Objective: To explore the comorbidity and associated factors of dental caries and overweight/obesity among primary and secondary school students in Guangxi, so as to provide a scientific basis for the development of targeted prevention strategies. Methods: A stratified cluster random sampling method was used to survey 178 700 students from the fourth grade of primary school to the third year of high school in Guangxi Zhuang Autonomous Region from September to November 2023, including physical examination, oral screening, and questionnaire survey. Chisquare tests and binary Logistic regression analysis were employed to investigate the related factors of the cooccurrence of dental caries and overweight/obesity among students. Results: The comorbidity rate of dental caries and overweight/obesity was 9.55%, with urban areas (9.95%) higher than rural counties (9.24%), boys (10.54%) higher than girls (8.54%), primary school students (11.49%) higher than senior high school students (8.92%) and junior high school students (8.05%), and nonboarding students (11.44%) higher than boarding students (7.94%), and all differences were statistically significant (χ2=26.07, 207.91, 471.54, 629.14,P<0.01). Multivariate Logistic regression analysis showed that consuming cereal for breakfast (OR=0.91, 95%CI=0.88-0.94), drinking milk in the past week (OR=0.89, 95%CI=0.83-0.95), meeting sleep standards (OR=0.95, 95%CI=0.91-0.99), and brushing teeth at least once a day (OR=0.82, 95%CI=0.73-0.93) had a lower risk of the comorbidity of dental caries and overweight/obesity. In contrast, drinking beverages in the past week (OR=1.14, 95%CI=1.09-1.20), consuming fried foods in the past week (OR=1.11, 95%CI=1.06-1.17), eating fruit ≥1 time every day (OR=1.06, 95%CI=1.02-1.11), consuming fruit ≥1 type every day (OR=1.07, 95%CI=1.01-1.12), and having fish, poultry, meat, or eggbased breakfasts (OR=1.03, 95%CI=1.05-1.13) had a higher risk of the comorbidity of dental caries and overweight/obesity (P<0.05). Conclusions Dietary habits and lifestyle behaviors are associated with the comorbidity of dental caries and overweight/obesity among primary and secondary school students in Guangxi. Guiding students to form healthy living habits is helpful to preven dental caries and overweight/obesity.

Objective To determine the rules of acupoint selection for hiccup based on data mining.Methods From the acupuncture and moxibustion sections of 53 medical books included in the 5th edition of Chinese Medical Classics,entries related to acupuncture treatment for hiccups was screened and constructed a"Classical Chinese Medicine Database for Acupuncture Treatment of Hiccups."Data mining techniques,including cluster analysis and association rule analysis,were employed to study the characteristics and patterns of acupoint selection for hiccup treatment in ancient medical texts.Results A total of 126 prescriptions were collected,involving 65 acupoints with a total application frequency of 172 times.The most frequently selected acupoints were Taiyuan(LU9),Shaoshang(LU11),Shiguan(KI18),Wenliu(LI7),Laogong(PC8),and Zusanli(ST36).The primary meridians used were the conception vessel(CV1)and the lung meridian of hand-taiyin.The most commonly stimulated body regions were the upper limbs and the chest/abdomen.Among special acupoint categories,the five-shu points and crossing points were predominantly utilized.Cluster analysis identified two significant clusters:Daling(PC7)-Ximen(PC4)-Yuji(LU10),and Qimen(LR14)-Chengjiang(CV24)-Dadun(LR1)-Guanyuan(CV4)-Juque(CV14).Association rule analysis revealed the strongest acupoint correlation between Danzhong(CV17)and Zhongwan(CV12),followed by the combination of Danzhong-Zhongwan-Zusanli.Conclusion In ancient acupuncture treatment of hiccups,particular emphasis was placed on the flexible combination of Taiyuan-Shaoshang and Danzhong-Zhongwan with other acupoints.This approach fully embodies the meridian syndrome differentiation principle of"where the meridian passes,it can treat"and"where the disease locates,it can treat."The selection follows the acupoint pairing principles of"combining distal and local points"and"coordinating upper and lower regions",while also emphasizing the application of specific acupoint categories.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

OBJECTIVE To observe the effect of Jiangqi Pingxiao Formula on airway inflammation in mice with acute asthma and explore its possible mechanism.METHODS A total of 36 BALB/c mice were randomly divided into normal group,model group,dexamethasone group,low-dose,medium-dose and high-dose groups of Jiangqi Pingxiao Formula,with 6 mice in each group.Except for the normal group,the other groups were given ovalbumin to establish the acute asthma attack mouse model.The normal group and the model group were given distilled water by gavage,and the Jiangqi Pingxiao Formula groups were given Jiangqi Pingxiao Formula by gavage at the corresponding dose,once a day,for 5 consecutive days.Whole Body Plethysmography was used to measure the changes of enhanced respiratory interval(Pehn)of bronchial contraction parameters in mice.HE staining was used to observe the pathological changes of lung tissue in mice.ELISA method was adopted to detect the expression levels of interleukin 1β(IL-1β),interleukin 18(IL-18)and tumor necrosis factor α(TNF-α)in lung tissue homogenate of mice.Immunohistochemistry method was used to detect the expression level of NOD-like receptor pyrin domain-associated protein 3(NLRP3)in lung tissue of mice.Western blot method was employed to detect the expression of NLRP3 inflammasome activation-associated protein κ gene binding nuclear factor-κB(NF-κB),NOD-like receptor pyrin domain-associated protein 3(NLRP3),NIMA-associated kinase 7(NEK7),Caspase 1(Cleaved-Caspase 1)and apoptosis-associated speck-like protein(ASC)in lung tissue of mice.RESULTS Compared with the normal group,the Penh level of mice in the model group was increased(P<0.001),and the pathological results of lung tissue showed that the number of inflammatory cells around the airway increased,the inflammatory score increased(P<0.001),the expression of IL-1β,IL-18,and TNF-α in lung tissue homogenate increased(P<0.001),and the expression of NF-κB,NLRP3,NEK7,Cleaved-Caspase 1,and ASC proteins in lung tissue increased(P<0.05,P<0.01,P<0.001).Compared with the model group,the Penh level of mice in the Jiangqi Pingxiao Formula groups and the dexamethasone group was reduced(P<0.05,P<0.001),the number of inflammatory cells in lung tissue decreased,and the inflammatory score decreased(P<0.001);the expression of IL-1β,IL-18,and TNF-α in lung tissue homogenate decreased(P<0.05,P<0.01,P<0.001);the expression of NF-κB,NLRP3,NEK7,Cleaved-Caspase 1,and ASC pro-teins in lung tissue decreased(P<0.05,P<0.01,P<0.001).CONCLUSION Jiangqi Pingxiao Formula can improve lung function and airway inflammation in asthma model mice,and its mechanism may be related to regulating NLRP3 inflammasome-mediated IL-1β secretion.

Thoracic anesthesia with spontaneous respiration represents a form of precision anesthesia meticulously customized to individual patients.Considering the more stringent requirements this anesthesia approach imposes on the regulation of respiratory function,the writing group of the"Consensus of Experts on the Management of Thoracic Anesthesia with Spontaneous Respiration"has formulated elaborate guidelines regarding indications and contraindications,preoperative evaluation,anesthesia implementation,common complications,and treatment strategies.This was accomplished by referencing relevant domestic and international literature and integrating it with actual clinical requirements.The objective is to standardize the rational application of this anesthesia method.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

OBJECTIVE To observe the effect of Jiangqi Pingxiao Formula on airway inflammation in mice with acute asthma and explore its possible mechanism.METHODS A total of 36 BALB/c mice were randomly divided into normal group,model group,dexamethasone group,low-dose,medium-dose and high-dose groups of Jiangqi Pingxiao Formula,with 6 mice in each group.Except for the normal group,the other groups were given ovalbumin to establish the acute asthma attack mouse model.The normal group and the model group were given distilled water by gavage,and the Jiangqi Pingxiao Formula groups were given Jiangqi Pingxiao Formula by gavage at the corresponding dose,once a day,for 5 consecutive days.Whole Body Plethysmography was used to measure the changes of enhanced respiratory interval(Pehn)of bronchial contraction parameters in mice.HE staining was used to observe the pathological changes of lung tissue in mice.ELISA method was adopted to detect the expression levels of interleukin 1β(IL-1β),interleukin 18(IL-18)and tumor necrosis factor α(TNF-α)in lung tissue homogenate of mice.Immunohistochemistry method was used to detect the expression level of NOD-like receptor pyrin domain-associated protein 3(NLRP3)in lung tissue of mice.Western blot method was employed to detect the expression of NLRP3 inflammasome activation-associated protein κ gene binding nuclear factor-κB(NF-κB),NOD-like receptor pyrin domain-associated protein 3(NLRP3),NIMA-associated kinase 7(NEK7),Caspase 1(Cleaved-Caspase 1)and apoptosis-associated speck-like protein(ASC)in lung tissue of mice.RESULTS Compared with the normal group,the Penh level of mice in the model group was increased(P<0.001),and the pathological results of lung tissue showed that the number of inflammatory cells around the airway increased,the inflammatory score increased(P<0.001),the expression of IL-1β,IL-18,and TNF-α in lung tissue homogenate increased(P<0.001),and the expression of NF-κB,NLRP3,NEK7,Cleaved-Caspase 1,and ASC proteins in lung tissue increased(P<0.05,P<0.01,P<0.001).Compared with the model group,the Penh level of mice in the Jiangqi Pingxiao Formula groups and the dexamethasone group was reduced(P<0.05,P<0.001),the number of inflammatory cells in lung tissue decreased,and the inflammatory score decreased(P<0.001);the expression of IL-1β,IL-18,and TNF-α in lung tissue homogenate decreased(P<0.05,P<0.01,P<0.001);the expression of NF-κB,NLRP3,NEK7,Cleaved-Caspase 1,and ASC pro-teins in lung tissue decreased(P<0.05,P<0.01,P<0.001).CONCLUSION Jiangqi Pingxiao Formula can improve lung function and airway inflammation in asthma model mice,and its mechanism may be related to regulating NLRP3 inflammasome-mediated IL-1β secretion.

Thoracic anesthesia with spontaneous respiration represents a form of precision anesthesia meticulously customized to individual patients.Considering the more stringent requirements this anesthesia approach imposes on the regulation of respiratory function,the writing group of the"Consensus of Experts on the Management of Thoracic Anesthesia with Spontaneous Respiration"has formulated elaborate guidelines regarding indications and contraindications,preoperative evaluation,anesthesia implementation,common complications,and treatment strategies.This was accomplished by referencing relevant domestic and international literature and integrating it with actual clinical requirements.The objective is to standardize the rational application of this anesthesia method.

Objective To investigate the role of lncSIL in transforming growth factor-β1(TGF-β1)-induced alveo-lar epithelial interstitial transformation(EMT)and its related signaling pathways.Methods Western blot was used to detect the effect of lncSIL silencing on the expression of E-cadherin(E-cad),alpha-smooth muscle actin(α-SMA)and Collagen I(Col I)in the process of EMT induced by TGF-β1.LncSIL interacting proteins were ana-lyzed by RNA pulldown.Western blot was used to detect the effect of overexpression or silencing of lncSIL on the expression of its target gene enhancer of zeste homolog 2(EZH2)and its downstream factors P21 and cyclin-de-pendent kinase 6(CDK6).Flow cytometry was used to analyze the effect of lncSIL on cell cycle progression.Re-sults After lncSIL silencing,the expression of α-SMA and Col I increased,the expression of E-cad decreased.RNA pulldown assay showed that EZH2 was the target protein that interacted with lncSIL,and the expression of EZH2 increased after silencing lncSIL,the expression of EZH2 downstream gene P21 decreased,CDK6 increased.Flow cytometry showed that the number of cells in S phase significantly increased.When lncSIL was overexpressed,the expression of EZH2 and CDK6 was down-regulated,the expression of P21 was up-regulated,and the number of S phase cells significantly decreased.Conclusion LncSIL inhibits TGF-β1-induced alveolar epithelial cell mesen-chymal transition by negatively regulating EZH2/P21/CDK6 signaling pathway to inhibit cell cycle progression.

Objective·To investigate the potential causal relationship between type l diabetes and colorectal cancer by using Mendelian randomization(MR).Methods·Two-sample bidirectional MR was used to investigate the causal relationship between type 1 diabetes and colorectal cancer.All research data were collected from the IEU Open GWAS Project database.The dataset of type l diabetes included 9 266 cases and 15 574 controls,with correlation analysis in 12 783 129 single nucleotide polymorphisms(SNPs);the dataset of colorectal cancer included 5 657 cases and 372 016 controls,with correlation analysis in 29 999 696 SNPs.The instrumental variables SNPs were screened.The results derived from the inverse-variance weighted(IVW)method were used as the main indicator of effect.The results derived from other four methods,namely MR-Egger regression,weighted median,simple mode,and weighted mode,were used as reference.Sensitivity was analyzed with the leave-one-out method.Heterogeneity was analyzed with Cochran's Q test by using both IVW and MR-Egger methods.Pleiotropy was analyzed with MR-pleiotropy function,and Steiger test was used for directional research.The colocation analysis was used to find out whether the causal relationship between type 1 diabetes and colorectal cancer was caused by the same SNP.The genetic correlation between 2 diseases was analyzed by using the linkage disequilibrium score regression(LDSC).All tests were analyzed by using R language software(version 4.3.1).Results·After being screened,a total of 33 instrumental variables(SNPs)were used.The heterogeneity test results showed that there was heterogeneity among the SNPs(IVW and MR-Egger:P＜0.05),so the effect evaluation was based on the results of the random effect model.MR analysis showed that type 1 diabetes had a significant causal effect on colorectal cancer(P＜0.05)by using IVW,MR-Egger,weighted median and weighted mode.Sensitivity analysis showed that the results were stable.Pleiotropy was not detected in pleiotropy test(P＞0.05).Steiger test showed that the effect of type l diabetes on colorectal cancer was not interfered with by the reverse effect.Reverse MR analysis showed no causal effect of colorectal cancer on type l diabetes(P＞0.05).The results of colocalization analysis showed that the probability of H4 hypothesis was 45.7％,and the causal relationship between the 2 diseases was not caused by the same SNP in the gene sequences.LDSC analysis demonstrated that there was no genetic correlation between the two diseases.Conclusion·Type 1 diabetes may promote colorectal cancer,but colorectal cancer has no effect on type 1 diabetes.