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Accurate prediction of athlete performance is a challenges issue of significance in sports science and analytics and has application in training design, injury prevention, and talent management. Conventional statistical models usually cannot represent nonlinearities that are highly intricate in terms of physiological, lifestyle, and contextual characteristics. The main aim of the study is the prediction of performance (predictive validity/generalization) of the performance scores of the athletes based on the tabular data. An interpretability is a secondary objective that is tackled through SHAP-based explanations, and computational efficiency is considered as the practical aspect of the selected model class; deployment feasibility is only presented as a possible application, not as a proven real-world application. The main objective is to offer a dependable platform of determining the main determinants of athlete performance and data-driven decision making in sports coaching. Kaggle Athlete Performance Prediction Dataset was used, which included demographic, training, physiological, and/or lifestyle features. Imputation, normalization, encoding, and feature engineering then followed, and finally, partitioning into training, validation, and test sets. Gradient Regression Model was trained with tenfold cross-validation and compared against various baseline which included linear regression, Ridge Regression, Support Vector Regression (SVR), Random Forest, and Neural Networks. Measures of evaluation wereR 2 , RMSE, and MAE. The proposed model had an R² of 0.923, which was higher than baselines, which included Neural Networks (R² = 0.901) and Random Forest (R² = 0.887). The presence of residual and error analysis ensured that bias and variance were reduced to a minimum, whereas learning dynamics showed that convergence and stability were achieved efficiently. The Gradient Regression Model is better at predicting and is also more interpretable, with applications that are applicable to individualized training and performance monitoring. This study is presented as an application and evaluation work with a publicly available dataset, with its contribution being a transparent end-to-end pipeline, strict validation, and analysis that relates predictive factors to the performance of athletes, as opposed to a new learning algorithm. The future research will cover larger and longitudinal studies along with the hybrid frameworks that incorporate both biomechanical and psychological aspects.

Background & aims The epidemiological characteristics of malnutrition in cancer patients remain unclear. The Global Leadership Initiative on Malnutrition (GLIM) criteria, published in 2019, were established to compare the prevalence of malnutrition globally, drive the development of standardized care practices, and promote improved clinical outcomes. This study aimed to systematically assess the prevalence and related factors of malnutrition in cancer patients based on the GLIM criteria, and to evaluate its association with clinical outcomes. Methods Two authors independently searched PubMed, Web of Science, the Cochrane Library, and Embase up to July 20, 2024. Eligible studies were observational (cross-sectional or cohort), involved adult cancer patients, and assessed nutritional status using the GLIM criteria. Studies were required to report at least one of the following outcomes: prevalence of malnutrition, associated factors, or relevant clinical outcomes. Heterogeneity was assessed using the I ² and Q tests. A random-effects model was used when significant heterogeneity was present ( I ²>50%, P  < 0.05); otherwise, a fixed-effects model was applied. PROSPERO registration number: CRD420251053345. Results A total of 20 cross-sectional studies and 45 cohort studies were included, all of which reported the prevalence of malnutrition and together covered over 30,000 cancer patients. Three studies examined factors influencing malnutrition. Nine studies evaluated its impact on overall survival (OS), while three assessed its effect on postoperative complications. Overall, the prevalence of malnutrition was 41% (95% CI: 36-45%), with moderate malnutrition at 19% (95% CI: 16-23%) and severe malnutrition at 20% (95% CI: 17-23%). The main factors influencing malnutrition in cancer patients were tumor-related symptoms. Malnutrition in cancer patients is significantly associated with OS (HR = 2.04, 95% CI: 1.56–2.67). Specifically, the risk is significantly increased in patients with moderate malnutrition (HR = 1.34, 95% CI: 1.07–1.72), and even higher in those with severe malnutrition (HR = 1.92, 95% CI: 1.55–2.39). Additionally, malnutrition in cancer patients is also significantly associated with an increased risk of postoperative complications (OR = 1.90, 95% CI: 1.41–2.55). Conclusion Malnutrition prevalence is high among cancer patients, primarily due to tumor-related symptoms. It significantly increases the risk of poor clinical outcomes, with a more pronounced effect in patients suffering from severe malnutrition.

Background Daratumumab (Dara), a humanized IgGκ monoclonal antibody targeting CD38, has shown significant efficacy in the treatment of multiple myeloma (MM). However, its impact on myeloma bone disease (MBD) and skeletal-related events (SREs) remains inadequately explored. Elucidating the effect of Dara on the incidence of SREs is of considerable clinical importance for MM management. Methods We conducted a multicenter retrospective analysis of 164 newly diagnosed MM (NDMM) patients who received first-line treatment with or without Dara-based regimens between December 2019 and December 2023. The primary endpoint was the incidence of first SRE within 6 months. Subgroup analyses were performed based on risk stratification, baseline hypercalcemia, extramedullary disease, circulating plasma cells, and use of anti-bone resorption drugs. Statistical analyses included Kaplan-Meier survival curves, log-rank tests, and Cox proportional hazards models with adjustment for covariates. Results The overall incidence of SREs was 17.68% (29/164), with 9.80% (5/51) in the Dara group and 21.23% (24/113) in the control group (log-rank P  = 0.08). Univariable and multivariable Cox regression analyses consistently showed a non-significant reduction in SRE risk with Dara-based treatment (HR = 0.44, 95% CI: 0.17–1.15, P  = 0.09; adjusted HR = 0.47, 95% CI: 0.17–1.28, P  = 0.14). Subgroup analyses revealed a significant benefit of Dara in patients without baseline hypercalcemia (HR = 0.19, 95% CI: 0.05–0.81, P  = 0.02) and a suggestive benefit in the standard-risk subgroup (log-rank P  < 0.05). A significant interaction was observed between Dara use and hypercalcemia status (P for interaction = 0.03). Conclusions While Dara-based treatment did not significantly reduce SRE incidence in the overall cohort, it may provide protective benefits against SREs in specific subgroups, particularly among patients without hypercalcemia. Our finding warrants further investigation into the bone-protective effects of Dara in MM.

Background Third‑generation CAR-T cells demonstrated promising efficacy and remarkably low toxicity in refractory or relapsed (R/R) B-cell malignancies. However, data on the patients with central nervous system (CNS) involvement are limited due to concerns regarding treatment-related neurotoxicity. This study aimed to evaluate the safety and efficacy of a novel third-generation anti-CD19 CAR T cells in patients with CNS involvement of B-cell malignancies. Methods A total of 21 patients with R/R B-cell malignancies with CNS involvement, including 11 with B-cell acute lymphoblastic leukemia (B-ALL) and 10 with B-cell non-Hodgkin lymphoma (B-NHL) were enrolled. Patients derived lymphocytes were collected through apheresis and lentivirally transduced with the third-generation CAR incorporating both CD28 co-stimulation and TLR2-derived stimulatory domains (1928zT2). Patients received a single-dose 1928zT2 CAR-T cell infusion following lymphodepleting regimen. Safety, efficacy and cellular pharmacokinetics were investigated. Results Of the 21 patients with CNS involvement, the overall response rate (ORR) was 71% (15/21), with 73% (8/11) in B-ALL and 70% (7/10) in B-NHL. At a median follow-up of 20.4 months, median duration of response (DOR) was 11.1 months (95% CI, 2.9–24.4). 12-months progression-free survival (PFS) and overall survival (OS) estimates were 41.5% and 61.2%, respectively. Cytokine release syndrome (CRS) of any grade occurred in 20 patients (95%; grade ≥ 3 in 3 patients). Immune effector cell-associated neurotoxicity syndrome (ICANS) occurred in 9 patients (42.8%; grade ≥ 3 in 6 patients). All CRS and ICANS events were manageable. The outcomes and adverse events are comparable between B-ALL and B-NHL patients. Notably, 1928zT2 CAR-T cells demonstrated blood–brain barrier penetrance, with subsequent detection in patient cerebrospinal fluid (CSF) correlating significantly with improved clinical outcomes. Conclusions Third-generation 1928zT2 CAR-T cells are associated with high response rates, manageable safety and durable remissions in R/R B-cell malignancies with CNS involvement. Trial registration : ClinicalTrials.gov, NCT04605666. Registered 1 May 2020.

Background Mitophagy is an essential cellular autophagic process which maintains mitochondrial homeostasis, but its role in high fat diet (HFD)-induced lipid accumulation is unclear in the yellow catfish. Thus, this study aimed to elucidate mechanism of mitochondria mediating HFD-induced hepatic fat accumulation. Results In the present study, yellow catfish were fed three diets with dietary fat at 6.31% (low fat; LFD, control), 12.03% (middle fat; MFD) and 15.32% (high fat; HFD), respectively, for 8 weeks. High dietary fat addition raised hepatic lipid accumulation, and declined mRNA and protein levels of Parkin-dependent mitophagy, down-regulated the Parkin protein expression and the estrogen-related receptor alpha (Errα) ubiquitination, and induced Errα protein levels; fatty acid (FA) incubation reduced Parkin-dependent mitophagy, inhibited Errα ubiquitination and increased Errα protein expression, and raised TG accumulation. Furthermore, yellow catfish hepatocytes were isolated and cultured. Nicotinamide mononucleotide, N -acetyl-L-cysteine, Parkin and errα siRNA knockdown were used under FA incubation, respectively. Parkin downregulation mediated FA incubation-induced TG accumulation and mitoautophagic inhibition; Parkin ubiquitinated Errα, and K63 was an important ubiquitination site for deubiquitinating Parkin activity; Errα targets fas , acca and pparγ genes, whose activation contributed to FA-induced lipogenesis and lipid accumulation. Thus, high fat diet (HFD) and FA incubation inhibited Parkin activity, suppressed mitophagy and activated Errα pathway, and induced hepatic lipogenic metabolism and lipotoxicity. Conclusions Overall, our study provided new targets against HFD-induced hepatic lipid accumulation and non-alcoholic fatty liver disease in the vertebrates.

Background Survival prediction accuracy of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) in extra-nodal natural killer/T-cell lymphoma (ENKTL) is controversial. This study aimed to evaluate the prognostic value of 18 F-FDG PET/CT parameters including maximum standardized uptake value (SUVmax), total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG), and to develop a new prognostic model for ENKTL. Methods We analyzed 390 ENKTL patients with comprehensive clinical and survival data. All patients received asparaginase-based chemotherapy with or without radiotherapy, or radiotherapy alone. Metabolic tumor volume (MTV) was calculated using a 41% SUVmax threshold, and TLG was computed as MTV multiplied by the average SUV. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan–Meier curves and compared with log-rank tests. Optimal cut-off values were determined using the Youden’ index. Cox regression analysis identified significant prognostic factors. A nomogram predicting 1-, 3-, and 5-year survival was developed and validated using the C-index and calibration curves. Statistical significance was set at p  < 0.05. Results Of the 390 patients, 262 (67.2%) were included in the training set and 128 (32.8%) in the validation set. 18 F-FDG PET-CT parameters with cutoff values of SUVmax > 12.8, TMTV > 16.4 cm 3 , and TLG > 137.0, were significantly associated with poorer OS ( p  = 0.009) and PFS ( p  = 0.003). Multivariable Cox regression identified the following as independent predictors of worse OS: age > 60 years (HR = 1.923, 95% CI: 1.001—3.693), presence of B symptoms (HR = 1.861, 1.132—3.059), ECOG score ≥ 2 (HR = 2.076, 1.165—3.699), extranodal involvement ≥ 2 sites (HR = 2.349, 1.384—3.988), bone marrow involvement (HR = 4.884, 2.137—11.163), SUVmax > 12.8 (HR = 2.226, 1.260—3.930), and TMTV > 16.4 cm 3 (HR = 1.854, 1.093—3.147). The new prognostic model achieved a C-index of 0.772 for OS and 0.750 for PFS in the training set, and 0.777 for OS and 0.696 for PFS in the validation set. Area under the curve (AUC) values for 1-, 3-, and 5-year OS were 0.841, 0.804, and 0.767 in the training set, and 0.718, 0.786, and 0.893 in the validation set. Risk stratification divided patients into four groups with significant differences in survival ( p  < 0.001). Conclusion SUVmax, TMTV, and TLG are independent prognostic factors in ENKTL. Our new model, which integrates 18 F-FDG PET/CT metrics with clinical data, enhances survival prediction and may support personalized treatment strategies, though further validation is required.

Background Heart failure imposes a significant healthcare burden, with early unplanned readmissions post-discharge linked to poor outcomes. Identifying risk factors and their predictive value is crucial for targeted interventions. Objective To investigate gender differences in cumulative hazard function and the factors influencing 30-day unplanned readmissions in heart failure patients, and to compare their predictive value. Methods A prospective study of heart failure patients hospitalized in Beijing Hospital from October 2023 to March 2024. Patients’ nutritional status was assessed using the Mini-Nutritional Assessment Scale Short Version (MNA-SF), frailty was evaluated using the Groningen Frailty Index (GFI), and the Appendicular Skeletal Muscle Mass Index (ASMI) was calculated. Multifactorial Cox regression analysis was conducted, and ROC curves were plotted for predictive modeling. Results A total of 121 heart failure patients (60.3% males), aged (69.87 ± 11.9) years were included. With a median follow-up duration of 30 days, 25 (20.7%) patients with readmission. COX regression analysis stratified by gender showed that age, regular smoking, nutritional status, left ventricular ejection fraction(LVEF), brain natriuretic peptide(BNP), GFI, and ASMI were independent predictors of readmission within 30 days in patients with heart failure ( P  < 0.050). ROC curve analysis showed that age, BNP, ASMI, smoking status, LVEF, nutritional status, and GFI individually as well as in combination predicted readmission within 30 days in patients with heart failure; the joint model performed optimally, with an AUC value reaching 0.877 (95%CI 0.801 ∼ 0.952, P  < 0.001), with a sensitivity of 0.920 and a specificity of 0.729. Conclusion A multifactorial approach including age, BNP, ASMI, smoking status, LVEF, nutritional status, and GFI predicts 30-day readmission risk, offering a basis for clinical intervention strategies to improve patient outcomes.

Background To find a useful hypoxia non-invasive biomarker for evaluating early treatment response and prognosis to definitive chemoradiotherapy (dCRT) in patients with esophageal squamous cell carcinoma (ESCC), using blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI). Methods The R2* values were obtained pre- and 2–3 weeks post-dCRT in 28 patients with ESCC using BOLD MRI. Independent samples t-test (normality) or Mann-Whitney U test (non-normality) was used to compare the differences of R2*-related parameters between the complete response (CR) and the non-CR groups. Diagnostic performance of parameters in predicting response was tested with receiver operating characteristic (ROC) curve analysis. The 3-year overall survival (OS) was evaluated using Kaplan Meier curve, log rank test, and Cox proportional hazards regression analysis. Results The post-R2*, ∆R2*, and ∆%R2* in the CR group were significantly higher than those in the non-CR group ( P  = 0.002, 0.003, and 0.006, respectively). The R2*-related parameters showed good prediction of tumor response, with AUC ranging from 0.813 to 0.829. The 3-year OS rate in patients with ∆R2* >-7.54 s − 1 or CR were significantly longer than those with ∆R2* ≤ -7.54 s − 1 (72.37% vs. 0.00%; Hazard ratio, HR = 0.196; 95% confidence interval, 95% CI = 0.047–0.807; P  = 0.024) or non-CR (76.47% vs. 29.27%; HR = 0.238, 95% CI = 0.059–0.963; P  = 0.044). Conclusions The preliminary results demonstrated that the R2* value might be a useful hypoxia non-invasive biomarker for assessing response and prognosis of ESCC treated with dCRT. BOLD MRI might be used as a potential tool for evaluating tumor oxygenation metabolism, which is routinely applied in clinical practice and beneficial to clinical decision-making. A large sample size was needed for further follow-up studies to confirm the findings.

IntroductionFrailty significantly influences the prognosis of elderly patients diagnosed with heart failure. The assessment of frailty is a critical initial step in the management of these patients, as a systematic and precise evaluation facilitates the identification of individuals at high risk. This identification enables timely and targeted interventions, which can subsequently reduce the likelihood of adverse cardiovascular events and improve the quality of life for elderly patients with heart failure. Nevertheless, there exists a notable deficiency in research regarding the most effective frailty assessment tools specifically for elderly patients with heart failure in China. The objective of this study is to identify the frailty assessment tool that demonstrates the highest predictive value for outcomes in this population.Methods and analysisThis study is a multicentre, prospective cohort investigation that commenced in October 2023 across three tertiary hospitals in Beijing, China. Employing a continuous enrolment strategy, the study encompasses all elderly patients diagnosed with heart failure who are undergoing either outpatient or inpatient treatment, continuing until an adequate sample size is achieved. Follow-up evaluations are scheduled every 3 months from the point of patient enrolment, extending until the 12th month post-enrolment. Comprehensive data collection, which includes demographic information, heart failure-related metrics, frailty assessments and significant biochemical test results, is conducted through face-to-face interviews at baseline.Ethics and disseminationParticipant inclusion will depend on obtaining written informed consent from the patient or guardian. The trial protocol was approved by the Central Ethics Committee of Beijing Hospital. The approval letter number is 2023BJYYEC-356-01. Outcomes of the study will be published in a peer-reviewed scientific journal.