OR-004 Changes in serum indexes of obese adolescents induced by closed weight loss summer camp

Objective A series of experiments were conducted to explore the changes of some serum indexes in obese adolescents induced by closed weight loss summer camp. Methods The 12 to 18 year old obese adolescents (BMI ≥ 28), who volunteered to participate in the Haoqian summer camp, were selected for 4 weeks of closed summer camp. The main activities of the summer camp included compound exercise (aerobic exercise + resistance exercise, 3 times / day, 6 days / week), Dietary intervention, fun activities and health knowledge lectures. In order to explore the changes of serum indexes of obese adolescents, glycolipid metabolism index, fatty acid components, inflammatory factors and oxidative stress markers were analyzed before and after 4 weeks. Results (1) The 4 week weight loss summer camp had no significant effect on blood sugar, but it can obviously reduce the level of serum total cholesterol, triglyceride and low density lipoprotein cholesterol, and significantly improve the abnormal lipid metabolism. (2) The level of serum total saturated fatty acid (P < 0.05), total monounsaturated fatty acid (P < 0.01) and total polyunsaturated fatty acid (P < 0.05) in obese adolescents were decreased significantly in the 4 week weight loss summer camp. (3) The 4 week weight loss summer camp significantly reduced serum inflammatory factors IL-6 and TN F- alpha in obese adolescents, increased the level of adiponectin per body fat mass (P < 0.05), and relieved the inflammatory state of the body. (4) After 4 weeks weight loss summer camp, the serum total antioxidant capacity T-AOC, antioxidant enzyme catalase CAT, superoxide dismutase SOD and glutathione peroxidase GPx activity in obese adolescents were significantly enhanced (P < 0.05); oxidative damage markers 8-iso-PGF2α, 8-OHdG, and MDA levels were not significantly changed (P > 0.05), while protein oxidation product protein carbohydrate PC content decreased significantly (P < 0.05). Conclusions 4 weeks weight loss summer camp can significantly alleviate the body's lipid metabolism abnormalities, change the serum fatty acid components, reduce the body's inflammatory state, enhance the body's antioxidant capacity, and reduce the body's oxidative damage

Hot deformation behaviours and spheroidization mechanisms of Ti-5322 alloy during hot compression

The hot deformation behavior of Ti-5322 alloy are researched at compression temperatures range of 750–1050 °C and strain rate range of 0.01–10 s ^−1 , to optimize its hot workability. Processing map analysis and microstructure observations reveal that the optimal processing parameters of Ti-5322 alloy are temperatures of 750–825 °C and strain rates of 0.01–0.05 s ^−1 , and temperatures of 925–975 °C and strain rates of 0.01–1 s ^−1 . The peak efficiency of power dissipation can reach 40% owing to the transformation from α phase to β phase, spheroidization behavior and dynamic recrystallization of the β phase. The dynamic recrystallization was the primary form of microstructure evolution above 900 °C, while the spheroidization of α phase below 900 °C. The spheroidization of α lamellae can be attributed to the instability of subgrain boundaries appeared in the α phase during hot deformation. The β phase wadges into the α / α subgrain boundary and α / β interface migration induced the α phase spheroidization. In addition, three instability domains are detected in the processing maps, which confirmed by the presence of microstructures with wedge cracking and adiabatic shear bands

Exposure to Titanium Dioxide Nanoparticles During Pregnancy Changed Maternal Gut Microbiota and Increased Blood Glucose of Rat

Abstract Titanium dioxide nanoparticles (TiO2 NPs) were used worldwide for decades, and pregnant women are unable to avoid exposing to them. Studies revealed that TiO2 NPs could kill many kinds of bacteria, but whether they would affect the composition of gut microbiota, especially during pregnancy, was seldom reported. And, what adverse effects may be brought to pregnant females was also unknown. In this study, we established the prenatal exposure model of rats to explore the effects of TiO2 NPs on gut microbiota. We observed an increasing trend, but not a significant change of alpha-diversity among control and exposure groups at gestation day (GD) 10 and GD 17 during normal pregnancy process. Each different time point had unique gut microbiota operational taxonomic units (OTUs) characteristics. The abundance of Ellin6075 decreased at GD 10 and GD 17, Clostridiales increased at GD 10, and Dehalobacteriaceae decreased at GD 17 after TiO2 NPs exposure. Further phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) prediction indicated that the type 2 diabetes mellitus related genes were enhanced, and taurine metabolism was weakened at the second-trimester. Further study showed that the rats’ fasting blood glucose levels significantly increased at GD 10 (P < 0.05) and GD 17 (P < 0.01) after exposure. Our study pointed out that TiO2 NPs induced the alteration of gut microbiota during pregnancy and increased the fasting blood glucose of pregnant rats, which might increase the potential risk of gestational diabetes of pregnant women

Fusion of CNN- and COSFIRE-based features with application to Gender Recognition from Face Images

Convolution neural networks (CNNs) have been demonstrated to be very eective in various computer vision tasks. The main strength of such networks is that features are learned from some training data. In cases where training data is not abundant, transfer learning can be used in order to adapt features that are pre-trained from other tasks. Similarly, the COSFIRE approach is also trainable as it configures lters to be selective for features selected from training data. In this study we propose a fusion method of these two approaches and evaluate their performance on the application of gender recognition from face images. In particular, we use the pre-trained VGGFace CNN, which when used as standalone, it achieved 97.45% on the GENDER-FERET data set. With one of the proposed fusion approaches the recognition rate on the same task is improved to 98.9%, that is reducing the error rate by more than 50%. Our experiments demonstrate that COSFIRE filters can provide complementary features to CNNs, which contribute to a better performance