Search Results (5,999)

Background/Objectives: Sex differences in metabolic dysfunction-associated steatotic liver disease (MASLD) have been established in adult males; however, data on paediatric populations remain scarce. This study aimed to elucidate the sex-specific correlations of serum uric acid (SUA), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels with MASLD in children with obesity. Methods: Clinical data from 262 children with obesity were retrospectively analysed. Participants were categorised by sex and MASLD status (MASLD+ vs. MASLD-). Laboratory tests, including ALT, AST, SUA, fasting glucose, glycated haemoglobin, lipid profile, and insulin levels, were compared. Comparison of significant influencing factors of obesity in children with non-alcoholic fatty liver disease was conducted using multivariable logistic regression analysis by sex. Results: Hyperinsulinemia was significantly associated with MASLD in all children. Sex-based analyses revealed differentiated patterns. In males, elevated SUA (p = 0.008) and ALT (p < 0.05) were independently associated with MASLD; however, in females, only elevated AST (p = 0.003) was significantly associated. Conclusions: While insulin resistance is a common risk factor for MASLD in all children with obesity, this study suggests that its manifestation may differ by sex. Elevated SUA and ALT levels may serve as sex-specific indicators in males, while elevated AST levels appear more relevant in females. These findings support the potential value of sex-specific metabolic markers in early MASLD screening, although further validation is needed. Full article

Flash floods arise from the interaction of rugged topography, short-duration intense rainfall, and rapid flow concentration. Conventional risk mapping often builds empirical indices with expert-assigned weights or trains supervised models on historical event inventories—approaches that degrade in data-scarce regions. We propose a fully data-driven, unsupervised Geographic Information System (GIS) framework based on fractional order k-means, which clusters multi-dimensional geospatial features without labeled flood records. Five raster layers—elevation, slope, aspect, 24 h maximum rainfall, and distance to the nearest stream—are normalized into a feature vector for each 30 m × 30 m grid cell. In a province-scale case study of Zhejiang, China, the resulting risk map aligns strongly with the observations: 95% of 1643 documented flash flood sites over the past 60 years fall within the combined high- and medium-risk zones, and 65% lie inside the high-risk class. These outcomes indicate that the fractional order distance metric captures physically realistic hazard gradients while remaining label-free. Because the workflow uses commonly available GIS inputs and open-source tooling, it is computationally efficient, reproducible, and readily transferable to other mountainous, data-poor settings. Beyond reducing subjective weighting inherent in index methods and the data demands of supervised learning, the framework offers a pragmatic baseline for regional planning and early-stage screening. Full article

Background/Objectives: Maternal depression, anxiety, perceived stress, and resilience are recognized determinants of perinatal health, yet routine psychological screening is still uncommon in Romanian obstetric practice. This study examined how these four psychological factors relate to preterm birth, gestational hypertension, intra-uterine growth restriction (IUGR), and low birth weight in primiparous women. Methods: In a cross-sectional study at a tertiary maternity center in Timișoara (February 2024–February 2025), 240 women at 20–28 weeks’ gestation completed the Edinburgh Postnatal Depression Scale (EPDS), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale-10 (PSS-10), and Connor–Davidson Resilience Scale-25 (CD-RISC-25). Obstetric outcomes were abstracted from medical records. Pearson correlations described bivariate associations; multivariate logistic regression assessed independent effects after mutual adjustment. Results: Preterm birth occurred in 21% of pregnancies, gestational hypertension in 17%, IUGR in 15%, and low birth weight in 21%. Higher EPDS, GAD-7, and PSS-10 scores correlated positively with each complication (r = 0.19–0.36; p < 0.02), whereas CD-RISC-25 scores showed inverse correlations (r = −0.22 to −0.29; p ≤ 0.012). In the fully adjusted model, GAD-7 remained the only independent psychological predictor of the composite obstetric outcome (β = 0.047; 95% CI 0.010–0.083; p = 0.013). Perceived stress approached significance; depression and resilience were no longer significant after adjustment. Conclusions: Generalized anxiety was the most robust psychological determinant of adverse obstetric outcomes, with perceived stress, depression, and lower resilience showing contributory roles at the unadjusted level. Incorporating brief instruments such as the GAD-7, PSS-10, and CD-RISC-25 into routine prenatal care could facilitate early identification of at-risk pregnancies and inform targeted preventive interventions. Full article

Background/Objectives: Pulmonary embolism (PE) is a life-threatening condition that frequently results in persistent exertional dyspnea, reduced exercise tolerance, and psychological distress, even after acute-phase management. Despite growing recognition of post-PE impairments, structured early rehabilitation remains underutilized. This narrative review aims to evaluate current evidence on the role, components, and outcomes of early rehabilitation strategies following acute PE. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, a comprehensive literature search was conducted across PubMed, Embase, Scopus, Web of Science, Google Scholar, and the Cochrane Library. Articles published between 2020 and 2025 were screened for relevance to early rehabilitation in PE patients. Inclusion criteria prioritized randomized controlled trials, prospective studies, meta-analyses, and systematic reviews. Study quality was assessed using Cochrane, Newcastle–Ottawa, and AMSTAR 2 tools. Results: Out of 306 records, 158 studies were included. Early pulmonary rehabilitation—including aerobic and resistance exercise, inspiratory muscle training, and psychological support—demonstrated improvements in functional capacity, dyspnea, and quality of life, without adverse effects. Supplementation with omega-3 fatty acids and vitamin D may further mitigate thromboembolic risk via anti-inflammatory pathways. However, evidence remains predominantly observational, with limited high-quality data addressing timing, dosage, and patient stratification. Conclusions: Early, individualized rehabilitation appears safe and potentially beneficial in improving recovery and limiting complications after acute PE. Nonetheless, the absence of robust randomized trials underscores the urgent need for hypothesis-driven research to establish standardized, evidence-based rehabilitation protocols and guidelines tailored to risk stratification and patient phenotype, so as not to prolong recovery time and keep survivors from becoming disabled. Full article

Background/Objectives: Delayed cerebral ischemia (DCI) after an aneurysmal subarachnoid hemorrhage (aSAH) often presents with bilateral vasospasm and cortical spreading depolarizations. Computer tomography perfusion (CTP) is the prevailing screening method for detecting early changes in the cerebral blood flow. Commonly used CTP thresholds include an rCBF < 30% for the core volume and a Tmax > 6 s for hypoperfused tissue detection in acute ischemic stroke. These stroke algorithm computing thresholds compared to the contralateral hemisphere may or may not apply to detect tissue at risk of DCI. We aimed to quantify the volumetric agreement of three different stroke algorithms compared to the final infarct volumes as the standard. Methods: Furthermore, 123 CTP datasets of 75 patients with aSAH suspicious of DCI were processed using Intellispace Portal (ISP), Cercare Threshold, and Cercare Artificial Intelligence (AI) to calculate the tissue-at-risk (hypoperfused) and non-viable tissue (core) volumes. CT infarct volumes in plain CTs were segmented in the follow-up study by using a 3D slicer. Results: The calculated core volumes corresponded best to the final infarct volumes if DCI-related treatment was performed subsequently. Additional postprocessing improved the calculation of core volumes but overestimated the tissue at risk of hypoperfusion in DCI. Whereas the accuracy of tissue-at-risk prediction accelerated without treatment, underlining the importance of intra-arterial spasmolysis and induced hypertension in the prevention of DCI. Conclusions: Cercare AI and ISP revealed a sensitivity of 100% each, with a serious low specificity of <5% that was independent of treatment. Overall, the Cercare Threshold, applying the commonly used stroke thresholds, performed the best in predicting tissue at risk of hypoperfusion in DCI. Full article

Background: Radon, a naturally occurring radioactive gas, is increasingly recognized as a major risk factor for lung cancer (LC), especially among non-smokers. The objective of this study was to identify serum biomarkers for the early detection of LC in individuals at high risk due to prolonged residential radon exposure in Chiang Mai, Thailand, and to assess whether the use of single or combined biomarkers improves the sensitivity and specificity of detection. Methods: A total of 15 LC patients and 30 healthy controls (HC) were enrolled. The HC group was further stratified into two subgroups: low radon (LR, n = 15) and high radon (HR, n = 15) exposure. All participants were non-smokers or former smokers. Serum levels of cytokeratin 19 fragment (CYFRA 21-1), carcinoembryonic antigen (CEA), interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor-alpha (TGF-alpha), and indoleamine 2,3-dioxygenase-1 (IDO-1) were measured using the Milliplex^® Kit on a Luminex^® Multiplexing Instrument (MAGPIX^® System). Results: Serum CEA, IL-6 and IL-8 levels were significantly higher in LC patients compared to the HC group (p < 0.05). Among analyzed biomarkers, only IL-8 was significantly elevated in LC patients compared to the HR group (p = 0.04). Notably, CYFRA 21-1 was the only biomarker that significantly differed between LR and HR groups (p = 0.004). The diagnostic potential of these biomarkers was evaluated using receiver operating characteristic (ROC) analysis. Individually, IL-6 showed the highest discriminative ability for differentiating LC patients from both HC and HR groups, with high specificity but moderate sensitivity. Combining IL-6 and IL-8 improved specificity and increased the area under the ROC curve (AUC), though it did not enhance sensitivity for distinguishing LC from HC. For distinguishing LC from HR individuals, IL-6 and CYFRA 21-1 exhibited strong diagnostic performance. Their combination significantly improved diagnostic accuracy, yielding the highest AUC, sensitivity, and specificity. In contrast, CEA, IL-8, TGF-alpha, and IDO-1 demonstrated limited diagnostic utility. Conclusions: Based on the available literature, this is the first study to evaluate the combined use of IL-6 and CYFRA 21-1 as potential biomarkers for LC screening in individuals with high residential radon exposure. Our findings highlight their utility, particularly in combination, for improving diagnostic accuracy in this high-risk population. Full article

Background/Objectives: Dementia is a leading cause of cognitive decline, with significant challenges for early detection and timely intervention. The lack of effective, user-centred technologies further limits clinical response, particularly in underserved areas. This study aimed to develop and describe a co-design process for creating a Diagnostic and Statistical Manual of Mental Disorders (DSM-5)-compliant, AI-powered Smart Assistant (SmartApp) to monitor neurocognitive decline, while ensuring accessibility, clinical relevance, and responsible AI integration. Methods: A co-design framework was applied using a novel combination of Agile principles and the Double Diamond Model (DDM). More than twenty iterative Scrum sprints were conducted, involving key stakeholders such as clinicians (psychiatrist, psychologist, physician), designers, students, and academic researchers. Prototype testing and design workshops were organised to gather structured feedback. Feedback was systematically incorporated into subsequent iterations to refine functionality, usability, and clinical applicability. Results: The iterative process resulted in a SmartApp that integrates a DSM-5-based screening tool with 24 items across key cognitive domains. Key features include longitudinal tracking of cognitive performance, comparative visual graphs, predictive analytics using a regression-based machine learning module, and adaptive user interfaces. Workshop participants reported high satisfaction with features such as simplified navigation, notification reminders, and clinician-focused reporting modules. Conclusions: The findings suggest that combining co-design methods with Agile/DDM frameworks provides an effective pathway for developing AI-powered clinical tools as per responsible AI standards. The SmartApp offers a clinically relevant, user-friendly platform for dementia screening and monitoring, with potential to support vulnerable populations through scalable, responsible digital health solutions. Full article

Background/Objectives: Temperament is an innate personality trait, influenced by genetic, biological, and environmental factors. Hearing loss, particularly during the critical period of auditory development, can influence cognitive and temperamental development. This study aims to assess the impact of hearing loss on temperamental development in infants aged between 1 and 12 months. Methods: A cross-sectional study of a sample of 132 pediatric patients from the infant hearing screening program was conducted from June 2023 to June 2024. The infants were divided into two groups based on hearing status and the presence of risk factors; cognitive and temperamental parameters were assessed using the QUIT questionnaire. Results: No significant differences were found between infants with and without hearing loss when also considering the infants without risk factors. Normal temperament was found in infants with and without hearing loss, considering both risk and non-risk factors. Finally, no relationship between hearing loss degree and temperament type, considering both the absence and presence of risk factors, was observed. Conclusions: In the early months of an infant’s life, hearing loss does not appear to significantly affect temperamental development. Only through the monitoring of these hearing-impaired infants to detect more severe hearing loss and/or in the presence of other risk factors can deviant development be hypothesized. In this regard, multidisciplinary evaluations may be crucial for the early detection and correction of dysfunctional behaviors. Full article

Background: Chronic kidney disease (CKD) is a progressive global health burden often diagnosed in late stages due to reliance on invasive and centralized blood and urine tests. Saliva, as a non-invasive diagnostic fluid, has emerged as a promising alternative for assessing renal function. This scoping review aims to evaluate the diagnostic accuracy of salivary biomarkers compared to traditional methods, and to explore the potential of emerging biosensing technologies for CKD detection and monitoring. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, and Cochrane Library up to 1 July 2025, following the PRISMA-ScR guidelines. Studies involving adult CKD patients and healthy controls that assessed the diagnostic performance of salivary biomarkers against validated reference standards (e.g., serum creatinine, eGFR) were included. A total of 29 eligible studies were selected after applying predefined inclusion and exclusion criteria. Results: Salivary creatinine and urea were the most frequently assessed biomarkers and demonstrated strong correlations with serum levels (AUCs up to 1.00; sensitivity and specificity frequently >85%). Several studies reported high diagnostic potential for novel salivary markers such as Trimethylamine N-oxide (TMAO), cystatin C, and amino acids. Technological innovations, including electrochemical biosensors and ATR-FTIR spectroscopy, showed promise for enhancing sensitivity and enabling point-of-care testing. However, heterogeneity in sampling protocols and limited data for early-stage CKD were notable limitations. Conclusions: Salivary diagnostics, supported by biosensor technologies, offer a feasible and non-invasive alternative for CKD screening and monitoring. Standardization, broader clinical validation, and integration into dental workflows are key to clinical implementation. Full article

Risdiplam is an orally administered small molecule that modifies the mRNA splicing of SMN2 for the treatment of spinal muscular atrophy (SMA). Its use is approved in presymptomatic patients diagnosed by neonatal screening with early and severe forms with two copies of SMN2, but we do not have real data on the evolution of oral treatment in this early phenotype of SMA. We present two cases treated at one month of life with a follow-up of 12 months and discuss their different evolutions and the causes of this. Familial adherence to treatment is important, as discontinuation can convert an early form of presymptomatic SMA to symptomatic. Molecular biomarkers such as plasma monitoring of neurofilament light chain (pNf-L) should be considered in the follow-up of early forms of SMA and may support the decision to change treatment in infants with SMA. Full article

Background/Objectives: Ovarian cancer (OC) is frequently diagnosed at an advanced stage due to the nonspecific nature of its symptoms. While population-wide screening has failed to reduce mortality, timely diagnosis in symptomatic women remains a promising and underutilized strategy to improve clinical outcomes. The aim of this study was to develop a sensitive, scalable biomarker assay to improve early-stage detection in symptomatic women. Methods: A multi-omic diagnostic model was developed using serum samples from symptomatic women. Lipidomic profiles were generated by liquid chromatography–mass spectrometry (LC-MS), and protein levels were measured using immunoassays. Statistical and machine learning approaches were applied to assess diagnostic performance across disease stages and subtypes. Results: The multi-omic model demonstrated robust performance across a clinically challenging population, with both lipid and protein data necessary for detecting OC across a range of stages and subtypes. The model achieved 98.7% sensitivity in early-stage OC and 98.6% across a range of OC subtypes and stages at 70% fixed specificity, which represented significant improvements over CA125 in the same cohort. In addition, in a small subset of samples, lipid and protein profiles from OC patients undergoing treatment differed from untreated patients and controls, suggesting that this approach may also be useful in other aspects of clinical management, such as treatment monitoring. Conclusions: This multi-omic assay offers a promising solution to accelerate diagnosis, improve early detection, and potentially reduce OC mortality. Full article

Background/Objectives: Hydroxychloroquine (HCQ) retinopathy can be underrecognized early, as structural changes in OCT may precede symptoms and are often subtle. Early detection is crucial to prevent irreversible damage. This study evaluated longitudinal OCT changes preceding overt HCQ toxicity using ellipsoid zone (EZ) mapping. Methods: Patients on long-term HCQ underwent two macular cube scans at least one year apart using Cirrus HD-OCT. Scans were analyzed with an EZ-mapping platform and manually validated. Patients with baseline OCT signs of toxicity or co-existing macular disease were excluded based on masked expert review. Results: Three hundred and seventy-three eyes of 373 patients were included. The mean age was 57.0 ± 12.6 years, the mean HCQ dose was 379.4 ± 59.4 mg, the treatment duration was 5.6 ± 3.7 years, and the OCT interval was 3.1 ± 0.9 years. Outer retinal metrics remained stable across the cohort. The mean en face EZ attenuation increased from 3.3% to 3.9% (p = 0.24). Thirty-four eyes (9.1%) experienced an absolute increase of ≥4% (~1.5 mm²) in EZ attenuation. This increase was significantly associated with age at HCQ initiation (p < 0.001), age at the time of the first and second OCT (p < 0.001), and baseline visual acuity (p = 0.01), and demonstrated changes in other outer retinal metrics (p < 0.01). Only 3/34 eyes (8.9%) were diagnosed by the managing clinician with HCQ toxicity at the time of the second OCT. However, 26 of these eyes (76.5%) had signs of HCQ toxicity by expert review, suggesting the overall greater sensitivity of these quantitative outer retinal metrics for detecting toxicity compared with clinician review. Conclusions: Longitudinal OCT assessment revealed overall stability in outer retinal metrics in eyes on HCQ, but a subset showed increased EZ attenuation, which correlated with age at the time of HCQ initiation, baseline visual acuity, and expert OCT review. These changes may help identify at-risk eyes and eyes with early toxicity and warrant further validation as potential screening biomarkers. Full article

Amphibian populations have experienced a severe decline over the past 40 years, driven primarily by environmental pollution, habitat destruction, climate change, and disease. This work reports, for the first time, saprolegniosis in Pelophylax perezi egg masses and saprolegniosis in amphibians in Portugal. After isolation and phylogenetic analysis, the pathogen was identified as Saprolegnia australis. Following this, the present work intended to screen a collection of P. perezi skin bacteria for the existence of bacterial strains with inhibitory action against the newly identified S. australis SC1 and two other species, Saprolegnia diclina SAP 1010 UE and Saprolegnia australis SAP 1581 UE. The results showed that various bacterial species could inhibit the growth of these three species of oomycetes. Bacteria with the most significant antagonistic action against Saprolegnia spp. predominantly belonged to the genus Bacillus, followed by Serratia, Pseudomonas, and Aeromonas. Despite variations in bacterial diversity among frog populations, the present study also demonstrated the presence of bacteria on frogs’ skin that were capable of inhibiting Saprolegnia spp., as evidenced by in vitro challenge assays. These findings highlight the protective function of bacteria present in amphibian skin. The observed bacterial diversity may contribute to the metabolic redundancy of the frog skin microbiome, helping to maintain its functional capacity despite shifts in the community composition. Additionally, the study found that, when providing a more advantageous environment for pathogen growth—in this case a peptone–glucose (PG) medium instead of R2A—the percentage of bacteria with moderate-to-strong antagonistic activity dropped by 13% to 4%. In conclusion, the presence of bacteria capable of inhibiting Saprolegnia spp. in adult individuals and across different environmental conditions may contribute to lowering the susceptibility of frog adults towards Saprolegnia spp., compared with that in the early stages of development, like the tadpole or egg stages. Full article

Objectives: This study aimed to identify differences in risk factors for carbapenem-resistant Enterobacteriaceae (CRE) infections across different anatomical sites and to explore risk factors associated with mortality in CRE-infected patients. Methods: Patients who underwent CRE screening and were subsequently diagnosed with CRE infections were included and categorized by infection site: respiratory tract (RTI), urinary tract (UTI), and bloodstream (BSI). Forty ICU patients without CRE infection were randomly selected as controls. Statistical comparisons were performed using the Mann–Whitney U or Chi-square test, as appropriate. Potential risk factors were evaluated via univariate and multivariate analyses, and a predictive model was constructed, with its performance assessed using ROC curve analysis. Results: CRE colonization was identified as a common independent risk factor across all three groups (RTI, UTI, and BSI). Infection-site-specific analyses revealed independent risk factors: RTI was associated with mechanical ventilation, UTI with trauma, and BSI with gastrointestinal injury. Predictive models for RTI, UTI, and BSI demonstrated good discrimination, with ROC AUCs of 0.94, 0.94, and 0.95, respectively. In the analysis of Survived versus Deceased patients, the BSI group had the highest mortality, though the difference was not statistically significant. Deceased patients exhibited significantly higher PCT levels than Survived patients (p = 0.005). Prior use of carbapenems and antifungal agents, as well as Ln(PCT), were independently associated with mortality in CRE-infected patients. Conclusions: Risk factors for CRE infections vary across anatomical sites, with CRE colonization, mechanical ventilation, trauma, and gastrointestinal injury playing key roles. Overuse of antibiotics and elevated inflammatory responses are associated with increased mortality. These findings provide evidence for early identification of high-risk patients and optimization of individualized treatment strategies. Full article

Background: Tumor-educated platelets (TEPs) represent a promising biosource for non-invasive multi-cancer early detection (MCED). While machine learning (ML) has been applied to TEP data, the integration of explainability to reveal gene-level contributions and regulatory associations remains underutilized. This study aims to develop an interpretable ML framework for cancer detection using platelet RNA-sequencing data, combining predictive performance with biological insight. Methods: This study analyzed 2018 TEP RNA samples from 18 tumor types using seven machine learning classifiers. SHAP (Shapley Additive Explanations) was applied for model interpretability, including global feature ranking, local explanation, and gene-level dependence patterns. A weighted SHAP consensus was built by combining model-specific contributions scaled by Area Under the Receiver Operating Characteristic Curve (AUC). Regulatory insights were supported through network analysis using GeneMANIA. Results: Neural models, including shallow Neural Network (NN) and Deep Neural Network (DNN) achieved the best performance (AUC ~0.93), with Extreme Gradient Boosting (XGB) and Support Vector Machine (SVM) also performing well. Early-stage cancers were predicted with high accuracy. SHAP analysis revealed consistent top features (e.g., SLC38A2, DHCR7, IFITM3), while dependence plots uncovered conditional gene interactions involving USF3 (KIAA2018), ARL2, and DSTN. Multi-hop pathway tracing identified NFYC as a shared transcriptional hub across multiple modulators. Conclusions: The integration of interpretable ML with platelet RNA data revealed robust biomarkers and context-dependent regulatory patterns relevant to early cancer detection. The proposed framework supports the potential of TEPs as a non-invasive, information-rich medium for early cancer screening. Full article