Effects of dietary phytosterols on growth performance, antioxidant status, and meat quality in Partridge Shank chickens.

To investigate the effects of dietary phytosterols (PS) on growth performance, antioxidant status, and meat quality of Partridge Shank chickens, a total of 256 1-day-old male Partridge Shank chicks were randomly assigned into 4 dietary treatments, and each of them replicated 8 times with 8 chicks per replicate. Birds in the 4 treatments were fed a basal diet supplemented with 0 (Control group), 20, 40, and 80 mg/kg PS for 50 D, respectively. Dietary supplementation of PS quadratically increased average daily gain of chickens during the grower and overall periods, whereas linearly decreased the feed-to-gain ratio during the starter period. Compared with control group, a significant increase in average daily gain during the grower and overall periods was observed in chickens fed the basal diet supplemented with 40 mg/kg PS. Increasing PS addition linearly increased serum glutathione peroxidase (GSH-Px) activity at 21 and 50 D and hepatic GSH-Px and superoxide dismutase activities at 21 D, whereas linearly decreased malondialdehyde concentration of breast muscle at 50 D. Meanwhile, 40 mg/kg PS supplementation significantly increased serum GSH-Px activity, and hepatic superoxide dismutase and GSH-Px activities at 21 D as compared with the control. PS supplementation linearly and quadratically decreased drip loss (24 and 48 h postmortem) and luminance value (24 h postmortem) of breast muscle in broilers at 50 D, and there was statistical difference between the control and PS-supplemented group. In conclusion, PS supplementation can improve growth performance, antioxidant status, and meat quality of Partridge Shank chickens, with its optimum level in Partridge Shank chickens' diet being 40 mg/kg.

Effect of FGF2 on the activity of SPRYs/DUSP6/ERK signaling pathway in endometrial glandular epithelial cells of endometriosis.

OBJECTIVE: We aimed at exploring the positive feedback loop in eutopic and ectopic endometrial glandular epithelial cells (EuECs and EECs) in endometriosis. MATERIALS AND METHODS: Normal epithelial cells (NECs), EuECs and EECs were treated with fibroblast growth factor (FGF)2, FGF2 neutralizing antibody, mitogen-activated protein kinases (MAPKs) inhibitors U0126 and PD98059. FGF2 protein level was detected by enzyme-linked immunosorbent assay (ELISA). The expressions of FGF2, FGF receptor 1 (FGFR1), extracellular signal-regulated kinase (ERK)1/2/pERK1/2 and Sproutys (SPRYs) (Sprouty1, Sprouty2, Sprouty4) and dual specificity phosphatase 6 (DUSP6) were detected by Western blot. The mRNA levels of FGF2, FGFR1 (FGF receptor 1), SPRYs (Sprouty1, Sprouty2, Sprouty4) and DUSP6 mRNA were detected by RT-PCR. RESULTS: Among treatment groups, the content of FGF2 in EuECs and EECs was significantly higher than that in NECs (p < 0.05). The mRNA and protein levels of FGF2, FGFR1, SPRYs (Sprouty1, Sprouty2, Sprouty4) and DUSP6 in EuECs and EECs were increased after adding FGF2 (p < 0.05), but decreased after adding FGF2 neutralizing antibody, no significant change was found in NECs (p > 0.05). The inhibitory effect of PD9805 on NECs was not significantly different from that of U0126 (p > 0.05); however, the inhibitory effects of PD9805 on EuECs and EECs were significantly lower than those of U0126 (p< 0.05). CONCLUSIONS: The positive feedback loop existed in EuECs and EECs, but maybe not in NECs. The results may provide the guideline to treat endometriosis patients.

Up-regulation of long non-coding RNA PCAT-1 correlates with tumor progression and poor prognosis in gastric cancer.

OBJECTIVE: Long non-coding RNAs (lncRNAs), emerging non-coding RNAs, have been proved to serve as a critical role in the proliferation, metastasis apoptosis of gastric cancer. However, the potential biological role PCAT-1 in gastric cancer (GC) remains undefined. The present study aimed to investigate the expression and clinical significance of PCAT-1 in GC. PATIENTS AND METHODS: The expression of PCAT-1 was detected with a quantitative Real-time PCR assay. The association between PCAT-1 expression and clinicopathological factors, as well as survival rates, was analyzed. Cox proportional-hazards regression analysis was applied in order to estimate univariate and multivariate hazard ratios for overall survival. Then, effects of PCAT-1 on the biological behavior of GC cells were investigated. RESULTS: We found that PCAT-1 expression was elevated in GC tissues and cell lines, and PCAT-1 levels were highly positively correlated with invasion depth (p < 0.001), TNM stages (p < 0.001) and lymphatic metastasis (p = 0.003). The biological function of PCAT-1 was explored and the results showed silencing of PCAT-1 could suppress cell proliferation, migration and invasion in vitro. Kaplan-Meier analysis demonstrated that increased PCAT-1 expression contributed to poor overall survival (OS) (p < 0.01). Furthermore, in a multivariate Cox model, our results showed that PCAT-1 expression was an independent poor prognostic factor for OS in GC. CONCLUSIONS: Our finding suggested that PCAT-1 may have potential roles as a biomarker and/or a therapeutic target in gastric cancer.

[Effect of combination model on fitting cancer mortality and prediction].

Objective: To reduce the cancer burden in the Jinchang cohort and provide evidence for developing cancer prevention strategies and performing effectiveness evaluation in the Jinchang cohort. We are fitting thirteen years of cancer mortality data from the Jinchang cohort by using six kinds of predicting methods to compare relative fitness and to select good predicting methods for the prediction of cancer mortality trends. Methods: The mortality data of cancer in Jinchnag cohort from 2001-2013 were fitted using six kinds of predicting methods: dynamic series, linear regression, exponential smoothing, autoregressive integrated moving average (ARIMA) model, grey model (GM), and Joinpoint regression. Weight coefficients of combination models were calculated by four methods: the arithmetic average method, the variance inverse method, the mean square error inverse method, and the simple weighted average method. Results: The cancer mortality was fitted and compared by using six kinds of forecasting methods; the fitting precision of the Joinpoint linear regression had the highest accuracy (87.64%), followed by linear regression (87.32%), the dynamic series (86.99%), GM (1, 1) (86.25%), exponential smoothing (85.72%) and ARIMA (1, 0, 0) (81.98%), respectively. Prediction accuracy of the combination model derived from GM (1, 1) and linear regression (>99%) was higher than that of the combination model derived from ARIMA (1, 0, 0) and GM (1, 1). The combination model derived from the GM (1, 1) and linear regression, with weight coefficients based on the arithmetic average method and the mean square error inverse method, had the best prediction effect of the four weight calculation methods. Conclusion: Prediction accuracy of the combination model, with accuracy >95%, was higher than that of the single prediction methods.