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Comparative evaluation of root canal obturation techniques and sealers in Diabetic Dentin: An in-vitro push-out bond strength test

This study evaluated the comparative performance of different root canal obturation approaches using different sealing materials on the push-out bond strength of dentin samples obtained from patients with diabetes mellitus (DM). Forty single-rooted mandibular premolars were instrumented using the Reciproc R40 system and randomly assigned to four groups (n = 10 teeth each): (1) cold lateral compaction with AH Plus, (2) warm vertical compaction with AH Plus, (3) hydraulic single-cone obturation with gutta-percha and Bioserra sealer, and (4) sealer-only technique using the Bioserra bioceramic sealer. After storage at 37°C and 100% humidity for one week, 1-mm slices were prepared from the coronal, middle, and apical thirds and subjected to push-out testing. Data were analyzed using ANOVA and Tukey’s test (p < 0.05). Significant differences in push-out bond strength were observed among the obturation approaches using different sealer materials (p < 0.05). Bioceramic sealers exhibited higher bond strengths than epoxy resin–based sealers, particularly in the middle and apical thirds. Hydraulic single-cone and bioceramic sealer-only approaches outperformed conventional techniques (p < 0.001), whereas no significant difference was observed between cold lateral and warm vertical compaction techniques. Obturation approaches employing bioceramic sealers demonstrated superior bonding in diabetic dentin, suggesting potential advantages over conventional methods in the context of diabetic dentin.

Association of uric acid and red blood cell distribution width with severe obstructive sleep apnea–hypopnea syndrome in middle-aged males

Background Obstructive sleep apnea-hypopnea syndrome (OSAHS) is sleep-related breathing disorder with high prevalence. Polysomnography is the gold diagnosis standard. Routine clinical biomarkers would assist to reflect disease severity. Our study aimed to explore the association between hematological parameters and newly diagnosed severe OSAHS in middle-aged males. Methods This retrospective study enrolled 132 cases (40 ~ 65 years). Patients were divided into non-severe group (n = 69) and severe group (n = 63) based on the apnea-hypopnea index (AHI). Hematological parameters were compared between the two groups. Unitarian and multivariate logistic regression were performed to identify factors independently correlated with severe OSAHS. Receiver operating characteristic (ROC) curve analysis was performed to evaluate discriminative performance. Spearman correlation and multiple linear regression were utilized to investigate correlated factors with sleep hypoxia. Results Significantly higher hemoglobin, hematocrit (HCT), mean corpuscular volume (MCV), red blood cell distribution width-standard deviation (RDW-SD), and uric acid were found in the severe group than the non-severe group (all P < 0.05). Multivariate logistic regression identified uric acid as the only independent correlate of severe OSAHS (OR = 1.01, P = 0.012). The combination of uric acid and RDW-SD yielded an AUC of 0.79 (95% CI: 0.69–0.89), with a sensitivity of 77.4% and specificity of 80.4%. Spearman analysis showed that uric acid correlated significantly with sleep mean SpO 2 (r = –0.26, P = 0.034) and sleep minimum SpO 2 (r = –0.30, P = 0.014), but not with AHI (r = 0.19, P = 0.123). In multiple linear regression adjusted for age and BMI, both uric acid and RDW-SD remained independently associated with sleep mean and minimum SpO 2 (P < 0.001). Conclusions Uric acid and RDW-SD are independently associated with OSAHS severity and sleep hypoxia in middle-aged males. The combination of these two routine clinical markers may offer useful information for risk stratification, while prospective studies is needed for validation.

Adolescent cognitive function and risk of gestational diabetes mellitus: A retrospective population-based cohort study

Background Gestational diabetes mellitus (GDM) is increasingly prevalent and linked with adverse maternal and neonatal outcomes. Low cognitive function in youth has been associated with various adverse metabolic outcomes. This study examined the association between adolescent cognitive function and GDM in the first pregnancy. Methods In this retrospective nationwide population-based cohort study, data from the Israel Defense Forces conscription database, including cognitive assessments conducted at approximately age 17 years (1976–2016), were linked with electronic medical records from Maccabi Healthcare Services, documenting prenatal care and gestational diabetes screening data. General intelligence test (GIT) scores were standardized into sex-specific Z-scores and categorized as low, intermediate, or high. GDM during first pregnancy was defined according to the two-step approach. Logistic regression analyses were used to calculate odds ratios (OR) for GDM. Results Among 189,663 women, 21,979 (11.6%) had low, 130,215 (68.7%) had intermediate, and 37,469 (19.8%) high GIT Z-scores; 10,187 (5.4%) developed GDM. Relative to high scores, low and intermediate scores were associated with higher odds of GDM: OR 1.17 (95% CI 1.08–1.26) and OR 1.09 (1.03–1.15), respectively. Conclusions Lower adolescent cognitive function was modestly associated with increased risk of GDM in the first pregnancy, independent of sociodemographic factors and adolescent BMI. Cognitive function may serve as an early marker of maternal metabolic health.

Evaluating the effect of bilateral transcutaneous auricular vagus nerve stimulation on motor function recovery after stroke: A multicenter, randomized controlled trial protocol

Introduction Previous studies have demonstrated that vagus nerve stimulation (VNS) is an emerging approach for stroke rehabilitation and numerous studies have shown that VNS can promote motor function recovery and alleviate neurological deficits both in clinical and animal models. However, current clinical applications primarily involve invasive or unilateral stimulation with limited sample sizes and a focus mainly on upper limb function. Recent evidence indicates that bilateral transcutaneous auricular vagus nerve stimulation (BtaVNS) may offer superior signal conduction and therapeutic outcomes compared with unilateral left transcutaneous auricular vagus nerve stimulation (LtaVNS). To date, the efficacy and safety of BtaVNS for comprehensive limb motor rehabilitation after stroke remain underexplored. This study aims to address this gap by conducting a multicenter, randomized controlled trial evaluating BtaVNS in post-stroke patients with hemiplegic limb motor dysfunction. Methods and analysis We will conduct a prospective, double-blind, multicenter randomized controlled trial involving 114 stroke patients diagnosed with hemiplegic limb motor dysfunction. Participants will be randomly assigned to one of three groups: a BtaVNS group, a LtaVNS group, or a control group. All groups will receive routine post-stroke rehabilitative therapy, while the intervention groups will additionally receive non-invasive taVNS: either bilaterally or on the left ear only. The taVNS parameters will be set at 20 Hz frequency, 300 µs pulse width, and individually adjusted intensity (0.5-1 mA), delivered for 30 minutes per session, twice daily, six days per week for four weeks. The co-primary outcomes include the Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and Fugl-Meyer Assessment of Lower Extremity (FMA-LE). Secondary outcomes include the Wolf Motor Function Test (WMFT), Berg Balance Scale (BBS) and Modified Barthel Index (MBI). Exploratory outcomes include neuroimaging evaluations using functional near-infrared spectroscopy (fNIRS). Assessments will be conducted at baseline, after 2 weeks of treatment, after 4 weeks of treatment and at the 8-week follow-up. Safety and adverse events will be monitored throughout the study. Trial registration number ChiCTR2400093825

Renal and endothelial biomarkers in Chagas disease in the Brazilian Amazon region: Early indicators of kidney injury and disease progression

Chagas disease (CD) has impact on Amazon public health, where oral transmission is frequently related to acute cases. This peculiarity influences clinical severity and immunological responses, highlighting the need to investigate novel biomarkers for early detection of renal and endothelial dysfunctions, since conventional methods are limited in identifying subclinical renal injury. The aim of this study is to investigate the expression of biomarkers of renal and endothelial injury in acute and chronic CD in the Brazilian Amazon. A cross-sectional study was conducted between 2021 and 2023 at the Fundação de Medicina Tropical Doutor Heitor Vieira Dourado (FMTHVD), Manaus, Amazonas, Brazil. Seventy-eight native Amazonian patients diagnosed with CD were evaluated and grouped by disease clinical phase: G1a (acute pre-treatment), G1b (acute post-treatment), G2a (chronic indeterminate), and G2b (chronic cardiac). Blood and urine levels of SYN-1, ANG-2, MCP-1, and NGAL were quantified using ELISA test and correlated with creatinine, urea, proteinuria, and glomerular filtration rate (GFR). Biomarkers were elevated across CD phases, despite routine renal function parameters remaining within normal ranges. Urinary NGAL and MCP-1 levels were significantly elevated in G1, reflecting early renal inflammation. SYN-1 was elevated in patient groups compared with controls, indicating early endothelial damage, while ANG-2 showed high variability with limited subgroup discrimination in G2, suggesting progressive endothelial dysfunction. Overall, G1, especially G1b, exhibited a more severe inflammatory and tissue injury profile, whereas G2 groups were similar to controls. Conventional markers did not correlate with the biomarkers, suggesting their sensitivity in detecting early subclinical injury. The novel biomarkers studied showed an association with different phases of CD and signs of endothelial and renal dysfunction, suggesting potential to aid in the detection of subclinical changes related to the disease.

Design of a high-efficiency brushless wound rotor synchronous machine with reduced torque ripple employing a novel stator winding scheme

This paper presents a novel configuration of a brushless wound rotor synchronous machine (BLWRSM). In the proposed configuration, the stator incorporates a specially designed winding having two series-connected sections with unequal numbers of turns. This unique stator winding (SW) scheme generates an additional subharmonic component (SHC) in the stator magnetomotive force (sMMF), which facilitates brushless excitation of the rotor. The rotor includes a field winding (FW) and a harmonic winding (HW), which are connected through an embedded diode bridge rectifier. The SHC in the sMMF produces an alternating voltage in the HW. This alternating voltage is subsequently rectified to direct current (DC) for exciting FW to realize brushless operation. The proposed configuration, employing a unique SW scheme, is evaluated for an 8-pole, 12-slot BLWRSM using two-dimensional finite element analysis in JMAG Designer. The simulation results validate the proposed concept. In comparison with the existing BLWRSM design, the proposed BLWRSM delivers 4.85% higher output power and 4.9% more average torque while using 50.5% lower input current. Unlike conventional BLWRSM topologies requiring dual inverters, the proposed machine operates with a single three-phase inverter and exhibits 0.69% torque ripples. Due to its brushless and spark-free design, the proposed configuration is well-suited for applications in fire-hazard environments such as aircraft systems and the oil and gas industry.

Effects of artificially increased activation of the gluteus medius on ipsilateral lower limb muscles force during gait

Background Functional Electrical Stimulation is widely used in rehabilitation to improve muscle function in individuals with neurological impairments. The gluteus medius muscle plays a key role in pelvic stability and balance during gait. The purpose of this study was to simulate functional electrical stimulation using musculoskeletal modelling to examine the effects of artificially increased gluteus medius activation on the activation of other ipsilateral lower limb muscles during the stance phase of gait in healthy adults. Methods Musculoskeletal modelling simulations were conducted on gait data from 30 healthy participants to compare normal gait and gait modified by artificially increased gluteus medius activation. A static optimisation model was used to promote gluteus medius activation, replicating a functional electrical stimulation intervention. Changes in peak muscle forces, body-weight–normalised muscle impulse, force traces, peak hip joint reaction force, and hip joint reaction force traces were analysed. Results Artificially enhanced gluteus medius activation significantly (p < 0.05) affected the peak force of seven muscles, the body-weight–normalised muscle impulse of eight muscles, peak hip joint reaction force, the force traces of ten muscles, and hip joint reaction force traces during stance. Conclusions Increased gluteus medius muscle activation altered lower extremity muscle coordination through agonist–antagonist interactions, resulting in a redistribution of muscle forces that may be mechanistically associated with improved frontal-plane pelvic control and dynamic balance during walking. These findings, obtained in healthy individuals within an inverse dynamics-based musculoskeletal modelling framework, provide a mechanistic insight into how the increased contribution of the gluteus medius affects distal muscle loading patterns. Although this approach does not directly represent the phase-dependent or adaptive effects of functional electrical stimulation, the observed force distribution patterns may contribute to hypothesis generation for future studies investigating gait disorders.

Experimental and numerical investigation on micro-motion characteristics of lightweight spacecraft

Accurate prediction of micro-motion characteristics is essential to the success of space mission operations. In this paper, the lightweight spacecraft is selected as the research object. Firstly, the micro-motion characteristic test device is designed to carry out the micro-motion experiment, and the micro-motion characteristic of the test device is numerically simulated to verify the accuracy of the model compared with test data. On this basis, the angular velocity interferences of different values and different directions are simulated, and it is verified that the transversal initial interference is much larger than the spinning angular velocity interference. The cloud images of transversal angular velocity and precession angle under different transversal initial interferences are calculated. The conclusions have some guiding significance for the influence of initial disturbance on the micro-motion characteristics of lightweight spacecraft.

Modification and validation of the InVEST erosion model for application at a national scale

Soil erosion is an important ecological impact of human activities such as agriculture, and models can aid in identifying areas most at risk. However, to aid targeting of actions, predictions must simultaneously cover large spatial extents and account for site-specific variation in retention, while achieving adequate parameterisation and evaluation of models remains demanding. To address these issues, we adapted and assessed an erosion model using the InVEST platform, which applies the Revised Universal Soil Loss Equation (RUSLE), for Great Britain (GB). We parametrised the model using GB-specific input data, for multiple crop types, and integrating new factors including sub-annual periodicity, a GB-specific erosivity layer, and Normalized Difference Vegetation Index (NDVI) derived cover management metrics. Our modelled predictions validated well against sediment concentration measurements in rivers, with a predictive accuracy of 78% on normalised data and rank correlation of 0.46 between predictions and observations. However, absolute model values were overestimated by 28-times, especially at higher levels of sediment erosion. This seems related to a lack of measurements of sediment concentrations at peak flows in the validation data, combined with known RUSLE methodological issues. To allow for future model training, we call for improvements to national sediment load monitoring in rivers, by including measurements during peak flows especially, and inclusion of a within stream sedimentation function in the InVEST Sediment Delivery Ratio model. Our InVEST model parametrisation example provides a valuable tool for relative risk mapping, comparing regions and targeting where ecosystems are more prone to erosion. Cover management factors based on NDVI observations are a substantial methodological improvement for RUSLE modelling that can be readily reproduced in other locations. Whereas a sub-annual version did not lead to differences from an annual model in this all-year around rain area it could enhance modelling for more seasonal areas.

Agentic AI-enhanced digital twins for Smart City civil infrastructure: A secure, autonomous and auditable management framework

Smart city implementation increasingly relies on sensing and analytics; however, a persistent operational gap remains between anomaly detection and safe, timely, and accountable intervention in civil infrastructure systems. This paper proposes an Agentic AI-supported Digital Twin framework for smart city civil infrastructure management, where monitoring and action are linked and auditability is maintained. The Digital Twin continuously updates asset and network models of bridges, roads, and water infrastructure using multi-stream telemetry, incorporating state estimation, predictive maintenance, and what-if simulation services. At the orchestration layer, an agent-based Perception–Conceptualization–Action workflow implemented with LangChain and LangGraph enables cross-domain reasoning and coordinated mitigation planning through controlled API calls to municipal data. A permissioned blockchain cryptographically binds observations, approvals, and executed interventions, ensuring provenance, governance, and tamper evidence. To evaluate the framework, 18,000 incident simulations were conducted across five architectural configurations and three scenario complexity levels over 30 independent runs. This simulation study characterises framework behaviour under controlled stochastic conditions and does not constitute real-world operational validation. Ablation analysis isolates each component’s contribution, demonstrating that latency and mitigation gains are primarily attributable to multi-agent orchestration, while the blockchain layer drives decision auditability. Across all configurations, the fully agentic system substantially outperforms the rule-based baseline: mean detection latency of 3,197 s vs. 39,374 s, mitigation success rate of 66.2% vs. 45.5%, blockchain-anchored decision justification of 71.8% vs. 0%, and operator workload reduction of 91.7% vs. 0%. These results demonstrate that combining simulation-enabled digital twins with governance-aware agentic orchestration measurably improves response efficiency, recommendation quality, and action accountability within the bounds of a synthetic evaluation environment.

Hybrid 1D CNN-BiLSTM with focal loss for robust intrusion detection in in-vehicle CAN networks

The Controller Area Network (CAN) bus serves as the primary communication framework in modern vehicles, enabling reliable data exchange among Electronic Control Units (ECUs) for seamless interaction. The CAN protocol lacks built-in protection, leaving in-vehicle networks vulnerable to cyberattacks such as denial-of-service, message injection, replay, and suppression.To address these challenges, this study presents a deep learning–based intrusion detection approach that integrates a 1D Convolutional Neural Network (1D CNN) with a Bidirectional Long Short-Term Memory (BiLSTM) model, along with focal loss to improve detection performance. The 1D CNN is responsible for capturing spatial patterns from CAN frame attributes, including arbitration ID, data length code, and payload information. In contrast, the BiLSTM learns temporal dependencies by analyzing sequence patterns in both forward and backward directions. Furthermore, instead of relying on synthetic data balancing techniques such as SMOTE, focal loss is applied to give greater importance to difficult-to-detect attack samples during training, thereby effectively addressing the issue of class imbalance in CAN datasets. Additionally window labeling tactic that helps detect attacks more sensitively within a temporal window is also proposed. Besides these, the Car-Hacking dataset (driving scenario) with stratified 10-fold cross-validation is used to test the above framework. The experimental results demonstrate that the proposed approach can achieve an accuracy of 97.41%, precision of 96.37%, recall of 96.73%, F1-score of 96.49%, and ROC-AUC of 0.9971 which is way above the baseline BiLSTM model performance from the previous work. These findings confirm that a combination of spatial feature extraction, temporal sequence modeling, and imbalance-aware optimization not only ensures but also delivers a highly effective and more reliable intrusion detection solution for in-vehicle CAN network security.

Rates and predictors of hospital visits after “Possible AF” alerts from a home ECG monitor in older adults with hypertension: A sub-analysis of the Omron Heart Study

Background Home ECG can detect atrial fibrillation (AF), but patients’ hospital visit behavior after “possible AF” alerts remains uncertain. We assessed the rates, timing, and correlates of hospital visits following “possible AF” alerts in older adults with hypertension. Methods and findings In a nationwide, decentralized cohort in Japan, 4,078 individuals aged ≥60 years enrolled; 3,820 were analyzed after exclusions. Participants used a home BP monitor equipped with a 30-s single-lead ECG capable of detecting “possible AF”, twice daily for 3 months. Of 1,700 participants who received ≥1 “possible AF” alert, 399 (23.5%) reported an alert-prompted healthcare facility visit within 3 months, and 289 (17.0%) underwent additional testing. Among 175 participants with valid visit dates, the median time to visit was 28 days (mean 36.4). In multivariable models, factors associated with lower odds of a hospital visit included age < 65 years (OR 0.75, 95% CI 0.59–0.95, p = 0.016), current drinking (OR 0.73, 0.57–0.95, p = 0.018), no daily palpitations (OR 0.69, 0.50–0.95, p = 0.022), and no palpitations on the alert day (OR 0.51, 0.30–0.85, p = 0.010). Notably, 105 of 220 (47.7%) participants with physician-adjudicated AF remained without a clinical diagnosis at 12 months. Conclusions In this cohort of older, hypertensive individuals, follow-up rates after a “possible AF” alert were low; fewer than one in four individuals visited a healthcare facility, and fewer than one in five underwent additional testing within 3 months. Hospital visits were less common among younger participants, those who consume alcohol, and those without palpitations. These findings highlight significant gaps between mHealth alerts and subsequent clinical action.

Design and testing of a soil-dividing device for a pineapple strip-tillage furrower

To address issues such as high soil backfilling rates and difficulty in maintaining the trench shape during the operation of pineapple strip-rotary cultivators, we designed a V-shaped soil-dividing device. Structural modelling was performed using SolidWorks 2022 by establishing force analysis equations for the soil-dividing device and soil motion trajectory equations. A dynamic simulation model based on the discrete element method was constructed using the EDEM software to determine the structural parameters of the soil-dividing device. Stress analysis conducted using the ANSYS software verified that the structural strength of the soil-dividing device met the application requirements. To optimize operational parameters further, a four-factor, five-level orthogonal rotational combination field trial was designed using the central composite response surface method in Design-Expert 12. The installation distance, V-angle, blade roller speed, and forward speed were defined as the experimental factors, with the soil backfilling rate as the evaluation indicator. We analyzed the effects of various factor interactions on the soil backfilling rate. The experimental results indicated that the minimum soil backfilling rate of 38.12%, which is satisfactory for pineapple planting trenching requirements, was achieved at a V-angle of 30°, forward speed of 3.7 km/h, blade roller speed of 290 r/min, and installation distance of 125 mm. This study has significant implications for advancing the mechanization of pineapple cultivation.

Enhancing low-light images with MSHCDI-Net: A multi-scale hybrid cross-domain interaction approach

Low-light image enhancement aims to improve visual visibility and perceptual quality under challenging illumination conditions. However, conventional convolutional neural networks (CNNs) are inherently limited in modeling long-range dependencies due to their restricted receptive fields, which often leads to insufficient global context modeling and suboptimal restoration results. To address this limitation, we propose MSHCDI-Net, a Multi-Scale Hybrid Cross-Domain Interaction Network that effectively integrates CNN and Transformer branches to jointly capture local texture details and global contextual relationships. Specifically, the proposed framework adopts a hierarchical encoder–decoder architecture to perform multi-scale feature extraction and progressive reconstruction. A cross-domain interaction mechanism is introduced to facilitate effective information exchange between convolutional and Transformer representations across multiple resolutions, enabling complementary modeling of fine-grained structures and long-range dependencies. Through adaptive feature fusion and multi-scale guidance, the network achieves improved structural consistency and detail restoration in low-light scenes. Extensive experiments on several public benchmarks demonstrate the effectiveness of the proposed method. MSHCDI-Net achieves 23.45 dB PSNR / 0.848 SSIM on LOL-v1, 23.74 dB / 0.910 SSIM on LOL-v2-synthetic, and 22.24 dB / 0.868 SSIM on LOL-v2-real, demonstrating competitive performance in both quantitative metrics and visual quality.

YOLO11-FR: A bridge crack detection method based on frequency-domain fusion and an edge enhancement mechanism

Bridge cracks are important indicators of structural deterioration, and accurate crack detection is essential for bridge operation, maintenance, and safety assessment. However, crack detection remains challenging because cracks are often slender, low-contrast, and easily confused with concrete texture, stains, and other background patterns. To address these problems, this paper proposes YOLO11-FR, an improved YOLO11-based bridge crack detector that integrates a Fused Fourier Conv Mixer (FFCM) and a Residual Edge Enhancement Module (REEM). FFCM combines local convolution with a gated residual Fourier branch to introduce full-spectrum Fourier-domain feature interaction, while lightweight gating and bounded residual scaling regulate the reconstructed response. REEM enhances crack boundary features using local and dilated depthwise branches, horizontal and vertical stripe-convolution branches, a Sobel edge prior, and channel-spatial gates. Comparative experiments were conducted on GYU-DET-Crack, a crack subset extracted from the public GYU-DET dataset. Compared with the YOLO11n baseline, YOLO11-FR improves mAP50 and mAP50-95 by 3.4 and 3.7 percentage points, respectively. Validation on the Crack500 crack dataset further shows that YOLO11-FR increases mAP50 from 56.0% to 57.7% and mAP50-95 from 32.7% to 34.8%. These results indicate that the proposed YOLO11-FR improves bridge crack detection accuracy and provides a practical detection approach for crack screening under complex concrete surface backgrounds.

Navigating resilience: Mental health self-care among middle-aged and older LGBTQ+ adults in Thailand

Introduction This study explores how middle-aged and older LGBTQ+ adults in Thailand engage in mental health self-care within complex social and cultural environments. While global research has largely reflected Western perspectives, little is known about how self-care is practiced in non-Western, Buddhist, and collectivist contexts. This study situates mental health self-care as both an individual and socially embedded process shaped by cultural beliefs, kinship norms, and structural inequalities. Methods A qualitative study was conducted with 30 LGBTQ+ participants aged 50–68 from Thailand, using thematic analysis. Semi-structured, in-depth interviews were carried out online and analyzed within a thematic framework to identify recurring patterns and culturally grounded meanings. Results Two overarching themes emerged: (1) Socio-cultural backgrounds shaping mental health self-care, which included Family and Childhood Memories, Community Environment, Cultural Beliefs and Mental Health, and Intimacy and Romantic Experience; and (2) Lived Experiences of Mental Health Self-Care, encompassing strategies for Coping with Stigma and Discrimination, Barriers to Mental Health Services, Cultivating Joy, Pride, and Self-Reliance, Community Contribution and Advocacy, Physical Health as Mental Anchor, and Self-Education on Mental Health. Self-care was intertwined with Buddhist ethics, caregiving norms, and digital peer support, reflecting both adaptation and quiet resistance within Thai society. Conclusion Mental health self-care among older LGBTQ+ Thais represents a culturally informed resilience that bridges individual agency and collective well-being. The findings highlight the importance of integrating social determinants of health and cultural context into inclusive mental health policies and community-based interventions for aging LGBTQ+ populations.

Skin manifestations of primary COVID-19 infection with the omicron variant

Background Although cutaneous manifestations of COVID-19 have been increasingly documented across earlier variants, the dermatological characteristics specifically associated with the Omicron variant, particularly in the Chinese population, remain insufficiently characterized in the literature. Objective To characterize cutaneous manifestations in patients with primary COVID-19 infection caused by the Omicron variant and corresponding management. Methods 94 participants were included in this retrospective analysis, who developed dermatologic symptoms within one month of COVID-19 Omicron Variant infection. Results Mean age was 38 years old, ranging from 7 to 89; with 66% aged within 25–50. A significantly higher incidence of skin manifestations was reported among females (males vs. females, 1:2.76, p = 0.001). Skin rashes typically appeared three days after the onset of COVID symptoms (ranging between 2–7 days), which were mostly mild to moderate. Common morphological types included wheals, erythema, and papular/papulovesicular eruptions. Generalized rashes occurred in 50% of cases, while localized rashes mainly affected the extremities. Pruritus was the most frequent symptom (>90%), particularly in patients presenting with wheals. Clinical management included topical steroid creams and antiviral treatment for COVID-19. No follow-ups were required for most participants (>95%). Conclusion Skin rashes associated with Omicron variant COVID-19 infection, predominantly affecting young and middle-aged women, are characterized by wheals, erythema, and papular/papulovesicular eruptions. Early identification and management of these cutaneous symptoms should be integrated in the overall treatment plan of Omicron variant COVID-19 infection.

Correction: Modelling Hepatitis B virus related hospital discharges in Spain: ARIMAX based liver disease forecasting tool for hospital workload and mortality progression

Adverse fetal/neonatal and obstetric outcomes in pregnant women with heart disease: Data from the Registry of Pregnancy and Cardiac Disease (ROPAC) of the Kermanshah, Iran

Background Pregnancy complicated by heart disease can pose serious risks and complications for both the mother and the fetus. Understanding the prevalence of these conditions during pregnancy, along with the various types of cardiac diseases and their associated complications, is essential for reducing maternal and fetal morbidity and mortality during pregnancy and childbirth. Objective This study aims to examine the clinical characteristics, risk factors, and outcomes of heart disease in pregnant women. Methods This single-center prospective registry-based cohort study without a comparison group (single arm) was conducted using data from the Cardiac Disease Registry for pregnant women in Kermanshah, Iran. All pregnant women with structural heart diseases-including congenital heart disease, valvular disease, prosthetic heart valves, cardiomyopathy, ischemic heart disease, aortopathy, and arrhythmias-were included. Data were collected using validated checklists and entered into an online registry. Results A total of 36 pregnant women with heart disease were included. The most common diagnoses were congenital heart disease (38.9%), valvular heart disease (30.6%), and cardiomyopathy (22.2%). Most patients (94.5%) had preserved left ventricular ejection fraction (LVEF ≥40%), and 88.9% had pre-existing cardiac disease, with 86.2% receiving pre-pregnancy cardiac counseling. No cases of maternal or neonatal mortality were observed. New-onset heart failure occurred in 13.9% of women, and 27.8% required hospitalization for cardiac reasons during pregnancy. The total abortion rate was 19.4% (11.1% spontaneous, 8.3% therapeutic). Preterm birth occurred in 24.1% of cases, and low birth weight in 17.2%. The cesarean delivery rate was high (80.6%). Hypertensive disorders and gestational diabetes were relatively uncommon. No congenital heart defects were observed in neonates. Conclusion Comprehensive pre-pregnancy counseling, specialized prenatal care, and multidisciplinary management can lead to favorable maternal and neonatal outcomes in high-risk pregnancies complicated by heart disease. The absence of mortality in this cohort highlights the effectiveness of organized care models. Despite the limited sample size, these findings underscore the value of structured, registry-based approaches to improving outcomes in pregnant women with cardiac disease.

Applying Brazilian front-of-pack nutrition labeling and PAHO nutritional criteria to digital food advertising: regulatory implications for protecting children and adolescents

Front-of-pack nutrition labeling (FoPNL) and restrictions on food advertising are regulatory strategies to support informed dietary choices and reduce exposure to unhealthy food. These measures are often integrated through a policy package, that employs a Nutrient Profile Model (NPM) for the classification of food. In Brazil, however, these policies remain fragmented, and current food advertising regulations do not fully cover all channels, particularly digital media. This study applied the NPM adopted in Brazil’s FoPNL (RDC No. 429/2020 in conjunction with IN No. 75/2020, hereafter RDC 429) and those proposed by the Pan American Health Organization (PAHO) for identifying foods subject to advertising restrictions on social media posts directed at children and adolescents. The sample included posts from ultra-processed food brands/products on Instagram (n = 623), TikTok (n = 257), and YouTube (n = 114). Both NPM were applied to assess non-compliance at the food-item level and at the advertisement level (considering posts containing at least one non-compliant food). At the food-item level, 61.28% of products exceeded at least one item of RDC 429, with the highest prevalence on TikTok (72.63%), while 93.86% were non-compliant according to PAHO, reaching 100% on TikTok and 98.5% on YouTube. At the advertisement level, 49.53% of posts contained at least one non-compliant food under RDC 429, and 74.13% under PAHO, with YouTube showing the greatest potential for restriction (62.16% RDC; 99.10% PAHO). Both models are feasible for regulating digital food advertising: the PAHO provides a robust framework, while RDC 429 offers a strategic starting point given its current implementation in Brazil.