Dexamethasone suppresses osteogenesis of osteoblast via the PI3K/Akt signaling pathway in vitro and in vivo.

The hypofunction of osteoblasts induced by glucocorticoids (GCs) has been identified as a major contributing factor for GC-induced osteoporosis (GIO). However, the biological mechanism underlying the effect of GC in osteoblasts are not fully elucidated. Recent studies implicated an important role of phosphoinositide 3-kinase (PI3K)/protein kinase B(Akt) signaling pathway in the regulation of bone growth. We propose that the PI3K/Akt signaling may be implicated in the process of GC-induced osteogenic inhibition in osteoblasts. In this study, primary osteoblasts were used in vitro and in rats in vivo to evaluate the biological significance of the PI3K/Akt pathway in GC-induced bone loss. In vivo, dexamethasone (Dex)-treated rats had low bone mineral density and decreased expression levels of alkaline phosphatase (ALP), osteocalcin (OCN), and phosphorylated Akt (p-Akt) in bone tissue. In vitro study shows that Dex over the dose of 10-8 M remarkably inhibited cellular osteogenesis, as represented by decreased cell viability, lessened ALP activity, and suppressed osteogenic protein expressions including ALP and OCN. Meanwhile, a dramatic downregulation in the PI3K/Akt pathway phosphorylation was also observed in Dex-treated osteoblasts. These changes were marked rescued by treatment with a PI3K agonist 740Y-P. Moreover, downregulation of ALP and OCN expressions by LY294002 can mimic the suppressive effects of Dex. These data together reveal that the suppressed PI3K/Akt pathway is involved in the regulatory action of Dex on osteogenesis.

[Study on Multi-Bands Recognition for Varieties of Mutton by Using Hyperspectral Technologies].

This paper focused on the research on identifying and classifying for mutton varieties of Tan-han hybrid sheep,Yanchi Tan-sheep and small-tailed sheep in Ningxia by using visible/ near-infrared (400~1 000 nm). Near infrared (900~1 700 nm) hyperspectral technologies, baseline and SG convolution smoothing spectra pretreatment methods were applied respectively according to the characteristics of different spectrum bands; the characteristic wavelengths were extracted by using successive projection algorithm (SPA);then combined with linear discriminant analysis (LDA) and radial basis kernel function of support vector machine (RBFSVM) model were applied to identify the different mutton varieties under characteristic wavelengths and full-wave bands. Results showed that there were good effects for mutton varieties identification in different hyperspectral bands, among which Baseline-Fullwave-RBFSVM and the same models under 12 characteristic wavelengths obtained accuracy of 100% and 98.75% in 400~1 000 nm respectively, and Baseline-Fullwave-RBFSVM and the same models under 7 characteristic wavelengths obtained accuracy of 96.25% and 87.80% in 900~1 700 nm respectively.The identification accuracy of RBFSVM nonlinear classification was higher than the LDA linear discriminant result, meanwhile the identification accuracy in 400~1 000 nm bands was better than in 1 000~1 700 nm bands, which explained that the differences of color and texture were more significant than the component contents among the 3 varieties mutton. Combined hyperspectral technologies with RBFSVM models can obtain a better recognition effect of mutton varieties.