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With the exploitation of offshore oil and gas gradually moving to deep water, higher temperature differences and pressure differences are applied to the pipeline system, making the global buckling of the pipeline more serious. For unburied deep-water pipelines, the lateral buckling is the major buckling form. The initial imperfections widely exist in the pipeline system due to manufacture defects or the influence of uneven seabed, and the distribution and geometry features of initial imperfections are random. They can be divided into two kinds based on shape: single-arch imperfections and double-arch imperfections. This paper analyzed the global buckling process of a pipeline with 2 initial imperfections by using a numerical simulation method and revealed how the ratio of the initial imperfection's space length to the imperfection's wavelength and the combination of imperfections affects the buckling process. The results show that a pipeline with 2 initial imperfections may suffer the superposition of global buckling. The growth ratios of buckling displacement, axial force and bending moment in the superposition zone are several times larger than no buckling superposition pipeline. The ratio of the initial imperfection's space length to the imperfection's wavelength decides whether a pipeline suffers buckling superposition. The potential failure point of pipeline exhibiting buckling superposition is as same as the no buckling superposition pipeline, but the failure risk of pipeline exhibiting buckling superposition is much higher. The shape and direction of two nearby imperfections also affects the failure risk of pipeline exhibiting global buckling superposition. The failure risk of pipeline with two double-arch imperfections is higher than pipeline with two single-arch imperfections.

For health technology assessment (HTA) to be more policy relevant and for health technology-related decision-making to be truly evidence-based, promoting knowledge translation (KT) is of vital importance. Although some research has focused on KT of HTA, there is a dearth of literature on KT determinants and the situation in developing countries and transitional societies remains largely unknown.To investigate the determinants of HTA KT from research to health policy-making from the perspective of researchers in China.Cross-sectional study.A structured questionnaire which focused on KT was distributed to HTA researchers in China. KT activity levels in various fields of HTA research were compared, using one-way ANOVA. Principal component analysis was performed to provide a basis to combine similar variables. To investigate the determinants of KT level, multiple linear regression analysis was performed.Based on a survey of 382 HTA researchers, it was found that HTA KT wasn't widespread in China. Furthermore, results showed that no significant differences existed between the various HTA research fields. Factors, such as attitudes of researchers toward HTA and evidence utilization, academic ranks and linkages between researchers and policy-makers, had significant impact on HTA KT (p-values

Pathway analysis is a common approach to gain insight from biological experiments. Signaling-pathway impact analysis (SPIA) is one such method and combines both the classical enrichment analysis and the actual perturbation on a given pathway. Because this method focuses on a single pathway, its resolution generally is not very high because the differentially expressed genes may be enriched in a local region of the pathway. In the present work, to identify cancer-related pathways, we incorporated a recent subpathway analysis method into the SPIA method to form the "sub-SPIA method." The original subpathway analysis uses the k-clique structure to define a subpathway. However, it is not sufficiently flexible to capture subpathways with complex structure and usually results in many overlapping subpathways. We therefore propose using the minimal-spanning-tree structure to find a subpathway. We apply this approach to colorectal cancer and lung cancer datasets, and our results show that sub-SPIA can identify many significant pathways associated with each specific cancer that other methods miss. Based on the entire pathway network in the Kyoto Encyclopedia of Genes and Genomes, we find that the pathways identified by sub-SPIA not only have the largest average degree, but also are more closely connected than those identified by other methods. This result suggests that the abnormality signal propagating through them might be responsible for the specific cancer or disease.

TERT is of great importance in cancer initiation and progression. Many studies have demonstrated the TERT polymorphisms as risk factors for many cancer types, including lung cancer. However, the impacts of TERT variants on cancer progression and treatment efficacy have remained controversial. This study aimed to investigate the association of TERT polymorphisms with clinical outcome of advanced non-small cell lung cancer (NSCLC) patients receiving first-line platinum-based chemotherapy, including response rate, clinical benefit, progression-free survival (PFS), overall survival (OS), and grade 3 or 4 toxicity. Seven polymorphisms of TERT were assessed, and a total of 1004 inoperable advanced NSCLC patients treated with platinum-based chemotherapy were enrolled. It is exhibited that the variant heterozygote of rs4975605 showed significant association with a low rate of clinical benefit, and displayed a much stronger effect in never-smoking female subset, leading to the clinical benefit rate decreased from 82.9% (C/C genotype) to 56.4% (C/A genotype; adjusted OR, 3.58; P=1.40×10(-4)). It is also observed that the polymorphism rs2736109 showed significant correlation with PFS (log-rank P=0.023). In age > 58 subgroup, patients carrying the heterozygous genotype had a longer median PFS than those carrying the wild-type genotypes (P=0.002). The results from the current study, for the first time to our knowledge, provide suggestive evidence of an effect of TERT polymorphisms on disease progression variability among Chinese patients with platinum-treated advanced NSCLC.

The number of the overweight people continues to rise across the world. Studies have shown that being overweight can increase health risks, such as high blood pressure, diabetes mellitus, coronary heart disease, and certain forms of cancer. Therefore, identifying the overweight status in people is critical to prevent and decrease health risks. This study explores a new technique that uses blood and biochemical measurements to recognize the overweight condition. A new machine learning technique, an extreme learning machine, was developed to accurately detect the overweight status from a pool of 225 overweight and 251 healthy subjects. The group included 179 males and 297 females. The detection method was rigorously evaluated against the real-life dataset for accuracy, sensitivity, specificity, and AUC (area under the receiver operating characteristic (ROC) curve) criterion. Additionally, the feature selection was investigated to identify correlating factors for the overweight status. The results demonstrate that there are significant differences in blood and biochemical indexes between healthy and overweight people (p-value < 0.01). According to the feature selection, the most important correlated indexes are creatinine, hemoglobin, hematokrit, uric Acid, red blood cells, high density lipoprotein, alanine transaminase, triglyceride, and γ-glutamyl transpeptidase. These are consistent with the results of Spearman test analysis. The proposed method holds promise as a new, accurate method for identifying the overweight status in subjects.

Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.

Blunt snout bream (Megalobrama amblycephala) are susceptible to hepatic steatosis when maintained in modern intensive culture systems. The aim of this study was to investigate the potential roles of microRNAs (miRNAs) in diet-induced hepatic steatosis in this species. MiRNAs, small non-coding RNAs that regulate gene expression at the posttranscriptional level, are involved in diverse biological processes, including lipid metabolism. Deep sequencing of hepatic small RNA libraries from blunt snout bream fed normal-fat and high-fat diets identified 202 (193 known and 9 novel) miRNAs, of which 12 were differentially expressed between the normal-fat and high-fat diet groups. Quantitative stem-loop reverse transcriptase-polymerase chain reaction analyses confirmed the upregulation of miR-30c and miR-30e-3p and the downregulation of miR-145 and miR-15a-5p in high-fat diet-fed fish. Bioinformatics tools were used to predict the targets of these verified miRNAs and to explore potential downstream gene ontology biological process categories and Kyoto Encyclopedia of Genes and Genomes pathways. Six putative lipid metabolism-related target genes (fetuin-B, Cyp7a1, NADH dehydrogenase (ubiquinone) 1 beta subcomplex subunit 2, 3-oxoacid CoA transferase 1b, stearoyl-CoA desaturase, and fatty-acid synthase) were identified as having potential important roles in the development of diet-induced hepatic steatosis in blunt snout bream. The results presented here are a foundation for future studies of miRNA-controlled lipid metabolism regulatory networks in blunt snout bream.

DNA methylation is involved in tissue-specific and developmentally regulated gene expression. Here, we screened a novel methylation gene Sox30, whose methylation might contribute to its regulation and testis development in mice. Sox30 is a member of Sox transcription factors, and is considered to be involved in spermatogonial differentiation and spermatogenesis. However, the precise function and regulatory expression pattern remain unclear. In the present study, we found that Sox30 is highly expressed in adult testes but not in ovaries. Sox30 expression begins in early development, and in the testes, it is specifically increased coincidentally with development until adulthood. Moreover, Sox30 is expressed not only in testis germ cells, but also in sertoli cells. Sox30 is hypo-methylated in testis, epididymis and lung of adult mice, in which Sox30 is expressed. By contrast, Sox30 is hypermethylated in ovary, heart, brain, liver, kidney, spleen, pancreas, muscle, intestine, pituitary gland, blood and hippocampus of adult mice, in which the Sox30 is absent. Importantly, decreased methylation at CpG islands of Sox30 is observed in mouse developmental testes after birth, which is associated with enhanced Sox30 expression. However, the hypermethylated status of Sox30 is maintained in ovaries that does not express Sox30 during this period. Further, following demethylation treatment using 5-aza-dC, Sox30 expression is restored in GC2, TM3 and TM4 cell lines. This observation convincingly confirms that methylation really contributes to Sox30 silencing. In summary, we show that Sox30 expression is under the control of DNA methylation status, and this expression pattern is associated with testis development in mice.

Osterix (Osx) is an osteoblast-specific transcription factor which is essential for bone formation. MicroRNAs (miRNAs) have been previously shown to be involved in osteogenesis. However, it is unclear whether Osx is involved in the regulation of miRNA expression. In this study, we have identified groups of miRNAs that are differentially expressed in calvaria of the E18.5 Osx(-/-) embryos compared to wild type embryos. The correlation between the levels of miRNAs and Osx expression was further verified in cultured M-Osx cells in which over-expression of Osx is inducible. Our results suggest that Osx down-regulates expression of a group of miRNAs including mir-133a and -204/211, but up-regulates expression of another group of miRNAs such as mir-141/200a. Mir-133a and -204/211 are known to target the master osteogenic transcription factor Runx2. Further assays suggest that Sost, which encodes the Wnt signaling antagonist Sclerostin, and alkaline phosphatase (ALP) are two additional targets of mir-204/211. Mir-141/200a has been known to target the transcription factor Dlx5. Thus, we postulate that during the process of Osx-controlled osteogenesis, Osx has the ability to coordinately modulate Runx2, Sclerostin, ALP and Dlx5 proteins at levels appropriate for optimal osteoblast differentiation and function, at least in part, through regulation of specific miRNAs. Our study shows a tight correlation between Osx and the miRNAs involved in bone formation, and provides new information about molecular mechanisms of Osx-controlled osteogenesis.

BACKGROUND:Lysophosphatidic acid (LPA) governs a number of physiologic and pathophysiological processes. Malignant ascites fluid is rich in LPA, and LPA receptors are aberrantly expressed by ovarian cancer cells, implicating LPA in the initiation and progression of ovarian cancer. However, there is an absence of systematic data critically analyzing the transcriptional changes induced by LPA in ovarian cancer. METHODOLOGY AND PRINCIPAL FINDINGS:In this study, gene expression profiling was used to examine LPA-mediated transcription by exogenously adding LPA to human epithelial ovarian cancer cells for 24 h to mimic long-term stimulation in the tumor microenvironment. The resultant transcriptional profile comprised a 39-gene signature that closely correlated to serous epithelial ovarian carcinoma. Hierarchical clustering of ovarian cancer patient specimens demonstrated that the signature is associated with worsened prognosis. Patients with LPA-signature-positive ovarian tumors have reduced disease-specific and progression-free survival times. They have a higher frequency of stage IIIc serous carcinoma and a greater proportion is deceased. Among the 39-gene signature, a group of seven genes associated with cell adhesion recapitulated the results. Out of those seven, claudin-1, an adhesion molecule and phenotypic epithelial marker, is the only independent biomarker of serous epithelial ovarian carcinoma. Knockdown of claudin-1 expression in ovarian cancer cells reduces LPA-mediated cellular adhesion, enhances suspended cells and reduces LPA-mediated migration. CONCLUSIONS:The data suggest that transcriptional events mediated by LPA in the tumor microenvironment influence tumor progression through modulation of cell adhesion molecules like claudin-1 and, for the first time, report an LPA-mediated expression signature in ovarian cancer that predicts a worse prognosis.

Background: Lysophosphatidic acid (LPA) governs a number of physiologic and pathophysiological processes. Malignant ascites fluid is rich in LPA, and LPA receptors are aberrantly expressed by ovarian cancer cells, implicating LPA in the initiation and progression of ovarian cancer. However, there is an absence of systematic data critically analyzing the transcriptional changes induced by LPA in ovarian cancer. Methodology and Principal Findings: In this study, gene expression profiling was used to examine LPA-mediated transcription by exogenously adding LPA to human epithelial ovarian cancer cells for 24 h to mimic long-term stimulation in the tumor microenvironment. The resultant transcriptional profile comprised a 39-gene signature that closely correlated to serous epithelial ovarian carcinoma. Hierarchical clustering of ovarian cancer patient specimens demonstrated that the signature is associated with worsened prognosis. Patients with LPA-signature-positive ovarian tumors have reduced disease-specific and progression-free survival times. They have a higher frequency of stage IIIc serous carcinoma and a greater proportion is deceased. Among the 39-gene signature, a group of seven genes associated with cell adhesion recapitulated the results. Out of those seven, claudin-1, an adhesion molecule and phenotypic epithelial marker, is the only independent biomarker of serous epithelial ovarian carcinoma. Knockdown of claudin-1 expression in ovarian cancer cells reduces LPA-mediated cellular adhesion, enhances suspended cells and reduces LPA-mediated migration. Conclusions: The data suggest that transcriptional events mediated by LPA in the tumor microenvironment influence tumor progression through modulation of cell adhesion molecules like claudin-1 and, for the first time, report an LPA-mediated expression signature in ovarian cancer that predicts a worse prognosis. [ABSTRACT FROM AUTHOR]