Clustering Mining Algorithm of Internet of Things Database Based on Python Language

In order to solve the problems of reading delay in data mining of the Internet of Things database, a clustering mining algorithm of the Internet of Things database based on Python language is proposed. We designed an improved crawler algorithm based on the open-source structure of scratch through Python language, judge the similarity of recruitment data topics in the Internet of Things database through Bayesian classifier, and crawl the recruitment data in the Internet of Things database: the number of keywords in the text space, the degree of keyword extraction, and the number of keyword data in the text space. The time series model is used to eliminate the delay of text features. On this basis, the semi-supervised learning and semi-cluster analysis method is used to construct the corresponding classifier, complete the adaptive classification process of the text data stream and realize the clustering mining of the Internet of Things database based on Python language. The experimental results show that this method has a low reading delay, and can mine the attention, number of posts and click time frequency of the Internet of Things database from which the recruitment data are obtained

Microbiota and bile acid profiles in retinoic acid-primed mice that exhibit accelerated liver regeneration.

Background & aimsAll-trans Retinoic acid (RA) regulates hepatic lipid and bile acid homeostasis. Similar to bile acid (BA), RA accelerates partial hepatectomy (PHx)-induced liver regeneration. Because there is a bidirectional regulatory relationship between gut microbiota and BA synthesis, we examined the effect of RA in altering the gut microbial population and BA composition and established their relationship with hepatic biological processes during the active phases of liver regeneration.MethodsC57BL/6 mice were treated with RA orally followed by 2/3 PHx. The roles of RA in shifting gut microbiota and BA profiles as well as hepatocyte metabolism and proliferation were studied.ResultsRA-primed mice exhibited accelerated hepatocyte proliferation revealed by higher numbers of Ki67-positive cells compared to untreated mice. Firmicutes and Bacteroidetes phyla dominated the gut microbial community (>85%) in both control and RA-primed mice after PHx. RA reduced the ratio of Firmicutes to Bacteroidetes, which was associated with a lean phenotype. Consistently, RA-primed mice lacked transient lipid accumulation normally found in regenerating livers. In addition, RA altered BA homeostasis and shifted BA profiles by increasing the ratio of hydrophilic to hydrophobic BAs in regenerating livers. Accordingly, metabolic regulators fibroblast growth factor 21, Sirtuin1, and their downstream targets AMPK and ERK1/2 were more robustly activated in RA-primed than unprimed regenerating livers.ConclusionsPriming mice with RA resulted in a lean microbiota composition and hydrophilic BA profiles, which were associated with facilitated metabolism and enhanced cell proliferation

On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles

Dysregulated microRNA (miRNA) expression is a well-established feature of human cancer. However, the role of specific miRNAs in determining cancer outcomes remains unclear. Using Level 3 expression data from the Cancer Genome Atlas (TCGA), we identified 61 miRNAs that are associated with overall survival in 469 ovarian cancers profiled by microarray (p<0.01). We also identified 12 miRNAs that are associated with survival when miRNAs were profiled in the same specimens using Next Generation Sequencing (miRNA-Seq) (p<0.01). Surprisingly, only 1 miRNA transcript is associated with ovarian cancer survival in both datasets. Our analyses indicate that this discrepancy is due to the fact that miRNA levels reported by the two platforms correlate poorly, even after correcting for potential issues inherent to signal detection algorithms. Further investigation is warranted

Comprehensive evaluation of RNA-seq quantification methods for linearity

Figure S3. Concordant analysis between rank of estimated quantifications and rank of measured abundance value at gene level (a) and isoform level (b). The fitted value in the y-axis is estimated from model D∼m×A+n×B+ε. Ranks were normalized by the number of quantifications in each plot. (PDF 5950 kb

Analyses of domains and domain fusions in human proto-oncogenes

Background: Understanding the constituent domains of oncogenes, their origins and their fusions may shed new light about the initiation and the development of cancers. Results: We have developed a computational pipeline for identification of functional domains of human genes, prediction of the origins of these domains and their major fusion events during evolution through integration of existing and new tools of our own. An application of the pipeline to 124 well-characterized human oncogenes has led to the identification of a collection of domains and domain pairs that occur substantially more frequently in oncogenes than in human genes on average. Most of these enriched domains and domain pairs are related to tyrosine kinase activities. In addition, our analyses indicate that a substantial portion of the domain-fusion events of oncogenes took place in metazoans during evolution. Conclusion: We expect that the computational pipeline for domain identification, domain origin and domain fusion prediction will prove to be useful for studying other groups of genes. Originally published BMC Bioinformatics, Vol. 10, No. 88, Mar 200

Regulation of the transcription factor NF-κB1 by microRNA-9 in human gastric adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a new class of naturally occurring, small, non-coding RNAs that regulate protein-coding mRNAs by causing mRNA degradation or repressing translation. The roles of miRNAs in lineage determination and proliferation, as well as the localization of several miRNA genes at sites of translocation breakpoints or deletions, have led to speculation that miRNAs could be important factors in the development or maintenance of the neoplastic state.</p> <p>Results</p> <p>We showed that miR-9 was downregulated in human gastric adenocarcinoma. Overexpression of miR-9 suppressed the growth of human gastric adenocarcinoma cell line MGC803 cell as well as xenograft tumors derived from them in SCID mice. Bioinformatics analysis indicated a putative miR-9 binding site in the 3'-untranslated region (3'UTR) of the tumor-related gene NF-κB1 mRNA. In an EGFP reporter system, overexpression of miR-9 downregulated EGFP intensity, and mutation of the miR-9 binding site abolished the effect of miR-9 on EGFP intensity. Furthermore, both the NF-κB1 mRNA and protein levels were affected by miR-9. Finally, knockdown of NF-κB1 inhibited MGC803 cell growth in a time-dependent manner, while ectopic expression of NF-κB1 could rescue MGC803 cell from growth inhibition caused by miR-9.</p> <p>Conclusion</p> <p>These findings indicate that miR-9 targets NF-κB1 and regulates gastric cancer cell growth, suggesting that miR-9 shows tumor suppressive activity in human gastric cancer pathogenesis.</p

Bis(1,3-diethyl­benzimidazolium) tetra­bromidomercurate(II)

In the title compound, (C11H15N2)2[HgBr4], the tetra­coordinated HgII center of the complex anion adopts a distorted tetra­hedral geometry [Hg—Br = 2.5755 (8)–2.623 (11) Å and Br—Hg—Br = 103.78 (19)–116.4 (3)°]. One of the Br atoms is disordered over two sites [site-occupancy factors = 0.51 (6) and 0.49 (6)]. The N—C—N angles in the cations are 110.7 (6) and 111.4 (7)°. In the crystal packing, a supra­molecular chain is formed via both weak inter­molecular C—H⋯Br hydrogen bonds and π–π aromatic ring stacking inter­actions [centroid–centroid separation = 3.803 (1) Å]