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Many individuals visit rural telemedicine centres to obtain safe and effective health remedies for their physical and emotional illnesses. This study investigates the antecedents of patients’ satisfaction relating to telemedicine adoption in rural public hospitals settings in Bangladesh through the adaptation of Expectation Disconfirmation Theory extended by Social Cognitive Theory. This research advances a theoretically sustained prediction model forecasting patients’ satisfaction with telemedicine to enable informed decision making. A research model explores four potential antecedents: expectations, performance, disconfirmation, and enjoyment; that significantly contribute to predicting patients’ satisfaction concerning telemedicine adoption in Bangladesh. This model is validated using two-staged structural equation modeling and artificial neural network approaches. The findings demonstrate the determinants of patients’ satisfaction with telemedicine. The presented model will assist medical practitioners, academics, and information systems practitioners to develop high-quality decisions in the future application of telemedicine. Pertinent implications, limitations and future research directions are endorsed securing long-term telemedicine sustainability.

Despite modern treatment, infertility remains one of the most common gynecologic diseases causing severe health effects worldwide. The clinical and epidemiological data have shown that several cancerous risk factors are strongly linked to Female Infertility (FI) development, but the exact causes remain unknown. Understanding how these risk factors affect FI-affected cell pathways might pave the door for the discovery of critical signaling pathways and hub proteins that may be targeted for therapeutic intervention. To deal with this, we have used a bioinformatics pipeline to build a transcriptome study of FI with four carcinogenic risk factors: Endometrial Cancer (EC), Ovarian Cancer (OC), Cervical Cancer (CC), and Thyroid Cancer (TC). We identified FI sharing 97, 211, 87 and 33 differentially expressed genes (DEGs) with EC, OC, CC, and TC, respectively. We have built gene-disease association networks from the identified genes based on the multilayer network and neighbour-based benchmarking. Identified TNF signalling pathways, ovarian infertility genes, cholesterol metabolic process, and cellular response to cytokine stimulus were significant molecular and GO pathways, both of which improved our understanding the fundamental molecular mechanisms of cancers associated with FI progression. For therapeutic intervention, we have targeted the two most significant hub proteins VEGFA and PIK3R1, out of ten proteins based on Maximal Clique Centrality (MCC) value of cytoscape and literature analysis for molecular docking with 27 phytoestrogenic compounds. Among them, sesamin, galangin and coumestrol showed the highest binding affinity for VEGFA and PIK3R1 proteins together with favourable ADMET properties. We recommended that our identified pathway, hub proteins and phytocompounds may be served as new targets and therapeutic interventions for accurate diagnosis and treatment of multiple diseases.

Purpose Drawing on the job demands-resources (JD-R) model, the authors examine how working in the hybrid workplace model (telework and flexible work) affects job performance via the intervening role of work engagement. Design/methodology/approach The authors adopted a quantitative approach and collected data from 277 employees working in universities in Nigeria. Partial least square structural equation modelling was used to analyse the data and test the hypotheses. Findings The findings reveal that flexible work, not telework, has a significant and positive effect on job performance. It also emerges that flexible work positively affects work engagement, and work engagement significantly mediates the relationship between flexible work and job performance. However, the findings do not support the effect of telework on work engagement and the mediating role of work engagement in the proposed relation between telework and job performance. Originality/value The paper provides fresh insights by linking the components of the hybrid workplace model with job performance and employee work engagement and extending the JD-R model to the hybrid workplace setting. The practitioners can benefit from the findings of this study by factoring in the importance of the hybrid workplace model in designing policies and procedures to promote job performance.

One of the primary drawbacks associated with natural fiber reinforced composites is their relatively poor mechanical properties. One potential approach to overcome this challenge is to augment the fiber loading, thereby improving the interfacial characteristics and hybridization. In this study, hybrid polyester composite structures reinforced with jute/hemp fibers were fabricated via the hand layup process, with fiber loadings varying between 30%, 50%, and 70% by volume. Fibers were subjected to alkali solutions (NaOH) containing 3% and 5% alkali in advance of the composites' formation. The impact, flexural, and tensile characteristics of hybrid jute/hemp reinforced polyester composites were investigated via laboratory studies. The composite materials that underwent testing with a 50 vol% fiber loading and 3% NaOH exhibited the maximum tensile strength (26.6 MPa), tensile modulus (733.56 MPa), flexural strength (62.7 MPa), and flexural modulus (3.04 GPa). Highlights Hybrid polyester composite structures reinforced with jute/hemp fibers were fabricated. Hand layup method used with various fiber loadings (30%, 50%, and 70% by volume). Highest mechanical properties were obtained for 3% NaOH treatment and 50% fiber loading. Fiber reinforced polymer composites.

Cell-penetrating peptides (CPPs) can translocate across the plasma membrane of living eukaryotic cells and enter the cytosol without significantly affecting cell viability. Consequently, CPPs have been used for the intracellular delivery of biological cargo such as proteins and oligonucleotides. However, the mechanisms underlying the translocation of CPPs across the plasma membrane remain unclear. In this mini-review, we summarize the experimental results regarding the entry of CPPs into lipid bilayer vesicles obtained using three methods: the large unilamellar vesicle (LUV) suspension method, the giant unilamellar vesicle (GUV) suspension method, and the single GUV method. The advantages and disadvantages of these methods are also discussed. Experimental results to date clearly indicate that CPPs can translocate across lipid bilayers and enter the vesicle lumen. Three models for the mechanisms and pathways by which CPPs translocate across lipid bilayers are described: (A) through pores induced by CPPs, (B) through transient prepores, and (C) via formation of inverted micelles. Both the pathway of translocation and the efficiency of entry of CPPs depend on the lipid composition of the bilayer and the type of CPP. We also describe the interaction of CPPs with bacterial cells. Some CPPs have strong antimicrobial activities. There are two modes of action of CPPs on bacterial cells: CPPs can induce damage to the plasma membrane and thus increase permeability, or CPPs enter the cytosol of bacterial cells without damaging the plasma membrane. The information currently available on the elementary processes by which CPPs enter lipid bilayer vesicles and bacterial cells is valuable for elucidating the mechanisms of entry of CPPs into the cytosol of various eukaryotic cells.

Unlike traditional cancer therapies, such as surgery, radiation and chemotherapy that are typically non-specific, cancer immunotherapy harnesses the high specificity of a patient’s own immune system to selectively kill cancer cells. The immune system is the body’s main cancer surveillance system, but cancers may evade destruction thanks to various immune-suppressing mechanisms. We therefore need to deploy various immunotherapy-based strategies to help bolster the anti-tumour immune responses. These include engineering T cells to express chimeric antigen receptors (CARs) to specifically recognise tumour neoantigens, inactivating immune checkpoints, oncolytic viruses and dendritic cell (DC) vaccines, which have all shown clinical benefit in certain cancers. However, treatment efficacy remains poor due to drug-induced adverse events and immunosuppressive tendencies of the tumour microenvironment. Recent preclinical studies have unveiled novel therapies such as anti-cathepsin antibodies, galectin-1 blockade and anti-OX40 agonistic antibodies, which may be utilised as adjuvant therapies to modulate the tumour microenvironment and permit more ferocious anti-tumour immune response.

Nowadays, the socioeconomic status has been changed a lot, so people are now more concerned about their life style and health. They have knowledge about the detrimental effects of synthetic products. That is why they are interested in natural products. Utilization of natural products of plant origin having fewer side effects has gained popularity over the years. There is immense scope for natural products that can intimate health benefits beyond traditional nutrients. Moringa oleifera is one such tree having tremendous nutritional and medicinal benefits. It is rich in macro- and micronutrients and other bioactive compounds which are important for normal functioning of the body and prevention of certain diseases. Leaves, flowers, seeds, and almost all parts of this tree are edible and have immense therapeutic properties including antidiabetic, anticancer, antiulcer, antimicrobial, and antioxidant. Most of the recent studies suggested that Moringa should be used as a functional ingredient in food. The aim of this review is to focus the use of Moringa oleifera as a potential ingredient in food products.

Groundwater is a vital source of safe drinking water in Bangladesh and most South Asian countries. The study aimed to identify the sources and assess the contamination of Fe, Mn, and Pb in groundwater. The study considered published articles, reports, and data repositories of concerned departments over the past two decades using various search engines, including Web of Science, Scopus, Science Direct, Google Scholar, etc. The study results showed the concentrations of Fe, Mn, and Pb in groundwater exceeded 55.93, 75.44, and 37.50%, respectively, of different standards, including the World Health Organization and United Nations Environmental Protection Agency. The concentrations of Fe, Mn, and Pb ranged from 0.003 to 16.6, 0.00063 to 3.11, and 0.0006 to 5.01 mg/L, respectively, and followed the order Fe > Mn > Pb in the groundwater of Bangladesh. Sources of Fe and Mn in groundwater are mostly geogenic in origin, while Pb contamination in groundwater is anthropogenic and derives from industry dust piles, vehicle exhaust discharge, lead pipes, faucets, fixtures, and batteries. The higher levels of heavy metals in groundwater cause health and environmental hazards. The study recommended that the higher concentrations of Fe, Mn, and Pb in groundwater make it unsuitable for drinking purposes and should be treated before consumption.

Malware has emerged as a significant threat to end-users, businesses, and governments, resulting in financial losses of billions of dollars. Cybercriminals have found malware to be a lucrative business because of its evolving capabilities and ability to target diverse platforms such as PCs, mobile devices, IoT, and cloud platforms. While previous studies have explored single platform-based malware detection, no existing research has comprehensively reviewed malware detection across diverse platforms using machine learning (ML) techniques. With the rise of malware on PC or laptop devices, mobile devices and IoT systems are now being targeted, posing a significant threat to cloud environments. Therefore, a platform-based understanding of malware detection and defense mechanisms is essential for countering this evolving threat. To fill this gap and motivate further research, we present an extensive review of malware detection using ML techniques with respect to PCs, mobile devices, IoT, and cloud platforms. This paper begins with an overview of malware, including its definition, prominent types, analysis, and features. It presents a comprehensive review of machine learning-based malware detection from the recent literature, including journal articles, conference proceedings, and online resources published since 2017. This study also offers insights into the current challenges and outlines future directions for developing adaptable cross-platform malware detection techniques. This study is crucial for understanding the evolving threat landscape and for developing robust detection strategies.

Underground gas storage supports the energy transition, enabling long‐term CO2${\\text{CO}}_{2}$sequestration and seasonal H2${\\mathrm{H}}_{2}$storage. A key process shaping the fate of injected gases is Ostwald ripening—the curvature‐driven mass transfer between trapped ganglia—yet its behavior in confined porous structures remains poorly constrained. We present ultra‐high‐resolution microfluidic experiments that track residually trapped hydrogen for weeks in realistic heterogeneous pore networks. The data show rapid local equilibration among neighboring bubbles, followed by slow global depletion driven by long‐range diffusion. We develop a continuum model that couples pore‐scale capillary pressure–saturation relationship, derived using the pore‐morphology method, with macroscopic diffusion. The model predicts saturation evolution without fitting parameters and collapses results across diverse conditions. Reservoir‐scale estimates indicate that local equilibration far outpaces convective dissolution for CO2${\\text{CO}}_{2}$and occurs on timescales comparable to seasonal H2${\\mathrm{H}}_{2}$storage. Because minimal redistribution is required to reach local capillary equilibrium, residual trapping remains stable in the absence of sinks.