Search Results (7,720)

Background: Multimorbidity frequently involves overlapping neuro-psychic, cardiometabolic, and renal disturbances, yet clinical assessment often relies on diagnosis-based comorbidity counts that may not fully capture cumulative physiological stress. We developed the Neuro–Cardio–Renal Stress Index (NCR-SI) as a pragmatic composite framework to describe multisystem burden using routinely available clinical data. Methods: This cross-sectional study analyzed electronic medical record data from adult patients with chronic conditions. NCR-SI integrates three domains: neuro-psychic burden (text-derived indicators and psychotropic medication use), cardiometabolic stress (triglyceride–glucose index and cardiometabolic diagnoses), and renal function (MDRD-estimated eGFR staging). Importantly, this study is not intended to demonstrate incremental predictive value over individual components or established comorbidity indices. Rather, it presents NCR-SI as a transparent, domain-based descriptive framework and reports its internal coherence and distribution across clinically recognizable multimorbidity contexts. Results: A total of 148 patient records were screened; 143 patients met complete-case criteria and were included in the main NCR-SI analyses. NCR-SI ranged from 0 to 10 (median 5). Higher scores were observed in renometabolic profiles. NCR-SI showed expected structural associations with declining renal function (eGFR; ρ ≈ −0.71), moderately with the TyG index (ρ ≈ 0.42), and weakly with medication burden. Correlation with age-adjusted CCI was minimal (ρ ≈ 0.09), indicating limited overlap with diagnosis-based comorbidity counts. Domain-specific correlations were consistent with predefined score construction rules, particularly between the renal domain and eGFR, and between the cardiometabolic domain and TyG. Conclusions: NCR-SI provides a pragmatic, integrative descriptor of neuro-cardio-renal stress using routinely collected clinical data. Rather than replacing established comorbidity indices, NCR-SI may complement them by summarizing multidimensional physiological burden patterns. NCR-SI is proposed as a research-oriented, hypothesis-generating descriptive framework. External validation in independent cohorts and longitudinal evaluation against clinically meaningful outcomes (e.g., hospitalization, mortality, functional status, healthcare utilization) are required before any claims of clinical performance can be made. Full article

Background/Objectives: Sex estimation from craniofacial morphology is a fundamental component of biological profile construction in forensic anthropology. Population-specific reference data for Thai individuals derived from computed tomography (CT) remain limited, and direct comparisons between discriminant function analysis (DFA) and machine learning classifiers are frequently complicated by inconsistent validation protocols. This study aimed to characterize sexual dimorphism in CT-derived craniofacial measurements, compare the classification performance of DFA, support vector machine (SVM), and random forest (RF) under a unified validation protocol, and demonstrate their practical application in a forensic context. Methods: CT images from 300 Thai adults (150 males, 150 females; age range 20–90 years) were obtained from Srinagarind Hospital, Khon Kaen University. Eight linear craniofacial measurements spanning the cranial vault, facial skeleton, nasal aperture, and orbital region were obtained from each case. DFA, SVM, and RF were developed and compared under a unified leave-one-out cross-validation protocol. Classification performance was assessed using accuracy, AUC, and Matthews correlation coefficient (MCC). Results: Seven of eight measurements exhibited statistically significant sexual dimorphism, with facial breadth and nasal height demonstrating the greatest dimorphism. DFA achieved the highest classification accuracy of 85.7%, AUC of 0.924, and MCC of 0.713, incorporating five measurements into the canonical function. SVM and RF achieved comparable accuracy of 84.7% and 84.0%, respectively. All three classifiers correctly classified both forensic application cases with high confidence. Conclusions: CT-derived craniofacial measurements provide a reliable basis for sex estimation in Thai adults. The convergence of performance across all three classifiers under a unified internal validation protocol strengthens confidence in the internally validated performance estimates. The derived discriminant function equation and saved machine learning models constitute a complementary and immediately applicable toolkit for CT-based forensic sex estimation in the Thai population. Full article

The role of amino acid disturbances in the mother–fetus system remains poorly understood, despite their critical involvement in gestational diabetes mellitus (GDM), fetal macrosomia (FM) and offspring metabolic programming. This study included 62 mother–newborn dyads stratified by GDM and FM status. An analysis of the association of amino acids with clinical parameters was performed using the Spearman test. Amino acid markers of GDM were identified using the mutual information index and the Mann–Whitney test. A random forest method was used to identify amino acid markers, with the SHAP value used to estimate the contribution of each amino acid. In maternal serum, GDM was associated with significantly lower levels of glycine, 1-methylhistidine, γ-aminobutyric acid, lysine, and tryptophan. Umbilical cord serum from GDM pregnancies showed reduced concentrations of glutamine, glycine, asparagine, methionine, and proline. In amniotic fluid, GDM with FM was characterized by elevated lysine and 1-methylhistidine. Cord blood exhibited increased lysine, proline, leucine, and allo-isoleucine, while amniotic fluid showed low homocitrulline, asparagine, and lysine, together with high histidine. Fetal weight correlated directory with lysine and isoleucine and inversely with homocitrulline. Pathway analysis linked maternal serum markers to disturbances in biotin, glutamate, and carnitine metabolism, whereas cord blood markers involved broader alterations in amino acid, purine, and amino sugar metabolism. In amniotic fluid from GDM with FM, the methylhistidine pathway was specifically enriched, suggesting changes in neonatal muscle protein turnover. GDM induces distinct alterations in the amino acid profiles of all three compartments, and the combination with FM yields unique metabolic signatures. These findings identify candidate biomarkers for prediction of GDM and its complications and point to potential targets for metabolic intervention. Full article

Background: Diabetic nephropathy (DN), also referred to as diabetic kidney disease, represents one of the most common microvascular complications of type 2 diabetes mellitus (T2DM) and remains a leading cause of end-stage renal disease worldwide. Conventional clinical markers, including albuminuria and estimated glomerular filtration rate (eGFR), are widely used for diagnosis and staging but may have limited sensitivity for detecting early renal injury and predicting disease progression. In recent years, circulating microRNAs (miRNAs) have emerged as promising non-invasive biomarkers that reflect underlying molecular mechanisms of diabetic nephropathy and may complement traditional clinical indicators. Objective: The present study aimed to evaluate serum and urinary levels of hsa-miRNA-770-5p across different stages of diabetic nephropathy and to assess its potential diagnostic value in relation to established indicators of renal function. Methods: A total of 257 participants were included and divided into four groups: healthy controls, patients with T2DM without nephropathy, patients with T2DM and DN in CKD stages I–II, and patients with DN undergoing maintenance hemodialysis (MHD). Serum and urinary levels of miRNA-770-5p were measured using quantitative real-time polymerase chain reaction (qPCR) and analyzed using the 2^−ΔΔCt method. Statistical analyses included comparisons between groups using ANOVA, correlation analyses with renal function parameters such as eGFR and proteinuria/albuminuria, and receiver operating characteristic (ROC) curve analysis to evaluate diagnostic performance. Results: Serum levels of miRNA-770-5p were significantly elevated in patients with DN and in patients undergoing maintenance hemodialysis compared with healthy controls and patients with T2DM without nephropathy. In contrast, urinary levels of miRNA-770-5p were markedly reduced in patients with DN. Serum levels in patients with T2DM without nephropathy were slightly lower than those observed in healthy controls. Significant correlations were identified between miRNA-770-5p levels and renal function parameters, including eGFR and proteinuria/albuminuria, supporting the biological relevance of this microRNA in renal injury. ROC curve analysis demonstrated good discriminatory ability for differentiating DN from T2DM without nephropathy (serum AUC = 0.82; urine AUC = 0.79). Conclusions: hsa-miRNA-770-5p demonstrates distinct and opposite patterns in serum and urine that correlate with the severity of diabetic nephropathy. The complementary changes observed in circulating and urinary levels support the potential of miRNA-770-5p as a non-invasive biomarker that may complement conventional clinical markers and provide additional insight into the molecular mechanisms involved in the development and progression of diabetic nephropathy. Full article

Background: Adolescent insomnia is a public health concern associated with affective disturbances, poor academic performance, and cardiometabolic risk. In Peru, nighttime screen use, psychosocial stressors, and social inequalities intensify its impact; however, brief, validated screening instruments remain limited. Objective: To translate, culturally adapt, and evaluate the psychometric properties of the Youth Self-rated Insomnia Scale (YSIS) in Peruvian adolescents, examining its internal structure, reliability, and invariance across sex. Methods: An instrumental study was conducted with 300 students aged 13 to 17 years (M = 15.02; SD = 1.07). Descriptive statistics were calculated, and confirmatory factor analysis (CFA) was performed using a robust estimator. Reliability was assessed through Cronbach’s alpha (α), McDonald’s omega (ω), and average variance extracted (AVE). Factorial invariance by sex was examined at the configural, metric, scalar, and strict levels. Results: The unidimensional model demonstrated adequate fit (χ² = 44.55, df = 18, p < 0.001; CFI = 0.97; TLI = 0.95; RMSEA = 0.07; SRMR = 0.04), with factor loadings ranging from 0.47 to 0.76, high internal consistency (α = 0.86; ω = 0.81), and AVE = 0.51. Although the two-factor model showed acceptable global fit indices, it revealed insufficient AVE in one factor (AVE = 0.40) and a high inter-factor correlation (r = 0.93), suggesting a lack of discriminant validity. Factorial invariance across sex was supported at all evaluated levels. Conclusions: The Spanish version of the YSIS demonstrates a unidimensional structure, adequate internal consistency, and factorial invariance across sex, supporting its use as a brief screening tool in clinical and school settings, as well as in epidemiological studies among Peruvian and Latin American adolescents. Full article

Background: The evaluation of renal function in neonates is challenging due to maternal creatinine transfer, reduced muscle mass, and non-steady-state physiology. Cystatin C emerged as a promising biomarker for assessing neonatal glomerular filtration rate. This review summarizes evidence from studies evaluating serum and urine cystatin C in healthy neonates and high-risk groups, including preterm newborns, neonates with acute kidney injury, and those with congenital kidney and urinary tract defects. Methods: Twenty studies were included and qualitatively synthesized following PRISMA guidelines. Results: In the included studies, serum cystatin C exhibited consistent postnatal patterns independent of maternal influence and showed a strong correlation with gestational age and renal development. Cystatin C enabled earlier detection of renal dysfunction compared to serum creatinine, especially in preterm infants and critically ill neonates. In babies with congenital renal abnormalities, cystatin C levels were associated with disease severity and clinical outcomes, while the cystatin C-based estimated glomerular filtration rate surpassed creatinine-based estimations. Urinary cystatin C correlated with tubular damage and increased risk of chronic kidney disease during follow-up. Conclusions: Cystatin C is a reliable biomarker for evaluating neonatal renal function, although further standardization and validation are required for clinical implementation. Full article

Background: Epidural procedures benefit from a pre-procedural informed estimation of epidural depth, as anticipating the approximate distance can support safer needle placement and reduce technical difficulties during analgesia or anesthesia procedures. The influence of ethnicity has been established across different populations worldwide; however, there is a lack of Saudi-specific MRI data on epidural depth among the adult population. Aim of this Study: To measure the skin to epidural space distance (SED) at the lumbar interspaces L3–L4 and L4–L5 in the Saudi adult population using magnetic resonance imaging (MRI) and to examine its correlations with age, sex, height, weight, and body mass index (BMI). Methods: In this retrospective cross-sectional study, sagittal T1-weighted lumbar MRI images of the spine of 169 adult Saudi patients were studied. The age group ranged from 20 to 70 years, with an equal distribution of males and females. The skin to epidural space distance (SED) was measured at the L3–L4 and L4–L5 interspaces, and its correlations with age, sex, height, weight, and BMI were analyzed. Results: The average measurement of skin to epidural space distance (SED) was 59.08 mm in L3–L4, and 63.21 in L4–L5. BMI and weight showed strong positive correlations with SED across both levels. Female sex was associated with longer SED values at L4–L5. There was no significant correlation between SED and age or height of the patients. Conclusions: MRI-based assessment of SED revealed strong correlations with weight and BMI, but no correlation with height, age, and sex. These findings support the individualized estimation of epidural depth and needle length selection to enhance procedural safety and reduce complications. Full article

Saudi Arabia experienced rapid convergence in women’s financial inclusion between 2014 and 2024, a period marked by the 2018–2019 reforms expanding women’s economic rights and the accelerated deployment of digital payment infrastructure. Using four waves of Global Findex microdata (2014, 2017, 2021, and 2024), this study estimates probability-weighted logit models with average marginal effects and decomposes gender gaps using nonlinear Kitagawa and Blinder–Oaxaca methods. Reform-era dynamics are examined by tracing changes in the gender gap across survey waves. The findings indicate that aggregate gender gaps in account ownership and digital payment usage narrowed substantially by 2024, with conditional gaps among employed adults no longer statistically significant, while sizable disparities persist among individuals outside the workforce. Decomposition results highlight increased female labor force participation as a key correlate of convergence, consistent with labor market integration playing a central role in women’s financial inclusion during the reform era. Full article

Background: Wearable sensors have gained increasing popularity as an objective method for remotely monitoring infant movement in naturalistic settings. Over the first year of life, infants generate a wide range of motions, from goal-directed to spontaneous movement. These include linear movements, such as kicks, and orientation changes, such as postural transitions. Many sensor processing pipelines emphasize capturing linear movements through movement-generated acceleration while focusing less on information about orientation embedded in the gravitational part of the data. Here, we introduce a complementary gravity-referenced approach that extracts the gravitational component of accelerometer signals to estimate limb orientation, extending the reliable quantification of rich and detailed aspects of infant movement. Infant orientation has demonstrated clinical relevance, including associations with later neuromotor outcomes, and it can be used to chart infant motor development, motivating the development of objective methods to quantify orientation from sensor data. Methods: Wearable sensors (Opal APDM) were used to longitudinally evaluate infant motor activity recorded in sessions conducted at 3, 6, 9, and 12 months of age. We extracted data from a 5 min segment that has simultaneous video recordings. From these datasets, applying the gravity-referenced method, we computed pitch, roll, and yaw, angles that collectively describe limb orientation. We then quantified orientation variability using axis-specific circular standard deviations (SDs) for pitch, roll, and yaw and a multi-axis composite measure based on generalized variance. Results: Axis-specific circular SDs for pitch, roll, and yaw, as well as the composite generalized variance, increased significantly from 3 to 12 months (p ≤ 0.01 for each metric). Composite variability was strongly associated with Mullen gross motor outcomes at 9 and 12 months of age (r = 0.55, p < 0.001). Conclusions: Overall, gravity-referenced pitch, roll, and yaw provide rich orientation features that increased as infants develop more postural transitions. Furthermore, the orientation features correlated with standardized measures of infant motor function. These orientation metrics can complement traditional linear kinematic measures and improve our ability to granularly track infant motor development in the first year of life. Full article

Background: While human cranial sutures are well-established indicators for age-at-death estimation in forensic anthropology, facial sutures remain an underutilized resource despite their critical role in facial growth and development. Macroscopic examination of craniofacial suture closure patterns reflects physiological aging processes and can provide valuable information at crime scenes. This study aimed to address the gap of knowledge by quantitatively evaluating the efficacy of facial suture closure patterns for age estimation. Methods: A sample consisting of 296 Thai skulls was analyzed to assess facial suture closure based on anatomical morphology. The sutures were evaluated using various established classification systems to determine the most effective method for predicting age ranges. To ensure consistency and reliability, the evaluations were conducted by three independent raters. Results: The assessment demonstrated good Intraclass Correlation (ICC = 0.755, df = 14, p < 0.05). Among the classification methods tested, the Modified Meindl and Lovejoy Scoring System yielded the highest sensitivity, ranging from 90.9% to 100% in males and 75.4% to 96.1% in females. Specifically, the zygomaticomaxillary suture showed the highest sensitivity in males, whereas the frontonasal and sphenozygomatic sutures were the most sensitive indicators in females. Utilizing the total sum score (TSS), the following sex-specific linear regression formulas for age-at-death were generated: (Males: Age-at-death = 1.7625(TSS) − 17.094. Females: Age-at-death = 1.7325(TSS) − 12.865). Conclusions: Facial sutures exhibit distinct, sex-specific closure patterns that serve as robust and reliable indicators for estimating age, with higher sensitivity generally observed in males. The utility of this novel method is heavily dependent on the scoring system employed, highlighting the critical importance of utilizing modified, sex-specific analyses. While these population-specific models tailored to the Thai demographic effectively refine age estimation outcomes, integrating this methodology with broader biological profiling remains essential for high-confidence forensic identification. Full article

Short-term facial landmark forecasting is important for anticipatory facial behavior in human–robot interaction, yet models trained with pointwise reconstruction losses often suffer from mean reversion, producing low-error predictions with weakened motion dynamics. To address this issue, we propose a peak-aware gated recurrent unit (GRU) framework that separates forecasting into peak planning and peak-conditioned trajectory generation. The planning stage estimates the timing and intensity of a salient motion peak within the forecast horizon together with a global motion direction, and the generation stage produces short-horizon landmark displacements through temporal gating and structured motion composition. The model is trained with reconstruction loss, peak supervision, peak-integrity regularization, and correlation-based temporal-shape regularization. Experiments on the MEAD dataset using 3D facial landmarks under a subject-independent protocol show a clear distortion–dynamics trade-off. Compared with static and sequence-to-sequence baselines, the proposed method better preserves peak-related facial dynamics while maintaining competitive 24-step prediction accuracy. Full article

The COVID-19 pandemic caused stark global mortality disparities, influenced by a complex interplay of demographic, economic, and health factors. This ecological study investigates associations between country macroscopic variables and COVID-19 accumulated mortality ratio (AMR) across 174 countries and may serve as a preparation for new pandemics. Methods: The study applies bidirectional stepwise multiple linear regression. To ensure statistical validity, we conducted diagnostic tests for multicollinearity and heteroscedasticity, applying robust M-estimation where necessary to minimize root mean squared error. The analysis covered six distinct stratifications based on development status (developed, developing, least developed, and combinations), and incorporated temporal analyses across three specific annual periods: 21 January 2020–20 January 2021; 21 January 2021–20 January 2022; and 21 January 2022–10 January 2023. Data: AMR per country values, accumulated between 21 January 2020 and 10 January 2023, and data on the prevalence of health conditions, and socioeconomic descriptive variables were extracted from Our World in Data (OWID) and other public data sites, like the World Bank. Results: The percentage of population aged over 65 years has the most consistent association with increased AMR globally. Obesity prevalence and income inequality (Gini index) were positively associated with AMR regardless of country development status. Conversely, the study finds a consistent negative correlation with diabetes prevalence, while the prevalence of respiratory diseases is a significant association only for developed nations. Socioeconomic factors were significantly associated with AMR, but this influence is stronger in developed countries than in the developing and least developed countries. Conclusions: While population aging is the primary association with increased AMR, the mortality impact of comorbidities and socioeconomic factors is heavily conditioned by a country’s development stage, pointing to the necessity of development-status-aware public health strategies for incoming pandemics. Full article

Real-time coal–rock identification is essential for intelligent mining, enabling hazard prevention and geological modeling. However, existing methods often suffer from unclear bit–rock interaction mechanisms, signal distortion, sensor remoteness, or delayed data acquisition, limiting their effectiveness in continuous operations. This study proposes a novel approach for real-time coal–rock identification based on multi-source near-bit drilling data. A near-bit data acquisition system was developed and positioned directly behind the drill bit, integrating sensors to capture high-fidelity parameters—including weight on bit (WOB), torque, rotational speed, rate of penetration (ROP), natural gamma ray, and borehole trajectory—thereby eliminating frictional interference from the drill string. A data-driven theoretical model was established to derive a near-bit drillability index (NDI) for rock strength and to correlate gamma ray responses with lithology. Field trials were conducted in a coal mine in northern Shaanxi, involving over 30 boreholes and systematic core validation. The results demonstrate that the method enables continuous, high-resolution identification of coal–rock interfaces and strength variations along the borehole trajectory, with interpreted results aligning well with core logs and achieving approximately 85% accuracy in strength estimation. By ensuring compatibility with conventional drilling rigs and supporting real-time data transmission and 3D geological updating, this study offers a practical and robust technical pathway for achieving geological transparency and real-time steering in underground coal mining. Full article

Background: Erectile dysfunction (ED) is increasingly recognized as an early manifestation of systemic vascular disease and might represent a window for cardiovascular risk assessment. Dynamic penile colour Doppler ultrasound (PCDU) provides quantitative arterial and venous parameters that could reflect subclinical vascular impairment. We investigated the association between PCDU parameters and estimated cardiovascular risk in men with ED. Methods: In this single-center retrospective observational study, 275 men undergoing PCDU for ED were evaluated. Clinical characteristics, biochemical data, and QRISK3 10-year cardiovascular risk scores were collected. Mean peak systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index (RI) were analyzed. Correlation analyses, logistic regression using a QRISK3 ≥ 10% threshold, linear regression models, age-stratified analyses, and receiver operating characteristic (ROC) curve analyses were performed. Results: Patients with impaired PSV (<35 cm/s) were older and exhibited higher QRISK3 scores and a greater prevalence of diabetes mellitus and previous cardiovascular events. Mean PSV was inversely correlated with QRISK3 (r = −0.203, p < 0.01) and was associated with higher cardiovascular risk categories in unadjusted logistic regression (β = −0.016, p = 0.048), but not after adjustment for age and diabetes mellitus. ROC analysis showed modest discrimination of increased cardiovascular risk (AUC = 0.60). The addition of PSV to a model including age and diabetes resulted in minimal improvement in discrimination (AUC 0.966 vs. 0.968). Age-stratified analysis demonstrated a significant association between lower PSV and higher cardiovascular risk only in patients ≤60 years. A progressive increase in QRISK3 was observed according to the number of abnormal Doppler parameters (p = 0.013). Conclusions: PCDU parameters reflect the overall cardiovascular risk burden in men with ED. Although not independent predictors beyond traditional risk factors, penile Doppler abnormalities might identify a vascular phenotype associated with higher estimated cardiovascular risk, particularly in younger individuals. These findings support the role of comprehensive vascular assessment in selected patients with ED. Full article

Leaf Area Index (LAI) is a fundamental parameter for characterizing the growth of tea (Camellia sinensis L.). However, in rugged mountainous regions, the combined effects of topographic relief and canopy structural heterogeneity severely constrain the accuracy of UAV-based multispectral LAI retrieval. This study develops an integrated framework combining topographic correction with interpretable machine learning to improve LAI estimation. We utilized a UAV multispectral dataset collected during the peak growing season from a typical tea-growing region in Fujian Province, China (altitude range: 58–186 m), comprising a total of 90 samples. Three topographic correction methods, including Sun–Canopy–Sensor (SCS), SCS with C correction (SCS+C), and Minnaert+SCS, were evaluated in combination with Linear Regression (LR), Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) models. Results indicated that the SCS+C algorithm outperformed other methods by effectively accounting for direct and diffuse radiation components, thereby reducing topographic dependence while maintaining radiometric consistency across heterogeneous surfaces. The XGBoost model combined with SCS+C correction achieved the highest performance (R² = 0.8930, RMSE = 0.6676, nRMSE = 7.93%, MAE = 0.4936, Bias = −0.0836). SHapley Additive exPlanations (SHAP) analysis revealed a structure-dominated retrieval mechanism, in which red-band textural features (Correlation_R) exhibited higher importance than conventional vegetation indices. Compared with previous studies that primarily focus on either topographic correction or model development, this study provides quantitative insights into the underlying retrieval mechanisms. This framework improves the precision of tea LAI retrieval in complex terrains and provides a robust methodological basis for digital management in mountainous agriculture. Full article