Search Results (7,301)

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID-19 syndrome (LC) show substantial clinical overlap, but direct comparative microbiome studies remain limited. Methods: In this cross-sectional study, we compared the fecal gut microbiome of patients with ME/CFS, LC, and healthy controls (HC) within a unified analytical framework using 16S rRNA profiling, differential abundance testing, and multivariate modeling. We also examined associations between microbiome variation and questionnaire-derived symptom-domain scores. Results: Alpha-diversity did not differ significantly among groups, whereas beta-diversity analyses showed small but significant disease-associated community differences with broad overlap between cohorts. Differential abundance analysis identified stronger signals in disease-versus-control contrasts than in the direct ME/CFS vs. LC contrast. Both ME/CFS and LC shared enrichment of Sutterella and depletion of Terrisporobacter and Lachnospiraceae relative to HC. Predicted functional profiling showed shared disease-versus-control changes in pathways related to anaerobic acetate/H₂ carbon flow, inositol/polyol degradation, phosphonate/C1-related metabolism, and lysine-derived fermentation. Regression analyses showed the strongest microbiome associations with fatigue-related and physiosomatic domains, while affective, cognitive, and gastrointestinal outcomes showed weaker signals. Conclusions: Overall, these findings support the presence of overlapping but non-identical gut microbiome alterations in ME/CFS and LC. The results provide a basis for future longitudinal and multi-omics studies aimed at clarifying the stability, functional relevance, and clinical utility of these microbial patterns. Full article

Low temperature and low irradiance (LTLI) stress severely limits strawberry growth and productivity during winter protected cultivation. This study investigated the physiological responses of the short-day strawberry cultivar ‘Benihoppe’ to individual and combined LTLI stress and developed a quantitative damage evaluation index. Seedlings were exposed to four treatments for 20 d: control (25/15 °C, 600 μmol m⁻² s⁻¹), single low temperature (LT: 15/5 °C), single low irradiance (LI: 100 μmol m⁻² s⁻¹), and combined stress (LTLI: 15/5 °C, 100 μmol m⁻² s⁻¹). Compared to isolated stress factors, combined LTLI treatment exhibited a statistically verified synergistic damaging effect (two-factor ANOVA, LT × LI p < 0.01) on leaf structure and function. LTLI-treated plants showed severe reductions in leaf area, palisade tissue thickness, chlorophyll content, and net photosynthetic rate (Pn), alongside elevated malondialdehyde (MDA) accumulation. Chlorophyll a fluorescence (OJIP) analysis revealed that LTLI stress strongly blocked the electron transport chain at the PSII acceptor side, increasing the J-step relative variable fluorescence (Vj) and suppressing the performance index (PI). To quantify these impacts, a Low Temperature and Low Irradiance Damage Index (LTLDI) was derived from 12 core physiological and morphological variables. The LTLDI scores demonstrated that LTLI induced severe damage by day 10 (score: 0.69) and extremely severe damage by day 20 (0.87), which were substantially higher than the damage caused by LT (0.58 at 20 d) and LI (0.63 at 20 d) alone. The index reliability was confirmed by its strong correlation (r > 0.9) with key stress markers (Fv/Fm, Pn, and MDA). Overall, combined LTLI stress exacerbates structural degradation and PSII photoinhibition in strawberry leaves. The proposed LTLDI offers a practical, standardized tool for evaluating stress severity, facilitating timely environmental management in greenhouse strawberry production. Full article

The integration of non-immersive digital technologies into anatomy education has expanded substantially; however, their relationship with students’ academic motivation remains underexplored. This study examined the association between two non-immersive instructional modalities (Sectra^® Table and Complete Anatomy^®) and academic motivation among medical students, framed within Keller’s ARCS model. An analytical cross-sectional quasi-experimental design was utilized with 109 participants, whose group allocation was determined by existing curricular organization (LMC13: Sectra^® Table; LMC23: Complete Anatomy^®). Academic motivation was assessed using the Reduced Instructional Materials Motivation Survey (RIMMS), which evaluates attention, relevance, confidence, and satisfaction. Due to non-normal data distribution and variance heterogeneity, group differences were analyzed using permutation multivariate analysis of variance (PERMANOVA). The analysis revealed significant differences between instructional groups (R² = 0.17, p = 0.001). Students in the Complete Anatomy^® group reported higher motivational scores across domains, with the largest difference observed in confidence (R² = 0.10). Although effect sizes were modest, the findings indicate that differences in accessibility and opportunities for autonomous interaction are related to variations in motivational engagement in technology-enhanced anatomy learning contexts. These results highlight the importance of considering motivational constructs when comparing instructional design approaches. Future longitudinal and controlled studies are needed to further examine these associations and their potential educational implications. Full article

Traditional treatment strategies for Type 2 diabetes (T2D) adopt a “one-size-fits-all” approach, limiting individual effectiveness. This study presents an explainable, data-driven framework for multi-treatment and single-treatment selection of SGLT2 inhibitors (SGLT2-i) and DPP-4 inhibitors (DPP4-i) based on patient-specific health characteristics. Our approach evaluates treatment effectiveness across four outcomes—glycosylated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and body mass index (BMI)—to enable individualized treatment recommendations. The multi-treatment model, based on multi-output regression, achieved an R² score of 0.44 and an RMSE of 5.58, identifying benefit subgroups for SGLT2-i and DPP4-i across all outcomes. Integrated with SHapley Additive exPlanations (SHAP) analysis, the model offers insights into the factors influencing treatment effects. The single-treatment selection algorithm achieved an accuracy of 0.47 and an F1 score of 0.46, showing a higher average treatment effect with SGLT2-i on all outcomes, notably in the reduction in HbA1c, LDL, and BMI and a modest increase in HDL. While DPP4-i demonstrated beneficial effects on HbA1c, LDL, and HDL, it was associated with an increase in BMI. These findings highlight the benefits of a multi-faceted, patient-centered precision medicine approach for T2D management, enabling treatment strategies that address individual health needs beyond HbA1c. Full article

Perception-oriented evaluation of automotive headlamps still relies mainly on human-vision photometric criteria, although forward-facing cameras are increasingly safety-critical sensing elements for night driving. This paper benchmarks 16 measured production headlamp light distributions with a simulation chain that combines headlamp spectra and beam patterns, diffuse scene reflection, an imaging-transfer model, and an EMVA-based camera model. The quantitative chain maps scene radiance to sensor-domain signal-to-noise ratio, derives task-specific required signal-to-noise curves from a six-network object-recognition ensemble, and aggregates local threshold satisfaction as region-of-interest coverage across three target reflectances and five driving speeds using WLTP moving-time weights. For the baseline RGB camera, WLTP-weighted coverage ranges from 18.95% to 53.48% across the evaluated light distributions, corresponding to a factor of 2.82 between the weakest and strongest distribution. The camera-parameter sweeps show that favorable beam placement can deliver comparable benchmark coverage with roughly 60% smaller pixel pitch than the weakest distribution, corresponding to an 84% reduction in pixel area, or at materially shorter exposure times. The WLTP-weighted coverage score correlates positively with the established Headlamp Safety Performance Rating, with Pearson $r=0.68$ for the RGB configuration, indicating partial alignment between human-centric and camera-centric illumination needs while confirming that the metrics are not interchangeable. The results identify headlamp light distribution as a primary design parameter for nighttime camera perception and provide a quantitative basis for co-design of automotive lighting and camera-based systems. Full article

Background/Objectives: Survival rates after pediatric liver transplantation have improved substantially over recent decades, yet the psychiatric consequences for recipients remain a concern that warrants closer attention. We sought to map the psychiatric symptom burden across multiple domains in this population and to determine which symptom clusters carry the greatest impact on health-related quality of life (HRQOL). Materials and Methods: Fifty liver transplant recipients between the ages of 8 and 18 were enrolled at a single center. Children and their parents completed four psychiatric measures—the CBCL, CDI, SCARED, and CRIES-13—alongside the parent-proxy PedsQL to capture HRQOL across physical, emotional, social, and school functioning domains. Correlations between instruments were calculated, and linear regression was used to determine which psychiatric variables independently predicted PedsQL Total scores. Results: Across all psychiatric measures, higher symptom scores were associated with lower HRQOL, with school functioning recording the lowest absolute PedsQL domain score, while emotional functioning demonstrated the strongest and most consistent inverse correlations with all psychiatric symptom measures across instruments. CBCL Total (r = −0.607), SCARED Total (r = −0.557), and CRIES-13 Total (r = −0.548) scores all correlated meaningfully with overall HRQOL. When entered into multivariable analysis, anxiety symptoms measured by the SCARED (β = −0.295, p = 0.032) and post-traumatic stress symptoms measured by the CRIES-13 (β = −0.400, p = 0.004) stood out as the two independent predictors of worse PedsQL Total scores. Conclusions: Even in medically stable recipients, anxiety and post-traumatic stress symptoms were independently associated with lower daily functioning scores and overall quality of life. These findings suggest that routine psychosocial screening and trauma-informed approaches may warrant integration into post-transplant care protocols, and that prospective, adequately powered studies are needed to confirm and extend these associations. Full article

The non-invasive determination of live weight and body composition of ewes is an important element in ensuring precision livestock management and animal well-being. Traditional practices tend to be subjective, labor-intensive, or rely on expensive medical imaging such as Computed Tomography (CT). This paper proposes a new hybrid deep learning method to predict live weight and carcass traits in Coopworth ewes. The dataset of 1184 images taken from 156 ewes was analyzed and compared using a hybrid model (ResNet18 with Multi-Layer Perceptron through simple concatenation) and two more advanced models: Attention-Guided Feature Fusion Network (AGFF-Net) based on cross-modal attention and a Vision Transformer-based Hybrid Regressor (ViT-HR). Auxiliary tabular variables are the Body Condition Score (BCS) and size category. The Transformer architecture predicts (R² = 0.93) the live weight of ewes by dynamically ranking each visual patch and asking it to query the self-attention sequence. This technique treats the BCS as a distinct token in the self-attention sequence. Data partitioning at the animal level was stringent, thereby giving strong generalization. Findings indicate that the best advanced fusion systems are far better than baseline concatenation, with a high accuracy confirmed with gold standards obtained by CT. Grad-CAM visual explainability makes sure that models are able to localize biologically relevant anatomical locations successfully. The study closes the gap between complex deep learning models and real-world agriculture implementation to provide a correct, interpretable and scalable solution to real-time livestock measurements. Full article

Purpose: Prostate cancer is one of the most common malignancies in men, yet current prognostic methods remain suboptimal. Emerging evidence indicates that microRNAs (miRNAs) play critical roles in prostate cancer progression. This study aimed to identify miRNAs associated with adverse clinical outcomes by comparing miRNA expression profiles between prostate tumors with unfavorable versus favorable prognostic features. Materials and Methods: High-throughput next-generation sequencing (NGS) was used to analyze miRNA expression in formalin-fixed, paraffin-embedded prostate cancer tissue samples. Patients were classified into favorable or unfavorable prognosis groups based on risk stratification scores, Gleason grade group, and biochemical recurrence. Differentially expressed miRNAs were identified using a fold-change threshold ≥2 and a false discovery rate (FDR) <0.05. Predicted target genes and pathway analyses were conducted to generate candidate regulatory hypotheses rather than confirm mechanistic relationships. Results: Several miRNAs were differentially expressed according to prognostic category. miR-206 was significantly downregulated in high-risk tumors compared with low-risk tumors. High-Gleason-grade tumors showed reduced expression of miR-7704 and miR-4454, while miR-25-3p and let-7f-5p were upregulated. In patients with early biochemical recurrence, miR-7704 and miR-10400-5p were downregulated relative to those with prolonged recurrence-free survival. Target prediction analysis identified CPEB3, HAND1, PTAR1, and SPRYD4 as shared candidate targets, with CPEB3 emerging as a prioritized candidate supported by consistency in external datasets rather than a confirmed molecular target. Conclusions: Distinct miRNA expression patterns correlate with prostate cancer aggressiveness and clinical outcomes. miR-206, miR-7704, miR-4454, miR-25-3p, and let-7f-5p represent candidate prognostic biomarkers. Their shared target CPEB3 should be interpreted as a prioritized candidate for future investigation. Given the very small sample size and the lack of qRT-PCR and functional validation, these findings should be considered preliminary and hypothesis-generating, requiring validation in larger independent cohorts and experimental studies. Full article

Background: This study investigates textbook oncologic outcomes (TOO), a measurement operationally defined to produce a holistic measure of surgical success, with respect to patients diagnosed with pancreatic adenocarcinoma undergoing distal (left) pancreatectomy for pancreatic adenocarcinoma. This study aims to identify factors associated with achieving TOO, emphasizing the role of hospital type. Methods: The NCDB (2010–2022) was queried for patients with clinical stage I–III pancreatic adenocarcinoma. Inclusion criteria consisted of patients > 18 who underwent curative partial or total pancreatectomy. The primary outcome was the achievement of TOO—operationally defined as R0 resection, ≥12 lymph nodes examined, no prolonged hospital stay, absence of 30-day mortality, and no readmissions. Logistic regression analyses were conducted to identify predictors of TOO. Results: Analysis of 11,194 patients showed that 38.9% achieved TOO. Achievement of TOO was associated with a median increase in one year in overall survival. Factors associated with TOO achievements in the adjusted model include female sex, private insurance, a lower Charlson/Deyo score, minimally invasive surgery (MIS), and high-volume centers. Notably, MIS emerged as a significant factor associated with 26% higher TOO (OR 1.26, 95% CI: 1.14–1.40) while treatment at high-volume hospitals was associated with 28–112% increased TOO (OR 1.28, 95% CI: 1.08–1.54 for Q3 volume and OR 2.12, 95% CI: 1.76–2.55 for Q4 volume). Conclusions: Achieving TOO is significantly influenced by patient demographics, clinical characteristics, and notably, the case volume of the treatment facility. These findings underscore the importance of considering centers experienced in surgical planning and patient counseling to optimize outcomes in distal pancreatectomies. Full article

Measuring the impact of citizen-science projects is hard because inputs are heterogeneous, mostly categorical, and sparse. We present Alquimics, a compact supervised neural network trained on one-hot project descriptors to predict impacts across five domains (Environment, Economy, Governance, Science, and Society). Each project is encoded as a binary vector of length 4460 (223 questions × 20 options, flattened). The network employs a 4460–42–5 topology with logistic activations throughout; labels consist of five continuous targets in [0, 1] obtained by scaling expert domain scores in [1, 42]. We implement L2-regularised training in Octave using fmincg with MaxIter = 10 and lambda = 0.07. Leave-one-out cross-validation (LOOCV) over nine projects yields an overall RMSE = 10 and R² = 0.06 on the 1–42 scale, with Governance being the most predictable domain (RMSE = 6, R² = 0.3). We document the entire data pipeline, objective, and implementation, provide a minimal reproducible script, and discuss limitations arising from the small dataset (n = 9 projects). This establishes a transparent baseline that complements rule-based scoring and can be expanded as more labelled projects become available. Full article

Traditional doubanjiang was investigated to identify endogenous peptides that may contribute to taste maintenance under salt-reduction conditions. Peptidomics identified 1230 peptides at −10logP ≥ 15. UMPred-FRL predicted 161 potential umami peptides, and molecular docking showed that 141 of these peptides could enter the binding site of the T1R1/T1R3 receptor. The successfully docked sequences were mainly short oligopeptides containing three to five amino acid residues. Based on docking scores, six representative candidate peptides were screened, namely EESP, SCPH, SSSGF, PDTE, SYH, and DYDS. Docking and MM-GBSA analyses suggested that these peptides mainly bound within the VFT cavity of T1R1/T1R3, and the interacting residues were dominated by polar residues such as Ser, Asn, Gln, and His and hydrophobic residues such as Tyr, Ile, Leu, and Val. MM-GBSA further suggested that vdW was the major favorable contributor, while Lipo supported complex stability. The umami thresholds of the six peptides ranged from 0.14 to 1.09 mmol/L. Experimental validation by threshold determination and sensory addition showed that all six peptides significantly increased saltiness, whereas their effects on umami differed. PDTE showed the strongest umami-enhancing effect, while SSSGF, SYH, and SCPH exhibited more pronounced saltiness synergy. These results suggest that the screened peptides do not necessarily amplify umami in complex food systems, but may contribute to taste maintenance under salt-reduction conditions through umami support, saltiness synergy, and taste-structure remodeling. Full article

Control-barrier-function-based safety filters are promising for autonomous driving, but most existing formulations treat obstacle perception as deterministic or account only for bounded ego state-estimation errors. This becomes limiting when obstacle existence, position, motion, and sensing quality vary online. We present a sensor-health- and belief-aware risk-adaptive high-order control barrier function (HOCBF) safety filter for dynamic obstacle avoidance. The method uses obstacle belief from a perception/tracking module, inflates residual obstacle uncertainty according to an object-wise sensor-health score, and converts upper-tail risk into adaptive HOCBF tightening through conditional value-at-risk (CVaR). Sensor health enters the controller through both covariance inflation and online CVaR confidence scheduling. The resulting quadratic program combines deterministic ego-error robustness with probabilistic perception uncertainty while minimally modifying the nominal control input. The zero-slack solution guarantees forward invariance of the risk-tightened safe set under the stated assumptions, whereas the slack-activated mode provides a quantified least-violation fallback rather than a strict safety guarantee. Simulations on a nonlinear 3-DOF bicycle model evaluate critical cut-in, sudden perception degradation, merge-bottleneck, fixed-CVaR, sensitivity, runtime-scaling, heterogeneous multi-obstacle, and heavy-tailed uncertainty cases. Full article

Background/Objectives: Nutrient profiling models are widely used to support healthier food choices, but their applicability may be limited in dietary cultures with multi-dish meals and high consumption of minimally processed foods. This study extended the Ajinomoto Group Nutrient Profiling System (ANPS), originally developed for dish- and meal-level assessment, to evaluate overall quality of daily intake (ANPS-Day) based on four components (protein, vegetables, saturated fatty acids [SFAs], and sodium), and examined its criterion-related validity using 24 h urinary biomarkers. Methods: A total of 324 healthy Japanese adults aged 20–69 years completed four-day semi-weighed dietary records and two non-consecutive 24 h urine collections. Urinary sodium, potassium and urea nitrogen were measured. Associations were examined using age- and sex-adjusted Spearman correlation coefficients and trend analyses. Results: The crude ANPS-Day score showed weak and inconsistent correlations with urinary biomarkers. In contrast, the energy-adjusted ANPS-Day score was positively correlated with estimated potassium intake (r = 0.25) and inversely correlated with the urinary sodium-to-potassium (Na/K) ratio (r = −0.24). In quartile analyses, higher energy-adjusted ANPS-Day scores were associated with higher protein and potassium intakes and with a lower Na/K ratio (all p for trend ≤ 0.001). In component analysis, vegetable points were positively associated with potassium intake, whereas sodium points were inversely associated with estimated sodium intake and the Na/K ratio. SFA points were not associated with urinary biomarkers. Conclusions: The energy-adjusted ANPS-Day score showed modest but biologically plausible associations with urinary biomarkers, providing partial evidence of criterion-related validity in assessing diet quality in multi-dish dietary settings. Full article

Standard predictive equations for maintenance energy requirements often do not account for individual variability in dogs, potentially leading to nutritional inaccuracies. This prospective proofofconcept study evaluated a dynamic energy prescription protocol integrating wearable activity data in adult shelter dogs. Twenty-six dogs were enrolled, of which 19 had valid longitudinal data for analysis. The 10-week protocol comprised a fixed energy prescription phase (R1), based on perceived activity level, followed by a dynamic phase (R2), in which energy allowance was recalculated weekly incorporating accelerometer-derived activity data and other individual parameters. During R2, BCS remained unchanged in 12/19 dogs and varied one unit in 7/19. Of these, two dogs with above-ideal baseline BCS decreased, and one dog with below-ideal BCS increased. Body weight (mean ± SD: 24.2 ± 7.0 vs. 23.6 ± 6.7 kg; p < 0.001) and body fat percentage (19.9 ± 5.4 vs. 18.3 ± 4.6%; p = 0.010) decreased, while muscle condition score remained stable. Feeding adherence improved significantly from 8/19 during R1 to 18/19 during R2 (p = 0.004). These findings support the feasibility of integrating activity monitoring into a dynamic energy prescription and its potential to improve alignment between prescribed and consumed energy. Longer-term studies are warranted to confirm these observations. Full article

Drawing on mobile foot reflexology in Taiwan, this article examines innovation readiness in small-scale wellness services where formal R&D resources, standardized workstations, and organizational support systems are limited. It conceptualizes readiness as a staged service-design condition comprising problem-recognition readiness, practitioner-agency readiness, co-creation readiness, and implementation-fit readiness. The empirical design integrated workplace observation, a survey of 59 therapists, semi-structured interviews with 10 therapists, expert consultation with 7 specialists, and two rounds of prototype evaluation (n = 17 and n = 19). Rather than treating ergonomic symptoms as an isolated occupational health outcome, the analysis traces how discomfort, posture constraints, psychosocial resources, practitioner narratives, and expert judgment were translated into design parameters and two chair prototypes for mobile service delivery. Three cross-phase mechanisms emerged: constraint visibility, practitioner-mediated translation, and implementation-fit testing. Shoulder, wrist/hand, and low-back discomfort signaled unresolved operational friction; high meaning and competence scores pointed to a practitioner resource base for adaptive participation; and staged prototype testing identified portability, adjustability, stability, and bodily comfort as the central adoption conditions. The article contributes to Administrative Sciences by showing that grassroots service innovation readiness is not simply an attitudinal state but an enacted process through which field constraints are made visible, jointly interpreted, and converted into a deployable service-support solution. Beyond this case, the staged readiness logic may also inform mobile wellness, community-care, rehabilitation-support, personal-care, and other low-resource service organizations that must convert frontline constraints into feasible service-support interventions. Full article