Background Head and neck squamous cell carcinoma (HNSCC) is the six leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains less than 65% due to lack of symptoms in the early stage. Hence, biomarkers which can improve detection of HNSCC should improve clinical outcome. Methods Gene expression profiles (GSE6631, GSE58911) and the Cancer Genome Atlas (TCGA) HNSCC data were used for integrated bioinformatics analysis; the differentially expressed genes (DEGs) were then subjected to functional and pathway enrichment analysis, protein–protein interaction (PPI) network construction. Subsequently, module analysis of the PPI network was performed and overall survival (OS) analysis of hub genes in subnetwork was studied. Finally, immunohistochemistry was used to verify the selected markers. Results A total of 52 up-regulated and 80 down-regulated DEGs were identified, which were mainly associated with ECM–receptor interaction and focal adhesion signaling pathways. Importantly, a set of prognostic signatures including SERPINE1, PLAU and ACTA1 were screened from DEGs, which could predict OS in HNSCC patients from TCGA cohort. Experiment of clinical samples further successfully validated that these three signature genes were aberrantly expressed in the oral epithelial dysplasia and HNSCC, and correlated with aggressiveness of HNSCC patients. Conclusions SERPINE1, PLAU and ACTA1 played important roles in regulating the initiation and progression of HNSCC, and could be identified as key biomarkers for precise diagnosis and prognosis of HNSCC, which will provide potential targets for clinical therapies. Electronic supplementary material The online version of this article (10.1007/s10147-019-01435-9) contains supplementary material, which is available to authorized users.
In this work, we construct a large-scale dataset for vehicle re-identification (ReID), which contains 137k images of 13k vehicle instances captured by UAV-mounted cameras. To our knowledge, it is the largest UAV-based vehicle ReID dataset. To increase intra-class variation, each vehicle is captured by at least two UAVs at different locations, with diverse view-angles and flight-altitudes. We manually label a variety of vehicle attributes, including vehicle type, color, skylight, bumper, spare tire and luggage rack. Furthermore, for each vehicle image, the annotator is also required to mark the discriminative parts that helps them to distinguish this particular vehicle from others. Besides the dataset, we also design a specific vehicle ReID algorithm to make full use of the rich annotation information. It is capable of explicitly detecting discriminative parts for each specific vehicle and significantly outperforms the evaluated baselines and state-of-the-art vehicle ReID approaches.
Background: Due to the lack of research on the pathological mechanism of temporomandibular joint osteoarthritis (TMJOA), there are few effective treatment measures in the clinic. In recent years, microRNAs (miRs) have been demonstrated to play an important role in the pathogenesis of osteoarthritis (OA) by regulating a variety of target genes, and the latest evidence shows that miR-21-5p is specifically overexpressed in OA. The purpose of this project was to clarify whether miR-21-5p can regulate the TMJOA process by targeting Spry1. Methods: TMJOA was induced by a unilateral anterior crossbite (UAC) model, and the effect of miR-21-5p knockout on TMJOA was evaluated by toluidine blue (TB), immunohistochemical (IHC) staining, Western blotting (WB) and RT-qPCR. Primary mouse condylar chondrocytes (MCCs) were isolated, cultured and transfected with a series of mimics, inhibitors, siRNA-Spry1 or cDNA Spry1. WB, RT-qPCR, IHC and TB were used to detect the effect of miR-21-5p and its target gene Spry1 on the expression of MMP-13, VEGF and p-ERK1/2 in TMJOA. The effect of miR-21-5p on angiogenesis was evaluated by chick embryo chorioallantoic membrane (CAM) assay and WB.
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