Search Results (170,276)

Background: Difficulties in recruiting patients for clinical trials increase costs and delay the implementation of new therapies. A better understanding of participants’ motivations and barriers can help with developing effective recruitment strategies. The aim of the study was to identify the factors influencing the decisions of adult Poles to participate in clinical trials. Methods: The survey was conducted among Polish adults aged 18 years and older by the independent research company Ariadna between January and February 2023. The questionnaire consisted of 22 questions, nine of which related to the determinants of participation in clinical trials. 1079 people took part in the survey. Results: The study population included 568 women (52.6%) and 511 men (47.4%). The mean age of respondents was 44.96 years (SD = 16.30). 49.9% of respondents (n = 538) declared their willingness to participate in clinical trials in the future. Among those who were reluctant (n = 158, 14.6%), the main barriers were: safety concerns (n = 59, 5.5%), lack of trust (n = 43, 4.0%), and insufficient knowledge (n = 33, 3.1%). The strongest motivation was the desire to improve health (n = 869, 80.5%), and the most frequently indicated reason for participation was cancer (n = 740, 68.6%). The least frequently indicated were diseases of the urinary and reproductive systems (n = 125; 11.6%). Conclusions: The results highlight key aspects important to patients when deciding whether to participate in clinical trials. Such findings may prove useful for researchers in getting to know their patients better and in developing effective strategies to recruit and retain participants in clinical trials. Full article

To enhance the early-age properties of steel slag cement mortar and promote the resource utilization of metallurgical solid waste, in this study, nano-SiO₂ (KH-NS) was modified using a KH550 silane coupling agent. The hydration kinetics and microstructure evolution were systematically analyzed by means of a macroscopic performance test (setting time and compressive strength) and multi-scale microscopic characterization (characterized by Fourier Transform Infrared Spectroscopy, Scanning Electron Microscopy, X-ray Diffraction, Thermogravimetry-Differential Thermal Analysis, and isothermal calorimetry). The influence mechanism of its content on the early performance of the steel slag cement system was systematically studied. Research findings indicate that at a given dosage, increasing the proportion of KH-NS results in a shorter setting time for steel slag mortar. When the KH-NS dosage reaches 1.5%, the initial and final setting times of steel slag mortar decrease by 24.21% and 21.20%, respectively. The addition of KH-NS effectively enhances the compressive strength of mortar, with a particularly pronounced effect on early strength prior to 14 h of curing. At a KH-NS dosage of 1.5%, the onset of the accelerated phase of hydration heat release in steel slag cement mortar is advanced by 2.5 h. Mechanistic studies indicate that KH-NS accelerates cement hydration by promoting C₃S dissolution and C-S-H gel nucleation through interactions between surface silanol groups (Si-OH) and amino groups (-NH₂). Furthermore, KH-NS refines the pore structure via a micro-aggregate filling effect, reducing the number of harmful pores and improving the pore size distribution. KH-NS continuously consumes Ca(OH)₂ through pozzolanic reactions to generate C-S-H, with its reactivity increasing with higher dosage. Research confirms that KH-NS significantly enhances the early strength and density of steel slag mortar, providing both theoretical justification and technical support for developing low-carbon building materials based on solid waste with high dosage. Full article

Cardiovascular disease (CVD) and cancer frequently coexist in older patients, posing significant challenges in clinical management due to overlapping risk factors and treatment-related complications. This narrative review summarizes current knowledge on the epidemiology, shared pathophysiological mechanisms and clinical impact of neoplastic comorbidities in older adults with cardiovascular diseases. It highlights the increased mortality, morbidity and diminished quality of life resulting from the coexistence of these conditions. The review also discusses personalized management strategies, emphasizing comprehensive geriatric and cardiac assessments, and tailoring oncologic treatments to minimize cardiotoxicity, as well as the role of prevention and rehabilitation programs. As the population ages and cancer survival improves, integrated cardio-oncology care adapted to older adults becomes increasingly essential to optimize outcomes and preserve functional status. Full article

Deoxynivalenol (DON), a Fusarium-derived mycotoxin widely found in grain-based feed, has become a major global environmental contaminant. Reproductive toxicity is one of its most important toxic effects, yet systematic investigations covering both male and female reproductive injury remain limited. This study aimed to establish a combined strategy of network toxicology, molecular docking, molecular dynamics simulation, and single-cell RNA sequencing to evaluate the reproductive toxicity of DON. AKT1, EGFR, PIK3CA, PIK3R1, and SRC were identified as key targets involved in DON-induced reproductive injury. For testicular injury, the prolactin, Ras, HIF-1, and AGE-RAGE signaling pathways were closely associated with DON toxicity. For ovarian injury, the PI3K-Akt, HIF-1, prolactin, insulin, and AGE-RAGE signaling pathways were strongly implicated. Molecular docking demonstrated favorable binding affinities between DON and the hub targets, while molecular dynamics simulation further confirmed the stability of the DON–PIK3CA complex. Single-cell RNA sequencing analysis revealed that these five hub genes were highly expressed in both testicular (SRA667709:SRS3065430) and ovarian (SRA638923:SRS2797100) tissues. These findings deepen current understanding of DON-induced reproductive toxicity, provide new insights into the effects of environmental toxins on reproductive health, and offer a theoretical basis for future studies integrating DON exposure with in vivo validation of core targets and signaling pathways. Full article

Background/Objectives: Complementary medicines (CMs) are widely used in Australia, yet consumer beliefs about their safety and effectiveness often diverge from the scientific evidence. Contemporary statewide data from Victoria, particularly about these perceptions and underlying perception profiles, are limited. We therefore aimed to characterise CM use patterns and perceptions of it among Victorian adults and identify the demographic and use-related belief patterns. Methods: A cross-sectional survey was conducted in metropolitan and regional Victoria (November 2024–August 2025) among adults (≥18 years) who had used complementary medicines in the previous 12 months (N = 447). The questionnaire assessed CM use patterns, perceived effectiveness, safety, quality, perceived risk relative to prescription medicines, adverse events, and demographics. The analyses included descriptive statistics, χ² tests with multiple-comparison control, Spearman correlations, and a multivariable regression. An exploratory factor analysis (EFA) and latent class analysis (LCA) were used to identify the perception dimensions and distinct consumer profiles. Results: CM use was frequent (62.2% daily; 19.2% weekly) and often long term (>1 year, 55.0%). The most commonly used products were vitamin D (53.0%), multivitamins (39.8%), magnesium (34.5%), iron (33.8%), and vitamin C (30.0%). The perceptions were favourable: 77.3% rated CMs as effective, 90.4% as safe, and 60.3% as high quality; 78.5% perceived CMs to have lower side-effect risks than prescription medicines. Adverse events were reported by 12.3%. In the adjusted models, adults ≥ 65 years and monthly/occasional users were less likely to endorse “lower risk than prescription medicines” (aOR: 0.18; 95% CI: 0.06–0.51; aOR: 0.36, 0.18–0.72). East Asian respondents had lower odds of endorsing CM effectiveness than Caucasian/White respondents (aOR: 0.28, 0.11–0.72). Their perceived quality was higher among men (aOR: 1.73, 1.09–2.74) and adults aged 55–65 years (aOR: 3.81, 1.39–10.48). Conclusions: In this contemporary statewide Victorian sample, CM use was common and generally viewed positively, yet the comparative risk may be underestimated. Profiling perception patterns and identifying belief patterns by age, culture, and use intensity provides actionable targets for clinician/pharmacist counselling and culturally tailored education to support safer, evidence-aligned CM use. Full article

Urban mental health is increasingly influenced by daily environmental exposures, yet limited empirical evidence exists regarding how the spatial configuration of blue–green environments, rather than their mere quantity, relates to emotional behavior in high-density cities. Guided by restoration theories and a perception-based perspective on landscape integration, this study analyzes the urban core of Shanghai by linking blue–green configurations to emotional states inferred from 20,907 geotagged social media facial photographs. Facial expressions serve to derive indices for emotional valence and arousal. The results demonstrate significant spatial clustering of emotional behavior, where hotspots are concentrated in higher-quality and more open settings, while coldspots cluster in dense areas with sparse vegetation. Emotional behavior also exhibits demographic heterogeneity, as females display higher valence and arousal than males. Furthermore, happiness tends to increase with age across both genders, whereas arousal declines specifically among male age groups. Crucially, emotional outcomes align more consistently with landscape integration and configuration than with isolated blue or green areas. Factors such as high connectivity, superior vegetation condition, and configurations featuring water embedded within green space are associated with favorable emotional responses. Conversely, extensive edge-dominated interfaces and high traffic exposure correlate with less favorable outcomes. These findings suggest a shift in blue–green planning from increasing total area toward optimizing spatial composition. Specifically, priority should be given to embedded and cohesive designs alongside the reduction of ambient stressors to foster emotionally supportive environments in dense urban cores. Methodologically, image-derived behavioral traces provide a scalable and ecologically grounded approach for investigating place-based affect at a city scale. Full article

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy characterized by profound molecular heterogeneity and high relapse rates, posing significant clinical challenges. Programmed cell death (PCD), encompassing diverse regulated modalities such as apoptosis, necroptosis, and ferroptosis, plays a key role in leukemogenesis and therapeutic response; however, a comprehensive prognostic framework integrating multi-modal PCD pathways in AML remains elusive. In this study, we performed a systematic transcriptomic analysis of 1624 genes associated with 13 distinct PCD forms. A novel computational pipeline combining a variational autoencoder (VAE) for dimensionality reduction and a multilayer perceptron (MLP) for classification was employed to identify robust PCD-related biomarkers, interpreted via SHapley Additive exPlanations (SHAP) analysis. This approach identified 48 candidate genes with discriminative potential between AML and normal bone marrow. Unsupervised consensus clustering based on these genes delineated two molecular subtypes exhibiting divergent clinical outcomes and immune microenvironment profiles. The subtype demonstrated an immunosuppressive phenotype, characterized by enriched regulatory T cells, M2 macrophages, and elevated expression of inhibitory immune checkpoints, correlating with inferior survival. We developed an 8-gene prognostic signature (SORL1, PIK3R5, RIPK3, ELANE, GPX1, VNN1, CD74, and IL3RA) that effectively categorized patients into high- and low-risk groups with notable survival differences, validated across independent cohorts. A prognostic nomogram combining the risk score, age, and cytogenetic risk enhanced the prediction accuracy for overall survival. Our study presents an integrative model that connects multi-modal PCD pathways to AML prognosis, offering a new molecular subtyping system and a clinically applicable risk assessment tool for improved prognostication and personalized treatment strategies. Full article

Postoperative stroke is a serious and fatal condition that often affects elderly surgical patients. This rare but severe complication arises from complex interactions between comorbidities, physiologic instability and demographic disturbances that traditional risk tools often fail to capture.This study aims to develop and validate a machine learning model with an improved ability to predict the risk of postoperative stroke in elderly patients utilising the comprehensive clinical and demographic ICU data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. External validation was performed on MIMIC-III and the eICU Collaborative Research Database, with eICU being the primary validation set. We identified postoperative surgical intensive care unit (SICU) patients aged 55 years or older from all databases. A strict temporal window of the first 24 h of ICU admission was applied across all three datasets while extracting features like laboratory measurements and vital sign summaries in order to ensure that all predictor values were derived from a fixed observation period at the beginning of ICU stay. After preprocessing, applying Multivariate Imputation by Chained Equations (MICE) imputation and initial screening of 88 candidate variables, 20 clinically meaningful predictors were selected through a multistage feature selection pipeline incorporating RFECV and permutation importance. SHAP analysis and LIME analysis were used for interpretability. We evaluated ten machine learning techniques, including Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbors (KNNs), Support Vector Machine (SVM–RBF Kernel), Gradient Boosting (GBDT), Neural Network, XGBoost, CatBoost, Naive Bayes. Among them, Random Forest demonstrated strong predictive performance by achieving an AUROC of 0.8072 (95% CI [0.7890, 0.8253]) on the internal validation set. The model also achieved AUROC of 0.7557 (95% CI [0.7267, 0.7794]) and 0.9144 (95% CI [0.8893, 0.9378]) on the external validation sets eICU and MIMIC-III, respectively. Mean systolic blood pressure, Elixhauser score, minimum calcium, and minimum INR (PT) were consistently identified as the most influential predictors through both SHAP analysis and LIME analysis, thus strengthening model interpretability. Our findings suggest that a Random Forest-based predictive model can provide an accurate and generalisable prediction of postoperative stroke in elderly ICU patients using routinely collected physiologic and laboratory data. This also supports early risk stratification and targeted postoperative monitoring. Full article

The rapid integration of generative artificial intelligence (GAI) tools into academic and professional contexts has raised concerns regarding unethical use and the potential development of problematic usage patterns. Drawing on personality and moral psychology frameworks, the present study examined the associations between antagonistic personality traits (narcissism, Machiavellianism, and psychopathy) and problematic (i.e., addictive) GAI use (PGAIU), as well as the chain mediating effect of moral disengagement and unethical GAI use (UGAIU). Data were collected from an adult sample (N = 491; 52% men; M_age = 43.92) using validated self-report measures. Path analysis indicated that narcissism exhibited significant direct and indirect associations with PGAIU. In contrast, Machiavellianism and psychopathy were indirectly related to PGAIU via moral disengagement and UGAIU but demonstrated non-significant total and direct effects. Multi-group analyses revealed broadly similar structural patterns across men and women, although some paths involving moral disengagement were significant only among men. A comparable pattern was also observed across age groups, with only minor variations in the mediation pathways. Overall, the findings highlight the central role of moral disengagement and unethical GAI-related behaviors in linking antagonistic personality traits to PGAIU. Full article

Antimicrobial resistance represents a major global challenge for healthcare systems, particularly in urinary tract infections (UTIs), where empirical antibiotic therapy is frequently required. Acute pyelonephritis (AP) remains a severe condition, requiring prompt diagnosis and treatment. Local epidemiological data are essential for optimizing therapeutic strategies. The aim of this study was to analyze the pathogen distribution and antimicrobial resistance (AMR) patterns in patients with complicated AP. An observational, analytical study on community-acquired and hospital-acquired AP was conducted on patients admitted with complicated AP between January 2021 and December 2025. After applying the inclusions and exclusions criteria, 553 urinary isolates with complicated AP were analyzed to determine pathogen distribution and phenotypic AMR patterns derived from antimicrobial susceptibility testing. A total of 109 (19.7%) AMR isolates presented resistance phenotype. Resistant phenotypes were more frequently observed among male gender; age did not reach statistical significance. This study highlights the continued predominance of Escherichia coli in complicated AP while demonstrating a significant AMR burden among non-Escherichia coli pathogens, particularly Klebsiella and Pseudomonas species. These findings emphasize the importance of local epidemiological surveillance and culture-guided antibiotic therapy in the management of complicated UTIs. Full article

Background/Objectives: Neoadjuvant chemotherapy is the standard of care for patients with locally advanced gastric cancer. Inflammatory and nutritional indices have been proposed as potential prognostic biomarkers in this setting. This study aimed to evaluate their association with pathological response and relapse-free survival (RFS) in patients with locally advanced gastric cancer treated with the perioperative FLOT regimen. Methods: This multicenter retrospective study included 120 patients treated with perioperative FLOT between 2018 and 2022. Pathological response was assessed using the Becker regression grading system. Pretreatment inflammatory and nutritional biomarkers were calculated from baseline data. Association with pathological responses and RFS were analyzed using logistic regression, Kaplan–Meier estimates, and Cox models. Results: Pathological response was strongly associated with higher radiologic and R0 resection rates and lower recurrence (all p < 0.001). None of the biomarkers correlated significantly with pathological response. Pathological response was the strongest prognostic factor for RFS (p < 0.001), while age (p = 0.011) and histologic subtype (p = 0.004) were also independent predictors. The CEA/albumin ratio showed a trend toward significance (HR 1.805; 95% CI 0.918–3.551; p = 0.087), and patients with lower ratios had longer RFS (median not reached vs. 15.8 months, p = 0.014). Conclusions: Pathological response remains the most powerful prognostic factor in locally advanced gastric cancer treated with perioperative FLOT. Although inflammatory and nutritional indices alone may not predict treatment response, the CEA/albumin ratio demonstrates potential prognostic value for RFS. Larger prospective studies with standardized cut-off values are warranted to validate these findings and to further explore the dynamic prognostic role of immunonutritional markers. Full article

Background/Objectives: This study examined the concurrent validity and test–retest reliability of the novel virtual reality-based Stroop test (VRST), developed based on the principles of embodied cognition. The VRST simulates a clothing-sorting task to assess inhibitory control using cognitive and behavioral (kinematic) measures. Methods: A total of 224 cognitively healthy older adults (mean age = 71.51 years) completed the VRST and a traditional Stroop test in randomized order. The VRST implemented a fixed-difficulty design consisting of 30 incongruent trials, where participants were required to sort virtual objects by their semantic category while ignoring conflicting color cues. The task duration ranged from approximately 1 to 3 min. The VRST assessed task completion time, error count, 3D movement distance, and hesitation latency. Test–retest reliability was examined after two weeks. Concurrent validity was analyzed via Pearson correlation coefficients with traditional Stroop metrics. Test–retest reliability was assessed using intraclass correlation coefficients (ICCs). Results: VRST performance metrics showed significant correlations with traditional Stroop completion time: task completion time (r = 0.821; p < 0.001), movement distance (r = 0.801; p < 0.001), and hesitation latency (r = 0.784; p < 0.001), indicating good concurrent validity. No significant correlations were observed for error counts. Test–retest analysis showed high reliability for completion time (ICC > 0.9; p < 0.001), movement distance (ICC > 0.9; p < 0.001), and hesitation latency (ICC > 0.9; p < 0.001), but not for error count. These findings suggest that the VRST provides reliable and ecologically grounded behavioral indicators of inhibitory control. Conclusions: This preliminary study supports the VRST as a valid and reliable measure of inhibitory control in healthy older adults. By combining kinematic data with realistic task contexts, the VRST extends executive function assessment beyond traditional methods. Although limited to non-clinical populations, the findings suggest its utility for detecting subtle variations in executive functioning during healthy aging, warranting further investigation across broader cognitive profiles. Full article

Background: Frailty is highly prevalent among older adults with cardiovascular disease (CVD) and strongly predicts disability and mortality after cardiac events. Although cardiac rehabilitation (CR) improves prognosis, frail older patients often face barriers to participating in in-person programs. eHealth-based, home-delivered CR programs incorporating tele-rehabilitation and remote monitoring may improve accessibility, yet evidence regarding their effectiveness on frailty status remains limited. Methods: We designed a multicenter, randomized, parallel-group trial enrolling people ≥65 years recently hospitalized for acute heart failure (AHF) and/or acute coronary syndrome (ACS). Participants were randomized 1:1 to an eHealth home-based tele-rehabilitation program or the usual care. The primary endpoint is frailty prevalence at follow-up, defined by an Essential Frailty Toolset (EFT) score ≥3, with co-primary outcomes being between-group differences in the mean levels of EFT and Short Physical Performance Battery (SPPB) scores after 3–6 months. Secondary endpoints include mortality and hospitalization, among others. Results: The full protocol and study procedures are reported. Between May 2024 and December 2025, 589 patients were screened at the two Italian centers involved; 442 met eligibility criteria and 209 were enrolled and randomized. Baseline characteristics were largely comparable between groups. The mean age was 77 ± 9 years, 70% were male, and 55% had ACS. Lower-than-expected enrollment was mainly attributable to refusal related to difficulties in using digital devices. Conclusions: This randomized trial will evaluate whether a multidomain, eHealth-based CR intervention can reduce the prevalence or degree of frailty in older people after AHF or ACS. We report the study protocol and baseline characteristics of the enrolled cohort, highlighting the challenge of digital illiteracy in contemporary older populations. Full article

Background and objectives: Artificial intelligence (AI)-based adaptive learning has the potential to strengthen clinical decision-making and enhance quality of care at primary health centers. The present study assessed the perceptions, barriers, and learning needs involved in AI-based adaptive learning among primary care physicians in Northern Saudi Arabia. Methods: We used a cross-sectional study design to obtain data from 285 primary care physicians of different cadres working in various primary health centers. A validated data collection tool was used to measure three domains: perceptions, barriers, and learning needs. A multivariable analysis was carried out to identify the factors associated with these three domains. Results: Among the studied participants, low perceptions were observed in 55.1% of physicians; they were higher among those aged >40 years (p = 0.019) and non-Saudi nationals (p = 0.003). High barriers were reported by 42.5% of respondents, and this was higher among those aged >40 years (p = 0.031). Learning needs were higher among non-Saudi nationals (p = 0.017) and those with >10 years of experience (p = 0.007). The perception and learning need scores were positively correlated, and barrier scores were negatively correlated with the other two domains (p < 0.001). Conclusions: The authorities concerned may consider implementing targeted measures for AI-based adaptive learning. Moreover, efforts should be made to reduce the barriers to AI-based adaptive learning at all levels. These measures could strengthen primary care practice and enhance patient care. Full article

Amid the prevailing trend of “pan-entertainment” in cyberspace, adults increasingly interpret children’s lives through utilitarian, adult-centric, and entertainment-focused perspectives, leading to the alienation of children’s online images. This study examines child influencer accounts on Douyin—typically managed by parents—and conducts content and discourse analysis on them. Drawing on critical theories by Douglas Kellner, we employed Scrapy and NVivo to analyze 30 popular children’s videos and 15,000 user comments posted beneath them. The analysis identifies five key characteristics in the construction of such images: spectacular visual mechanisms, younger-age production trends, covert commercial penetration, homogenized spectacle types, and adult-centric implicit influence. The study underscores the urgency of strengthening protective mechanisms to counteract platform capitalism’s intrusion into childhood and to uphold children’s digital privacy and agency. Full article