Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.

Objective:To construct a failure mode and effects analysis(FMEA)evaluation model for medical devices to manage devices,so as to enhance management efficiency for medical devices.Methods:The FMEA was adopted to construct FMEA evaluation model for medical devices,so as to conduct comprehensive lifecycle management for medical devices.The process of management for equipment was optimized,and the operational risk of medical devices was reduced through failure mode(FM)analysis and the construction of management system for equipment.A total of 47 medical devices in clinical use of The First People's Hospital of Neijiang from January to December 2023 were included.In them,23 devices received conventional management mode during January and June 2023,and 24 devices received FMEA evaluation model(model management mode)during July and December 2023.For each group,2,000 patients'medical records were selected.The control effectiveness of infectious indicators,effect of cleaning and disinfection,and quality scores of infectious control for medical devices were compared between different management modes.A self-designed questionnaire was adopted to investigate the recognition scores of engineers who used and managed devices,operators,physicians,and department administrators for two kinds of management modes.Results:In 2,000 patients'medical records,who adopted model management mode,the infection rate of patients,and infection rate of aseptic surgical incision were respectively 0.15%and 0.05%,both were significantly lower than those in the conventional management mode(x2=5.420,8.358,P<0.05).The cleaning rate,and disinfection qualification rate of 24 medical devices,which adopted model management mode,were respectively 83.33%and 87.50%,all of which were significantly higher than these of conventional management mode(x2=8.080,6.741,P<0.05).The scores of standardized operation,rational use,disinfection and cleaning,and emergency intervention for medical devices in adopting model management mode were significantly higher than those in adopting conventional management mode(t=14.435,16.014,13.049,12.537,P<0.05).The recognition scores of engineers who used and managed devices,operators,physicians,and department administrators for adopting model management mode were significantly higher than those for adopting conventional management mode,and the differences were significant(t=12.219,12.147,17.437,13.420,P<0.05).Conclusion:The FMEA evaluation model for medical devices can real-time monitor the entire management process for medical devices,and reduce clinical infections,and ensure normal operation of devices,and improve clinically operational quality of them,and increase satisfaction of staffs in clinical departments.

Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.

Objective:To construct a failure mode and effects analysis(FMEA)evaluation model for medical devices to manage devices,so as to enhance management efficiency for medical devices.Methods:The FMEA was adopted to construct FMEA evaluation model for medical devices,so as to conduct comprehensive lifecycle management for medical devices.The process of management for equipment was optimized,and the operational risk of medical devices was reduced through failure mode(FM)analysis and the construction of management system for equipment.A total of 47 medical devices in clinical use of The First People's Hospital of Neijiang from January to December 2023 were included.In them,23 devices received conventional management mode during January and June 2023,and 24 devices received FMEA evaluation model(model management mode)during July and December 2023.For each group,2,000 patients'medical records were selected.The control effectiveness of infectious indicators,effect of cleaning and disinfection,and quality scores of infectious control for medical devices were compared between different management modes.A self-designed questionnaire was adopted to investigate the recognition scores of engineers who used and managed devices,operators,physicians,and department administrators for two kinds of management modes.Results:In 2,000 patients'medical records,who adopted model management mode,the infection rate of patients,and infection rate of aseptic surgical incision were respectively 0.15%and 0.05%,both were significantly lower than those in the conventional management mode(x2=5.420,8.358,P<0.05).The cleaning rate,and disinfection qualification rate of 24 medical devices,which adopted model management mode,were respectively 83.33%and 87.50%,all of which were significantly higher than these of conventional management mode(x2=8.080,6.741,P<0.05).The scores of standardized operation,rational use,disinfection and cleaning,and emergency intervention for medical devices in adopting model management mode were significantly higher than those in adopting conventional management mode(t=14.435,16.014,13.049,12.537,P<0.05).The recognition scores of engineers who used and managed devices,operators,physicians,and department administrators for adopting model management mode were significantly higher than those for adopting conventional management mode,and the differences were significant(t=12.219,12.147,17.437,13.420,P<0.05).Conclusion:The FMEA evaluation model for medical devices can real-time monitor the entire management process for medical devices,and reduce clinical infections,and ensure normal operation of devices,and improve clinically operational quality of them,and increase satisfaction of staffs in clinical departments.

In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contracting COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.
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Humans ; Lung Neoplasms/complications* ; COVID-19 ; SARS-CoV-2 ; Multiple Pulmonary Nodules ; Pandemics/prevention & control* ; Lung

Osteoporotic vertebral compression fracture (OVCF) can lead to lower back pain and may be even accompanied by scoliosis, neurological dysfunction and other complications, which will affect the daily activities and life quality of patients. Vertebral augmentation is an effective treatment method for OVCF, but it cannot correct unbalance of bone metabolism or improve the osteoporotic status, causing complications like lower back pain, limited spinal activities and vertebral refracture. The post-operative systematic and standardized rehabilitation treatments can improve curative effect and therapeutic efficacy of anti-osteoporosis, reduce risk of vertebral refracture, increase patient compliance and improve quality of life. Since there still lack relevant clinical treatment guidelines for postoperative rehabilitation treatments following vertebral augmentation for OVCF, the current treatments are varied with uneven therapeutic effect. In order to standardize the postoperative rehabilitation treatment, the Spine Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized relevant experts to refer to relevant literature and develop the "Guideline for postoperative rehabilitation treatment following vertebral augmentation for osteoporotic vertebral compression fracture (2022 version)" based on the clinical guidelines published by the American Academy of Orthopedic Surgeons (AAOS) as well as on the principles of scientificity, practicality and advancement. The guideline provided evidence-based recommendations on 10 important issues related to postoperative rehabilitation treatments of OVCF.

Objective:To study the role of miR-155 in the differentiation of papillary thyroid carcinoma (PTC) cells, and to explore the possible mechanism.Methods:Human miR-155 analogues were constructed and transfected into PTC BCPAP cells in vitro. CCK8 test and Transwell test were used to observe the changes of cell proliferation and invasiveness. The miR-155 was transfected into BCPAP cells in vitro and the protein background and phosphorylation expression of MAPK pathway were detected by Western blot. ERK pathway inhibitor U0126 was given to observe whether it could reverse the abnormal proliferation and invasion of thyroid cancer cells caused by over-expression of miR-155.Results:The proliferation of BCPAP cells was detected by CCK8 test 48 hours after overexpression of miR-155, and the invasiveness of thyroid cancer cells was significantly enhanced by Transwell test 48 hours after overexpression of miR-155 ( P<0.05) ; Western blot method found that the expression of JNK, ERK and p38 in MAPK signal pathway was significantly up-regulated ( P<0.05) . At the same time, the expression of p-ERK protein in the cells was increased significantly ( P<0.05) . The expression of p-ERK in the cells treated with ERK pathway inhibitor U0126 and miR-155 was significantly lower than that in the miR-155 group ( P<0.05) . By detecting the proliferation and invasion of cells in each group, we found that the U0126 could reverse the proliferation and invasion promoting effect caused by miR-155. Conclusion:miR-155 can promote the proliferation and invasion of PTC BCPAP cells by activating the ERK pathway of MAPK pathway, which provides a potential target for the treatment of thyroid cancer.

Epigenetic modification is closely related to the occurrence and development of tumors. It mainly regulates gene function and expression level through DNA methylation, histone modification, regulation of non-coding RNA and chromatin structure reconstruction. At present, epigenetic drugs have been gradually applied to the treatment of malignant tumors. Common drug types include: DNA methyltransferase inhibitors and histone deacetylase inhibitors. However, these drugs still have many shortcomings and a wide range of clinical applications need further research. Encouragingly, the epigenetic drugs in combination with various anti-tumor drugs have shown great application potential. In this paper, we summarized the development mechanism of epigenetics in malignant tumors and the progress of related drugs.

BACKGROUND: The incidence and mortality of lung cancer often rank first in all malignant tumors. DNA methylation, as one of epigenetics, often participates in the development and progression of tumors. CDO1 as a tumor suppressor gene always undergoes methylation changes early in tumor development. Therefore, this study aims to discuss the value of CDO1 methylation in the early diagnosis of lung cancer. METHODS: Peripheral blood samples were collected from tumor patients and healthy people. Detection of the methylation level of CDO1 in plasma by sulfite modification and quantitative real-time PCR. RESULTS: The level of gene methylation in peripheral blood of lung cancer patients was significantly higher than that of benign lung disease patients and healthy people. The methylation level of CDO1 was significantly different in the stratified comparison of gender, lymph node metastasis and tumor-node-metastasis (TNM) stage (P<0.05). The sensitivity and specificity of CDO1 were 52.2% and 78.6%, respectively. The overall accuracy of the diagnosis was significantly higher than that of the clinical tumor markers, and the sensitivity of CDO1 to stage I and II patients was the highest (40.8%, 47.1%). In addition, CDO1 could effectively increase the sensitivity of diagnosis in multiple joint examinations. CONCLUSIONS Detecting the methylation level of CDO1 has a potentially huge advantage for the early diagnosis of lung cancer.

Objective: To compare the carcinogenic abilities of CD133⁺CD44⁺ laryngeal cancer stem cells and general laryngeal cancer stem cells and to identify the mechanism underlying the action of miRNAs. Methods: Solid tumor-derived laryngeal carcinoma stem cells and Hep-2-derived laryngeal carcinoma stem cells were cultured, and CD133⁺CD44⁺ laryngeal cancer stem cells were sorted by flow cytometry. Boden chamber invasion assay, cell migration assay and tumor formation assay were then performed to compare the invasion, migration and tumorigenic abilities of CD133⁺CD44⁺ laryngeal cancer stem cells and general laryngeal cancer stem cells. And then, miRNAs isolated from two laryngeal cancer stem cells were detected and analysed with miRNA chip. Results: (1)In Boyden chamber invasion assay, the cell invasion rate of CD133⁺CD44⁺ laryngeal cancer stem cells was obviously higher (80.2%±2.3% vs. 63.9%±3.2%, t=5.011, P=0.027); (2)CD133⁺CD44⁺ laryngeal cancer stem cells also had higher mobility in cell migration assay (82.9%±1.1% vs. 70.9%±0.6%, t=4.514, P=0.031); (3)In tumor formation assay, the tumor formation rate of CD133⁺CD44⁺ laryngeal cancer stem cells was also higher (80% vs. 50%). What′s more, we identified 15 miRNAs that were significantly upregulated in CD133⁺CD44⁺ laryngeal cancer stem cells and 3 miRNAs that were significantly downregulated in CD133⁺CD44⁺ laryngeal cancer stem cells, compared with normal laryngeal cancer stem cells. Conclusions CD133⁺CD44⁺ laryngeal cancer stem cells have stronger invasion, migration and tumorigenic abilities compared with normal laryngeal cancer stem cells, and the difference of miRNAs′ expression is one of the possible causes.