Browse Articles

Association of the CD14 gene rs2569190 polymorphism with the risk of allergic rhinitis: a systematic review and meta-analysis

Determinants of cervical cancer screening among women aged 30 to 49 years in 20 low- and middle-income countries: A multilevel analysis

Background Cervical cancer is preventable, yet it remains a leading cause of cancer death in women. About 90% of cases and 94% of deaths occur in low- and middle-income countries (LMICs). Limited access to screening drives high incidence and mortality. Screening is central to secondary prevention and global elimination efforts. Objective This study aimed to assess determinants of cervical cancer screening among women aged 30–49 years in low- and middle-income countries: a multilevel analysis. Methods A cross-sectional study used nationally representative data from 148,605 weighted women aged 30–49 years in 20 LMICs (2019–2024). Multilevel logistic regression identified factors associated with cervical cancer screening while accounting for cluster-level variation. Statistical significance was set at p < 0.05, with AORs and 95% CIs reported. Model fit and random effects were assessed using deviance, MOR, ICC, and PCV. Result Overall cervical cancer screening uptake was 14.03% (95% CI: 13.63–14.45%), ranging from 0.92% in Mauritania to 42.98% in Zambia. Higher screening was associated with older age 40–49 years (AOR = 1.48; 95% CI: 1.41–1.54), occupation (AOR = 1.15; 95% CI: 1.10–1.21), contraceptive use (AOR = 1.38; 95% CI: 1.31–1.44), recent health-facility visit (AOR = 1.93; 95% CI: 1.84–2.02), prior abortion (AOR = 1.28; 95% CI: 1.22–1.34), female-headed households (AOR = 1.11; 95% CI: 1.05–1.18), high community education (AOR = 1.63; 95% CI: 1.49–1.79), and high media exposure (AOR = 2.54; 95% CI: 2.30–2.80). Lower uptake was observed among individuals in high-poverty communities (AOR = 0.63; 95% CI: 0.57–0.68), higher parity (1–4 birth) (AOR = 0.86; 95% CI: 0.78–0.94); (five or more births) (AOR=0.66 95% CI: 59–0.73), and those residing in rural areas (AOR = 0.89; 95% CI: 0.82–0.97). Conclusion Cervical cancer screening uptake in LMICs is far below the WHO 2030 target, with wide country disparities. Socio-demographic factors, health-facility contact, and community education increase uptake, while poverty and geographic barriers reduce it. Integrating screening into routine reproductive and maternal care, strengthening community and media education, and addressing structural barriers to access are essential to improving coverage.

TCF-CBM: a three-stage collaborative poisoned sample filtering method based on composite backdoor mechanism

Machine learning identifies pupil size and corneal thickness as key predictors of axial elongation rate

Purpose This study aimed to develop a machine learning-based prediction model for myopia progression using ocular biometric parameters to provide an objective assessment tool for clinical practice. Methods A retrospective analysis was conducted on patients treated at Shanghai Parkway Health Ophthalmology Department as the training set, and myopic individuals from the Optometry Center of Peking University People’s Hospital as the validation set. Demographic and biometric data were collected, including central corneal thickness (CCT), axial length (AL), corneal curvature (K-value), anterior chamber depth (ACD), corneal diameter (WTW), and pupil size (PS). Seven machine learning models (e.g., XGBoost, random forest, support vector machine) were employed for modeling, with performance optimized via 5-fold cross-validation. Model accuracy was evaluated using mean squared error (MSE) and the coefficient of determination (R²), and variable importance was analyzed. Results No statistically significant differences were observed in baseline characteristics between the training and validation sets (all P > 0.05). The XGBoost model demonstrated the best performance, achieving R² = 0.913 (MSE = 0.005) on the training set and R² = 0.766 (MSE = 0.016) on the test set. Variable importance analysis revealed pupil size (score 100) and corneal thickness (40.88) as the key predictors of axial elongation rate, followed by age of onset (17.96). Conclusion The machine learning-based prediction model effectively utilizes ocular biometric data to assess myopia progression risk, with pupil size and corneal thickness identified as core predictive factors. This model provides a quantitative tool for early clinical intervention. Future studies should expand the sample size and incorporate additional biomarkers to optimize performance.

A novel improved high-gain quadratic DC–DC converter based on two synchronous power switches and a two-winding coupled inductor

Clip-plate versus suture-anchor in double-door laminoplasty for degenerative cervical myelopathy: Protocol for a multicenter, non-inferiority, randomized controlled trial

Background Degenerative cervical myelopathy (DCM) is a leading cause of spinal cord dysfunction. While cervical laminoplasty (LAMP) is the standard treatment, the optimal fixation method for the opened lamina, specifically between the conventional suture-anchor method and the modern plate system, remains debated. Although clip-plates offer rigid fixation for the opened lamina, they are associated with higher costs and potential complications such as lamina reclosure due to screw dislodgement or hinge fracture. This study aims to verify the non-inferiority of the suture-anchor method compared to the clip-plate method in double-door LAMP. Methods This is a multicenter, open-label, non-inferiority randomized controlled trial. A total of 216 patients with DCM (cervical spondylotic myelopathy [CSM] or ossification of the posterior longitudinal ligament [OPLL]) will be recruited from three high-volume spine centers in Japan. Participants will be randomized (1:1) to undergo double-door LAMP using either clip-plates (control group) or suture-anchors (experimental treatment group). The primary endpoint is the recovery rate of the Japanese Orthopaedic Association (JOA) score at 1 year postoperatively. Secondary endpoints include operative time, blood loss, clinical assessments (EQ-5D-5L, visual analog scale [VAS], and neck disability index [NDI]), radiological outcomes (cervical spinal alignment, lamina retention rate, hinge fracture, bone union, and MRI findings), direct medical costs, and perioperative complications. Conclusions We hypothesize that the suture-anchor technique is non-inferior to the clip-plate system regarding neurological recovery and laminar stability. By rigorously comparing these techniques, this trial seeks to establish high-level evidence for a surgical strategy that maintains clinical standards while potentially reducing healthcare costs. Trail registration Japan Registry of Clinical Trials (jRCT) jRCT1032250437

Effect of time-dependent forcing on pole reversals in a conceptual dynamo model

Short-duration phase-change material cryotherapy selectively enhances early neuromuscular and perceptual recovery

The purpose of this study was to examine whether short-duration phase-change material cooling (PCM) applied at different temperatures influences acute recovery following fatigue induced by stretch–shortening cycle exercise (SSC). Sixty-four physically active participants were randomly assigned to 5°C, 10°C, or 15°C PCM cryotherapy group or a passive recovery control group. After completing a SSC fatigue protocol, participants underwent a 15-minute PCM intervention, and peak torque (PT), mean power, rate of force development (RFD), countermovement jump (CMJ) performance, Rating of perceived exertion (RPE), modified endurance ratio (MER), vastus lateralis (VL) and Rectus Femoris (RF) stiffness were assessed immediately after fatigue (Imm-fatigue), immediately after PCM cryotherapy (Imm-PCM), and 60 minutes post PCM cryotherapy (Post60-PCM). Mean power and RFD were significantly greater in PCM groups compared with the control group at Imm-PCM (P ≤ 0.01), with mean power remaining elevated in the 15°C PCM group at post-60-PCM (P ≤ 0.05). RPE was significantly lower in all PCM groups at Imm-PCM and post60-PCM compared with control (P ≤ 0.01). No between-group differences were observed for PT, CMJ, MER, or muscle stiffness, and no temperature-dependent effects were detected within the 5–15 °C. These findings indicate that 15-minute PCM cryotherapy selectively accelerates early-phase neuromuscular and perceptual recovery without affecting maximal strength, endurance capacity, or passive muscle mechanical properties. From an applied perspective, PCM cryotherapy may be an effective strategy to enhance explosive performance and perceived readiness during short recovery intervals in training or competition settings.

The study on the transport and phosphorylation kinetics of zidovudine in the Chinese population and its significance for individualized antiretroviral therapy

An online stigma reduction education program for healthcare workers working with people who inject drugs: Development

Canada has a high prevalence of people who inject drugs (PWID), many of whom experience limited access to necessary diagnosis, treatment, and support. PWID often avoid seeking care due to stigma from healthcare workers (HCWs). Implementing a stigma reduction education program for HCWs could improve healthcare outcomes for PWID by fostering compassionate, evidence-based approaches to care, enabling HCWs to overcome biases and deliver non-judgmental care. The objective of this study is to determine the content and format for the development of an online stigma reduction education program for HCWs working with PWID. To accomplish that, we completed interviews with PWID and focus groups with HCWs to obtain input about the content and format for the development of an online stigma reduction education program. PWID provided input on the content of the education program, highlighting the importance of module topics through personal accounts of encountering judgment and discrimination in healthcare settings, which led to their reluctance to seek available services due to fear of stigma. HCWs who participated in the focus groups provided input on the content and reached a consensus regarding the format to inform the program development. Through feedback, participants contributed to shaping the content and format, informing the development of a stigma reduction education program. These findings supported the development and refinement of a program prototype to guide future feasibility and effectiveness evaluations.

Wire arc additive manufacturing of ER5183 aluminium alloy

Baa-iov: Blockchain-enabled anonymous authentication for internet of vehicles

As a core component of intelligent transportation systems, the Internet of Vehicles (IoV) relies heavily on secure and efficient authentication mechanisms to support real-time information exchange and data sharing among network entities. However, traditional centralized authentication schemes widely adopted in current IoV systems suffer from several drawbacks, including performance bottlenecks, inefficient cross-domain authentication, and insufficient identity privacy protection, which severely restrict the security and scalable deployment of IoV systems. To address these challenges, this paper proposes a novel blockchain-based multi-Trusted Authority (TA) collaborative authentication and key agreement scheme. The scheme adopts a decentralized cross-TA authentication architecture based on blockchain-enabled trust transfer to eliminate single point of failure risks. Furthermore, it constructs an anonymous authentication protocol supporting both vehicle-to-TA and vehicle-to-vehicle key agreement, ensuring identity privacy and resisting various security attacks. Comprehensive security validation, including Burrows-Abadi-Needham (BAN) logic formal analysis, informal security verification, and ProVerif-based verification, confirms the scheme’s strong security guarantees. Comparative evaluations with existing schemes demonstrate that the proposed scheme achieves reasonable energy consumption while ensuring high security performance. Specifically, its computational cost is reduced by 39.42% compared with the best existing scheme.

Associations of social capital dimensions with charitable giving and hometown tax donation participation in Japan

Association between muscle relaxant dosage and recovery in pediatric otolaryngological surgery: A retrospective cohort study

Background Standardized guidelines for dosing strategies of muscle relaxants—specifically aimed at reducing extubation time and side effects—are currently lacking in pediatric otolaryngological surgery. This retrospective cohort study examined the association between induction dosages of neuromuscular blocking drugs and extubation times in children undergoing ambulatory procedures, aiming to provide evidence for future clinical decision-making. Objective This study examined the association between induction doses of muscle relaxants and two key outcomes in pediatric otolaryngological surgery: extubation times and the incidence of neuromuscular blockade-related complications (particularly residual paralysis and its clinical consequences, such as reintubation). The goal was to provide evidence that can inform dosing strategies aimed at accelerating recovery and minimizing adverse events. Methods A retrospective review was conducted using electronic medical records of pediatric patients who underwent otolaryngological surgery at Shenzhen Hospital, Southern Medical University;data access for research purposes occurred between June 23, 2020, and June 23, 2021. A total of 90 children, aged 3–12 and classified as ASA I-II, was included in this study. The patients were categorized into three groups based on the muscle relaxant used during surgery: R1 (0.4 mg/kg rocuronium bromide), R2 (0.6 mg/kg rocuronium bromide), and C (0.05 mg/kg cisatracurium). Extracted parameters included mean blood pressure (MBP), heart rate (HR), blood oxygen saturation (SpO₂), Cooper scores, Ramsay Sedation Scale (RSS), Agitation Scale (AS), extubation time, and surgery duration. Results The R2 group showed significantly higher mean blood pressure (MBP) than both R1 and C at T1 (both P < 0.05), and higher MBP than R1 and C at T2 (P < 0.01 and P < 0.05, respectively). Heart rate was significantly higher in both rocuronium groups compared to C at T1 and T2 (all P < 0.01). Cooper scores were significantly higher in R2 than in R1 or C (P < 0.01). No significant differences were found in SpO₂ at any time point (including T3 and T4), extubation time, surgery duration, RSS, or AS among groups (P > 0.05). No adverse events were observed in any of the three groups. Conclusion Despite the absence of pharmacological reversal, no clinical manifestations of residual neuromuscular blockade—including hypoxemia, reintubation, or severe emergence agitation—were observed in any group.Notably, rocuronium 0.6 mg/kg exhibited rapid onset, superior intubation conditions, and hemodynamic stability; extubation times and emergence quality were comparable among all groups receiving a single intubating dose of 1–1.5 × ED₉₅ of a neuromuscular blocking agent under the same intravenous-inhalation combined anesthesia.

Hierarchical feature alignment for cross-view geo-localization

Abstract Cross-view geo-localization aims to estimate the geographic coordinates of a street-view query by matching it with an aerial image database containing geotags. However, this task is fundamentally challenged by extreme viewpoint transformations and scale inconsistencies, which hinder the extraction of stable global structures and fine-grained local details. To address these limitations, we propose the GeoAlignNet (GANet), a hierarchical feature learning framework designed to achieve robust cross-scale and cross-view representation alignment for retrieval-based geo-localization. Specifically, GANet comprises two complementary components. First, the Spatial Structure Attention (SSA) module performs structure-aware aggregation by combining window-based attention with adaptive window partitioning and enhanced positional encoding, enabling the network to capture view-invariant spatial layouts and to alleviate spatial misalignment induced by strong perspective changes. Second, the Local Representation Refinement (LRP) module adopts depthwise separable convolutions and a multi-scale gating mechanism to optimally model fine-grained local feature representations, so as to improve the perception of geometric textures and achieve stable characterization against appearance variations and environmental noise. To further improve retrieval discriminability, we adopt a hybrid objective that jointly enforces intra-class compactness and inter-class separability in the embedding space, facilitating stable optimization under extreme cross-domain structural variations. Extensive experiments demonstrate that GANet achieves competitive performance compared with existing cross-view geo-localization methods, highlighting its strong effectiveness and generalization capability.

The stress reduction potential of Bhagavad Gita and Yoga for healthcare workers during the COVID-19 pandemic: A randomized controlled trial

Background Healthcare workers (HCWs) experienced elevated psychological distress during the COVID-19 pandemic. Culturally embedded, non-stigmatizing approaches may improve uptake of mental health support in this population. We aimed to evaluate the impact of Yoga, Bhagavad Gita learning, and their combination (Yoga+Gita) on psychological distress among HCWs. Methods We conducted a prospective, single-center, parallel-group randomized controlled trial at a secondary hospital in India. Eligible HCWs (>18 years, without pre-existing diagnosed mental health conditions) were randomized in a 1:1:1:1 ratio to: Yoga (daily 60-min sessions for one week), Gita (daily 60-min teaching of Bhagavad Gita Chapter 2 for one week), Yoga+Gita (30 min Yoga + 30 min Gita daily for one week), or Control (usual care). Psychological distress was assessed using the Generalized Anxiety Disorder-7 (GAD7) scale at baseline (B-GAD7), immediately post-intervention (IPI-GAD7), and 45 days post-intervention (DPI-GAD7). Participants were aware of group assignment, but data analysts were blinded. Group comparisons used Friedman and Kruskal–Wallis tests with Bonferroni-adjusted post-hoc analyses. We hypothesized that (1) all three interventions would reduce GAD-7 scores compared with control, (2) Gita would produce more durable effects than Yoga alone, and (3) the combined Yoga+Gita intervention would yield the greatest overall reduction in psychological distress. Findings Sixty-eight participants were enrolled (17 per group), with no losses to follow-up. B-GAD7 did not differ across groups (p = 0.908). Compared with Control, Yoga+Gita reduced anxiety immediately (p = 0.009), and Gita reduced anxiety at 45 days (p = 0.047). A clinically meaningful (≥4-point) GAD7 reduction at 45 days occurred in 17.6% (Yoga), 47.1% (Gita), 41.2% (Yoga+Gita), and 11.8% (Control) of the participants. Exploratory analyses suggested larger benefits among women and among those who continued practice. Interpretation Yoga and Gita-learning, particularly in combination, were associated with reductions in psychological distress among HCWs. Trial registration Prospectively registered with the CTRI (CTRI/2021/10/037365).

AI-assisted assessment of bowel preparation from patient-generated images for pre-procedure triage

A multi-dimensional analysis of native and non-native academic research articles in twelve disciplines

Multi-dimensional analysis (MDA) approach has been widely adopted to compare linguistic and register variations between native and non-native researchers’ academic writing in numerous studies. However, only a few MDA studies have identified specific linguistic features for academic writing to develop an MDA framework suitable for this genre. To fill in this gap, this study identified 62 academic English linguistic features which were tagged with MDA tagger and counted by PatCount software programs to develop a novel MDA model for distinguishing native English and Chinese researchers’ research article writing. This yielded four dimensions: academic involvement and interaction vs. information density; interactive argumentation vs. static description; impersonal evaluation vs. personal opinion; and explicit elaborating style vs. simplified reporting style. It was found that native English researchers are more academically and interactionally involved; they are more interactive and personal, and they use an explicit elaborating style than Chinese researchers do. In disciplines of hard or pure sciences, native researchers are more strategic to freely express their author stance, but Chinese researchers tend to be conservative as they follow pre-set disciplinary conventions. These findings suggest that Chinese researchers should exhibit their authorial stance, interact with the readers with confidence and employ more interactive devices to make their writing coherent and explicit. Meanwhile, Chinese conciseness displays clarity and efficiency for native researchers prone to verbosity; Chinese impersonality offers objectivity where natives risk bias. This study also proposed a new method to tag linguistic features in MDA research so that researchers can utilize this method to develop novel MDA models based on their research objectives.

SegFormer-based boundary-aware polyp segmentation with adaptive multi-branch fusion

Enhanced rock recognition via EVSS-integrated YOLO11: A deep learning approach for precise geological classification

Rock identification plays a fundamental role in geological work, particularly in resource reservoir characterization, stratigraphic division, engineering stability assessment, and hazard prevention. However, traditional manual identification approaches exhibit low efficiency and limited ability to capture dynamic and fine-grained features. To address these challenges, this study employs image recognition and object detection techniques to classify igneous, sedimentary, and metamorphic rocks. We propose an improved You Only Look Once version 11 (YOLO11)-based model by integrating the Efficient Visual State Space (EVSS) module, which enhances the extraction of key rock characteristics—such as texture and fractures—by modeling long-range spatial dependencies and overcoming the locality limitations of conventional convolutional networks. The proposed method is evaluated against three mainstream deep learning models. Experimental results show that the EVSS-enhanced YOLO11 achieves the highest classification accuracy of 92%, outperforming the Vision Transformer (ViT, 85%), ResNet (74%), and the standard YOLO11 (87%). In object detection tasks, the EVSS-integrated YOLO11 also demonstrates superior performance, achieving a mean average precision at 50% intersection-over-union (mAP50) of 91.8% compared to 87.7% for the original YOLO11. By combining efficient visual feature modeling with multi-scale detection capability, this study confirms the effectiveness and robustness of the EVSS-YOLO11 framework for rock image identification, providing strong technical support for intelligent geological analysis.