Search Results (1,454)

Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, pathogens, and clinical biomarkers with high sensitivity and specificity. We analyze technological innovations in cell-free protein synthesis optimization, preservation strategies, and field deployment methods that have enhanced sensitivity, and practical applicability. The integration of synthetic biology approaches has enabled complex signal processing, multiplexed detection, and novel sensor designs including riboswitches, split reporter systems, and metabolic sensing modules. Emerging materials such as supported lipid bilayers, hydrogels, and artificial cells are expanding biosensor capabilities through microcompartmentalization and electronic integration. Despite significant progress, challenges remain in standardization, sample interference mitigation, and cost reduction. Future opportunities include smartphone integration, enhanced preservation methods, and hybrid sensing platforms. Cell-free biosensors hold particular promise for point-of-care diagnostics in resource-limited settings, environmental monitoring applications, and food safety testing, representing essential tools for addressing global challenges in healthcare, environmental protection, and biosecurity. Full article

Avian influenza A viruses (IAVs) pose a persistent threat to the poultry industry, causing substantial economic losses. Although traditional vaccines have helped reduce the disease burden, they typically rely on multivalent antigens, emphasize humoral immunity, and require intensive production. This study aimed to establish a genetically matched host–cell system to evaluate antigen-specific immune responses and identify conserved CD8+ T cell epitopes in avian influenza viruses. To this end, we developed an MHC class I genotype (B21)-matched host (Lohmann VALO SPF chicken) and cell vector (DF-1 cell line) model. DF-1 cells were engineered to express the hemagglutinin (HA) gene of clade 2.3.4.4b H5N1 either transiently or stably, and to stably express the matrix 1 (M1) and nucleoprotein (NP) genes of A/chicken/South Korea/SL20/2020 (H9N2, Y280-lineage). Following prime-boost immunization with HA-expressing DF-1 cells, only live cells induced strong hemagglutination inhibition (HI) and virus-neutralizing (VN) antibody titers in haplotype-matched chickens. Importantly, immunization with DF-1 cells transiently expressing NP induced stronger IFN-γ production than those expressing M1, demonstrating the platform’s potential for differentiating antigen-specific cellular responses. CD8+ T cell epitope mapping by mass spectrometry identified one distinct MHC class I-bound peptide from each of the HA-, M1-, and NP-expressing DF-1 cell lines. Notably, the identified HA epitope was conserved in 97.6% of H5-subtype IAVs, and the NP epitope in 98.5% of pan-subtype IAVs. These findings highlight the platform’s utility for antigen dissection and rational vaccine design. While limited by MHC compatibility, this approach enables identification of naturally presented epitopes and provides insight into conserved, functionally constrained viral targets. Full article

Since the initial use of biological ion channels to detect single-stranded genomic base pair differences, label-free and highly sensitive resistive pulse sensing (RPS) with nanopores has made remarkable progress in single-molecule analysis. By monitoring transient ionic current disruptions caused by molecules translocating through a nanopore, this technology offers detailed insights into the structure, charge, and dynamics of the analytes. In this work, the RPS platforms based on biological, solid-state, and other sensing pores, detailing their latest research progress and applications, are reviewed. Their core capability is the high-precision characterization of tiny particles, ions, and nucleotides, which are widely used in biomedicine, clinical diagnosis, and environmental monitoring. However, current RPS methods involve bottlenecks, including limited sensitivity (weak signals from sub-nanometer targets with low SNR), complex sample interference (high false positives from ionic strength, etc.), and field consistency (solid-state channel drift, short-lived bio-pores failing POCT needs). To overcome this, bio-solid-state fusion channels, in-well reactors, deep learning models, and transfer learning provide various options. Evolving into an intelligent sensing ecosystem, RPS is expected to become a universal platform linking basic research, precision medicine, and on-site rapid detection. Full article

Introduction: Despite the key role of healthcare workers (HCWs) in tuberculosis (TB) prevention and control, there is a lack of regional data on their knowledge, attitudes, and practices (KAPs) regarding the disease in Atlantic Canada. Objectives: To assess the KAPs of HCWs and identify targets for educational interventions to enhance TB care and control. Methods: A cross-sectional study was conducted among HCWs in Atlantic Canada aged $\ge$19 years from October 2023 to February 2024. Participants were recruited via multiple channels such as social media, collegiate email lists, and snowball sampling. Survey data were collected using an online platform and analyzed using IBM SPSS Statistics v29. KAPs were assessed using Likert-type scales and internal consistency was evaluated using Cronbach’s alpha. Results: A total of 157 HCWs participated in this study (age range: 19 to 69 years); most were women (n = 145, 92%), born in Canada (n = 134, 85.4%), with nearly three-quarters (n = 115, 73.2%) who had never lived outside of Canada. Study participants demonstrated moderately high knowledge (M = 29.32, SD = 3.25) and positive attitudes (M = 3.87, SD = 0.37) towards TB and strong practices (M = 4.24, SD = 0.69) in TB care; however, gaps were identified in HCW abilities to recognize less common TB symptoms (e.g., rash and nausea), as well as inconsistent practices in ventilation and pre-treatment initiation. Internal consistency analysis indicated suboptimal reliability across all three KAP domains, with Cronbach’s alpha values falling below 0.7, thwarting further planned analyses. Conclusions: This study found overall moderate-to-strong TB-related KAPs among HCWs in Atlantic Canada; however, critical gaps in knowledge and practice were noted. This new information can now guide future educational initiatives and targeted training to enhance TB preparedness and ensure equitable care for patients in the region. Full article

This paper introduces a passive face-authenticity detection system, designed for integration into an employee work time registration platform. The system is implemented as a stacking ensemble of multiple models. Each model independently assesses whether a camera is capturing a live human face or a spoofed representation, such as a photo or video. The ensemble comprises a convolutional neural network (CNN), a smartphone bezel-detection algorithm to identify faces displayed on electronic devices, a face context analysis module, and additional CNNs for image processing. The outputs of these models are aggregated by a neural network that delivers the final classification decision. We examined various combinations of models within the ensemble and compared the performance of our approach against existing methods through experimental evaluation. Full article

Background: Stigma associated with tuberculosis (TB) continues to undermine patient well-being, treatment adherence, and public health goals and objectives. This study aims to systematically review the literature to identify and synthesize TB stigma reduction interventions published between 2015 and 2025. Methods: Following the PRISMA guidelines, we conducted a comprehensive literature search across PubMed, Scopus, Science Direct, ProQuest, and Google Scholar. Eligible studies included those with qualitative, quantitative, and mixed-methods designs that focused on interventions related to TB-related stigma. We categorized the studies into three groups: (1) intervention development studies, (2) TB treatment programs with stigma reduction outcomes, (3) stigma-specific interventions. Data extraction and quality appraisal were conducted independently by two reviewers using the Mixed Methods Appraisal Tool (MMAT). Results: A total of 15 studies met the inclusion criteria. Five studies focused on co-developing stigma interventions, which incorporated multi-level and multicomponent strategies targeting internalized, enacted, anticipated, and intersectional stigma. Two studies assessed TB treatment-related interventions (e.g., home-based care, digital adherence tools) with incidental stigma reduction effects. The remaining seven studies implemented stigma-targeted interventions, including educational programs, video-based therapy, peer-led support, and anti-self-stigma toolkits. Interventions addressed stigma across individual, interpersonal, institutional, community, and policy levels. Conclusions: This review highlights the evolution and diversification of TB stigma interventions over the past decade. While earlier interventions emphasized education and support, recent strategies increasingly integrate peer leadership, digital platforms, and socio-ecological frameworks. The findings underscore the need for comprehensive, contextually grounded interventions that reflect the lived experiences of people affected by TB. Full article

Alpha-Synuclein (α-Syn) is a presynaptic neuronal protein implicated in the pathogenesis of Parkinson’s disease (PD) and other synucleinopathies, primarily through its aggregation into insoluble fibrils. The extended α-Syn half-life necessitates treatment durations that are incompatible with efficient high-throughput drug screening, can risk compound stability or cause cellular toxicity. To address this, we inserted a PEST sequence, a motif known to promote rapid protein degradation, at the C-terminus of the SNCA gene using CRISPR/Cas9 to create a novel cell line with reduced α-Syn half-life. This modification accelerates α-Syn turnover, providing a robust model for studying α-Syn dynamics and offering a platform that is applicable to other long-lived proteins. Our results demonstrate a six-fold reduction in α-Syn half-life, enabling the rapid detection of changes in protein levels and facilitating the identification of molecules that modulate α-Syn production and degradation pathways. Using inhibitors of the proteasome, transcription, and translation further validated the model’s utility in examining various mechanisms that impact protein levels. This novel cell line represents a significant advancement for studying α-Syn dynamics and offers promising avenues to develop therapeutics for α-synucleinopathies. Future research should focus on validating this model in diverse experimental settings and exploring its potential in high-throughput screening applications. Full article

This paper looks at and describes the potential of using artificial intelligence in smart environments. Various environments such as houses and residential and commercial buildings are becoming smarter through the use of various technologies, i.e., various sensors, smart devices and elements based on artificial intelligence. These technologies are used, for example, to achieve different levels of security in environments, for personalized comfort and control and for ambient assisted living. We investigated the deep learning approach, and, in this paper, describe its use in this context. Accordingly, we developed four deep learning models, which we describe. These are models for hand gesture recognition, emotion recognition, face recognition and gait recognition. These models are intended for use in smart environments for various tasks. In order to present the possible applications of the models, in this paper, a house is used as an example of a smart environment. The models were developed using the TensorFlow platform together with Keras. Four different datasets were used to train and validate the models. The results are promising and are presented in this paper. Full article

Background/Objectives: Embryo selection in IVF is traditionally based on morphology, yet many high-quality embryos fail to implant. Preimplantation genetic testing for aneuploidy (PGT-A) using next-generation sequencing (NGS) has been proposed to improve selection by identifying euploid embryos. However, its effectiveness in women of advanced maternal age remains unclear due to limited randomized data. This pilot trial assessed the feasibility of a full-scale RCT comparing PGT-A to morphology-based selection in women aged 35–42. Methods: This single-centre, two-arm parallel RCT (NCT05009745) enrolled women aged 35–42 undergoing IVF/ICSI with ≥3 good-quality day-3 embryos. Participants were randomized (1:1) to either embryo selection by morphology with fresh transfer or PGT-A with frozen transfer of a single euploid embryo. Allocation concealment was achieved via a secure web-based randomization platform; patients and clinicians were unblinded, but the biostatistician remained blinded. The primary outcome was feasibility of recruitment, randomization, and adherence. Results: Between June 2021 and January 2023, 138 women consented (recruitment rate: 55.8%, 95% CI: 49.7–62.0%) and 100 were randomized. Protocol adherence was 94%. Barriers to recruitment included preference for private PGT-A (19%) or fresh transfer (6%). Among biopsied embryos, 51.4% were euploid and 6.6% low-level mosaic. Intention-to-treat analysis showed no significant differences between PGT-A and control groups in clinical pregnancy rate (50% vs. 40%), live birth rate (50% vs. 38%), or miscarriage rate (12% vs. 8%). Cumulative live birth rate after up to three SETs was 72% vs. 52%, respectively (p > 0.05). No multiple pregnancies occurred. Conclusions: RCTs of PGT-A in older women are feasible. A multicentre design with broader inclusion criteria could improve recruitment and allow better assessment of clinical benefit. Full article

Background/Objectives: This study aims to present a strategic approach to enhancing the photostability and antioxidative resilience of curcumin and capsaicin by integrating selected natural stabilizers within a nanoemulsion-based delivery system. Methods: Coffee extract (Coffea arabica Linn.), along with its active components and vitamin E-containing natural oils, was assessed in terms of improving the photostabilizing and antioxidative retention abilities of curcumin and capsaicin. An optimized ratio of the active mixture was then loaded into a nanoformulation. Results: The analysis of active contents with validated high-performance liquid chromatography (HPLC), ferric reducing antioxidant power (FRAP), and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays confirmed the stabilization enhancement after irradiation with UV and white light for 72,000–84,000 lux hours. The optimized combination of coffee extract with turmeric and chili mixtures loaded into the optimized nanoemulsion enhanced the half-lives (T_1/2) of curcumin and capsaicin by 416% and 390%, respectively. The interactions of curcumin and capsaicin with caffeine and chlorogenic acid were elucidated using computational calculations. Interaction energies (E_int), HOMO-LUMO energy gap (HLG) analysis, and global reactivity descriptors revealed hydrogen bonding interactions be-tween capsaicin and chlorogenic acid, as well as between curcumin and caffeine. Conclusions: By leveraging the synergistic antioxidative properties of coffee extract and vitamin E within a nanoemulsion matrix, this study overcomes the intrinsic stability limitations of curcumin and capsaicin, offering a robust platform for future pharmaceutical and nutraceutical applications. Full article

Cancer remains a leading global health burden, profoundly affecting patient survival and quality of life. Current treatments—including chemotherapy, radiotherapy, immunotherapy, and surgery—are often limited by toxicity or insufficient specificity. Conventional chemotherapy, for instance, indiscriminately attacks rapidly dividing cells, causing severe side effects. In contrast, peptide-based therapeutics offer a paradigm shift, combining high tumour-targeting precision with minimal off-target effects. Their low immunogenicity, multi-pathway modulation capabilities, and adaptability for diagnostics and therapy make them ideal candidates for advancing oncology care. Innovative peptide platforms now enable three transformative applications: (1) precision molecular diagnostics (e.g., ¹⁸F-PSMA-1007 for prostate cancer detection), (2) targeted therapies (e.g., BT5528 and SAR408701 targeting tumour-specific antigens), and (3) theranostic systems (e.g., RAYZ-8009 and ¹⁷⁷Lu-FAP-2286 integrating imaging and radiotherapy). Despite their promise, peptides face challenges like metabolic instability and short half-lives. Recent advances in structural engineering (e.g., cyclization and D-amino acid incorporation) and delivery systems (e.g., nanoparticles and PEGylation) have significantly enhanced their clinical potential. This review highlights peptide-based agents in development, showcasing their ability to improve early cancer detection, reduce metastasis, and enhance therapeutic efficacy with fewer adverse effects. Examples like CLP002 underscore their role in personalised medicine. By overcoming current limitations, peptide drugs are poised to redefine cancer management, offering safer, more effective alternatives to conventional therapies. Their integration into clinical practice could mark a critical milestone in achieving precision oncology. Full article

We present a miniaturized, inexpensive, and user-friendly microfluidic platform to support biological applications. The system integrates a mini-incubator providing controlled environmental conditions and housing a microfluidic device for long-term cell culture experiments. The incubator is designed to be compatible with standard inverted optical microscopes and Raman spectrometers, allowing for the non-invasive imaging and spectroscopic analysis of cell cultures in vitro. The microfluidic device, which reproduces a dynamic environment, was optimized to sustain a passive, gravity-driven flow of medium, eliminating the need for an external pumping system and reducing mechanical stress on the cells. The platform was tested using Raman analysis and adherent tumoral cells to assess proliferation prior and subsequent to hydrogen peroxide treatment for oxidative stress induction. The results demonstrated a successful adhesion of cells onto the substrate and their proliferation. Furthermore, the platform is suitable for carrying out optical monitoring of cultures and Raman analysis. In fact, it was possible to discriminate spectra deriving from control and hydrogen peroxide-treated cells in terms of DNA backbone and cellular membrane modification effects provoked by reactive oxygen species (ROS) activity. The 800–1100 cm⁻¹ band highlights the destructive effects of ROS on the DNA backbone’s structure, as its rupture modifies its vibration; moreover, unpaired nucleotides are increased in treated sample, as shown in the 1154–1185 cm⁻¹ band. Protein synthesis deterioration, led by DNA structure damage, is highlighted in the 1257–1341 cm⁻¹, 1440–1450 cm⁻¹, and 1640–1670 cm⁻¹ bands. Furthermore, membrane damage is emphasized in changes in the 1270, 1301, and 1738 cm⁻¹ frequencies, as phospholipid synthesis is accelerated in an attempt to compensate for the membrane damage brought about by the ROS attack. This study highlights the potential use of this platform as an alternative to conventional culturing and analysis procedures, considering that cell culturing, optical imaging, and Raman spectroscopy can be performed simultaneously on living cells with minimal cellular stress and without the need for labeling or fixation. Full article

The treatment of type 1 diabetes through pancreatic islet transplantation faces significant limitations, including donor organ shortages and poor islet survival due to post-transplantation loss of extracellular matrix support and inadequate vascularization. Developing biocompatible scaffolds that mimic the native islet microenvironment could substantially improve transplantation outcomes. This study aimed to create and evaluate decellularized (DCL) matrices from porcine organs as potential platforms for islet transplantation. Porcine lung and pancreatic tissues were decellularized using four different protocols combining detergents (Triton X-100, SDS and SDC) with optimized incubation times. The resulting matrices were characterized through DNA quantification and histological staining (H&E and Van Gieson). Islet viability was assessed in vitro using Live/Dead staining after 3 and 7 days of culture on the matrices. In vivo biocompatibility was evaluated by implanting matrices into rat omentum or peritoneum, with histological analysis at 1-, 4-, and 8 weeks post-transplantation. Protocols 3 (for lung tissue) and 4 (for pancreas tissue) demonstrated optimal decellularization efficiency with residual DNA levels below 8%, while preserving the collagen and elastin networks. In vitro, islets cultured on decellularized lung matrix had maintained 95% viability by day 7, significantly higher than the controls (60%) and pancreatic matrix (83%). The omentum showed superior performance as an implantation site, exhibiting minimal inflammation and fibrosis compared to the peritoneum sites throughout the 8-week study period. These findings establish DCL as a promising scaffold for islet transplantation due to its superior preservation of ECM components and excellent support of islet viability. This work provides a significant step toward developing effective tissue-engineered therapies for diabetes treatment. Full article

With the rise of live-streaming services on e-commerce platforms, AI-powered virtual idols have demonstrated tremendous application potential and thus possess high commercial value. From the perspective of psychological distance, this study adopts the Stimulus–Organism–Response (S–O–R) theoretical framework to construct a research model of “AI-powered virtual idols–psychological distance–impulsive buying intention”. The model aims to explore how AI-powered virtual idols promote digital natives’ impulsive buying intention in the context of e-commerce live streaming. Furthermore, this study examines the moderating effect of technology readiness on the relationship between AI-powered virtual idols and psychological distance. The findings reveal that the level of intelligence of AI-powered virtual idols—including interactivity, anthropomorphism, homogeneity, and reputation—enhances digital natives’ impulsive buying intention by reducing psychological distance. For digital natives with lower technology readiness, the effect of AI-powered virtual idols in narrowing psychological distance is more pronounced. These findings enrich AI-driven consumer behavior models from a theoretical perspective and offer theoretical support and practical insights for developing AI-empowered digital marketing strategies tailored to the psychological traits and technological adaptability of digital natives. Full article

Mucosal immunization represents a promising strategy for preventing enteric infections. Rotavirus (RV), a leading gastrointestinal pathogen distinguished by its remarkable stability and segmented double-stranded RNA genome, has been engineered into a versatile oral vaccine vector through advanced reverse genetics systems. The clinical efficacy of live-attenuated RV vaccines highlights their unique capacity to concurrently induce mucosal IgA responses and systemic neutralizing antibodies, positioning them as a multiple action vector for multiple immune protection. In this review, we summarize the RV colonization of the intestine and stimulation of intestinal immunity, as well as recent advancements in RV reverse genetics, and focus on their application in the rational design of a multivalent mucosal vaccine vector targeting enteric pathogens considering the advantages and challenges of RV as a vector. We further propose molecular strategies to overcome genetic instability in recombinant RV vectors, including the codon optimization of heterologous inserts. These insights provide a theoretical foundation for developing next-generation mucosal immunization platforms with enhanced safety, stability, and cross-protective efficacy. Full article