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| 1 | Aquaporin 5 is degraded by autophagy in diabetic submandibular gland显示文摘Autophagy is a catabolic process which is involved in the development of many diseases including diabetes mellitus and its complications. Hyposalivation is a common complication of diabetes mellitus, whereas its mechanism remains unclear. Here, we observed that the stimulated salivary flow rate of SMG was significantly decreased in db/db mice, a diabetic mice model. The expressions of aquaporin 5(AQP5), a water channel protein, were decreased, whereas the m RNA level of AQP5 was increased in SMGs of both diabetic patients and mice. Under transmission electron microcope, more autophagosomes were detected in diabetic SMGs. Expressions of autophagy related proteins LC3 II, Beclin-1 and ATG5 were increased, meanwhile autophagy substrate p62 was decreased in SMGs of diabetic patients and mice, indicating that autophagy was activated in diabetic SMG.Double immunofluorescence staining showed that the colocalization of AQP5 and LC3 was increased in SMGs of diabetic mice.In cultured SMG-C6 cells, high glucose(HG), but not high osmotic pressure, reduced AQP5 protein expression and induced autophagy. Moreover, inhibition of autophagy by 3-methyladenin, an autophagy inhibitor, or by autophagy-related gene 5 siRNA, decreased HG-induced AQP5 reduction in SMG-C6 cells. Additionally, the expression of p-p85, p-Akt and p-mTOR were decreased in HG-treated SMG-C6 cells. Pretreatment with 740 Y-P, a PI3 K agonist, significantly suppressed HG-induced autophagy and AQP5 degradation. Taken together, these results indicate that autophagy plays a crucial role in AQP5 degradation in diabetic SMG via PI3 K/Akt/mTOR signaling pathway, which contributes to the dysfunction of diabetic SMG. Our study provides a novel mechanism of diabetic hyposalivation. | Yan Huang Xijin Shi Qianying Mao Yan Zhang Xin Cong Xueming Zhang Zhejing Zhang Liling Wu Ruolan Xiang Guangyan Yu | 2018 | Science China(Life Sciences)2018,61,9: | 5 |
| 2 | Evaluation and Hydrological Application of CMADS Reanalysis Precipitation Data against Four Satellite Precipitation Products in the Upper Huaihe River Basin, China显示文摘Satellite-and reanalysis-based precipitation products are important data source for precipitation, particularly in areas with a sparse gauge network. Here, five open-access precipitation products, including the newly released China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool(SWAT) model(CMADS)reanalysis dataset and four widely used bias-adjusted satellite precipitation products [SPPs;i.e., Tropical Rainfall Measuring Mission(TRMM) Multisatellite Precipitation Analysis 3B42 Version 7(TMPA 3B42V7), Climate Prediction Center(CPC) morphing technique satellite–gauge blended product(CMORPH-BLD), Climate Hazards Group Infrared Precipitation with Station Data(CHIRPS), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record(PERSIANN-CDR)], were assessed. These products were first compared with the gauge observed data collected for the upper Huaihe River basin, and then were used as forcing data for streamflow simulation by the Xin’anjiang(XAJ) hydrological model under two scenarios with different calibration procedures. The performance of CMADS precipitation product for the Chinese mainland was also assessed. The results show that:(1) for the statistical assessment, CMADS and CMORPH-BLD perform the best, followed by TMPA 3B42V7, CHIRPS, and PERSIANN-CDR, among which the correlation coefficient(CC) and rootmean-square error(RMSE) values of CMADS are optimal, although it exhibits certain significant negative relative bias(BIAS;-22.72%);(2) CMORPH-BLD performs the best in capturing and detecting rainfall events, while CMADS tends to underestimate heavy and torrential precipitation;(3) for streamflow simulation, the performance of using CMADS as input is very good, with the highest Nash–Sutcliffe efficiency(NSE) values(0.85 and 0.75 for calibration period and validation period, respectively);and(4) CMADS exhibits high accuracy in eastern China while with significant negative BIAS, and the performance declines from southeast to northwest. The statistical and hydrological evaluations show that CMADS and CMORPH-BLD have high potential for observing precipitation. As high negative BIAS values showed up in CMADS evaluation, further study on the error sources from original data and calibration algorithms is necessary. This study can serve as a reference for selecting precipitation products in datascarce regions with similar climates and topography in the Global Precipitation Measurement(GPM) era. | Shanhu JIANG Ruolan LIU Liliang REN Menghao WANG Junchao SHI Feng ZHONG Zheng DUAN | 2020 | Journal of Meteorological Research2020,34,5: | 1 |
| 3 | Promoting hybrid twins structure to reduce yield asymmetry of rolled AZ31 plates by combining side-rolling and torsion显示文摘In this work,an as-rolled AZ31 square bar with c-axis//ND(normal direction)texture was used.Side-rolling and reciprocating torsion were performed to treat the bar.Microstructure evolution and tensile-compressive properties were investigated in detail.Initial rolled AZ31 bar exhibits a large yield asymmetry along the rolling direction(RD).Reciprocating torsion can generate extension twins to introduce twin boundaries and twin-texture.The twin structure can reduce yield asymmetry.However,only limited regions in the rolled AZ31 bar can be twinned during torsion.Pre-side-rolling along the transverse direction(TD)can generate two texture components(c-axis//TD texture and c-axis//ND texture)by introducing profuse{10–12}twins.Such dual texture components help increase the regions which are favorable for twinning during torsion.Finally,combining side-rolling and reciprocating torsion generates hybrid{10–12}twins structure on the entire cross-section,resulting in a remarkably low yield asymmetry.The relevant mechanisms were discussed in detail. | Bo Song Meng Wang Ruolan Shi Zhiwen Du Ning Guo Fang Wang Shengfeng Guo | 2023 | Journal of Magnesium and Alloys2023,11,6: | 1 |