20, p = 0.03, slope -16.2, 95% CI -30.9 to -1.4, intercept 1.1, 95% CI 0.7-1.4) and also with DI (r = -0.22, p = 0.02, slope -10.0, 95% CI -18.5 to -1.6, intercept 0.9, 95% CI 0.7-1.3). Disposition index, accounting for the combined contribution of insulin sensitivity and beta-cell function, and glucose effectiveness were identified as possible determinants of insulin clearance in women with a previous history of GDM. This may be of relevance for more accurate estimation and prevention of the risk for recurrent GDM and T2D.Long non-coding RNAs (lncRNAs) consist of over 200 nucleotides and are not translated into proteins. Previous studies have shown the importance of lncRNAs in the development of the lung adenocarcinoma (LUAD). Emergence of the high-throughput sequencing technology has led to the identification of a lot of lncRNAs which plays important roles in various biological events. Increasingly evidence has revealed that aberrant lncRNAs expression is related to the development of various cancers. We analyzed the RNA-seq data of 551 lung adenocarcinoma patients downloaded from The Cancer Genome Atlas (TCGA). By analyzing the pre-cancerous and cancer tissues of the relevant patient transcriptomes, we discovered the significant lncRNAs associated with the lung adenocarcinoma. Based on their median score, the prognosis of the patients was categorized as either poor or favorable. Univariate and multivariate COX analysis were used to further analyze the differential lncRNAs. Co-expression and gene enrichment analysis were performed to further investigate the function of the related lncRNA. RNA-seq data analysis led to the discovery of the lncRNA, OGFRP1 as an interesting factor involved in the lung adenocarcinoma. Therefore, lncRNAs play an important role in the clinical diagnosis and the treatment of the lung adenocarcinoma.Affected by illumination, gesture, expression and other factor’s variation, face image pattern is easy to be changed, so it is important to find a robust data representation for the correct classification of face pattern. In this paper, a face image recognition algorithm based on 2-D Gabor wavelet transform and Local Binary Pattern (LBP) is proposed. LBP is a local describe operator, which is invariant against illumination variation. 2-D Gabor wavelet transform have the invariant property against pose and expression variation. Experimental results show that the large scale 2-D Gabor wavelet representation could get good classification accuracy. Using LBP to describe 2-D Gabor wavelet representation of face image, together with image block, histogram statistics, PCA dimensionality reduction, nearestneighbors classification, we finally find this algorithm can get a better classification performance in different scales and directions.Collaborative filtering has been widely used in recommendation systems to recommend items that users might like. However, collaborative filtering based recommendation systems are vulnerable to shilling attacks. Malicious users tend to increase or decrease the recommended frequency of target items by injecting fake profiles. In this paper, we propose a Kalman filter-based attack detection model, which statistically analyzes the difference between the actual rating and the predicted rating calculated by this model to find the potential abnormal time period. The Kalman Filter filters out suspicious ratings based on the abnormal time period and identifies suspicious users based on the source of these ratings. The experimental results show that our method performs much better detection performance for the shilling attack than the traditional methods.Objective The purpose of this study is to investigate the relationship between N-methylN’-nitro-N-nitrosoguanidine (MNNG)-induced lung adenocarcinoma mouse of different stages and the level of exosomes in serum. Methods Fifty KM mice (4 weeks old, weighing 18-22 g, female) were selected for experiment. MNNG was applied to induce lung adenocarcinoma in mice for model establishment. HE staining method was used to observe pathological changes of lung tissues. Exosomes in serum were extracted, and observed under a Transmission Electron Microscopy (TEM). Western blot was employed to examine the protein levels of exosome markers TSG101 and CD63. Results HE staining results suggested MNNG-induced lung adenocarcinoma model mice were successfully constructed. The morphology of exosomes in serum of mouse model was observed under an Electron Microscopy, showing clear membrane structures presenting as saucer or concave hemisphere. In addition, the protein level of exosome marker CD63 in advanced mouse model was significantly up-regulated relative to that in the control group. selleckchem Meanwhile, the expression of exosome marker protein TSG101 was found to be markedly increased in mouse models by comparison with that in control cases. Conclusion In lung adenocarcinoma model mice, the occurrence and development of lung adenocarcinoma are greatly correlated with the expression level of exosomes in serum, which provides theoretical basis for the diagnosis of pathological staging of lung adenocarcinoma by exosomes.Objective To explore the mechanism of miR-223-3p regulating the occurrence and development of liver cancer cells by targeting FAT1 gene. Methods Bioinformatics analysis was used to analyze the differentially expressed genes in liver cancer tissue chips. Forty-eight cases of liver cancer tissues and corresponding adjacent tissues were selected, and qRT-PCR was used to detect the expression of miR-223-3p and FAT1mRNA in tissues. Wound healing assay was used to detect the migration ability of liver cancer cells. Transwell assay was used to detect cells invasion ability. Dual-luciferase assay was used to detect the targeting relationship between miR-223-3p and FAT1. Western blot was used to detect the protein expression of EMT-related markers, E-cadherin and Vimentin. Results FAT1 was highly expressed in liver cancer tissues and cells, while miR-223-3p was lowly expressed. Silencing FAT1 could inhibite the proliferation, migration, invasion and EMT of liver cancer cells. miR-223-3p targeted down-regulated the expression of FAT1, and inhibited the proliferation, migration, invasion and EMT of liver cancer cells by targeting FAT1.