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Objective:To Investigate comprehensive predictive ability of first-trimester complete blood count combined with maternal characteristics for gestational diabetes mellitus (GDM).Methods:From May 2015 to July 2018, 1 412 pregnant women were retrospectively screened at the Fifth People′s Hospital of Shanghai, Fudan University. We recruited 258 women who developed GDM and 1 154 women who had normal glucose level during pregnancy. At the first visit, clinical data and complete blood count result were obtained. GDM prediction models were established through logistic regression analysis of GDM related risk factors and the prediction abilities of each model were compared.Results:Logistic regression analyses identified age, pre-pregnancy body mass index, previous GDM history, family history of diabetes mellitus, the neutrophil-to-lymphocyte ratio, leukocyte, neutrophil, and monocyte counts were significantly independent predictors of GDM. In the entire cohort, the predictive ability of neutrophil and monocyte counts together with maternal basal characteristics model for the development of GDM [areas under the receiver operating characteristic curve (AUC-ROC)=0.809, integrated discrimination improvement (IDI)=0.056, P=0.001] was the best among various models (basal characteristics model, AUC-ROC=0.753; Monocyte count+ basal characteristics model, AUC-ROC=0.764; neutrophil count + basal characteristics model, AUC-ROC=0.775). Similar results obtained by the same way in all pregnant women without previous GDM history. Conclusion:It could improve the prediction of GDM with model incorporated maternal characteristics and first-trimester neutrophil and monocyte counts.
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Objective@#To investigate the role of neutrophil elastase inhibitor, sivelestat, in preventing and treating nonalcoholic steatohepatitis (NASH) and its underling mechanisms.@*Methods@#A total of forty 4-week-old male C57BL/6J ApoE-/-mice were equally divided into the following four groups: standard chow (SC)+isotonic saline; SC+sivelestat; high-fat, high-cholesterol (HFHC) diet+isotonic saline; and HFHC+sivelestat. These mice were treated with above methods for 12 weeks. Blood and liver tissue samples were collected to measure biochemical parameters, hepatic steatosis and non-alcoholic fatty liver disease (NAFLD) activity score (inflammation) were evaluated by oil red O staining and HE staining, respectively. The mRNA and protein expression levels of hepatic inflammatory cytokines, CD68, and F4/80 were determined by quantitative RT-PCR and immunohistochemistry, respectively. Comparison of means between the four groups was made by one-way analysis of variance, and comparison between any two groups was made by the LSD or SNK method (for data with homogeneity of variance) or the Tamhane or Dunnett method (for data with heterogeneity of variance).@*Results@#Mice fed with an HFHC diet for 12 weeks developed typical pathological features of NASH compared with those fed with SC. Compared with mice fed with HFHC diet without sivelestat, those treated with HFHC and sivelestat exhibited the following features: (1) significantly reduced fast blood glucose, blood cholesterol, and hepatic biochemical parameters, as well as increased insulin sensitivity; (2) significantly reduced NAFLD activity score (5.71±1.11 vs 3.16±1.16, P < 0.05); (3) reduced monocyte chemoattractant protein-1 and tumor necrosis factor -α; (4) significantly reduced mRNA levels of CD68 and F4/80; and (5) reduced expression of CD68 in the liver.@*Conclusion@#Sivelestat alleviates the hepatic steatosis and inflammation of NASH in mice by inhibiting the activation of Kupffer cells.
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Objective To investigate possible independent association between metabolic syndrome (MS) and obstructive sleep apnea-hypopnea syndrome (OSAHS). Methods According to polysomnography (PSG) examination, 82 obese patients were divided into OSAHS group (n = 55) and non OSAHS group (n = 27) and 30subjects with normal weight were recruited as the control group. PSG parameters such as AHI (apnea hyponea index), oxygen saturation (Spo2,) in obese patients were measured. MS-associated parameters, such as fasting blood glucose (FBG), fasting insulin (FINS), plasma lipid profile, insulin homeostasis model assessment of insulin resistance (HOMA-IR) and blood pressure, height, body weight, waist circumference, were measured in all cases. The prevalence of MS and the parameters were compared among different groups. The correlations between them were analyzed. Results The prevalence of MS in obese patients with OSAHS was significantly higher than that in obese patients without OSAHS (69.09% vs 37.04%, P <0.01). Systolic blood pressure and diastolic blood pressure (DBP), FBG and HOMA-IR were higher in subjects with OSAHS than those without OSAHS (P <0.05 or P <0.01). Multiple stepwise regression showed that DBP was negatively correlated with Spo2, FINS and HOMA-IR were positively correlated with AHI. Conclusion OSAHS is found to be independently associated with MS, which may be a risk factor of cardiovascular disease and other systemic diseases.