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Transcription factor cellular promoter 2 is required for upstream binding protein 1 -mediated angiogenesis

Angiogenesis is a key process of repairing tissue damage, and it is regulated by the delicate balance between anti-angiogenesis factors. In the present study, we investigate whether transcription factor cellular promoter 2 (TFCP2) is required for upstream binding protein 1 (UBP1)-mediated angiogenesis. Levels of UBP1 and TFCP2 in human umbilical vein endothelial cells (HUVECs) are detected by quantitative polymerase chain reaction (q-PCR) and Western blotting (WB). Effects of UBP1 on angiogenesis and migration are detected by tube-like network formation on matrigel assay and scratch assay. The interaction between UBP1 and TFCP2 is predicted and verified by STRING and Co-immunoprecipitation (Co-IP). Firstly, the UBP1 expression level was up-regulated in the stimuli of vascular endothelial growth factor (VEGF) in HUVECs, and the knockdown of UBP1 inhibited angiogenesis and migration of HUVECs. Then, UBP1 interacted with TFCP2. Besides, the TFCP2 expression level was up-regulated in VEGF-stimulated HUVECs. Furthermore, knockdown of TFCP2 inhibited angiogenesis and migration in VEGF-stimulated HUVECs, and down-regulation of UBP1 enhanced the inhibition. TFCP2 also plays a key role in UBP1 mediated angiogenesis of HUVECs stimulated by VEGF. These findings will provide a new theoretical basis for the treatment of angiogenic diseases.

Identification of novel candidate genes leading to sex differentiation in primordial germ cells of Drosophila

Germline sex determination and differentiation are pivotal processes in reproduction. In Drosophila, sex determination of the germline occurs in primordial germ cells (PGCs), and the sex differentiation of these cells is initiated during embryogenesis. However, the molecular mechanism initiating sex differentiation remains elusive. To address this issue, we identified sex-biased genes using RNA-sequencing data of male and female PGCs. Our research revealed 497 genes that were differentially expressed more than twofold between sexes and expressed at high or moderate levels in either male or female PGCs. Among these genes, we used microarray data of PGCs and whole embryos to select 33 genes, which are predominantly expressed in PGCs compared to the soma, as candidate genes contributing to sex differentiation. Of 497 genes, 13 genes that were differentially expressed more than fourfold between sexes were also selected as candidates. Among the 46 (33+13) candidates, we confirmed the sex-biased expression of 15 genes by in situ hybridization and quantitative reverse transcription-polymerase chain reaction (qPCR) analysis. Six and nine genes were predominantly expressed in male and female PGCs, respectively. These results represent a first step toward elucidating the mechanisms that initiate sex differentiation in the germline.

Cloning, subcellular localization and expression analysis of squalene epoxidase gene BsSE1 from Bletilla striata

Squalene epoxidase catalyzes the oxidation of squalene to 2,3-oxo-squalene (BsSE1), and is the key rate limiting enzyme in the synthesis of triterpenoids and sterols in plants. This study focused on the basic aspects of BsSE1 including the sequence information, sub-cellular localization expression patterns of BsSE1. Using to the sequence information of Bletilla striata transcriptome, the full-length CDS of BsSE1 gene was amplified. The physicochemical properties and structural characteristics of BsSE1 protein were analyzed by bioinformatics analysis software, and vector was constructed to analyze the protein locations and expression patterns. The results showed that the CDS of BsSE1 gene was 1542 bp, encoding 513 amino acids. BsSE1 protein is a hydrophobic protein with two transmembrane domains but no signal peptides. It is localied in the endoplasmic reticulum membrane and belongs to the typical squalene epoxidase gene. BsSE1 has the closest genetic relationship with SE protein of Dendrobium officinale and Phalaenopsis equestris. The expression level of BsSE1 was higher in pseudobulblet of Bletilla striata seedlings, followed by roots, and lower in seedling stems. After SA induction, the expression of BsSE1 in Bletilla striata showed significant changes, increased first, then decreased, finally increase again. The results provide a basis for further study of this gene family in plants.

Differential gene expression associated with flower development of mango (Mangifera indica L.) varieties with different shelf-life

Mango (Mangifera indica L.) is one of the most important commercial fruit crop grown in many parts of the world. Major challenges affecting mango trade are short shelf-life, high susceptibility to chilling injury, post-harvest diseases and consumer demand for improved fruit quality. The objective of the present study was to reveal the key regulators present in bud and flower tissues during flower development stage, associated with fruit development and affect the shelf-life of the mango fruit. RNA-sequencing of contrasting genotypes having short and long shelf-life, was carried out. Comparative differential expression pathway studies of long shelf-life (Totapuri) and short shelf-life (Bombay Green) mango genotypes revealed a total of 177 highly differentially expressed genes. Out of 177 total genes, 101 genes from endoplasmic reticulum pathway and very few from gibberellins (3) and jasmonic acid (1) pathway were identified. Genes from endoplasmic reticulum pathway like hsp 90, SRC2, DFRA, CHS, BG3 and ASPG1 mainly up regulated in Bombay Green. Uniprotein B9R8D3 also shows up regulation in Bombay Green. Ethylene insensitive pathway gene EIL1 up regulated in Bombay Green. Gene CAD1 from phenylpropanoid pathway mainly up regulated in Bombay Green. A total of 4 SSRs and 227 SNPs were mined from these pathways specific to the shelf-life. Molecular studies of endoplasmic reticulum, phenylpropanoid, ethylene, polygalacturonase and hormone pathways at the time of bud and flower formation revealed key regulators that determine the shelf-life of mango fruit.

RNA-Seq analysis of ovary and testis reveals potential differentially expressed transcripts associated with gonadal unsynchronization development in Onychostoma macrolepis

The Onychostoma macrolepis (O. macrolepis) is a rare and endangered wild species. Their endangered extinction might be due to their low fertility. To further illustrate the molecular mechanism of gonad development of the male and female O. macrolepis, the present study carried out de novo testicular and ovarian transcriptome sequencing. By comparing ovary and testis, 30,869 differentially expressed unigenes (9870 in female, 20999 in male) were identified. In addition, KEGG and GO analysis suggested that the Hedgehog signaling pathway have important roles in testis maintenance and spermatogenesis, whereas the Hippo signaling pathway and Wnt signaling pathway are likely to participate in ovary maintenance. RT-qPCR analysis results were consistent with transcriptome sequencing that all of gender differentiation-related genes (FOXL2, GDF9, WNT4, CYP19A1, SOX9 and GATA4), temperature-enriched genes (NOVA1, CTGF and NR4A1), clock-related genes (PER2, PER3, CRY1, CRY2, BMAL1 and CIPC) were significantly differential expression in testis compared with ovaries. Taken together, these results revealed a potential molecular mechanism that low fertility of the O. macrolepis might strong correlate with the gonadal dyssynchrony development of the male and female, which might provide theoretical basis and technical support for artificial reproduction and germplasm resource protection of the O. macrolepis.

Expression patterns of ABCE model genes during flower development of melon (Cucumis melo L.)

In production, most cultivars of melon are andromonoecious and characterized by carrying both male and bisexual flowers on the same plant. In this study, four A-class genes (CmAP1a, CmAP1b, CmAP2a and CmAP2b), two B-class genes (CmAP3 and CmPI), two C-class genes (CmAGa and CmAGb) and four E-class genes (CmSEP1,2,3,4) were identified in melon. However, no D-class gene of melon was identified. The conserved domains of ABCE function proteins showed relatively high similarity between Arabidopsis and melon. The expression patterns of ABCE homeotic genes in different flower buds of melon suggested that transcripts of CmAP1a, CmPI and CmSEP1 in bisexual buds were significantly lower than that in male flower buds, while the expression levels of CmAGa, CmAGb and CmSEP4 in bisexual flower buds were significantly higher than that in male flower buds. There was no significant difference in expression levels of other ABCE model genes between male buds and bisexual buds. Subsequently, qRT-PCR was performed in different floral organs of bisexual flowers in melon. For A class genes, CmAP1a and CmAP1b showed the highest accumulation in sepals than petals, stamens and pistil, while CmAP2a and CmAP2b revealed the highest expression in pistil than other three floral organs. For B class genes, CmAP3 and CmPI were highly accumulated in petals and stamens though CmAP3 also showed abundant accumulation in pistil. For C class genes, the expression levels of CmAGa and CmAGb were higher in stamens and pistil than that in sepals and petals. For E class genes, CmSEP1 showed higher expression level in sepals and petals than stamens and pistil. CmSEP2, CmSEP3 and CmSEP4 showed the highest accumulation in pistil than other floral organs. These results provided a theoretical basis for studying the function of ABCE homeotic genes in floral organs development of melon.

Neurod1 mediates the reprogramming of NG2 glial into neurons in vitro

Neuronal defect and loss are the main pathological processes of many central nervous system diseases. Cellular reprogramming is a promising method to supplement lost neurons. However, study on cellular reprogramming is still limited and its mechanism remains unclear. Herein, the effect of Neurod1 expression on differentiation of NG2 glia into neurons was investigated. In this study, we successfully isolated NG2 glial cells from mice prior to identification with immunofluorescence. Afterwards, AAV-Neurod1 virus was used to construct Neurod1 overexpression vectors in NG2 glia. Later, we detected neuronal markers expression with immunofluorescence and real time quantitative polymerase-chain reaction (qRT-PCR). Besides, expression of MAPK-signaling-pathway-related proteins were detected by western blotting technique. Through immunofluorescence and qRT-PCR techniques, we observed that Neurod1 overexpression contributed to NG2 cells differentiated into neurons. Further experiments also showed that Neurod1 overexpression induced the activation of MAPK pathway, but PD98059 (a selective inhibitor of MAPK pathway) partly inhibited the neuronal differentiation induced by Neurod1 overexpression. These findings suggest that Neurod1 could promote NG2 glia cells differentiating into neurons, wherein the mechanism under the differentiation is related to activation of MAPK pathway.

Fingerprint matching using the onion peeling approach and turning function

Fingerprint, as one of the most popular and robust biometric traits, can be used in automatic identification and verification systems to identify individuals. Fingerprint matching is a vital and challenging issue in fingerprint recognition systems. Most fingerprint matching algorithms are minutiae-based. The minutiae points are the ways that the fingerprint ridges can be discontinuous. Ridge ending and ridge bifurcation are two frequently used minutiae in most fingerprint matching algorithms. This article presents a new minutiae-based fingerprint matching using the onion peeling approach. In the proposed method, fingerprints are aligned to find the matched minutiae points. Then, the nested convex polygons of matched minutiae points are constructed and the comparison between peer-to-peer polygons is performed by the turning function distance. Simplicity, accuracy, and low time complexity of the onion peeling approach are three important factors that make it a standard method for fingerprint matching purposes. The performance of the proposed algorithm is evaluated on the database FVC2002. Since the fingerprints that the difference between the number of their layers is more than 2 and the a minutiae matching score lower than 0.15 are ignored, better results are obtained. KEYWORDS: Fingerprint Matching, Minutiae, Convex Layers, Turning Function, Computational Geometry.

Open Access
Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning

The early sign detection of liver lesions plays an extremely important role in preventing, diagnosing, and treating liver diseases. In fact, radiologists mainly consider Hounsfield Units to locate liver lesions. However, most studies focus on the analysis of unenhanced computed tomography images without considering an attenuation difference between Hounsfield Units before and after contrast injection. Therefore, the purpose of this work is to develop an improved method for the automatic detection and classification of common liver lesions based on deep learning techniques and the variations of the Hounsfield Units density on computed tomography scans. We design and implement a multi-phase classification model developed on the Faster Region-based Convolutional Neural Networks (Faster R-CNN), Region-based Fully Convolutional Networks (R-FCN), and Single Shot Detector Networks (SSD) with the transfer learning approach. The model considers the variations of the Hounsfield Unit density on computed tomography scans in four phases before and after contrast injection (plain, arterial, venous, and delay). The experiments are conducted on three common types of liver lesions including liver cysts, hemangiomas, and hepatocellular carcinoma. Experimental results show that the proposed method accurately locates and classifies common liver lesions. The liver lesions detection with Hounsfield Units gives high accuracy of 100%. Meanwhile, the lesion classification achieves an accuracy of 95.1%. The promising results show the applicability of the proposed method for automatic liver lesions detection and classification. The proposed method improves the accuracy of liver lesions detection and classification compared with some preceding methods. It is useful for practical systems to assist doctors in the diagnosis of liver lesions. In our further research, an improvement can be made with big data analysis to build real-time processing systems and we expand this study to detect lesions from all parts of the human body, not just the liver.