Search Results (9,252)

This paper summarizes an analysis of the Joint Clinical Assessment (JCA) subgroup’s recommendations for systematic literature reviews (SLRs). While the JCA offers clear guidance on study classification, exclusion criteria reporting, and PRISMA diagram use, several of its recommendations diverge from established best practices in evidence-based medicine (EBM). A comparison with recognized guidelines, such as those from Cochrane and EUnetHTA, reveals that the JCA guidance may lack reliability, comprehensiveness, and reproducibility. Aligning JCA recommendations with gold standards in SLR methodology would address these shortcomings and enhance methodological rigor. Full article

Background/Objectives: Early recurrence after curative-intent resection is a major determinant of poor prognosis in hepatocellular carcinoma (HCC). Artificial intelligence (AI)-driven predictive models have emerged to identify patients at high risk of recurrence but remain incompletely synthesized for early recurrence specifically. This review aimed to identify and appraise AI-driven models predicting early recurrence after surgical resection. Methods: PubMed/MEDLINE, Scopus and Web of Science were searched from inception to November 2025. Eligible studies developed and evaluated AI-driven models predicting early recurrence (≤24 months) after curative-intent hepatectomy as first-line treatment for HCC. Risk of bias and applicability were assessed using PROBAST+AI, and findings were synthesized narratively due to methodological heterogeneity. The review was registered in PROSPERO. Results: Thirty-six studies involving 14,716 patients were included. Most studies originated from China (33/36, 91.7%), were single-center (27/36, 75%), and retrospective (35/36, 97.2%). Magnetic resonance imaging (MRI) was the predominant imaging modality (15/36, 41.7%), followed by computed tomography (CT) (11/36, 30.6%) and ultrasound (US)/contrast-enhanced ultrasound (CEUS) (6/36, 16.7%). Three studies developed non-imaging models, and one combined CT and MRI. In within-study comparisons, multimodal models generally showed better discrimination than unimodal approaches. Peritumoral, habitat-based, and multiphasic strategies appeared promising. However, external validation was reported in only 6/36 studies (16.7%), calibration and decision-curve analysis were inconsistently reported, and most studies had high risk of bias. Conclusions: AI-driven models show potential to predict early recurrence of HCC after curative-intent resection. Nevertheless, evidence remains limited by methodological heterogeneity and restricted geographical diversity, while clinical utility remains inconsistently evaluated, and no model has yet been generalized in clinical practice. Prospective multicenter studies with standardized outcomes, transparent reporting, and external validation are needed for clinical implementation. Full article

Low health literacy is associated with risky alcohol use among young people, particularly those exposed to social and environmental factors that normalize drinking. In digital contexts, innovative and engaging interventions are needed to strengthen alcohol-preventive competencies among hazardous drinkers. This study evaluated the effectiveness of an online health literacy promotion program integrating artificial intelligence (AI) and gamification in improving health literacy and alcohol-preventive behaviors among hazardous-drinking vocational students. A quasi-experimental two-group pre-test–post-test design with a 1-month follow-up was conducted among 114 first-year Higher Vocational Certificate students aged 18–20 years in Bangkok, Thailand. Participants were assigned to an intervention group (n = 57) or a comparison group (n = 57). The intervention group received the ALC Literacy Program, while the comparison group received standard educational materials on alcohol prevention. Data were analyzed using descriptive statistics, chi-square tests, independent t-tests, and two-way mixed-design repeated-measures ANOVA with Bonferroni post hoc comparisons. At baseline, no significant between-group differences were observed. After the intervention and at 1-month follow-up, the intervention group showed significantly greater improvements in both health literacy and alcohol-preventive behaviors than the comparison group (p < 0.001). Large interaction effect sizes were observed for health literacy (partial η² = 0.623) and alcohol-preventive behaviors (partial η² = 0.622). These findings indicate that the ALC Literacy Program was effective in enhancing health literacy and strengthening alcohol-preventive behaviors among hazardous-drinking vocational students. This intervention may represent a potentially useful digital health promotion approach for alcohol prevention in educational settings. Full article

Edge-side acoustic monitoring enables animal sound recognition in remote environments, but microcontroller deployment remains constrained by feature extraction, numerical consistency, memory, latency, and energy consumption. This study presents a sensor-based tiny machine learning (TinyML) acoustic monitoring system on an Arduino Nano 33 BLE Sense Rev2 platform, integrating onboard pulse-density modulation (PDM) microphone acquisition, Mel-frequency cepstral coefficient (MFCC) feature extraction, deployment-side standardization, 8-bit integer (INT8) neural-network inference, and edge-side decision output. To reduce training-to-deployment feature drift, consistent frame parameters, mirrored C++ feature operators, and exported standardization parameters are used to align personal-computer-side and microcontroller-side feature representations. A source-isolated seven-class protocol was constructed for six target animal classes and one compound background-noise class. In the single-run baseline comparison, the proposed multilayer perceptron achieved 98.28% test accuracy and 97.21% test macro-F1, while the ten-seed stability analysis yielded 98.64% ± 0.26% test accuracy and 97.87% ± 0.38% test macro-F1. The deployed INT8 model occupied approximately 26.9 KB, with a post-window latency of about 303 ms. System-level input power was 0.783–0.825 W, corresponding to an estimated autonomy of 7.63–8.03 h under the reference battery setting. Full article

The agricultural and environmental application of Miscanthus × giganteus biomass ash (MBA) as a soil amendment requires a thorough assessment of its properties, nutrient potential, and associated risks. This study characterizes the elemental composition, pH, cation exchange capacity (CEC), and polycyclic aromatic hydrocarbons (PAHs) content of MBA in comparison with other common biomass ashes (crops, wood, and sewage sludge) referred to the international regulatory standards. The ash exhibits a strong alkaline pH (11.03), suggesting potential to improve soil pH in acid soils, but requires careful controlled application to prevent excessive alkalization. The main nutrients detected include K (5.54%), Ca (2.07%), Mg (0.37%), and P (0.86%), indicating its potential as a soil amendment, though long-term use may cause nutrient imbalances. Micronutrients such as Zn (240.67 mg·kg⁻¹), Mn (297 mg·kg⁻¹), and Cu (33.5 mg·kg⁻¹) are found in concentrations suitable for agricultural use, while potentially toxic elements (PTEs), including Cd, Cr, Ni, and Pb, are below detection limits, thereby reducing the risk of pollution. As (8.3 mg·kg⁻¹) and ΣPAHs (1.63 mg·kg⁻¹) remain within safety thresholds, suggesting a low environmental toxicity of MBA. The low Na content (0.12%) indicates a minimal risk of salinity accumulation, distinguishing MBA from high-sodium biomass ashes. Soil alkalization, disruptions in nutrient balance, and element leaching are risks to be considered. Despite these concerns, its composition is in agreement with established safety guidelines, supporting its feasibility for valorization as a sustainable soil amendment and remediation material. To maximize agronomic benefits and mitigate environmental risks, it is important to utilize the ash, considering site conditions and carry out regular monitoring of the soil. Full article

Background/Objectives: Sex estimation is a cornerstone of research and practice in bioarchaeology and forensic anthropology. However, morphological and metric methods are often hampered by population-specific variation, subjectivity in assessment, and taphonomy. This study compares morphological analysis and ancient DNA (aDNA)-based sex assessment in a 19th-century Portuguese sample to evaluate the accuracy of osteological (anthropological) criteria. Methods: This study analysed 37 skeletons from the Venerável Ordem Terceira da Nossa Senhora do Carmo burial grounds in Porto. Sex estimation was based on (1) the bioanthropological assessment of morphological traits of the os coxae and the skull (2) through aDNA analysis using a multi-marker approach, including real-time PCR (qPCR) targeting autosomal loci, the amelogenin locus, a Y-chromosomal INDEL, and Y-STRs. aDNA was extracted via a non-destructive protocol. Results: Whilst anthropological analysis was possible on all 37 individuals, estimation of sex through aDNA analysis was possible for 26 individuals. A 20% discordance rate was found between morphological and aDNA results. Many individuals morphologically classified as “possible female” or “indeterminate” were genetically identified as male. Genetic analysis resolved most cases that biological anthropologists concluded were “indeterminate”. Conclusions: The high discordance in the Carmo sub-sample may indicate reduced skeletal sexual dimorphism, with males exhibiting skeletal traits typically associated with females, suggesting a sample-specific reduction in sexual dimorphism likely influenced by environmental, nutritional, and/or genetic stressors. A limitation of this study is its small sample size: only 26 of 37 individuals yielded usable genetic results, and only a portion of these individuals provided sufficient data for a direct comparison between morphological and genetic data. Nevertheless, these findings highlight the risk that applying generalised osteological standards relying solely on morphology can lead to systematic misclassification, emphasising the need for a critical, multidisciplinary approach to sex estimation. Full article

One of the most commonly diagnosed malignancies in men worldwide, prostate cancer (PCa) is the subject of much study across various treatment approaches and medical specialties. Currently, 5-year survival rates exceed 90%, and research efforts have increasingly shifted towards approaches that improve quality of life, minimizing the likelihood and severity of morbidities associated with treatment. Focal cryoablation is an approach that has been steadily gaining traction in recent years, both for its reduced risk of morbidity and greater potential for salvage therapy, relative to standard treatment. The goal of this work is to discuss the safety and efficacy of focal cryoablation for prostate cancers and define it in context among other treatment approaches. Publications describing approaches to, results from, and the science behind PCa cryoablation were reviewed and collated, describing the current landscape. Additional comparisons were made against analogous approaches, including radiation, surgical resection, hormone therapy, and other ablation modalities. Currently available literature characterizes prostate cryoablation as an effective and well-tolerated approach for treating primary and recurrent PCa, although the data are limited by heterogeneous evidence, lack of standardized endpoints, and an absence of robust randomized comparisons. Cryoablation for prostate cancer continues to evolve, offering a minimally invasive treatment option for both primary and salvage prostate cancer patients, although additional long-term studies are needed. Full article

Purpose: To investigate the agreement on perfusion parameters derived from two different commercially available solutions for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with prostate cancer (PCa). Methods: A total of 50 patients (mean age, 71.6; range 56–86) who had undergone radical prostatectomy between December 2021 and September 2022 were included in this retrospective study. All patients had undergone DCE-MRI on a single 3T-MR scanner. Tumor segmentation on MR images was performed by two radiologists in consensus after radiologic-pathologic correlation using topographic maps as a reference standard. Subsequently, four perfusion parameters were calculated by dedicated commercially available solutions from two different vendors. Both solutions adopted a population-based arterial input function and an extended Tofts model as the pharmacokinetic model. The perfusion parameters were as follows; volume transfer constant (K^trans), rate constant (k_ep), volume fraction of extravascular extracellular space (v_e), and volume fraction of plasma (v_p). The differences between paired measurements were compared by Bland–Altman analyses and the reproducibility was evaluated using the intraclass correlation coefficient (ICC). Results: The study population consisted of Gleason score (GS) 6 (n = 12), GS 7 (n = 34), GS 8 (n = 1), and GS 9 (n = 3). Significant differences were found for all parameters (p < 0.0001). Mean differences were as follows: K^trans, −0.2102 (95% confidence interval; −0.2687 to −0.1518); k_ep, −0.7632 (−0.9005 to −0.6258); v_e, −0.1507 (−0.2422 to −0.05907); v_p, −0.02929 (−0.03383 to −0.02476). ICCs for average measures were as follows: K^trans, 0.2989 (−0.2355 to 0.6021); k_ep, 0.6883 (0.4507 to 0.8231); v_e, −0.1331 (−0.9967 to 0.3570); v_p, 0.2653 (−0.3106 to 0.5881). Conclusion: All perfusion parameters were significantly different between the two solutions. Therefore, comparison of perfusion parameters across different solutions is not recommended. Full article

Background and Objectives: Comparisons of swallowing physiology between coronavirus disease 2019 (COVID-19) pneumonia and clinically diagnosed aspiration pneumonia (AP) have largely relied on ordinal scales, leaving etiology-specific biomechanical profiles unclear. We quantitatively compared videofluoroscopic swallowing study (VFSS) measures of pharyngeal residue and clearance mechanics to identify differential dysphagia phenotypes. Materials and Methods: This single-center retrospective cohort study included 50 adult inpatients with pneumonia (COVID-19, n = 25; AP, n = 25) who underwent VFSS for suspected dysphagia. COVID-19 pneumonia was laboratory-confirmed, and AP was clinically diagnosed after negative tests for severe acute respiratory syndrome coronavirus 2. Blinded ImageJ analysis examined the first standardized semisolid yogurt swallow (International Dysphagia Diet Standardisation Initiative level 4). Primary outcomes were Normalized Residue Ratio Scale values for the valleculae (NRRSv) and piriform sinuses (NRRSp); secondary outcomes were upper esophageal sphincter (UES) opening width and epiglottic rotation angle. Penetration–Aspiration Scale (PAS) score, hyoid displacement, and pharyngeal transit time were exploratory. Results: Baseline characteristics were comparable. COVID-19 pneumonia showed higher NRRSv (0.20 [0.12–0.56] vs. 0.13 [0.00–0.20]; p = 0.01). NRRSp was numerically higher but not statistically significant (0.12 [0.00–0.43] vs. 0.00 [0.00–0.17]; p = 0.07). COVID-19 pneumonia also showed smaller UES opening width (5.08 ± 2.48 vs. 6.50 ± 2.01 mm; p = 0.03) and reduced epiglottic rotation angle (66.0 [29.0–80.8] vs. 93.4 [74.2–100.4] degrees; p = 0.04). No statistically significant between-group difference was detected in PAS-defined airway invasion severity on the standardized semisolid task. Conclusions: These findings suggest an efficiency-predominant dysphagia phenotype in COVID-19 pneumonia, characterized by greater vallecular residue and restrictive clearance-related mechanics on a standardized semisolid task. The results indicate that PAS-defined safety metrics alone may underestimate residue-related dysphagia burden in this population. Full article

Introduction: Fish skin is the first line of defense against the aquatic environment, acting as a physical, chemical, and immunological barrier. In addition to preventing pathogen entry, the skin and its mucus contribute to osmoregulation, innate immunity, and redox balance. Skin lesions—caused by mechanical damage, parasites, environmental stress, or handling—disrupt this barrier, increasing susceptibility to infections, inflammation, and production losses. Thus, efficient skin regeneration is essential for fish welfare and performance. Nutrition plays a key role in this process by providing substrates for epithelial repair, immune function, and antioxidant defense. Among dietary factors, zinc (Zn) is particularly important due to its involvement in cell proliferation, enzymatic activity, and maintenance of skin integrity. Objective: Our objective is to assess the effectiveness of image-based analysis in quantifying the skin healing process in Atlantic salmon fed diets supplemented with zinc. Methodology: The trial comprised three dietary treatments: a control diet with 42 mg Zn per kg (D1), and two diets supplemented up to 120 mg/kg of zinc, derived from inorganic (D2) or organic (D3) forms. Pit-tagged fish with an initial body weight (78 ± 0.1 g) were fed the diets for 75 days. After 15 days of experimental feeding, a standardized wound lesion (2.5 mm diameter × 0.5 mm depth) was inflicted in deeply anesthetized fish, with a disposable biopsy punch, in the dorsal area. After wound infliction, the fish resumed their normal feeding regime for the rest of the trial days. The progression of skin wound healing was assessed using standardized digital image analysis. High-resolution photographs of individual wounds were collected 8, 16, 24 and 32 days post-wounding. All images were acquired under standardized conditions with the inclusion of ArUco identifiers to enable a subsequent computer-assisted comparison. Morphometric parameters (wound width, diameter, perimeter and area) were used to assess wound contraction and closure over time. In parallel, a semi-quantitative visual scoring system was applied to each wound image to capture qualitative aspects of healing that are not fully described by morphometric data alone. Results: Full data analysis is currently underway, but the first results show beneficial effects of dietary zinc supplementation on the skin regenerative process. Conclusions: The combined use of objective digital measurements and standardized visual scoring enabled a comprehensive evaluation of wound healing progress, bridging quantitative tissue remodeling with biologically relevant phenotypic outcomes. This image-based framework provides a sensitive and reproducible approach for assessing dietary interventions targeting skin regeneration and barrier restoration in Atlantic salmon. Full article

Background/Objectives: The “small-n-large-p” dilemma in mammography artificial intelligence (AI)—where the number of candidate imaging features far exceeds the number of labeled cases—commonly results in model overfitting, unstable feature selection, and poor generalization across clinical settings. This study aims to reassess the internal performance of the HiTopology-GOA-CSA (Grasshopper Optimization Algorithm–Crow Search Algorithm) feature-selection framework for mammography using a larger real Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) cohort and a stricter leakage-aware evaluation strategy. Methods: In this retrospective computational study using public anonymized datasets, an expanded internal cohort of 98 CBIS-DDSM mass cases (49 benign, 49 malignant) was assembled from digital imaging and communications in medicine (DICOM) region of interest (ROI) series. A total of 1074 features were extracted per case, including 88 handcrafted radiomic descriptors and 986 EfficientNet-B5 deep features. HiTopology-GOA-CSA selected 102 features, corresponding to 91% feature reduction. Two internal evaluation modes were compared: Mode A, which matched the original pilot methodology by performing feature selection once on the full cohort before cross-validation, and Mode B, which used strict nested feature selection within training folds. Performance was assessed with 5-fold stratified cross-validation using a multilayer perceptron (MLP) classifier. Results: On the expanded cohort, Mode A achieved an area under the receiver operating characteristic curve (AUC) of 0.726 (95% CI: 0.594–0.858), sensitivity of 0.658, specificity of 0.651, and F1-score of 0.644. Under the stricter nested evaluation, Mode B achieved AUC of 0.683 (95% CI: 0.549–0.817), sensitivity of 0.598, specificity of 0.631, and F1-score of 0.595. Mean pairwise Jaccard similarity across nested folds was 0.604, indicating moderate feature stability. Benchmark comparisons showed that the proposed method was competitive but did not outperform standard baselines; LASSO logistic regression achieved the highest AUC of 0.739, while the proposed HiTopology-GOA-CSA + MLP achieved an AUC of 0.683. Real external validation on the locked VinDr-Mammo subset (n = 25) remained near-random (AUC of 0.500 [95% CI: 0.304–0.696]), with complete prediction collapse (sensitivity of 1.000, specificity of 0.000). Conclusions: The framework demonstrated feasibility for structured feature selection and stress testing in a small-cohort mammography AI setting; however, external validation revealed near-random discrimination and prediction collapse, indicating limited generalizability. These findings emphasize the need for benchmark comparisons, transparent uncertainty reporting, patient-level validation, and larger multicenter datasets before clinical translation. Full article

One of the most widely used regression models for count data is the Conway–Maxwell–Poisson regression model (CMPRM), which often provides a better fit for over- and underdispersed count data than traditional models, such as Poisson regression and negative binomial regression. Parameter estimation in the CMPRM is typically performed using the maximum likelihood estimation (MLE) method. However, when explanatory variables are highly correlated, a phenomenon known as multicollinearity arises, posing a significant challenge to the analysis. Multicollinearity makes it difficult to identify the individual effects of explanatory variables, leading to inflated variances and larger standard errors of the MLEs. To address the issue of multicollinearity, this paper introduces a new class of Liu-type estimators within the CMPRM. The proposed estimators aim to improve the estimation accuracy and reliability of the CMPRM compared with existing biased estimation methods. The efficiency of the proposed estimator is evaluated through theoretical comparisons and Monte Carlo simulation experiments conducted under various conditions. Furthermore, two real-data applications are presented to demonstrate the practical usefulness of the proposed estimation method. The results from the theoretical analysis, simulation study, and empirical applications indicate that the proposed estimators outperform existing methods in terms of achieving more accurate and reliable estimates. Full article

Daidzein is a naturally occurring isoflavone phytoestrogen, mainly found in leguminous plants. This component exerts anti-inflammatory effects by regulating inflammatory cells via multiple targets, blocking core inflammatory pathways, and inhibiting the release of inflammatory factors. It also scavenges reactive oxygen species, activates the antioxidant enzyme system, and regulates antioxidant signaling pathways to achieve antioxidant effects. By regulating these two core pathological processes, it exerts protective effects in diseases such as cancer, cardiovascular disease, and acute kidney injury, based on preclinical evidence. The development of nanodelivery systems has effectively improved the physicochemical properties of daidzein, enhanced its bioavailability, and enabled disease-targeted delivery. Most previous reviews have either focused exclusively on daidzein or broadly covered the pharmacological activities of isoflavones, yet have largely overlooked the dual anti-inflammatory and antioxidant mechanisms specific to daidzein. This review summarizes these mechanisms and their preclinical effects on various diseases, including cancer, cardiovascular diseases, and acute kidney injury. It also reviews the pharmacokinetic limitations of daidzein and recent progress in nanodelivery strategies aimed at enhancing its bioavailability and bioactivity. Overall, this review serves as a reference for the future standardized comparison of nanocarriers, targeted therapies, and clinical applications. Full article

Edible insects are increasingly recognized as a viable alternative protein source, offering a potentially sustainable approach to addressing global food security challenges. This narrative review critically examines the nutritional composition, environmental advantages, techno-functional attributes, and potential applications of insect-based proteins within human food systems. Edible insects are characterized by high protein content, favourable essential amino acid profiles, and appreciable levels of key micronutrients, rendering them nutritionally comparable to conventional livestock-derived proteins. Moreover, insect production systems generally require substantially lower inputs of land, water, and feed, resulting in comparatively lower greenhouse gas emissions and reduced overall environmental burden. Despite these advantages, broader adoption remains constrained by challenges related to regulatory heterogeneity, food safety concerns, and limited consumer acceptance. Overall, the available evidence suggests that edible insects can function as a nutritionally adequate and environmentally sustainable complementary protein source; however, significant variability in nutrient composition, limitations in standardized safety assessment, and socio-cultural barriers currently restrict their large-scale integration into mainstream food systems. In addition, inconsistencies in analytical methodologies and reliance on in vitro data further complicate cross-study comparisons and translational relevance. Future research should focus on standardization of rearing and processing conditions, harmonization of evaluation frameworks (e.g., protein quality indices), comprehensive safety assessments, and well-designed clinical studies to validate nutritional and functional benefits, alongside the development of effective strategies to improve consumer acceptance and support regulatory alignment across regions. Full article

Healthcare-associated infections (HAIs) remain a major public health concern, contributing to increased morbidity, mortality, and antimicrobial resistance. Healthcare workers (HCWs) are recognized as key vehicles in the transmission of nosocomial pathogens, primarily via contaminated hands and medical devices. This study assessed the effectiveness of hand hygiene protocols among HCWs, their correlation with bloodstream infections, and the potential of natural antimicrobial agents as complementary preventive measures. Between January and June 2025, 128 hand samples were collected from HCWs in surgical, intensive care, and internal medicine units of hospitals managed by ASL Caserta (Marcianise, n = 65; Piedimonte Matese, n = 30; Sessa Aurunca, n = 18; Maddaloni, n = 15). Sampling was performed upon entry to clinical areas and after antiseptic handwashing, using Rodac TSA plates to quantify microbial load (CFU/cm²). Isolates were identified via MALDI-TOF, and multidrug resistance was confirmed using the Phoenix BD system. Microbial growth was detected in 54.7% of samples. Coagulase-negative staphylococci, mainly Staphylococcus epidermidis and S. hominis, accounted for 67.1% of positive cultures, followed by Enterobacteriaceae (28.6%). Comparison with concurrently collected blood cultures revealed potential overlapping pathogens, with Staphylococcus spp. prevalence ranging from 35 to 56% and Gram-negatives from 18 to 39. Selected isolates were further tested for susceptibility to natural antimicrobial agents, derived from hop, red vine leaf, green tea, and pomegranate fruit, as well as thyme essential oil. Thyme essential oil (Thymus vulgaris) demonstrated notable antimicrobial activity, in several cases surpassing that of standard hygiene agents. These findings highlight not only that maintaining high standards of hand hygiene, proper care of invasive devices, and continuous microbiological surveillance is critical for preventing HAIs, but also that incorporating natural antimicrobial compounds into hygiene protocols may provide an effective and sustainable adjunct to reduce microbial contamination and combat infections caused by multidrug-resistant organisms. Full article