Objective To investigate the relationship between tooth loss and the occurrence of esophageal cancer in a natural village in Wenfeng District, Anyang City, Henan Province. Methods A prospective cohort study was conducted to observe the occurrence of tooth loss and esophageal cancer among the asymptomatic residents of the natural village for 16 years from January 2008 to July 2024. Data were analyzed by chi-square test, binary logistic regression, and restricted cubic spline. Results Among the total population of 711 cases, 136 cases were lost to follow-up and 575 cases were included in the final statistics, including 45 cases with esophageal cancer. Significant statistical difference was found between esophageal cancer patients with and without tooth loss (P<0.05). Logistic regression analysis showed that tooth loss was associated with the occurrence of esophageal cancer (OR=3.977, 95%CI: 1.543-10.255). After the adjustment for confounders, tooth loss remained significantly associated with the occurrence of esophageal cancer (OR=3.038, 95%CI: 1.035-8.914). A nonlinear dose-response relationship was observed between the number of teeth lost and the incidence of esophageal cancer. When the number of teeth lost was less than 12, the risk of esophageal cancer increased with the number of teeth lost. When more than 12 teeth were lost, the risk of esophageal cancer decreased as the number of teeth lost increased. Conclusion Tooth loss is a risk factor for the occurrence of esophageal cancer in this natural village. When the number of teeth lost is less than 12, the risk of esophageal cancer increases with the number of teeth lost.

Although stage Ⅰ non-small cell lung cancer(NSCLC)is a type of malignant tumor that can be cured through surgical treatment,its 5-year recurrence rate is still as high as 10%-29%,with a 5-year survival rate of 77%-93.7%.Therefore,better treat-ment strategies are urgently needed to further improve the long-term survival rate of patients with stage I NSCLC.In recent years,ma-jor breakthroughs have been made in targeted therapy and immunotherapy for locally advanced NSCLC in the perioperative period.It was believed in the past that patients with stage I NSCLC had limited benefits from adjuvant chemotherapy,but there are still controver-sies over whether stage I patients can benefit from perioperative targeted therapy and immunotherapy.Therefore,Chongqing Precision Lung Oncology Group discusses the main issues in the treatment of stage I NSCLC in the perioperative period and provides related rec-ommendations,including the selection and optimization of indications for perioperative targeting therapy or immunotherapy,the formu-lation and optimization of regimens and strategies for single therapy or combined therapy,and the optimal time of perioperative target-ing therapy or immunotherapy,so as to provide guidance for clinical practice.

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

Objective To investigate the predictive value of the preoperative fasting Triglyceride-Glucose index(TyG)for contralateral new silence ischemic brain lesions(CNSIBL)following carotid artery stenting(CAS).Methods A retrospective study was conducted to analyze the clinical data of 183 patients who underwent carotid CAS.The patients were divided into a CNSIBL group(50 cases)and a non-CNSIBL group(133 cases)based on the occurrence of CNSIBL.Baseline data,laboratory tests,and imaging indicators were collected,and TyG was calculated.Using the occurrence of CNSIBL as the dependent variable,multivariate logistic regression analysis was performed with TyG as the independent variable after controlling for confounding factors,and the predictive value of TyG for CNSIBL post-CAS was evaluated using receiver operating characteristic(ROC)curves.Results(1)The number of patients with a history of diabetes mellitus,as well as systolic and diastolic blood pressure on admission in CNSIBL group were statistically significantly higher than that in non-CNSIBL group(P<0.05).(2)Triglyceride(TC)levels were higher in the CNSIBL group compared to the non-CNSIBL group(P<0.05);TyG was also higher in the CNSIBL group than in the non-CNSIBL group(P<0.05);(3)Multivariate Logistic regression analysis results showed that TyG[a OR=1.125,95%CI(1.042-1.214),P<0.001]was an independent risk factor for contralateral new silent ischemic brain lesions after carotid artery stenting;(4)The ROC curve suggested that the AUC for TyG predicting contralateral new silent ischemic brain lesions post-CAS was 0.77[95%CI(0.71-0.84),P<0.001],with a cut-off value of 1.93,sensitivity of 86.0%,and specificity of 63.9%.Conclusion TyG is an independent influencing factor for contralateral new silent ischemic brain lesions following carotid artery stenting.

Objective:To investigate the association of the interaction and combined effect of renal function and body mass index (BMI) with the risk for all-cause death in patients with type 2 diabetes mellitus (T2DM) in communities of Jiangsu Province.Methods:The study subjects were from the Comprehensive Research Project of Diabetes Prevention and Control conducted in Jiangsu from December 2013 to January 2014, and follow up was conducted for them until September 30, 2023. A total of 20 025 subjects were included in the study. Cox proportional hazards regression model was used to analyze the association of renal function with risk for death in T2DM patients, and the association of interaction between renal function and BMI and their combined effect with all-cause death risk in T2DM patients.Results:In the follow up for 198 370 person-years, a total of 4 459 deaths were recorded. Cox proportional hazards regression model analysis showed that renal dysfunction was associated with 71% risk of all-cause mortality in all T2DM patients [hazard ratio ( HR) =1.71, 95% CI: 1.59-1.84], as well as in all BMI subgroups. Likelihood ratio test indicated an interaction between renal function and BMI (interaction for P=0.030). Compared with patients with normal renal function and normal BMI, those with normal renal function and over weight or obesity had a lower risk of all-cause mortality, and those with renal dysfunction and low weight had the highest risk for death ( HR=2.78, 95% CI: 1.87-4.14). Conclusions:There is association of interaction between renal function and BMI with all-cause mortality in T2DM patients. T2DM patients with renal dysfunction and low body weight had significant higher risk for death.

Objective:To investigate the expression and methylation status of the SALL4 gene in placental tissues of fetal growth restriction (FGR) and its effects on trophoblast cell proliferation, migration, and invasion. Methods:Placental tissues were collected from 20 full-term FGR patients and 20 healthy term controls who underwent regular prenatal examination and cesarean section at the Third Affiliated Hospital, Zhengzhou University between July 2023 and February 2024. SALL4 mRNA and protein expression were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. Methylation specific polymerase china reaction (MSP) assessed promoter methylation levels. HTR8/SVneo cells were transfected with SALL4-targeting small interfering RNA (si-SALL4) or negative control small interfering RNA (si-NC). HTR8/SVneo cells were treated with the demethylating agent 5-aza-2′-deoxycytidine (5-Aza-dC) to inhibit gene methylation (5-Aza-dC group) or with 10% RPMI-1640 medium as a vehicle control. Transfection efficiency (for siRNA) and the efficacy of 5-Aza-dC-induced demethylation were assessed by qRT-PCR and Western blot. The functional effects of SALL4 knockdown and methylation inhibition on trophoblast cells were evaluated using proliferation assays, scratch wound healing assays, and Transwell invasion assays. Statistical analyses included independent t-tests and Chi-square test. Results:(1) Human tissues: FGR placentas showed lower SALL4 mRNA (0.802±0.194 vs. 1.015±0.186, t=3.55) and protein expression (0.445±0.114 vs. 0.701±0.113, t=3.19), alongside higher methylation rates of SALL4 [80% (16/20) vs. 15% (3/20), χ2=14.44] compared to controls (all P<0.05). (2) In vitro: si-SALL4 transfection reduced HTR8/SVneo proliferation (OD450 at 48 h: 0.653±0.021 vs. 0.827±0.040, t=6.60), migration [healing rate at 48 h: (24.317±2.637)% vs. (49.327±1.961)%, t=13.18], and invasion [counted invaded cells: (133.000±6.557) vs. (272.667±18.009) cells, t=12.62] versus si-NC (all P<0.05). Conversely, 5-Aza-dC treatment increased HTR8/SVneo proliferation (0.917±0.042 vs. 0.783±0.031, t=－4.47), migration [(71.097±3.354)% vs. (51.632±2.877)%, t=－7.63], and invasion [(384.000±12.166) vs. (202.833±7.095) cells, t=－13.69] versus vehicle control (all P<0.05). Conclusions:Hypermethylation of the SALL4 promoter in FGR placentas suppresses its expression, impairing trophoblast cell function. Demethylation restores SALL4 expression and enhances cellular proliferation, migration, and invasion, involving in the occurrence and development of FGR disease.

Objective:To define the concept of proactive health behavior.Methods:Literature related to proactive health behavior was retrieved from China National Knowledge Infrastructure, Wanfang Data, VIP, SinoMed, PubMed, Web of Science, Embase, and Ovid databases, with a retrieval time frame from database inception to March 1, 2025. Walker and Avant's concept analysis method was used to analyze the concept of proactive health behavior.Results:A total of 46 articles related to proactive health behavior were included. Proactive health behavior encompasses five key attributes: self-initiation, long-term persistence, multidimensional integration, future orientation, and overcoming barriers. Antecedents include individual factors, supportive factors, and environmental factors. Outcomes include promoting individual health and improving quality of life, enhancing personal health literacy, reducing disease burden, and fostering a proactive health atmosphere.Conclusions:The concept attributes of proactive health behavior were clarified through concept analysis. Future researchers may develop proactive health behavior assessment tools and construct intervention strategies based on their connotation.

Objective To analyze the influencing factors of health behaviors in stroke patients,and explore the chain mediating effects of self-efficacy and e-health literacy between the perception of stroke recurrence risk and health behaviors in stroke patients,providing a reference for strengthening the health behavior and reducing recurrence risk in stroke patients.Methods 249 stroke patients were selected as the research objects from March to September 2024 in a tertiary hospital in Shanghai,China.Patients were surveyed using General Information Questionnaire,Stroke Recurrence Risk Perception Scale,Stroke Health Behavior Scale(HBS-SP),Chronic Disease Self-Efficacy Scale(CDSES),and the e-health Literacy Scale(e-HEALS).Pearson correlation analysis was used to explore the correlations among various variables,and SPSS 26.0 software macro program Process Model 6 was used to conduct chain mediation model test.Results The scores of Recurrence Risk Perception,HBS-SP,CDSES and e-HEALS of stroke patients were(42.88±6.48)scores,(68.32±14.13)scores,(6.87±1.55)scores and(27.76±6.06)scores,and all the variables were positively correlated(P<0.01).The mediating effect model showed that self-efficacy and e-health literacy played a chain mediating role in the recurrence risk perception and health behavior in stroke patients,with an effect size of 0.488,accounting for 37.22%of the total effect.Conclusions The recurrence risk perception and health behavior of stroke patients are both at a moderate level.In the future,we can establish a mobile management platform to provide comprehensive health management for stroke patients.Further exploration of strategies to enhance stroke patients'self-efficacy and channels for online health education could be pursued to improve their health behaviors.

Objective:To define the concept of proactive health behavior.Methods:Literature related to proactive health behavior was retrieved from China National Knowledge Infrastructure, Wanfang Data, VIP, SinoMed, PubMed, Web of Science, Embase, and Ovid databases, with a retrieval time frame from database inception to March 1, 2025. Walker and Avant's concept analysis method was used to analyze the concept of proactive health behavior.Results:A total of 46 articles related to proactive health behavior were included. Proactive health behavior encompasses five key attributes: self-initiation, long-term persistence, multidimensional integration, future orientation, and overcoming barriers. Antecedents include individual factors, supportive factors, and environmental factors. Outcomes include promoting individual health and improving quality of life, enhancing personal health literacy, reducing disease burden, and fostering a proactive health atmosphere.Conclusions:The concept attributes of proactive health behavior were clarified through concept analysis. Future researchers may develop proactive health behavior assessment tools and construct intervention strategies based on their connotation.

Objective:To construct service quality evaluation indicators for brain-heart health management outpatient clinics, providing a reference for the standardized, high-quality management and evaluation of brain-heart health management clinics.Methods:Based on Donabedian's "structure-process-outcome" three-dimensional quality evaluation theory, the initial evaluation indicators were drafted after reviewing relevant literature and conducting qualitative interviews. After two rounds of Delphi expert consultation, the final service quality evaluation indicators for brain-heart health management outpatient clinics were established.Results:The effective response rate for the questionnaires from both rounds of expert consultation was 100.00% (15/15). The experts' authority coefficients were 0.925 and 0.930, respectively, the variation coefficients of the indicators were 0 to 0.21 and 0 to 0.19, and the Kendall concordance coefficients were 0.231 and 0.219 ( P<0.01). The final service quality evaluation indicators for brain-heart health management outpatient clinics included three primary indicators, nine secondary indicators, and 23 tertiary indicators, with specific definitions for the tertiary indicators. Conclusions:The service quality evaluation indicators for brain-heart health management outpatient clinics constructed in this study are scientific and reliable. The indicators reflect the specialty of brain-heart health management and highlight the professional value of brain-heart health managers, providing a reference for the high-quality development of brain-heart health management.