BACKGROUND:With the promotion of 3D printing technology, 3D printing scaffolds for bone tissue engineering have become the new ideas for jaw bone repair. OBJECTIVE:To compare the physical and biological properties of sheep vertebral bone meal/polyvinyl alcohol (PVA) scaffold, nano-hydroxyapatite (nHA)/PVA scaffold, and sheep vertebral bone meal/PVA nonporous bone plate. METHODS:3D printing technology was used to print sheep vertebral bone meal/PVA scaffold, nHA/PVA scaffold, and sheep vertebral bone meal/PVA nonporous bone plate. Porosity, morphology, water absorption rate and mechanical properties of different scaffolds were detected. Three kinds of scaffolds were al used to culture bone marrow mesenchymal stem cel s, and cel proliferation ability was detected using cel counting kit-8 at 1, 4, 7 days of culture. RESULTS AND CONCLUSION:Under scanning electron microscope, the sheep vertebral bone meal/PVA scaffold and nHA/PVA scaffold exhibited regular and interconnected pores with good continuity and clear network structure;the sheep vertebral bone meal/PVA nonporous bone plate had no obvious pores;however, it had dense and evenly distributed micropores with different sizes on its surface. The porosity of nHA/PVA scaffold was lower than that of the sheep vertebral bone meal/PVA scaffold (P<0.05). The water absorption rate was highest for the nHA/PVA scaffold fol owed by the sheep vertebral bone meal/PVA scaffold and the sheep vertebral bone meal/PVA nonporous bone plate (P<0.05). In contrast, the scaffold toughness was highest for the sheep vertebral bone meal/PVA nonporous bone plate, fol owed by the sheep vertebral bone meal/PVA scaffold and nHA/PVA scaffold. In addition, the cel proliferation activity of cel s cultured on the sheep vertebral bone meal/PVA scaffold was significantly higher than that cultured on the other two kinds of scaffolds. Taken together, the 3D printing sheep vertebral bone/PVA scaffold has good physical and chemical performance.

Objective To study the role of glucagon-like peptide-1 (GLP-1) analogue liraglutide played in the proliferation of CD4+CD25 T cells in normal people and newly-onset type 1 diabetic patients,and to evaluate the possible immune regulatory role of liraglutide in the therapy of type 1 diabetes.Methods CD4+ CD25-T cells of 10 normal people and 10 newly-onset type 1 diabetic patients were separated from peripheral blood by MACS immunomagnetic beads and stimulated by Human T-Activator CD3/CD28 Dynabeads to proliferate.CFSE labeling technique was used to evaluate the proliferation of CD4+ CD25-T cells by flow cytometry.Liraglutide of different concentrations(0,25,50,and 100 nmol/ml) was added to the proliferation system,then the proliferation of CD4+CD25-T cell was measured.Results (1) Liraglutide suppressed the proliferation of CD4+ CD25-T cells from either normal people or type 1 diahetic patients with dose-dependent manner (P ＜ 0.05).(2) Under the different concentrationsofliraglutide,the proliferation ofCD4+CD25 T cells from diabetic patients was mueh more robust than that of normal people (P＜0.01).(3) The inhibitory effects of liraglutide on CD4+ CD25-T cells proliferation in normal people and diabetic patients were similar (P＞0.05).Conclusion The proliferation of CD4+ CD25 T cells in type 1 diabetic patients was more robust than normal people,which indicated cellular immune dysfunction in type 1diabetes.Liraglutide inhibits the proliferation of CD4+ CD25-T cells of type 1 diabetic patients in vitro.The immunosuppression effect of liraglutide may have potential value in the treatment of type 1 diabetes.

This study is to explore the effects of quercetin (QUE) on the 3 week-old mice ovarian development and relative hormone levels. The 3 week-old mice were exposed to QUE (45, 25, and 5 mg x kg(-1) x hd(-1)) by gavage for 50 days. The estrous cycle during 50 days and the changes of hormone level such as FSH, LH, etc were monitored. Moreover, the ovaries were removed after sacrifice. The organ index was measured, and the ratios of different stages of follicles were analyzed by HE staining. Furthermore, the proportion of PCNA positive cells during all stages was detected by immunohistochemistry. The results showed that QUE could increase body weight of mice and reduce the anogenital distance (AGD) to some extent, and was able to disrupt mice's estrous cycle, but it could not extend or reduce the cycle regularity. It increased ovarian organ index with a dose-dependent manner. The proportion of the primordial follicle and secondary follicles rose obviously, and that of mature follicles', atretic follicles' and corpus luteums' reduced, while primordial follicle had no change. Immunohistochemistry analysis showed that QUE could effectively increase the percentage of proliferating cells in all kinds of follicles. Serum hormone assay showed that there were significant changes of FSH and LH levels. In summary, QUE showed an estrogen-like effect on mice's ovarian development. The weight of ovary, the proportion of all kinds of follicles, the development of ovarian cells and the level of plasma hormone in mice were altered obviously by oral administration of QUE.

Objective To compare clinical effect of gonadotropin releasing hormone agonist(GnRH-a) alone and GnRH-a combined with low-dose dydrogesteronea and estradiol valerate on sex hormone, hypoestrogenic symptoms, quality of life and bone mineral density (BMD)in treatment of endometriosis.Methods Seventy patients with moderate or severe endometriosis, who were diagnosed by laparotomy or laparoscopic surgery within two months, were randomly assigned into two groups.35 patients in GnRH-a group were treated by goserelin (3.6 mg)for three months, and 35 patients in add-back group were treated by goserelin (3.6 mg)combined with estradiol valerate 0.5 mg and dydrogesteronea 5 mg daily.Before and after the treatment, clinical parameters were recorded and analyzed, including visual analog scale (VAS), medical outcomes survey short form 36 (SF-36), Kupperman menopausal index(KMI), BMD, the serum level of follicle stimulating hormone (FSH), estradiol (E_2) and bone gla-protein (BGP) .The first menstruation and VAS were also followed up after treatment.Results Every 3 cases in two groups lost follow-up.(1)Reproductive hormone: the level of E_2 in add-back group [(94 ± 71) pmol/L]was significantly higher than (54±52) pmol/L in GnRH-a group(P <0.01).The level of FSH in add-back group [(3.0 ± 1.9) U/L]was significantly lower than (5.7 ± 2.9) U/L in GnRH-a group (P < 0.05).(2) VAS: after treatment, VAS in both group decreased significantly when compared with that before treatment(P < 0.05), and remained until menstruated.(3) KMI: KMI in add back-group (10 ± 8) was significantly lower than (14 ± 6) in GnRH-a group (P < 0.05).(4) BMD: compared with that before treatment, BMD decreased significantly after treatment in GnRH-a group (P < 0.05), no remarkable difference of BMD was observed before and after treatment in add-back group.Before treatment, serum BGP in both groups did not show statistical difference.After treatment, the level of BGP in GnRH-a group [(7932±5206) ng/L]was significantly higher than (5419±2917) ng/L in add-back group (P <0.05).Conclusions GnRH-a combined with estrogen-progesterone regimen could relieve pain from endometriosis as effectively as GnRH-a alone and reduce hypoestrogenic symptoms and bone loss.Therefore,it is a safe and effective treatment.

Logistic regression is a kind of multiple regression method to analyze the relationship between a binary outcome or categorical outcome and multiple influencing factors, including multiple logistic regression, conditional logistic regression, polytomous logistic regression, ordinal logistic regression and adjacent categorical logistic regression. This paper illustrates the basic principle, independent variable selection and assignment, applied condition, model evaluation and diagnosis for multiple logistic regression model. Moreover, the principle and application for polytomous logistic regression and ordinal logistic regression models were also introduced. By providing SAS codes and detailed explanations of the result for an example of obesity, readers could be able to better understand logistic regression model, and apply this method correctly to their research and daily work, so as to improve their capacity of the data analysis.

Logistic regression is a kind of multiple regression method to analyze the relationship between a binary outcome or categorical outcome and multiple influencing factors, including multiple logistic regression, conditional logistic regression, polytomous logistic regression, ordinal logistic regression and adjacent categorical logistic regression. This paper illustrates the basic principle, independent variable selection and assignment, applied condition, model evaluation and diagnosis for multiple logistic regression model. Moreover, the principle and application for polytomous logistic regression and ordinal logistic regression models were also introduced. By providing SAS codes and detailed explanations of the result for an example of obesity, readers could be able to better understand logistic regression model, and apply this method correctly to their research and daily work, so as to improve their capacity of the data analysis.

Multiple Linear Regression (MLR) is a generalization of simple linear regression and is one of the commonly used models in multivariate statistical analysis. This article introduces the MLR model from the perspective of practical application. Four parts, including basic principle, application examples, the application condition and diagnosis, and the extension of the model, are sequentially illustrated in this article. Particularly, in the last part, alternative methods of the model are introduced when the application condition of the model is not met. We sincerely hope that this article could make our audiences have a better understanding of the MLR model in order to improve the efficiency of data utilization and statistical analysis by correctly performing this model in their research.

Logistic regression is a kind of multiple regression method to analyze the relationship between a binary outcome or categorical outcome and multiple influencing factors, including multiple logistic regression, conditional logistic regression, polytomous logistic regression, ordinal logistic regression and adjacent categorical logistic regression. This paper illustrates the basic principle, independent variable selection and assignment, applied condition, model evaluation and diagnosis for multiple logistic regression model. Moreover, the principle and application for polytomous logistic regression and ordinal logistic regression models were also introduced. By providing SAS codes and detailed explanations of the result for an example of obesity, readers could be able to better understand logistic regression model, and apply this method correctly to their research and daily work, so as to improve their capacity of the data analysis.

Analyses of the multivariate regression model are ued very widely in the medical research. Analytical methods of the mutivariate regression model including multiple linear regression, logistic regression, Poisson regression and Cox proportional hazard model were introduced in this article. The contents of the article covered the application conditions of regression models, analytical procedures, strategies of selecting independent variables, extended discussions of regression models and application notes. It is expected that authors could understand the principle of the mutivariate regression model, accurately use these analytical methods in their research, improve the efficiency of data utilization, and enhance the level of statistical analyses.

Vaccination is the most effective way to prevent influenza and severe outcoming caused by influenza viruses.Health care workers(HCW) are exposed to patients with influenza and they are at high risk of occupationally acquired influenza and of causing nosocomial infection among patients,increasing the incidence rate,the risk of severe and death of patients.Improving the influenza immunization in HCW can not only reduce the prevalence of themselves and keep a weel-oiled of health care facilities during the influenza seasons,but also reduce the risk of severe and death among patients and increase the influenza vaccine uptake in whole population.At present,the influenza immunization coverage of HCW is low.The obstacles and myths of influenza vaccine are barriers for vaccine uptake among HCW.The various strategies are critical in order to improve the influenza coverage rates of HCW.