A Pilot Study: Changes of Gut Microbiota in Post-surgery Colorectal Cancer Patients

Colorectal cancer (CRC) is a growing health problem throughout the world. Strong evidences have supported that gut microbiota can influence tumorigenesis; however, little is known about what happens to gut microbiota following surgical resection. Here, we examined the changes of gut microbiota in CRC patients after the surgical resection. Using the PCoA analysis and dissimilarity tests, the microbial taxonomic compositions and diversities of gut microbiota in post-surgery CRC patients (A1) were significantly different from those in pre-surgery CRC patients (A0) and healthy individuals (H). Compared with A0 and H, the Shannon diversity and Simpson diversity were significantly decreased in A1 (P < 0.05). Based on the LEfSe analysis, the relative abundance of phylum Proteobacteria in A1 was significantly increased than that in A0 and H. The genus Klebsiella in A1 had higher proportions than that in A0 (P < 0.05). Individual variation was distinct; however, 90% of CRC patients in A1 had more abundances of Klebsiella than A0. The Klebsiella in A1 was significantly associated with infectious diseases (P < 0.05), revealed by the correlation analysis between differentiated genera and metabolic pathway. The Klebsiella (Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae) in A1 was significantly linked with lymphatic invasion (P < 0.05). Furthermore, the PCA of KEGG pathways indicated that gut microbiota with a more scattered distribution in A1 was noticeably different from that in A0 and H. The nodes, the links, and the kinds of phylum in each module in A1 were less than those in A0 and H, indicating that gut microbiota in A1 had a relatively looser ecologcial interaction network. To sum up, this pilot study identified the changes of gut microbiota in post-surgery CRC patients, and highlights future avenues in which the gut microbiota is likely to be of increasing importance in the care of surgical patients

Investigating the Mechanisms of Action of Depside Salt from Salvia miltiorrhiza Using Bioinformatic Analysis

Salvia miltiorrhiza is a traditional Chinese medicinal herb used for treating cardiovascular diseases. Depside salt from S. miltiorrhiza (DSSM) contains the following active components: magnesium lithospermate B, lithospermic acid, and rosmarinic acid. This study aimed to reveal the mechanisms of action of DSSM. After searching for DSSM-associated genes in GeneCards, Search Tool for Interacting Chemicals, SuperTarget, PubChem, and Comparative Toxicogenomics Database, they were subjected to enrichment analysis using Multifaceted Analysis Tool for Human Transcriptome. A protein-protein interaction (PPI) network was visualised; module analysis was conducted using the Cytoscape software. Finally, a transcriptional regulatory network was constructed using the TRRUST database and Cytoscape. Seventy-three DSSM-associated genes were identified. JUN, TNF, NFKB1, and FOS were hub nodes in the PPI network. Modules 1 and 2 were identified from the PPI network, with pathway enrichment analysis, showing that the presence of NFKB1 and BCL2 in module 1 was indicative of a particular association with the NF-κB signalling pathway. JUN, TNF, NFKB1, FOS, and BCL2 exhibited notable interactions among themselves in the PPI network. Several regulatory relationships (such as JUN → TNF/FOS, FOS → NFKB1 and NFKB1 → BCL2/TNF) were also found in the regulatory network. Thus, DSSM exerts effects against cardiovascular diseases by targeting JUN, TNF, NFKB1, FOS, and BCL2

Mechanisms for estrogen receptor expression in human cancer

Abstract Estrogen is a steroid hormone that has critical roles in reproductive development, bone homeostasis, cardiovascular remodeling and brain functions. However, estrogen also promotes mammary, ovarian and endometrial tumorigenesis. Estrogen antagonists and drugs that reduce estrogen biosynthesis have become highly successful therapeutic agents for breast cancer patients. The effects of estrogen are largely mediated by estrogen receptor (ER) α and ERβ, which are members of the nuclear receptor superfamily of transcription factors. The mechanisms underlying the aberrant expression of ER in breast cancer and other types of human tumors are complex, involving considerable alternative splicing of ERα and ERβ, transcription factors, epigenetic and post-transcriptional regulation of ER expression. Elucidation of mechanisms for ER expression may not only help understand cancer progression and evolution, but also shed light on overcoming endocrine therapy resistance. Herein, we review the complex mechanisms for regulating ER expression in human cancer

Pauropods (Myriapoda: Pauropoda) from eastern China, descriptions of three new species and revision of Pauropus bifurcus Zhang & Chen, 1988

Qian, Changyuan, Dong, Yan, Guo, Hua, Chu, Kelin, Sun, Hongying (2013): Pauropods (Myriapoda: Pauropoda) from eastern China, descriptions of three new species and revision of Pauropus bifurcus Zhang & Chen, 1988. Zootaxa 3608 (2): 116-126, DOI: 10.11646/zootaxa.3608.2.

Multichannel semi-supervised active learning for PolSAR image classification

Deep neural networks have recently been extensively utilized for Polarimetric synthetic aperture radar (PolSAR) image classification. However, this heavily relies on extensive labeled data which is both costly and labor-intensive. To lower the collection of labeling data and enhance the classification performance, a novel multichannel semi-supervised active learning (MSSAL) method is proposed for PolSAR image classification. First, a multichannel strategy-based committee model with cooperative representation classification is presented to explore more effective information in the limited training data. Second, a loss prediction (LP) module is designed to identify the most informative pixels, and an ensemble learning (EL) strategy is designed to select the pixels with the highest confidence. Then, the deep neural network is fine-tuned with the obtaining target pixels through LP and EL in each iteration. Finally, the trained deep model predicts labels for all unlabeled data, outputting the final classification results. The proposed method is evaluated on three real-world PolSAR datasets, demonstrating superior performance to other PolSAR image classification methods with limited labeled samples

Perivascular epithelioid cell neoplasm of the urinary bladder in an adolescent: a case report and review of the literature

Abstract Perivascular epithelioid cell neoplasms (PEComas) of the urinary bladder are extremely rare and the published cases were comprised predominantly of middle-aged patients. Herein, the authors present the first urinary bladder PEComa occurring in an adolescent. This 16-year-old Chinese girl present with a 3-year history of abdominal discomfort and a solid mass was documented in the urinary bladder by ultrasonography. Two years later, at the age of 18, the patient underwent transurethral resection of the bladder tumor. Microscopically, the tumor was composed of spindled cells mixed with epithelioid cells. Immunohistochemically, the tumor were strongly positive for HMB45, smooth muscle actin, muscle-specific actin, and H-caldesmon. Fluorescence in situ hybridization analysis revealed no evidence of EWSR1 gene rearrangement. The patient had been in a good status without evidence of recurrence 13 months after surgery. Urinary bladder PEComa is an extremely rare neoplasm and seems occur predominantly in middle-aged patients. However, this peculiar lesion can develop in pediatric population and therefore it should be rigorously distinguished from their mimickers. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1870004378817301</p

Multivariate Analysis of Trace Element Concentrations in Atmospheric Deposition in the Yangtze River Delta, East China

The Yangtze River Delta (YRD), one of the fastest developing regions in China, was investigated for its trace element concentrations. Forty-three samples of atmospheric deposition were analyzed for their concentrations of thirteen elements, As, Cd, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, S and Zn. The results show that, in comparison with Chinese soil, the atmospheric deposition in the YRD generally has elevated trace element concentrations, except for Fe and Mn. The current atmospheric deposition of Cd, Cr, Cu, Pb and Zn in the YRD is significantly higher than the results from previous studies in other regions around the world. Four main sources of the trace elements were identified using statistical techniques including descriptive, correlation, and multivariate analyses, such as principal component analysis (PCA) and cluster analysis (CA). The four sources and associated cluster elements are: (1) road traffic emissions contributing As, Hg, Cu, Cd, Mo, S and Zn; (2) pyrometallurgical processes associated with Cr and Ni; (3) resuspension of soil particles contributing Fe and Mn; (4) coal combustion associated with Pb and Se. The four major sources were further verified by enrichment factor (EF) calculation and spatial analysis. Spatial distributions of four factor scores and EFs of elements show that high scores and EFs of trace metals (As, Hg, Cu, Cd, Mo, S and Zn) are mostly concentrated in the sites with high traffic conditions, and high scores of Fe and Mn are found at rural sites associated with high impact of soil particles resuspension, while Cr and Ni are higher in the area with long history of alloy machining