Search Results (12,344)

Background/Objectives: In soccer, scanning before receiving the ball helps players better perceive and interpret their surroundings, enabling faster and more effective passes. Despite its importance, no standardized tests currently incorporate scanning actions into assessments of passing abilities. In this study, we test the reliability and validity of a battery of passing tests that assess a player’s ability to control and pass the ball while also scanning for the appropriate target. Methods: We designed three passing tests that reflect different scanning demands that are routinely placed upon players during matches. Using players from the first and reserve teams of two professional clubs in Ghana (Club A, first-team n = 11, reserve-team n = 10; Club B, first-team n = 16, reserve-team n = 17), we: (i) tested the repeatability of each passing test (intraclass correlations), (ii) assessed whether the tests could distinguish between first and reserve team players (linear mixed-effects model), and (iii) examined whether players who were better in the passing tests had higher performances in 3v1 Rondo possession games (linear models). Results: All passing tests were significantly repeatable (ICCs = 0.77–0.85). Performance was highest in the 120-degree test (30.11 ± 7.22 passes/min), where scanning was not required, and was lowest in the 360-degree test (25.55 ± 5.94 passes/min), where players needed to constantly scan behind them. When players were scanning through an arc of 180 degrees, their average performance was 27.41 ± 6.14 passes/min. Overall passing performance significantly distinguished first from reserve team players (β = −1.47, t (51) = −4.32, p < 0.001)) and was positively associated with 3v1 Rondo possession performance (R² = 0.51, p < 0.001). Conclusions: Our results show that these passing tests are reliable, distinguish players across competitive levels, and correlate with performance in possession games. These tests offer a simple, ecologically valid way to assess scanning and passing abilities for elite players. Full article

Systemic sclerosis (SSc) is an autoimmune connective tissue disorder characterized by vascular abnormalities, immune dysfunction, and progressive fibrosis. One of the most common manifestations of SSc is interstitial lung disease (ILD), known by a progressive course leading to significant morbidity and mortality. Aim: to investigate autoantibodies, cytokines, and genetic markers in SSc-ILD through a systematic review and analysis of a Kazakh cohort of SSc-ILD patients. Methods: A PubMed search over the past 10 years was performed with “SSc-ILD”, “autoantibodies”, “cytokines”, and “genes”. Thirty patients with SSc were assessed for lung involvement, EScSG score, and modified Rodnan skin score. IL-6 was measured by ELISA, antinuclear factor on HEp-2 cells by indirect immunofluorescence, and specific autoantibodies by immunoblotting. Genetic analysis was performed using a 120-gene AmpliSeq panel on the Ion Proton platform. Results: The literature review identified 361 articles, 26 addressed autoantibodies, 20 genetic variants, and 12 cytokine profiles. Elevated levels of IL-6, TGF-β, IL-33, and TNF-α were linked to SSc. Based on the results of the systemic review, we created a preliminary immunogenic panel for SSc-ILD with following analysis in Kazakh patients with SSc (n = 30). Fourteen of them (46.7%) demonstrated signs of ILD and/or lung hypertension, with frequent detection of antibodies such as Scl-70, U1-snRNP, SS-A, and genetic variants in SAMD9L, REL, IRAK1, LY96, IL6R, ITGA2B, AIRE, TREX1, and CD40 genes. Conclusions: Current research confirmed the presence of the broad range of autoantibodies and variations in IRAK1, TNFAIP3, SAMD9L, REL, IRAK1, LY96, IL6R, ITGA2B, AIRE, TREX1, CD40 genes in of Kazakhstani cohort of SSc-ILD patients. Full article

T-cell-engaging antibodies are a promising new type of treatment for patients with refractory or relapsed (R/R) diffuse large B-cell lymphoma, which has changed the prognosis and evolution of these patients in clinical trials. Bispecific antibodies (BsAbs) bind to two different targets (B and T lymphocytes) at the same time and in this way mimic the action of CAR (chimeric antigen receptor) T-cells. They are the T-cell-engaging antibodies most used in practice and are a solution for patients who do not respond to second- or later-line therapies, including chemoimmunotherapy, followed by salvage chemotherapy and hematopoietic stem cell transplantation. They are a therapeutic option for patients who are ineligible for CAR T-cell therapy and are also active in those with prior exposure to CAR T-cell treatment. A remarkable advantage of BsAbs is their rapid availability, even if the disease progresses rapidly, unlike CAR T-cell treatment, and they avoid the practical and financial challenges raised by autologous CAR T-cell therapies. CAR-T has been proven to have better efficacy compared to BsAbs, but cytokine release syndrome and neurotoxicity have appeared significantly more frequently in patients treated with CAR T-cells. The possibility of combining BsAbs with chemotherapy and their administration for relapses or as a frontline therapy is being studied to increase their efficacy. BsAbs are a life-saving therapy for many patients with diffuse large B-cell malignant non-Hodgkin’s lymphoma (NHL) who have a poor prognosis with classical therapies, but are not without adverse effects and require careful monitoring. Full article

Accurate fetal R-peak detection from low-SNR fetal electrocardiogram (FECG) signals remains a critical challenge as current NI-FECG methods struggle to extract high SNR FECG signals and conventional algorithms fail when signal quality deteriorates. We proposed a U-Net-based method that enables robust R-peak detection directly from low-SNR FECG signals (0–12 dB), bypassing the need for high-SNR inputs that are clinically difficult to acquire. The method was evaluated on both real (A&D FECG) and synthetic (FECGSYN) databases, comparing against ten state-of-the-art detectors. The proposed method significantly reduces false predictions compared to commonly used detection algorithms, achieving a PPV of 99.81%, an SEN of 100.00%, and an F1-score of 99.91% on the A&D FECG database and a PPV of 99.96%, an SEN of 99.93%, and an F1-score of 99.94% on the FECGSYN database. Further investigation of robustness in low-SNR conditions (0 dB, 5 dB, and 10 dB) achieved 87.38% F1-score at 0 dB SNR on real signals, surpassing the best-performing algorithm implemented in Neurokit by 13.58%. In addition, the algorithm showed ≤2.65% performance variation across tolerance windows (50 reduced to 20 ms), further underscoring its detection accuracy. Overall, this work reduces the reliance on high-SNR FECG signals by reliably extracting R-peaks from suboptimal signals, providing implications for the reliability of fetal heart rate variability analysis in real-world noisy environments. Full article

Governments worldwide have set ambitious targets for decarbonising energy grids, driving the need for increased renewable energy generation and improved energy efficiency. One key strategy for achieving this involves enhanced energy management in buildings, often using machine learning-based forecasting methods. However, such methods typically rely on extensive historical data collected via costly sensor installations—resources that many buildings lack. This study introduces a novel forecasting approach that eliminates the need for large-scale historical datasets or expensive sensors. By integrating custom-built models with existing energy data, the method applies calculated weighting through a distance matrix and accuracy coefficients to generate reliable forecasts. It uses readily available building attributes—such as floor area and functional type to position a new building within the matrix of existing data. A Euclidian distance matrix, akin to a K-nearest neighbour algorithm, determines the appropriate neural network(s) to utilise. These findings are benchmarked against a consolidated, more sophisticated neural network and a long short-term memory neural network. The dataset has hourly granularity over a 24 h horizon. The model consists of five bespoke neural networks, demonstrating the superiority of other models with a 610 s training duration, uses 500 kB of storage, achieves an R² of 0.9, and attains an average forecasting accuracy of 85.12% in predicting the energy consumption of the five buildings studied. This approach not only contributes to the specific goal of a fully decarbonized energy grid by 2050 but also establishes a robust and efficient methodology for maintaining standards with existing benchmarks while providing more control over the method. Full article

The kallikrein–kinin system and its B1 and B2 receptors are key regulators in metabolic disorders such as obesity, diabetes, and insulin resistance. Obesity, a chronic and multifactorial condition often associated with comorbidities like type 2 diabetes and dyslipidemia, remains poorly understood at the metabolic level. The kinin B2 receptor (B2R) is involved in blood pressure regulation and glucose metabolism, promoting glucose uptake in skeletal muscle via bradykinin. Studies in B2R-KO mice demonstrate that the absence of this receptor predisposes animals to glucose intolerance under a high-fat diet and impairs adaptive thermogenesis, indicating a protective role for B2R in metabolic homeostasis and insulin sensitivity. In contrast, the kinin B1 receptor (B1R) is inducible under pathological conditions and is activated by kinin metabolites. Mouse models lacking B1R exhibit improved metabolic profiles, including protection against high-fat diet-induced obesity and insulin resistance, enhanced energy expenditure, and increased leptin sensitivity. B1R inactivation in adipocytes enhances insulin responsiveness and glucose tolerance, supporting its role in the development of insulin resistance. Moreover, B1R deficiency improves energy metabolism and thermogenic responses to adrenergic and cold stimuli, promoting the activation of brown adipose tissue and the browning of white adipose tissue. Collectively, these findings suggest that B1R and B2R represent promising therapeutic targets for the treatment of metabolic disorders. Full article

Maternal undernutrition (MUN) causes severe metabolic disruption in the offspring of mammals. Here we determined the role of histone modification in hepatic gene expression in late-gestation fetuses of nutritionally restricted cows, an established model using low-nutrition (LN) and high-nutrition (HN) conditions. The chromatin immunoprecipitation sequencing results show that genes with an altered trimethylation of histone 3 lysine 4 (H3K4me3) are associated with cortisol synthesis and secretion, the PPAR signaling pathway, and aldosterone synthesis and secretion. Genes with the H3K27me3 alteration were associated with glutamatergic synapse and gastric acid secretion. Compared to HN fetuses, promoter H3K4me3 levels in LN fetuses were higher in GDF15, IRF2BP2, PPP1R3B, and QRFPR but lower in ANGPTL4 and APOA5. Intriguingly, genes with the greatest expression changes (>1.5-fold) exhibited the anticipated up-/downregulation from elevated or reduced H3K4me3 levels; however, a significant relationship was not observed between promoter CpG methylation or H3K27me3 and the gene set with the greatest expression changes. Furthermore, the stress response genes EIF2A, ATF4, DDIT3, and TRIB3 were upregulated in the MUN fetal liver, suggesting activation by upregulated GDF15. Thus, H3K4me3 likely plays a crucial role in MUN-induced physiological adaptation, altering the hepatic gene expression responsible for the integrated stress response and systemic energy metabolism, especially circulating lipoprotein lipase regulation. Full article

Background/Objectives: Cancer is a complex disease that affects patients’ nutritional and psychological status. This study aimed to assess the nutritional status of patients diagnosed with lung and gastrointestinal system cancers and evaluate its association with anthropometric measurements, nutrient intake, and psychological symptoms. Methods: This cross-sectional study was conducted with 180 patients with lung and gastrointestinal system cancers. Data were collected face-to-face by a questionnaire that included the Subjective Global Assessment-(SGA), Cachexia Assessment Criteria, 24 h Food Consumption Record, and Symptom Checklist-90-Revised-(SCL-90-R). Some anthropometric measurements were collected. Results: Body Mass Index (BMI) was found to be significantly lower (p < 0.001) in SGA-B (moderately malnourished) and SGA-C (severely malnourished) compared to those in SGA-A (well-nourished). The calf circumference was significantly lower (p = 0.002) in SGA-C compared to those in SGA-A and SGA-B. The mean SGA scores were found to be higher in cachexia-diagnosed participants (p < 0.001). The energy intake of SGA-C was significantly lower than SGA-A and SGA-B (p < 0.001). In addition, the energy intake of SGA-B was lower than SGA-A (p < 0.001). The protein intake of SGA-C was lower than SGA-A and SGA-B (p < 0.001). The protein intake of SGA-B was lower than SGA-A (p < 0.001). Regarding the intake of vitamins A, C, E, B1, and B6 and carotene, folate, potassium, magnesium, phosphorus, iron, and zinc, SGA-B and SGA-C were significantly lower than SGA-A (p < 0.001). Additionally, only phobic anxiety was found to be significantly higher in SGA-B than in SGA-A (p: 0.024). Conclusions: As the level of malnutrition increased, a reduction in some nutrient intake and anthropometric measurements was observed. No significant difference was found in any psychological symptoms except phobic anxiety. With this in mind, it is important that every cancer patient, regardless of the stage of the disease, is referred to a dietitian from the time of diagnosis. Full article

This paper proposes an intelligent power adaptation framework for Free-Space Optics (FSO) communication systems operating under different weather conditions exploiting a deep learning (DL) analysis of received eye diagram images. The system incorporates two Convolutional Neural Network (CNN) architectures, LeNet and Wide Residual Network (Wide ResNet) algorithms to perform regression tasks that predict received signal quality metrics such as the Quality Factor (Q-factor) and Bit Error Rate (BER) from the received eye diagram. These models are evaluated using Mean Squared Error (MSE) and the coefficient of determination (${\mathrm{R}}^2$ score) to assess prediction accuracy. Additionally, a custom CNN-based classifier is trained to determine whether the BER reading from the eye diagram exceeds a critical threshold of ${10}^{-4}$; this classifier achieves an overall accuracy of 99%, correctly detecting 194/195 “acceptable” and 4/5 “unacceptable” instances. Based on the predicted signal quality, the framework activates a dual-amplifier configuration comprising a pre-channel amplifier with a maximum gain of 25 dB and a post-channel amplifier with a maximum gain of 10 dB. The total gain of the amplifiers is adjusted to support the operation of the FSO system under all-weather conditions. The FSO system uses a 15 dBm laser source at 1550 nm. The DL models are tested on both internal and external datasets to validate their generalization capability. The results show that the regression models achieve strong predictive performance, and the classifier reliably detects degraded signal conditions, enabling the real-time gain control of the amplifiers to achieve the quality of transmission. The proposed solution supports robust FSO communication under challenging atmospheric conditions including dry snow, making it suitable for deployment in regions like Northern Europe, Canada, and Northern Japan. Full article

Background/Objectives: Gallbladder cancer (GBC) is a lethal malignancy curable only by surgical resection in early stages (Tis, T1, T2). Significant controversy exists regarding the optimal extent of surgery. This review summarizes recent trends and evidence on surgical strategies for Tis, T1, and T2 GBC to guide practice and research. Methods: This narrative review synthesizes recent literature on surgical management of Tis, T1a, T1b, and T2 GBC based on American Joint Committee on Cancer (AJCC) 8th edition staging. It examines simple vs. extended cholecystectomy (simple cholecystectomy (SC) vs. extended/radical cholecystectomy (EC/RC)), the role of lymphadenectomy (LND) and hepatectomy, and minimally invasive surgery (MIS). Results: Simple cholecystectomy is curative for Tis/T1a GBC. For T1b, regional LND is essential for staging/potential benefit, especially examining ≥5–6 nodes. Tumor size is critical; SC alone may suffice for T1b < 1 cm (low lymph node metastasis (LNM) risk), while EC/RC with LND is indicated for ≥1 cm (higher LNM risk). Routine hepatectomy for T1b lacks survival support. For T2 GBC, mandatory regional LND (≥6 nodes) is required for both T2a and T2b substages due to high LNM rates; T2b has higher LNM than T2a. Routine hepatectomy for T2 is debated; evidence suggests no routine benefit for T2a beyond LND, with conflicting findings for T2b. R0 resection is paramount. MIS is feasible for early stages in experienced hands. Conclusions: Management of early GBC is moving towards risk stratification. SC is standard for Tis/T1a. Adequate regional LND is crucial for T1b (especially ≥1 cm) and mandatory for T2 GBC. Routine hepatectomy, particularly for T2b, remains controversial. Tailored surgery prioritizes R0 resection and comprehensive LND, necessitating further standardized research. Full article

Chronic musculoskeletal pain negatively affects patients’ quality of life, and pain perceptions may significantly influence rehabilitation outcomes. This study investigated the relationships among pain intensity, pain perceptions, and kinesiophobia in individuals with chronic musculoskeletal pain. No previous studies have examined these variables in combination. A cross-sectional observational study was conducted with 37 participants with non-specific chronic musculoskeletal pain for at least 6 months, affecting the neck (n = 8), lower back (n = 18), upper limbs (n = 5), lower limbs (n = 5), or shoulder (n = 1). The following validated tools were used: (a) Pain Beliefs and Perceptions Inventory (PBPI), (b) the Tampa Scale for Kinesiophobia (TSK), and (c) the Short-Form McGill Pain Questionnaire (SF-MPQ). Spearman r correlation analyses were performed. Total kinesiophobia scores were positively correlated with (a) total pain intensity (McGill score) (r = 0.37, p = 0.022), (b) present pain intensity (PPI) (r = 0.52, p = 0.001), (c) pain duration (r = 0.51, p = 0.001), (d) the “mystery” factor of pain perception (r = 0.41, p = 0.013), and (e) the Visual Analogue Scale (VAS) (r = 0.42, p = 0.009). The total pain perception scores were positively associated with the “fear of injury” factor of kinesiophobia (r = 0.36, p = 0.028). The McGill pain scores were strongly correlated with both PPI (r = 0.63, p = 0.001) and VAS (r = 0.51, p = 0.001). There is a significant relationship between pain perception and kinesiophobia levels in patients with chronic musculoskeletal pain. Limitations of the study include a small and heterogeneous sample regarding pain localization. Further research is required using larger, more homogeneous populations to confirm the present findings. Full article

Ischemic stroke is a serious disease that frequently occurs in the elderly and is characterized by a complex pathophysiology and a limited number of effective therapeutic agents. Salvianolic acid A (SAL-A) is a natural product derived from the rhizome of Salvia miltiorrhiza, which possesses diverse pharmacological activities. This study aims to investigate the effect and mechanisms of SAL-A in inhibiting ferroptosis to improve ischemic stroke. Brain injury, oxidative stress and ferroptosis-related analysis were performed to evaluate the effect of SAL-A on ischemic stroke in photochemical induction of stroke (PTS) in mice. Lipid peroxidation levels, antioxidant protein levels, tissue iron content, nuclear factor erythroid 2-related factor 2 (Nrf2), and mitochondrial morphology changes were detected to explore its mechanism. SAL-A significantly attenuated brain injury, reduced malondialdehyde (MDA) and long-chain acyl-CoA synthase 4 (ACSL4) levels. In addition, SAL-A also amplified the antioxidative properties of glutathione (GSH) when under glutathione peroxidase 4 (GPX4), and the reduction in ferrous ion levels. In vitro, brain microvascular endothelial cells (b.End.3) exposed to oxygen-glucose deprivation/reoxygenation (OGD/R) were used to investigate whether the anti-stroke mechanism of SAL-A is related to Nrf2. Following OGD/R, ML385 (Nrf2 inhibitor) prevents SAL-A from inhibiting oxidative stress, ferroptosis, and mitochondrial dysfunction in b.End.3 cells. In conclusion, SAL-A inhibits ferroptosis to ameliorate ischemic brain injury, and this effect is mediated through Nrf2. Full article

Background and Objectives: Risk stratification in acute heart failure (AHF) remains challenging, particularly in settings where biomarker availability is limited. Echocardiography offers valuable hemodynamic insights, but no single parameter fully captures the complexity of biventricular dysfunction and pressure overload. This study aimed to evaluate a novel echocardiographic index (ViRTUE Index–VTI-RVRA-TAPSE Unified Evaluation) integrating a peak systolic gradient between the right ventricle and right atrium (RV-RA gradient), tricuspid annular plane systolic excursion (TAPSE), the velocity–time integral in the left ventricular outflow tract (VTI LVOT), NT-proBNP (N-terminal pro–B-type Natriuretic Peptide) levels, and in-hospital mortality among patients with AHF. Materials and Methods: We retrospectively analyzed 123 patients admitted with AHF. Echocardiographic evaluation at admission included TAPSE, VTI LVOT, and the RV-RA gradient. An index was calculated as ${\displaystyle \frac{RV-RA gradient }{TAPSE x VTI LVOT}}$. NT-proBNP levels and in-hospital outcomes were recorded. Statistical analysis included correlation, logistic regression, and ROC curve evaluation. Results: The proposed index showed a significant positive correlation with NT-proBNP values (r = 0.543, p < 0.0001) and good discriminative ability for elevated NT-proBNP (AUC = 0.79). It also correlated with in-hospital mortality (r = 0.193, p = 0.032) and showed moderate prognostic performance (AUC = 0.68). Higher index values were associated with greater mortality risk. Conclusions: This novel index, based on standard echocardiographic measurements, reflects both systolic dysfunction and pressure overload in AHF. Its correlation with NT-proBNP and in-hospital mortality highlights its potential as a practical, accessible bedside tool for early risk stratification, particularly when biomarker testing is unavailable or delayed. Full article

Soil salinization is a major constraint to global crop productivity, highlighting the need to identify salt tolerance genes and their molecular mechanisms. Here, we integrated mRNA and miRNA profile analyses to investigate the molecular basis of salt tolerance of an elite Brassica napus cultivar S268. Time-course RNA-seq analysis revealed dynamic transcriptional reprogramming under 215 mM NaCl stress, with 212 core genes significantly enriched in organic acid degradation and glyoxylate/dicarboxylate metabolism pathways. Combined with weighted gene co-expression network analysis (WGCNA) and RT-qPCR validation, five candidate genes (WRKY6, WRKY70, NHX1, AVP1, and NAC072) were identified as the regulators of salt tolerance in rapeseed. Haplotype analysis based on association mapping showed that NAC072, ABI5, and NHX1 exhibited two major haplotypes that were significantly associated with salt tolerance variation under salt stress in rapeseed. Integrated miRNA-mRNA analysis and RT-qPCR identified three regulatory miRNA-mRNA pairs (bna-miR160a/BnaA03.BAG1, novel-miR-126/BnaA08.TPS9, and novel-miR-70/BnaA07.AHA1) that might be involved in S268 salt tolerance. These results provide novel insights into the post-transcriptional regulation of salt tolerance in B. napus, offering potential targets for genetic improvement. Full article

We report a case of catheter-associated bloodstream infection caused by a putative novel species in the genus Erwinia, identified using whole-genome sequencing (WGS). A female adolescent receiving long-term home parenteral nutrition via a central venous catheter (CVC) presented with a fever. Gram-negative rods were isolated from two CVC-derived blood culture sets, while peripheral cultures remained negative. Conventional identification methods, including VITEK 2, Phoenix M50, MALDI-TOF MS, and 16S rRNA and rpoB gene sequencing, failed to achieve species-level identification. WGS was performed on the isolate using Illumina MiSeq. Genomic analysis revealed a genome size of 5.39 Mb with 56.8% GC content and high assembly completeness. The highest average nucleotide identity (ANI) was 90.3% with Pantoea coffeiphila, and ≤85% with known Erwinia species, suggesting that it represents a distinct taxon. Phylogenetic analyses placed the isolate within the Erwinia clade but separate from any known species. Antimicrobial susceptibility testing showed broad susceptibility. This case highlights the utility of WGS for the identification of rare or novel organisms not captured by conventional methods and expands the clinical spectrum of Erwinia species. While the criteria for species delineation were met, the phenotypic characterization remains insufficient to formally propose a new species. Full article