搜索结果：predicts

Somatic mutations rewire the ubiquitin-proteasome system (UPS) to support tumor growth, but the proteome-wide consequences of cancer-driver alterations on UPS composition remain incompletely understood. Using harmonized proteogenomic data from up to 11 CPTAC cohorts, we performed an integrated pan-cancer analysis of UPS protein dysregulation, prognostic associations, and mutation-driven remodeling. We show that mRNA poorly predicts UPS protein abundance, that a defined set of E3 ligases is recurrently dysregulated across cancers, and that somatic mutations (most strikingly TP53 loss) produce coherent UPS protein-quantitative trait locus (pQTL) signatures. Two case studies (UBR5 and TRIM28) illustrate orthogonal modes of UPS rewiring: a mutation-driven axis in which TP53-mutant tumors elevate UBR5 to support replication stress tolerance, and a lineage-driven axis in which TRIM28 engages tissue-restricted regulatory networks with opposing prognostic effects in glioblastoma versus head and neck cancer. Each axis exposes context-specific therapeutic vulnerabilities, including sensitivity to DNA damage response inhibitors (UBR5-high) and lineage-specific drug responses (TRIM28-high). Together, these analyses define a mechanistic framework for how cancer-driver mutations reshape proteostasis through the UPS and nominate mutation- and lineage-defined dependencies for precision degrader therapy. The harmonized pan-tissue atlas and the UbiDash interactive resource that underpin parts of this analysis are reported in our companion paper [1].

Manganese metabolism may be involved in the malignant progression of lung adenocarcinoma (LUAD). Clarifying the roles of manganese metabolism-related genes (MMRGs) in LUAD may provide potential therapeutic targets for LUAD treatment. Mendelian randomization analysis and machine learning methods were applied to analyze transcriptome data for screening prognosis-related genes in LUAD. Subsequently, a risk model was constructed and a nomogram was plotted. Meanwhile, a series of analyses were carried out focusing on the immune microenvironment, drug sensitivity, and the single-cell level. Finally, the expression of relevant proteins was further verified by combining RT-qPCR and Western Blot. We have screened out six risk genes for LUAD: TXNRD1, CDKN3, BTG2, SELENBP1, DTYMK, and CHEK1. Subsequently, a risk model was constructed, which effectively predicts the survival of LUAD patients. Gene Set Enrichment Analysis (GSEA) revealed that these six genes may be involved in the regulation of the cell cycle in LUAD. In addition, they may modulate the tumor immune microenvironment and induce resistance to chemotherapeutic drugs. RT-qPCR and Western Blot confirmed low BTG2 and SELENBP1 and high CDKN3, CHEK1, DTYMK, and TXNRD1 expression in LUAD tissues and cell lines. Our study indicates that TXNRD1, CDKN3, BTG2, SELENBP1, DTYMK, and CHEK1 may be important biomarkers for the prognosis of LUAD, providing potential approaches for prognostic evaluation and medication strategies in LUAD.

With the continuous deepening of the digital transformation of higher education, college physical education teachers in China are increasingly integrating digital technologies into their teaching practice. However, the explanatory pathways through which digital competence is associated with job satisfaction in digitally mediated work contexts remain insufficiently understood. This study, grounded in the job demands-resources (JD-R) model, examines how facilitating conditions, behavioral intention, teaching self-efficacy, and technostress are linked to job satisfaction through the mediation of digital competence. Using cross-sectional survey data from 523 physical education teachers across 10 Chinese universities, the hypothesized relationships were tested through partial least squares structural equation modeling (PLS-SEM). The results indicate that facilitating conditions, behavioral intention, and teaching self-efficacy positively predict digital competence and job satisfaction, while digital competence mediates their relationships with job satisfaction. Technostress, in contrast, negatively predicts job satisfaction and weakens the positive effect of digital competence on job satisfaction. The findings suggest that digital competence plays an important role in shaping job satisfaction among college physical education teachers, while technostress acts as a constraining factor in this process. This study offers theoretical and practical insights into the digital transformation of college physical education teachers.

Islands with contrasting herbivore histories provide a natural framework to investigate the evolution of plant defenses. Theory predicts that on islands with historically intense vertebrate herbivory, juveniles maintain strong defenses while adults may reduce them once out of reach, whereas islands lacking vertebrate browsers show minimal ontogenetic differences and generally lower defenses. Alternatively, when extinct herbivores were particularly large, selection might also favor stronger adult defenses. Despite these theoretical expectations, empirical tests across multiple island systems remain scarce. In this study, we quantified leaf physical, chemical, and nutritional traits related to resistance and palatability in juvenile and adult individuals of 60 woody plant species across 33 families from six archipelagos: three with extinct large herbivores (New Zealand, New Caledonia, Mauritius) and three without vertebrate browsers (the Canary Islands, Azores, Channel Islands of California). We found that species from islands with historical herbivory exhibited overall lower defenses, with trait expression strongly shaped by ontogeny. Adults displayed higher phenolic concentrations and lower nutrient content than juveniles, reducing leaf palatability. By contrast, species from islands lacking herbivores showed no ontogenetic variation. These results reveal the lasting evolutionary legacy of extinct herbivores and show how herbivore history and ontogeny shape island plant defenses.

Most pediatric emergency departments (EDs) in the United States use Emergency Severity Index (ESI) system to triage patients. Because the 5-level classification provides limited risk stratification, this study aims to improve patient prioritization by developing an operationally useful model that predicts risk of critical care interventions using only information available during ED triage. We conducted a retrospective study at a large urban academic pediatric ED from 2016 to 2024. We developed predictive models using 6 machine learning (ML) algorithms. Models were evaluated on Average Precision and tradeoff between sensitivity and positive predictive value (PPV). We performed a counterfactual analysis to assess potential clinical effects of risk predictions on timeliness of evaluation for critical care patients. Among 886 183 ED visits, 26 721 (3.0%) received critical care interventions. The neural network had the highest Average Precision of 0.6 (95% CI 0.59-0.61). The model could identify 88% (87%-89%) of patients who received critical care interventions with PPV of 32% (31%-32%). Supplementing ESI with these risk predictions would have increased the proportion of critical care patients being timely evaluated by physicians from 23.3% to 75.0% for ESI 3 patients. Similarly, improvements would have been achieved for other ESI levels. We developed models capable of quickly identifying ED pediatric patients at risk of requiring critical care interventions without causing alarm fatigue. Potential improvements in time-to-pediatrician for at-risk patients suggest utility of our ML-support triage framework in improving patient care and safety in pediatric ED.

Frailty is a clinical syndrome of reduced physiological reserve in older adults for which no pharmacological treatment exists and whose cellular basis remains incompletely defined. As life expectancy rises without a comparable extension of healthspan, the absence of a mechanistic account able to guide targeted intervention is a growing clinical problem. The dominant model of primary mitochondrial bioenergetic insufficiency does not accommodate several features of the phenotype. Among the conditions most strongly associated with frailty in aging, obesity, particularly when coupled with sarcopenia, stands out for its rising prevalence and the depth of its systemic metabolic consequences. Drawing on a recent multi-omics characterisation of skeletal muscle in sarcopenic obesity and on the convergent literature in aging metabolism, organelle communication, and redox biology, we propose a complementary framework in which the proximate cellular abnormality of frailty is energetic congestion, a chronic mismatch between substrate input, energetic demand, and the capacity to dispatch the resulting flux through demand-driven oxidative metabolism. In this view the mitochondrion is not failing because fuel is scarce, but because energetic demand declines below the rate at which substrate continues to be delivered, so that substrate persists in relative rather than absolute excess, while mitochondrial adaptability is progressively impaired. The resulting cycle is self-amplifying, anchored in reverse electron transport, and generalises across skeletal muscle, adipose tissue, liver, heart and brain. Strategies that re-engage demand-driven metabolic flux through AMPK activation, substrate restriction, mild mitochondrial uncoupling, modulation of endoplasmic reticulum stress, and clearance of irreversibly congested cells are predicted to produce more durable benefits than energy supplementation, with structured exercise as the prototype of demand-driven recoupling. This perspective offers a path toward a precision pharmacology of frailty grounded in molecular stratification of patients.

Despite non-selective beta-blockers (NSBBs), patients with cirrhosis and portal hypertension (PH) remain at substantial risk of death. Statins may improve intrahepatic microcirculation and potentially complement NSBB effects. We searched PubMed, Web of Science, Embase, Cochrane Library, and ClinicalTrials.gov from inception to October 2025 for randomized controlled trials (RCTs) comparing NSBB-based therapy plus statins versus NSBB-based therapy alone. Rare events were synthesized using fixed-effect Peto odds ratios; other outcomes were pooled with random-effects models, with prediction intervals (PI) reported. Prespecified subgroup and sensitivity analyses were performed. Seven RCTs (n&#x202f;=&#x202f;954) were included. Statin add-on therapy was not clearly associated with fewer PH-related complications, including variceal bleeding (RR&#x202f;=&#x202f;0.79, P&#x202f;=&#x202f;0.10), new or worsening ascites (RR&#x202f;=&#x202f;0.81, P&#x202f;=&#x202f;0.13), or hepatic encephalopathy (RR&#x202f;=&#x202f;0.41, P&#x202f;=&#x202f;0.06). However, it was associated with a lower risk of all-cause mortality (RR&#x202f;=&#x202f;0.46, 95% CI: 0.32-0.65, 95% PI: 0.28-0.76, P < 0.001, I2&#x202f;=&#x202f;0). Adding statins also resulted in greater hepatic venous pressure gradient (HVPG) reductions and a higher proportion of patients achieving a &#x2265; 20% HVPG decrease. Aches and transaminase elevations occurred more often with statins. In subgroup analyses, the mortality association was observed in Child-Pugh A/B patients. In cirrhosis with PH, statin add-on therapy is associated with improved portal hemodynamics and lower all-cause mortality, whereas associations with PH-related complications remain uncertain. CRD420251172719.

Congenital heart disease is a leading cause of infant death, arising from genetic and environmental factors. GenX, a replacement for legacy pollutants, is now a widespread contaminant. However, its cardiovascular risks are poorly understood. This study integrated network toxicology and experimental models to investigate the mechanisms of GenX-induced heart defects, focusing on its interaction with genes linked to common CHD subtypes. Network toxicology analysis, including protein-protein interaction network construction, hub gene identification, and functional enrichment, prioritized the JAK2-STAT3 signaling pathway for focused mechanistic validation, with JAK2 as the central candidate. Molecular docking suggested that GenX can bind to the JAK2 catalytic region, and ruxolitinib was used as a positive-control reference compound to benchmark the predicted JAK2 binding site. Subsequent molecular dynamics simulations demonstrated the stability and key interaction dynamics of the GenX-JAK2 complex. The experimental validation was performed in vivo and in vitro. Exposure of transgenic zebrafish larvae Tg(myl7:eGFP) and Tg(flk1:eGFP) to a tiered GenX concentration range, including an environmentally relevant concentration and higher exploratory concentrations, resulted in cardiac malformations, including pericardial edema and looping defects, alongside impaired vascular integrity. In human AC16 cardiomyocytes and zebrafish larvae, GenX exposure inhibited JAK2-STAT3 axis phosphorylation and activation, leading to increased caspase-3 activity and apoptotic cell death. Crucially, co-treatment with the JAK2 agonist butyzamide effectively rescued the signaling suppression and apoptotic phenotype induced by GenX. Our findings establish, for the first time, that the emerging contaminant GenX exerts cardiovascular developmental toxicity by directly targeting and inhibiting the JAK2-STAT3 pathway. This study delineates a novel molecular mechanism and identifies JAK2 agonism as a potential countermeasure against the cardiac hazards posed by this widespread environmental PFAS.

Skull base reconstruction after endoscopic resection of sinonasal tumors remains challenging, particularly in preventing cerebrospinal fluid leaks. Autologous grafts are traditionally favored, whereas non-autologous materials may reduce donor-site morbidity with similar success. In this study, we explore surgical outcomes in patients undergoing unilateral resection of sinonasal tumors reconstructed with the septal flip flap (SFF), focusing on the impact of graft type on the efficacy and safety of the reconstructive strategy. This multicenter retrospective cohort study included adult patients with malignant sinonasal tumors treated via unilateral endoscopic resection and SFF reconstruction. Clinical and surgical variables were analyzed to identify predictors of early postoperative complications and factors influencing hospitalization using univariate and multivariate methods. A total of 133 patients were included. Early postoperative complications occurred in 9.7%, with 4.5% related to skull base reconstruction. No variables, including graft type, significantly predicted SB-related complications in univariate logistic regression. Autologous grafts were associated with increased use of adjuvant radiotherapy (67.1% vs. 36.8%, p&#x2009;=&#x2009;0.015). Conversely, the median hospitalization was 7 days. Dura mater resection, autologous graft use, early complications, and prior treatment were independent predictors of prolonged hospitalization at multivariate linear regression. This multicenter study confirms SFF as a reliable and safe option for anterior skull base reconstruction following unilateral sinonasal malignancy resection. The technique achieved robust closure, no flap necrosis, and low reconstruction-related complication rates. Graft type did not significantly influence outcomes, although autologous grafts provided better integration in patients receiving adjuvant radiotherapy, while non-autologous substitutes proved equally safe and effective in selected unimodal settings.

Continuous biomanufacturing is gaining significant attention in biopharmaceutical production, offering enhanced productivity, scalability, and process consistency compared with conventional batch and fed-batch operations. Regulatory initiatives, including the FDA's Quality by Design (QbD) framework and the ICH Q13 guideline, emphasize the need for robust operational control to ensure consistent product quality under continuous processing. Within this context, process control has advanced from conventional feedback approaches to advanced model-based and data-driven strategies, such as model predictive control (MPC) and reinforcement learning (RL). This review provides a comprehensive and systematic analysis of control strategies for continuous biopharmaceutical manufacturing, across unit operations from upstream cell culture to downstream purification. Key control objectives and representative case studies are discussed for each unit operation, emphasizing their roles in maintaining stable operation and product quality. Furthermore, this review discusses how advanced process analytical technologies (PAT), model-based control, and digital twin (DT) frameworks can be integrated into sensing-modeling-control architectures tailored to interconnected and long-duration continuous biomanufacturing. This perspective provides a basis for developing predictive, adaptive, and risk-aware control systems that support a sustained state of control in continuous biopharmaceutical manufacturing.

This study proposes a hybrid AI model which integrates Graph Neural Networks and Transformer models to predict the economic consequence of the disruption of the supply chains with unprecedented accuracy (MAPE: 3.7%). The framework is based on multi-dimensional data from 137 companies in 23 countries, and shows the non-linear cascading effects as well as the difference between output and throughput effects. There's a dynamic resilience scoring system (91.4% accuracy) and customized explainability techniques (attributional, counterfactual and strategic) for actionable insights. Empirical tests confirm that the prediction of the impacts of the earthquakes in the long term is improved by 27.3% compared to the traditional econometric model and the ML model. The work takes a theoretical approach to resilience and connects it with tangible economic results, providing relevant policy makers with tools to reduce risks and increase stability. Its contributions encompass an economic consequences layer to enable economic interpretation, a propagation model for disruption effects, and a scalable architecture for global supply chains. The framework's effectiveness at industry and geographical levels highlights its relevance for strategic and operational decision making.

The ratio of serum sodium to log(D-dimer) (log-SDR) in different types of chronic heart failure (CHF) is not well established. A total of 1,221 hospitalized CHF patients from the First Affiliated Hospital of Kunming Medical University between January 2017 and October 2021 were retrospectively analyzed. Patients were categorized into log-SDR-L group (log-SDR&#x2009;<&#x2009;47.90) and log-SDR-H group (log-SDR&#x2009;&#x2265;&#x2009;47.90).Prognostic assessments included Kaplan-Meier survival analysis, Cox survival analyses and time-dependent Receiver operating characteristic (ROC) curves analysis to evaluate predictive performance. We collected data from 1008 patients with CHF. Kaplan-Meier survival analysis revealed that patients with high log-SDR levels had better overall survival (OS). After multivariate adjustment Cox proportional hazards analysis, the level of log-SDR was still independently related to mortality, regardless of CHF subtype. log-SDR is an important predictor of all-cause mortality in patients with HF, especially female HFrEF plus HFmrEF(HR:0.927, 95%CI:0.898-0.958, p&#x2009;<&#x2009;0.001). Lower log-SDR levels are associated with an increased risk of all-cause mortality, irrespective of the HF subtype.

暂无摘要（点击查看详情）

Head and neck squamous cell carcinoma (HNSCC) involves complex dysregulation of metabolic, inflammatory, and proliferative pathways, limiting the effectiveness of single target therapies. Medicinal plants containing multiple bioactive compounds may provide complementary strategies to modulate cancer related networks. Hemidesmus indicus (H. indicus) has been reported to have anticancer activity, but its relevance to HNSCC remains insufficiently defined. HNSCC-related targets of H. indicus phytochemicals were identified using an integrated network pharmacology approach. Drug-likeness, pharmacokinetics, and toxicity were assessed, followed by protein-protein interaction analysis, functional enrichment, gene expression, survival, and druggability evaluation. Molecular docking was performed against prioritized hub targets. Experimental validation was performed in KB cells using an MTT cytotoxicity assay, acridine orange/ethidium bromide staining, Rhodamine 123 mitochondrial membrane potential analysis, and quantitative real-time PCR. Eighty-five overlapping targets between H. indicus phytochemicals and HNSCC genes were identified, with PPARG, PTGS2, PPARA, HMGCR, and MAPK3 emerging as hub genes. Enrichment analyses highlighted roles in metabolic regulation, inflammatory signaling, and cancer-associated pathways. Docking studies demonstrated moderate to favorable binding of selected phytochemicals to PPARA and PTGS2. In vitro assays showed concentration-dependent cytotoxicity, apoptotic morphological changes, and mitochondrial membrane depolarization in KB cells. qPCR revealed increased PPARA expression and reduced PTGS2 expression. These findings provide preliminary support for the potential relevance of H. indicus in HNSCC research and emphasize the need for further in vivo and mechanistic investigations.

Intention to use contraceptives reflects an individual's or couple's plan to adopt contraceptive methods, supporting women's reproductive autonomy. It is associated with reduced unintended pregnancies, unsafe abortions, and high fertility rates, thereby improving maternal and infant health outcomes. Machine learning approaches can strengthen prediction accuracy and support evidence-based reproductive health planning. This study aimed to predict women's intention to use contraceptives in East Africa using machine-learning methods. We analyzed Demographic and Health Survey (DHS) data from 11 East African countries (2015-2024) in a community-based cross-sectional design. Country-specific sampling weights, stratification, and clustering were applied to account for the complex survey design. Missing data were imputed using the KNNImputer, and predictors were harmonized across surveys. Data preprocessing included cleaning, transformation, integration, and one-hot encoding, with an 80/20 train-test split. Seven machine learning algorithms were evaluated: adaptive boosting, CatBoost, random forest, light gradient boosting, extreme gradient boosting, logistic regression, and decision tree. Hyperparameters for CatBoost were tuned using Bayesian optimization under stratified 10-fold cross-validation. Model transportability was assessed using leave-one-country-out cross-validation. Among 123,290 reproductive-age women in East Africa, 51.23% reported intention to use contraceptives. Boosted tree algorithms performed best, particularly CatBoost achieving the highest discrimination with an AUC of 80.09% and an accuracy of 73.48%. Leave-one-country-out cross-validation confirmed moderate transportability with an AUC 74%, while calibration analysis showed reliable probability estimates (Brier score 0.179). SHAP feature importance identified employment, education, age, hearing about family planning, pregnancy, breastfeeding, barriers to healthcare access, and fertility preference as the most influential predictors of contraceptive intention. This study provides a transparent, reproducible framework for pooled DHS prediction modeling, offering actionable insights for policymakers and health planners while serving as a methodological foundation for future applied work.

暂无摘要（点击查看详情）

Prior&#xa0;studies comparing different imaging modalities in assessing axillary response&#xa0;after neoadjuvant systemic therapy (NST) in locally advanced breast cancer (LABC) are limited. This study evaluated the efficacy of different imaging modalities in identifying residual lymphadenopathy after NST in modern cohort of LABC patients. A retrospective review was performed examining LABC patients undergoing NST followed by surgical axillary staging from 2018 to 2023. Patients with LABC (T3-4,N1-3 or any T stage with N2-3 disease) were included. Inflammatory breast cancer&#xa0;was excluded. The efficacy of US, MRI, and PET/CT in evaluating residual nodal disease and the variables associated with radiologic-pathologic concordance were analyzed. A total of 101 patients meeting inclusion were identified. Post-NST imaging included US (n = 57), MRI (n = 53), and PET/CT (n = 45). Ultrasound had the highest sensitivity of 71% and positive predictive value of 76%. PET/CT had the highest specificity of 73% and negative predictive value of 70%. MRI had the lowest performance in all diagnostic measures. There was a significant relationship between complete imaging response (CIR)-pathologic complete response (pCR) concordance and pretreatment nodal status (&#x3c7;2(57) 8.9,&#xa0;p = 0.01). Higher N stage&#xa0;was associated with CIR-pCR concordance with cN3 disease having the highest odds compared with cN1 disease (OR 6.2,&#xa0;p = 0.006). The absence of lymphovascular invasion was associated with CIR-pCR concordance (OR 9.2,&#xa0;p = 0.008). Post-NST imaging provides valuable information on treatment response in LABC. However, CIR should not preclude surgical axillary evaluation. Further studies investigating the relationships between pre-treatment nodal status in LABC patients and radiologic-pathologic complete response after NST are warranted.

Due to its suitable half-life of 3.62&#xa0;min and positron emission, 128Cs (I&#x3b2;+ = 61%; E&#x3b2;+ = 2.885&#xa0;MeV) is a favorable radionuclide for applying in positron emission tomography (PET) imaging. In this work, the production 128Cs radionuclide via the indirect reaction of 133Cs(p,6n)128Ba&#x2192;128Cs and two new direct reactions of 127I(3He,2n)128Cs and 127Xe(d, n)128Cs was predict using the Monte Carlo GEANT4-10.7 toolkit, the Monte Carlo SRIM-2013-Pro code, the EMPIRE-3.2.3 software, and the TALYS-2.0 package. The range and stopping power values of protons, deuterons, and 3He particles within the 133Cs, 127Xe, and 127I targets were calculated by the GEANT4 and SRIM codes. Moreover, the cross-section of the mentioned reactions was computed utilizing the GEANT4, EMPIRE, TALYS (OMPs, BSFGM, CGCM, and GSM models) codes. To estimate the production yield of the mentioned reactions, the optimum energy range for the 133Cs(p,6n)128Ba&#x2192;128Cs, 127I(3He,2n)128Cs, and 127Xe(d, n)128Cs reactions were selected (48-68&#xa0;MeV), (5-10&#xa0;MeV), and (9-20&#xa0;MeV), respectively. The previous experimental cross-section and production yield of the 133Cs(p,6n)128Ba&#x2192;128Cs reaction was compared with the present simulated values of the GEANT4, TALYS, and EMPIRE codes. A good compatibility between the experimental data and simulated values was observed. The good agreement between the experimental data and simulated results is a proof that using a combination of nuclear codes like GEANT4, SRIM, TALYS, and EMPIRE for studying the nuclear reactions can be a good method before performing them practically.

Taste dysfunction affects quality of life, yet its biological development remains poorly understood. We investigated clinical and biochemical differences between 50 patients with idiopathic dysgeusia and 102 healthy controls (110 women, 42 men; mean age 46.4 &#xb1; 1.4 years). Each participants underwent a clinical anamnesis, a taste test, and a blood analysis. Patients were older (61 vs. 39 years; p < 0.001) and more often female (86% vs. 66%; p = 0.009). Patients had lower Taste Strips scores, and higher scores on depression (Beck Depression Index) and mood-related questionnaires (Zerssen Mood Scale; both p < 0.001). Blood analyses revealed that patients had higher levels of complement C4 (p = 0.011) and calcium (p = 0.019 ANCOVA, age-controlled). A logistic regression model including age, gender, C4, Ca, K, and transferrin predicted taste dysfunction with high accuracy (Nagelkerke R&#xb2;=0.74; 91.4% correctly classified). Increased age, higher C4 and female sex were associated with higher odds of taste dysfunction, while higher potassium, transferrin levels, and salivary calcium were protective (p &#x2264; 0.030). These findings suggest that taste dysfunction is accompanied by systemic inflammatory conditions and lower levels of electrolytes in serum may contribute to development of taste diseases. Overall, the results suggest that idiopathic dysgeusia appears to be related to metabolic imbalance.