A novel approach to measuring subtidal habitat complexity

Habitat complexity plays an important role in determining benthic community structure. A diverse range of methods for its measurement have been adopted but none are convenient for use underwater where access time is at a premium. We describe a novel, calibrated, tool for rapidly measuring scale-dependent habitat complexity developed, primarily, for use underwater. This tool is based on a distance-wheel with interchangeable wheels of different sizes to allow a scale-dependent measure of distance. This technique was calibrated against a profile of known complexity, at relevant scales, and then trialed on the Loch Linnhe Artificial Reef, a replicated artificial substratum offering two different scale-dependent habitat complexities. The distance-wheel was cost-effective, simple to fabricate and enabled the rapid and straightforward measurement of perceived distance over the step-length range of 133-1020 mm.     

A novel network-based method for measuring the functional relationship between gene sets

MOTIVATION: In the functional genomic era, a large number of gene sets have been identified via high-throughput genomic and proteomic technologies. These gene sets of interest are often related to the same or similar disorders or phenotypes, and are commonly presented as differentially expressed gene lists, co-expressed gene modules, protein complexes or signaling pathways. However, biologists are still faced by the challenge of comparing gene sets and interpreting the functional relationships between gene sets into an understanding of the underlying biological mechanisms. RESULTS: We introduce a novel network-based method, designated corrected cumulative rank score (CCRS), which analyzes the functional communication and physical interaction between genes, and presents an easy-to-use web-based toolkit called GsNetCom to quantify the functional relationship between two gene sets. To evaluate the performance of our method in assessing the functional similarity between two gene sets, we analyzed the functional coherence of complexes in functional catalog and identified protein complexes in the same functional catalog. The results suggested that CCRS can offer a significant advance in addressing the functional relationship between different gene sets compared with several other available tools or algorithms with similar functionality. We also conducted the case study based on our method, and succeeded in prioritizing candidate leukemia-associated protein complexes and expanding the prioritization and analysis of cancer-related complexes to other cancer types. In addition, GsNetCom provides a new insight into the communication between gene modules, such as exploring gene sets from the perspective of well-annotated protein complexes. Availability and Implementation: GsNetCom is a freely available web accessible toolkit at http://bioinfo.hrbmu.edu.cn/GsNetCom.     

A novel approach for addressing enrichment and exercise for dogs in a teaching institution

The author describes a pilot Animal-Assisted Activities (AAA) program that provides additional enrichment and exercise for beagles maintained for educational purposes. In addition, the program educates the community on research involving animals, provides positive interactions between the institution and the community, and develops community service skills in students.     

A novel scratching approach for measuring age-related changes in the in situ toughness of bone

A scratch test using a nanoindentation system was proposed in this study to assess the age-related changes in the in situ toughness of bone matrix at ultrastructural levels. A tissue removal energy density (u(r)) was defined and estimated as the work done by the scratch (U(T)) divided by the total volume of the scratch groove (u(s)). The value of u(s) was used as a relative measure of the in situ toughness of the tissue. Human cortical bone specimens obtained from middle-aged (between 49 and 59 years old) and elderly groups (over 69 years old) were tested using this technique. A significant difference in the estimated removal energy density (u(s)) in the secondary osteons was found between the middle-aged and elderly groups (5.49+/-0.696 vs. 4.09+/-1.30 N/mm(2), respectively).     

A novel approach to measuring heat flux in swimming animals

We present a design for long-term or removable attachment of heat flux sensors (HFSs) to stationary or swimming animals in water that enables collection of heat flux data on both captive and free-ranging pinnipeds. HFSs were modified to allow for independent, continuous, and long-term or removable attachment to study animals. The design was tested for effects of HFSs and the attachment mechanism on resultant heat flux. Effects were insulative and consistent across water temperatures and flow speeds, resulting in a correction factor of 3.42. This correction factor was applied to all measurements of heat flux from animal experiments to account for the thermal resistance of HFSs and insulative effects of the attachment mechanism. Heat flux and skin temperature data were collected from two captive Steller sea lions (Eumetopias jubatus) as they swam in a large habitat tank over time periods ranging from approximately 4 to 9 min. Of the 72 HFSs deployed using the attachment mechanism, data were successfully retrieved from 70. The HFS attachment mechanism was also used on two wild free-ranging Weddell seals (Leptonychotes weddellii) off Ross Island, Antarctica, for up to 7 days. Heat flux data were retrieved from all eight sensors deployed. These results, along with those from Steller sea lions, suggest that HFSs can be deployed with success on captive and wild animals using the designed attachment mechanism.     

Absolute enrichment: gene set enrichment analysis for homeostatic systems

The Gene Set Enrichment Analysis (GSEA) identifies sets of genes that are differentially regulated in one direction. Many homeostatic systems will include one limb that is upregulated in response to a downregulation of another limb and vice versa. Such patterns are poorly captured by the standard formulation of GSEA. We describe a technique to identify groups of genes (which sometimes can be pathways) that include both up- and down-regulated components. This approach lends insights into the feedback mechanisms that may operate, especially when integrated with protein interaction databases.     

A spin probe approach for measuring the nucleic acid affinity of gene 32 protein.

A novel and fast procedure for determining by electron spin resonance the affinity of proteins for nucleic acids is described. The assay makes use of nitroxide radicals which are covalently bound to various polynuleotides to the extent of one probe per 75 to 100 nucleotides. As a test example gene 32 protein was used, a protein known to interact with single stranded nucleic acids. Competition experiments with unlabeled nucleic acids made it feasible to directly monitor the gene 32 protein affinity for different nucleic acids. It was observed that DNA single strands are not necessarily favored by this protein for preferential binding. The experimental data also suggest that the difference in the binding constants for most of the complexes is remarkably large; for instance, (dT)_n binds at least 3 to 4 orders of magnitude better to gene 32 protein than (dA)_n.     

A test for measuring the effects of enzyme inactivation

In the single-enzyme, single-substrate reaction with non-mechanism-based enzyme inactivation, the formation of the product and inactivation of the enzyme occur independently. For this reaction, we show that the steady-state hypothesis is applicable even when degradation of the enzyme occurs. An equation for the rate of product formation has been derived and it shows Michaelis-Menten kinetics with an apparent Michaelis-Menten constant K(M)(app)=K(M)+K(delta) where K(delta) is the enzyme inactivation constant. Use of a Lineweaver-Burk plot yields values for K(M)(app), which can be used to estimate K(delta) and, consequently, the degree of enzyme inactivation in a particular experiment. We employ this methodology to estimate the inactivation constant for the arsenate reductase catalyzed production of arsenite with appreciable enzyme inactivation.     

A new null hypothesis for measuring the degree of plant community organization

An attempt is made to derive a measure for the degree of plant community organization, which would not be based on species co-occurrence and co-abundance. The use of the independent random distribution hypothesis (IRDH) is suggested for this purpose. The hypothesis is expected to be valid, if no deterministic phytosociological-structure-generating mechanism is present. If structural variability is used as a statistic for testing the hypothesis, deviances from the conditions of IRDH (species distributions are independent from each other, environmental gradients are lacking) will be attributable either to species interactions (smaller structural variability than expected), or to environmental heterogeneity (greater structural variability than expected). Structural variability is evaluated as the variance of species diversity, the indexN=exp(H') is used for measuring diversity. The precise measure of the degree of community organizationW is computed as the shift between two empirical distributions:D ^* (VN) or Bootstrap distribution of variance of diversity in the community, andD ^o (VN) or the random community variability distribution, which is evaluated after simulating the IRDH conditions.A satisfactory interpretation can be given to the results of evaluatingW for 11 data sets of 10 relevés each.Abbreviation IRDH Independent random distribution hypothesis     

A computational approach to measuring coherence of gene expression in pathways

This study uses a computational approach to analyze coherence of expression of genes in pathways. Microarray data were analyzed with respect to coherent gene expression in a group of genes defined as a pathway in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Our hypothesis is that genes in the same pathway are more likely to be coordinately regulated than a randomly selected gene set. A correlation coefficient for each pair of genes in a pathway was estimated based on gene expression in normal or tumor samples, and statistically significant correlation coefficients were identified. The coherence indicator was defined as the ratio of the number of gene pairs in the pathway whose correlation coefficients are significant, divided by the total number of gene pairs in the pathway. We defined all genes that appeared in the KEGG pathways as a reference gene set. Our analysis indicated that the mean coherence indicator of pathways is significantly larger than the mean coherence indicator of random gene sets drawn from the reference gene set. Thus, the result supports our hypothesis. The significance of each individual pathway of n genes was evaluated by comparing its coherence indicator with coherence indicators of 1000 random permutation sets of n genes chosen from the reference gene set. We analyzed three data sets: two Affymetrix microarrays and one cDNA microarray. For each of the three data sets, statistically significant pathways were identified among all KEGG pathways. Seven of 96 pathways had a significant coherence indicator in normal tissue and 14 of 96 pathways had a significant coherence indicator in tumor tissue in all three data sets. The increase in the number of pathways with significant coherence indicators may reflect the fact that tumor cells have a higher rate of metabolism than normal cells. Five pathways involved in oxidative phosphorylation, ATP synthesis, protein synthesis, or RNA synthesis were coherent in both normal and tumor tissue, demonstrating that these are essential genes, a high level of expression of which is required regardless of cell type.     

A novel method for measuring the thermal conductivity of organisms

Based on the theories of tissue optics and artificial neural network, the relationship between the optical properties and biological parameters was studied, and a new experimental method was derived. The properties of the organism were obtained indirectly by a black-box model derived by self-study of the artificial neural network between optical parameters and thermo-physical properties without using the heat transfer equation. In this method, the energy of light in diffuse radiation, diffuse transmission and collimated transmission was absorbed by a dual-integrating sphere experimental system of a spectrometer, and the spectrogram of the energy was obtained. Combining these spectral data of the energy, the diffuse-reflecting power, the diffuse transmissivity and the collimated transmissivity were calculated. The calculated results were taken as the input parameters of a black-box model. The experimental results show that there are apparent differences between the spectrogram of the energy on the diffuse radiation, the diffuse transmission and the collimated transmission of different matters, while there is a little difference in the same matter. Each spectrogram has its own characteristic. The values of the four thermal properties including the density, the constant pressure specific heat, the thermal diffusivity and the viscosity were calculated using the black-box model. Compared with the real values the calculated one has an average relative error between −5% and 5%. The conductivity of the tongue is 0.68 W/(m K) that calculated from the value of the density, the constant pressure specific heat and the thermal diffusivity. The results also show that there is a little difference on the conductivities in the longitudinal cross-section and the transverse section, but the effect of temperature on the conductivity of the tongue is not apparent. The difference implies the anisotropy of the properties of the organism, which cannot be easily obtained by a conventional experimental method.     

A high-throughput approach for measuring temporal changes in the interactome

Interactomes are often measured using affinity purification-mass spectrometry (AP-MS) or yeast two-hybrid approaches, but these methods do not provide stoichiometric or temporal information. We combine quantitative proteomics and size-exclusion chromatography to map 291 coeluting complexes. This method allows mapping of an interactome to the same depth and accuracy as AP-MS with less work and without overexpression or tagging. The use of triplex labeling enables monitoring of interactome rearrangements.     

A general modular framework for gene set enrichment analysis

Background  

Analysis of microarray and other high-throughput data on the basis of gene sets, rather than individual genes, is becoming more important in genomic studies. Correspondingly, a large number of statistical approaches for detecting gene set enrichment have been proposed, but both the interrelations and the relative performance of the various methods are still very much unclear.     

DNase test as a novel approach for the routine screening of Corynebacterium diphtheriae

Aims: To examine the value of the DNase test as an alternative procedure for differentiating Corynebacterium diphtheriae from Corynebacterium‐like colonies. Methods and Results: DNase test medium was inoculated by spotting a loopful of bacterial growth and incubated aerobically at 37°C. The DNase production was detectable following both 24 and 48 h incubation periods. The DNase activity was detected in all 91 C. diphtheriae (37 toxigenic and 54 nontoxigenic) strains examined, previously identified by both conventional biochemical methods and API Coryne System. Conversely, DNase test results were negative in 93·9% of the 564 nondiphtherial Gram‐positive rod clinical strains. Conclusions: The DNase test emerged as an easily interpretable and cost‐effective alternative screening procedure for C. diphtheriae laboratory identification. Significance and Impact of the Study: The method should facilitate routine laboratory diagnosis of toxigenic and nontoxigenic C. diphtheriae.     

A novel population health approach: Using fish retinoblastoma gene profiles as a surrogate for humans

Retinoblastoma, a tumor suppressor gene, is frequently mutated in diverse types of human tumors. We have previously shown that two types of fish tumor, eye and liver, also possess mutant Rb genes. Our aim is to determine if the Rb allele status is linked to environmentally-induced cancer and whether this information in fish can be used to predict future phenotype. This is a proof-of-concept investigation to elucidate if fish may act as surrogates in assessing pollution-induced tumor incidence and inform regulatory authorities of potential long-term population health consequences. Marine flatfish, Limanda limanda, that display either normal liver histopathology, liver adenoma or liver hepatocellular carcinoma were analysed for the presence of Rb gene alterations. Several Rb alterations were detected in the fish displaying adenoma and carcinoma, and not in the surrounding normal tissue from the same individuals. The profile is similar to that reported in humans in that they spread across the gene, particularly exons 8-23, and a functionally important region of the protein. This Rb allele data was then used to build statistical classifier sets, linking Rb status with tumor pathology. Further flatfish caught from coastal-water areas of differing contaminant burden around the UK were subsequently analysed for the presence of Rb alterations. Using novel pattern matching statistics of the classifier sets compared with the coastal samples, the coastal fish were considered more similar to the characterised disease phenotype than the normal phenotype. Preliminary data suggests that using a statistical approach, based on classifying sets of histopathologically-defined tumor states, makes it possible to predict the phenotype of wild fish based on the status of the Rb allele. Since the Rb gene is orthologous, fish populations could act as surrogates for human populations in an eco-epidemiological investigation of the combined roles of genetics and environmental exposures in the tumorigenesis process.