Optimization of Supercritical Fluid Extraction of Tea Flower Polysaccharides by Using Response Surface Method

Polysaccharide production from tea flower(TFPS) was carried out using supercritical fluid extraction(SFE).Response surface methodology(RSM),based on a five level,four variable small central composite design,was employed to obtain the best possible combination of extraction time,pressure,temperature and ethanol content of modifier for maximum production.The optimum conditions were as follows:extraction time of 170 min,pressure of45 MPa,temperature of 75 ℃,and 50% aqueous ethanol solution as modifier.Under these conditions,the experimental yield was 6.56 ± 0.37%,which was similar to the value predicted by the model.Monosaccharide composition of TFPS was fucose,rhamnose,arabinose,xylose,galactose,glucose,mannose,fructose,ribose,galacturonic acid and glucuronic acid in a molar percent of 31.69,0.21,0.49,1.29,35.82,0.97,1.63,18.34,7.88,1.06 and 0.63.Compared to other extraction methods,SFE could achieve higher yield and gain more types of monosaccharide.

Prognostic significance of serum inflammation indices for different tumor infiltrative pattern types of gastric cancer

BACKGROUND Inflammatory indices are considered to be potential prognostic biomarkers for patients with gastric cancer(GC).However,there is no evidence defining the prognostic significance of inflammatory indices for GC with different tumor infiltrative pattern(INF)types.AIM To evaluate the significance of inflammatory indices and INF types in predicting the prognosis of patients with GC.METHODS A total of 962 patients who underwent radical gastrectomy were retrospectively selected for this study.Patients were categorized into the expansive growth type(INFa),the intermediate type(INFb),and the infiltrative growth type(INFc)groups.The cutoff values of inflammatory indices were analyzed by receiver operating characteristic curves.The Kaplan–Meier method and log-rank test were used to analyze overall survival(OS).The chi-square test was used to analyze the association between inflammatory indices and clinical characteristics.The independent risk factors for prognosis in each group were analyzed by univariate and multivariate analyses based on logistic regression.Nomogram models were constructed by R studio.RESULTS The INFc group had the worst OS(P<0.001).The systemic immune-inflammation index(P=0.039)and metastatic lymph node ratio(mLNR)(P=0.003)were independent risk factors for prognosis in the INFa group.The platelet-lymphocyte ratio(PLR)(P=0.018),age(P=0.026),body mass index(P=0.003),and postsurgical tumor node metastasis(pTNM)stage(P<0.001)were independent risk factors for prognosis in the INFb group.The PLR(P=0.021),pTNM stage(P=0.028),age(P=0.021),and mLNR(P=0.002)were independent risk factors for prognosis in the INFc group.The area under the curve of the nomogram model for predicting 5-year survival in the INFa group,INFb group,and INFc group was 0.787,0.823,and 0.781,respectively.CONCLUSION The outcome of different INF types GC patients could be assessed by nomograms based on different inflammatory indices and clinicopathologic features.