Browse Articles

Clinical and cardiopulmonary predictors of functional recovery and complications after transcatheter aortic valve implantation: Protocol of a prospective interventional study

Introduction Transcatheter Aortic Valve Implantation (TAVI) has emerged as a less invasive alternative to surgical aortic valve replacement, especially for high-risk patients. While TAVI is expected to improve symptoms and functional status, clinical recovery is often heterogeneous, and subjective assessments may not fully capture the degree of improvement. To our knowledge, the changes in functional capacity following TAVI have not been well explored using cardiopulmonary exercise testing (CPET).The study aims to characterise mid-term changes in exercise tolerance after TAVI and identify clinical and functional predictors of improvement in exercise capacity and complications after TAVI. Methods and analysis A total of 161 patients with severe aortic stenosis scheduled for TAVI will be prospectively enrolled across three expert centres. Each will undergo clinical assessment and incremental CPET within two weeks before and four to six weeks after the procedure. The primary outcome is a change in VO₂ peak and VO₂ at the anaerobic threshold. Secondary outcomes include exploratory associations between baseline characteristics and observed changes in functional capacity, quality of life and complications. Ethics and dissemination The bioethics committee of the Hospital Clínic de Barcelona, Spain, approved this protocol (HCB/2024/0782). All the participating centres obtained local approval prior to patient recruitment. The findings will be published in a peer-reviewed journal and submitted to relevant conferences. Trial registration ClinicalTrials.gov NCT06833762 (registered 10th of March 2025).

Shear performance of slender reinforced concrete beams: an analysis of various international standards

Abstract The performance and design of reinforced concrete, also known as slender beams are explained in the current study by a number of international codes. Slender beams are essential in modern construction because they preserve structural integrity while allowing for efficient material use. This research conducts a comprehensive comparative analysis of shear design provisions for slender reinforced concrete beams across major international standards, including ECP, ACI, Eurocode, CSA, BS, and JSCE. The innovation lies in systematically identifying differences and commonalities in methodologies related to shear capacity determination, minimum reinforcement requirements, and serviceability criteria. By addressing the current gap of exhaustive analyses needed to standardize criteria and resolve methodological discrepancies, the work aims to enhance the reliability, effectiveness, and uniformity of global shear design processes for slender beams. This comparative approach is intended to assist engineers and academics in making more informed design decisions, thereby improving the efficiency, structural integrity, and safety of slender beam applications in modern construction. In summary, the novel contribution is the exhaustive and systematic comparison of various international design codes concerning slender RC beam shear design. Identification of inconsistencies and variations that affect structural security and design efficiency. Providing insights that could aid in harmonization and standardization of shear design provisions worldwide. Offering recommendations towards achieving more consistent, safe, and economical slender beam designs in contemporary construction.

A solo journey in the shadow of a double-edged pandemic: A qualitative study of women’s experience of being pregnant during the COVID-19 pandemic

The COVID-19 pandemic profoundly affected the emotional well-being of pregnant women. In Sweden, no national lockdown was implemented; instead, healthcare restrictions were imposed, most notably limiting partner involvement in perinatal care. This marked a significant shift from standard practices that emphasize partner participation as a key component for maternal support and well-being. This study aimed to explore women’s experiences of being pregnant during the COVID-19 pandemic. A qualitative interview study was conducted in Sweden, including 30 pregnant women. The data were analyzed using content analysis with an inductive approach. Four overarching themes were identified: Living in the Shadow of the Pandemic, Missing Out on the Shared Journey, Unpredictability Creates Worry and Fear, and Adaptation and Growth in a Threatening World. The findings describe pregnant women’s experiences during the COVID-19 pandemic as a period marked by vulnerability, partner exclusion, uncertainty and emotional strain. However, many participants also demonstrated resilience and developed adaptive strategies. A recurring desire emerged for more inclusive, consistent healthcare practices and clearer communication tailored to the needs of expectant families. The findings highlight the importance of patient-centered, accessible perinatal healthcare and contribute to the existing research by emphasizing the role of support systems and national guidelines in safeguarding maternal and family well-being during future pandemics.

Mesoporous silica nanoparticles functionalized with folic acid and zinc for enhanced targeted delivery of daunorubicin to breast cancer cells

PufCB-Auth: A lightweight continuous multi-factor authentication scheme integrated PUF with charging behavior features for EV charging

As electric vehicles (EVs) gain widespread adoption, interactions between EVs and charging infrastructure are increasing, driving the need for secure and efficient authentication methods. However, existing authentication approaches are inadequate to address the unique challenges of dynamic EV charging scenarios. Moreover, they often suffer from static credentials, high computational overhead, and limited adaptability to dynamic user behavior and environmental variability. To address these challenges, this paper proposed PufCB-Auth, a lightweight multi-factor authentication scheme that integrates hardware-level Physical Unclonable Functions (PUFs) with charging behavior features to generate a multi-modal digital fingerprint. To alleviate the negative effects rooting from EV user’s charging behavior drift and PUF response fluctuations, the paper also proposed Enhanced PufCB-Auth by incorporating a fingerprint update mechanism. The proposed scheme achieves lightweight design, strong robustness, and continuous authentication capability, making it well-suited for dynamic and resource-constrained EV charging environments. Simulation results validate its effectiveness in improving authentication accuracy and robustness, with minimal system overhead, enabling practical deployment in real-world ChaoJi charging pile–EV interaction environments.

Canonical coherence for the estimation of within- and cross-frequency cortico-kinematic interactions

Abstract Cortico-kinematic coherence (CKC) quantifies coupling between cortical activity and movement kinematics, serving as a non-invasive marker of sensorimotor integration and motor control. Conventional CKC approaches primarily assess within (linear) frequency coupling and overlook cross-frequency interactions, which are increasingly recognized as central to corticomuscular communication. We present a novel multivariate framework that extends the canonical coherence (caCOH) method by applying a non-linear warping of peripheral measures, enabling detection of cross-frequency CKC. The method jointly analyzes multichannel EEG and acceleration signals, maximizing sensitivity to spatially distributed neural sources while accounting for frequency-specific structure. Simulations with realistic head modeling show that the approach robustly recovers underlying patterns even at very low signal-to-noise ratios, closely matching the ground truth. Application to empirical EEG and acceleration data demonstrates that cross-frequency CKC is statistically significant in most participants and interaction pairs, indicating consistent non-random coupling. We further introduce an analysis strategy to determine whether observed interactions arise from shared (e.g. due to the signal shape) or distinct cortical sources. This framework provides a multivariate tool for characterizing the neural mechanisms of motor control and offers future opportunities for investigating their disruption in neurological disorders.

Evaluation of plasma anti-CS3 and anti-LTB IgG avidity among Zambian children vaccinated with ETVAX

Background Enterotoxigenic Escherichia coli (ETEC) remains a major cause of diarrheal disease in low- and middle-income countries (LMICs). To curb ETEC related diarrhoea, several candidate vaccines are in development, with ETVAX® being the most advanced. Although immunogenicity studies have primarily focused on measuring antibody titres, assessing antibody avidity offers additional valuable insight into antibody quality and immune maturity. This study assessed anti-CS3 and anti-LTB IgG avidity in Zambian children to better understand vaccine-induced antibody responses in an endemic setting. Methods Children aged 6–23 months (n = 60) received three quarter-doses of ETVAX® with dmLT adjuvant on days 1, 14, and 90. Plasma samples collected at baseline prior to the first vaccination (Day 1; V1), seven days after the second dose (Day 22; V5), and seven days after the third dose (Day 97; V7) were analysed by limiting antigen dilution ELISA to calculate avidity indices (AI). Naïve classification was performed using titre-based thresholds (20th percentile of baseline titres) and avidity-defined naivety (AI < 0.5). Receiver operating characteristic (ROC) analysis was used to evaluate the discriminatory performance of avidity indices against titre-defined naïve status. Results Baseline avidity was detectable for both CS3 and LTB, consistent with prior natural exposure. Mean CS3 IgG avidity decreased from 0.7 at baseline to 0.6 after the third dose ( p  < 0.001), while LTB IgG avidity showed transient decreases but no net gain. Naïve classification at baseline revealed that 9/60 children had titres but low avidity (functional naivety), and 6/60 had waned titres but high avidity. Only one child was naïve by both criteria for CS3, and none for LTB. ROC analysis demonstrated moderate discrimination for CS3 (AUC = 0.65; optimal cut-off AI = 0.36) but poor discrimination for LTB (AUC = 0.30). Conclusion In this endemic population, ETVAX® induced strong antibody titres but minimal changes in avidity over time, with notable inter-individual variability. ROC analysis highlighted context-specific limitations in using avidity to discriminate immune maturity. Together, these findings suggest that while antibody avidity may provide complementary information on antibody quality, its interpretation should be cautious and considered alongside antibody titres in endemic settings.

Mechanistic insights into 18β-glycyrrhetinic acid-induced apoptosis in SCC-9 cells revealed by TMT proteomics and network pharmacology

Engaging communities through participatory learning action for the control and prevention of diabetes: A protocol for the Process Evaluation of the EMPOWER-D trial in Pakistan and Afghanistan

Background Type 2 diabetes is a growing challenge in low- and middle-income countries (LMIC), where health systems face major capacity gaps. Participatory learning and action (PLA) has shown effectiveness in preventing type 2 diabetes in Bangladesh, but little is known about its use in other LMICs for diabetes. The EMPOWER-D (Engagement of community through Participatory learning and action for cOntrol and prevention of type 2 diabetes) trial is testing PLA for diabetes prevention in communities in Pakistan and Afghanistan. This protocol describes the plans for the embedded process evaluation (PE). Methods The PE will use a mixed-methods design across three sites, following the UK Medical Research Council framework for PE, examining implementation, mechanisms of impact and context. Implementation will be assessed using adaptation reports, fidelity checklists, attendance data and supervisor reports. Mechanisms of impact will be explored through interviews, focus group discussions and photovoice. Contextual factors will be examined through interviews with participants, community mobilisers, supervisors and key stakeholders. Quantitative data will be analysed descriptively, while qualitative data will undergo thematic analysis using a theory of change framework. Comparative analysis will identify common and context-specific influences. Discussion This is the first multi-country PE of a PLA intervention for diabetes prevention to our knowledge, and the first in Afghanistan and Pakistan. The study will provide insights into how the intervention was delivered, how and why it worked (or did not work) and the contextual factors shaping outcomes. Findings will inform the adaptation and scale-up of participatory approaches for non-communicable disease prevention in resource strained setting health systems. Trial registration: ClinicalTrials.gov: NCT06561126 (registered 23 August 2024); NCT06570057 (registered 26 August 2024).

Neural grid control systems with predictive transient stability enhancement enabling 100 percent renewable integration through distributed intelligence and real time topology reconfiguration

The library of isolated bacteria from gut microbiota in classical fish models: Zebrafish (Danio rerio), marine (Oryzias melastigma) and freshwater (Oryzias latipes) medaka

Zebrafish ( Danio rerio ), Marine medaka ( Oryzias melastigma ), and freshwater medaka ( Oryzias latipes ) are three major animal species in evaluation of environmental pollutant toxicity and building of human disease models with conserved physiological and molecular pathways. Bacterial strains from gut microbiota should firstly be isolated for their functions’ exploration. In this study, we optimized a culture-based workflow under aerobic and anaerobic conditions to recover intestinal bacteria from adult zebrafish (ZF), marine medaka (MM), and freshwater medaka (OL) using both dissection-based and in vivo sampling. The isolates were then identified by Gram staining, 16S rRNA gene sequencing, phylogenetic analysis, and API 20E-based biochemical characterization. The culturable bacteria isolated from gut microbiota were identified belonged to 14 genera in ZF, 12 genera in MM, and 18 genera in OL. Comparative analysis showed clear differences in the composition of cultured gut bacteria among the three fish species. Overall, the library and the differences of gut bacteria in three key fish models provided the potential applications of bacterial strains as the probiotics, to against the fish pathogens and to increase the pollutant toxicity-resistant. Moreover, the bacterial library will support the deep researches combined with germ-free (GF) animals to clarify the relationships of intestinal microbiota to host health.

Comparative phytochemical and biological profiling of Trifolium rubens L. leaves, flowers, and callus cultures for cosmetic applications

Abstract Trifolium rubens (Fabaceae) is a rare and regionally endangered European species with limited phytochemical and biological data. This study compares extracts obtained from leaves, flowers, and in vitro derived callus cultures. HPLC–DAD analysis confirmed three major groups of metabolites: flavonoids, isoflavonoids, and phenolic acids, with leaves showing the highest polyphenol levels, including trifolin (1257.13 mg/100gDW) and myricetin (1068.20 mg/100gDW). Callus cultures exhibited a distinct isoflavonoid profile dominated by calycosin-7- O -glucoside (516.01 mg/100gDW) and formononetin (103.26 mg/100gDW), accompanied by reduced genistein content compared with parent tissues. All extracts demonstrated antioxidant activity (ABTS IC₅₀: flower 0.02 mg/mL, leaf 0.17 mg/mL, callus 1.51 mg/mL; DPPH IC₅₀: 3.21, 3.93, and 6.16 mg/mL, respectively), moderate inhibition of tyrosinase and elastase, and no cytotoxicity toward HaCaT keratinocytes or A375 melanoma cells. In ex vivo Franz diffusion studies, genistein showed limited permeation but substantial skin accumulation (leaf: 17.07 µg/g; flower: 16.55 µg/g; callus: 2.58 µg/g), supporting localized antioxidant effects. Despite lower total polyphenol content, callus cultures retained relevant bioactivity and accumulated unique isoflavonoids, highlighting their potential as a sustainable alternative source of bioactive compounds. These findings support the cosmetic and dermatological relevance of T. rubens and emphasize the importance of optimizing in vitro cultures to enhance metabolite production.

RDA-YOLO: A robust dynamic adaptive network for tiny insulator defect detection

Insulator defect detection is a critical component in ensuring the safe operation of smart grids. To achieve more effective detection, image-based inspection utilising drone aerial photography offers advantages such as low cost, high efficiency, and superior accuracy. Compared to other approaches, the You Only Look Once (YOLO) method demonstrates outstanding performance in insulator defect detection. However, it struggles to achieve satisfactory results when detecting small defects against complex backgrounds. To address this issue, this paper proposes a high-precision insulator defect detection algorithm named RDA-YOLO, which builds upon the YOLOv8 algorithm as its baseline model. Firstly, a reverse large-selection kernel module is designed to effectively adjust the receptive field size, enhancing feature extraction capabilities for long insulator strings and minute features. Secondly, a Dynamic Head replaces the original detection head, utilising its unified attention mechanism to obtain more consistent classification and localisation features. Finally, a distribution-aware Wise-IoU metric is proposed, modelling bounding boxes as two-dimensional Gaussian distributions. By employing normalised Wasserstein distance, this enhances the network’s detection capability for small targets. Experiments on a proprietary dataset demonstrate that, with only a modest increase in computational overhead, this network achieves 91.6% precision and 91.4% mAP0.5, outperforming other state-of-the-art algorithms. Moreover, we conducted extensive robustness experiments, which demonstrated that our approach achieves significantly enhanced robustness compared to baseline models, rendering it more suitable for detecting extreme weather conditions.

The influence of women’s empowerment on childhood vaccination coverage in Nigeria: a spatio-temporal analysis

A curated dataset and lightweight deep learning framework for tea leaf disease classification

Tea ( Camellia sinensis ) is the world’s second most consumed beverage, enjoyed daily by more than two billion people. In Bangladesh, it serves as a cornerstone agricultural export and a major sector of the domestic economy. However, commercial tea cultivation remains highly vulnerable to fungal and pest-related diseases such as Blight, Red Rust, and Helopeltis which severely reduce crop yield and compromise leaf quality. While early detection is critical to preventing widespread outbreaks, traditional manual inspection is slow, subjective, and highly error-prone. Deep learning provides a scalable alternative, yet single-branch networks often struggle to capture both minute disease lesions and broader structural degradation simultaneously. To address this, we propose a Hybrid Feature Fusion architecture that runs two highly efficient feature extractors in parallel: EfficientNetV2-Small to isolate fine-grained local textures, and MobileNetV3-Small to capture the global structural context of the leaf. The models were trained and evaluated on a real-world dataset of 2,000 annotated images, evenly distributed across the four target classes (Blight, Red Rust, Helopeltis, and Healthy). Before training, the images underwent a standardized preprocessing pipeline including resizing to 224 × 224 pixels and normalization, supplemented by a dynamic augmentation strategy featuring random rotations, horizontal flips, and brightness adjustments to improve model robustness. The proposed hybrid framework achieved an outstanding peak classification accuracy of 96.80% alongside a macro Area Under the Curve (AUC) of 0.9980. To rigorously validate its performance, the hybrid model was benchmarked against six diverse architectures: a Vision Transformer (ViT-B16 at 76.40%), a Custom CNN (89.60%), MobileNetV3 (94.40%), ResNet50 (95.60%), DenseNet121 (96.40%), and EfficientNetV2-B3 (97.60%). Although EfficientNetV2-B3 achieved a marginally higher raw accuracy, the proposed dual-branch framework delivered a superior precision-recall balance and faster convergence stability. These findings demonstrate that the proposed hybrid methodology is highly reliable and computationally balanced, making it an ideal candidate for integration into Internet of Things (IoT) edge devices for real-time disease monitoring in precision agriculture.

Development of an energy consumption map for turning inconel 718 through coupled chip-morphology and material-deformation analysis

Burden of head and neck cancers in five East Asian countries from 1990 to 2023: Observation, comparison, and forecast from the global burden of disease study 2023

Background Head and neck cancer (HNC) poses a significant public health challenge worldwide, yet the long-term trends and heterogeneity of its burden within East Asia remain inadequately characterized. This study aims to provide a comprehensive assessment of the HNC burden in five East Asian countries from 1990 to 2023 and project future trends. Methods Utilizing data from the Global Burden of Disease (GBD) 2023, we analyzed the incidence, prevalence, mortality, and disability-adjusted life years (DALYs) of HNC in China, Japan, the Republic of Korea, the Democratic People’s Republic (DPR) of Korea, and Mongolia. We employed a comprehensive analytical approach encompassing age-standardized rates, temporal trends, Joinpoint regression, risk factor attribution, age-period-cohort analysis, as well as decomposition and forecasting analyses. Results From 1990 to 2023, substantial heterogeneity was observed. China demonstrated significant declines in age-standardized incidence rate (ASIR) and mortality rate (ASMR). Conversely, Japan experienced concerning increases in ASIR and ASMR. The Republic of Korea maintained a stable ASIR while achieving a marked ASMR reduction. The Democratic People’s Republic of Korea showed increases in both ASIR and ASMR, while Mongolia reported declines in ASIR and ASMR. Age distribution shifted markedly towards older populations in China, Japan, and the Republic of Korea. Smoking remained the predominant risk factor across HNC subtypes. Forecasts to 2038 project a continued rise in ASIR for Japan and the DPR of Korea, and a high ASMR for the DPR of Korea. Conclusion The HNC burden in East Asia exhibits divergent national trajectories, with smoking remaining the predominant attributable risk factor. Further research is needed to elucidate underlying causes of these cross-country disparities.

Keratin 1 and keratin 18 as immunohistochemical markers for distinguishing pulmonary metastases of oral squamous cell carcinoma from primary lung squamous cell carcinoma

A comparative analysis of objectively assessed physical activity levels in kindergarten and home among children aged 5 to 6

Children’s physical activity (PA) is positively associated with a wide range of developmental and health outcomes. This study compared individual levels of PA in children aged 5–6 years across two settings: kindergarten and home. A total of 522 children (51.9% girls) participated. PA was objectively measured using ActiGraph GT3X-BT accelerometers, and selected socioeconomic indicators (SSI) were parent-reported. Children accumulated significantly more light physical activity (PA) in kindergarten than at home, whereas moderate, vigorous, and total moderate-to-vigorous physical activity (MVPA) were significantly higher at home than in kindergarten (all p < 0.001). Boys showed consistently higher PA levels than girls in both environments. Notably, median MVPA in boys was 22.7 min at home and 17.3 min in kindergarten, compared to 19.0 and 14.0 min in girls, respectively. Median daily step counts in the total sample were also significantly higher at home (3315.5) than in kindergarten (3111.0). Significant associations were observed between selected SSI and PA. Lower parental education levels were associated with higher step counts, light (father’s education) and moderate PA (mother’s education) in kindergarten. Children from families with less favorable financial conditions also had higher MVPA in kindergarten. These findings underscore the importance of the home environment and suggest that certain aspects of socioeconomic disadvantage may be linked to higher PA levels in early childhood.

Optimized GM(0,N) model with exponential–trigonometric transformations and PSO for queue length prediction at metered roundabouts

Abstract This study proposes an optimized GM(0,N) model that integrates entry traffic volume, conflicting flow, and signal timing (green and red times) for predicting queue lengths at metered roundabouts. While conventional GM models have the advantage of requiring few samples and offering high prediction accuracy, they can lead to prediction errors as they do not consider the influence of other factors on time series. To enhance prediction accuracy, the proposed model transforms the original sequence by combining exponential and trigonometric functions to overcome the limitations of single transformation functions in processing original sequences and the difficulty of fixed transformation functions adapting to various data types. Optimal parameters are then determined using PSO. This model was validated using real-world data obtained from metered roundabouts in Adelaide, Australia. Compared to An’s model, as well as the GM(1,1), GM(1,N), and conventional GM(0,N) models, the proposed method demonstrated superior accuracy across MRE, RMSE, MAE, and box plot analyses. These results support the model’s applicability for managing unbalanced roundabout traffic and for effective detector placement.