Traditional Chinese medicine Pien-Tze-Huang ameliorates LPS-induced sepsis through bile acid-mediated activation of TGR5-STAT3-A20 signalling

Pien Tze Huang(PZH),a class-1 nationally protected traditional Chinese medicine(TCM),has been used to treat liver diseases such as hepatitis;however,the effect of PZH on the progression of sepsis is unknown.Here,we reported that PZH attenuated lipopolysaccharide(LPS)-induced sepsis in mice and reduced LPS-induced production of proinflammatory cytokines in macrophages by inhibiting the activation of mitogen-activated protein kinase(MAPK)and nuclear factor-kappa B(NF-κB)signalling.Mechanistically,PZH stimulated signal transducer and activator of transcription 3(STAT3)phosphorylation to induce the expression of A20,which could inhibit the activation of NF-κB and MAPK signalling.Knockdown of the bile acid(BA)receptor G protein-coupled bile acid receptor 1(TGR5)in macrophages abolished the effects of PZH on STAT3 phosphorylation and A20 induction,as well as the LPS-induced inflammatory response,suggesting that BAs in PZH may mediate its anti-inflammatory effects by activating TGR5.Consistently,deprivation of BAs in PZH by cholestyramine resin reduced the effects of PZH on the expression of phosphorylated-STAT3 and A20,the activation of NF-κB and MAPK signalling,and the production of proinflammatory cytokines,whereas the addition of BAs to cholestyramine resin-treated PZH partially restored the inhibitory effects on the production of proinflammatory cytokines.Overall,our study identifies BAs as the effective components in PZH that activate TGR5-STAT3-A20 signalling to ameliorate LPS-induced sepsis.

Social network learning efficiency in the principal-agent relationship

Under the bounded rationality assumption,a principal rarely provides an optimal contract to an agent.Learning from others is one way to improve such a contract.This paper studies the efficiency of social network learning(SNL)in the principal–agent framework.We first introduce the Cobb-Douglas production function into the classic Holmstrom and Milgrom(1987)model with a constant relative risk-averse agent and work out the theoretically optimal contract.Algorithms are then designed to model the SNL process based on profit gaps between contracts in a network of principals.Considering the uncertainty of the agent's labor output,we find that the principals can reach a consensus that tends to result in overcompensation compared to the optimal contract.Then,this study examines how network attributes and model parameters impact learning efficiency and posits several summative hypotheses.The simulation results validate these hypotheses,and we discuss the relevant economic implications of the observed changes in SNL efficiency.

A cylindricalÖffner stretcher based on ternary reflector for femtosecond petawatt-level laser system

A cylindricalÖffner stretcher based on ternary reflector(COSTER)is proposed and analyzed.Compared with the traditionalÖffner stretcher,the COSTER has no off-axis aberration in the multipass configuration,and the output laser of COSTER has lower spectral phase noise and higher temporal contrast in the far field.The COSTER is quite suitable to be used in multipetawatt laser facilities,and it might be the preferred stretcher configuration for ultrafast and ultra-intense lasers.