Search Results (1,670)

Wearable inertial measurement units (IMUs) offer an accessible alternative to optical motion capture (MoCap) gait analysis, but their performance in Progressive Supranuclear Palsy (PSP) requires validation. We assessed the concurrent validity of IMU-derived versus MoCap-derived gait metrics and static postural sway in 30 patients with PSP using Bland–Altman analysis, Intraclass Correlation Coefficients (ICC), and Spearman rank correlations. Finally, we assessed equivalence using the Two one-sided tests (TOST) procedure. Multivariable linear regression was used to determine whether clinical severity, as measured by the PSP Rating Scale (PSPRS), independently predicted absolute IMU measurement error while controlling for patient age and gait velocity. IMUs demonstrated excellent between-system agreement for parameters such as cadence (100.76 ± 11.42 vs. 100.52 ± 11.59) and cycle time (1.21 ± 0.15 vs. 1.22 ± 0.15; ICC > 0.98), despite a systematic underestimation of gait velocity (p < 0.05). Agreement significantly diminished for micro-phases (e.g., single/double support times) and spatial asymmetry. Interestingly, the TOST procedure revealed that only sagittal and transverse trunk kinematics were equivalent between systems, with all other measures failing to find equivalency. For static sway, the IMU demonstrated strong rank-order correspondence for tracking relative postural instability (ρ = 0.82, p < 0.05). Multivariable analysis revealed that higher PSPRS scores are independently associated with greater between-system discrepancies in support phases and pelvic and trunk kinematics (p < 0.05), irrespective of reduced gait speed. These findings highlight the need to develop disease-specific algorithms, rather than relying on normative commercial models, to establish reliable digital biomarkers for monitoring progressive motor decline. Full article

Traveling-wave fault location in distribution networks confronts two fundamental challenges: insufficient robustness of the cost function against heavy-tailed synchronization noise, and the location-resolution bottleneck imposed by the discrete search step. Starting from first physical principles, we identify that faulty-branch identity is encoded in the ordering pattern of multi-terminal TW arrival times rather than in their absolute values. Building on this insight, we propose a faulty-branch identification and precise fault-location method that integrates amplitude-assisted rank correlation (AAC) features with random forest (RF). At the theoretical level, we employ Hampel’s finite-sample breakdown-point framework to quantitatively establish that the $L_2$ cost function has an asymptotic breakdown point of zero, whereas the Spearman rank correlation coefficient attains an asymptotic breakdown point of 0.5—providing a rigorous robustness justification for replacing the $L_2$ residual with a rank-consistency cost. At the algorithmic level, the method consists of a three-stage inference pipeline: AAC computes a joint rank correlation cost for every line section across the network and extracts a 42-dimensional feature vector encompassing cost statistics, timing residuals, and topological attributes; feature selection is performed via fused ranking, which combines Pearson correlation, point-biserial correlation, and RF out-of-bag permutation importance through a weighted harmonic mean; the RF classifier directly performs branch identification over the full edge space, and the RF regressor predicts the coarse-location residual from local cost-terrain statistical features along the correctly identified branch, breaking through the 20 m search-step resolution bottleneck. We construct a five-layer physical noise model covering wavefront detection, time synchronization, wave-velocity deviation, reflected-wave misdetection, and terminal failure. Experiments on three structurally distinct 10 kV radial distribution network topologies, each with 5000 independently generated fault samples, demonstrate that branch identification accuracy remains stably above 94%, and residual correction reduces the mean location error from approximately 60 m to approximately 40 m—an improvement exceeding 30%—confirming the effectiveness of the physics–data hybrid framework for TW fault location in distribution networks. Full article

Background and Objectives: Efficient landing shock attenuation is important for both athletic performance and lower-extremity injury prevention in youth soccer players. Although landing biomechanics and change-of-direction (COD) performance have been widely investigated, the relationship between field-based COD performance and landing impact characteristics remains unclear. This study aimed to examine the relationships between linear sprint performance, COD performance, and landing impact during a standardized single-leg forward drop jump landing task in junior soccer players. Methods: Thirty-six junior soccer players (22 boys and 14 girls; 10–12 years) participated in this cross-sectional study. Linear sprint performance and COD performance were assessed using a 30 m sprint test and a 30 m zigzag run test, respectively. Landing impact was evaluated during a standardized single-leg forward drop jump landing task using a force plate. Body weight-normalized peak vertical ground reaction force (peak vGRF, %BW) was calculated for each trial, and the average of the final five successful trials was used for analysis. Relationships between performance measures and body weight-normalized peak vGRF were examined using Spearman’s rank correlation coefficients and partial Spearman correlation analyses adjusted for sex. Results: No significant correlation was observed between 30 m sprint performance and body weight-normalized peak vGRF (ρ = 0.106, p = 0.537). In contrast, 30 m zigzag run performance showed a moderate positive correlation with body weight-normalized peak vGRF (ρ = 0.401, p = 0.015), indicating that poorer COD performance was associated with greater landing impact. This association remained significant after adjustment for sex (partial ρ = 0.474, p = 0.004). Conclusions: These findings suggest that landing impact characteristics may represent one biomechanical factor associated with COD performance. Although the observed association was moderate, field-based COD assessments may provide practical information regarding landing impact characteristics. Future studies should incorporate biological maturation, COD deficit, and additional biomechanical variables to further clarify these relationships. Full article

Porcine-derived gelatin sponge SPONGOSTAN™ is an adjunct material routinely used in neurosurgery. This study aimed to describe its MRI features, since its imaging features are not available yet in veterinary medicine. Post-operative MR images of dogs that underwent decompressive ventral slot surgery following cervical intervertebral disc extrusion were retrospectively reviewed by three readers; inter-rater association was evaluated using the Spearman’s rank correlation coefficient. Seventy-eight cases were included. In 51% of cases, the hemostatic sponge appeared isointense in T1-W images compared to the semispinalis capitis muscle, and in the remaining 49% of the cases, it appeared iso-hypointense. On T2-W sequences, the material appeared hyperintense in 76% of cases, with signal intensity from hypointense to iso-hyperintense in the remaining 24%. On the GET2-W* sequences, the material appeared hypointense in 91% and iso-hypointense in 9% of cases. A peripheral hyperintense rim was described in 41%, 35% and 6% of T2-W, T1-W and GET2*-W images, respectively. A strong association was detected with a p-value < 0.05 and a correlation between 0.74 and 1. To conclude, based on the findings herein achieved, the association of hyperintensity in T2-W, hypointensity with signal void in GET2*-W images when compared to semispinalis capitis muscle and the presence of a peripheral hyperintense rim can be considered distinctive features for the hemostatic gelatin sponge called SPONGOSTAN™ to correctly identify this hemostatic product in post-operative MRI examinations. Full article

Accurate estimation of the state of health (SOH) of lithium ion batteries is a fundamental prerequisite for the safe and reliable operation of battery management systems. To address the issues of insufficient feature representativeness, manually dependent hyperparameter tuning, and limited generalization under small sample conditions in existing SOH estimation methods, this paper proposes a hybrid SOH estimation approach based on a convolutional neural network and bidirectional gated recurrent unit optimized by the RIME optimization algorithm. Unlike existing CNN GRU/LSTM models that rely on unidirectional recurrent structures and can only utilize forward temporal information, the proposed CNN-BiGRU architecture captures bidirectional contextual dependencies inherent in battery degradation, enabling more comprehensive characterization of aging dynamics from limited cycle data. Firstly, 13 health indicators (HIs) related to capacity degradation are extracted from the incremental capacity (IC) curves, and Spearman’s rank correlation coefficient is employed to select the optimal feature subset with the highest correlation. Secondly, a CNN BiGRU hybrid architecture is constructed, where CNN extracts local degradation features and BiGRU captures bidirectional temporal dependencies. More importantly, instead of relying on manual trial and error or grid search for hyperparameter determination, the RIME algorithm is introduced to automatically and globally optimize the core hyperparameters of the model. Finally, ablation and comparative experiments are conducted on the public NASA dataset. The results demonstrate that the proposed model significantly outperforms other comparison methods in terms of MAE, MAPE, and RMSE for three battery cells under both 80% and 60% training set ratios, confirming its comprehensive superiority in estimation accuracy, robustness, and generalization capability with limited samples. Full article

Background and Objectives: Psychiatric symptoms and multidimensional impulsivity may be associated with the clinical and functional heterogeneity of substance use disorders (SUDs), but evidence from Saudi Arabian treatment populations remains limited. This study examined concurrent associations with a study-specific aggregate of Addiction Severity Index (ASI-5) interviewer severity ratings. Materials and Methods: This cross-sectional study included 204 adults receiving inpatient detoxification or residential rehabilitation services in Najran, Saudi Arabia. The seven ASI interviewer ratings were summed as an aggregate score. Psychiatric symptoms were assessed using the Brief Psychiatric Rating Scale (BPRS), and impulsiveness using the Barratt Impulsiveness Scale-11 (BIS-11). Analyses included age- and sex-adjusted analyses of covariance, false-discovery-rate correction, bootstrap Spearman correlations, an a priori multivariable model with HC3 robust confidence intervals, and sensitivity analyses addressing content overlap, multicollinearity, influential observations, functional form, and the bounded outcome distribution. Results: The mean age was 34.4 ± 7.3 years; 78.9% were male. The aggregate score was 26.33 ± 4.15. It correlated strongly with BPRS total (ρ = 0.874, 95% CI 0.827–0.908) and moderately with BIS-11 total (ρ = 0.590, 95% CI 0.494–0.669). In the primary model (adjusted R² = 0.864), age, BPRS total, motor impulsiveness, and non-planning impulsiveness were conditional correlates of greater aggregate burden; male sex was inversely associated, and polysubstance use was not. BPRS remained associated after exclusion of the ASI psychiatric domain. Separate impulsivity-domain and BIS-11 total models, 5000-resample bootstrap analysis, median regression, and fractional-logit analysis retained the principal psychiatric and impulsivity directions. The polysubstance coefficient varied across sensitivity models. Conclusions: Psychiatric symptom burden and selected impulsivity dimensions were concurrently associated with higher study-specific aggregate ASI interviewer severity scores. Integrated psychiatric and impulsivity assessment may help characterize patients with greater concurrent multidomain clinical burden; the aggregate score should not be interpreted as a validated global severity or prediction measure. Full article

Background: Atrial fibrillation (AF) is associated with oxidative stress and inflammation. Glutathione reductase (GR) and microRNA-144 (miR-144) may participate in redox-related pathways. This study aimed to evaluate relative GSR mRNA and miR-144 expression in peripheral blood samples from patients with and without AF and to explore their associations with selected clinical characteristics. Methods: This case–control study included 189 hospitalized adults: 95 without AF and 94 with AF. Clinical, anthropometric, biochemical, and echocardiographic data were collected for all participants. GSR mRNA was assessed by quantitative real-time PCR in whole blood samples, whereas circulating miR-144 expression was evaluated in serum. Group differences were assessed using nonparametric tests, correlations were evaluated using Spearman’s rank correlation coefficient, and multivariable logistic regression was used to identify variables independently associated with AF. Model stability was assessed using bootstrap internal validation. Results: Relative GSR mRNA expression was significantly lower in the AF group than in controls (0.1539 vs. 0.2058, p < 0.001), whereas miR-144 expression was significantly higher in patients with AF (0.3636 vs. 0.2550, p = 0.0183). In multivariable logistic regression adjusted for clinical confounders, higher miR-144 (OR = 1.336, p = 0.048) and lower GSR (OR = 0.343, p < 0.001) expression remained associated with AF. Bootstrap internal validation supported the statistical stability of the GSR association (optimism-corrected AUC = 0.709, bootstrapped 95% CI: 0.622–0.785), whereas miR-144 showed only a more modest and less stable association (optimism-corrected AUC = 0.598, bootstrapped 95% CI: 0.519–0.684); both signals remain exploratory and do not yet support routine clinical use as diagnostic or risk-stratification biomarkers in AF. Both markers showed exploratory correlations with selected clinical and biochemical variables. Given the cross-sectional design of the study, all reported relationships should be interpreted as statistical associations rather than as evidence of causality. The observed correlations between molecular markers and clinical parameters are hypothesis-generating and warrant further investigation. Full article

Background/Objectives: Large language models (LLMs) show promise for clinical decision support, yet their accuracy in interpreting specialized medical guidelines remains uncertain. Retrieval-augmented generation (RAG) may enhance performance by grounding responses in authoritative knowledge bases. This study aimed to compare the accuracy, comprehensiveness, and safety of RAG-enhanced versus standard LLMs for answering clinical questions derived from the German S3 guideline for oral cavity carcinoma. Methods: We conducted a prospective, single-blind benchmark study evaluating six LLMs: one RAG-enhanced model (Custom GPT with guideline access), one consensus-based model (ConsensusGPT), and four standard models (DeepSeek-V3.2, Mistral Small 3.2, Qwen3-Next-80B, GPT-OSS-120B). Fifty clinical questions covering 17 guideline domains were presented to each model three times, yielding 900 evaluations. Three expert reviewers assessed responses using 5-point Likert scales for accuracy, comprehensiveness, and clarity, under a single-blind procedure, the effectiveness of which was tested by a pre-specified manipulation check. We then ran a paired within-model experiment in which each base model was queried with and without guideline access through a transparent, openly released retrieval pipeline, and scored every response with a condition-blind automated judge alongside deterministic retrieval metrics computed from the logs. Secondary outcomes included hallucination rates and guideline citation behavior. Inter-rater reliability was assessed using intraclass correlation coefficients (ICCs). Results: In a paired within-model design that held each base model fixed, adding transparent guideline retrieval improved accuracy—significantly in the three weaker open-weight models (Mistral, Qwen3, and GPT-OSS) and directionally in the already-strong DeepSeek and GPT-5 bases. Because a pre-specified blinding check found that experts could still identify retrieval-augmented answers with 98.5% accuracy, we anchored causal interpretation on measures that do not depend on the human raters, ranked by their independence: deterministic, log-derived retrieval metrics first, and then an automated, condition-blind LLM judge, whose agreement with the experts (Spearman ρ = 0.81, 95.7% within-one agreement) establishes shared calibration rather than independence from their bias. Deterministically from the retrieval logs, citation groundedness rose from 0% to 51–89% and retrieval recall@5 was 92%. On the judge, content-level hallucination fell from 42% to 4% and accuracy rose by a pooled +0.64 points (95% CI 0.47–0.80); the accuracy gain persisted after adjustment for response length (+0.48, 95% CI 0.22–0.73), which retrieval shortened rather than lengthened. The accuracy gain was large for weaker base models and small or non-significant for already-strong ones, whereas the hallucination and auditability gains were consistent across all models. The human ratings reproduced the judge’s accuracy effect (+0.61, 95% CI 0.49–0.74), and GPT-5 run through the transparent pipeline showed no significant difference from the proprietary Custom GPT (judge accuracy 4.48 vs. 4.58). Conclusions: Guideline retrieval yields a reproducible, largely base-independent improvement in the safety and auditability of LLM answers to clinical guideline questions, with accuracy gains concentrated in weaker base models. Because retrieval-augmented answers are recognizable to experts, rigorous evaluation should rely on rater-independent measures, and residual hallucination continues to require human oversight. Full article

Melon (Cucumis melo L.) germplasm resources are vital for seed-industry innovation and cultivar breeding. To systematically characterize their phenotypic variation, classification relationships, and breeding potential, 403 melon accessions were evaluated using nine quantitative characteristics specified in the guidelines for tests of distinctness, uniformity, and stability. These characteristics included fruit longitudinal diameter, fruit transverse diameter, fruit peduncle length, internode length, flesh thickness, petiole length, rind thickness, soluble solids content, and seed cavity diameter. The evaluated population exhibited extensive phenotypic variation, with coefficients of variation ranging from 14.0% to 57.4%. Rind thickness showed the greatest variation, while fruit transverse diameter, flesh thickness, fruit peduncle length, and fruit longitudinal diameter also displayed considerable differentiation. The Shannon–Weaver diversity index ranged from 1.74 to 1.96, indicating substantial diversity in fruit morphology, vegetative growth, internal fruit structure, and quality-related characteristics. Spearman rank correlation analysis revealed close developmental relationships among fruit-related characteristics, with rind thickness showing the strongest positive correlation with flesh thickness. Principal component analysis extracted three components with eigenvalues greater than one, which together explained 65.22% of the total phenotypic variation and primarily represented fruit morphological structure, vegetative growth, and fruit quality. Hierarchical cluster analysis classified the 403 accessions into four quantitative phenotypic groups, with highly significant differences among the groups for all nine characteristics. Furthermore, a weighted comprehensive selection index identified several accessions with superior combined agronomic performance, among which accession 20225110454A ranked first. These findings provide a quantitative phenotypic basis for melon germplasm conservation, core collection development, parental selection, and breeding-oriented resource utilization. Full article

Background: This study examined associations between C-reactive protein (CRP), interleukin-6 (IL-6), ordinal procalcitonin (PCT) categories, and delirium severity in critically ill adults. Secondary exploratory analyses evaluated whether baseline CRP and IL-6 discriminated subsequent incident delirium and remained associated with this outcome after adjustment. Methods: This prospective observational cohort included 267 adults treated in a general intensive care unit. Delirium severity was assessed using CAM-ICU-7 at 12 h after admission and on days 2, 4, 7, and 14. CRP and IL-6 were analyzed as continuous variables, whereas PCT was analyzed as a three-level ordinal variable across all five assessment times. Associations with delirium severity and intensive care unit length of stay were evaluated using Spearman rank correlations. Among patients without delirium at 12 h, bootstrap receiver operating characteristic analysis and Firth-penalized logistic regression adjusted for age and sex were performed as secondary exploratory analyses. PCT was not included in these prospective analyses because only ordinal PCT categories were available. Results: Delirium was recorded at least once in 38 of 267 patients (14.2%). Thirteen patients had delirium at 12 h, and 25 additional patients subsequently developed incident delirium. Concurrent correlations with CAM-ICU-7 severity ranged from 0.271 to 0.898 for CRP and from 0.312 to 0.735 for IL-6. Concurrent correlations for ordinal PCT categories were 0.304, 0.666, 0.711, 0.720, and 0.329 at the five respective assessment times. All concurrent associations were positive and statistically significant at p < 0.001. PCT categories also showed weak positive correlations with intensive care unit length of stay, with coefficients ranging from 0.151 to 0.281. Among 254 patients without delirium at 12 h, baseline CRP showed an AUC of 0.969 (95% bootstrap CI, 0.923 to 0.997), compared with an AUC of 0.653 (95% bootstrap CI, 0.569 to 0.750) for IL-6. Both baseline CRP concentrations and incident delirium were concentrated at floor values in most patients, and this discrimination should be read accordingly as a largely binary separation between floored and elevated CRP rather than a graded biomarker-severity gradient. In the joint Firth model, CRP remained associated with incident delirium, with an adjusted odds ratio of 10.75 per 5 mg/L increase, 95% confidence interval 4.50 to 33.18, p < 0.001. IL-6 was not associated with incident delirium after adjustment for CRP, age, and sex, with an adjusted odds ratio of 0.81 per 5 pg/mL increase, 95% confidence interval 0.42 to 2.04, p = 0.510. Conclusions: CRP, IL-6, and ordinal PCT categories were positively associated with concurrent delirium severity, although no consistent biomarker hierarchy was observed across assessment times. In secondary exploratory analyses, baseline CRP showed high apparent within-sample discrimination for subsequent incident delirium and remained associated with the outcome after adjustment for IL-6, age, and sex. However, the cutoff, discrimination, and effect estimates were derived from a single-center cohort with only 25 incident events. Model calibration, optimism-corrected performance, net clinical benefit, and clinical utility were not evaluated. These findings should not be interpreted as establishing a diagnostic test or clinical prediction tool and require validation in independent external cohorts before any clinical application. Full article

Background/Objectives: Filipino Americans are one of the least likely Asian American subgroups to use formal mental health services, even when mental health needs are present. This study used the Capability–Opportunity–Motivation–Behavior (COM-B) framework to examine mental health symptomatology, perceived social support, help-seeking intentions, and perceived barriers to mental health treatment among Filipino American older adults residing in the United States. Methods: We used a cross-sectional descriptive correlational design. A sample of 100 Filipino American older adults completed the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, an 8-item subset of the Multidimensional Scale of Perceived Social Support, the Mental Health Seeking Intention Scale, and the Perceived Barriers to Psychological Treatment scale. We performed descriptive statistics and correlation analyses using Pearson’s and Spearman’s coefficients. Results: Participants experienced low levels of depressive symptoms (M = 2.73, SD = 4.80) and anxiety symptoms (M = 2.56, SD = 4.11), high perceived social support (M = 5.32, SD = 1.83), moderate help-seeking intentions (M = 4.90, SD = 2.18), low overall perceived barriers to care (M = 1.67, SD = 0.90), and nearly universal health insurance coverage. Of the barrier domains, stigma/interpersonal barriers had the highest mean scores. Greater depressive and anxiety symptom severity was associated with higher overall perceived barriers to mental health care (r = 0.45–0.47) and with higher structural, motivational, and stigma/interpersonal barriers (r = 0.41–0.46). Conclusions: Despite high healthcare access and strong perceived social support, Filipino American older adults expressed only moderate intentions to seek professional mental health care. Culturally mediated factors may shape mental health help-seeking beyond structural barriers to access. The COM-B framework offers a useful lens for understanding help-seeking behavior and guiding culturally responsive interventions with Filipino American older adults. Full article

Background/Objectives: Time perspective and resilience are both relevant to adolescent mental health, yet their association has rarely been examined in clinical adolescent populations. This study investigated associations between resilience and time perspective and tested their independent associations with depressive, anxiety, and PTSD symptoms beyond trauma-related variables. Methods: A total of 105 adolescents aged 14 to 20 years were recruited from a child and adolescent psychiatric outpatient department. Participants completed self-report measures of resilience, time perspective, trauma exposure, and PTSD, depressive, and anxiety symptoms. Discrepancy from the optimal balanced time-perspective profile was quantified using the revised Deviation from a Balanced Time Perspective coefficient (DBTP-r). Spearman correlations and linear regression models were computed using DBTP-r alone, DBTP-r plus resilience, and extended models including trauma-related variables. Results: Higher DBTP-r was associated with lower resilience. Higher resilience was associated with higher Future and Past Positive scores and lower Past Negative scores. DBTP-r accounted for substantial variance in symptom severity. When resilience was added, both DBTP-r and resilience were independently associated with depressive, anxiety, and PTSD symptoms. In the extended models, DBTP-r and resilience remained significant for all three outcomes. Of the trauma-related predictors, physical sexual abuse was associated with PTSD symptoms in the extended model, but this association was no longer significant after controlling for biological sex. The cumulative number of other potentially traumatic experiences was not independently associated with symptom severity in the extended models. Conclusions: Time perspective and resilience appear to be related but distinguishable constructs. Both were independently associated with symptom levels of depression, anxiety, and PTSD in adolescents. Full article

Background/Objectives: Femicide-related orphanhood exposes children and adolescents to psychological distress and may disrupt their health-related quality of life (HRQoL). This study examined the relationships between anxiety, depression, and HRQoL among children and adolescents orphaned by femicide and tested whether depressive symptoms mediate the association between anxiety and HRQoL. Methods: A cross-sectional study was conducted with 57 children and adolescents aged 8 to 18 years who had been orphaned by femicide and were residing in the Federal District of Brazil. Participants completed the Revised Child Anxiety and Depression Scale (RCADS-25) to assess anxiety and depressive symptoms and the KIDSCREEN-27 to evaluate HRQoL. Data were analyzed using Spearman correlation coefficients, linear regression models with bootstrap procedures, and mediation analyses to explore direct and indirect relationships among variables. Results: Depressive symptoms were negatively associated with HRQoL, while anxiety symptoms showed a weaker negative association with HRQoL. In the regression analysis, depression emerged as the only significant predictor of HRQoL. Mediation analysis indicated that the relationship between anxiety and HRQoL was largely explained by depressive symptoms, suggesting a partial indirect effect of anxiety through depression. Conclusions: The findings indicate that depressive symptoms may play a central role in the relationship between anxiety and perceived quality of life among children and adolescents orphaned by femicide. These results highlight the importance of assessing both anxiety and depression in this population and suggest that interventions addressing depressive symptomatology may contribute to improving psychosocial well-being and HRQoL following exposure to severe family violence. Full article

Background/Objectives: Aging is associated with physiological changes that impair thermoregulation and may increase vulnerability to thermal stress. Body composition, particularly adiposity and skeletal muscle mass, may influence skin temperature distribution and thermographic asymmetry; however, evidence in older adults remains limited. This study aimed to characterize thermographic asymmetry patterns in older adults and examine their association with body composition parameters potentially influencing thermoregulatory function during aging. Methods: A cross-sectional study was conducted in 127 community-dwelling older adults from Burgos, Spain. Body composition was assessed using multi-frequency bioelectrical impedance analysis (InBody S10), including the body fat percentage (PBF), appendicular skeletal muscle mass index (ASMI), phase angle, and extracellular water-to-total body water ratio (ECW/TBW). Infrared thermography was performed using an FLIR E6390 thermal camera (FLIR Systems Inc., Wilsonville, OR, USA), and thermographic images were analyzed with ThermoHuman software version 3.0. Variables included global temperature, trunk thermal asymmetry, upper-limb thermal asymmetry, mean absolute thermal asymmetry, the Thermal Recovery Index (TRI), and the Symmetry Assessment Parameter (SAP). Sex differences, Spearman correlations, and multiple linear regression analyses were performed. Results: Women presented significantly higher body fat percentage and greater thermographic asymmetry than men (p < 0.05). Body fat percentage was positively associated with upper-limb thermal asymmetry (ρ = 0.229, p = 0.015), mean absolute thermal asymmetry (ρ = 0.280, p = 0.003), TRI (ρ = 0.250, p = 0.008), and SAP (ρ = 0.276, p = 0.003). In contrast, the ASMI, phase angle, and ECW/TBW ratio showed no significant associations with thermographic asymmetry indices. In the adjusted regression analysis, body fat percentage showed a statistically significant coefficient for mean absolute thermal asymmetry; however, the overall model was not statistically significant and explained only 5% of the variance (R² = 0.050, p = 0.144). Conclusions: Body fat percentage showed modest associations with several thermographic asymmetry parameters, whereas skeletal muscle mass showed limited relationships with thermographic outcomes. Given the weak magnitude of the correlations and the limited explanatory capacity of the regression model, these findings should be considered exploratory. Body composition may represent one of several factors associated with thermographic variability in older adults. Full article

The Phenylalanine Hydroxylase Gene Locus-Specific Database and BIOPKU are public databases used to track genotypes in hyperphenylalaninemia. However, the rapidly expanding databases and evolving nomenclature standards require a comprehensive characterization of the current variant landscape. We performed a descriptive statistical analysis of PAH variant allocations, allele frequencies (AF%), and phenotypic annotations using PAHvdb database. Over the period 2022–2026, the PAHvdb expanded by 169.26%. Of the 3409 variants studied, 75.68% of the phenotypes were not assigned. Splicing-related mutations comprised approximately 4.37% of the database, with classic phenylketonuria phenotypes represented in both donor–acceptor and splice-region categories. Only 3.84% of the variants had enzymatic activity (EA%) data, which offer the most direct biochemical evidence for genotype–phenotype inference. The strong Spearman’s rank correlation coefficient (ρ) between EA% and APV (ρ = 0.745, p < 0.001) was consistent with the established relationship between residual PAH EA% and the severity of metabolic phenotype. The AF% distribution was markedly asymmetric and dominated by a small number of alleles that were most frequently reported in the database. These findings highlight the increasing clinical reliance on these databases. Our analysis highlights a heterogeneity of rare, uncharacterized variants of uncertain significance and underscores the need for unified, systematic reviews to standardize nomenclature and resolve phenotype–genotype discrepancies. Full article