When the going gets tough: Emergence of a complex methane-driven interaction network during recovery from desiccation-rewetting

Microorganisms interact in complex communities, affecting microbially-mediated processes in the environment. Particularly, aerobic methanotrophs showed significantly stimulated growth and activity in the presence of accompanying microorganisms in an interaction network (interactome). Yet, little is known of how the interactome responds to disturbances, and how community functioning is affected by the disturbance-induced structuring of the interaction network. Here, we employed a time-series stable isotope probing (SIP) approach using 13C–CH4 coupled to a co-occurrence network analysis after Illumina MiSeq sequencing of the 13C-enriched 16S rRNA gene to directly relate the response in methanotrophic activity to the network structure of the interactome after desiccation-rewetting of a paddy soil. Methane uptake rate decreased immediately (<5 days) after short-term desiccation-rewetting. Although the methanotroph subgroups differentially responded to desiccation-rewetting, the metabolically active bacterial community composition, including the methanotrophs, recovered after the disturbance. However, the interaction network was profoundly altered, becoming more complex but, less modular after desiccation-rewetting, despite the recovery in the methanotrophic activity and community composition/abundances. This suggests that the legacy of the disturbance persists in the interaction network. The change in the network structure may have consequences for community functioning with recurring desiccation-rewetting

Adaptive finite element method for eigensolutions of regular second and fourth order Sturm-Liouville problems via the element energy projection technique

Purpose The purpose of this paper is to present a numerically adaptive finite element (FE) method for accurate, efficient and reliable eigensolutions of regular second- and fourth-order Sturm–Liouville (SL) problems with variable coefficients. Design/methodology/approach After the conventional FE solution for an eigenpair (i.e. eigenvalue and eigenfunction) of a particular order has been obtained on a given mesh, a novel strategy is introduced, in which the FE solution of the eigenproblem is equivalently viewed as the FE solution of an associated linear problem. This strategy allows the element energy projection (EEP) technique for linear problems to calculate the super-convergent FE solutions for eigenfunctions anywhere on any element. These EEP super-convergent solutions are used to estimate the FE solution errors and to guide mesh refinements, until the accuracy matches user-preset error tolerance on both eigenvalues and eigenfunctions. Findings Numerical results for a number of representative and challenging SL problems are presented to demonstrate the effectiveness, efficiency, accuracy and reliability of the proposed method. Research limitations/implications The method is limited to regular SL problems, but it can also solve some singular SL problems in an indirect way. Originality/value Comprehensive utilization of the EEP technique yields a simple, efficient and reliable adaptive FE procedure that finds sufficiently fine meshes for preset error tolerances on eigenvalues and eigenfunctions to be achieved, even on problems which proved troublesome to competing methods. The method can readily be extended to vector SL problems. </jats:sec

Membrane-Bound sn-1,2-Diacylglycerols Explain the Dissociation of Hepatic Insulin Resistance from Hepatic Steatosis in MTTP Knockout Mice

Microsomal triglyceride transfer protein (MTTP) deficiency results in a syndrome of hypolipidemia and accelerated NAFLD. Animal models of decreased hepatic MTTP activity have revealed an unexplained dissociation between hepatic steatosis and hepatic insulin resistance. Here, we performed comprehensive metabolic phenotyping of liver-specific MTTP knockout (L-Mttp(-/-)) mice and age-weight matched wild-type control mice. Young (10-12-week-old) L-Mttp(-/-) mice exhibited hepatic steatosis and increased DAG content; however, the increase in hepatic DAG content was partitioned to the lipid droplet and was not increased in the plasma membrane. Young L-Mttp(-/-) mice also manifested normal hepatic insulin sensitivity, as assessed by hyperinsulinemic-euglycemic clamps, no PKC epsilon activation, and normal hepatic insulin signaling from the insulin receptor through AKT Ser/Thr kinase. In contrast, aged (10-month-old) L-Mttp(-/-) mice exhibited glucose intolerance and hepatic insulin resistance along with an increase in hepatic plasma membrane sn-1,2-DAG content and PKC epsilon activation. Treatment with a functionally liver-targeted mitochondrial uncoupler protected the aged L-Mttp(-/-) mice against the development of hepatic steatosis, increased plasma membrane sn-1,2-DAG content, PKC epsilon activation, and hepatic insulin resistance. Furthermore, increased hepatic insulin sensitivity in the aged controlled-release mitochondrial protonophore-treated L-Mttp(-/-) mice was not associated with any reductions in hepatic ceramide content. Taken together, these data demonstrate that differences in the intracellular compartmentation of sn-1,2-DAGs in the lipid droplet versus plasma membrane explains the dissociation of NAFLD/lipid-induced hepatic insulin resistance in young L-Mttp(-/-) mice as well as the development of lipid-induced hepatic insulin resistance in aged L-Mttp(-/-) miceThis work was supported by National Institutes of Health Grants R01 DK116774, R01 DK119968, R01 DK114793, R01 DK113984, K23 DK10287, P30 DK045735, DK121490, and HL137202 and the Veterans Health Administration Merit Review Awards I01 BX000901 and BX004113. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the U.S. Department of Veterans Affair

POLYMORPHISMS FOR VINYL CHLORIDE METABOLISM IN FRENCH VINYL CHLORIDE WORKERS

Abstract. Genetic polymorphisms of aldehyde dehydrogenase 2 (ALDH2) and cytochrome P450 2E1 (CYP2E1) have been shown to influence the degree of genetic damage in Taiwanese workers exposed to the carcinogen -vinyl chloride (VC). Certain French VC workers have been found to express biomarkers of mutant forms of cancer-related proteins (ras-p21 and p53) that have been related to their exposure. ALDH2 and CYP2E1 polymorphisms were investigated in 211 of these workers in an attempt to correlate differences in VC metabolic capacity with differences in the presence of these biomarkers. All of the workers were found to have the normal, wild-type ALDH2 gene, and none of them were found to be homozygous for the variant CYP2E1 allele. Sixteen workers were found to be heterozygous for the variant CYP2E1 allele. After adjusting for age, smoking, drinking and cumulative VC exposure, the odds ratio for the presence of either the mutant ras-p21 or the mutant p53 biomarker in these heterozygous workers was found to be statistically significantly increased in comparison to their homozygous, wild-type counterparts (OR = 5.05; 95% CI = 1.10-23.25). However, as opposed to the case in Taiwanese workers, these polymorphisms are relatively uncommon, and thus differences in ALDH2 and CYP2E1 can account for only a small proportion of the variability in mutagenic response to VC exposure in a Caucasian population

Integrative Genomic Data Mining for Discovery of Potential Blood-Borne Biomarkers for Early Diagnosis of Cancer

Background: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types. Methodology/Principal Findings: In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function. Conclusion/Significance: The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the ‘omics’ era

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe