Metastasis-Associated Protein 1 is an Upstream Regulator of DNMT3α and Stimulator of Insulin-Growth Factor Binding Protein-3 in Breast Cancer

Despite a recognized role of DNA methyltransferase 3a (DNMT3a) in human cancer, the nature of its upstream regulator(s) and relationship with the master chromatin remodeling factor MTA1, continues to be poorly understood. Here, we found an inverse relationship between the levels of MTA1 and DNMT3a in human cancer and that high levels of MTA1 in combination of low DNMT3a status correlates well with poor survival of breast cancer patients. We discovered that MTA1 represses DNMT3a expression via HDAC1/YY1 transcription factor complex. Because IGFBP3 is an established target of DNMT3a, we investigated the effect of MTA1 upon IGFBP3 expression, and found a coactivator role of MTA1/c-Jun/Pol II coactivator complex upon the IGFBP3 transcription. In addition, MTA1 overexpression correlates well with low levels of DNMT3a which, in turn also correlates with a high IGFBP3 status in breast cancer patients and predicts a poor clinical outcome for breast cancer patients. These findings suggest that MTA1 could regulate the expression of IGFBP3 in both DNMT3a-dependent and -independent manner. Together findings presented here recognize an inherent role of MTA1 as a modifier of DNMT3a and IGFBP3 expression, and consequently, the role of MTA1-DNMT3a-IGFBP3 axis in breast cancer progression

Metastasis-Associated protein 1 is an upstream regulator of DNMT3a and stimulator of insulin-growth factor binding protein-3 in breast cancer.

Despite a recognized role of DNA methyltransferase 3a (DNMT3a) in human cancer, the nature of its upstream regulator(s) and relationship with the master chromatin remodeling factor MTA1, continues to be poorly understood. Here, we found an inverse relationship between the levels of MTA1 and DNMT3a in human cancer and that high levels of MTA1 in combination of low DNMT3a status correlates well with poor survival of breast cancer patients. We discovered that MTA1 represses DNMT3a expression via HDAC1/YY1 transcription factor complex. Because IGFBP3 is an established target of DNMT3a, we investigated the effect of MTA1 upon IGFBP3 expression, and found a coactivator role of MTA1/c-Jun/Pol II coactivator complex upon the IGFBP3 transcription. In addition, MTA1 overexpression correlates well with low levels of DNMT3a which, in turn also correlates with a high IGFBP3 status in breast cancer patients and predicts a poor clinical outcome for breast cancer patients. These findings suggest that MTA1 could regulate the expression of IGFBP3 in both DNMT3a-dependent and -independent manner. Together findings presented here recognize an inherent role of MTA1 as a modifier of DNMT3a and IGFBP3 expression, and consequently, the role of MTA1-DNMT3a-IGFBP3 axis in breast cancer progression

Expression and regulation of avian beta-defensin 8 protein in immune tissues and cell lines of chickens

Objective Defensins are a large family of antimicrobial peptides and components of the innate immune system that invoke an immediate immune response against harmful pathogens. Defensins are classified into alpha-, beta-, and theta-defensins. Avian species only possess beta-defensins (AvBDs), and approximately 14 AvBDs (AvBD1–AvBD14) have been identified in chickens to date. Although substantial information is available on the conservation and phylogenetics, limited information is available on the expression and regulation of AvBD8 in chicken immune tissues and cells. Methods We examined AvBD8 protein expression in immune tissues of White Leghorn chickens (WL) by immunohistochemistry and quantitative reverse transcription-polymerase chain reaction (RT-qPCR). In addition, we examined AvBD8 expression in chicken T-, B-, macrophage-, and fibroblast-cell lines and its regulation in these cells after lipopolysaccharide (LPS) treatment by immunocytochemistry and RT-qPCR. Results Our results showed that chicken AvBD8 protein was strongly expressed in the WL intestine and in macrophages. AvBD8 gene expression was highly upregulated in macrophages treated with different LPS concentrations compared with that in T- and B-cell lines in a time-independent manner. Moreover, chicken AvBD8 strongly interacted with other AvBDs and with other antimicrobial peptides as determined by bioinformatics. Conclusion Our study provides the expression and regulation of chicken AvBD8 protein in immune tissues and cells, which play crucial role in the innate immunity

Liver Infection Prediction Analysis using Machine Learning to Evaluate Analytical Performance in Neural Networks by Optimization Techniques

Liver infection is a common disease, which poses a great threat to human health, but there is still able to identify an optimal technique that can be used on large-level screening. This paper deals with ML algorithms using different data sets and predictive analyses. Therefore, machine ML can be utilized in different diseases for integrating a piece of pattern for visualization. This paper deals with various machine learning algorithms on different liver illness datasets to evaluate the analytical performance using different types of parameters and optimization techniques. The selected classification algorithms analyze the difference in results and find out the most excellent categorization models for liver disease. Machine learning optimization is the procedure of modifying hyperparameters in arrange to employ one of the optimization approaches to minimise the cost function. To set the hyperparameter, include a number of Phosphotase,Direct Billirubin, Protiens, Albumin and Albumin Globulin. Since it describes the difference linking the predictable parameter's true importance and the model's prediction, it is crucial to minimise the cost function

Distribution and differential expression of microRNAs in the intestinal mucosal layer of necrotic enteritis induced Fayoumi chickens

Objective Despite an increasing number of investigations into the pathophysiology of necrotic enteritis (NE) disease, etiology of NE-associated diseases, and gene expression profiling of NE-affected tissues, the microRNA (miRNA) profiles of NE-affected poultry have been poorly studied. The aim of this study was to induce NE disease in the genetically disparate Fayoumi chicken lines, and to perform non-coding RNA sequencing in the intestinal mucosal layer. Methods NE disease was induced in the Fayoumi chicken lines (M5.1 and M15.2), and non-coding RNA sequencing was performed in the intestinal mucosal layer of both NE-affected and uninfected chickens to examine the differential expression of miRNAs. Next, quantitative real-time polymerase chain reaction (real-time qPCR) was performed to further examine four miRNAs that showed the highest fold differences. Finally, bioinformatics analyses were performed to examine the four miRNAs target genes involvement in the signaling pathways, and to examine their interaction. Results According to non-coding RNA sequencing, total 50 upregulated miRNAs and 26 downregulated miRNAs were detected in the NE-induced M5.1 chickens. While 32 upregulated miRNAs and 11 downregulated miRNAs were detected in the NE-induced M15.2 chickens. Results of real-time qPCR analysis on the four miRNAs (gga-miR-9-5p, gga-miR-20b-5p, gga-miR-196-5p, and gga-let-7d) were mostly correlated with the results of RNAseq. Overall, gga-miR-20b-5p was significantly downregulated in the NE-induced M5.1 chickens and this was associated with the upregulation of its top-ranking target gene, mitogen-activated protein kinase, kinase 2. Further bioinformatics analyses revealed that 45 of the gene targets of gga-miR-20b-5p were involved in signal transduction and immune system-related pathways, and 35 of these targets were predicted to interact with each other. Conclusion Our study is a novel report of miRNA expression in Fayoumi chickens, and could be very useful in understanding the role of differentially expressed miRNAs in a NE disease model