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Objective To explore the role of leptin in the onset and development of obesity-associated hypertension. Subjects and Methods A case-control study that had finished recruiting 153 subjects divided as four characteristic groups. Leptin serum levels were tested by ELISA in these subjects among these four characteristic Chinese adult physical examination groups. Waist circumference (WC), body mass index (BMI), systolic blood pressure (SB), diastolic blood pressure (DB), and other clinical laboratory data were collected. Analyzation of correlations between the research index and differences between groups was done by SPSS. Results Serum leptin levels statistically significantly positively correlated with BMI and WC, and negatively with the HDLC (high-density lipoprotein cholesterol), even after adjustment for age and gender. There was no significant difference in the serum leptin levels between the normal healthy group (NH group) and the newly diagnosed untreated just-hypertension group (JH group). And the same is between the newly diagnosed untreated obesity-hypertension group (OH group) and the newly diagnosed untreated just-obesity group (JO group). Multiple linear regression analysis indicated BMI and gender as significant independent correlates of serum leptin. Conclusions These results show leptin may not be essential but play an additive effect in the development of obesity-associated hypertension. Leptin may only play an additive effect role in the intricate interwoven network of regulators contributing to the development of hypertension in obese patients.

Objective To explore the role of adiponectin-resistin (AR) index as a better indicator of obesity-related hypertension. Method(s) This study continued a case control study that had finished recruiting 153 subjects divided as four characteristic groups. Fasting serum resistin levels (FSR) and Fasting serum adiponectin levels (FSA) were tested by ELISA. And, other related anthropometric clinical and metabolic data were collected. Analyzation on correlations between research index and differences between groups were done by SPSS. AR index’s performance was also validated by the receiver operating characteristic (ROC) curves, the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI). Result(s) The AR index was defined as 1+ log10(R0)-log10(A0). AUC of the AR index was 0.660 and NRI and IDI indicated AR index outperformed FSA alone. AR index statistically significantly negatively correlated with SB and DB and positively with ALB and SCR. AR index was statistically significantly different between the NH group and OH group and more specific than FSR alone as a biomarker of obesity-related hypertension. Conclusion(s) The AR index was more strongly associated with increased risk of obesity-related hypertension than the solely index of FSR or FSA and was useful for early diagnosis of obesity-related hypertension.

Objective: To explore the role of resistin in the onset and development of obesity-related hypertension. Methods: Resistin serum levels were tested by ELISA in 153 adult subjects among four characteristic Chinese adult physical examination groups. Waist circumference (WC), body mass index (BMI), systolic blood pressure (SB), diastolic blood pressure (DB), and other clinical laboratory data were collected. Following, correlations between research index and differences between groups were analyzed using SPSS. Results: Serum resistin levels statistically significantly negatively correlated with SB, DB and BMI, but statistically significantly positively correlated with serum creatinine (SCR) and serum albumin (ALB), even after adjustment for age and/or gender. The serum level of resistin in the normal healthy subject group (NH) was higher than in other groups. Conclusions: Resistin’s role in the onset of obesity-related hypertension may be more important than what has been previously assumed. More pathway substances in the early onset of obesity-related hypertension should be tested. Abbreviations: WC, waist circumference; GGT, Gamma-glutamyltransferase; ALB, Albumin; ALT, Alanine aminotransferase; LDL, Low density lipoprotein cholesterol; TG, Triglyceride; HDLC, High density lipoprotein cholesterol; FA Fructosamine; SCR, serum creatinine; IB, Indirect bilirubin; ALP, Alkaline phosphatase; CB, Conjugated bilirubin; UREA, Urea; Ua, Uric acid; FBG, fasting blood glucose; TC, Total cholesterol; TB, Total bilirubin; TP, Total protein; TC/HDLC, TC/HDLC ratio; SB, systolic blood pressure; DB, diastolic blood pressure

Annually, tons and tons of zinc oxide nanoparticles (ZnO NPs) are produced in the world. And they are applied in almost all aspects of our life. Their release from the products into environment may pose issue for human health. Although many studies have reported the adverse effects of ZnO NPs on organisms, little is known about the effects on female reproductive systems or the related mechanisms. Quantitative proteomics have not been applied although quantitative transcriptomics have been used in zinc oxide nanoparticles (ZnO NPs) research. Genes are very important players however proteins are the real actors in the biological systems. By using hen's ovarian granulosa cells, it was found that ZnO-NP-5μg/ml and ZnSO4-10μg/ml treatments produced the same amount of intracellular Zn and resulted in similar cell growth inhibition. And NPs were found in the treated cells. However, ZnO-NP-5μg/ml specifically regulated the expression of genes and proteins compared with that in ZnSO4-10μg/ml treatment. For the first time, this investigation reports that intact NPs produce different impacts on the expression of genes and proteins involved in specific pathways compared to that by Zn2+. The findings enrich our knowledge for the molecular insights of zinc oxide nanoparticles effects on the female reproductive systems. This also may raise the health concern that ZnO NPs may adversely affect the female reproductive systems through regulation of specific signaling pathways.

Background: The obesity-hypertension pathogenesis is complex. From the phenotype to molecular mechanism, there is a long way to clarify the mechanism. To explore the association between obesity and hypertension, we correlate the phenotypes such as the waist circumference (WC), body mass index (BMI), systolic blood pressure (SB), and diastolic blood pressure (DB) with the clinical laboratory data between four specific Chinese adult physical examination groups (newly diagnosed untreated just-obesity group, newly diagnosed untreated obesity-hypertension group, newly diagnosed untreated just-hypertension group, and normal healthy group), and the results may show something. Objective: To explore the mechanisms from obesity to hypertension by analyzing the correlations and differences between WC, BMI, SB, DB, and other clinical laboratory data indices in four specific Chinese adult physical examination groups. Methods: This cross-sectional study was conducted from September 2012 to July 2014, and 153 adult subjects, 34 women and 119 men, from 21 to 69 years, were taken from four characteristic Chinese adult physical examination groups (newly diagnosed untreated just-obesity group, newly diagnosed untreated obesity-hypertension group, newly diagnosed untreated just-hypertension group, and normal healthy group). The study was approved by the ethics committee of Hangzhou Center for Disease Control and Prevention. WC, BMI, SB, DB, and other clinical laboratory data were collected and analyzed by SPSS. Results: Serum levels of albumin (ALB)，alanine aminotransferase (ALT), low density lipoprotein cholesterol (LDLC), triglyceride (TG), high density lipoprotein cholesterol (HDLC), alkaline phosphatase (ALP), uric acid (Ua), and TC/HDLC (odds ratio) were statistically significantly different between the four groups. WC statistically significantly positively correlated with BMI, ALT, Ua, and serum levels of glucose (GLU), and TC/HDLC, and negatively with ALB, HDLC, and serum levels of conjugated bilirubin (CB). BMI was statistically significantly positively related to ALT, Ua, LDLC, WC, and TC/HDLC, and negatively to ALB, HDLC, and CB. DB statistically significantly positively correlated with ALP, BMI, and WC. SB was statistically significantly positively related to LDLC, GLU, serum levels of fructosamine (FA), serum levels of the total protein (TC), BMI, and WC. Conclusion: The negative body effects of obesity are comprehensive. Obesity may lead to hypertension through multiple ways by different percents. GGT, serum levels of gamma glutamyltransferase; ALB, serum levels of albumin; ALT, serum levels of alanine aminotransferase; LDLC, serum levels of low density lipoprotein cholesterol; TG, serum levels of triglyceride; HDLC, serum levels of high density lipoprotein cholesterol; FA, serum levels of fructosamine; S.C.R, serum levels of creatinine; IB, serum levels of indirect bilirubin; ALP, serum levels of alkaline phosphatase; CB, serum levels of conjugated bilirubin; UREA, Urea; Ua, serum levels of uric acid; GLU, serum levels of glucose; TC, serum levels of the total cholesterol; TB, serum levels of the total bilirubin; TP, serum levels of the total protein; TC/HDLC, TC/HDLC ratio.