疏血通抑制Bim依赖的小脑颗粒神经元凋亡

目的探究疏血通及其主要成分水蛭素对Sprague-Dawley（SD）大鼠小脑颗粒神经元（CGNs）凋亡的影响及机制。方法体外成熟7 d的CGNs分为存活对照组（用含K+浓度为25 mmol/L的培养基，即25 K组）、凋亡组（用含K+浓度为5 mmol/L的培养基，即5 K组）、以1/50、1/40、1/30、1/20、1/10浓度（稀释50、40、30、20、10倍）疏血通注射液处理组（25 K以及5 K合并疏血通处理组）以及对应不同浓度（2 U/mL、2.5 U/mL、3.34 U/mL、5 U/mL、10 U/mL）水蛭素处理组（25 K以及5 K合并水蛭素处理组），用Hoechst染色法观察并统计凋亡率。在蛋白印迹实验中，在25 K和5 K条件下用1/50、1/10浓度疏血通注射液以及对应2 U/mL、10 U/mL浓度水蛭素处理细胞，用Western blot法检测Cleaved Caspase-3、Bim、VEGF的表达水平。结果核染色结果显示，与25 K存活对照组比较，5 K凋亡组凋亡率增加；与25 K存活对照组比较，不同浓度疏血通注射液与水蛭素处理细胞后凋亡率无明显变化；与5 K凋亡组比较，不同浓度疏血通注射液与水蛭素处理细胞后凋亡率下降，且随着浓度的升高，凋亡率下降越明显。Western blot结果显示，与5 K凋亡组比较，不同浓度疏血通与水蛭素处理细胞后Cleaved Caspase-3、Bim蛋白表达水平均下降，VEGF蛋白表达水平升高。结论疏血通及其主要成分水蛭素通过抑制Bim表达，进而抑制线粒体依赖的小脑颗粒神经元凋亡

hydrophilicinteractionliquidchromatographycoupledwithmassspectrometryforserummetabolomicsanalysisofbladdercancer

Bladder cancer (BC) is a fatal malignancy with considerable mortality, and can cause a serious threat to human health. The successful treatment of bladder cancer relies mainly on early detection. Biomarkers are vital to early diagnosis of bladder cancer, and metabonomics play an important role in biomarkers finding. In this study, we used 69 polar metabolites to select the appropriate separation system and develop the zwitterionic hydrophilic chromatography/mass spectrometry (ZIC-HILIC/MS) method. In this method, 50 representative compounds had broad linear ranges between 2-6 orders of magnitude. Moreover the limit of detection of the method was below ng/mL levels. The analysis for six serum samples prepared in parallel showed that this method had good reproducibility, and the RSDs of more than 85% metabolites were less than 30%. Based on this method, it was found that 35 metabolites had significant differences in BC group and healthy control. After screening and validation, the combination of chenodeoxycholic acid, eicosenoic acid, GPC, dodecenoic acid and cystine was a potential biomarker to distinguish BC and normal group. These results indicated that the ZIC. HILIC/MS method could detect diverse metabolites for metabolomic analysis purpose with good reproducibility and stability

hydrophilicinteractionliquidchromatographycoupledwithmassspectrometryforserummetabolomicsanalysisofbladdercancer

Bladder cancer (BC) is a fatal malignancy with considerable mortality, and can cause a serious threat to human health. The successful treatment of bladder cancer relies mainly on early detection. Biomarkers are vital to early diagnosis of bladder cancer, and metabonomics play an important role in biomarkers finding. In this study, we used 69 polar metabolites to select the appropriate separation system and develop the zwitterionic hydrophilic chromatography/mass spectrometry (ZIC-HILIC/MS) method. In this method, 50 representative compounds had broad linear ranges between 2-6 orders of magnitude. Moreover the limit of detection of the method was below ng/mL levels. The analysis for six serum samples prepared in parallel showed that this method had good reproducibility, and the RSDs of more than 85% metabolites were less than 30%. Based on this method, it was found that 35 metabolites had significant differences in BC group and healthy control. After screening and validation, the combination of chenodeoxycholic acid, eicosenoic acid, GPC, dodecenoic acid and cystine was a potential biomarker to distinguish BC and normal group. These results indicated that the ZIC. HILIC/MS method could detect diverse metabolites for metabolomic analysis purpose with good reproducibility and stability

Determination of the number of ψ(3686) events taken at BESIII

The number of ψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×106 by counting inclusive ψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers of ψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×106 and (345.4±2.6)×106, respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number of ψ(3686) events in the three data samples is (2712.4±14.3)×10^