Advancing Open Science

Background: One of the main tools for investigating pulmonary disorders is computed tomography. Starting with a CT, analyses can be qualitative (e.g., direct interpretation of 2D slices, virtual bronchoscopy) or quantitative (e.g., fibrosis score). Qualitative analyses can be performed without segmentation, but quantitative analyses require lung segmentation. Methods: We present the concepts for a class of lung segmentation methods that use region-growing algorithms, the implementation and testing details, and the results obtained in our software platform. Accurate segmentation of lung regions from medical images is a crucial step in computer-aided diagnosis (CAD) systems for pulmonary diseases such as chronic obstructive pulmonary disease (COPD), pneumonia, and lung cancer. Manual segmentation is time-consuming and subjective, while fully automated methods may fail under challenging imaging conditions. Results: This article presents a semi-automated lung segmentation approach, based on region-growing methods, that balances automation with user control. Conclusions: The proposed technique effectively delineates lung boundaries in computed tomography (CT), minimizing computational complexity and manual effort.

Background: Sarcopenia is defined by decreased muscle strength along with low muscle quantity or quality. The assessment of muscle strength may be performed by grip strength test or chair stand test (CST) and both of these tests are treated as equivalent tools for assessing muscle strength. Heart failure with preserved ejection fraction (HFpEF) contributes to the progression of sarcopenia, and it is left ventricular diastolic dysfunction (LVDd) which primarily leads to the development of HFpEF. The aim of this study was to examine the relationship of muscle strength with echocardiographic parameters of LVDd in patients with CKD and eGFR ≤ 29 mL/min/1.73 m² not treated with dialysis. Methods: The study samples consisted of 46 men with CKD stages G4–G5 not treated with dialysis: 23 participants with HGS < 27 kg and 23 individuals with HGS ≥ 27 kg. The assessment of muscle strength was provided by the hand grip strength (HGS) test and the five-times sit-to-stand test (FTSST). Transthoracic echocardiography was performed with the use of a convex probe in conjunction with a Logiq P6 ultrasound system. Results: In G4–G5 CKD patients, upper limb muscle strength did not correspond to lower limb muscle strength. Participants with prolonged FTSST had a lower mean value of septal e’ and higher mean E/e’ compared to individuals with correct both HGS and FTSST. Participants with correct HGS and prolonged FTSST had the lowest mean left ventricular ejection fraction (LVEF), as well as the lowest mean tricuspid annular plane systolic excursion (TAPSE). Conclusions: In G4–G5 CKD patients not treated with dialysis, HGS and FTSST are not equivalent and should not be used interchangeably. In this population, decreased muscle strength is associated with LVDd and FTSST is more sensitive than HGS in the prediction of LVDd. Low muscle strength is also associated with systolic function of the left and right ventricle in G4–G5 CKD patients not treated with dialysis.

Background: Autoimmune diseases (AIDs) are characterized by chronic inflammation and tissue damage resulting from abnormal immune responses. While genetic and environmental factors play significant roles in disease development, essential micronutrient deficiencies (MNDs) represent a critical and often overlooked contributor. Methods: This review examines the interactions between micronutrients and immune cells, focusing on vitamin D, vitamin B12, folate (FA), and iron, and their roles in AIDs, such as rheumatoid arthritis, autoimmune thyroid disorders, multiple sclerosis, systemic lupus erythematosus, and other connective tissue diseases. We explore the immunomodulatory effects of these micronutrients, their impact on immune tolerance, and the mechanisms by which MNDs contribute to disease progression. Results: MNDs are commonly observed in patients with AIDs and are associated with worsening immune dysregulation, increased inflammation, and disease severity. Vitamin D plays a pivotal role in modulating immune responses and attenuating inflammation, while iron and FA are essential for immune cell proliferation and function. Vitamin B12 supports methylation processes and genomic stability. Conclusions: MNDs significantly influence the pathogenesis and progression of AIDs. Routine micronutrient screening and targeted supplementation should be considered as part of clinical management, offering potential adjunctive benefits alongside conventional therapies. Further research is needed to define optimal dosing strategies and to identify patient subgroups most likely to benefit from nutrition-based interventions.

Background: Older adults, including those with Alzheimer’s disease and Alzheimer’s disease-related dementias (AD/ADRD), face barriers in maintaining regular physical activity, which increases their fall risk and reduces their quality of life. The Activity Tracking, Care Partner Co-Participation, Text Reminders, Instructional Education, Video-Guided Physical Rehabilitation, and Exercise trial aims to improve physical activity among older adults. This pilot study aims to assess the feasibility and preliminary efficacy of the ACTIVE intervention. Methods: ACTIVE is a multi-method, two-arm randomized, analyst-blinded crossover pilot trial with an embedded qualitative component. We will recruit 50 community-dwelling dyads (older adult–care partner, n = 100), with and without mild AD/ADRD, in a 1:1 ratio. Each dyad will be randomized to the intervention or control arm, stratified by AD/ADRD diagnosis. The intervention arm will receive activity tracking, motivational texts, walking exercises, educational videos, and video-guided physical rehabilitation sessions, while the control arm will receive only activity tracking. The intervention will run in two halves: a three-week intervention/control, a one-week crossover phase, and a three-week control/intervention phase. The quantitative outcome measures will include feasibility measures (recruitment, adoption, adherence, acceptability, fidelity, and retention), and measures of preliminary efficacy (activity metrics, fall risk and fear of falling, functional limitations, and quality of life). Qualitatively, we will assess participants’ experiences, and facilitators and barriers to engagement in physical activity through semi-structured dyadic interviews and thematic analysis. Conclusions: This pilot study will generate data on the feasibility and preliminary efficacy of the ACTIVE trial. Findings will inform a full-scale implementation trial.

Background/Objectives: Maternal immunization against respiratory syncytial virus (RSV) is an emerging strategy to protect infants during early life when they are most vulnerable to severe RSV infection. However, little is known about the willingness to receive maternal RSV vaccination in China, where the vaccine has not yet been officially approved for marketing. This study aimed to assess the willingness to receive maternal RSV vaccination among women who are currently pregnant and those planning pregnancy in Guangzhou, and to identify the key determinants influencing vaccination willingness. Methods: A cross-sectional survey was conducted in April 2025 among 406 women at Guangzhou Women and Children’s Medical Center, China. Participants completed a self-administered questionnaire covering predisposing factors, enabling resources, health behaviors and awareness, and need factors. Logistic regression analyses were used to identify factors associated with vaccine willingness. A nomogram prediction model was constructed based on significant predictors. Results: Overall, 67.2% (n = 273) of participants reported willingness to receive maternal RSV vaccination. Younger maternal age, higher levels of social support, moderate or high perceived RSV risk, a history of HPV vaccination, and having medical insurance were independently associated with higher willingness to vaccinate. A predictive nomogram incorporating these factors demonstrated good discrimination (AUC = 0.753) and calibration. Age-stratified analysis revealed differing concerns across age groups, with vaccine safety and neonatal protection being the most cited factors influencing decision-making. Conclusions: This study provides the first evidence on maternal RSV vaccination willingness in southern China and highlights several psychosocial and demographic factors influencing vaccine intentions. The nomogram offers a practical tool to estimate individual willingness and guide targeted communication. These findings have implications for future maternal RSV vaccine application strategies in China.

Wireless communication systems, which rely on radio frequencies (RFs), are widely utilized in various applications, such as mobile communications, radio frequency identification, marine networks, smart farms, and smart homes. Due to their ease of installation, wireless systems offer advantages over wired alternatives. But the deployment of high-frequency radio waves for a communication system can pose potential health risks. To address these concerns, many researchers have explored the use of visible light as a safer alternative to radio frequency communication. In this context, optical camera communication has emerged as a good candidate compared to the RF system. Meanwhile, artificial intelligence (AI) is reshaping industries and human life by solving complex problems, enabling intelligent automation, and driving advancements in technologies such as smart farms, smart homes, and future internet of things systems. In this study, we recommend a Multiple-Input Multiple-Output Camera On–Off Keying (MIMO C-OOK) modulation that integrates a YOLOv11 for light source detection and tracking and a deep learning network-based decoder algorithm, optimized for long-range and mobility communication scenarios. The proposed approach enhances the conventional C-OOK system by increasing the data rate and transmission range while reducing errors at the receiver. Implementation results show that the proposed approach can achieve reliable communication up to 10 m with minimal errors, even under mobility conditions (3 m/s, equivalent to walking speed), by optimizing camera parameters and employing forward error correction (FEC).

Lung cancer in never-smokers is increasingly recognized as a distinct clinical and biological entity, often enriched for actionable oncogenic alterations and characterized by molecular profiles that differ from tobacco-associated disease. However, therapeutic evidence for this growing patient population has frequently been extrapolated from trials in which smokers predominate, potentially limiting treatment optimization and biomarker-driven decision-making. In this review, we map and critically appraise clinical trials registered in ClinicalTrials.gov that explicitly target never-smokers with lung cancer, focusing on therapeutic strategies, molecular stratification approaches, trial design features, and temporal trends. We discuss how eligibility definitions, histological and genomic enrichment, and endpoints have been handled across studies, and we highlight persistent gaps in dedicated trial activity, particularly in prospective biomarker-guided designs and contemporary platform strategies. Finally, we propose priorities for future trials to better reflect never-smoker lung cancer biology, improve external validity, and accelerate evidence generation for personalized therapeutic approaches in this population.

E-government adoption rates in emerging economies remain persistently low despite substantial infrastructure investments. Understanding adoption drivers requires synthesizing fragmented empirical evidence on technology acceptance and service quality factors across diverse contexts. Purpose: This study aimed to quantify relationships between (a) perceived ease of use and perceived usefulness, (b) perceived usefulness and behavioral intention, and (c) service quality and user satisfaction in emerging economy e-government contexts. Methods: Following PRISMA 2020 guidelines, we systematically searched Scopus, Web of Science, and Google Scholar (January 2021–October 2024) for peer-reviewed studies reporting standardized path coefficients from structural equation models examining e-government adoption in emerging economies. Two independent reviewers screened 191 records; 15 studies (23 effect sizes; 6732 participants across 10 countries) met inclusion criteria. Three separate random-effects meta-analyses using restricted maximum likelihood estimation assessed pooled effects, heterogeneity, publication bias, and sensitivity to influential observations. Results: Perceived ease of use strongly predicted perceived usefulness (β = 0.385, k = 7, N = 2516), perceived usefulness moderately predicted behavioral intention (β = 0.289, k = 10, N = 3846), and service quality predicted user satisfaction (β = 0.261, k = 6, N = 3151). All effects were statistically significant (p < 0.001) with substantial heterogeneity across studies, and sensitivity analyses confirmed robustness. All prediction intervals remained entirely positive, and sensitivity analyses confirmed robustness. Conclusions: Technology acceptance and service quality constructs consistently predict e-government adoption in emerging economies, though effect sizes are attenuated compared to developed-country benchmarks. The systematic heterogeneity gradient (I²: 89.5%→69.5%→58.4%) indicates that technology acceptance constructs require greater contextual adaptation than service quality dimensions. Policymakers should prioritize interface simplification and address ecosystem barriers to connectivity, digital literacy, and institutional trust alongside system design.