P2X_(1) receptor-mediated pressor responses in the anesthetized mouse

P2X_(1) receptors and adrenoceptors are mainly responsible for vasoconstriction in a variety of blood vessels.However,previous studies have shown that α,β-methylene adenosine 5'-triphosphate(α,β-MeATP),a stable analogue of ATP,can induce both pressor and depressor responses in la boratory animals.In this study,the effects of increasing intravenous doses of α,β-MeATP and noradrenaline(NA)(0-30 nmol/kg)administered at 20 min intervals on systolic(SBP),diastolic(DBP)and mean(MBP)blood pressure in groups of anesthetized mice(n=6)were compared.Both α,β-MeATP and NA caused transient,dose-dependent increases in SBP,DBP and MBP but the effect of α,β-MeATP was more rapid and significantly larger at doses of 10 and 30 nmol/kg(P<0.01).At the dose of 30 nmol/kg,α,β-MeATP increased SBP,DBP and MBP by 65.8±7.0,65.7±5.0 and 65.7±5.5 mmHg,respectively,compared to increases of 36.8±4.6,33.3±4.9 and 34.5±4.7 mmHg,respectively,produced by NA.These results indicate P2X_(1) receptors play an important role in BP regulation although purinergic vasoconstriction alone may not explain the more potent pressor response to α,β-MeATP in the anesthetized mouse.

StarIn:An Approach to Predict the Popularity of GitHub Repository

The popularity of repository in GitHub is an important indicator to evaluate its quality.Exploring the trend of popularity is a crucial guideline to study its development potential.Herein,StarIn,a stargazer-influence based approach is proposed to predict the popularity of GitHub repository.Using the followers in GitHub as a basic dataset,stargazer-following based network was established.The indicator,stargazer influence,was measured from three aspects of basic influence,network dynamic influence and network static influence.Experiments was conducted,and the correlation of StarIn was analyzed with the popularity of repository from the perspective of six characteristics.The experimental evaluation provides an interesting approach to predict the popularity of repositories in GitHub from a new perspective.StarIn achieves an excellent performance of predicting the popularity of repositories with a high accurate rate under two different classifiers.