Objective To investigate the safety and efficacy of endoscopic multi-band mucosectomy (EMBM) in the treatment of early esophageal cancer and intraepithelial neoplasia.Methods A retrospective analysis was made on the clinical data of 34 cases diagnosed with early esophageal cancer and intraepithelial neoplasia.All the patients accepted EMBM.The therapeutic effects and safety were summarized.Results A total of 34 patients with 36 lesions were successfully completed in the treatment of one session.The entire biopsy specimen was tested by pathological examination.High-grade intraepithelial neoplasia in 24 lesions,low-grade intraepithelial neoplasia in 4 lesions,intramucosal cancer in 6 lesions,a submucosal shallow cancer and a submucosal deep cancer were diagnosed.Clamps electric coagulation hemostasis was used during the operation in 2 bleeding cases.No delayed postoperative bleeding,subcutaneous emphysema and esophageal perforation happened.Two cases appeared esophageal stenosis after EMBM.Bougienage were used to relieve dysphagia.One case confirmed with deep submucosal lymphovascular invasion accepted surgery later in department of thoracic surgery.No local recurrence and metastasis were found in the other 33 cases during the 6-24 months of follow-up time.Conclusions EMBM is a minimally invasive,safe and effective method for the treatment of early esophageal cancer and intraepithelial neoplasia.EMBM is worthy of promotion.

Objective To establish a simple method to extract the methylated ctDNA in urine using magnetic beads as solid phase adsorption carri?er with a specific design reagent system and extraction process,and evaluate its application feasibility for methylated gene detection in urine sample . Methods Fourty cases of methylated ctDNA were extracted in urine using magnetic beads. After methylated modification,the concentration and pu?rity of DNA was determined by ultraviolet spectrophotometer. Results The extraction of 50 mL urine can gain 61?200 ng/mL methylated ctDNA, and the OD260/280 was 1.8 ± 0.05. Conclusion There are methylated ctDNA exist in the urine which can be extracted by magnetic beads. The estab?lished extraction method is simple,effective,and with high purity.

ObjectiveIn view of the problems of large errors and poor accuracy in pulmonary function testing in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), a predictive classification model of pulmonary function in patients with AECOPD was proposed by comparing the prediction performance of different machine learning models to find the optimal model. MethodsFrom January, 2018 to February, 2020, 90 patients with different degrees of COPD from the Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University were collected. Six machine learning model algorithms (K-nearest neighbor, logistic regression, support vector machine, naive Bayes, decision tree and random forest) were used to establish AECOPD predictive classification models. Their area under the curve of receiver operating characteristic (AUC-ROC) and accuracy were compared. Ten-fold cross-validation method was used to validate the data set. ResultsThe model based on random forest worked best in predicting and classifying AECOPD patients, with an accuracy rate of 0.844 and an AUC-ROC of 0.916. ConclusionRandom forest-based predictive model is a powerful tool for identifying patients with AECOPD, providing decision support when it is difficult to give a definitive diagnosis.