The design and practice of graduation project is not only an important part of teaching plan on pharmaceutical students,but also a good opportunity to train and improve their scientific research ability.In this paper,taking the practical training of graduation project on pharmaceutical students as an example,and combined with the actual teaching work,some experience from the graduation project selection,experiment design,data collection,writing papers and oral defense will be separately discussed about how to train the scientific research ability of pharmaceutical students.Through designing and practicing of the graduation project,the comprehensive quality and scientific research ability of pharmaceutical students have been effectively trained and promoted,which will lay a good foundation for continuing postgraduate research or taking drug research jobs.

Objective To investigate the distribution of B cells in both tumor and non-tumor tissues of gastric cancer patients,analyze their phenotypic characteristics and explore the impact on T cell proliferation.Methods Immunohistochemical staining was utilized to detect the expression of B cell surface marker CD 19 in tumor and non-tumor tissues from 33 gastric cancer patients.The expression levels of chemokine receptors and immunoglobulin molecules on B cells in both tumor and non-tumor tissues were measured using flow cytometry.Chemotaxis experiments were conducted to examine the role of the CXCL12-CXCR4 axis in B cell chemotaxis.B cells isolated and purified from both tissue types were co-cultured with autologous peripheral T cells to assess their effect on T cell proliferation.Results There were significantly more B cells infiltrated in tumor tissues than those infitrated in the non-tumor tissues of gastric cancer patients(P＜0.01),and CXCR4 was highly expressed on tumor-infiltrating B cells compared with B cells derived from non-tumor tissues(P＜0.05).The Cancer Genome Atlas(TCGA)analysis indicated that the expression level of CXCL12 in tumor tissues was positively correlated with the expression level of CD19 in gastric cancer patients(r=0.15,P＜0.01).And the expression level of CXCL12 in tumor tissues of the gastric cancer patients was also positively correlated with the number of B cells infiltrated in tumor tissues.Chemotaxis experiments confirmed that the CXCL12-CXCR4 axis was involved in promoting B cell chemotaxis(P＜0.05).Although B cells in tumor and non-tumor tissues had similar levels of IgM,IgG,and IgA expression,tumor-infiltrating B cells significantly inhibited the proliferation of T cells when compared with B cells derived from non-tumor tissues(P＜0.01).Conclusion There are more B cells infiltrated in gastric cancer tissues,which may be recruited to tumor tissues through the CXCL12-CXCR4 axis,and then inhibit T cell proliferation to promote the progression of gastric cancer.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.