Exposure Analysis of C8- and C9-Alkylphenols,Alkylphenol Ethoxylates,and Their Metabolites in Surface Water Systems within the United States

This study was conducted to develop a statistical understanding of exposures to C8- and C9-alkylphenol ethoxylates (APEO) and their metabolites (APEM) in U.S. surface waters. Concentrations of APEO/APEM (all analytes) in freshwater have been reported by 19 investigations over the past 15 years. Only limited data are available for sediments and marine ecosystems. Based on the frequency of detection in surface waters, 67% of all analytes were below their detection limits. Although maximum reported concentrations varied with time, the average and 90th centile concentrations have remained relatively constant. Examination of frequency distributions for nonylphenol (NP) concentrations indicated that 99% of the levels in fresh surface waters are below the U.S. Environmental Protection Agency's Aquatic Life Ambient Chronic Water Quality Criteria for NP (6.6 μg/L). A conservative evaluation of aggregated NPEO/NPEM concentrations suggested that 97% of the samples contained aggregate NP equivalent concentrations that are also below 6.6 μg/L. These results suggest that on a nationwide basis, the likelihood of surface water concentrations exceeding the chronic USEPA Water Quality Criterion for NP is low.     

The minimum information required for reporting a molecular interaction experiment (MIMIx)

A wealth of molecular interaction data is available in the literature, ranging from large-scale datasets to a single interaction confirmed by several different techniques. These data are all too often reported either as free text or in tables of variable format, and are often missing key pieces of information essential for a full understanding of the experiment. Here we propose MIMIx, the minimum information required for reporting a molecular interaction experiment. Adherence to these reporting guidelines will result in publications of increased clarity and usefulness to the scientific community and will support the rapid, systematic capture of molecular interaction data in public databases, thereby improving access to valuable interaction data.     

Role of mitochondrial electron transport complex I in coenzyme Q1 reduction by intact pulmonary arterial endothelial cells and the effect of hyperoxia

The objective was to determine the impact of intact normoxic and hyperoxia-exposed (95% O(2) for 48 h) bovine pulmonary arterial endothelial cells in culture on the redox status of the coenzyme Q(10) homolog coenzyme Q(1) (CoQ(1)). When CoQ(1) (50 microM) was incubated with the cells for 30 min, its concentration in the medium decreased over time, reaching a lower level for normoxic than hyperoxia-exposed cells. The decreases in CoQ(1) concentration were associated with generation of CoQ(1) hydroquinone (CoQ(1)H(2)), wherein 3.4 times more CoQ(1)H(2) was produced in the normoxic than hyperoxia-exposed cell medium (8.2 +/- 0.3 and 2.4 +/- 0.4 microM, means +/- SE, respectively) after 30 min. The maximum CoQ(1) reduction rate for the hyperoxia-exposed cells, measured using the cell membrane-impermeant redox indicator potassium ferricyanide, was about one-half that of normoxic cells (11.4 and 24.1 nmol x min(-1) x mg(-1) cell protein, respectively). The mitochondrial electron transport complex I inhibitor rotenone decreased the CoQ(1) reduction rate by 85% in the normoxic cells and 44% in the hyperoxia-exposed cells. There was little or no inhibitory effect of NAD(P)H:quinone oxidoreductase 1 (NQO1) inhibitors on CoQ(1) reduction. Intact cell oxygen consumption rates and complex I activities in mitochondria-enriched fractions were also lower for hyperoxia-exposed than normoxic cells. The implication is that intact pulmonary endothelial cells influence the redox status of CoQ(1) via complex I-mediated reduction to CoQ(1)H(2), which appears in the extracellular medium, and that the hyperoxic exposure decreases the overall CoQ(1) reduction capacity via a depression in complex I activity.     

A molecular assessment of northeast Pacific Alaria species (Laminariales, Phaeophyceae) with reference to the utility of DNA barcoding

Despite their relatively complex morphologies, species in the genus Alaria Greville are notoriously difficult to identify with certainty. Morphological characters, often influenced by environmental factors, make individuals in similar habitats artificially appear related. Species identification would, therefore, benefit greatly from the application of molecular tools. We applied DNA barcoding, using the 5' end of the cytochrome c oxidase I (coxI-5') gene from the mitochondrial genome, to define species limits and relationships in northeast Pacific populations of Alaria. This emerging technique is being employed to catalogue species diversity worldwide, particularly among animals, and it has been shown to be sensitive enough to discriminate between closely related species. However, the utility of this marker for identifying or categorizing the majority of life remains unclear. We compared the resolution obtained with this marker to two other molecular systems commonly used in algal research: the nuclear internal transcribed spacer (ITS) of the ribosomal cistron, and the plastid Rubisco operon spacer (rbcSp). In agreement with previous results, Alaria fistulosa Postels & Ruprecht, with its distinct morphological, ecological and molecular features, stands apart from the other species in the genus and we establish Druehlia gen. nov. to accommodate it. For the remaining isolates, distinct mitochondrial haplotypes resolved with the barcode data indicate a period of genetic isolation for at least three incipient species in the northeast Pacific, whereas unexpected levels and patterns of ITS variation, as well as the extreme morphological plasticity found among these isolates, have most probably resulted from a recent collapse in species barriers. The cloning of ITS amplicons revealed multiple ITS copies in several individuals, further supporting this hypothesis.     

A simple centrifugal dehydration force method to characterize water compartments in fresh and post-mortem fish muscle

A centrifugal dehydration force (CDF) method to quantify changes in tissue hydration in fresh and in post-mortem muscular fish tail tissue is presented. The data obtained were used to assess fluid flow rate from tissues and the size of hydration compartments expressed in g water/g dry mass (DM). Curve fit analysis demonstrated that muscle tissue has three detectable water compartments. Application of the method to the fresh fish indicated the presence of a large non-bulk water compartment (3.14 g water/g DM) with a much smaller (0.11 g water/g DM) inner non-bulk water sub-compartment in addition to a comparatively small bulk water compartment (0.99 g water/g DM). At 10 min and at 4h post-mortem, no significant change in size or flow rate of the water compartments was observed. At 24h post-mortem the muscular fish tissue, stored in water, swelled with statistically significant increase in total water and in the bulk water compartment but no significant change in the size of the non-bulk water compartments. The water flow rate from the non-bulk water compartment was, however, increased significantly in the 24h dead tissue. This simple CDF method has application for quantization of bulk and non-bulk water compartments in other biological and non-biological systems.     

Oligonucleotide fingerprint identification for microarray-based pathogen diagnostic assays

MOTIVATION: Advances in DNA microarray technology and computational methods have unlocked new opportunities to identify 'DNA fingerprints', i.e. oligonucleotide sequences that uniquely identify a specific genome. We present an integrated approach for the computational identification of DNA fingerprints for design of microarray-based pathogen diagnostic assays. We provide a quantifiable definition of a DNA fingerprint stated both from a computational as well as an experimental point of view, and the analytical proof that all in silico fingerprints satisfying the stated definition are found using our approach. RESULTS: The presented computational approach is implemented in an integrated high-performance computing (HPC) software tool for oligonucleotide fingerprint identification termed TOFI. We employed TOFI to identify in silico DNA fingerprints for several bacteria and plasmid sequences, which were then experimentally evaluated as potential probes for microarray-based diagnostic assays. Results and analysis of approximately 150 in silico DNA fingerprints for Yersinia pestis and 250 fingerprints for Francisella tularensis are presented. AVAILABILITY: The implemented algorithm is available upon request.     

Estimating p-values in small microarray experiments

MOTIVATION: Microarray data typically have small numbers of observations per gene, which can result in low power for statistical tests. Test statistics that borrow information from data across all of the genes can improve power, but these statistics have non-standard distributions, and their significance must be assessed using permutation analysis. When sample sizes are small, the number of distinct permutations can be severely limited, and pooling the permutation-derived test statistics across all genes has been proposed. However, the null distribution of the test statistics under permutation is not the same for equally and differentially expressed genes. This can have a negative impact on both p-value estimation and the power of information borrowing statistics. RESULTS: We investigate permutation based methods for estimating p-values. One of methods that uses pooling from a selected subset of the data are shown to have the correct type I error rate and to provide accurate estimates of the false discovery rate (FDR). We provide guidelines to select an appropriate subset. We also demonstrate that information borrowing statistics have substantially increased power compared to the t-test in small experiments.     

A global approach to identify differentially expressed genes in cDNA (two-color) microarray experiments

MOTIVATION: Currently most of the methods for identifying differentially expressed genes fall into the category of so called single-gene-analysis, performing hypothesis testing on a gene-by-gene basis. In a single-gene-analysis approach, estimating the variability of each gene is required to determine whether a gene is differentially expressed or not. Poor accuracy of variability estimation makes it difficult to identify genes with small fold-changes unless a very large number of replicate experiments are performed. RESULTS: We propose a method that can avoid the difficult task of estimating variability for each gene, while reliably identifying a group of differentially expressed genes with low false discovery rates, even when the fold-changes are very small. In this article, a new characterization of differentially expressed genes is established based on a theorem about the distribution of ranks of genes sorted by (log) ratios within each array. This characterization of differentially expressed genes based on rank is an example of all-gene-analysis instead of single gene analysis. We apply the method to a cDNA microarray dataset and many low fold-changed genes (as low as 1.3 fold-changes) are reliably identified without carrying out hypothesis testing on a gene-by-gene basis. The false discovery rate is estimated in two different ways reflecting the variability from all the genes without the complications related to multiple hypothesis testing. We also provide some comparisons between our approach and single-gene-analysis based methods. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.