Genetic polymorphisms in plasminogen activator inhibitor-1 predict susceptibility to steroid-induced osteonecrosis of the femoral head in Chinese population

BACKGROUND: Steroid usage has been considered as a leading cause of non-traumatic osteonecrosis of the femoral head (ONFH), which is involved in hypo-fibrinolysis and blood supply interruption. Genetic polymorphisms in plasminogen activator inhibitor-1 (PAI-1) have been demonstrated to be associated with ONFH risk in several populations. However, this relationship has not been established in Chinese population. The aim of this study was to investigate the association of PAI-1 gene polymorphisms with steroid-induced ONFH in a large cohort of Chinese population. METHODS: A case–control study was conducted, which included 94 and 106 unrelated patients after steroid administration recruited from 14 provinces in China, respectively. Two SNPs (rs11178 and rs2227631) within PAI-1 were genotyped using Sequenom MassARRAY system. RESULTS: rs2227631 SNP was significantly associated with steroid-induced ONFH group in codominant (P = 0.04) and recessive (P = 0.02) models. However, there were no differences found in genotype frequencies of rs11178 SNP between controls and patients with steroid-induced ONFH (all P > 0.05). CONCLUSIONS: Our data offer the convincing evidence for the first time that rs2227631 SNP of PAI-1 may be associated with the risk of steroid-induced ONFH, suggesting that the genetic variations of this gene may play an important role in the disease development. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1569909986109783

Effect of Ermiao Fang with Xixin (Herba Asari Mandshurici) on bone marrow stem cell directional homing to a focal zone in an osteoarthritis rat model

AbstractObjectiveTo investigate the effects of Ermiao Fang (EM) with medical guide Xixin (Herba Asari Mandshurici) (HAM) on bone marrow stem cell migration to a focal zone in osteoarthritis (OA) rats.MethodsOA rats were induced by arthrectomy and assigned to sham-operated, model, EM, or EM plus HAM groups. All rats were injected with recombinant human granulocyte colony-stimulating factor 30 μg • kg−1 • d−1 for 7 days and treated with EM or EM plus HAM at 1.6 or 1.9 g • kg−1 • d−1 for 3 or 6 weeks, respectively. Chondrocyte apoptosis and cartilage matrix components were tested by transferase-mediated deoxyuridine triphosphate-biotin nick end labeling assay and special staining. Levels of interleukin-1 beta (IL-1β) tumor necrosis factor alpha (TNF-α) nitric oxide (NO), and inducible nitric oxide synthase (iNOS) in serum were detected by enzyme-linked immunosorbent assay or radioimmunoassay. Matrix metalloproteinases (MMPs)-13, tissue inhibitors of metalloproteinases (TIMPs)-1, Bromodeoxyuridine (BrdU), cluster of differentiation 34 (CD34), and stromal cell-derived factor 1 (SDF-1) were measured by immunohistochemical assay.ResultsThe EM and EM plus HAM groups had significantly less cartilage damage and synovium inflammation the model group. Moreover, the EM and EM plus HAM groups had less chondrocyte apoptosis and more proteoglycan and collagen content than the model group. The EM and EM plus HAM groups had obviously higher MMPs-13 and TIMPs-1 expression in the cartilage than the model group. Moreover, the two formula groups had less release of IL-1β, TNF-α, NO, and iNOS than model group. Importantly, the expressions of BrdU, CD34, and SDF-1 in cartilage were significantly higher in the EM and EM plus HAM-Medtreated rats than model group. Notably, the EM plus HAM treatment seemed to have the greatest effects.ConclusionsHAM improves the therapeutic effects of EM on OA rats by enhancing BMSC directional homing to the focal zone

A Detail Preserving Neural Network Model for Monte Carlo Denoising

International audienceMonte Carlo based methods such as path tracing are widely used in movie production. To achieve noise-free quality, they tend to require a large number of samples per pixel, resulting in longer rendering time. To reduce that cost, one solution is Monte Carlo denoising: render the image with fewer samples per pixel (as little as 128) and then denoise the resulting image. Many Monte Carlo denoising methods rely on deep learning: they use convolutional neural networks to learn the relationship between noisy images and reference images, using auxiliary features such as position and normal together with image color as inputs. The network predicts kernels which are then applied to the noisy input. These methods have shown powerful denoising ability. However, they tend to lose geometric details or lighting details and over blur sharp features during denoising. In this paper, we solve this issue by proposing a novel network structure, a new input feature-light transport covariance from path space-and an improved loss function. In our network, we separate feature buffers with color buffer to enhance detail effects. Their features are extracted separately and then are integrated to a shallow kernel predictor. Our loss function considers perceptual loss, which also improves the detail preserving. In addition, we present the light transport covariance feature in path space as one of the features, which is used to preserve illumination details. Our method denoises Monte Carlo path traced images while preserving details much better than previous work

Circulating LncRNAs Analysis in Patients with Type 2 Diabetes Reveals Novel Genes Influencing Glucose Metabolism and Islet β-Cell Function

Background/Aims: The islet is an important endocrine organ to secrete insulin to regulate the metabolism of glucose and maintain the stability of blood glucose. Long noncoding RNAs (lncRNAs) are involved in a variety of biological functions and play key roles in many diseases, including type 2 diabetes (T2D). The aim of this study was to determine whether lncRNA-p3134 is associated with glucose metabolism and insulin signaling in pancreatic β cells. Methods: LncRNA microarray technology was used to identify the differentially expressed circulating lncRNAs in T2D patients. RT-PCR analyses were performed to determine the expression of lncRNA-p3134 in 30 pairs of diabetic and non-diabetic patients. The correlation of lncRNA-p3134 to clinical data from T2D patients was analyzed. LncRNA-p3134 was overexpressed in Min6 cells and db/db mice by adenovirus-mediated technology. CCK-8, TUNEL, Western blot, glucose-stimulated insulin secretion (GSIS), ELISAs and immunochemistry were performed to determine the effect of lncRNA-p3134 on proliferation, apoptosis and insulin secretion both in vitro and vivo. Results: The circulating level of lncRNA-p3134 was higher in diabetic patients than in non-diabetic controls and was correlated with fasting blood glucose and HOMA-β levels. The lncRNA-p3134 had risen by 4 times in serum exosomes but nearly unchanged in exosome-free samples. The secretion of lncRNA-p3134 was dynamically modulated by glucose in both Min6 cells and isolated mouse islet cells. LncRNA-p3134 positively regulate GSIS through promoting of key regulators (Pdx-1, MafA, GLUT2 and Tcf7l2) in β cells. In addition, the overexpression of lncRNA-p3134 resulted in a decreased apoptosis ratio and partially reversed the glucotoxicity effects on GSIS function in Min6 cells. The restoration of insulin synthesis and secretion the increase of the insulin positive cells areas by upregulation of lncRNA-p3134 in db/db mice confirmed the compensatory role of lncRNA-p3134 to preserve β-cell function. Furthermore, a protective effect of lncRNA-p3134 on GSIS by positive modulation of PI3K/Akt/mTOR signaling was also confirmed. After blocking the PI3K/AKT signals with their specific inhibitor, the effect of overexpressed lncRNA-p3134 on insulin secretion was obviously attenuated. Conclusion: Taken together, the results of this study provide new insights into lncRNA-p3134 regulation in pancreatic β cells and provide a better understanding of novel mechanism of glucose homeostasis