1.The Effect of ~60Co?-ray on Antibody-secreting Cell and Its Dose-response Relation
Chuansong CHEN ; Yachun LI ; Jianren XU
Academic Journal of Second Military Medical University 1985;0(06):-
The mice B lymphocyte hybridoma cells were irradiated by 60Co?-rays with doses of 1, 2, 4, 6. 8Gy. A markedly dose-relation depression in cell survival rate, cell concentration and clone-forming rate was observed. D37 value of clone-forming rate was 8.26 Gy. Dose-relation depression was also observed in total production of monoclonal antibody of clones. But production of monoclonal antibody per clone was raised with radiation doses. These results indicate that ionization radiation depresses the survival activity of hybridoma cells, but stimulates the secretion of monoclonal antibody of survival cells.
2.Medical students' cognition on laboratory biosafety
Yunshu LI ; Jian XU ; Xia JIANG ; Shijiao ZHAO ; Qun HUANG ; Yachun GUO
Chinese Journal of Infection Control 2017;16(1):73-77
Objective To investigate cognitive status of medical students of a medical university on laboratory biosafety,and provide basic data for laboratory biosafety management in Chinese universities.Methods 900 full-time undergraduate medical students were chosen by cluster random sampling,questionnaires were filled out in by them.Results 900 questionnaires were distributed,877 (98.21%) valid questionnaires were obtained,49.03% (n =430) were from sophomores,50.97 % (n =447) from juniors,148 (16.88 %) students have ever participated in students'scientific research.The overall awareness rate of laboratory biosafety was 58.72%,only 32.16% of students understood the detailed contents of laboratory biosafety regulations,only 8.21% of students have received training in laboratory biosafety;the awareness rate of laboratory biosafety cabinet was only 14.14%,only 7.75% of students knew which operation should be performed in biosafety cabinet;28.28% of students could deal with waste according to the rules,68.19% of students were able to identify warning signs of biological hazard;92.82% of the students thought that laboratory biosafety-related courses should be set up.The overall awareness rate of laboratory biosafety knowledge and safety behavior was low,which were 42.65% and 41.96% respectively,juniors was higher than that of sophomores(P<0.05);in the aspect of chemical hazards and biological hazards,students with scientific research experience scored higher than those who did not participate in scientific research(all P<0.05).Conclusion Medical students' cognition on knowledge of laboratory biosafety is not optimistic,it is imperative to strengthen the management of education and publicity of laboratory biosafety.
3.Study of quantitative detection of circulating DNA in the plasma of patients with cervical lesion
Hong WANG ; Shiyang PAN ; Jian XU ; Meijuan ZHANG ; Dan CHEN ; Wenying XIA ; Yachun LU ; Yan GENG ; Bai JIN
Chinese Journal of Obstetrics and Gynecology 2011;46(7):501-504
Objective To quantitatively detect circulating DNA levels in the plasma of patients withcervical lesion and to determine the value for diagnosis of cervical lesion and cervical cancer . Methods Preoperative blood samples were collected from 53 cases of low-grade lesions, 49 cases of high-grade lesions, 44 cases of cervical invasive cancer and 70 cases of healthy women. Plasma DNA was extracted by magnetic bead method (BILATEST DNA kit). The quantity of plasma DNA was determined by duplex real-time quantitative PCR. Results Median plasma DNA level of invasive cervical cancer patients was 61. 59 mg/L (32. 06 - 162. 16 mg/L) , which was significantly higher than that of healthy women [16. 35 mg/L(11. 98 -22.71 mg/L), P < 0.01]. Among invasive cervical cancer patients, median plasma DNA level of squamous carcinoma patients was slightly higher than that of adenocarcinoma (50. 43 versus 47. 31 mg/L,P>0. 05). Median plasma DNA level of stage I patients was lower than that of stage Ⅱ- Ⅲ patients (46. 02 versus 71. 35 mg/L, P <0. 05). Conclusion Quantitatively detecting plasma circulating DNA may be with some application prospect in the diagnosis of cervical diseases.
4.Machine learning model predicts benign and malignant pulmonary nodules based on CT features
Yulin CONG ; Xiaohu XU ; Chunlin SHEN ; Yachun XU
Chinese Journal of Medical Physics 2024;41(10):1315-1320
Objective To construct a machine learning model for predicting benign and malignant pulmonary nodules based on CT features.Methods A total of 129 patients with single solid nodules on CT from January 2021 to January 2023 in Hai'an People's Hospital were selected.All of them underwent chest CT scan,and the quantitative parameters,morphological features and radiomics features were recorded.The differentiation of benign and malignant pulmonary nodules was carried out according to relevant diagnostic criteria.The cases were divided into the training set and the internal test set.The constructed models included radiomics labels,morphological model,CT model and combined model.Results There were 98 cases in the training set(27 malignance and 71 benign)and 31 cases in the internal test set(7 malignance and 24 benign).Univariate analysis showed that there were significant differences in age,lesion diameter,mean density,burr sign,pleural depression sign,vacuole sign and air bronchial sign between malignant group and benign group(P<0.05).Compared with benign group,malignant group had higher proportions of burr sign,pleural depression sign,vacuole sign,air bronchial sign,and larger lesion diameter and mean density(P<0.05).LinkDocAI intelligent diagnosis system for pulmonary nodules was used to outline regions of interest and from which 1 000 radiomics features were extracted.The feature selection was performed in 98 cases,and 20 features were screened out after standardized treatment and correlation testing,excluding missing features,low importance feature values and highly correlated features.Through LASSO regression and 10-fold cross validation,λ1se was selected as the optimal λ to construct radiomics labels,and the two most meaningful features(LBP_Glszm_ZoneEntropy and Gradient_Shape_MinorAxis)were enrolled.CT model was considered as the optimal model in this study,and it had an area under receiver operating characteristic curve of 0.912 and 0.889 in the training set and the internal testing set,respectively.Conclusion The machine learning model to predict benign and malignant lung nodules based on CT features has good predictive efficiency,and it can realize the differential diagnosis of benign and malignant pulmonary nodules.
5.Effects and adverse drug reactions of mtrisone in the treatment of patients with severe acute respiratory syndrome
Rui WANG ; Xiaoqing ZHOU ; Jun DONG ; Rong WEI ; Xiutang CAO ; Yachun ZHOU ; Jin WANG ; Daihong GUO ; Kun CHEN ; Jian ZHOU ; Jiesong WANG ; Xiumei ZHU ; Beibei LIANG ; Yanping XU ; Xianzhi ZHOU
Chinese Journal of Clinical Pharmacology and Therapeutics 2004;0(09):-
AIM: To study effects and adverse drug reactions of mtrisone in the treatment of patients with severe acute respiratory syndrome. METHODS: The information of the medications in 680 patients with severe acute respiratory syndrome (SARS) in Xiaotangshan Hospital was collected by HIS system and the effects and ADRs of metrisone were staiated. RESULTS: The kinds of drugs of SARS patients who had been cured by metrisone were more than those which were not cured by metrisone. Condition of SARS patients who had been cured by metrisone was more serious than those which were not cured by metrisone. The ADRs rate, blood glucose and leukocyte of SARS patients who had been cured by metrisone are higher than those which were not cured by metrisone while blood K+ is lower. CONCLUSION: The utilization of metrison to SRAS patient should be more cautious to balance the effects and ADRs of metrisone.