Search Results (1,947)

Background and Objectives: Soft denture lining materials improve stress distribution and patient comfort but can lose mechanical stability under routine chemical cleansing. This study aimed to evaluate the time-dependent effects of two alkaline peroxide-based denture cleansing tablets (i.e., Efferdent and Protefix) on Shore A hardness and weight change of three soft lining materials (i.e., Ufi Gel P, Ufi Gel SC, and Visco-gel) at days 1, 7, and 30. Materials and Methods: Ninety specimens (n = 10/group) were assigned to a 3 × 3 factorial design. Specimens were immersed in cleansing solutions for 8 h daily and stored in artificial saliva for 16 h; controls remained solely in artificial saliva. Shore A hardness was measured using a durometer, and weight was recorded with a precision scale. Data were analyzed by mixed-design ANOVA and linear regression (α = 0.05). Results: Material type significantly affected hardness and weight change (p < 0.001). Visco-gel showed a marked increase in Shore A hardness (from about 15–16 to 26–27 HA) and greater weight loss (approximately 0.04–0.06 g), whereas silicone-based materials (Ufi Gel P and Ufi Gel SC) demonstrated more stable hardness values (from about 24–25 to 31–32 HA) with minimal weight variation (generally below about 0.02 g). The type of cleansing tablet had a smaller but significant effect (p = 0.004), with Protefix causing greater alterations. Weight change was negatively correlated with hardness increase (R² = 0.33, p < 0.001). Conclusions: Within the limitations of this in vitro study, material composition was identified as the main determinant of degradation resistance, with silicone-based liners demonstrating greater durability under the tested conditions, while Efferdent may be considered a milder option for long-term cleansing. Full article

Phthalates (PAEs) are ubiquitous endocrine-disrupting chemicals (EDCs), but their association with early pregnancy loss (gestational age ≤ 12 weeks) remains controversial. This study enrolled pregnant women aged 20–45 years in Zunyi City, China, and included 107 cases and 349 controls following propensity score matching. Logistic regression, restricted cubic spline (RCS) analysis, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression were employed to investigate associations between urinary phthalate metabolites and early pregnancy loss. We found that monoethyl phthalate (MEP), mono(2-ethylhexyl) phthalate (MEHP), monooctyl phthalate (MOP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) were associated with spontaneous abortion in early pregnancy, with corresponding odds ratios (ORs; 95% confidence intervals [CIs]) of 1.62 (1.26–2.09), 1.49 (1.07–2.09), 1.64 (1.26–2.12), 1.78 (1.27–2.50), 2.63 (1.90–3.64), 1.41 (1.11–1.79), and 5.39 (3.53–8.25). Non-linear dose–response relationships were observed between exposure to MMP, MEP, MEHP, MOP, monobenzyl phthalate (MBZP), MEOHP, MEHHP, and mono-(3-carboxypropyl) phthalate (MECPP) and early pregnancy loss (non-linear p < 0.05; overall p < 0.05). Co-exposure to multiple phthalate metabolites was also linked to a significantly non-linear elevation in the risk of early pregnancy loss (OR; 95% confidence interval [CI]) of 1.92 (1.76–2.15). Among these metabolites, MMP, MOP, MEOHP, and MECPP make the largest contribution to the correlation. In summary, our findings indicate that exposure to phthalate esters during early pregnancy is associated with early pregnancy loss, with MMP, MOP, MEOHP, and MECPP as the primary contributors. However, these results are based on a single urine sample, and caution is warranted when interpreting the findings. Full article

Extreme precipitation constitutes one of the most devastating climatic resulting from global climate change. Jilin Province, a significant commodities grain base in China by a temperate monsoon climate, is particularly susceptible to flood disasters caused by extreme precipitation, usually occurring from late July to early August. The 2010 flood impacted moreover 5.12 million individuals and resulted in direct economic damages amounting to 45.1 billion CNY. However, research on the spatiotemporal characteristics and future trends of extreme precipitation in Jilin Province is still quite inadequate. This study examined the spatiotemporal distribution and future forecasts of extreme precipitation utilizing daily meteorological data from 31 stations (1960–2019) and three CMIP6 models (CanESM5, MPI-ESM1-2-HR, FGOALS-g3) under SSP2-4.5 and SSP5-8.5 scenarios. Eleven extreme precipitation indices, as specified by the WMO, were analyzed utilizing linear regression, the Mann–Kendall test, wavelet analysis, and inverse distance weighting interpolation. The findings indicated that from 1960 to 2019, extreme precipitation demonstrated traits of “increased frequency and total amount, decreased intensity”, with a significant decline in CDD (−2.184 d·(10a)⁻¹, p < 0.001), a notable increase in PRCPTOT (1.493 mm·(10a)⁻¹, p < 0.05), and a significant reduction in SD II (−0.016 mm·d⁻¹·(10a)⁻¹, p < 0.01). The majority of indicators had a predominant cycle of 30 to 50 years. A significant northwest-to-southeast gradient characterized most indicators, with PRCPTOT varying from 327.5 mm in Baicheng to 824.3 mm in Tonghua. Future projections (2025–2100) suggested scenario-dependent intensification. Under SSP5-8.5, all three models forecast substantial increases in precipitation amount indices (PRCPTOT: 2.071–2.457 mm·(10a)⁻¹) and SD II (0.010–0.013 mm·d⁻¹·(10a)⁻¹), reversing the past downward trend in intensity. The anticipated alterations exhibited a northwest-to-southeast gradient, with PRCPTOT increases above 230 mm in the central and southeastern regions. These findings offer a scientific basis for flood management and climate change adaptation in Jilin Province and analogous areas. Full article

Background/Objectives: This study aims to develop a comprehensive Clinical Decision Support System (CDSS) that integrates multi-sequence sacroiliac joint (SIJ) MRIs with rheumatological, clinical, and laboratory findings into the decision-making process for the early diagnosis of axial spondyloarthritis (axSpA), incorporating segmentation-supported explainability. Methods: Multi-sequence SIJ MRI data (T1-WI, T2-WI, STIR, and PD-WI) were analysed from 367 participants (n = 193 axSpA; n = 174 non-axSpA controls). Sequence-based classification was performed using VGG16, ResNet50, DenseNet121, and InceptionV3 models; additionally, a lightweight and parameter-efficient SacroNet architecture was developed. Slice-level probability scores were converted to patient-level scores using the Dynamic Top-K Averaging method. Image-based scores were combined with a logistic regression-based clinical risk score using weighted linear integration (0.60 image/0.40 clinical) and a conservative threshold (τ = 0.70). Grad-CAM was applied for visual interpretability. Furthermore, to support the diagnostic outcomes with precise spatial data, active inflammation in STIR and T2-WI sequences was segmented. For this purpose, the MDC-UNet model was employed and compared with baseline U-Net derivatives. Results: Sequence-specific analysis showed VGG16 performing best on T1-WI (AUC = 0.920; Accuracy = 0.878) and DenseNet121 on STIR (AUC = 0.793; Accuracy = 0.771). The SacroNet architecture provided competitive classification performance at the patient level despite its low number of parameters (~110 K). Furthermore, MDC-UNet successfully segmented active inflammation, yielding Dice scores of 0.752 (HD95: 19.25) for STIR and 0.682 (HD95: 26.21) for T2-WI. Conclusions: The findings demonstrate that patient-level decision integration based on multi-sequence MRI, when used in conjunction with clinical risk scoring and segmentation-assisted interpretability, can provide a feasible and interpretable DSS framework for the early diagnosis of axSpA. Full article

Industrial volatile organic compound (VOC) emissions from large-scale petroleum storage represent a persistent environmental challenge, particularly in agricultural perimeters where atmospheric “breathing” cycles drive localized soil loading. This study investigates the thermodynamic and spatial relationship between gasoline storage emissions and chemical contamination in the Constanta South terminal area using a multi-layered analytical approach. By integrating gas chromatography (GC-MS) headspace analysis with an artificial intelligence (AI) framework utilizing high-order polynomial regression, we quantified the source–path–receptor dynamics across a thermal gradient (12 °C to 70 °C). The results reveal a non-linear surge in VOC emissions at temperatures exceeding 37 °C, characterized by a shift toward medium-weight hydrocarbons (C4–C6) that act as carriers for heavier aromatics. The AI risk model identified a significant spatial gradient, identifying a 500 m “critical zone” where the Hazard Quotient (HQ) is elevated, necessitating technological upgrades like Vapor Recovery Units (VRUs) to mitigate ecological risks. Full article

This study develops a kinetic model that captures poly-ether-ether-ketone (PEEK) crystallization over a temperature $T$ window from glass transition ($T_g$) to melting ($T_m$) temperature, and across cooling rates from 5 to ~10³ °C/min. The framework is a parallel dual-Nakamura formulation whose isokinetic parameters {$k_i\left(T\right),n_i,w_i\left(T\right)$} are obtained from a bi-level non-linear regression of isothermal crystallization tests conducted using a flash-differential scanning calorimeter (FSC). The weight $w_i\left(T\right)$ partitions the faster primary and slower secondary crystallization and is represented by a physics-based analytical function that captures its dome-shaped temperature dependence. A maximum isothermally achievable enthalpy function is introduced so that the model predicts enthalpy $\Delta H\left(t\right)$ natively under arbitrary thermal profiles. To extend this isothermal backbone to non-isothermal conditions, two explicit cooling-rate-dependent scalars are introduced, $\omega \left(\dot{T}\right)$ and $\chi \left(\dot{T}\right)$, which shift $w_i\left(T\right)$ and limit attainable crystallinity at high cooling rates respectively. Finally, a rate-dependent induction time relation is added to adjust the onset of crystallization. Calibrating these rate functions against non-isothermal experiments, while keeping the isokinetic parameters fixed, yields a single isothermal–non-isothermal model that predicts $\Delta H\left(t\right)$ under arbitrary $T\left(t\right)$ profiles. Model performance is validated using an interrupted FSC experiment with a multi-segment cooling program that mimics a local transient thermal history of PEEK during additive manufacturing. The sample is cooled through successive constant-rate segments with intermittent quench–remelt cycles to probe the accumulated crystallinity along the path. Without additional fitting, the model predicts the measured enthalpy evolution with R² ≈ 0.95. The framework thus provides a practical route for predicting polymer crystallinity under processing-relevant thermal histories. Full article

Background/Objectives: Medial meniscus extrusion (MME) is a quantitative marker of altered meniscal containment and load sharing. Although ultrasonography enables dynamic assessment under functional loading, it remains unclear whether generalized ligamentous hypermobility influences physiologic extrusion behavior in healthy knees. The aim of this study was to quantify load-dependent MME in healthy adults and to determine whether generalized hypermobility is associated with greater physiologic extrusion under progressive loading conditions. Methods: In this prospective observational study, 106 healthy adults aged 18–40 years were evaluated between October and December 2025. Generalized joint hypermobility was defined as a Beighton score ≥5. MME was measured by standardized ultrasonography on the dominant limb in three conditions: sitting (unloaded), bipedal stance, and unipedal stance. Patellar tendon shear-wave elastography (SWE) was recorded in kilopascals (kPa). Interobserver reliability was assessed in the first 25 participants using ICC (2,1). Group comparisons, multivariable linear regression for loading-related Δ-extrusion (Unipedal−Sitting and Bipedal−Sitting), and a linear mixed-effects model for repeated MME measures, including a Position × Hypermobility interaction, were performed. Results: Twenty-eight participants (26.4%) were classified as hypermobile. The hypermobile group showed significantly lower patellar tendon SWE than controls (23.8 ± 7.0 vs. 37.6 ± 9.7 kPa, p < 0.001). MME increased stepwise with loading in both groups and remained consistently higher in hypermobile participants across sitting, bipedal, and unipedal conditions (all p < 0.001). Loading-related extrusion was also greater in the hypermobile group for both Bipedal−Sitting (p = 0.037) and Unipedal−Sitting (p = 0.002). In multivariable regression, lower patellar tendon SWE independently predicted greater loading-related extrusion, whereas hypermobility status did not remain an independent predictor. In the mixed model, the Position × Hypermobility interaction was significant and was most pronounced during the unipedal stance. Conclusions: In healthy adults, medial meniscus extrusion increases stepwise from unloaded sitting to bipedal and unipedal weight bearing. Participants with generalized hypermobility demonstrated higher physiologic MME values and a more pronounced load-dependent pattern, particularly during unipedal stance. However, in adjusted analyses, lower patellar tendon stiffness on SWE, rather than hypermobility status itself, independently predicted greater loading-related extrusion. These findings support a contextual interpretation of ultrasound-based MME measurements in relation to loading condition and hypermobility phenotype. Full article

Accurate prediction of production dynamics in chemical composite cold production (CCCP) for heavy oil reservoirs remains challenging due to complex multi-phase fluid interactions and nonlinear flow regime transitions. Traditional numerical simulations are computationally expensive and rely heavily on detailed geological characterization. To address these limitations, a data-driven predictive framework integrating physical mechanisms with machine learning is proposed. A dual-driven feature selection strategy combining Spearman rank correlation and the Entropy Weight Method (EWM) was applied to quantify nonlinear parameter correlations and data informativeness, identifying injection-production balance and development and maximum adsorption capacity as dominant factors controlling oil production fluctuations. Latin Hypercube Sampling (LHS) was used to construct a representative parameter space, followed by weighted standardization. A Multiple Linear Regression (MLR) model was then trained to jointly predict key production indicators. Field validation shows strong predictive capability, with a coefficient of determination above 0.94 and relative fitting error below 5%. The method reduces computational time by over two orders of magnitude while maintaining high precision. Full article

Background: Clinical remission has become a realistic treatment goal in severe asthma, but current evidence mostly reports global remission rates without accounting for baseline disease burden. No simple tool exists to quantify baseline severity and estimate an individual patient’s probability of achieving remission under biologic therapy. Methods: This prospective observational study included 93 adults with severe asthma initiating tezepelumab across 14 specialised severe asthma units in Spain. Four baseline domains—poor symptom control (ACT < 20), ≥1 severe exacerbation in the previous 12 months, maintenance oral corticosteroid (OCS) use, and FEV₁ < 80% predicted—were used to construct an empirically weighted composite score (Base4Score) based on the inverse probability of correcting each abnormal domain at 12 months. Strict clinical remission at 12 months was defined as ACT ≥ 20, no severe exacerbations, no maintenance OCS, and FEV₁ ≥ 80%. Logistic regression was used to assess the association between the score and non-remission, adjusting for age, sex, smoking status, T2 phenotype, and biologic-naive status. Results: Of 93 treated patients, 81 had complete baseline data for Base4Score derivation and 77 had complete 12-month data for strict clinical remission analysis. Strict clinical remission was achieved in 16/77 patients (20.8%). Remission rates decreased across increasing baseline score strata: 40.0% for scores < 5, 17.6% for scores 5 to <9, and 12.5% for scores ≥ 9 (linear p-trend = 0.022). Each 1-point increase in the continuous Base4Score was associated with higher adjusted odds of non-remission (OR 1.22; 95% CI 1.00–1.49; p = 0.047), and patients with scores ≥ 9 had approximately sevenfold higher adjusted odds of non-remission than those with scores < 5 (OR 6.77; 95% CI 1.40–32.84; p = 0.018). Conclusions: The Base4Score is a simple, empirically derived baseline severity index that predicts 12-month strict clinical remission in severe asthma treated with tezepelumab. If externally validated, it could help personalise expectations, optimise timing of biologic initiation and guide treat-to-target strategies in severe asthma. Full article

This study examines the relationship between digitalisation and eco-innovation across countries, with a particular focus on the role of digital government and digital standardisation. Using cross-country data for 2022, eco-innovation is proxied by environment-related patenting activity, while digitalisation is measured using the United Nations E-Government Development Index (EGDI). Employing a combination of ordinary least squares, population-weighted regressions, spline specifications, and quantile regressions, we document three main findings. First, digitalisation is positively and robustly associated with eco-innovation across countries. Second, the relationship is non-linear, with marginal effects that strengthen at higher levels of digital development, suggesting important complementarities between digital capabilities and national innovation systems. Third, the association between digitalisation and eco-innovation is heterogeneous across the distribution of eco-innovation, with particularly strong associations observed among countries with intermediate levels of innovative activity. Taken together, these findings suggest that digitalisation is systematically associated with eco-innovation across countries and indicate the potential relevance of digital governance and digital standardisation to sustainable technological change. Full article

Background: Hospitalizations for hepatocellular carcinoma (HCC) increasingly reflect a complex interplay among chronic liver disease, cardiometabolic comorbidities, and systemic complications, which now exert greater influence on patient outcomes than tumor-specific factors alone. Despite this shift, contemporary data regarding the impact of the evolving comorbidity burden on inpatient resource utilization and procedural care remain limited. This study examines national trends in inpatient characteristics, procedural utilization, and outcomes among patients hospitalized with HCC between 2018 and 2022. Methods: A retrospective, cross-sectional analysis of adult hospitalizations was performed using the National Inpatient Sample (NIS) from 2018 to 2022. Hospitalizations involving HCC were identified through ICD-10 diagnosis codes, encompassing both principal and secondary diagnoses. Survey-weighted analyses were used to estimate national prevalence, in-hospital mortality, length of stay (LOS), and total hospital charges. Temporal trends were evaluated using survey-weighted logistic or linear regression, with calendar year as a continuous variable. Multivariable survey-weighted logistic regression models were constructed to identify adjusted predictors of inpatient mortality and procedural utilization, including liver transplantation, hepatic resection, and transjugular intrahepatic portosystemic shunt (TIPS) placement. Results: During the study period, an estimated 275,000 HCC-related hospitalizations occurred nationwide. The prevalence of cardiometabolic comorbidities increased significantly over time (all p < 0.001), including MASLD (6.6% to 8.7%), obesity (10.6% to 13.7%), diabetes (36.0% to 38.9%), and dyslipidemia (26.4% to 34.4%). In-hospital mortality rose from 8.82% (95% CI, 8.40–9.24%) in 2018 to 9.23% (95% CI, 8.81–9.65%) in 2022, with the highest rate in 2020 (9.42%). In parallel, inpatient resource utilization rose, as reflected by longer lengths of stay and higher hospitalization charges. Utilization of diagnostic endoscopic procedures, such as esophagogastroduodenoscopy and endoscopic retrograde cholangiopancreatography, increased, whereas rates of definitive inpatient oncologic and portal hypertension-directed interventions—including liver transplantation, hepatic resection, and TIPS—remained low and stable. In-hospital mortality was independently associated with markers of hepatic decompensation and systemic illness, including hepatic encephalopathy, acute kidney injury, sepsis, and hepatorenal syndrome. These associations were stronger than those observed for tumor-directed procedures, as reflected by inpatient procedural utilization patterns. Conclusions: Between 2018 and 2022, inpatient resource utilization among patients hospitalized with hepatocellular carcinoma increased in parallel with rising cardiometabolic comorbidity. It was primarily driven by management of hepatic decompensation and systemic illness rather than oncologic intervention. These findings characterize the evolving complexity of HCC hospitalizations in the contemporary inpatient setting. Full article

Background/Objectives: Ultra-processed food (UPF) consumption is increasing worldwide, yet its domain-specific impact on health-related quality of life (HRQoL) among postmenopausal women remains poorly characterized. This study investigated associations between UPF intake and domain-specific and overall HRQoL in a nationally representative sample of Korean postmenopausal women. Methods: Data from the Korea National Health and Nutrition Examination Survey (2013–2021) were analyzed. UPF consumption was assessed using a single 24 h dietary recall and classified according to the NOVA food classification system. HRQoL was evaluated using the five EQ-5D domains and the overall EQ-5D index. Survey-weighted logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs) across UPF intake quartiles, adjusting for socioeconomic and health-related covariates. Results: Higher UPF consumption was associated with impairments in specific HRQoL domains rather than a uniform decline across domains. In fully adjusted models, women in the third UPF intake quartile had higher odds of mobility impairment (OR 1.74; 95% CI 1.06–2.86) and anxiety/depression symptoms (OR 1.71; 95% CI 1.06–2.77) than those in the lowest quartile. A significant linear trend was observed for mobility (P-for-trend = 0.012). In contrast, associations with the overall EQ-5D index score were limited and not consistently observed after full adjustment. Conclusions: Higher UPF consumption is associated with domain-specific HRQoL impairments, particularly affecting physical mobility and mental health, among postmenopausal women. These findings underscore the importance of domain-specific assessments and suggest that UPF consumption may be related to certain aspects of functional and psychological well-being after menopause. Full article

Background/Objectives: Stroke is a leading cause of mortality and disability in Saudi Arabia; however, national estimates of stroke-related rehabilitation needs remain limited. This study quantified temporal trends in stroke incidence, prevalence, premature mortality, and disability from 1990 to 2021. It also examined disparities in stroke-related disability by subtype, sex, and age in 2021 and projected rehabilitation demand to 2030 to inform health system planning under Vision 2030. Methods: We conducted a secondary analysis of Global Burden of Disease (GBD) 2021 estimates for Saudi Arabia. Age-standardized rates for incidence, prevalence, years of life lost (YLLs), and years lived with disability (YLDs) were extracted for overall stroke and three subtypes: ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). Temporal trends were evaluated using log-linear regression to estimate the average annual percentage change (AAPC). YLDs were mapped to severity levels and four rehabilitation modalities, physiotherapy (PT), occupational therapy (OT), speech–language therapy (SLT), and multidisciplinary comprehensive rehabilitation (MCR), using utilization probabilities informed by the literature. Projections to 2030 incorporated national population forecasts and included 95% prediction intervals and sensitivity analyses. Results: From 1990 to 2021, age-standardized stroke incidence declined from 166.3 to 130.7 per 100,000 (−21.4%; AAPC, −0.86%, p = 0.004), prevalence from 982.4 to 965.2 per 100,000 (−1.8%; AAPC, −0.10%, p = 0.056), and YLL rates from 3209.0 to 1893.4 per 100,000 (−41.0%; AAPC, −1.76%, p < 0.001). In contrast, YLD rates declined modestly from 133.5 to 129.9 per 100,000 (−2.7%; AAPC, −0.13%; p = 0.032). Despite these reductions in age-standardized rates, absolute stroke-related YLDs more than tripled, increasing from approximately 10,900 (95% UI: 8100–13,900) in 1990 to 36,245 (95% UI: 26,600–46,100) in 2021, largely driven by population growth and aging. In 2021, ischemic stroke accounted for 71.1% of total YLDs, followed by ICH (20.3%) and SAH (8.5%). Among adults aged 15–49 years, females had higher hemorrhagic YLD rates than males, with particularly pronounced differences for SAH (female-to-male ratio, 1.5–1.7). By 2030, the projected YLD-equivalent workload, a standardized proxy measure of relative service demand rather than a direct headcount of required therapists, is expected to increase to 29,758 for PT, 21,809 for OT, 14,879 for SLT, and 15,083 for MCR. Sensitivity analyses showed that rehabilitation demand estimates were sensitive to assumptions regarding severity distribution, with a hemorrhagic-weighted scenario increasing projected MCR demand by 6.8%. Conclusions: The increasing absolute burden of stroke-related disability in Saudi Arabia, despite declining age-standardized rates and substantial reductions in premature mortality, highlights the necessity to expand rehabilitation capacity. Scaling community-based, outpatient, and telerehabilitation services in alignment with the Health Sector Transformation Program and integrating disability-informed planning into Vision 2030 should be prioritized. Full article

There are limited data on sequential computed tomographic (CT) evaluation and objective CT assessment of the metacarpal condyles in Thoroughbred racehorses. This longitudinal study aimed to document changes in attenuation of the metacarpal condyles during the first two years of training and racing. Fan-beam CT examination of the metacarpophalangeal regions was performed on 40 non-lame Thoroughbred yearlings, and repeated four more times, approximately six months apart. Mean Hounsfield Unit (HU) measurements were obtained on sagittal reconstructions of the dorsal and palmar halves of the medial and lateral condyles and parasagittal grooves. One-way ANOVA with a post hoc Tukey’s Test was used to investigate differences between mean HU values over time at the different regions of interest. Multivariable mixed-effects linear regression models assessed the association between dorsal and palmar HU and potential explanatory variables. Mean HU increased significantly with training, especially during the first six months, with a maximal sequential mean increase found in the medial parasagittal groove (119.8 [95% confidence interval 85.3, 154.30], p < 0.001). Dorsal regions had higher HU than palmar regions, with the highest HU recorded in the dorsal aspect of the medial condyle at time 3 (mean HU 1120.1 ± 63.4). Condyles had higher HU than parasagittal grooves (p < 0.001), the palmar half of the right condyles had higher HU than the left (p = 0.045) and the dorsal aspect of the medial condyle had higher HU than the lateral (p < 0.001). An increasing number of race starts and higher body weight:height ratio were associated with higher HU (p < 0.001). The main limitation was the loss of horses to follow-up as the study progressed. In conclusion, density of most regions of the metacarpal condyles increased with time spent in training, reflecting adaption to racehorse training. Full article

Background/Objectives: A ratio of subcutaneous adipose tissue to muscle mass may be more informative than defining low subcutaneous adipose tissue and muscle mass separately. The objective of this study was to determine which ultrasound measurement points in the upper and lower extremities predict the subcutaneous adipose tissue (SAT)-to-muscle ratio as measured by gold-standard computed tomography (CT) at the third lumbar vertebra (L3) level. Methods: Two hundred hospitalised patients (41% female; median (Q1–Q3) age: 61.3 (51.0–70.1) years) who underwent an abdominal CT scan for any clinical reason within 48 h prior to extremity ultrasound were included in this prospective observational study conducted from 2017 to 2019. Ultrasound measurements of subcutaneous adipose tissue and muscle thickness were obtained at three measuring points on the thigh and two on the upper arm. On the CT scan at the L3 level, subcutaneous (SAT) and visceral adipose tissue and skeletal muscle area were measured. A linear LASSO (Least Absolute Shrinkage and Selection Operator) model was used to identify which ultrasound sites best predicted the CT L3 SAT-to-muscle ratio. Results: Height, weight, sex, SAT-to-muscle ratio at four ultrasound measuring points and abdominal circumference predicted the CT SAT-to-muscle ratio in the LASSO model (R² = 0.70; cross-validated R² = 0.63; p values are not reported in LASSO regression and R² is used instead). The upper-arm anterolateral ultrasound site most strongly influenced the CT SAT-to-muscle ratio (estimate × standard deviation of predictor: 0.24). Conclusions: The CT SAT-to-muscle ratio at the L3 level can be predicted non-invasively using bedside ultrasound, particularly at the anterolateral measuring point of the upper arm. Bedside ultrasound assessment of the ratio of subcutaneous adipose tissue to muscle on the anterolateral upper arm provides a within-patient comparison of body compartments. Full article