Objective To analyze the indication,ways,therapeutic effect,dose prescription and complication of skull base tumor treated by Gamma Knife.Methods Clinical data,including general information,method of treatment and therapeutic effect of 278 benign skull base tumors treated by Gamma Knife were studied retrospectively.Results All patients were followed up for at least 2 years.The clinical conditions improved significantly in 130 patients,remained stable in 125 patients,and worsened in 23 patients.The 5 years progression-free survival rate was 89.5%(249/278)by Kaplan-Meier analysis.The results of Log-rank analysis revealed that better results appeared in patients with smaller tumors.≤3 cm compared with those tumors＞3 am(X2=5.41,P=0.02),and in patients experiencing tumor resection compared with those without history of su~ery respectively(X2=3.96,P=0.047).10 of the 11 cases with tumors＞3 cm who were treated by volume-staged prescription achieved local tumor control.Brain edema occurred in 3 patients,apoplexy of tumor in 1 patient,hydrocephalus in 3 patents,dysfunction of cranial nerves in 12 patients.Conclusion For skull base tumor,Gamma Knife is a major choice,with low risk and maybe an alternative for those small tumors.For those residues after craniotomy,Gamma Knife maybe an auxiliary treatment,and it can be cautiously applied in those with large tumors who cannot tolerate surgery for various reasons.

Objective To study the mechanism of p55 inducing cell apoptosis, the 180 bp fragment of Puma promoter was cloned into the pGL3-basic luciferase reporter vector. The biological activity of Pumareporter plasmid was verified by cell transfection. Methods The target fragments of Puma were amplified by RT-PCR method and the fragments were inserted into the pGL3-basic luciferase reporter vector. The acquired Puma-Luc plasmid was transfected into H1299 cell line and detected its activity. Results Sequencing indicated that the amplified Puma promoter is correct. Dual-luciferase Reporter Assay showed the Puma-Luc constructs have promoter activity. Conclusion The cloning of human Puma gene promoter and the construction of its reporter vector were successful. This study will lay the foundation for further research on the function of p53 inducing apoptosis through mitochondrial pathway.

Objective·To establish a multifactorial discriminative model for predicting the degree of infiltration in patients with non-small cell lung adenocarcinoma based on clinically accessible laboratory indicators,such as tumor markers,coagulation function indicators,routine blood count indicators,and biochemical indicators.Methods·A retrospective study was conducted on 202 patients with lung adenocarcinoma admitted to Shanghai Chest Hospital in 2022.Multifactorial Logistic regression analysis was applied to screen independent factors that influenced the predictive infiltration degree of lung adenocarcinoma and to establish a regression model.In addition,machine learning was used to construct a discriminative model,and the area under the receiver operating characteristic curve(AUC)was used to evaluate the discriminative ability of the model to discriminate the degree of infiltration in lung adenocarcinoma patients.Results·A total of 202 patients with lung adenocarcinoma were included in the study,and divided into pre-invasive lesion group(n=59)and invasive lesion group(n=143).Multifactorial Logistic regression analysis revealed that urea,percentage of basophilic granulocytes,and albumin were independent factors for predicting the degree of infiltration of lung adenocarcinoma(all P<0.05).The predictive model expression was P = eX/(1 + eX),where X =(0.534×urea)+(1.527×percentage of basophilic granulocytes)-(1.916×albumin)+ 6.373.Machine learning results showed that the model performed best when urea,fibrinogen,albumin,percentage of basophilic granulocytes,prealbumin and carcino embryonic antigen(CEA)were included.After comparing the performance of 8 machine learning algorithms(based on ridge regression,least absolute shrinkage and selection operator,neural network,random forest,k-nearest neighbors,support vector machine,decision tree,and adaptive boosting algorithms)using the DeLong test,the ridge regression algorithm with the highest AUC was selected.The AUC of the predictive model was calculated to be 0.744(95%CI 0.656-0.832),with a sensitivity of 70.8%and a specificity of 70.2%.Conclusion·A comprehensive differentiation model constructed by urea,fibrinogen,albumin,percentage of basophilic granulocytes,prealbumin and CEA can effectively predict the infiltration degree of the enrolled lung adenocarcinoma patients,holding the potential to provide more precise guidance for the clinical grading and adjunctive treatment of lung adenocarcinoma.