and clinical utility are provided.

Enhancing security in digitized healthcare system using blockchain technology.

BACKGROUND: In the modern medical industry, sensors and other medical electronic equipment such as ECG, thermometers, etc. that measure vitals like blood pressure, body temperature, heartbeat, and blood cells are used to record patient data. The information gathered helps to create a patient profile, which in turn helps doctors treat patients appropriately and helps users gain insights into their health. But, the information collected is regionally specific and not worldwide. Thus, this may create problems in transparency, integrity, and much more. The medical details of patients collected are stored in a simple database which appears to be a centralized application that is prone to be modified or hacked by intruders and also suffers from fault tolerance. OBJECTIVE: This paper aims to solve this problem using Blockchain and Data Possession methodologies. METHODS: Blockchain helps to store multiple copies of data in a decentralized fashion. Thus, a secured model could be implemented using blockchain in which the patient's data can be securely sent to any medical professional, thus promoting transparency, security, and integrity. RESULTS: Provable Data Possession helps the users to verify that their information is intact and has not been tampered. It can be achieved using cryptography which encrypts the information of the patients stored. CONCLUSION: This paper will be beneficial for the medical department and the public such that it will be beneficial in terms of transparency, scalability, and security.

Performance analysis of floating bifacial stand-alone photovoltaic module in tropical freshwater systems of Southern Asia: an experimental study.

The optimization of floating bifacial solar panels (FBS PV) in tropical freshwater systems is explored by employing response surface methodology (RSM) and central composite design (CCD). Previous studies have yet to explore the long-term durability, environmental impact, economic viability, and performance of FBS PV systems under various climatic conditions. This study addresses this gap by focusing on panel height, water depth, and tilt angle to improve performance. The quadratic model reveals significant non-linear relationships impacting FBS PV power generation with freshwater cooling. Our models demonstrate high explanatory power, with R-squared values of 0.9831 for output power and 0.9900 for Bi-Facial gain. Experimental validation using conventional white surface (CWS) and proposed freshwater surface (PFS) indicates notable improvements in power generation, achieving a 4.34 to 4.86% gain in bifacial efficiency across various irradiation levels. Under 950 W/m2 irradiation, freshwater cooling achieves a 3.19% higher bifacial gain compared to CWS cooling. Panel temperature analysis shows consistent reductions with freshwater cooling, ranging from 1.43 to 2.72 °C, enhancing overall efficiency and longevity. This research highlights the potential of freshwater cooling in optimizing bifacial solar systems, offering actionable insights for sustainable energy solutions in tropical regions.

Characterization of Gaze Metrics and Visual Search Pattern Among Glaucoma Patients While Viewing real-world Images.

PRCIS: We quantified and compared the gaze metrics during target-oriented visual search tasks between glaucoma and healthy controls. Based on a mathematical concept we showed that due to glaucoma, focal search becomes prominent over global search. PURPOSE: Visual Search (VS) which is essential for target identification and navigation is significantly impacted by glaucoma. VS metrics can be influenced by differences in cultural exposure or coping strategies, leading to varying VS patterns. The aim of this study was to explore and label the pattern of VS based on gaze metrics quantified using eye-tracking technology. METHODS: Twenty-seven glaucoma subjects and thirty healthy controls (median age 51 (14) and 54 (19) years respectively) underwent a VS experiment during which they had to identify specific targets from real-world images. Eye movements were recorded using a remote eye-tracker and gaze metrics - Fixation Count (FC), Fixation Duration (FD), Saccade Amplitude (SA), and VS Time (VST) were computed and compared between the study groups. A Z-score-based coefficient 'K' was derived to label the search patterns as global (K ≤ - 0.1: short FD with long SA), focal (K ≥ +0.1: long FD with short SA), or a combination (K between +/-0.1). RESULTS: Similar to other ethnicities, Indian glaucoma subjects also exhibited statistically significantly increased FC, FD, and VST (P=0.01). Healthy controls presented a comparable proportion of focal (47%) and global (42%) search patterns while glaucoma subjects exhibited predominantly focal (56%) than global search patterns (26%, P=0.008). CONCLUSIONS: This study suggests that glaucoma subjects perform more focal search during active gaze scanning. This change in viewing behavior reflects underlying compensatory strategies adapted for coping with their visual impairments. These search patterns can be influenced by factors such as saliency which requires further investigation.

Prevalence and influencing factors of metabolic syndrome among rural adult population in a district of South India.

Background: Metabolic syndrome has increased globally due to sedentary lifestyles, unhealthy diets and obesity, which is posing a substantial burden on healthcare systems. Understanding the determinants of metabolic syndrome like lifestyle factors, socioeconomic status and the environment are vital for devising effective prevention and management. Research into these determinants helps to identify high-risk populations and develop interventions to reduce its occurrence. Objectives: i. To estimate the prevalence of metabolic syndrome among the adult population. ii. To determine the factors associated with metabolic syndrome among the adult population. Methodology: A cross-sectional study was carried out among 410 adults (≥18 years). A semi-structured questionnaire was used to collect data and National Cholesterol Education Program's Adult Treatment Panel III criteria was used to diagnose metabolic syndrome. Continuous and categorical data were represented as mean and proportion, respectively. The strength of the association was determined using the prevalence ratio and adjusted prevalence ratio. Results: The mean age of the participants was 44.97 ± 14.7, about 58.3% of them were females. Metabolic syndrome prevalence was 39.8%. Multivariate regression analysis demonstrated that being over 40 years old, marital status, higher socioeconomic status, skilled workers, physical inactivity and obesity were independently linked to metabolic syndrome. Conclusions: The burden can be reduced by identifying the risk factors at the early stage through screening and by adopting a healthy lifestyle.

Regulatory Challenges and Frameworks for Fog Computing in Healthcare.

The integration of fog computing into healthcare promises significant advancements in real-time data analytics and patient care by decentralizing data processing closer to the source. This shift, however, introduces complex regulatory, privacy, and security challenges that are not adequately addressed by existing frameworks designed for centralized systems. The distributed nature of fog computing complicates the uniform application of security measures and compliance with diverse international regulations, raising concerns about data privacy, security vulnerabilities, and legal accountability. This review explores these challenges in depth, discussing the implications of fog computing's decentralized architecture for data privacy, the difficulties in achieving consistent security across dispersed nodes, and the complexities of ensuring compliance in multi-jurisdictional environments. It also examines specific regulatory frameworks, including Health Insurance Portability and Accountability (HIPAA) in the United States, General Data Protection Regulation (GDPR) in the European Union, and emerging laws in Asia and Brazil, highlighting the gaps and the need for regulatory evolution to better accommodate the nuances of fog computing. The review advocates for a proactive regulatory approach, emphasizing the development of specific guidelines, international collaboration, and public-private partnerships to enhance compliance and support innovation. By embedding privacy and security by design and leveraging advanced technologies, healthcare providers can navigate the regulatory landscape effectively, ensuring that fog computing realizes its full potential as a transformative healthcare technology without compromising patient trust or data integrity.

Risk Factors for Bacterial Keratitis and Severe Disease in Hydrogel Contact Lens Users: A Multicenter Case-Control Study and Case-Only Analysis.

PURPOSE: To assess risk factors for contact lens (CL)-related bacterial keratitis, cases and high-risk controls were enrolled. Using high-risk controls can help elucidate whether certain CL types or modalities are attributable to disease burden if risky wear patterns are similar between the cases and controls. This analysis identified whether such CL factors were associated with the occurrence of bacterial keratitis. In addition, a case-only analysis determined CL factors associated with severe disease. METHODS: From 2018 to 2021, 158 controls were enrolled at University Hospitals of Cleveland Eye Institute, and 153 bacterial keratitis cases were enrolled across 14 sites in the United States. Cases were soft CL wearers with either culture-proven bacterial keratitis or a corneal infiltrate with an overlying epithelial defect within the central 4 mm of the cornea, uveitis, or significant pain. Fungal, protozoan, or nonsoft CL wear-related microbial keratitis cases were excluded. Controls were recruited from high-risk CL wearers with no history of disease. All participants completed a questionnaire related to demographics, type of CL used, wearing schedule, lens handling practices, and storage case handling. Cases with ulcer/infiltrate size ≥2 mm in size, presence of hypopyon, or had fortified antibiotics prescribed were classified as severe keratitis. Univariate and multivariable logistic regression was used to assess association of CL variables with the occurrence of bacterial keratitis as well as occurrence of severe disease among the cases only. RESULTS: Compared with the control cohort, cases were older (mean age 45.6 vs. 38.9 years), had more males (42.5% vs. 23.6%), and had more current or former smokers (41.7% vs. 12.9%). There were no significant associations between CL material (silicone hydrogel vs. not) or CL type (daily disposable vs. reusable) and occurrence of bacterial keratitis. More than two-thirds (67.3%) of cases were classified as severe. Among cases only, univariate analyses found current smokers to have increased risk of severe disease (OR=2.87; 95% CI 1.13-7.26, P=0.03). Adjusting for age, sex, and smoking among the cases only, daily disposable lenses were protective against severe disease (OR=0.32; 95% CI 0.11-0.89, P=0.03). Reusable lenses increased risk of severe microbial keratitis between 3.0- and 4.4-fold compared with compliant daily disposability. DISCUSSION/CONCLUSION: Compared with a high-risk control cohort, no specific lens factors were associated with occurrence of CL-associated bacterial keratitis. Among cases only, current smokers and patients wearing reusable lenses are at increased risk of severe keratitis. Daily disposable lenses were protective even when noncompliance to daily disposability was considered.

Oral and vulval disease: Prevalence, associations, and management recommendations for the oral medicine clinician.

OBJECTIVE: The oral cavity is a common site for mucosal conditions which may be confined to the mouth, or may manifest as mucocutaneous involvement at other sites, including the anogenital region. This retrospective analysis aimed to assess the appropriateness of oral medicine referrals to a specialized vulval clinic and review the prevalence of oral disease associated with vulval involvement of the same condition. STUDY DESIGN: One hundred thirty-six patients referred from oral medicine to the vulval service at Guy's Hospital were analyzed. Retrospective data collated included: reason(s) for referral, onset of oral and genital symptoms, oral diagnosis, vulval diagnosis, correlation between the oral and vulval diagnosis, and discharge at first appointment. RESULTS: Forty-nine percent (n = 67) of the patients had oral and vulval manifestations of the same disease. The majority of these patients (n = 63) were diagnosed with vulval lichen planus, of whom 61 had concomitant oral lichen planus involvement (97%). Other associated oral and vulval diseases included aphthous ulceration, Behçet's disease, dryness secondary to Sjögren's disease, Crohn's disease, and mucous membrane pemphigoid. The remaining 51% (n = 69) of the patients presented with independent vulval conditions unrelated to their oral disease. CONCLUSION: Clinicians should recognize the association between genital symptoms and oral disease and refer to specialist allied services, as appropriate. (Oral Surg Oral Med Oral Pathol Oral Radiol YEAR;VOL:page range).

Evaluation of virulence determinants and cell surface properties associated with biofilm formation in methicillin-resistant Staphylococcus aureus (MRSA) and extended spectrum beta-lactamase (ESBL) Escherichia coli from livestock and poultry origin.

Antibiotic resistance poses a persistent threat to modern medicine due to the emergence of novel antibiotic-resistant strains. Therefore, a timely understanding of antibiotic resistance and the virulence biology of pathogenic bacteria, particularly those of public health significance, is crucial for implementing effective mitigation strategies. This study aimed to investigate the virulence profiles of ten S. aureus isolates (NDa to NDj) and ten E. coli isolates (ND1 to ND10) originating from livestock and poultry, and to assess how various cell surface properties and biofilm formation abilities influence antibiotic resistance phenotypes. Antibiotic resistance profiling through phenotypic (AST) and genotypic methods (PCR) confirmed that NDa to NDe were methicillin-resistant S. aureus (MRSA) and ND1 to ND5 were extended-spectrum ß-lactamase (ESBL) producing E. coli isolates. Virulence properties such as hemolytic activity, coagulase activity, and nuclease activity were found to be independent of the antibiotic resistance phenotype in S. aureus. In contrast, biofilm formation phenotype was observed to influence antibiotic resistance phenotypes, with MRSA and ESBL E. coli isolates demonstrating higher biofilm formation potency. Chemical and enzymatic analysis of S. aureus and E. coli biofilms revealed proteins and polysaccharides as major components, followed by nucleic acids. Furthermore, cell surface properties such as auto-aggregation and hydrophobicity were notably higher in isolates with strong to medium biofilm-forming capabilities (ESBL and MRSA isolates), corroborated by genomic confirmation of various genes associated with biofilm, adhesion, and colonization. In conclusion, this study highlights that surface hydrophobicity and biofilm formation ability of MRSA (NDa to NDe) and ESBL E. coli (ND1 to ND5) isolates may influence antibiotic resistance phenotypes.

Next generation sequencing to detect pathogens causing paediatric community-acquired pneumonia - A systematic review and meta-analysis.

BACKGROUND: Paediatric community-acquired pneumonia (CAP) is a major public health challenge in children, requiring accurate and timely diagnosis of causative pathogens for effective antibiotic treatment. We aimed to explore the utility of next-generation sequencing (NGS) in precise diagnosis of pediatric CAP and its effect on treatment outcome of these children. METHODS: A systematic review and meta-analysis was conducted to compare NGS-guided antibiotic therapy with conventional methods in pediatric CAP. The study followed PRISMA guidelines and searched for electronic databases including PubMed/MEDLINE, Embase, Scopus, and Web of Sciences from 2012 to 2023. Studies on pediatric CAP (<18 years) using NGS alongside conventional diagnostics, were included. RESULTS: Database search identified 721 studies and 6 were finally included for review, published between 2019 and 2023. Meta-analysis revealed an overall odds ratio of 2.39 (95 % CI 1.22, 3.56) for NGS vs conventional methods. Detection rates using NGS ranged from 86% to 100 %, surpassing conventional methods (26%-78.51 %). Five out of selected 6 studies (83.33 %) have documented that change in treatment based on NGS finding resulted in clinical improvement of patients. There was no significant heterogeneity and potential bias among the studies. Nearly 80 % of the studies were of good quality. CONCLUSION: The NGS (particularly metagenomic sequencing) is a promising tool for diagnosing paediatric CAP with high accuracy. It can improve antibiotic usage practices and patient outcomes, potentially reducing antibiotic resistance. Based on meta-analysis, training of healthcare professionals in NGS methodologies and result interpretation is highly recommended.

Leveraging new approach methodologies: ecotoxicological modelling of endocrine disrupting chemicals to Danio rerio through machine learning and toxicity studies.

New approach methodologies (NAMs) offer information tailored to the intended application while reducing the use of animals. NAMs aim to develop quantitative structure-activity relationship (QSAR) and quantitive-Read-Across structure-activity relationship (q-RASAR) models to predict and categorize the acute toxicity of known and unknown endocrine-disrupting chemicals (EDCs) against zebrafish. EDCs are a diverse group of toxic substances that disrupt the endocrine system of humans and animals. The q-RASAR model was constructed and verified using validation metrics (R2 = 0.886 and Q2 = 0.814) which found to be more reliable model compare to QSAR model. The substructure fingerprint was well-fitted for the classification model and it was validated using 10-fold average accuracy (Q = 86.88%), specificity (Sp = 88.89%), Matthew's correlation curve (MCC = 0.621) and receiver operating characteristics (ROC = 0.828). The dataset of unknown substances revealed that phenolphthalein (Php) exhibited a significant level of toxicity based on q-RASAR model. The docking and simulation study indicated that the computationally derived important features successfully bound to the target zebrafish sex hormone binding globulin (zfSHBG). The experimental LC50 value of 0.790 mg L-1 was very close to the predicted value of 0.763 mg L-1, which provides high confidence to the developed model.

An advanced double-phase stacking ensemble technique with active learning classifier: Toward reliable disruption prediction in Aditya tokamak.

Disruptions in tokamak nuclear reactors, where plasma confinement is suddenly lost, pose a serious threat to the reactor and its components. Classifying discharges as disruptive or non-disruptive is crucial for effective plasma operation and advanced prediction. Traditional disruption identification systems often struggle with noise, variability, and limited adaptability. To address these challenges, we propose an enhanced stacking generalization model called the "Double-Phase Stacking Technique" integrated with Pool-based Active Learning (DPST-PAL) for designing a robust classifier with minimal labor cost. This innovative approach improves classification accuracy and reliability using advanced data analysis techniques. We trained the DPST-PAL model on 162 diagnostic shots from the Aditya dataset, achieving a high accuracy of 98% and an F1-score of 0.99, surpassing conventional methods. Subsequently, the deep 1D convolutional predictor model is implemented and trained using the classified shots obtained from the DPST-PAL model to validate the reliability of the dataset, which is tested on 47 distinct shots. This model accurately predicts the disruptions 7-13 ms in advance with 93.6% accuracy and exhibited no premature alarms or misclassifications for our experimental shots.

Therapeutic potential of monoterpene molecules acts against 7KCh-mediated oxidative stress and neuroinflammatory amyloidogenic signalling pathways.

Alzheimer's disease (AD) is a degenerative disorder characterised by amyloid-beta aggregates activated by the accumulation of lipid molecules and their derivatives, especially 7-ketocholesterol (7KCh), an oxidised lipid that plays a great part in the progression of AD. The current therapeutics need bio-potential molecules and their biomedical application preventing 7KCh-induced cytotoxicity. In this study, bornyl acetate (BA) and menthol (ME), the natural monoterpenes were investigated for their neuroprotective effects against 7KCh-induced SH-SY5Y cells and their effects were compared to the standard drug galantamine (GA). 7KCh-induced changes like lipid accumulation, amyloid generation, free radical generation, acetylcholinesterase levels, calcium accumulation and mitochondrial membrane integrity were analysed in SH-SY5Y cells with or without BA and ME treatment. Furthermore, various mediators involved in the amyloidogenic, inflammatory and apoptotic pathways were studied. In our results, the cells induced with 7KCh upon co-treatment with BA and ME significantly reduced lipid accumulation and amyloid generation through toll-like receptor (TLR) 4 suppression and enhanced ATP binding cassette (ABCA) 1-mediated clearance. Co-treatment with BA and ME concurrently regulated oxidative stress, acetylcholinesterase activity, mitochondrial membrane potential and intracellular calcification altered by 7KCh-induced SH-SY5Y cells. Moreover, 7KCh-induced cells showed elevated mRNA levels of misfolded protein markers and apoptotic mediators which were significantly downregulated by BA and ME co-treatment. In addition, the protein expression of amyloidogenic, proinflammatory as well as pro-apoptotic markers was decreased by BA and ME co-treatment in 7KCh-induced cells. Overall, BA and ME mediated inhibition of amyloidogenic activation and cell survival against 7KCh-induced inflammation, thereby preventing the onset and progression of AD in comparison to GA.

Interaction of chikungunya virus glycoproteins with macrophage factors controls virion production.

Despite their role as innate sentinels, macrophages can serve as cellular reservoirs of chikungunya virus (CHIKV), a highly-pathogenic arthropod-borne alphavirus that has caused large outbreaks among human populations. Here, with the use of viral chimeras and evolutionary selection analysis, we define CHIKV glycoproteins E1 and E2 as critical for virion production in THP-1 derived human macrophages. Through proteomic analysis and functional validation, we further identify signal peptidase complex subunit 3 (SPCS3) and eukaryotic translation initiation factor 3 subunit K (eIF3k) as E1-binding host proteins with anti-CHIKV activities. We find that E1 residue V220, which has undergone positive selection, is indispensable for CHIKV production in macrophages, as its mutation attenuates E1 interaction with the host restriction factors SPCS3 and eIF3k. Finally, we show that the antiviral activity of eIF3k is translation-independent, and that CHIKV infection promotes eIF3k translocation from the nucleus to the cytoplasm, where it associates with SPCS3. These functions of CHIKV glycoproteins late in the viral life cycle provide a new example of an intracellular evolutionary arms race with host restriction factors, as well as potential targets for therapeutic intervention.

Silent Screams: A Narrative Review of Cyberbullying Among Indian Adolescents.

Cyberbullying is bullying with the use of digital technologies, which can take place on social media, messaging platforms, gaming platforms, and mobile phones. It is repeated behavior aimed at scaring, angering, or shaming those who are targeted. India happens to be one of the rapidly improving countries in the cyber world and thus faces a lot of problems regarding cyber crimes, especially cyberbullying. This narrative review aims to provide a thorough assessment of the impact of cyberbullying among Indian adolescents. The database engines such as PubMed, Google Scholar, and PsycINFO were searched relevant to the Indian context, focused on cyberbullying and victimization among adolescents, and published within the last 10 years (2014-2024) were included. Around 19 articles were reviewed and analyzed. Cyberbullying in India is on the rise due to increased technology access, social media, and insufficient awareness and prevention measures, with significant gender differences in aggression patterns. The severe psychological and physiological effects on victims, including depression and stress-related health issues, highlight the need for accurate data and culturally tailored interventions. Studies show varying prevalence rates, emphasizing the urgent need for focused efforts to combat cyberbullying among Indian youth. The review encompasses various aspects, including prevalence, standard methods, forms, causes, consequences, and effects on mental health factors contributing to cyberbullying in India. Additionally, the review explores cyberbullying during COVID-19 and interventions for cyberbullying and highlights the evidence from cohort studies, mixed-method studies, and systematic reviews. A growing number of adolescents are experiencing cyberbullying, which has a severe impact on their lives and leads to unexpected deviances. Cyberbullying remains a growing threat, requiring stronger, coordinated action by the government to genuinely make a difference and safeguard adolescents in India.

An automated ECG-based deep learning for the early-stage identification and classification of cardiovascular disease.

BACKGROUND: Heart disease represents the leading cause of death globally. Timely diagnosis and treatment can prevent cardiovascular issues. An Electrocardiograms (ECG) serves as a diagnostic tool for identifying heart difficulties. Cardiovascular Disease (CVD) often gets identified through ECGs. Deep learning (DL) garners attention in healthcare due to its potential in swiftly diagnosing ECG anomalies, crucial for patient monitoring. Conversely, automatic CVD detection from ECGs poses a challenging task, wherein rule-based diagnostic models usually achieve top-notch performance. These models encounter complications in supervision vast volumes of diverse data, demanding widespread analysis and medical capability to ensure precise CVD diagnosis. OBJECTIVE: This study aims to enhance cardiovascular disease diagnosis by combining symptom-based detection and ECG analysis. METHODS: To enhance these experiments, we built a novel automated prediction method based on a Feed Forward Neural Network (FFNN) model. The fundamental objective of our method is to develop the accuracy of ECG diagnosis. Our strategy employs chaos theory and destruction analysis to combine optimum deep learning features with a well-organized set of ECG properties. In addition, we use the constant-Q non-stationary Gabor transform (CQNGT) to convert one-dimensional ECG data into a two-dimensional picture. A pre-trained FFNN processes this image. To identify significant features from the FFNN output that correspond with the ECG data, we employ pairwise feature proximity. RESULTS: According to experimental findings, the suggested system, FFNN-CQNGT, surpasses other state-of-the-art systems in terms of precision of 94.89%, computational efficiency of 2.114 ms, accuracy of 95.55%, specificity of 93.77%, and sensitivity of 93.99% and MSE 40.32%. CONCLUSION: Contributing an automated ECG-based DL system based on FFNN-CQNGT for early-stage cardiovascular disease identification and classification holds great potential for both patient care and public health.