Search Results (5,843)

KRTAP24-1 belongs to the high-sulphur KAP family and has been associated with cashmere fibre diameter in goats, but its role in ovine wool traits remains unclear. This study assessed KRTAP24-1 tissue expression by RT-qPCR and investigated genetic variation and associations with wool traits in 277 Tibetan sheep. Polymorphisms in the coding region were identified by PCR amplification and Sanger sequencing, and genotyping was performed using PARMS. A linear mixed model (LMM) incorporating a genomic relationship matrix (GRM) was used to evaluate associations between SNPs, haplotypes, and 12 wool traits. Bioinformatic analyses were restricted to the five haplotypes observed in the study population and were used as preliminary in silico assessments. Three missense SNPs were identified: c.191C>T (p.L64P), c.527G>A (p.G176D), and c.656C>T (p.A219V). The c.191C>T variant was associated with mean fibre length (MFL), single fibre tenacity (SFT), and scoured yield (SY), whereas c.656C>T was associated with lock length (LL) and clean fleece yield (CFY). Several haplotype combinations were also associated with LL, elongation at break (EB), and CFY. KRTAP24-1 showed high expression in skin. The observed haplotypes showed only minor differences in predicted mRNA secondary structure and mainly local changes in predicted protein features. These findings suggest that KRTAP24-1 may provide a preliminary basis for marker-assisted selection in Tibetan sheep breeding, but its functional role requires further validation in independent populations and experimental systems. Full article

The field study was conducted between 2016 and 2018 by the Department of Agronomy at Poznań University of Life Sciences. The experiment took place at the fields of the Research and Education Centre in Gorzyń, Złotniki branch. It was a single-factor trial involving six different sowing dates of an ultra-early maize cultivar: A1—12 April, A2—26 April, A3—10 May, A4—24 May, A5—7 June, and A6—21 June. The cultivar ‘Pyroxenia’ was used in the study. It is characterized by very early maturity (FAO 130), rapid early growth, and intensive stem elongation. In the present study, the optimal sowing time for the maize variety ‘Pyroxenia’ was late April (A2) and early May (A3). Later sowing of this variety resulted in a reduction in fresh and dry matter yields, as well as a reduction in the quality of the feed. The difference between the first (A1) and the last sowing date (A6) resulted in a 47% reduction in fresh weight and a 49% reduction in dry weight yield. No effect of sowing date was observed on starch content or structural carbohydrates, including crude fiber and its fractions (NDF, ADF, and ADL), in maize forage intended for ensiling. Data analysis for the years 2016–2018 showed that air temperature and precipitation had a significant effect on fresh and dry straw weight yields. Partial factor productivity of nitrogen (PFPF_N) decreased with delayed sowing of maize. On average, this parameter for maize sown in June compared with April, was lower by 38.8% for straw dry yield, 54.5% for ear dry yield, and 46.3% for whole-plant dry yield. Full article

We propose and empirically evaluate a two-stage approximation to a Generalized Multivariate Functional Additive Mixed Model (GMFAMM) for the joint bias correction of five NASA POWER reanalysis variables: minimum and maximum temperature ($T_{\min }$, $T_{\max }$), relative humidity (RH), solar radiation (Rad), and precipitation occurrence ($P_{\mathrm{bin}}$). Our primary contribution is the first operational-scale evaluation of such a framework (≈200,000 station–day observations, two orders of magnitude beyond previous studies) together with its deployment in an open-access web application. A systematic grid of more than 200 marginal configurations is evaluated on a strict chronological 70/30 hold-out (training 2016–2022; testing 2023–2025) to identify the optimal marginal specification per variable. Against a correctly specified marginal baseline, station-level linear calibration combined with the marginal GAMM removes the bulk of the systematic bias (RMSE reductions of ≈80%, 82% and 30% for $T_{\min }$, $T_{\max }$ and RH). A shared latent step, using the first principal component of the marginal residual matrix as a scalar proxy for ${\Lambda }_0\left(t\right)$, yields additional but conditional out-of-sample reductions (≈17% $T_{\max }$, 10% RH, 9% Rad; negligible for $T_{\min }$, with precipitation occurrence retained in the shared representation but its joint gain treated as exploratory); because it requires co-located donor observations, at ungauged locations the deployed pipeline applies the marginal correction only, whose spatial transfer is confirmed by leave-one-station-out cross-validation. The residual cross-correlation structure is consistent with, though not in itself proof of, Clausius–Clapeyron coupling. The trained artefacts are deployed in ColClim, an open-access R Shiny application that queries the NASA POWER API and the Open-Meteo forecast service for any location in Colombia and delivers historical bias-corrected series and short-range (1–16 day) forecasts. Full article

Background/Objectives: Corneal confocal microscopy (CCM) quantifies subbasal corneal nerve fibers noninvasively and may inform peripheral neuroaging. PhenoAge is a validated clinical measure of biological aging linked to morbidity and mortality risk and therefore provides a geriatric-relevant index of systemic aging. We aimed to assess corneal nerve morphology in clinically healthy adults and determine whether CCM-derived parameters are associated with biological age (PhenoAge) beyond chronological age. Methods: Eighty-four healthy volunteers (22–89 years) underwent CCM. PhenoAge was calculated using the Levine algorithm. Associations with chronological age and PhenoAge were tested using Spearman correlations (eye-specific and participant-level mean of both eyes). Paired inter-eye differences were assessed, and linear mixed-effects models (random intercept for participant; fixed effects for age/PhenoAge and eye) were fitted. Results: Mean chronological age was 50.8 ± 15.5 years, and mean PhenoAge was 47.1 ± 16.3 years. No systematic inter-eye differences were detected (all p > 0.05). Across analyses, older age and higher PhenoAge were associated with lower main corneal nerve fiber measures, most consistently for main-fiber density. Participant-level sensitivity analysis (mean of both eyes) confirmed inverse associations of both chronological age and PhenoAge with main-fiber length and density (all p ≤ 0.035). In mixed-effects models, main-fiber density was associated with chronological age (β = −0.020/year, p = 0.032) and PhenoAge (β = −0.019/year, p = 0.037). Conclusions: CCM-derived corneal nerve morphology demonstrates aging-related patterns in clinically healthy adults. The association between PhenoAge and main-fiber density may suggest a systemic biological aging component and warrants longitudinal validation. Full article

Interpretable feature-group fusion for tabular regression remains challenging because strong predictive models often lack explicit group-level attribution, complexity control, and attribution-stability guarantees. This paper proposes SHAP-Weighted Feature Fusion with Residual Mixing (SWFF-R), a closed-form convex fusion framework that combines a full-feature predictor with a SHAP-weighted blend of group-specific expert models. Group weights are obtained from temperature-controlled softmax transformations of group-level TreeSHAP importances, and the residual mixing coefficient is selected on a validation set to preserve predictive robustness. To avoid terminological confusion, we stress that these weights are derived from aggregated TreeSHAP importance scores of the full-feature model, not from group-level Shapley values recomputed by treating each feature group as a single player; the construction is therefore best described as TreeSHAP-importance-weighted feature-group fusion. Under fixed fusion weights and explicit centering, the proposed attribution satisfies Shapley-consistency properties for the induced centered additive group decomposition. We derive a Rademacher complexity upper bound for SWFF-R, provide a complementary minimax lower-bound calculation on a simplified linear subclass, and establish guarantees for temperature search and fixed-coefficient Lipschitz stability. Experiments on seven real-world tabular regression datasets and a separate synthetic 500K scalability stress test show that SWFF-R preserves predictive performance, yields point-estimate RMSE improvements on several datasets, and provides stable group-level attribution. Overall, SWFF-R offers a theoretically grounded framework for interpretable feature-group fusion in tabular regression. Full article

Background and Objectives: Faricimab, the first bispecific antibody targeting VEGF-A and angiopoietin-2, has demonstrated durable efficacy in pivotal phase 3 trials for neovascular age-related macular degeneration (nAMD) and diabetic macular edema (DME). Real-world data on treatment-naïve patients managed with fixed-interval maintenance protocols, particularly from South-Eastern Europe, remain limited. This pilot study evaluated 24-month outcomes of intravitreal faricimab in treatment-naïve nAMD and DME, using a standardized four-injection loading phase followed by fixed every-16-week (Q16W) maintenance. Materials and Methods: This study conducted a retrospective, observational, single-center pilot cohort study of 20 consecutive treatment-naïve eyes (9 nAMD, 11 DME). All patients received four monthly loading injections followed by a fixed every-16-week (Q16W) maintenance schedule, supplemented by discretionary additional injections for residual or recurrent disease activity (215 injections total; mean 10.75 ± 0.79 per patient; range 9–12). Primary outcomes were changes in central foveal thickness (CFT) and best-corrected visual acuity (BCVA; Snellen lines with ETDRS letter equivalents) at months 4 and 24. Prespecified secondary analyses included bootstrap 95% confidence intervals, a linear mixed-effects model with a time × disease-group interaction, Bayesian credible intervals with weakly informative priors, false-discovery-rate (FDR) correction, and a minimum detectable effect-size analysis. Results: All 20 eyes completed 24-month follow-up. In nAMD, mean CFT decreased by 186.9 ± 71.9 µm (35.9%; bootstrap 95% CI 148.1–236.0; p < 0.001; d = 2.60), and BCVA improved by 3.89 ± 0.78 Snellen lines (~19 ETDRS letters; 95% CI 3.44–4.33; p < 0.001; d = 4.97). In DME, CFT decreased by 197.7 ± 65.7 µm (39.3%; 95% CI 162.5–237.3; p < 0.001; d = 3.01), and BCVA improved by 4.55 ± 1.04 lines (~23 ETDRS letters; 95% CI 4.00–5.09; p < 0.001; d = 4.39). All 20 eyes (100%) achieved ≥ 3 Snellen lines gain and ≥20% CFT reduction; 80% reached final BCVA ≥ 7 lines. A linear mixed-effects model showed a significant time effect (p < 0.001) but no time × group interaction (CFT p = 0.84; BCVA p = 0.51), indicating concordant trajectories across diseases. Bayesian analysis with weakly informative priors yielded posterior P(|d| > 0.8) ≥ 0.99 for all primary outcomes. After FDR correction, all pre-specified primary comparisons remained significant. The minimum detectable effect size with the realized sample sizes (Cohen’s d ≈ 0.66 combined, 1.07 nAMD, 0.94 DME at 80% power) was substantially below all observed effect sizes. No ocular or systemic adverse events were recorded. Conclusions: In this small, single-center, treatment-naïve pilot cohort, a fixed Q16W faricimab maintenance schedule with discretionary additional injections was associated with durable anatomical and functional improvements over 24 months in both nAMD and DME, with no adverse events recorded across 215 injections. Given the limited sample, these findings should be regarded as hypothesis-generating. The high responder rates likely reflect the cohort’s substantial baseline visual impairment (mean baseline BCVA ~20/120–20/200), which provides greater absolute capacity for measurable gain than in higher-acuity registration trial populations. These pilot data support fixed-interval faricimab as a logistically feasible candidate strategy in resource-constrained settings and should be confirmed in larger multicenter cohorts using standardized ETDRS acuity assessment. Full article

Background and objectives: Cardiac surgery with cardiopulmonary bypass (CPB) is associated with endothelial glycocalyx injury and perioperative endothelial dysfunction. Syndecan-1 is commonly used as a biomarker of glycocalyx shedding, but data on its perioperative changes and their relationship with operative and patient-related factors remain limited. The aim of this study was to evaluate perioperative Syndecan-1 dynamics during coronary artery bypass grafting (CABG) with CPB and to assess associations with ischemia–reperfusion exposure and patient characteristics. Materials and methods: This prospective observational study included 147 patients undergoing elective CABG with CPB. Syndecan-1 concentrations were measured at five time points: before induction of anaesthesia, immediately after aortic cross-clamp application, immediately after aortic declamping, on arrival at the ICU and 24 h after surgery. Perioperative changes were analysed using non-parametric tests, Spearman’s rank correlation analysis and mixed-effects modelling. The study was registered at ClinicalTrials.gov (NCT03491163; registered on 29 March 2018). Results: Syndecan-1 concentrations changed significantly over time (p < 0.001), increasing from a baseline median of 49.74 ng/mL to a peak of 147.78 ng/mL at ICU admission, followed by a partial decline to 65.26 ng/mL at 24 h. Aortic cross-clamp duration was weakly but significantly associated with Syndecan-1 concentration at ICU admission (r_s = 0.243, p = 0.003) and with perioperative increases from baseline to ICU admission (ΔS4-1: r_s = 0.196, p = 0.017) and from aortic clamping to ICU admission (ΔS4-2: r_s = 0.207, p = 0.012). No significant associations were observed between CPB duration and Syndecan-1 concentrations in univariable analyses. In the mixed-effects model, a significant non-linear temporal pattern of Syndecan-1 concentrations was observed (both linear and quadratic time terms, p < 0.001). Male sex (β = 0.247, p = 0.009) and aortic cross-clamp duration (β = 0.016, p = 0.005) were independently associated with higher Syndecan-1 concentrations, whereas smoking status, age, BMI, diabetes status, EuroSCORE II, and CPB duration were not independently associated. Conclusions: Syndecan-1 concentrations increase significantly during cardiac surgery with cardiopulmonary bypass, peaking at ICU admission and partially declining within 24 h. Aortic cross-clamping duration, but not total CPB duration, showed weak associations with glycocalyx shedding. Male sex was independently associated with higher Syndecan-1 concentrations. These findings support ischemia–reperfusion injury as an important contributor to endothelial glycocalyx shedding during cardiac surgery. Full article

Large Language Models (LLMs) have rapidly become central components of cognitive computing systems and AI-assisted knowledge work. However, the effectiveness of LLM-generated outputs depends not only on the model’s capabilities but also on the structure of the prompts used to guide them. This study investigates how structured prompting techniques influence perceived output usefulness in business-oriented tasks. First, we conduct a systematic literature review following PRISMA guidelines to identify, classify, and synthesize existing prompt enhancement strategies. The review leads to the development of a taxonomy distinguishing task-alignment techniques (e.g., one-shot and few-shot prompting) from reasoning-transparency techniques (e.g., Chain-of-Thought prompting). Building on this taxonomy, we design a controlled experimental study in which knowledge workers evaluate LLM-generated outputs across analytical and summarization tasks. Using linear mixed-effects modeling, we assess the impact of prompting techniques and the moderating role of Generative AI usage frequency. Results indicate that structured prompting significantly increases perceived usefulness compared to baseline approaches, with the combination of example-based conditioning and explicit reasoning scaffolding yielding the highest evaluations. The moderating effect of usage frequency is not statistically significant, suggesting that the benefits of structured prompt design are robust across different experience levels. These findings position prompt structure as a practical cognitive interface mechanism and provide evidence-based guidelines for enhancing human–AI interaction in cognitive computing environments. Full article

Mental toughness (MT) may contribute to within-athlete rowing performance variation, yet longitudinal evidence remains sparse. This pilot study examined within-athlete associations between MT and 2K ergometer performance across a competitive season in Division II female rowers. Twelve athletes (age 20.8 ± 2.1 years) completed the mental toughness index (MTI) before four standardized 2K time trials. Performance was modeled using a linear mixed-effects model with a random intercept for the athlete. The MTI was decomposed into within- and between-athlete components, with the timepoint as a categorical covariate. Small-sample inference used CR2 cluster-robust standard errors with Satterthwaite degrees of freedom. Performance improved mid-season relative to baseline (Timepoint 3: −7.29 s; 95% CI [−13.29, −1.29]; p = 0.023). The within-athlete MTI association was small and imprecise (β = −0.48 s/point; 95% CI [−1.56, 0.59]; p = 0.311), and the between-athlete MTI was unassociated with performance (β = 0.70; p = 0.667). Stable between-athlete differences dominated over variability (ICC = 0.946; R²_m = 0.033; R²_c = 0.948). The within-athlete MTI estimate was small and imprecise; given the wide compatibility interval, both the direction and magnitude of the association remain highly uncertain, and this inconclusive finding should not be interpreted as evidence of absence. Future studies with larger samples and key covariates (e.g., training load and illness/injury) are needed to confirm these preliminary estimates. Full article

Archaeological feature detection at complex, mixed-environment sites requires accurate, efficient methods for identifying subtle morphological signatures. This study presents a semi-automated remote sensing pipeline for the detection and delineation of archaeological earthworks at Cahokia Mounds (Illinois, USA), a major Mississippian urban center and UNESCO World Heritage Site. Three LiDAR datasets, two collected via UAV-mounted sensors and one from a piloted aircraft survey, were processed into Digital Terrain Models and transformed into Local Relief Models (LRM). K-means clustering was applied to segment the LRMs into feature classes, followed by contour bounding using the OpenCV library to outline mounds and borrow pits. Additionally, SAR-derived Local Incidence Angle (LIA) rasters from PALSAR-3 and Sentinel-1 were processed through angular deviation mapping to identify slope anomalies associated with archaeological features. Results across all five datasets demonstrate the complementary strengths of LiDAR and SAR: LiDAR excels at resolving elevation-defined features such as mound footprints, while LIA captures directional slope behavior that highlights mound edges, borrow pit rims, and linear features such as causeways. Comparative analysis of LiDAR acquisition frequencies reveals minimal differences in archaeological feature recovery between pulse settings, suggesting that sensor platform choice matters more than power-density tradeoffs for this application. Despite the need for human review to filter modern disturbances and natural false positives, the integrated workflow meaningfully accelerates prospection and reduces interpretive subjectivity. The methods are scalable, site-invariant, and work with open-access data, making them applicable to archaeological landscapes worldwide. Full article

Hyperspectral unmixing aims to extract pure endmembers and their corresponding abundance from mixed pixels. Existing deep learning-based unmixing methods predominantly rely on convolutional neural networks (CNNs) or Transformer architectures. However, CNNs suffer from limited receptive fields and struggle to capture long-range spectral dependencies across the entire spectral sequence. While Transformers possess global modeling capabilities, they are constrained by quadratic computational complexity and lack the ability to adaptively filter redundant noise in consecutive spectral bands. To address these limitations, this paper proposes a dynamic hyperspectral unmixing network integrating a spectral sequence Mamba with local spatial–spectral awareness. Specifically, the network features a novel asymmetric dual-stream collaborative architecture. The first branch, the spectral sequence Mamba, models hyperspectral data as a one-dimensional continuous sequence and employs the selective state space model to perform global scanning with linear complexity. This adaptively filters redundant spectral bands to accurately extract high-purity global spectral semantics. The second branch, dedicated to local spatial–spectral awareness, uses an attention-augmented CNN to capture local continuous spectral variations and spatial textures, providing fine-grained geometric boundary constraints for abundance estimation. Furthermore, a spatially adaptive gated fusion module is designed to dynamically balance global spectral semantics and local spatial–spectral details according to the pixel mixing complexity of varying spatial regions. Extensive experiments on multiple public hyperspectral datasets demonstrate that the proposed method achieves significant improvements in unmixing accuracy over comparative methods. Full article

Background/Objectives. Neurofilament light chain (NfL) is a biomarker of axonal injury with prognostic value in acute ischemic stroke and a promising surrogate outcome marker. This study evaluated whether serum NfL concentrations in ischemic stroke were modified by varying degrees of renal function. Methods. In this prospective, single-center observational study, patients aged 18–80 y admitted to the IRCCS Mondino Foundation—Stroke Unit between May 2022 and August 2024 were enrolled. Inclusion criteria were: radiologically confirmed ischemic stroke within 24 h of onset, NIHSS ≥ 1 at admission, pre-stroke mRS < 2, no other neurological comorbidities, and eGFR > 30 mL/min/1.73 m². Serum creatinine was measured on admission, and eGFR was calculated using the CKD-EPI equation. Serum NfL was measured by Ella™ immunoassay at T0 (≤24 h), T1 (5 ± 3 d), and T2 (7 ± 3 d). Factors associated with serum NfL concentrations were assessed using linear mixed-effects models, and prognostic associations were evaluated by multivariate logistic regression. Results. Ninety-seven patients were included (median age 68.3 y; 39.2% female). Higher NfL levels were independently associated with lower eGFR (−2.4% per mL/min/1.73 m² increase; 95% CI −3.2% to −1.6%; p < 0.001), and higher NIHSS at admission (+3.5% per point; 95% CI 0.7% to 6.4%; p = 0.014). Time from stroke onset was also associated with NfL (p < 0.001). Among patients with 3-month follow-up and T2 measurement (n = 62), the main effects of log10-transformed NfL at T2 and eGFR were not independently associated with unfavorable outcomes. However, a significant log10 NfL × eGFR interaction was observed (OR 0.22; 95% CI 0.07–0.73; p = 0.014), indicating that the prognostic association of NfL varied according to renal function. Conclusions. Renal function affects serum NfL after ischemic stroke and appears to modify its prognostic association with 3-month outcomes. Full article

Background/Objectives: Cognitive impairment, frailty, and systemic comorbidity burden are common in elderly patients with glaucoma and may influence both visual field (VF) performance and glaucoma severity. This study investigated the associations of comprehensive geriatric assessment (CGA) parameters, including Mini-Cog, G8, and Age-Adjusted Charlson Comorbidity Index (ACCI), with VF sensitivity and VF reliability indices in glaucoma patients. Methods: This retrospective cross-sectional study included 1125 eyes of 622 glaucoma patients who underwent Humphrey VF testing and CGA at a tertiary referral center. Associations between CGA parameters and VF indices, including mean deviation (MD), pattern standard deviation (PSD), foveal sensitivity, fixation loss rate (FL), false-negative rate (FN), and false-positive rate (FP), were evaluated. Generalized linear mixed models were used to assess independent associations after adjustment for demographic, systemic, and ocular covariates. Results: In univariate analyses, lower Mini-Cog and G8 scores and higher ACCI scores were associated with several VF sensitivity and reliability indices. After multivariable adjustment, ACCI remained independently associated with lower MD (estimate = −0.52, p = 0.004), higher PSD (estimate = 0.27, p = 0.04), and lower foveal sensitivity (estimate = −0.36, p = 0.01). Lower G8 scores and higher ACCI scores were independently associated with increased FN rates, whereas higher G8 scores were associated with increased FP rates. Conclusions: Systemic comorbidity burden, assessed using ACCI, was independently associated with both glaucomatous functional impairment and selected VF reliability indices. Frailty, assessed using G8, was associated with VF reliability but not VF sensitivity. Although cognitive function measured by Mini-Cog was associated with VF parameters in univariate analyses, these associations were not retained after multivariable adjustment. Consideration of systemic health status and geriatric vulnerability may improve interpretation of VF results in patients with glaucoma. Full article

Background: Despite evidence-based guidelines for cardiovascular risk management, many patients fail to achieve therapeutic targets. The relative contribution of medication non-adherence versus suboptimal treatment optimization to poor cardiovascular outcomes remains unclear in real-world primary care settings. The aim of this study was to describe changes in cardiovascular risk factor control following protocolized adherence reinforcement combined with physician-driven treatment optimization in high-risk patients. Methods: This multicenter, real-world longitudinal study included 789 participants with high or very high cardiovascular risk enrolled from primary care settings across 9 Spanish regions between 2023 and 2025. All participants received a protocolized intervention combining adherence reinforcement and physician-driven treatment optimization. This was a single-arm, pre–post study without a concurrent control group; observed changes therefore cannot be attributed to the intervention alone. Of 789 participants screened, all completed the baseline assessment, and 628 (79.6%) completed the 90-day follow-up. A total of 161 participants (20.4%) were lost to follow-up. Primary outcomes included changes in systolic and diastolic blood pressure, lipid parameters (total cholesterol [TC], low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], triglycerides [TG]), glucose, glycated hemoglobin (HbA1c), and body mass index (BMI) from baseline to 90-day follow-up. Changes were assessed using linear mixed models. Results: Among participants with complete paired data (n = 453–615 depending on the outcome), significant improvements were observed in most cardiovascular risk factors (HDL-c and HbA1c did not change significantly). Mean changes (95% confidence interval [CI]) were: systolic blood pressure, −9.24 mmHg (−10.41 to −8.06; p < 0.001); diastolic blood pressure, −4.75 mmHg (−5.49 to −4.01; p < 0.001); LDL-c, −22.29 mg/dL (−25.59 to −19.00; p < 0.001); TC, −23.24 mg/dL (−26.73 to −19.74; p < 0.001); TG, −16.75 mg/dL (−23.03 to −10.46; p < 0.001); fasting plasma glucose, −10.03 mg/dL (−12.61 to −7.46; p < 0.001); and BMI, −0.46 kg/m² (−0.58 to −0.35; p < 0.001). Linear mixed models including all available data (n = 628 at 90-day follow-up) confirmed these findings. No significant interactions were observed between assessment timepoint and sex, age, or overweight/obesity status for most outcomes, except for age-related differences in lipid responses. Conclusions: Protocolized adherence reinforcement combined with physician-driven treatment optimization was associated with clinically meaningful improvements in multiple cardiovascular risk factors in high-risk primary care patients. Given the single-arm pre–post design, the observed improvements are associative and cannot establish causality. Residual uncontrolled risk, particularly in lipid management and among older adults, persisted despite active treatment optimization (treatment was modified in 82.0% of participants), consistent with residual suboptimal treatment intensification even after adherence had been reinforced. These findings suggest that achieving optimal cardiovascular risk factor control requires addressing both medication adherence and treatment intensification, particularly in patients with multimorbidity. Full article

Background: Binge eating (BE) is frequently associated with negative emotional states, obesity, and physical inactivity. Although yoga may improve binge eating and emotional symptoms, its effects on physical fitness remain unclear. In contrast, high-intensity interval training (HIIT) has been demonstrated to effectively enhance physical fitness. This study compared the effects of low-volume HIIT (LV-HIIT), high-volume HIIT (HV-HIIT), and yoga on binge eating, negative emotional states, and physical fitness in female college students with binge eating. Methods: Fifty-five physically inactive female college students with binge eating (BES ≥ 18) were randomly assigned to LV-HIIT (n = 19), HV-HIIT (n = 18), or yoga (n = 18) for 8 weeks. The Binge Eating Scale (BES), Depression Anxiety Stress Scale-21 (DASS-21), body fat percentage, waist circumference, and maximal oxygen uptake (VO2max) were assessed before and after the intervention. Data were analyzed using intention-to-treat linear mixed models, with per-protocol repeated-measures ANOVA as a supplementary analysis. Results: After 8 weeks of intervention, significant improvements over time were observed across all groups in binge eating, negative emotional states, and cardiorespiratory fitness (all p < 0.05). Waist circumference and body fat percentage did not change significantly in the ITT analysis. No significant time × group interaction effects were detected for any outcome (all p > 0.05), indicating that the improvements did not differ significantly among the LV-HIIT, HV-HIIT, and yoga groups. Conclusions: An 8-week intervention of LV-HIIT, HV-HIIT, and yoga was associated with improvements in binge eating behaviors, negative emotional states, and VO2max in inactive young women with binge eating, with no evidence of differential efficacy between interventions. LV-HIIT may be promising because of its shorter duration and higher adherence; however, this requires confirmation in larger trials. Full article