Search Results (11,733)

Background/Objectives: In the present study, the Metabolic dysfunction-associated fatty liver disease (MAFLD) and Metabolic dysfunction-associated steatotic liver disease (MASLD) diagnostic criteria were applied to evaluate the relative performance in predicting short-term advanced fibrosis (AF) progression (AFpr) and hepatocellular carcinoma (HCC), as well as an ancillary outcome, i.e., the occurrence of acute cardiovascular events (ACEs) in steatotic liver disease (SLD) patients. Methods: We retrospectively analyzed the data stored in the University Hospital (UH)’s Official Health Documents Digitization Archive of 931 SLD patients, with a follow-up of 3 years. Based on the Body Mass Index (BMI), patients were subdivided into lean “L” (BMI < 25 kg/m²) (n = 134) and not-lean “NL” (n = 797), and, subsequently, into NL-MASLD (n = 206), NL-MASLD/MAFLD (n = 481), NL-MAFLD (n = 110), L-MASLD (n = 39), L-MASLD/MAFLD (n = 68), and L-MAFLD (n = 27). All study outcomes (AFpr, HCC, and ACE) were primarily evaluated in NL-SLD and by conducting a sub-analysis of L-SLD individuals. Results: MASLD and MAFLD criteria similarly estimated [p = 0.076] the overall 3-year risk of AF progression in NL-SLD. In the L-SLD sub-analysis, MAFLD criteria better estimated the overall 3-year risk of AF progression [p = 0.006]. Multivariate competing risk analysis (adjusted for sex, age, diabetes, steatosis, and fibrosis severity) revealed diabetes [adjusted Hazard Ratio (aHR) = 2.113, p = 0.001], high-sensitivity C-reactive protein (aHR = 1.441; p = 0.02), and Homeostatic Model Assessment for Insulin Resistance (aHR = 1.228; p = 0.03) as being associated with AF progression in L-MAFLD. Compared to MAFLD, MASLD diagnostic criteria similarly estimated the 3-year risk of HCC occurrence both in NL [HR = 1.104, C.I. 95%: 0.824–1.593, p = 0.741] and L [HR = 1.260, C.I. 95%: 0.768–2.104, p = 0.701] patients. Finally, no significant differences were reported between the MAFLD or MASLD criteria for ACE risk occurrence in all study groups. Conclusions: The MAFLD criteria better estimate the AF progression risk, limited to L-SLD patients. Full article

Background/Objectives: Heart disease (HD) is recently becoming the foremost cause of death worldwide, underlining the importance of early and correct diagnosis to improve patient outcomes. Although Internet of Things (IoT)-enabled machine learning approaches have demonstrated encouraging outcomes in screening, existing approaches often face challenges such as imbalanced dataset handling, influential feature selection identification, and the ability to adapt to evolving HD data forms. To tackle the aforementioned challenges, we present a sequential hybrid approach, RAVE-HD (ResNet And Vanilla RNN Ensemble for HD), that combines a number of cutting-edge techniques to enhance screening. Methods: Preprocessing phase includes duplicates removal and feature scaling for data consistency. Recursive Feature Elimination is employed to extract the most informative features, while a proximity-weighted random synthetic sampling technique addresses class imbalance to reduce class biases. The proposed RAVE model in RAVE-HD approach sequentially integrates a Residual Network (ResNet) for high-level feature extraction and Vanilla Recurrent Neural Network to capture the non-linearity of the feature relationships present in the HDHI medical dataset. Results: Compared to ResNet and Vanilla RNN baselines, the proposed RAVE model attained superior results: 92.06% accuracy and 97.12% ROC-AUC. Stratified 10-fold cross-validation validated the robustness of RAVE, while Sensitivity-to-Prevalence analysis demonstrated stable recall and predictable precision across varying disease prevalence levels. Additional evaluations, including bootstrap and DeLong analyses, showed statistical significance $(p<0.001)$ of the discriminative gains of RAVE. Minimum Clinically Important Difference (MCID) evaluation confirmed clinically meaningful improvements $(\ge$$3\%)$ over strong baselines. Cross-dataset validation using the CVD dataset verified robust generalization (92.4% accuracy). SHAP analysis provided interpretability to build clinical trust. Conclusions: RAVE-HD shows promise as a reliable, explainable, and scalable solution for large-scale HD screening, consistently performing well across diverse evaluations and datasets. Through statistical validation, the RAVE-HD approach emerges as a practical decision-support tool in HD predictive screening results. Full article

Background/Objectives: Systemic hydrocortisone (HCS) in very low birth weight (VLBW) infants is commonly used to treat early hypotension or prevent bronchopulmonary dysplasia. This study evaluated the associations between postnatal HCS exposure and neurodevelopment in VLBW infants by comparing regional brain volume at term-equivalent age (TEA) with neurodevelopmental outcomes in early infancy. Methods: This retrospective cohort study included VLBW infants admitted to a neonatal intensive care unit (NICU) between 2013 and 2019. The cumulative HCS dose during hospitalization was recorded, and regional brain volumes were analyzed using magnetic resonance imaging at TEA. Neurodevelopmental outcomes were assessed at a corrected age for prematurity of 18–24 months. Results: Among 146 infants, 57 were classified in the high HCS group (>90 mg/kg) and 89 in the low HCS group (≤90 mg/kg HCS). Bronchopulmonary dysplasia, periventricular leukomalacia, and sepsis were more frequent in the high HCS group. Ninety-five infants underwent magnetic resonance imaging, which revealed reduced brain volumes in the high HCS group. At follow-up, cerebral palsy (35.9% vs. 9.1%, p = 0.003), neurodevelopmental impairment (54.0% vs. 23.6%, p = 0.002), and head circumference <10th percentile (64.3% vs. 19.5%, p < 0.001) were more common in the high HCS group. After adjustment, HCS > 90 mg/kg remained independently associated with cerebral palsy (adjusted odds ratio [aOR] 5.44, p = 0.016) and reduced head circumference (aOR 4.45, p = 0.016). Conclusions: High cumulative HC exposure correlated with reduced brain volume at TEA and adverse neurodevelopmental outcomes at 24 months of age. Careful monitoring of dose and treatment duration is essential to balance therapeutic benefits against potential risks. Full article

Background/Objectives: Insulin resistance is a major public health issue in Mexico, closely linked to obesity, prediabetes, and type 2 diabetes. The euglycemic–hyperinsulinemic clamp is the diagnostic gold standard but is impractical for routine use. The triglyceride–glucose (TyG) index has been proposed as a simple alternative validated in diverse populations. We aimed to assess the utility of TyG relative to HOMA-IR and QUICKI as an early diagnostic tool in young Mexican adults. Methods: We performed an analytical cross-sectional study in young adults. Clinical, anthropometric, and fasting biochemical variables were collected to compute TyG. We compared TyG with HOMA-IR and QUICKI and evaluated diagnostic performance using receiver operating characteristic analysis to estimate area under the curve (AUC) and identify the optimal cut-off. Results: We analyzed 115 participants; 66.9% were insulin resistant by HOMA-IR, 79.1% by QUICKI, and 42.6% by TyG. TyG showed significant associations with anthropometric and biochemical measures. Diagnostic performance was good (AUC 0.707 vs. HOMA-IR; 0.960 vs. QUICKI). The optimal cut-off was 4.38, yielding sensitivity of 70.1% and specificity of 68.4% for diagnosing insulin resistance compared with HOMA-IR. Conclusions: The TyG index appears to be a useful, accessible, and cost-effective biomarker for early detection of insulin resistance in young Mexican adults. Its implementation could facilitate earlier diagnosis and prevention of cardiometabolic complications. Longitudinal, multicenter studies are warranted to establish population-specific reference values and to confirm its predictive value for adverse outcomes. Full article

High-quality 3D objects play a crucial role in digital twins, while synthetic data generated from these objects have become essential in deep learning-based computer vision applications. The task of collecting and labeling real defects on industrial object surfaces has many challenges and efforts, while synthetic data generation feasibly replicates huge amounts of labeled data. However, synthetic datasets lack realism in their rendered images. To overcome this issue, this paper introduces a single framework for 3D industrial object reconstruction and synthetic defect generation for digital twin smart factory applications. In detail, NeRF is applied to reconstruct our custom industrial 3D objects through videos collected by a smartphone camera. Several NeRF-based models (i.e., Instant-NGP, Nerfacto, Volinga, and Tensorf) are compared to choose the best outcome for the next step of defect generation on the 3D object surface. To be fairly evaluated, we train four models using the Nerfstudio framework with our three custom datasets of two objects. From the experiment’s results, Instant-NGP and Nerfacto achieve the best outcomes, outperforming all other methods significantly. The exported meshes of 3D objects are refined using Blender before loading into NVIDIA Omniverse Code to generate defects on the surface with the Replicator. To evaluate the object detection performance and to verify the benefits of synthetic defect data, we conducted experiments with YOLO-based models on our synthetic and real-plus-synthetic defects. From the experiment’s results, the synthetic defect data contribute to improving YOLO models’ generalization capability with the highest and lowest accuracy mAP@0.5 enhancement of 18.8 and 1.5 percent on YOLOv6n and YOLOv8s, respectively. Full article

Natural shampoos are increasingly designed to provide multifunctional benefits beyond cleansing, including hair conditioning, scalp protection, and reduced irritation potential. POLEVAN^®, a proprietary levan-based polysaccharide produced enzymatically from sugar, offers a combination of oligo- and polysaccharide fractions with potential cosmetic applications. This study evaluated POLEVAN^® in shampoo formulations for three targeted effects: improving hair glossiness, enhancing scalp moisturization, and boosting foam while enabling reduced surfactant levels. Glossiness was assessed ex vivo using damaged hair tresses. Moisturization was assessed in a randomized clinical trial, comparing the test formulation with hyaluronic acid (HA), employing corneometer readings and Trans Epidermal Water Loss (TEWL) measurements. The study was subject-blinded, and all outcomes were determined solely through quantitative, device-based measurements, minimizing observer bias. Foaming performance was tested using the Shaking Cylinder Method. Shampoos containing 2% POLEVAN^® significantly increased hair glossiness by 24% (p = 0.0375) versus a non-significant increase without POLEVAN^®. Moisturization studies showed no significant difference between POLEVAN^® and HA in maintaining hydration or preventing TEWL over 4 weeks. Foam analysis demonstrated that addition of POLEVAN^® allowed up to 50% reduction in surfactant content without compromising foam generation or stability. These results highlight POLEVAN^® as a multifunctional natural ingredient capable of improving sensory and performance attributes of shampoos while supporting gentler formulations. Full article

Subarachnoid hemorrhage (SAH) is a devastating cerebrovascular disorder with high mortality and long-term disability. It is more prevalent in women than men, but most preclinical research has been performed in male animals. Upregulation of lipocalin-2 (Lcn2), an acute-phase protein involved in iron homeostasis and neuroinflammation, has been implicated in hemorrhagic brain injury in male animals. The purpose of this study was to examine whether genetic deletion of Lcn2 also reduces early brain injury after SAH in female mice. Adult female wild-type (WT) and Lcn2 knockout (KO) mice were subjected to endovascular perforation to induce SAH. Lcn2 expression was assessed by immunohistochemistry and Western blotting, while brain injury was evaluated using MRI T2 lesion measurement, blood–brain barrier (BBB) permeability assays, Fluoro-Jade C staining, and Garcia’s neurological scoring. We found that Lcn2 expression was upregulated in multiple brain regions after SAH, particularly in astrocytes. Compared with WT mice, Lcn2 KO mice exhibited significantly reduced oxidative stress, attenuated ferritin induction, smaller T2 lesions, decreased BBB leakage, reduced neuronal degeneration, and improved neurological recovery over 7 days. These findings identify Lcn2 as a critical mediator of early brain injury after SAH in female mice. These results further support targeting Lcn2 as a therapeutic strategy to reduce brain damage and improve outcomes in SAH patients. Full article

Background: Rotavirus (RV) continues to be the leading cause of acute gastroenteritis (AGE) globally among children under five. National RV vaccination efforts have lowered morbidity and mortality. Vaccination is a key public health tool to alleviate this substantial burden of RV in middle- and low-income countries. In Syria, RV morbidity accounts for 27% of severe GE. We conducted a cost-effectiveness analysis of introducing rotavirus vaccinations (RVV) into Syria’s National Immunization Program. Methods: A decision tree model was developed to assess the cost-saving of two-dose rotavirus vaccinations (Rotarix^®) compared to no vaccination. A birth cohort of 573,944 newborns was simulated throughout a 5-year time frame to capture the near-term health and economic effects. The analysis adopted an incremental cost-saving approach, evaluating a hypothetical 2023 birth cohort from the government’s perspective. Outcomes included the cost per disability-adjusted life year (DALY) prevented and the cost per death averted. Model inputs were derived from local data, specifically including healthcare and vaccination costs and deaths attributable to RVGE, the scientific literature, and national/international databases. The incremental cost-effectiveness ratio (ICER) measures the cost of avoiding one disability-adjusted life year (DALY) adopted. Results: Over five years, the two-dose RV strategy would avert 77,500 RVGE cases, reduce outpatient visits by 59%, and reduce severe RV hospitalizations by 41%. The vaccination program would cost $21,817,918 USD and avert $3,239,907 USD in healthcare costs, resulting in a net cost of $18,578,011 USD. The incremental cost-effectiveness ratio (ICER) was $2098 USD per DALY averted, which is below three times Syria’s GDP per capita ($753.6 USD), indicating high cost-effectiveness according to WHO benchmarks. Conclusions: Introducing rotavirus vaccination is highly cost-saving and will result in a substantial reduction in healthcare burdens and lives lost. Policy planners must ensure its inclusion in the National Immunization Programs, ensuring sustainable financing and equitable access. Full article

Hylocereus species are promising for enhancing fruit productivity in arid regions, but high solar radiation often leads to yield loss. This study aimed to evaluate the short-term impact of different shading levels on the physiological performance, productivity, and post-harvest quality of Hylocereus costaricensis under semi-arid conditions. Plants were grown in the field under two shade levels, i.e., 35 and 50% and their performances were compared to plants under control, i.e., 0% of shade or full sunlight. The nighttime CO₂ assimilation and productivity increased significantly by 310.5 and 114.6% and 34.3 and 50.14% for plants under 35 and 50% of shade, respectively, compared to the control. A Principal Component Analysis (PCA) revealed that shade enhanced skin betalain (BETS) and phenolic content (PETP), whereas non-shaded plants expressed traits more closely associated with plant and fruit photoprotective pigment synthesis, i.e., total carotenoids and yellow flavonoids, respectively, along with total sugar accumulation, underscoring the significant impact of shading on both metabolic activity and overall agronomic outcomes. Shading within the 35% to 50% range is effective to cope with high solar radiation by improving photosynthetic capacity, productivity, and post-harvest quality, especially regarding the accumulation of pigments such as betalains, indicating that shade as an agro-technique is a valuable approach for the cultivation of Hylocereus species in dryland regions. Full article

Background: Exergame applications were introduced recently for orthopedic rehabilitation. This study aimed to evaluate the effectiveness of a 6-week home-based quadriceps exercise with mobile exergaming for treatment of primary knee osteoarthritis (KOA). Methods: A prospective randomized controlled trial was conducted in 56 primary KOA patients. All patients were allocated into two groups (n = 28 each group). Intervention group received the 6-week mobile exergaming program using a smartphone exercise game with a wearable wireless motion sensor. Control group received a standard 6-week exercise program. Outcomes were active knee arc of motion, quadriceps muscle power, visual analog scale score, timed “Up and Go” (TUG) test, and Knee Injury and Osteoarthritis Outcome Score (KOOS) at a 6-week follow-up. Results: At 6-week post-exercise, the intervention group significantly improved quadriceps power, arc of motion, VAS score at rest and on motion, TUG test, and KOOS-symptom domain compared to the control group (p < 0.05 all). No device- or exercise-related complications were found. Conclusions: Mobile exergaming with visual feedback control using a wearable wireless sensor significantly improves KOA outcomes compared to standard home-based exercise as early as 6 weeks post-application. Full article

This study aimed to investigate the regulatory mechanisms underlying the relationship between cardiac structure and function and plasma metabolic characteristics in Yili horses participating in an 80-km endurance, by integrating echocardiography, lipidomics, and energy metabolomics analyses. Twenty four competing Yili horses were selected and divided based on competition outcomes: Pre-Completion Group: PCG (n = 6); Post-Completion Group: PoCG (n = 6); Overtime Completion Group: OCG (n = 6); and Non-Completion Group: NCG (n = 6). Cardiac structural and functional parameters were assessed via echocardiography, and intergroup differences were analyzed using one-way ANOVA with a significance threshold of p < 0.05. Plasma lipids and energy metabolites were quantified using UPLC–MS/MS, applying screening criteria of variable importance in projection (VIP) > 1, p < 0.05, and fold change (FC) > 1.2 or FC < 0.833. Bioinformatics analyses were subsequently conducted to identify intergroup variations and correlations. Specifically, associations between cardiac structure/function and metabolites were examined using Pearson correlation analysis, with screening criteria of p < 0.05 and correlation coefficient > 0.8. The results revealed the following: (1) Regarding cardiac structure and function, the PCG group exhibited significantly superior indices, including End-diastolic left ventricular diameter (LVIDd), End-diastolic left ventricular volume (EDV), stroke volume (SV), and ejection fraction (EF), compared with OCG and NCG, and LVIDd showed a highly significant negative correlation with competition completion time. (2) In metabolomic analyses, few differential metabolites were found among groups before the competition (only 60 between PCG and NCG), whereas 234 differential lipids were detected between PoCG and PCG, mainly enriched in sphingolipid metabolism and fatty acid degradation pathways. Energy metabolites showed distinct exercise-responsive patterns, with 22 differential metabolites between PCG and NCG and 21 between PoCG and PCG, significantly enriched in amino sugar and nucleotide sugar metabolism and TCA pathways. Dynamic changes in key TCA intermediates, such as citrate and succinate, reflected enhanced aerobic oxidative metabolism during endurance exercise. (3) Carnitine C18:1, Carnitine C10:2, FFA (20:3), Cer (t17:2/23:0) and 3-phenyllactic acid were significantly correlated with cardiac indicators such as LVLD and LVFWs (p < 0.05). In summary, performance in the 80-km endurance of Yili horses was primarily influenced by enlarged LVIDd and EDV, as well as the regulation of sphingolipid–fatty acid metabolic pathways. Triglycerides, specific acyl compounds, and ceramides may serve as potential biomarkers for evaluating endurance performance, providing a theoretical basis for scientific training and breeding of endurance horses. Full article

Early and accurate diagnosis of Alzheimer’s disease (AD) is critical for patient outcomes yet presents a significant clinical challenge. This study evaluates the effectiveness of four machine learning models—Logistic Regression, Random Forest, Support Vector Machine, and a Feed-Forward Neural Network—for the five-class classification of AD stages. We systematically compare model performance under two conditions, one including cognitive assessment data and one without, to quantify the diagnostic value of these functional tests. To ensure transparency, we use SHapley Additive exPlanations (SHAPs) to interpret the model predictions. Results show that the inclusion of cognitive data is paramount for accuracy. The RF model performed best, achieving an accuracy of 84.4% with cognitive data included. Without this, performance for all models dropped significantly. SHAP analysis revealed that in the presence of cognitive data, models primarily rely on functional scores like the Clinical Dementia Rating—Sum of Boxes. In their absence, models correctly identify key biological markers, including PET (positron emission tomography) imaging of amyloid burden (FBB, AV45) and hippocampal atrophy, as the next-best predictors. This work underscores the indispensable role of cognitive assessments in AD classification and demonstrates that explainable AI can validate model behavior against clinical knowledge, fostering trust in computational diagnostic tools. Full article

Immune thrombocytopenia (ITP) is an autoimmune disorder often triggered by prior viral infections. Although there is considerable evidence suggesting platelets act as passive bystanders during viral illnesses, they are increasingly recognised as active participants in their interactions with viruses. Our descriptive observational retrospective study, conducted at a tertiary hospital in Romania, aimed to evaluate the impact of viral infections on the incidence and outcomes of ITP. This cohort study focused on newly diagnosed ITP cases over a 10-year period, comparing two patient groups: the first group (I-306 patients) from the viral outbreak period (2020–2024) and the second (II-213 patients) from an epidemic-free period (2015–2019). Despite non-pharmacological measures implemented to prevent respiratory infection spread, the number (p = 0.05) and incidence (p = 0.001) of newly diagnosed ITP cases in hospitalised children increased significantly, mainly associated with severe acute respiratory syndrome coronavirus 2 (r = 0.967, p = 0.007), Epstein–Barr virus (r = 0.974, p = 0.004), and influenza (r = 0.901, p = 0.037), with mild thrombocytopenia (p = 0.028). The severity and persistence or chronicity of ITP remained unchanged. The rise in newly diagnosed ITP cases, even without increased severity or chronic evolution, may impose a substantial burden of medical and non-medical costs, highlighting the need for preventive measures during risky viral infection outbreaks. Full article

Background/Objectives: Allele-specific genome editing using the CRISPR–Cas9 system is crucial for achieving precise therapeutic interventions in dominant inherited diseases that are otherwise difficult to treat with conventional approaches. However, Cas9–guide RNA (gRNA) complexes often tolerate single-base mismatches in target sequences, making it challenging to discriminate between wild-type and mutant alleles differing by only one nucleotide. Although previous studies have attempted to improve specificity by introducing mismatches into gRNAs, none has systematically investigated the impact of different mismatch types and positions on editing outcomes. In this study, we developed an effective strategy to enhance specificity and minimize off-target effects by deliberately introducing mismatches into gRNAs and comprehensively evaluating their editing performance. Results: We established an efficient strategy for the selective editing of mutant alleles that reduces Cas9 sequence tolerance and enhances specificity through the intentional introduction of mismatches into gRNAs. The efficacy of this approach was demonstrated by successful allele-specific editing of cancer-associated heterozygous point mutations in EGFR L858R and KRAS G12V, while minimizing editing of the corresponding wild-type alleles. Conclusion: Compared with perfectly matched gRNAs, the strategic incorporation of mismatches into gRNAs enhanced editing specificity for single-base mutant alleles. Our findings substantially improve the precision and safety of CRISPR-based genome editing for cancer therapy, particularly in cases involving mutant alleles. Full article

Objectives: This study aimed to systematically compare the diagnostic accuracy of magnetic resonance imaging (MRI) and transvaginal ultrasound (TVUS) for deep infiltrating endometriosis (DIE) and to evaluate their impact on surgical decision-making. Methods: We carried out a systematic review of studies (2015–2025) comparing MRI and TVUS for DIE in the same patients, with surgical/histological confirmation used as the reference standard. The primary outcomes were sensitivity and specificity by lesion site; the secondary outcomes included the reported impact on surgical decision-making and treatment planning. Results: Nine studies met the inclusion criteria. For rectosigmoid lesions, the sensitivity was 79–94% for TVUS and 86–94% for MRI, with a high specificity for both (84–95%). TVUS demonstrated strong diagnostic accuracy for posterior compartment disease, but its sensitivity was notably lower for uterosacral ligament and bladder lesions (25–83%). MRI showed higher sensitivity for anterior and multi-compartmental lesions (75–94%), reflecting its superior anatomical coverage. Imaging informed surgical planning, ensuring the inclusion of subspecialists such as colorectal or urological surgeons. It also guided the extent of resection and need for radical versus conservative procedures. Conclusions: TVUS and MRI are complementary imaging modalities in the diagnosis and staging of DIE. TVUS offers high specificity and remains particularly effective for posterior compartment disease, whereas MRI provides broader anatomical coverage and higher sensitivity for anterior and multi-compartmental involvement. Importantly, integrating imaging into preoperative planning improves multidisciplinary coordination, optimises preparedness, and guides resection. This is the first review to systematically compare MRI and TVUS for DIE with an emphasis on lesion-level accuracy and the impact on surgical decision-making. Full article