jiaogulan ( Gynostemma pentaphyllum) extract (0.25~2g/L. final concentration) obviously inhibited the platelet aggregation & TXB2 release induced by arachidonic acid ( AA ) in vitro, and the ID50 of inhibiting TXB2 release was 0.28g/L. With the dose of 35mg/kg i. v. , it evidently inhibited platelet aggregation at 10 & 20 min after injection, and also markedly decreased TXB2 released by platelets during 10~40 min after injection, especialy within 20 min. Jiaogulan extract (0.25~4g/L) did not influence 6-keto-PGF1? release of aorta thoracalis of rabbits in vitro. Enzyme immunoassay was used to measure the content of TXB2 & 6-keto-PGF1? in the experiments. The above results suggest that Jiaogulan extract may decrease TXA2/PGI2 ratio.

One hundred and seventy six consecutive patients with acute ischemic stroke who received intravenous recombinant tissue plasminogen activator ( rt-PA ) in 4.5 hours from symptom onset during February 2009 to July 2013 were included in the study.Modified Rankin Scale was used to evaluate the recovery of neurological functions.Patients were divided into good ( 0 -1 ) or poor ( 2 -6 ) outcome groups according modified Rankin Scale score.Univariate analysis and multivariate logistic regression analysis were used to determine the differences of clinical data between the two groups.The age of patients with good outcome was significantly lower than that of poor outcome group [ ( 61.4 ±11.5 ) vs.( 69.0 ± 13.2) years,P =0.000].Compared to patients with poor outcomes, patients with good outcome group showed lower rate of diabetes [ 13%( 12/93 ) vs.29%( 24/83 ) , P =0.009 ] , lower blood glucose level [(5.05 ±0.97) vs.(5.83 ±1.72) mmol/L,P=0.020], higher uric acid level[(404.4 ±151.7) vs.(345.6 ±107.5) μmol/L,P=0.028],shorter onset to treatment time [(1.92 ±0.94) vs.(2.30 ±1.01) h, P=0.019],lower baseline National Institute of Health Stroke Scale score [(14.0 ±5.2) vs.(16.0 ± 6.2),P=0.025],lower systolic blood pressure level at 2 h[(140.8 ±18.3) vs.(149.0 ±18.9) mmHg (1 mmHg=0.133 kPa),P=0.005]and 24 h [(137.6 ±21.9) vs.(147.1 ±17.4) mmHg,P=0.009] after thrombolysis.Logistic regression analysis showed that uric acid levels were not related to hemorrhagic transformation independently (P =0.172,OR =0.965,95%CI:0.917 -1.016), but were related to outcome independently (P=0.047,OR=0.957,95%CI:0.916-0.999).

Objective To explore the change of glyoxalase I in type 2 diabetic ocular muscles palsy (DOMP) and its associations with advanced oxidation protein products (AOPP) and oxidative stress. Methods 58 DOMP patients, 50 T2DM and 30 normal controls were enrolled in this study. Levels of blood lipids, fasting blood glucose, hemoglobin A1c, insulin, serum glyoxalase I, AOPP, malondialdehyde (MDA), superoxide dismutase (SOD) and total antioxidant capacity (T-AOC) were measured. Homeostasis model assessment was performed to evaluate the status of insulin resistance (IR). Results Levels of high-density lipoprotein cholesterol, SOD and T-AOC were positively correlated with glyoxalase I and inversely associated to AOPP. Levels of triglycerides , low-density lipoprotein cholesterol , fasting blood glucose , hemoglobin A1c , IR and MDA were negatively correlated with glyoxalase I and positively related to AOPP. AOPP had an inverse association with glyoxalase I (r = -0.823, P < 0.001). Multivariate regression analysis showed that serum levels of glyoxalase I (Sβ = 0.554) and AOPP (Sβ= -0.469) were influencing factors of groups. Conclusion Serum glyoxalase I levels were significantly decreased in DOMP and correlated with AOPP and levels of oxidative stress , which suggest that glyoxalase I could play crucial roles on the development of DOMP.

Objective To investigate the effects of advanced oxidation protein products (AOPP) in type 2 diabetic ocular muscles palsy (DOMP). Methods 58 DOMP patients and 50 type 2 diabetes patients were included in the research. Hemoglobin A1c (HbA1c), blood glucose (FPG), fasting insulin (FINS) and triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL) were measured and recorded. Homeostasis model assessment was performed to evaluate the status of insulin resistance (HOMA-IR), basal insulin secretion (HOMA-β) and the insulin sensitivity index (ISI). Serum AOPP was measured by enzyme linked immunosorbent assay. Unconditional logistic regression model was used to evaluate the influencing factors of DOMP. Results The DOMP group showed higher levels of plasma AOPP, TG, LDL, FPG, FINS, HbA1c and HOMA-IR, but lower levels of HDL, HOMA-β and ISI than those of the T2DM group. Unconditional logistic regression analysis revealed that AOPP was an independent risk factors for DOMP (OR =3.01, P = 0.002). Conclusion AOPP may be involved in the pathogenesis of DOMP. AOPP could be a useful indicator for monitoring the development of DOMP and for evaluating its severity.