Browse Articles

Proteomic analysis reveals lipid metabolism disruption and key targets in ARPE-19 cells after RNF13 knockdown

Prevalence and risk factors of hypertension in rural Bangladesh: A population-based cross-sectional study

Non-communicable diseases (NCDs), such as hypertension, are amongst the most fatal conditions afflicting people living in low- and middle-income countries (LMIC), including Bangladesh. This study addresses the lack of population-based studies in rural Bangladesh by examining the prevalence and distribution of hypertension and its associated risk factors. To this end, we surveyed adults aged ≥18 years (i.e., household heads and their spouses) from 7384 households across 149 villages in rural Bangladesh in 2017 using a semi-structured questionnaire to collect data on blood pressure, anthropometric, socioeconomic, lifestyle, and behavioral risk factors. Multivariate logistic regression analyses identified age, gender, and socioeconomic status as potential predictors of hypertension. The findings also showed that men and women from higher socioeconomic status (SES) groups had higher rates of overweight and obesity, risk factors for the development of hypertension (4.29% and 1.4% in adult men; 5.8% and 2.29% in adult women), as well as higher rates of fruit and vegetable consumption (10.29% and 7.25% in adult men; 9.95% and 6.84% in adult women). A significant association between tobacco consumption and age was observed for women (p=<0.0001), while higher levels of physical activity were found among men aged 45–54 years [OR:1.9, CI 95% (1.1–3.1)]. Furthermore, women in the highest SES brackets were 1.3 times as likely to engage in “moderate” physical activity as those in the lowest brackets. Age and overweight/obesity were found to be the strongest risk factors for hypertension in both genders, while education was not found to be significantly associated with hypertension in women. Notably, the findings revealed that 33.7% of men and 28.6% of women had elevated blood pressure, qualifying them as either prehypertensive or hypertensive. As such, we recommend that policy interventions aimed at stemming the growth of hypertension among Bangladesh’s rural populations should take gender-specific risk factors, rural-urban disparities, and socioeconomic context into serious policy consideration.

Role of umbilical cord and maternal blood levels of IL-6 and IL-8 in the diagnosis and prediction of early-onset neonatal sepsis

NLOS/LOS identification with LightGBM ensemble

Non-Line-of-Sight (NLOS)/Line-of-Sight (LOS) identification is crucial to accurate Ultra-Wideband (UWB) positioning. The current Machine Learning solutions to this problem have either too many parameters to tune or too simple features to input, which lead to unsatisfactory performance. To address this issue, this paper proposed a novel binary classifier called LightGBM Ensemble which integrates multiple LightGBMs in parallel with multi-scale patch extraction. The heterogeneous LightGBM ensemble architecture boosts the prediction power of individuals. The multi-scale patch extraction scheme extracts informative features from time-frequency domains. Extensive experiments on an open-source dataset were conducted to evaluate the proposed approach, which proves its superior classification performance and generalization performance with feasible complexity compared to the state-of-the-art Deep Learning and Decision Trees methods.

Selaginella sellowii gene regulatory networks reveal distinct transcriptional strategies for dehydration stress and recovery

Intuitionistic fuzzy PAMSSEM method for MAGDM incorporating cumulative prospect theory and its application to the assessment on water resource carrying capacity

Assessing water resources carrying capacity (WRCC) is essential for regional high-quality development. However, most existing WRCC assessment models fail to handle uncertainties and mixed data arising from multiple criteria, which compromises their practical applicability. To address this limitation, this study integrates cumulative prospect theory (CPT) with the PAMSSEM outranking method to develop a novel intuitionistic fuzzy CPT-PAMSSEM model. Then the proposed method is validated through a case study of four cities in the middle and lower reaches of the Tuojiang River Basin. Results show that: (1) WRCC varies significantly across the four cities: Luzhou and Ziyang show favorable conditions, Zigong is near the critical threshold, and Neijiang faces a severe water resource shortage crisis. (2) the proposed model markedly improves the discrimination of different evaluation results, achieving a differentiation level approximately 3–6 times greater than that of conventional methods. These findings provide actionable insights for sustainable water management.

Mapping 99 emotion terms with GPT4 prompting reveals nuanced semantic conceptual structure

Editorial Note: Heat health risk assessment analysing heatstroke patients in Fukuoka City, Japan

Hybrid strategy improved dung beetle optimization algorithm based 2D kapur entropy image segmentation method

Burnout in primary healthcare providers: A cross-sectional study from Al-Khobar, Saudi Arabia

Aim Job burnout is one of the emerging challenges in the healthcare sector which caused various issues among the primary healthcare providers. Hence, the present study was designed to evaluate the prevalence of burnout among the healthcare workers working in the primary healthcare clinics situated in the Alkhobar, Eastern Region of Saudi Arabia. Methods The study was also aimed to evaluate the associated factors related to the burnout. This cross-sectional study included 114 healthcare providers working in the different primary health care centers. Maslach Burnout Inventory (MBI) was used to evaluate the burnout among the respondents. Results The other questions were included the demographics and clinical factors. It was found that the prevalence of the burnout was 21.1%. Emotional exhaustion was found significantly high among females compared to males and those who had monthly income less than 12K compared to those with more than 12K monthly income. Daily patient load was another factor causing emotional exhaustion among the respondents. Conclusion In conclusion, the feeling of depersonalization among the participants was found to be very high followed by emotional exhaustion. The identification of the contributing factors would help to reduce the prevalence. Some of those factors were socio-demographic related and some were related to work.

An innovative bis-allyl rhodanine robust red fluorophore for wide-range optical pH sensing with reversible and durable acidic–alkaline OFF/ON fluorescence

Abstract A sustainable, ultrasound-assisted approach for synthesizing a bis -rhodanine derivative (BR) was established using N -allylrhodanine and 5-bromo-2-hydroxyisophthalaldehyde, employing a recyclable glycerol/proline (2:1) deep eutectic solvent. Structural characterization was unequivocally confirmed by NMR, FT-IR, HRMS, and elemental analysis. The red donor–π–acceptor fluorophore (BR) was evaluated as a wide-range spectrofluorometric pH probe. At 5.0 µM, BR exhibits dual absorption maxima at 357 and 568 nm with high molar absorptivity, and a red emission band centered at 718 nm with a 149 nm Stokes shift. Fluorescence is reversibly governed by a protonation/deprotonation equilibrium: acidification (pH 6.5–1.0) quenches emission with strong linearity ( r  ≈ 0.998), whereas alkalinity (pH 8.5–12.0) stabilizes an ICT-favored emissive state and linearly sensitizes fluorescence ( r  ≈ 0.995). The signal stabilizes within ~ 30 s, remains durable under reversible cycling between the fluorescence OFF mode at pH 2.0 and the fluorescence ON mode at pH 10.5. Therefore, BR interestingly functions as a dual-regime fluorescent pH probe, exhibiting acid-induced quenching at low pH and base-induced sensitization at high pH, with an explicitly characterized near-neutral transition (pH 6.5–8.5) that bridges the two operating domains. Moreover, BR is highly selective to pH as it resists common ionic interferents. Finally, the developed BR-derived spectrofluorometric pH probe is validated for the assay of acidic and alkaline pH in real samples of tap and lake waters, as well as in fresh lemon and orange juices, with high accuracy (98.9–102.3% recovery) and precision (% RSD: 0.93–1.13%).

GraphTransDTI: A novel hybrid framework combining graph transformer and CNN-BiLSTM for enhanced Drug-Protein Interaction prediction

Drug-protein interaction (DTI) prediction is a pivotal step in the drug discovery and repurposing process, helping to minimize experimental costs and time. However, existing deep learning methods often face limitations in simultaneously capturing the spatial structure of drug molecules and the deep contextual correlation with protein sequences. To address this issue, we propose GraphTransDTI, a synergistic hybrid framework that integrates a Graph Transformer to represent drug graph structures, a CNN-BiLSTM network to encode protein sequence context, and a Cross-Attention mechanism to model cross-domain interactions. Comprehensive experiments on two benchmark datasets, KIBA and Davis, across three rigorous scenarios: random splits, cold drug splits, and cold target splits demonstrate that GraphTransDTI achieves competitive performance compared to current state-of-the-art baseline models. Our findings confirm that the strategic combination of graph structural information and sequential attention mechanisms significantly enhances prediction accuracy and robustness in cold-start scenarios, offering a reliable and well-validated approach for high-precision virtual drug screening systems.

Protein kinase Cη–MARCKS axis associations with epithelial barrier disturbance and inflammatory readouts in ulcerative colitis

Sexual harassment at work: Targets’ perspectives on prevention and response

Harassment, including sexual harassment, in the workplace poses a significant threat to workers’ wellbeing and contributes to social inequities. Organizations play a pivotal role in both enabling and preventing workplace harassment. We use a grounded theory approach to understand how workers experience workplace sexual harassment. Drawing on semi-structured interviews with thirty U.S. workers, most from the service industry in the San Francisco Bay Area, who have experienced sexual harassment at work, we describe organizational practices that workers believe effectively prevent and respond to harassment. Findings demonstrate that workplaces may better support workers by (1) setting clear expectations that harassment will not be tolerated and (2) responding effectively to incidents of harassment by establishing an independent entity to whom victims can report incidents, providing verbal support, and taking appropriate actions to support and protect victims.

Detection of early-stage Parkinson’s disease using wearable sensors at multiple body locations and convolutional neural networks

Adaptive geometric-attention network for two-stage lung nodule segmentation and malignancy classification in federated healthcare IoT edge environments

Accurate segmentation and classification of lung nodules in computed tomography (CT) scans remains a critical challenge in early lung cancer detection within distributed healthcare Internet of Things (IoT) environments. This paper presents a novel two-stage framework called Adaptive Geometric-Attention Network (AGA-Net) that integrates geometric constraints with multi-scale attention mechanisms for precise nodule segmentation followed by uncertainty-aware malignancy classification in federated learning scenarios. Unlike existing approaches that rely on traditional convolutional architectures, our method introduces a Geometric-Constrained Attention Module (GCAM) that leverages the spherical nature of lung nodules and a Multi-Scale Uncertainty Quantification Network (MUQ-Net) for robust classification under privacy-preserving constraints. The proposed framework demonstrates superior performance across three benchmark datasets: LUNA16, LIDC-IDRI, and NSCLC-Radiomics, achieving a Dice coefficient of 0.927 for segmentation and AUC of 0.951 for malignancy classification while maintaining computational efficiency validated on IoT-class edge hardware including the NVIDIA Jetson AGX Orin and Jetson Orin Nano. The integration of geometric priors with attention mechanisms, uncertainty quantification, and federated learning capabilities provides both high accuracy and clinical interpretability, making it suitable for next-generation computer-aided diagnosis systems deployable on healthcare IoT edge devices.

A robust, high-content NAM for repeatable and predictive developmental and reproductive toxicity assessment in C. elegans

Abstract Developmental and reproductive toxicity (DART) assessment is essential for product safety evaluation but relies heavily on vertebrate models that are costly, time consuming, and resource intensive. Although Caenorhabditis elegans has emerged as a promising new approach methodology (NAM) for rapid, cost-effective, whole-organism toxicology, broader adoption has been limited by the lack of high-resolution, rapid imaging approaches, limited endpoints, and insufficient evidence supporting assay robustness. To overcome these limitations, we developed vivoDART, a multiparametric imaging-based DART assay designed to be accurate, efficient, robust, and sensitive. Building on our machine learning-accelerated developmental toxicity platform, vivoDART uses microfluidic-assisted, high-resolution brightfield imaging to quantify six developmental and reproductive endpoints for comprehensive DART analysis. Developmental endpoints are derived from automated body-dimension analysis, whereas reproductive endpoints are obtained by quantifying total in utero embryo number and classifying embryos as early- or late-stage relative to the twofold stage. The assay directly assesses sublethal DART phenotypes while minimizing reliance on non-specific apical endpoints such as lethality. vivoDART demonstrated high repeatability, with mean coefficients of variation of 1–5% for developmental endpoints and 6–17% for reproductive endpoints, supporting high statistical power. Assay validation performed using DMSO, methylmercury, and propiconazole involved phenotyping ~ 400,000 embryos across ~ 9,200 worms. Densely sampled concentration–response curves enabled EC x prediction with narrow confidence intervals and captured subtle to strong effects across a broad dynamic range of 1.0–237 µM. Notably, late-stage embryo number was the most sensitive endpoint among the chemicals tested, preceding changes in total embryo number, body size, or viability. These findings indicate that the observed responses reflected DART-specific effects rather than non-specific lethality. These results establish vivoDART as a sensitive, repeatable, and scalable whole-organism platform for rapid, cost-effective chemical prioritization and comparative hazard assessment.

Simulation of emulsion evolution in shear flow field under the control of bidirectional pulsed electric field

Electrostatic demulsification is a widely used technique for treating high-water-cut emulsions (O/W type). However, in high-water-cut emulsions, continuous electric fields often lead to short-circuiting and chain formation. Meanwhile, pure shear fields rely on random collisions, which is inefficient for fine droplets. To address these limitations, this article established a lattice Boltzmann model coupled with electric and shear field. It explored the impact of the combined action of bidirectional pulsed electric field (BPEF) and shear field on the demulsification process. Simulation results reveal that: Under the action of pure shear field, increasing the shear effect will lead oil droplets to move around the flow field center, and forming a stable state eventually. However, after applying bidirectional pulsed electric field on both sides of the flow field, the electric field force breaks this stable state and promotes further aggregation of oil droplets. Analysis of streamline diagrams indicates that: Bidirectional pulsed electric field periodically changes the direction of the electric field force. It leads to induce an unbalanced velocity distribution in the flow field. And this phenomenon can accelerate or decelerate the aggregation of oil droplets. Quantitative analysis indicates that the synergistic coupling of BPEF and shear field significantly outperforms single-field methods. Under the optimal electric potential of V = 300 and shear rate of γ = 0.001 , the composite morpho-dynamic index ( D r ) reached 11.5. This represents a 4.7-fold increase compared to the pure shear field ( D r ≈ 2.0 ) and a 109% improvement compared to the low-voltage condition (V = 100), indicating a highly aggregated and moderately deformed stable state. These simulation results are significant important for understand the synergistic demulsification effects of electric and shear fields.

Sustainable UHPC incorporating water hyacinth ash and magnetized water with enhanced mechanical and durability performance

Tear-film imaging measurements of the lipid and muco-aqueous layers and their association with dry eye disease signs and symptoms in adults: A pilot, prospective, cross-sectional study at a tertiary eye care center

The purpose of this study was to assess tear film (TF) parameters in subjects with signs and symptoms of dry eye disease (DED) using a novel nanometer resolution tear film imager (TFI, AdOM, Israel). In this prospective, cross-sectional observational study, TF parameters, including muco-aqueous layer thickness (MALT) and lipid-layer thickness (LLT), were assessed in 134 eyes of 79 subjects. All participants underwent an anterior segment examination to assess for clinical signs of DED. Subjects completed the ocular surface disease index (OSDI) questionnaire to assess symptoms of DED. Following exclusions, the final analysis included 60 eyes from 34 subjects. A Mann-Whitney test was used for statistical comparisons, with p < 0.05 considered statistically significant. Participants with clinical signs of DED demonstrated significantly lower mean LLT values (42.1nm + / − 13.6) compared to eyes without clinical signs of DED (64.1nm + / − 25.2), p < 0.001. Participants with symptoms of mild, moderate or severe DED had significantly lower mean MALT values (2,858nm + / − 911) compared to eyes without symptoms of DED (3,699nm + / − 1,184), p < 0.05. Our analysis of the human TF indicated that eyes presenting with signs of DED were associated with a thinner LLT, while symptomatic eyes were associated with a thinner MALT.