Effect of metformin and rosiglitazone in non-obese polycystic ovary syndrome women with insulin resistance / 中华妇产科杂志

Objective:To investigate effects of metformin and rosiglitazone in non-obese polycystic ovary syndrome (PCOS) women with insulin resistance.Methods:Totally 200 non-obese PCOS women with insulin resistance in West China Second Hospital of Sichuan University were enrolled into this study from Sep. 2013 to Jun. 2016, and were randomly divided into two treatment groups: metformin group (1 500 mg/d) and rosiglitazone group (4 mg/d). The treatment lasted for 6 months. Their clinical and biochemical parameters were collected and compared.Results:In both groups, menstrual cycles [metformin group (37±4) days, rosiglitazone group (35±4) days] were shorter after treatment for 6 months (both P<0.01). After treatment for 6 months, body mass index [metformin group (21.6±1.6) kg/m 2, rosiglitazone group (21.7±1.7) kg/m 2] decreased in both groups (both P<0.01); decreased LH/FSH ratio (metformin group 1.67±0.80, rosiglitazone group 1.70±0.83) was also observed (both P<0.05). After treatment for 6 months, fasting insulin level [metformin group (13.5±5.1) mU/L, rosiglitazone group (12.7±5.6) mU/L] and homeostasis model assessment-insulin resistance index (metformin group 3.0±1.2, rosiglitazone group 2.8±1.2) were decreased in both groups (all P<0.01). Conclusions:For non-obese PCOS insulin resistance patients, screening of anthropometric and metabolic parameters is necessary. For PCOS with insulin resistance, lifestyle plus insulin sensitizers such as metformin could improve their clinical symptoms, correct the biochemical and metabolic dysfunction.

Cigarette smoking in different manners induces acute lung injury in rats / 浙江大学学报·医学版

To investigate the effects of cigarette smoking in different manners on acute lung injury in rats.The commercially available cigarettes with tar of 1,5, 11 mg were smoked in Canada depth smoking (health canada method, HCM) manner, and those with tar of 11 mg were also smoked in international standard (ISO) smoking manner. Rats were fixed and exposed to mainstream in a manner of nose-mouth exposure. After 28 days, the bronchoalveolar lavage fluids from left lung were collected for counting and classification of inflammatory cells and determination of pro-inflammatory cytokines IL-1β and TNF-α. The right lungs were subjected to histological examination and determination of myeloperoxidase (MPO) and superoxide dismutase (SOD) activities and glutathione, reactive oxygen species (ROS) and malondialdehyde (MDA) levels.In both HCM and ISO manners, the degree of lung injury was closely related to the tar content of cigarettes, and significant decrease in the body weight of rats was observed after smoking for one week. In a HCM manner, smoking with cigarette of 11 mg tar resulted in robust infiltration of macrophages, lymphocytes and neutrophils into lungs, significant increase in IL-1β and TNF-α levels and MPO activities, and significant decrease in GSH levels and SOD activities and increase in ROS and MDA levels (all<0.05). Smoking with cigarette of 5 mg tar led to moderate increase in IL-1β and TNF-α levels, and MPO activities (all<0.05), and moderate decrease in GSH levels and SOD activities and increase of ROS and MDA levels (all<0.05). However, smoking with cigarette of 1 mg tar affected neither inflammatory cell infiltration nor IL-1β and TNF-α levels.Cigarette smoking in nose-mouth exposure manner can induce acute lung injury in rats; and the degree of lung injury is closely related to the content of tar and other hazards in cigarettes.

Ensemble Partial Least Squares Algorithm Based on Variable Clustering for Quantitative Infrared Spectrometric Analysis / 分析化学

Due to the ability of overcoming both the dimensionality and the collinear problems of the spectral data, partial least squares ( PLS ) is in ever increasingly used for quantitative spectrometric analysis, especially for near-infrared spectrum, mid-infrared spectrum and Raman spectrum. In this work, an improved PLS algorithm is proposed for efficient information extraction and noise reduction. The spectral variables are clustering to several subsets, and several sub-models are built for each subset. Then, the sub-models are re-weighted and ensemble to the final model. Experiments on two near-infrared datasets ( octane number prediction in gasoline and nicotine prediction in tobacco leafs ) demonstrate that the new method provides superior prediction performance and outperformed the conventional PLS algorithm, and the root mean square error of prediction ( RMSEP) is reduced by 32% and 22%, respectively.