ObjectiveTo explore the role of cuproptosis and identify cuproptosis-related genes in Wilson disease （WD） through bioinformatics analysis and clinical validation，providing implications and directions for the diagnosis and treatment of WD. Methods（1） Screening of target genes： The differentially expressed genes （DEGs） between WD and healthy control were obtained from GeneCards，and the cuproptosis-related genes were obtained from Gene Expression Omnibus （GEO） and published literature.The cuproptosis-related genes in WD were obtained by intersection.Through gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses，the specific biological process，functions or metabolic pathways of cuproptosis-related genes in WD were predicted.Molecular docking and PyMOL visualization were then performed to analyze and verify the potential regulatory mechanism of Gandou Fumu Decoction for cuproptosis.（2）Validation of target genes： The blood samples of 15 WD patients treated in the department of encephalopathy and 15 healthy volunteers undergoing physical examinations in the health management center were randomly collected from the First Affiliated Hospital of Anhui University of Chinese Medicine.The expression levels of target genes were determined by Western blot and real-time PCR. Results（1） A total of 3 607 DEGs in WD were obtained from GSE107323 in GEO，and 68 cuproptosis-related genes were obtained from GeneCards and published literature.Twelve common target genes were obtained by intersection，including three up-related genes（SQSTM1，MIF1，and TAX1BP1） and nine down-regulated genes（CP，SERPINE1，AOC3，GPX4，SLC27A5，VEGF-A，PDHB，PDK1，and ATP7B）.The common target genes were mainly enriched in monocarboxylic acid metabolism，oxidoreductase activity，negative regulation of molecular functions，which mainly involved HIF-1，ferroptosis and other signaling pathways.Molecular docking and PyMOL visualization results showed Gandou Fumu Decoction had good binding ability with the cuproptosis-related genes PDK1，SERPINE1，VEGFA，and AOC3 in WD.（2）A total of 30 blood samples were collected，including 15 WD patients and 15 health volunteers.Western blot results showed that expression levels of target genes were consistent with the results obtained by bioinformatics analysis.RT-qPCR results showed that compared with healthy volunteers，WD patients had down-regulated mRNA levels of SERPINE1，GPX4，SLC27A5，and VEGF-A and up-regulated mRNA levels of SQSTM1 and MIF1（P<0.05）. ConclusionThe expression levels of cuproptosis-related genes in WD patients are consistent with the results predicted by bioinformatics analysis.The characteristic preparation Gandou Fumu Decoction of Xin'an Medicine showed good binding abilities with the cuproptosis-related genes in WD.Cuproptosis may play a key role in the pathophysiological mechanism of WD，which can provide a new target for the diagnosis and treatment of WD.

Based on the pharmacokinetics theory, this study investigated the pharmacokinetic characteristics of albiflorin, paeoniflorin, wogonoside, and wogonin in normal and febrile rats and summarized absorption and elimination rules of Dayuanyin in them to provide reference for further development and clinical application of Dayuanyin. Blood samples were taken from the fundus venous plexus of normal and model rats after intragastric administration of Dayuanyin at different time points. The concentration of each substance in blood was determined by ultra performance liquid chromatography-triple quadrupole mass spectrometry(UPLC-MS/MS) technique at different time points. DAS 2.0, a piece of pharmacokinetics software, was used to calculate the pharmacokinetic parameters of each component. The results show that the 4 components had good linear relationship in their respective ranges, and the results of methodological investigation met the requirements. The pharmacokinetic parameters of C_(max), T_(max), t_(1/2), AUC_(0-t), AUC_(0-∞), and MRT_(0-t) were calculated by the DAS 2.0 non-compartmental model. Compared with those in the normal group, C_(max) and AUC_(0-t) of the 4 components in the model group were significantly increased. There were significant differences in the pharmacokinetic characteristics between the normal and model groups, suggesting that the absorption and elimination of Dayuanyin may be affected by the changes of internal environment of the body in different physiological states.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Fever/metabolism* ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Glucosides/pharmacokinetics* ; Monoterpenes

Based on the ultra performance liquid chromatography-quadrupole Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology, combined with related literature, databases, and reference material information, this study qualitatively analyzed the components of Dayuanyin in the tissue of rats after gavage and employed molecular docking technology to predict the rationality of the mechanism behind the antipyretic effect of the in vivo components in Dayuanyin. A total of 21, 26, 20, 21, 14, and 31 prototype components and 3, 16, 3, 7, 5, and 24 metabolites were identified from the heart, liver, spleen, lung, kidney, and hypothalamus of the rats, respectively, and the binding ability of key components and targets was further verified by molecular docking. The results showed that all components had good binding ability with targets. The established UPLC-Q-Exactive Orbitrap-MS could effectively and quickly identify the Dayuanyin components distributed in tissue and preliminarily identify their metabolites. Many components were identified in the hypothalamus, which suggested that the components delivered to the brain should be focused on in the study on Dayuanyin in the treatment of febrile diseases. The molecular docking technology was used to predict the rationality of the mechanism behind its antipyretic effect, which lays the foundation for the clarification of the material basis and action mechanism of Dayuanyin, the development of new preparations, and the prediction of quality markers.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Molecular Docking Simulation ; Male ; Antipyretics/metabolism* ; Rats, Sprague-Dawley ; Tissue Distribution ; Mass Spectrometry ; Chromatography, High Pressure Liquid ; Hypothalamus/metabolism*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

OBJECTIVE: To investigate hypertension (HTN) trends, key risk factors, and gender disparities in rural China, and to propose targeted strategies for improving HTN control in resource-limited settings. METHODS: This longitudinal study used data from the Henan Rural Cohort Study, including baseline (2015-2017; n = 39,224) and follow-up (2018-2022; n = 28,621) participants. HTN was defined as systolic/diastolic blood pressure ≥ 140/90 mmHg, self-reported diagnosis, or use of antihypertensive medication. Severity was classified using a 7-tier blood pressure (BP) staging system (optimal, normal, high normal, and HTN stages 1-4). A generalized linear mixed-effects model (GLMM) identified associated risk factors. RESULTS: HTN prevalence increased modestly from 32.7% (95% CI: 32.2-33.2) to 33.9% (95% CI: 33.3%-34.4%). Awareness and treatment improved from 20.1% to 25.3%, and from 18.8% to 24.4%, respectively, but control rates remained low (6.2% to 12.3%). After adjustment, women had a 1.53-fold higher HTN risk than men ( OR = 1.53, 95% CI: 1.43-1.63), revealing gender-specific trends. Key risk factors included alcohol use ( OR = 1.37, 95% CI: 1.27-1.47) and overweight status ( OR = 1.76, 95% CI: 1.66-1.86). BP staging showed an increase in optimal BP (42.3% to 45.8%), but stagnant management of advanced HTN stages. CONCLUSION Hypertension in rural China is shaped by behavioral risk factors and healthcare access gaps. Gender-sensitive, community-based interventions, including task-shifting models, are necessary to mitigate the growing burden of hypertension.
Humans ; Hypertension/etiology* ; China/epidemiology* ; Female ; Male ; Rural Population/statistics & numerical data* ; Prevalence ; Risk Factors ; Middle Aged ; Adult ; Aged ; Longitudinal Studies ; Sex Factors ; Cohort Studies ; East Asian People

Objective To construct and validate an interpretable machine learning model integrating contrast-enhanced venous phase CT radiomics and clinical features for preoperative prediction of central lymph node metastasis(CLNM)of papillary thyroid carcinoma(PTC).Methods A case-control study was conducted on 243 histologically confirmed PTC patients.Among them,196 patients from the First Affiliated Hospital of Army Medical University were randomly allocated into a training set(n=137)and an internal validation set(n=59)at a 7:3 ratio,while the left 47 patients from No.958 Hospital of PLA Army were assigned into an external validation set.All participants completed standardized preoperative contrast-enhanced neck CT scanning.Quantitative radiomic features were systematically extracted from venous phase CT images through an open-source big data AI platform.Six machine learning classifiers,eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM),Random Forest(RF),Logistic Regression(LR),k-Nearest Neighbors(KNN),and Decision Tree(DT)were implemented to construct clinical-radiomics integration models.The predictive performance was quantitatively assessed through receiver operating characteristic(ROC)curve analysis,with area under the curve(AUC)values calculated for training,internal validation,and external validation sets.Model interpretability was achieved using Shapley additive explanations(SHAP)framework,with particular focus on elucidating feature contributions in the best-performing model.Results The XGBoost model had an AUC value of 0.936(95%CI:0.895～0.976),0.832(95%CI:0.724～0.941),and 0.772(95%CI:0.632～0.912)in training,internal and external validation sets,respectively.SHAP analysis revealed age as the most influential clinical predictor,with younger patients showing higher CLNM risk(OR=0.968,P=0.042).Conclusion Our machine learning-based clinic-radiomic prediction model demonstrates satisfactory performance in predicting CLNM of PTC,providing valuable references for clinical decision-making.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

Objective:To compare the prognostic value of 3 diagnostic criteria of bronchopulmonary dysplasia (BPD) in preterm infants with gestational age<32 weeks.Methods:The retrospective cohort study was conducted to collect the clinical data of 285 preterm infants with BPD admitted to the Department of Neonatology, Children′s Hospital Affiliated to Zhengzhou University from January 2019 to September 2021, who were followed up regularly after discharge. The primary composite adverse outcome was defined as death or severe respiratory morbidity from 36 weeks of corrected gestational age to 18 months of corrected age, and the secondary composite adverse outcome was defined as death or neurodevelopmental impairment. According to the primary or secondary composite adverse outcomes, the preterm infants were divided into the adverse prognosis group and the non-adverse prognosis group. The 2001 National Institute of Child Health and Human Development (NICHD) criteria, 2018 NICHD criteria, and 2019 Neonatal Research Network (NRN) criteria were used to diagnose and grade BPD in preterm infants. Chi-square test, Logistic regression analysis, receiver operating characteristic (ROC) curve and Delong test were used to analyze the prognostic value of the 3 diagnostic criteria.Results:The 285 preterm infants had a gestational age of 29.4 (28.1, 30.6) weeks and birth weight of 1 230 (1 000, 1 465) g, including 167 males (58.6%). Among 285 premature infants who completed follow-up, the primary composite adverse outcome occurred in 124 preterm infants (43.5%), and the secondary composite adverse outcome occurred in 40 preterm infants (14.0%). Multivariate Logistic regression analysis showed that severe BPD according to the 2001 NICHD criteria, gradeⅡand Ⅲ BPD according to the 2018 NICHD criteria and grade 2 and 3 BPD according to the 2019 NRN criteria were all risk factors for primary composite adverse outcomes (all P<0.05). ROC curve showed that the area under the curve (AUC) of the 2018 NICHD criteria and 2019 NRN criteria were both higher than that of the 2001 NICHD criteria (0.70 and 0.70 vs. 0.61, Z=4.49 and 3.35, both P<0.001), but there was no significant difference between the 2018 NICHD and 2019 NRN criteria ( Z=0.38, P=0.702). Multivariate Logistic regression analysis showed that the secondary composite adverse outcomes were all associated with grade Ⅲ BPD according to the 2018 NICHD criteria and grade 3 BPD according to the 2019 NRN criteria (both P<0.05). ROC curve showed that the AUC of the 2018 NICHD criteria and 2019 NRN criteria were both higher than that of the 2001 NICHD criteria (0.71 and 0.71 vs. 0.58, Z=2.93 and 3.67, both P<0.001), but there was no statistically significant difference between the 2018 NICHD and 2019 NRN criteria ( Z=0.02, P=0.984). Conclusion:The 2018 NICHD and 2019 NRN criteria demonstrate good and comparable predictive value for the primary and secondary composite adverse outcomes in preterm infants with BPD, surpassing the predictive efficacy of the 2001 NICHD criteria.