BackgroundWomen with polycystic ovary syndrome (PCOS) are generally considered to be central obese and at higher risks of metabolic disturbances. Imaging methods are the golden standards for detecting body fat distribution. However, evidence based on magnetic resonance imaging (MRI) and computed tomography (CT) is conflicting. This study systematically reviewed the imaging-based body fat distribution in PCOS patients and quantitatively evaluated the difference in body fat distribution between PCOS and BMI-matched controls.MethodsPUBMED, EMBASE, and Web of Science were searched up to December 2019, and studies quantitatively compared body fat distribution by MRI, CT, ultrasound, or X-ray absorptiometry (DXA) between women with PCOS and their BMI-matched controls were included. Two researchers independently reviewed the articles, extract data and evaluated the study quality based on Newcastle-Ottawa Scale (NOS).Results47 studies were included in systematic review and 39 were eligible for meta-analysis. Compared to BMI-matched controls, higher accumulations of visceral fat (SMD 0.41; 95%CI: 0.23-0.59), abdominal subcutaneous fat (SMD 0.31; 95%CI: 0.20-0.41), total body fat (SMD 0.19; 95% CI: 0.06-0.32), trunk fat (SMD 0.47; 95% CI: 0.17-0.77), and android fat (SMD 0. 36; 95% CI: 0.06-0.66) were identified in PCOS group. However, no significant difference was identified in all the above outcomes in subgroups only including studies using golden standards MRI or CT to evaluate body fat distribution (SMD 0.19; 95%CI: -0.04-0.41 for visceral fat; SMD 0.15; 95%CI: -0.01-0.31 for abdominal subcutaneous fat). Moreover, meta-regression and subgroup analyses showed that young and non-obese patients were more likely to accumulate android fat.ConclusionsPCOS women seem to have abdominal fat accumulation when compared with BMI-matched controls. However, MRI- and CT- assessed fat distribution was similar between PCOS and controls, suggesting central obesity may be independent of PCOS. These findings will help us reappraise the relationship between PCOS and abnormal fat deposition and develop specialized lifestyle interventions for PCOS patients.Systematic Review RegistrationPROSPERO, identifier CRD42018102983.

IL-24 is a multifunctional cytokine that regulates both immune cells and epithelial cells. Although its elevation is associated with a number of autoimmune diseases, its tolerogenic properties against autoreactive T cells have recently been revealed in an animal model of central nervous system (CNS) autoimmunity by inhibiting the pathogenic Th17 response. To explore the potential of IL-24 as a therapeutic agent in CNS autoimmunity, we induced experimental autoimmune uveitis (EAU) in wildtype mice and intravitreally injected IL-24 into the inflamed eye after disease onset. We found that the progression of ocular inflammation was significantly inhibited in the IL-24-treated eye when compared to the control eye. More importantly, IL-24 treatment suppressed cytokine production from ocular-infiltrating, pathogenic Th1 and Th17 cells. In vitro experiments confirmed that IL-24 suppressed both Th1 and Th17 differentiation by regulating their master transcription factors T-bet and RORγt, respectively. In addition, we found that intravitreal injection of IL-24 suppressed the production of proinflammatory cytokines and chemokines from the retinas of the EAU-inflamed eyes. This observation appears to be applicable in humans, as IL-24 similarly inhibits human retinal pigment epithelium cells ARPE-19. In conclusion, we report here that IL-24, as a multifunctional cytokine, is capable of resolving ocular inflammation in EAU mice by targeting both uveitogenic T cells and RPE cells. This study sheds new light on IL-24 as a potential therapeutic candidate for autoimmune uveitis.

For classification of wood species with similar microstructure, 19 high-value hardwood species of Papilionaceae, Ebenaceae, and Caesalpiniaceae were used as experimental objects. Images of transverse sections, radial sections, and tangential sections were collected by Micro CT. Local binary patterns (LBP) are often used for feature extraction. LBP deformed forms such as uniform LBP, rotation-invariant LBP, and rotation-invariant uniform LBP were fused with Gray-Level Co-Occurrence Matrix (GLCM) to form three fusion features. The fusion features were combined with support vector machine (SVM) or BP neural network to realize wood classification. The texture feature fusion method was found to be better than the single feature classification. Among them, the effect of uniform LBP and GLCM fusion was the best, and the classification accuracy combined with SVM was the highest. The evaluation of the classification of 19 kinds of hardwood mainly depended on transverse sections, and its accuracy was higher than that of the radial and tangential sections. Therefore, the classification results of transverse sections should be taken as the main evaluation basis for the classification of the 19 high-value hardwood species.

Abstract-This article researches the phenomenon that Chinese enterprises rapidly become global industry leader in international competition, summarizes four models of rapid internalization of Chinese enterprises: make use of selfindependent innovation to rapidly occupy the market, merger and acquire the world's leading companies in the industry, extend to high value-added stages of global value chain and born globalization. Then it points out main factors that promote internalization of enterprises, hereby puts forward implementation points to promote Chinese enterprises to realize rapid internalization.