Search Results (20,154)

Background/Objectives: The glymphatic system is a recently characterized glial-dependent waste clearance pathway in the brain, which makes use of perivascular spaces for cerebrospinal fluid exchange. Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) offers a non-invasive method for estimating perivascular flow, but its biological specificity and susceptibility to methodological variation, particularly head position during MRI acquisition, remain as threats to the validity of this technique. This study aimed to assess the prevalence of current DTI-ALPS practices, evaluate the impact of head orientation on ALPS index calculation, and propose a novel computational approach to improve measurement validity. Methods: We briefly reviewed DTI-ALPS literature to determine the use of head-orientation correction strategies. We then analyzed diffusion MRI data from 172 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to quantify the influence of head orientation on ALPS indices computed using the conventional Unrotated-ALPS, a vecrec-corrected ALPS, and the new LD-ALPS method proposed within. Results: A majority of studies employed Unrotated-ALPS, which does not correct for head orientation. In our sample, Unrotated-ALPS values were significantly associated with absolute head pitch (r₁₆₉ = −0.513, p < 0.001), indicating systematic bias. This relationship was eliminated using either vecreg or LD-ALPS. Additionally, LD-ALPS showed more sensitivity to cognitive status as measured by Mini-Mental State Examination scores. Conclusions: Correcting for head orientation is essential in DTI-ALPS studies. The LD-ALPS method, while computationally more demanding, improves the reliability and sensitivity of perivascular fluid estimates, supporting its use in future research on aging and neurodegeneration. Full article

Wave-powered desalination systems integrate reverse osmosis (RO) with renewable ocean energy, providing a sustainable and environmentally responsible approach to freshwater production. This study aims to investigate wave-powered RO desalination using supervised and deep machine learning (ML) models to predict the effects of variable feed flow on permeate recovery and salt rejection under dynamic hydrodynamic conditions. Multiple ML models, including Gaussian process regression (GPR), support vector machines (SVMs), multi-layer perceptron (MLP), linear regression (LR), and decision trees (DTs) were systematically assessed for the prediction of permeate recovery and salt rejection (%) using three distinct input configurations: limited physicochemical features (M1), flow- and salinity-related parameters (M2), and a comprehensive variable set incorporating temperature (M3). GPR achieved near-perfect predictive accuracy R² values (~1.00) with minimal errors for permeate recovery and salt rejection, attributed to its flexible kernel and probabilistic design. MLP and SVM also performed well, though they showed greater sensitivity to feature complexity. In contrast, DT models exhibited limited generalization and higher error rates, particularly when key features were excluded. Sensitivity analyses revealed that feed pressure (FP) and brine salinity (BS) were dominant positive influencers of permeate recovery and salt rejection. In contrast, brine flow (BF) and permeate salinity (PS) had negative impacts. Full article

Background and Objectives: Circadian fluctuations in blood pressure, particularly the non-dipping pattern characterized by the absence of a nocturnal decline, are associated with an increased risk of microvascular complications. The retina, as a highly sensitive microvascular tissue, offers a valuable window into systemic hemodynamic alterations. However, the literature lacks detailed structural analyses that evaluate all retinal regions by segmenting nighttime into specific time intervals. Notably, the early morning period (04:00–08:00), during which stress hormones such as cortisol and catecholamines rise physiologically, leads to increased blood pressure that may significantly affect retinal microcirculation. This prospective study aims to assess retinal microvascular structures in dipper and non-dipper individuals using structural optical coherence tomography and to investigate their relationship with blood pressure parameters by dividing nighttime into distinct time segments. Materials and Methods: A total of 60 participants were classified as dipper (n = 26) or non-dipper (n = 34) based on 24 h ambulatory blood pressure monitoring results. Structural optical coherence tomography was used to evaluate superficial and deep capillary plexus densities in the foveal, parafoveal, and perifoveal regions, along with the area and perimeter of the foveal avascular zone (FAZ) and flow density (FD). Blood pressure values, including systolic, diastolic, mean arterial, and pulse pressure, were recorded during two nighttime intervals (00:00–04:00 and 04:00–08:00), and correlations with retinal parameters were analyzed. Results: No significant differences were observed in retinal microvascular parameters between the dipper and non-dipper groups. Deep capillary densities, particularly in the parafoveal and perifoveal regions, showed significant positive correlations with serum total protein, albumin, and very low-density lipoprotein (VLDL) levels. Furthermore, systolic and mean arterial pressures measured during the 04:00–08:00 interval demonstrated significant positive correlations with deep retinal vascular densities. The FAZ perimeter was negatively correlated with pulse pressure variability, while FD showed a negative correlation with mean arterial pressure variability. Conclusions: This prospective study is among the first to investigate the effects of circadian blood pressure patterns on retinal microvascular structures by segmenting nighttime into specific intervals and employing comprehensive structural optical coherence tomography across the entire retina. The findings suggest that retinal microvascular structure may be associated with fluctuations in blood pressure. Analyses of blood pressure measurements between 04:00 and 08:00 may offer supplementary insights into the evaluation of retinal microvascular structure. Full article

Knowledge graphs (KGs) represent a promising approach for detecting and correcting errors in automated audio and video transcripts. Yet the lack of accessible tools leaves human reviewers with limited support, as KG construction from media data often depends on advanced programming or natural language processing expertise. We present the Custom LLM Automated Relationship Extractor (CLARE), a system that lowers this barrier by combining context-aware relation extraction with an interface for transcript correction and KG refinement. Users import time-synchronized media, correct transcripts through linked playback, and generate an editable, searchable KG from the revised text. CLARE supports over 150 large language models (LLMs) and embedding models, including local options suitable for privacy-sensitive data. We evaluated CLARE on the Measure of Information in Nodes and Edges (MINE) benchmark, which pairs articles with ground-truth facts. With minimal parameter tuning, CLARE achieved 82.1% mean fact accuracy, exceeding Knowledge Graph Generation (KGGen, 64.8%) and Graph Retrieval-Augmented Generation (GraphRAG, 48.3%). We further assessed interactive refinement by revisiting the twenty-five lowest-scoring graphs for fifteen minutes each and found that the fact accuracy rose by an average of 22.7%. These findings show that CLARE both outperforms prior methods and enables efficient user-driven improvements. By streamlining ingestion, correction, and filtering, CLARE makes KG construction more accessible for researchers working with unstructured data. Full article

Obstructive coronary artery disease (CAD) is common in patients undergoing transcatheter aortic valve implantation (TAVI). While invasive coronary angiography (ICA) is the gold standard for coronary evaluation, coronary computed tomography angiography (cCTA) is gaining interest for its potential to exclude obstructive CAD during pre-procedural imaging. This study aimed to assess the diagnostic accuracy of cCTA in ruling out significant CAD in TAVI candidates. We retrospectively analyzed 95 TAVI candidates (mean age 77.7 ± 8.5 years) who underwent both cCTA and ICA. Diagnostic performance of cCTA—sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy—was assessed using ICA as the reference, in both patient- and vessel-based models. Obstructive CAD was defined as ≥50% luminal stenosis or occlusion of a stent/bypass graft. ICA detected obstructive CAD in 27 patients (28.4%). Excluding non-evaluable cases, cCTA showed a negative predictive value (NPV) of 97% (patient-level) and 95% (vessel-level), with a diagnostic accuracy of 85% and 87%, respectively. Including all patients, regardless of scan quality, the NPV remained high (97%), although overall accuracy dropped to 67% (patient-level) and 66% (vessel-level). cCTA demonstrated high accuracy in excluding significant CAD, with a stable NPV of 95–97%. The relatively high rate of non-diagnostic scans and the single-center, retrospective design suggest that its role should be considered complementary to ICA, potentially reducing—but not replacing—the need for ICA in selected TAVI candidates. Full article

Background/Objectives: Testicular germ cell tumours (GCT) have high cure rates, especially in early stages. MicroRNA-371a-3p (M371) has recently emerged as a highly sensitive biomarker for malignant GCTs, except teratoma. This study aimed to evaluate the diagnostic performance of M371-test in a real-life clinical setting, compared to conventional markers alpha-fetoprotein (AFP), lactate-dehydrogenase (LDH), and beta-human chorionic gonadotropin (β-HCG) in patients with suspected GCT. Methods: The study, approved by the Ethic-Committee of the Provincial Hospital of Bolzano (N.97-2021), included 91 M371-tests, performed from March 2021 to May 2025. A total of 75 patients had suspected GCT; 19 healthy males served as control. Serum levels of M371, AFP, LDH, and β-HCG were compared with final histopathological diagnosis. M371 was also assessed in controls to evaluate test performance. Secondary analyses investigated correlations between preoperative M371 levels and tumour size in non-metastatic patients, and between M371-levels and clinical stage in the entire GCT cohort. A cut-off of RQ > 5 (relative quantification) was used to calculate sensitivity, specificity, and predictive values. Results: M371 showed a sensitivity of 90.9% and specificity of 89.3%, outperforming in terms of sensitivity AFP (20.4%/96.4%), LDH (40.9%/96.4%), and β-HCG (43.1%/100%). Positive predictive value (PPV) and negative predictive value (NPV) were 93.0% and 86.2%, respectively. Sensitivity was 95% for non-seminomas and 87.5% for seminomas. In non-metastatic patients, M371 levels correlated with tumour size and were significantly higher in advanced stages (median RQ 1128.35 vs. 98.36; p = 0.015). Conclusions: M371 showed excellent diagnostic performance, even for small tumours, supporting its clinical use. Further studies are needed to define its role in treatment planning and follow-up. Full article

Sensitization to inhalant allergens is a major factor in the development of allergic diseases. Despite this, few studies have comprehensively analyzed age- and sex-specific patterns within defined populations. This study aimed to investigate the prevalence and distribution of sensitization to inhalant allergens in different demographic groups of the Lithuanian population using molecular diagnostics. We retrospectively reviewed molecular allergy profiles of 658 patients tested with the ALEX2 macroarray between 2020 and 2022. Sensitization to inhalant allergen components was assessed and compared across three age groups (<18, 18–44, >44 years) and by sex. Sensitization to at least one inhalant allergen was observed in 62.16% of patients. Rates were significantly higher in males compared to females, particularly in the reproductive-age group (p = 0.0167). Children exhibited the highest prevalence, which declined with age. Tree pollen, pet dander, grass pollen, and dust mites were the dominant allergen groups. Boys were more often sensitized than men, and girls more often than women. Male patients showed higher sensitization to most allergens, except dust mites and weeds in certain female subgroups. Distinct age- and sex-related differences in sensitization patterns were identified. These results emphasize the importance of demographic factors in allergy diagnostics and highlight the need for region-specific sensitization data to inform clinical care and public health strategies. Full article

Ceratitis capitata (Wiedemann) or medfly is a polyphagous pest of fruit crops worldwide. The Asian-native larval parasitoid Diachasmimorpha longicaudata (Ashmead) is mass-reared at the San Juan Biofactory and is currently released for medfly control in Argentina. Information on parasitoid survival, reproduction, and population growth parameters is critical for optimizing the mass-rearing process and successfully achieving large-scale release. This study provides a first-time insight into the demography of two population lines of D. longicaudata: one mass-reared on medfly larvae of the Vienna-8 temperature-sensitive lethal genetic sexing strain and the other on larvae of the wild biparental medfly strain. The aim was to compare both parasitoid populations to improve mass-rearing quality and to assess performance on medfly in a semi-arid environment, typical of Argentina’s central-western fruit-growing region. Tests were performed under laboratory and non-controlled environmental conditions in semi-field cages during three seasons. Dl_(Cc-bip) females exhibited higher reproductive potential than did Dl_(Cc-tsl) females under lab conditions. However, both Dl_(Cc-bip) and Dl_(Cc-tsl) were found to be similar high-quality females with high population growth rates in warm–temperate seasons, i.e., late spring and summer. Dl_(Cc-bip) females were only able to sustain low reproductive rates in early autumn, a colder season. These results are useful for improving the parasitoid mass production at the San Juan Biofactory and redesigning parasitoid release schedules in Argentina’s irrigated, semi-arid, fruit-growing regions. Full article

Accurately estimating the time of concentration (Tc) is critical for hydrological modelling, flood forecasting, and hydraulic infrastructure design. However, conventional methods often overlook the combined effects of rainfall intensity and antecedent soil moisture, thereby limiting their applicability under changing climates. This study presents a novel approach that integrates data-driven techniques with remote sensing data to improve Tc estimation. This method was successfully applied in the Kalu River Basin, Sri Lanka, demonstrating its performance in a tropical catchment. While an overall inverse relationship between rainfall intensity and Tc was observed, deviations in several events underscored the influence of initial soil moisture conditions on catchment response times. To address this, a modified kinematic wave-based equation incorporating both rainfall intensity and soil moisture was developed and calibrated, achieving high predictive accuracy (calibration: R² = 0.97, RMSE = 1.1 h; validation: R² = 0.96, RMSE = 0.01 h). A hydrological model was developed to assess the impacts of Tc uncertainties on design hydrographs. Results revealed that underestimating Tc led to substantially shorter lag times and significantly increased peak flows, highlighting the sensitivity of flood simulations to Tc variability. This study highlights the need for improved $T_C$ estimation and presents a robust, transferable methodology for enhancing hydrological predictions and climate-resilient infrastructure planning. Full article

Nanomaterials are increasingly used in the development of detection systems for various disease biomarkers as tools for reliable early diagnosis, which is a key factor in reducing mortality and increasing treatment effectiveness. The use of quantum dot–antibody conjugates allows for optical detection of various disease markers in biological fluids, tissues, and individual cells with high sensitivity and specificity. The sensitivity and specificity of detection are determined not only by the outstanding optical properties of fluorescent quantum dots but also by the type of antibodies used for binding target analytes and the methods of their conjugation with quantum dots. This review deals with methods of site-specific and site-nonspecific conjugation of quantum dots with antibodies, including full-length and single-domain antibodies, as well as antibody fragments, with a special focus on their structural features and active moieties used for binding to their targets. The review includes examples of successful applications of quantum dot–conjugated antibodies in diagnosis, environment monitoring, and food safety assessment. We also discuss the prospects of further research in this field, including new conjugation methods and issues related to the stability and specificity of probes. The review provides a comprehensive analysis of the current methods and achievements in antibody conjugation from the viewpoint of subsequent analyte detection, highlighting the importance of further research for improving the existing technologies. Full article

Background: Liver regeneration is a complex process involving multiple signaling pathways that coordinate hepatocyte proliferation, survival, and tissue repair. Natural compounds like silymarin, ursolic acid, quercetin, and resveratrol have shown regenerative potential, though their precise molecular mechanisms remain unclear. 6-O-trans-feruloyl catalpol (6FC), a major bioactive compound from Catalpa ovata, exhibits anti-inflammatory and potential antioxidant effects via regulation of NF-κB signaling and redox-sensitive pathways such as Akt and MAPK, which are critical for cell survival and proliferation. Moreover, 6FC exhibits peroxynitrite-scavenging activity, suggesting its potential antioxidant properties that may protect hepatocytes from oxidative damage during regeneration. However, the role of 6FC in liver regeneration has not been elucidated, positioning it as a promising natural therapeutic candidate for hepatic repair. Purpose: This study aimed to determine whether 6FC promotes hepatocyte proliferation and liver regeneration in vivo using a 2/3 PHx mouse model, and to validate its proliferative effects in vitro with HGF-stimulated Hep3B cells. Methods: A 2/3 PHx liver regeneration model was used to evaluate 6FC-mediated liver regeneration. Histological and molecular analyses assessed hepatocyte proliferation and signaling activation. HGF-stimulated Hep3B cells were also used to examine 6FC proliferative effects in vitro. Results: 6FC significantly promoted liver regeneration by restoring the liver-to-body weight ratio and reducing serum ALT and AST levels without inducing excessive immune responses. Mechanistic studies revealed that 6FC activates Akt and MAPK pathways, increases the expression of critical growth factors, and upregulates cell cycle regulators. These effects were also observed in HGF-stimulated Hep3B cells, suggesting that 6FC may enhance hepatocyte proliferation without triggering excessive immune responses. Conclusions: 6FC accelerates hepatocyte proliferation and promotes liver regeneration by activating key redox-sensitive signaling pathways, highlighting its potential as a natural antioxidant-based therapeutic agent. Full article

Background: Acute appendicitis is the most common surgical emergency in children, yet timely and accurate diagnosis remains challenging due to nonspecific clinical presentations and limitations of imaging and blood tests. Saliva has emerged as a promising diagnostic medium because it is non-invasive, painless, inexpensive, and highly acceptable for pediatric patients. Salivary biomarkers may provide rapid and child-friendly adjuncts to existing diagnostic pathways. Methods: A systematic literature search was performed in Ovid/MEDLINE, Scopus, Web of Science, and the Cochrane Library to identify studies assessing salivary biomarkers in pediatric appendicitis. Eligible studies included children with suspected or confirmed appendicitis and evaluated the diagnostic accuracy of salivary markers compared to clinical, laboratory, or imaging standards. Results: To date, only three salivary biomarkers have been investigated. Leucine-rich α-2-glycoprotein 1 (LRG1) demonstrated high specificity of 100% but low sensitivity of 35–36%, with diagnostic accuracy ranging from AUC 0.77 to 0.85. C-reactive protein (CRP) showed excellent diagnostic performance with sensitivity of 91.3% and specificity of 95.4% (AUC 0.97), and strong correlation with serum CRP (ρ = 0.96). Irisin showed sensitivity of 90% and specificity of 60% with estimated AUC around 0.75, suggesting potential as an adjunct marker but limited as a standalone test. Conclusions: Salivary biomarkers in pediatric appendicitis are promising but remain underexplored, with evidence limited to small, single-center studies totalling fewer than 300 patients. Their advantages include feasibility, tolerability, and suitability for integration into point-of-care testing. Future research should focus on multicenter validation, development of multi-marker salivary panels, and application of biosensor technologies. With further evidence, salivary diagnostics could complement existing strategies and improve the accuracy and child-friendliness of appendicitis care. Full article

Fish species’ biological vocalizations serve as essential acoustic signatures for passive acoustic monitoring (PAM) and ecological assessments. However, limited availability of high-quality acoustic recordings, particularly for region-specific species like the brown croaker (Miichthys miiuy), hampers data-driven bioacoustic methodology development. In this study, we present a framework for reconstructing brown croaker vocalizations by integrating fk14 wavelet synthesis, PSO-based parameter optimization (with an objective combining correlation and normalized MSE), and deep learning-based validation. Sensitivity analysis using a normalized Bartlett processor identified delay and scale (length) as the most critical parameters, defining valid ranges that maintained waveform similarity above 98%. The reconstructed signals matched measured calls in both time and frequency domains, replicating single-pulse morphology, inter-pulse interval (IPI) distributions, and energy spectral density. Validation with a ResNet-18-based Siamese network produced near-unity cosine similarity (~0.9996) between measured and reconstructed signals. Statistical analyses (95% confidence intervals; residual errors) confirmed faithful preservation of SPL values and minor, biologically plausible IPI variations. Under noisy conditions, similarity decreased as SNR dropped, indicating that environmental noise affects reconstruction fidelity. These results demonstrate that the proposed framework can reliably generate acoustically realistic and morphologically consistent fish vocalizations, even under data-limited scenarios. The methodology holds promise for dataset augmentation, PAM applications, and species-specific call simulation. Future work will extend this framework by using reconstructed signals to train generative models (e.g., GANs, WaveNet), enabling scalable synthesis and supporting real-time adaptive modeling in field monitoring. Full article

Background: Globally, uncorrected refractive errors are recognized as the primary cause of visual impairment and blindness. According to a report by the World Health Organization (WHO), providing spectacle lenses at an affordable cost remains a significant challenge, particularly for underprivileged populations in developing countries. This challenge contributes to the low compliance with spectacle wear worldwide. However, the benefits of wearing spectacles are influenced by the perceptions of the population regarding spectacle use. Methods: A quantitative, cross-sectional survey-based study was conducted at a superior educative center in Oman, the University of Buraimi. Participants were recruited from the four major colleges, namely, the College of Health Sciences (COHS), College of Business (COB), College of Engineering (COE), and College of Law (COL), and the Center for Foundation Studies (CFS). This study was conducted over the period from 18 December 2022 to 18 December 2023. Essential data were collected using an electronic questionnaire facilitated by the Google platform. The initial section of the questionnaire outlines this study’s objectives and its benefits to the community. The digital survey comprises three sections: the first section addresses the sociodemographic profile of the participants; the second section explores perceptions related to spectacles; and the third section examines visual symptoms associated with spectacle wear. In this study, a pre-tested survey was administered following consultation with a panel of three subject matter experts who reviewed the clarity and content validity of the test items. Data analyses were performed using descriptive statistics, and linear regression was applied to assess the effect of socioeconomic profile on perceptions of spectacles. Additionally, data entry, processing, and analysis were conducted using SPSS 25 software. The overall mean score for spectacle-related visual symptoms was 2.51 ± 0.75, indicating a moderate level of symptom occurrence. Results: A total of 415 participants (N = 415) were included in this study, comprising 133 males (32.0%) and 282 females (68.0%). The most prominent symptoms related to spectacle perception were “light sensitivity” and “eye pain”, with mean values of 3.03 ± 1.30 and 3.04 ± 1.25, respectively. Additionally, 249 participants (60%) reported moderate concern regarding spectacle-related visual symptoms. Among female participants, 118 (41.8%) exhibited little concern about visual symptoms associated with spectacle wear, whereas this was observed in 25.6% of male participants. Descriptive statistics indicated the mean perceived spectacle-related disadvantages score measured on a scale of 0 to 4 was 2.88 ± 1.16 (57.69% ± 23.15% in percentages), reflecting a moderate perception of such disadvantages. The linear regression model demonstrated statistical significance, as indicated by the likelihood ratio chi-square = 199.194 (df = 15, p < 0.001). The most significant predictor was study major (χ² = 72.922, p < 0.001). Conclusions: The present study indicates that undergraduate students generally exhibit a low perception of the disadvantages associated with wearing spectacles. Randomized sampling should be preferred in future studies to the convenience sampling technique. The most frequently reported visual symptoms include “light sensitivity and eye pain” among spectacle wearers. Therefore, it is imperative to implement health education programs and foundational studies across colleges to address these issues among undergraduate university students. Full article

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder connected with insulin resistance (IR), low-grade inflammation, dyslipidemia, and altered adipokine secretion. We evaluated serum levels of leptin, adiponectin, visfatin, resistin, IL-6, and TNF-α in 150 women with PCOS, stratified by IR status (IR, n = 76; non-IR, n = 74), and examined their associations with anthropometric, metabolic, hormonal, inflammatory, and atherogenic parameters. Anthropometric data included body weight, height, BMI, waist circumference, and waist-to-height ratio (WHtR), while IR was assessed using HOMA-IR and the Matsuda index. Serum adipokines were measured using ELISA, and lipid parameters and atherogenic indices—including non-HDL cholesterol, AIP, leptin/adiponectin, and adiponectin/resistin ratios—were calculated. Women with IR had higher levels of leptin, visfatin, resistin, and TNF-α, and lower levels of adiponectin. Leptin correlated positively with weight, WHtR, HOMA-IR, and atherogenic indices. Adiponectin showed the strongest and most consistent associations with anthropometric indices, HOMA-IR, and the Matsuda index. Resistin was linked to IR indices and IL-6, and visfatin correlated negatively with HDL-C and insulin sensitivity. In a multivariate general linear model, WHtR, but not HOMA-IR, remained independently associated with higher leptin levels and with atherogenic indices. These findings suggest that in PCOS, central adiposity rather than IR explains a substantial part of the adverse adipokine and inflammatory profile, thereby contributing to elevated cardiometabolic risk and highlighting the need for targeted treatment strategies. Full article