Objective To reduce the screening positive rate (SPR) and improve clinical efficiency of maternal serum screening for Down's syndrome.Methods Nine thousand and thirty-three cases of second trimester maternal serum screening for Down's syndrome were included from Apr.2013 to Apr.2014 in the present study.The screening results,all basic data and equation curves were analyzed retrospectively.Based on the data from the authors' laboratory,the important adjustment parameters were simulated.Combined with postnatal follow-up results,the quality and clinical performance of second trimester serum screening for Down's syndrome were evaluated.Results The SPR of second trimester serum screening for Down's syndrome was 6.69％(604/9033),the detection rate (DR) was 75％(3/4),and FPR was 6.65％(601/9033).The median multiple of median (MOM) of alpha-fetoprotein (AFP) was low and SPR was high,and MOM of free human chorionic gonadotropin β subunit (free hCGβ) were high and SPR was high,while MOM of unconjugated estriol (uE3) were a little bit low,and SPR was slightly high.Considering these three factors,it is believed that the screening positive rate is high.By the simulation adjustments of MOM value equations (AFP and free hCGβ) and weight correction equation,the SPR reduced to 4.11％(371/9033) after recalculating the risk,FPR declined to 4.07％(368/9033),and no more Down's syndrome fetus were missed compared with postnatal follow-up results.Conclusion Based on a localized setting depending on the local laboratory data,we suggest that the MOM value distributions(AFP,free hCGβ and uE3) and maternal weight should be regularly adjusted since it is a useful way to reduce the false-positive rate and improve clinical efficiency of maternal serum screening for Down's syndrome.

Objective To construct a diagnostic model for the phlegm-dampness obstruction syndrome in patients with coronary heart disease stable angina pectoris(CSAP);To provide a reference for clinical syndrome differentiation.Methods Totally 305 patients'clinical data were collected from the Department of Cardiology,Dongying Hospital Affiliated to Shandong University of Traditional Chinese Medicine,from May 2022 to January 2024.The least absolute shrinkage and selection operator(LASSO)was used to select features,and multiple models were constructed and compared using machine learning(ML)algorithms.The optimal ML model was selected for training,validation,and testing.Finally,the operational logic of the optimal model was explained using Shapley Additive Explanations(SHAP),and two typical examples were provided to help users understand the model's operational logic.Results LASSO regression identified chest pain,body mass index(BMI),limb heaviness,drinking history,age,triglycerides(TG),total cholesterol(TC),and low-density lipoprotein cholesterol(LDL-C)as features included in the model.After comparing multiple models,the Gaussian Naive Bayes(GNB)model demonstrated the best performance.The final constructed GNB model achieved an average AUC of 0.938(95%CI:0.903-0.972)in the training set,an average AUC of 0.927(95%CI:0.851-0.992)in the validation set,and an AUC of 0.856(95%CI:0.751-0.961)in the test set.The learning curve showed that the error between the training and validation sets in the model converged as the number of training samples increased.The calibration curve showed that the model had good consistency in predicting the probability of observed phlegm-dampness obstruction syndrome patients.The clinical decision curve(DCA)showed that the model could provide clinical benefits for patients at a decision threshold below 0.7.The features ranked by SHAP importance in order were chest pain,BMI,LDL-C,TG,limb heaviness,TC,drinking history and age.Conclusion The diagnostic model for CSAP phlegm-dampness obstruction syndrome constructed in this study can assist physicians in the syndrome differentiation of patients,thereby enabling the formulation of integrated clinical treatment plans combining traditional Chinese and Western medicine,and aiding patients in achieving better clinical therapeutic outcomes.

OBJECTIVETo observe autophagy induced by starvation in non-small cell lung cancer A459 and 95D cells.

METHODSA549 and 95D cells in logarithmic growth in 1640 medium were cultured in Earle's balanced salt solution (EBSS) for 0, 1, 2, 3, 4 or 5 h. Autophagosome formation in the cell culture was observed by MDC fluorescent staining, and the expression of microtubule-associated protein 1 light chain 3 (LC3) and Beclin1 in the cells were detected using Western blotting.

RESULTSCompared with the control cells, the cells with prolonged starvation showed increased MDC-positive cells and autophagosome formation. The expression of Beclin-1 and the LC3-II/LC3-I ratio also increased as the starvation prolonged, reaching the peak levels at 3 h and 4 h, respectively.

CONCLUSIONAutophagy can be induced by starvation in A549 and 95D cells in correlation with the expression of autophagy-related proteins LC3 and Beclin-1. These cell models of nutritional deficiency-induced autophagy may allow for a better understanding of the role of autophagy in the development of non-small cell lung cancer.

Apoptosis Regulatory Proteins ; metabolism ; Autophagy ; Beclin-1 ; Carcinoma, Non-Small-Cell Lung ; pathology ; Cell Line, Tumor ; Humans ; Membrane Proteins ; metabolism ; Microtubule-Associated Proteins ; metabolism

Objective To observe autophagy induced by starvation in non-small cell lung cancer A459 and 95D cells. Methods A549 and 95D cells in logarithmic growth in 1640 medium were cultured in Earle's balanced salt solution (EBSS) for 0, 1, 2, 3, 4 or 5 h. Autophagosome formation in the cell culture was observed by MDC fluorescent staining, and the expression of microtubule-associated protein 1 light chain 3 (LC3) and Beclin1 in the cells were detected using Western blotting. Results Compared with the control cells, the cells with prolonged starvation showed increased MDC- positive cells and autophagosome formation. The expression of Beclin-1 and the LC3-II/LC3-I ratio also increased as the starvation prolonged, reaching the peak levels at 3 h and 4 h, respectively. Conclusion Autophagy can be induced by starvation in A549 and 95D cells in correlation with the expression of autophagy-related proteins LC3 and Beclin-1. These cell models of nutritional deficiency-induced autophagy may allow for a better understanding of the role of autophagy in the development of non-small cell lung cancer.

Objective To observe autophagy induced by starvation in non-small cell lung cancer A459 and 95D cells. Methods A549 and 95D cells in logarithmic growth in 1640 medium were cultured in Earle's balanced salt solution (EBSS) for 0, 1, 2, 3, 4 or 5 h. Autophagosome formation in the cell culture was observed by MDC fluorescent staining, and the expression of microtubule-associated protein 1 light chain 3 (LC3) and Beclin1 in the cells were detected using Western blotting. Results Compared with the control cells, the cells with prolonged starvation showed increased MDC- positive cells and autophagosome formation. The expression of Beclin-1 and the LC3-II/LC3-I ratio also increased as the starvation prolonged, reaching the peak levels at 3 h and 4 h, respectively. Conclusion Autophagy can be induced by starvation in A549 and 95D cells in correlation with the expression of autophagy-related proteins LC3 and Beclin-1. These cell models of nutritional deficiency-induced autophagy may allow for a better understanding of the role of autophagy in the development of non-small cell lung cancer.