Objective To explore the clinical experience of Professor Wang Yan'gang in treating gastroesophageal reflux disease(GERD)using data mining methods.Methods SPSS 23.0 was used to statistically analyze the frequency,properties,flavors,and meridian tropism of Chinese herbal medicines in the prescriptions of effective GERD cases treated by Professor Wang Yan'gang in outpatient clinics from January 2020 to December 2022.Cluster analysis,factor analysis,and association rule analysis were performed on the relevant drugs.Results A total of 294 outpatient prescriptions for the treatment of GERD were collected,including 174 Chinese herbal medicines.The top 10 frequently-used drugs were Sepiae Endoconcha(Haipiaoxiao),Fritillariae Thunbergii Bulbus(Zhebeimu),Scutellariae Radix(Huangqin),Coptidis Rhizoma(Huanglian),Pinelliae Rhizoma Praeparatum Cum Alumine(Qingbanxia),Arecae Semen Tostum(Chaobinglang),Artemisiae Scopariae Herba(Yinchen),Gypsum Fibrosum(Shigao),Aurantii Fructus Immaturus(Zhishi),and Magnoliae Officinalis Cortex(Houpo).After cluster analysis,factor analysis,and association rule analysis,16 commonly-used herb pairs,such as Huangqin-Huanglian,Citri Reticulatae Pericarpium(Chenpi)-Zhuru(Bambusae Caulis in Taenia),Haipiaoxiao-Zhebeimu,Shichangpu(Acori Tatarinowii Rhizoma)-Yujin(Curcumae Radix),and Zhishi-Houpo were identified,and 9 herb groups such as"Huangqin,Huanglian,Yinchen"and"Chenpi,Zhuru,Qingbanxia"were obtained.Factor analysis was performed on 22 drugs with a usage frequency more than 110 times,and then 6 common factors were extracted after principal component analysis.Conclusion In differentiating and treating GERD,Professor Wang Yan'gang suggests that stagnated heat injuring yin should be taken as the core pathogenesis,and therapy of clearing heat and nourishing yin should be used as the core treatment method.Additionally,auxiliary methods such as soothing the throat,regulating the liver and stomach,and nourishing the heart and spirit can be adopted according to the accompanying symptoms during the disease progression.

Objective sampling method was used to conduct a questionnaire survey on outpatients in two hospitals in Guangdong province in order to evaluate patients’ satisfaction with the quality of medical service. This paper explored the factors that affect patients’ evaluation of medical service quality, and found that patients’ age was negatively correlated with the evaluation of medical service quality. It is suggested that the establishment of friendly medical institutions should be carried out according to the national policy. At the same time, the management mechanism of hospital should be improved, the number of medical service centers for "efficient" should be increased, and the medical service personnel should be regularly trained; carry out medical knowledge education in community, improve the popularization of personal medical knowledge and close the cognitive gap between doctors and patients.

Objective To research the procedure for creating an animal model of mitral regurgitation by implanting a device through the apical artificial chordae tendineae, and to assess the stability and dependability of the device. Methods Twelve large white swines were employed in the experiments. Through a tiny hole in the apex of the heart, the artificial chordae tendineae of the mitral valve was inserted under the guidance of transcardiac ultrasonography. Before, immediately after, and one and three months after surgery, cardiac ultrasonography signs were noted. Results All models were successfully established. During the operation and the follow-up, no swines died. Immediately after surgery, the mitral valve experienced moderate regurgitation. Compared with preoperation, there was a variable increase in the amount of regurgitation and the values of heart diameters at a 3-month follow-up (P<0.05). Conclusion In off-pump, the technique of pulling the mitral valve leaflets with chordae tendineae implanted transapically under ultrasound guidance can stably and consistently create an animal model of mitral regurgitation.

Objective:To establish and validate a prediction model for the risk of major upper gastrointestinal bleeding in patients with varices of liver cirrhosis.Method:This study retrospectively collected the clinical data of patients with esophageal and gastric variceal bleeding who were admitted to the emergency department of Ningxia Medical University General Hospital from October 2019 to October 2022. The patients were divided into modeling group and validation group according to the ratio of 7:3 by random number table method. The observation index was whether the upper gastrointestinal bleeding occurred within 24 hours after admission. The predictors in the logistic regression model were used to construct a prediction model for the risk of major upper gastrointestinal bleeding in patients with varices with liver cirrhosis, and the area under the receiver operating characteristic curve (AUC), the correction curve and the decision curve were analyzed to evaluate the discriminatory ability, accuracy and clinical utility of the prediction model.Results:A total of 305 patients were included, including 215 and 90 in the modeling and validation groups, respectively, and the clinical data of the two groups were comparable. Multivariate logistic regression showed that systolic blood pressure ( OR=0.918, 95% CI: 0.860-0.980, P=0.010), MAP(ASH) score ( OR=1.993, 95% CI: 1.017-3.907, P=0.045), Child-Pugh score ( OR=1.999, 95% CI: 1.139-3.510, P=0.016) and model for end-stage liver disease (MELD) ( OR=1.398, 95% CI: 1.037-1.886, P=0.028) were independent influencing factors for the occurrence of upper gastrointestinal bleeding in patients with liver cirrhosis varices. The AUC of the prediction model in the modeling group was 0.936 (95% CI: 0.895-0.976), and that of the prediction model in the validation group was 0.891 (95% CI: 0.807-0.975), the prediction model had good identification, calibration, and clinical application value. Conclusions:Systolic blood pressure, MAP (ASH) score, Child-Pugh score, and prediction models constructed by end-stage liver disease models are helpful for early prediction of the risk of upper gastrointestinal bleeding in patients with cirrhosis varices in the emergency department.

Objective:To explore the prognostic factors of elderly patients with community-acquired pneumonia-related sepsis and to construct a prediction model.Methods:The clinical data of elderly patients with community-acquired pneumonia-associated sepsis from October 2020 to October 2022 in the General Hospital of Ningxia Medical University from October 2020 to October 2022 were retrospectively included, and the clinical data of the two groups were divided into the modeling population and the validation population in the ratio of 7:3 by random number table method, and the clinical data of the two groups were compared. According to the 30-day outcomes of admission, the patients were divided into survival group and death group, and the independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-related sepsis were screened out by LASSO regression and multivariate logistic regression analysis, and the nomogram prediction model was constructed by R software. The area under the curve (AUC), calibration curve and decision curve of the receiver operating characteristic curve were used to validate the nomogram prediction model in the modeling population and the validation population to judge its discrimination, calibration and clinical practicability.Results:A total of 472 patients were included, with 331 and 141 models and validations, respectively, indicating that the clinical data were comparable between the modeled and validated populations. LASSO regression and multivariate logistic regression analysis showed that pneumonia severity index (PSI) score and sequential organ failure assessment (SOFA) score were independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-associated sepsis. The AUC of the modeled population prediction model was 0.984 (95% CI: 0.975-0.994), and the AUC of the validated population prediction model was 0.961 (95% CI: 0.926-0.996). The nomogram prediction model has good discrimination, calibration and clinical practicability in both the modeled and validated populations. Conclusions:The nomogram prediction model established in the study has high accuracy for early identification and risk of sepsis in elderly patients with CAP and can guide for clinicians to formulate personalized interventions.

Objective:To explore the risk factors of sepsis in patients with multiple trauma and construct a nomogram prediction model.Methods:The data of patients with multiple injuries admitted to the emergency intensive care unit (EICU) of the General Hospital of Ningxia Medical University from January 2021 to April 2022 were respectively collected. Inclusion criteria: (1) meet the diagnostic criteria for multiple injuries; (2) the time from injury to admission ≤ 24 hours; (3) age>18 years old; (4) all examination or rescue measures were approved by the patient or the patient's family; (5) the patient's clinical data were complete. The patients were divided into sepsis group and non-sepsis group according to the definition of Sepsis 3.0 at the 28-day of EICU hospitalization. The receiver operating characteristic curve was drawn. Logistic regression analysis was applied to determine the independent predictors for sepsis, and the nomogram was constructed.Results:A total of 291 patients were included, including 102 in the sepsis group and 189 in the non-sepsis group. Multivariate logistic analysis revealed that age, acute physiology and chronic health status score (APACHE) Ⅱ, Glasgow Coma Scale (GCS), injury severity score (ISS), sequential organ failure assessment (SOFA) within 24 hours after admission, blood transfusion frequency, the application of norepinephrine, mechanical ventilation, pathogenic culture results, and history of diabetes were independent factors influencing the occurrence of sepsis. A nomogram model was constructed by combining these variables (AUC=0.913, 95% CI: 0.847-0.942), and the model had a good fitting calibration curve. Conclusions:The nomogram constructed by age, APACHE-Ⅱ, GCS score, SOFA score, ISS score, number of blood transfusions, mechanical ventilation, norepinephrine drug use, pathogenic culture and diabetes has a good predictive value for sepsis in patients with multiple trauma in the later stage, which is worth promoting.

METTL3 and METTL14 are two components that form the core heterodimer of the main RNA m6A methyltransferase complex (MTC) that installs m6A. Surprisingly, depletion of METTL3 or METTL14 displayed distinct effects on stemness maintenance of mouse embryonic stem cell (mESC). While comparable global hypo-methylation in RNA m6A was observed in Mettl3 or Mettl14 knockout mESCs, respectively. Mettl14 knockout led to a globally decreased nascent RNA synthesis, whereas Mettl3 depletion resulted in transcription upregulation, suggesting that METTL14 might possess an m6A-independent role in gene regulation. We found that METTL14 colocalizes with the repressive H3K27me3 modification. Mechanistically, METTL14, but not METTL3, binds H3K27me3 and recruits KDM6B to induce H3K27me3 demethylation independent of METTL3. Depletion of METTL14 thus led to a global increase in H3K27me3 level along with a global gene suppression. The effects of METTL14 on regulation of H3K27me3 is essential for the transition from self-renewal to differentiation of mESCs. This work reveals a regulatory mechanism on heterochromatin by METTL14 in a manner distinct from METTL3 and independently of m6A, and critically impacts transcriptional regulation, stemness maintenance, and differentiation of mESCs.
Animals ; Mice ; Methylation ; Chromatin ; Histones/metabolism* ; RNA, Messenger/genetics* ; Methyltransferases/metabolism* ; RNA/metabolism*

OBJECTIVES: To investigate the effect of oral microscope-assisted surface decontamination on implants in vitro. METHODS: Twelve implants that fell off because of severe peri-implantitis were collected, and decontamination was carried out on the surfaces of implants through curetting, ultrasound, titanium brushing, and sandblasting at 1×, 8×, or 12.8× magnifications. The number and sizes of residues on the implants' surfaces after decontamination were determined, and the decontamination effect was analyzed according to the thread spacing in the different parts of the thread. RESULTS: 1) The 8× and 12.8× groups scored lower for implant surface residues than the 1× group (P<0.000 1), and the 12.8× group scored lower than the 8× group (P<0.001); 2) no difference in residue score was found between the wide and narrow thread pitch (P>0.05), and the 8× and 12.8× groups had lower scores than the 1× group (P<0.001); 3) the lowest number of contaminants was observed at the tip of the thread, whereas the highest was observed below the thread, and the difference was significant (P<0.001). However, the thread pitch had no effect on the number of contaminants in different areas (P>0.05); 4) the residue scores of the 8× and 12.8× groups were lower than those of the 1× group at the thread tip and above, sag, and below the thread of the implants (P<0.05). CONCLUSIONS Residues on the surfaces of contaminated implants can be effectively removed by using an oral microscope. After decontamination, the residues of pollutants were mainly concentrated below the thread of the implants, and the thread pitch of the implants had no significant effect on the residues.
Humans ; Dental Implants ; Decontamination ; Surface Properties ; Peri-Implantitis ; Titanium

Objective:To explore the prognostic risk factors of patients with multiple injuries and establish a nomogram prediction model.Methods:The clinical data of 291 patients with multiple injuries admitted to the Emergency Intensive Care Unit (EICU) of General Hospital of Ningxia Medical University were collected, including sex, age, open injury, norepinephrine use, mechanical ventilation, time to hospital after injury, distance to hospital, relative lymphocyte value, platelet count, lactic acid, injury severity score (ISS), acute physiology and chronic health evaluationⅡ (APACHE Ⅱ), Glasgow coma scale (GCS), number of blood transfusions, number of operations, and previous history of diabetes, hypertension and smoking within 24 h after admission. According to whether the condition worsened during the hospitalization of EICU, the patients were divided into the deterioration group and improvement group. SPSS26.0 software was used for statistical analysis of the data, univariate and multivariate analysis were used to screen the factors affecting the prognosis of patients with multiple injuries, receiver operating characteristic (ROC) curve and forest chart were drawn, and the influencing factors in binary Logistic regression model were used to make the nomogram.Results:Mechanical ventilation, norepinephrine use, age, relative lymphocyte value, lactic acid, APACHE-II score, GCS score, and number of operations were significant for predicting the prognosis of patients with multiple injuries ( P<0.05). The independent influencing factors obtained by binary Logistic regression model were age, lactic acid, APACHE-Ⅱ score and number of operations. ROC curve analysis showed that the area under the curve was the largest in multi-factor combined prediction, followed by APACHE-Ⅱ score. The diagnostic cut-off value of each index was as follows: age >58 years old, relative lymphocyte value≤ 8.62%, lactic acid >1.72, APACHE-Ⅱ score >16, GCS score≤ 6, and number of operations≤ 0. The R software was used to establish a nomogram of the influencing factors in the binary Logistic regression model, which had good predictive value. Conclusions:The nomogram constructed by age, relative lymphocyte value, lactic acid, APACHE-Ⅱ score, GCS score, number of operations, mechanical ventilation, and norepinephrine use has a good predictive value for the prognosis of patients with multiple injuries, and is worthy of promotion..