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Loss of peritubular capillaries is a notable feature of progressive renal interstitial fibrosis. Astaxanthin (ASX) is a natural carotenoid with various biological activities. The present study aimed to evaluate the effect of ASX on unilateral ureteral obstruction (UUO)-induced renal fibrosis in mice. For that purpose, mice were randomly divided into five treatment groups: Sham, ASX 100 mg/kg, UUO, UUO + ASX 50 mg/kg and UUO + ASX 100 mg/kg. ASX was administered to the mice for 7 or 14 days following UUO. The results demonstrated that UUO-induced histopathological changes in the kidney tissue were prevented by ASX. Renal function was improved by ASX treatment, as evidenced by decreased blood urea nitrogen and serum creatinine levels. Furthermore, the extent of renal fibrosis and collagen deposition induced by UUO was suppressed by ASX. The levels of collagen I, fibronectin and α-smooth muscle actin were increased by UUO in mice or by transforming growth factor (TGF)-β1 treatment in NRK-52E cells, and were reduced by ASX administration. In addition, ASX inhibited the UUO-induced decrease in peritubular capillary density by upregulating vascular endothelial growth factor and downregulating thrombospondin 1 levels. Inactivation of the TGF-β1/Smad signaling pathway was involved in the anti-fibrotic mechanism of ASX in UUO mice and TGF-β1-treated NRK-52E cells. In conclusion, ASX attenuated renal interstitial fibrosis and peritubular capillary rarefaction via inactivation of the TGF-β1/Smad signaling pathway. [ABSTRACT FROM AUTHOR]

In this paper, we study estimation of a semiparametric panel binary choice model with fixed-effects and continuous endogenous regressors. The proposed procedure combines the smoothed maximum score approach with the control function approach and allows for a fixed effect nonparametric first stage regression. Under some sufficient conditions, we show that the proposed estimator for the finite dimensional parameter is consistent and asymptotically normally distributed. A small scale simulation study demonstrates that the proposed procedure has some practical value. [ABSTRACT FROM AUTHOR]

Abstract\nHIGHLIGHTSUnder the promotion of urban planning and land development policies, the urban spatial structure of China is undergoing a transformation towards polycentricity. The improvement of environmental performance during the process of urban spatial transformation is crucial for urban sustainable development. This paper uses high-resolution population grid data from LandScan for the years 2001–2019 to measure the urban spatial structure of Chinese cities. Then we match the Chinese Industrial Enterprise Database with the Chinese Industrial Enterprise Pollution Emission Database for the years 2001–2014. This paper empirically examines the impact and mechanisms of the polycentric spatial structure of Chinese cities on enterprise pollution reduction at the micro-level. The findings indicate that compared to monocentricity, polycentricity is more conducive to improving enterprise environmental performance. Mechanism tests demonstrate that the improvement in enterprise environmental performance resulting from polycentricity can be achieved through three channels: increasing urban population and density, mitigating urban environmental pollution, and promoting enterprise innovation ability. Heterogeneity analysis reveals that polycentricity is more beneficial for emission reduction among small enterprises, young enterprises and enterprises in regions with higher environmental regulations. This paper provides micro-level evidence and policy implications for further strengthening the aggregation effect of polycentricity and improving enterprise environmental performance in the future.We quantify urban spatial structure using Landscan data in China.Polycentricity is conductive to the enterprise emission reduction of so2.Polycentricity reduces enterprise emission by improving population scale and density.Reliving urban pollution, improving enterprise innovation are also mechanisms.Polycentricity is common in the southeast, southwest and northeast cities of China. [ABSTRACT FROM AUTHOR]