Search Results (7,932)

Background/Objectives: Muscle wasting is often observed in the acute phase after spinal cord injury (SCI). We aim to investigate the factors determining rectus femoris muscle thickness and echo intensity on discharge for patients who had acute incomplete spinal cord injury undergoing inpatient rehabilitation. Methods: This is a prospective exploratory observational cohort study, conducted in a standalone inpatient multi-specialty tertiary rehabilitation center in Singapore. Forty-five patients with incomplete SCI, defined as American Spinal Injury Association Impairment Scale (AIS) B–D were recruited from January 2020 to October 2021. Variables including clinico-demographic data, lower limb spasticity, Lower Extremity Muscle Score (LEMS), Functional Independence Measure (FIM) motor score on admission were collected. Muscle ultrasound of the rectus femoris thickness and echo intensity were obtained at 6 weeks after acute SCI via standardized protocols. Stepwise multiple regression analyses were performed to identify the factors that were significant for rectus femoris muscle thickness and echo intensity on discharge. Results: The mean age of participants was 59.6 ± 16.6 years, with patients having AIS of B (11.1%), C (28.9%) or D (60.0%). Rectus femoris muscle thickness on discharge had a significant association with body mass index (B = 4.62; CI = 1.77, 7.47; p = 0.002) and onset of mobilization (B = −4.97; CI = −9.46, −0.484; p = 0.031). The significant variables associated with rectus femoris echo intensity on discharge were age (B = 0.546; CI = 0.126, 0.967; p = 0.012) and onset of mobilization (B = 2.49; CI = 0.439, 4.53; p = 0.019). Conclusions: Our findings suggest that age, body mass index and a delayed onset of mobilization may have significant impact on muscle ultrasound parameters. Patients with incomplete SCI may benefit from early mobilization and nutritional assessment for improved muscle strength and function. Full article

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle. Full article

Objective: Although the baseline prognostic nutritional index (PNI) is a well-known prognostic factor in lung cancer, the clinical significance of its fluctuation during treatment remains unclear. This study aimed to evaluate the prognostic value of dynamic changes in the PNI and to determine whether improvements in nutritional and immune status are correlated with survival outcomes. Methods: A total of 478 patients diagnosed with lung cancer were retrospectively analyzed. The PNI was calculated on the basis of serum albumin levels and total lymphocyte counts. The baseline value was termed PNI1, and the posttreatment value was termed PNI2. The dynamic changes in PNIΔ were categorized as increased, stable, or decreased. Relationships between these dynamic parameters and Overall Survival and Progression-Free Survival were assessed using Kaplan–Meier and Cox regression analyses. Results: The median follow-up was 19.9 months. Patients with higher PNI1 and PNI2 scores had significantly longer OS and PFS. Notably, patients who demonstrated an increase in PNIΔ during the treatment course had significantly longer overall survival than those with stable or decreased scores (p = 0.023). Multivariate analysis revealed that while cancer type and the posttreatment PNI (PNI2) were identified as independent prognostic factors (p = 0.007 for PNI2), the dynamic improvement in the PNI emerged as a critical indicator of a better clinical trajectory according to univariate analysis. Conclusion: This study demonstrates that the PNI is not merely a static baseline marker but also a dynamic biomarker that reflects the host’s response to treatment and disease. An increase in PNI values during treatment is associated with improved survival, suggesting that dynamic monitoring of nutritional and immune status provides valuable prognostic information for patient management in lung cancer patients. Full article

The chemical composition of vegetable cooking oils is a key parameter in determining the quality of their products. Antioxidants are widely used in these products to extend their shelf life. In this study, the concentration of butylated hydroxytoluene (BHT) in edible oil was quantitatively determined by Raman spectroscopy combined with chemometrics. Initially, Raman spectra of edible oil samples with varying concentrations of BHT were obtained. Subsequently, three variable selection methods were applied to the pre-processed spectra. Optimised characteristic wavelengths were then used to establish a Radial Basis Function (RBF) neural network and partial least squares (PLS) models. The impact of variable selection on feature wavelengths was evaluated for both models in both independent and combined cases. The results demonstrate that the features identified through multiple variable selection methods correlate highly with the BHT content and can be utilised to develop high-precision detection models. The findings indicate that the PLS model, optimised using competitive adaptive reweighting (CARS), achieved the best prediction performance, with an average $R_P^2$ of 0.9687, and RMSEP of 3.1211. These results demonstrate the feasibility of using Raman spectroscopy combined with chemometrics for the rapid screening of BHT in edible oils. While the current study focuses on a broad concentration range to validate the method’s linearity, further optimisation is required for trace-level detection to meet strict regulatory limits. Full article

Background/Objectives: Hip hemiarthroplasty (HHA) for femoral neck fractures (FNFs) can be performed via the posterolateral approach (PLA), straight lateral approach (SLA) or direct anterior approach (DAA). However, the optimal approach remains unclear. This study evaluated mortality and return-to-home rates following an institutional transition from SLA to DAA. Methods: This retrospective observational cohort study included patients who underwent primary cemented unipolar hip hemiarthroplasty for FNF during a period of transition in surgical approach (2015–2023). Clinical outcomes between the straight lateral and direct anterior approach were compared. Primary outcomes were the mortality and return-to-home rates. Secondary outcomes included perioperative parameters and complications. A subgroup analysis was performed using Fracture Mobility Score (FMS) and Katz activities of daily living (ADL) index to compare functional outcomes. Results: Over a 9-year period, a total of 762 HHA were performed, of which 411 SLA and 333 DAA. Mortality at 90 days (14.1% vs. 8.7%, p = 0.029) and 1 year (26.5% vs. 17.7%, p = 0.005) were significantly higher in the SLA group. Among patients living at home preoperatively, return-to-home after surgery was lower for SLA compared to DAA (23.2% vs. 41.4%, p < 0.001). In terms of complications, SLA had significantly lower rates of periprosthetic joint infections (SLA n = 6 (1.5%) vs. DAA n = 15 (4.6%), p = 0.024). The decline in Katz ADL score at three months was significantly greater in the SLA group than in the DAA group (ΔKatz ADL −0.73 ± 1.57 vs. −0.11 ± 1.60, p = 0.036). Conclusions: Transitioning from SLA to DAA in HHA was associated with improved preservation of independent living, higher return-to-home rates and lower 90-day and 1-year mortality. However, DAA was also associated with higher rates of PJI. Full article

Background/Objectives: D-dimer, a fibrin degradation product, is associated with tumor growth and metastasis. In breast cancer, high concentrations of D-dimer are linked to more advanced disease stages and metastatic spread. This research aimed to examine the relevance of D-dimer levels in estrogen and progesterone hormone receptor (HR)-positive breast cancer. Methods: This retrospective single-center cohort study included patients with HR-positive breast carcinoma who underwent adjuvant or palliative radiotherapy in Türkiye. Pre- and post-radiotherapy blood test results, including D-dimer levels, were required. D-dimer, lymphocyte percentage, and interleukin-6 levels were measured for evaluation. All statistical analyses were performed using R software (version 4.4.2) to evaluate associations between D-dimer levels and other laboratory parameters. Univariate and multivariate Cox proportional hazards regression were performed to identify prognostic factors for progression-free survival (PFS) and overall survival (OS). Statistical significance was defined as p < 0.05. Results: Elevated D-dimer levels were associated with worse Eastern Cooperative Oncology Group performance status, advanced disease stages, metastasis, elevated IL-6 and CRP levels, and lower lymphocyte counts. Pre-RT D-dimer was a strong prognostic factor. Patients with D-dimer ≤ 0.3 µg/mL showed significantly superior OS and PFS (>60 months; p < 0.001), with only one event, and this remained significant in multivariate analysis (OS: HR 4.55, 95% CI 1.89–11.3; p = 0.002; PFS: HR 3.43, 95% CI 1.54–7.8; p = 0.004). Similarly, D-dimer ≤ 0.5 µg/mL was associated with improved OS (4/72 vs. 19/40 events; p < 0.001) and longer PFS, confirmed in multivariate analysis (OS: HR 4.37, 95% CI 1.72–9.86; p = 0.002; PFS: HR 3.88, 95% CI 1.67–9.1; p = 0.003), whereas levels > 0.5 µg/mL predicted worse outcomes. Using a 0.65 µg/mL cutoff, patients with D-dimer > 0.65 µg/mL had significantly shorter OS (median 25.5 months; 95% CI, 18–NA) compared with those ≤0.65 µg/mL (median not reached; p < 0.001), and this remained independently significant (OS: HR 5.10, 95% CI 1.9–13.6; p < 0.001; PFS: HR 4.68, 95% CI 1.83–11.9; p = 0.002). Conclusions: D-dimer is an accessible, non-invasive biomarker with predictive and prognostic significance in HR-positive breast cancer. Elevated D-dimer levels are suggestive of a more aggressive disease and poorer survival outcomes. This has the potential to facilitate early assessment of treatment efficacy and disease progression. This study has several limitations. Its retrospective, single-center design may introduce selection bias and limit generalizability. Although the sample size was sufficient to detect significant associations, validation in larger, multi-center cohorts is warranted to confirm the prognostic value of D-dimer. Full article

Background/Objective: Local progression after concurrent chemoradiotherapy in T3 laryngeal carcinoma (LC) remains difficult to predict using conventional clinical assessment alone. This study aimed to develop a radiomics-derived risk score from routine post-treatment contrast-enhanced CT and evaluate its prognostic value—together with clinical variables—for predicting local progression-free survival (LPFS). Methods: In this single-center retrospective cohort, 67 patients with pathologically confirmed T3-stage LC treated with chemoradiotherapy were included. All patients underwent contrast-enhanced CT at baseline and 3 months after treatment completion; radiomics analysis was performed using post-treatment CT with 3D manual segmentation of the primary tumor. A total of 111 radiomic features were extracted (shape, first-order, and texture). Features with AUC > 0.60 were screened, and six top-performing features were used to construct a radiomics score (0–6) based on optimized cutoffs. The primary endpoint was LPFS, defined as time from end of treatment to biopsy-proven residual or recurrent primary tumor. Cox regression and Kaplan–Meier analyses were performed. Results: Mean age was 59.6 ± 9.4 years, and 37.3% developed local progression during follow-up. In multivariable Cox analysis, the radiomics score remained an independent predictor of local progression (HR per 1-point increase: 2.38; 95% CI: 1.59–3.56; p < 0.001), with high model discrimination (C-index: 0.855). LPFS differed significantly across radiomics score strata (p < 0.001); higher scores were associated with substantially shorter time to progression and poorer 1-, 3-, and 5-year LPFS rates. Conclusions: A post-treatment CT-derived radiomics score integrated with clinical parameters showed favorable performance for predicting local progression in T3 laryngeal cancer after chemoradiotherapy. Although external validation is required, this approach may support more individualized surveillance by identifying patients at higher risk of early treatment failure. Full article

The condition of technical surfaces strongly influences the functionality and lifetime of many components. In particular, the performance of aero-engines can be impaired by increased roughness of the turbine blade surfaces. In this work, an LED- and camera-based illumination sensor is presented for reflection-based characterisation of turbine blade surfaces, with a focus on rapid, wide-area assessment rather than direct roughness measurement. Traditional roughness measurements (e.g., profilometry, confocal microscopy) provide micrometre-scale height information but are limited in working distance and measurement volume, making complete surface coverage time-consuming. The proposed sensor acquires multi-illumination image data, from which an anisotropic BRDF (bidirectional reflectance distribution function) model is fitted on a per-pixel basis to obtain reflectance parameters. Independently, surface roughness parameters (Sa, Sq, Sz, Ssk, Sku) are measured using a confocal laser scanning microscope in accordance with ISO 25178 and used as reference data. Using two turbine blades with contrasting surface conditions (comparatively smooth vs. visibly rough), the study qualitatively investigates whether there are indications of relationships between BRDF model parameters and roughness characteristics. The results show weak relationships with height-based parameters (Sa, Sq, Sz), but clearer trends for distribution parameters (Ssk, Sku) and a good qualitative agreement between directional BRDF parameters and texture orientation. These findings indicate that the illumination sensor provides a complementary, reflectance-based approach for surface condition triage in MRO and QA contexts, highlighting regions that warrant more detailed roughness measurements. Extension of the approach to other component geometries and a comprehensive quantitative analysis of BRDF–roughness relationships are planned for follow-up studies. Full article

Background and Objectives: Professional voice users (PVUs) are individuals for whom the voice is the primary tool of work, and whose professional success and income largely depend on its quality. This paper’s study population predominantly consisted of occupational voice users with moderate vocal demands and the study aimed to identify risk factors and causes of voice quality and production disorders, as well as the socio-epidemiological characteristics of affected patients. Materials and Methods: A retrospective study was conducted in Serbia, including 145 occupational voice users aged 20–70 years who were treated for dysphonia between August 2019 and July 2024. Data collected included demographics, symptom duration, tobacco exposure, throat and nasal swab results, gastroenterological and endocrinological evaluations and information on treatment for allergic rhinitis, asthma, and dysphonia. Patients were stratified by age, profession, and cause of dysphonia into the appropriate groups. Results: Dysphonia is significantly more common among female occupational users. There is a significant association between the cause of dysphonia and both age and hyperthyroidism. Smoking was highly prevalent in the study population and showed associations with selected videolaryngostroboscopic parameters; however, causal inferences could not be made due to the lack of a non-smoking comparison group. No statistically significant association was observed between positive nasal or throat swabs and dysphonia, nor between allergic rhinitis or asthma and the onset of dysphonia in occupational voice users. Treatment modality varies by gender, with male occupational voice users more likely to undergo surgery and female occupational voice users more often receiving conservative therapy. Symmetric vocal fold vibrations were observed in 85.5% of participants, while regular vibrations were present in 53.1%, and insufficient glottal closure in 10.3%. Regular vocal fold vibration was significantly less frequent in patients with structural disorders and more common in individuals aged 30–39 years. Male sex showed a borderline association with reduced likelihood of symmetric vocal fold vibrations. No independent predictors of insufficient glottal closure were identified. Conclusions: These results support the implementation of systematic otolaryngologic examinations, combined with mandatory education on proper voice use, vocal hygiene, and the harmful effects of tobacco smoke, as measures to prevent voice disorders in occupational voice users. Full article

3D vision-based groove detection is playing a critical role in enabling autonomous recognition. However, most existing interference evaluation strategies rely on height-based statistics or handcrafted heuristics, which (i) confuse genuine groove geometries (e.g., deep gaps and rounded corners) with noise and (ii) are sensitive to measurement scale and scanning configurations, making parameter tuning unreliable across scenes. To address this challenge, this paper proposes a novel method for evaluating the degree of interference in groove detection data, providing a reliable basis for the adaptive adjustment of algorithm parameters. The method leverages the angles of reconstructed triangular patches to assess the interference level in groove 3D detection data and computes the eigenvalues of the covariance matrix of these angles, establishing a rotationally invariant model for interference quantification. Experimental results show that the proposed method outperforms traditional methods, identifying more regions of high dispersion and demonstrating better adaptability to common groove features, such as deep gaps and rounded corners. By exploiting geometric invariance as a form of symmetry, the proposed eigenvalue-based dispersion descriptor provides a robust and coordinate-independent criterion for interference evaluation. Quantitatively, across multiple real industrial datasets, the proposed descriptor achieves an average 30.99% improvement in identifying severely interfered regions compared with the mainstream height-difference-based evaluation baseline. Full article

In the last decade, the self-field critical current density J_c(s.f.) in Type-II superconductors has been considered fundamentally limited by a Silsbee-like criterion of J_c(s.f.) = H_c1/λ. We show that this universal limit to self-field critical current density J_c(s.f.) is not universally valid. We present several examples for this in YBa₂Cu₃O_7−δ-type and REBa₂Cu₃O_7−δ thin films and one for Nb thin films and show that calculated J_c(s.f.) using the Silsbee-like criterion using thermodynamic parameters has been substantially exceeded experimentally. We also show that J_c(s.f.) can be significantly improved by incorporation of artificial pinning centers (APCs), further implying that no such universal limit to J_c(s.f.) can exist because such an upper bound, J_c(s.f.) would have to be independent of APCs. These findings call for a revision of the accepted understanding of current-carrying limits in Type-II superconductors and reveal substantial potential for improving J_c in REBCO-based coated conductors through optimization of APCs for large-scale applications, including commercial nuclear fusion. Full article

Background: The ambulatory arterial stiffness index (AASI) is a non-invasive surrogate marker of arterial stiffness; however, the relative contributions of hemodynamic, cardiometabolic, and renal factors to the AASI remain incompletely understood. This study aimed to identify the independent clinical factors associated with the AASI. Methods: This retrospective cross-sectional study included 290 individuals aged 18–65 years who underwent ABPM between 2020 and 2024. Participants were classified as hypertensive or normotensive based on ABPM criteria. Hemodynamic parameters, cardiometabolic indices, and renal biomarkers, including the urine albumin-to-creatinine ratio (uACR), were assessed. Results: Associations between the AASI and clinical variables were evaluated using the following correlation analyses and hierarchical multivariable linear regression models: Model 1-1b (hemodynamic), Model 2 (hemodynamic plus cardiometabolic) and Model 3 (hemodynamic plus cardiometabolic plus renal). The AASI was significantly higher in hypertensive individuals compared with normotensive controls. In correlation analyses, the AASI was positively associated with age, systolic blood pressure parameters, atherogenic lipid indices, and uACR and negatively associated with diastolic blood pressure parameters and the estimated glomerular filtration rate (eGFR). In multivariable regression analyses, age, maximum systolic blood pressure, and maximum diastolic blood pressure remained independently associated with the AASI across models. uACR was also independently associated with the AASI in the fully adjusted model. Conclusions: The AASI is primarily associated with hemodynamic load and age-related vascular changes. Among non-hemodynamic factors, albuminuria demonstrated the strongest association with the AASI after multivariable adjustment. These findings suggest the potential clinical value of the AASI as a practical marker for early cardiorenal risk assessment using routine ABPM data. Full article

Background: Direct-acting antiviral (DAA) therapy has transformed chronic hepatitis C virus (HCV) infection into a curable disease. Beyond viral eradication, increasing attention has been directed toward metabolic changes following sustained virological response (SVR), particularly alterations in lipid metabolism. This study aimed to assess the long-term evolution of lipid parameters after HCV cure in a real-world clinical cohort. Methods: We conducted a prospective, single-center observational study including 85 patients with chronic HCV infection who achieved SVR after DAA therapy. Lipid parameters, including total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides, were assessed at baseline and during post-SVR follow-up at 24, 48, and 96 weeks. Body mass index (BMI) and non-invasive fibrosis indices were also evaluated. Longitudinal changes were analyzed using mixed-effects models. Results: Total cholesterol increased from 157.7 ± 35.6 mg/dL at baseline to 179.6 ± 42.9 mg/dL at SVR 24 and further to 189.0 ± 40.3 mg/dL at SVR 48, stabilizing at 177.7 ± 38.3 mg/dL at SVR 96. LDL-C showed a similar trajectory from 94.6 ± 30.8 mg/dL at baseline to 107.5 ± 33.3 mg/dL at SVR 24, further raising to 115.7 ± 36.2 mg/dL at SVR48, and 111.8 ± 39.5 mg/dL at SVR 96. HDL-C showed minimal change, while triglycerides demonstrated greater interindividual variability without a consistent population-level trend. BMI remained stable over follow-up (26.6 ± 4.7 to 27.6 kg/m²). Linear mixed-effects models confirmed a significant effect of time after SVR on total cholesterol and LDL-C (p < 0.05). Conclusions: In this real-world cohort, HCV cure with DAA therapy was associated with sustained long-term changes in lipid metabolism, characterized by increases in total cholesterol and LDL-C independent of major weight changes. These findings support the importance of continued metabolic monitoring after SVR, particularly in patients with additional cardiometabolic risk factors. Full article

Accurate prediction of wheat prices is crucial for market participants and policymakers because volatility in agricultural markets affects food security and economic planning. This study proposes a hybrid deep-learning-based framework for daily wheat price prediction in Türkiye. The approach first applies an autoencoder to detect and remove anomalous price–quality records from a dataset of 38,019 market transactions collected between June 2022 and May 2023. A weighted ensemble combining Linear Regression, Random Forest, Support Vector Regression and an attention-based Long Short-Term Memory network is then trained on quality parameters and market attributes, with data split into training, validation and test sets. On the independent test set the ensemble achieved a coefficient of determination R² = 0.9942 and a mean absolute error of 0.1646 TL, outperforming the constituent models. SHAP analysis identifies the price–quality ratio as the most influential feature, while the ablation analysis shows that some of the high accuracy derives from price-derived variables’ strong correlation with the target. Cross-validation confirms robustness and generalization. Overall, the framework provides an effective and interpretable tool for wheat price forecasting, though the short data collection period and single-product focus limit generalizability. Full article

Background and Objectives: Sperm DNA fragmentation (SDF) has emerged as an important marker of male reproductive potential; however, its relationship with sperm kinematic performance remains incompletely understood. While conventional semen analysis primarily evaluates sperm concentration and motility, computer-assisted semen analysis (CASA) enables a more detailed assessment of sperm motility parameters, including velocity, path length, and directionality. Materials and Methods: This observational study included 183 semen samples, stratified by SDF levels into control (1–15%), mild (15.01–25%), moderate (25.01–50%), and severe (>50%) fragmentation groups. Sperm kinematic parameters were assessed using CASA, including curvilinear velocity (VCL), straight-line velocity (VSL), average path velocity (VAP), linearity (LIN), straightness (STR), and wobble (WOB). Group comparisons were performed using ANOVA or Kruskal–Wallis tests, correlation analyses were conducted using Spearman’s rank coefficient, and multivariable linear regression models were applied to evaluate the independent effect of SDF after adjustment for sperm concentration and progressive motility. Results: Parameters reflecting directional motility and movement efficiency differed significantly across increasing SDF categories. VSL, LIN, STR, and WOB showed a progressive decline with higher levels of DNA fragmentation, whereas VCL and VAP did not demonstrate a proportional decrease across groups. Correlation analysis revealed significant negative associations between SDF and VSL (ρ = −0.367, p < 0.001), VAP (ρ = −0.323, p < 0.001), and VCL (ρ = −0.202, p = 0.006), while correlations with LIN, STR, and WOB were negative but not statistically significant. Multivariable regression analysis confirmed SDF as an independent negative predictor of VSL and VAP after adjustment for conventional semen parameters, whereas the association with VCL was no longer significant. Conclusions: Increased sperm DNA fragmentation is associated with impaired sperm motility efficiency and directionality, rather than a uniform reduction in motility. These findings highlight the functional relevance of sperm DNA integrity in shaping sperm kinematic performance and support the complementary use of SDF assessment and CASA parameters in evaluating male fertility. Full article