Using demographic data to better interpret pitfall trap catches

The results of pitfall trapping are often interpreted as abundance in a particular habitat. At the same time, there are numerous cases of almost unrealistically high catches of ground beetles in seemingly unsuitable sites. The correlation of catches by pitfall trapping with the true distribution and abundance of Carabidae needs corroboration. During a full year survey in 2006/07 in the Lake Elton region (Volgograd Area, Russia), 175 species of ground beetles were trapped. Considering the differences in demographic structure of the local populations, and not their abundances, three groups of species were recognized: residents, migrants and sporadic. In residents, the demographic structure of local populations is complete, and their habitats can be considered "residential". In migrants and sporadic species, the demographic structure of the local populations is incomplete, and their habitats can be considered "transit". Residents interact both with their prey and with each other in a particular habitat. Sporadic species are hardly important to a carabid community because of their low abundances. The contribution of migrants to the structure of carabid communities is not apparent and requires additional research. Migrants and sporadic species represent a "labile" component in ground beetles communities, as opposed to a "stable" component, represented by residents. The variability of the labile component substantially limits our interpretation of species diversity in carabid communities. Thus, the criteria for determining the most abundant, or dominant species inevitably vary because the abundance of migrants in some cases can be one order of magnitude higher than that of residents. The results of pitfall trapping adequately reflect the state of carabid communities only in zonal habitats, while azonal and disturbed habitats are merely transit ones for many species of ground beetles. A study of the demographic structure of local populations and assessment of the migratory/residential status of particular carabid species are potential ways of increasing the reliability of pitfall trap information.     

Accelerated search for biomolecular network models to interpret high-throughput experimental data

Background  

The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein expression. Models of biomolecular network structure and dynamics can be inferred from high-throughput measurements of gene and protein expression. We build on our previously developed fuzzy logic method for bridging quantitative and qualitative biological data to address the challenges of noisy, low resolution high-throughput measurements, i.e., from gene expression microarrays. We employ an evolutionary search algorithm to accelerate the search for hypothetical fuzzy biomolecular network models consistent with a biological data set. We also develop a method to estimate the probability of a potential network model fitting a set of data by chance. The resulting metric provides an estimate of both model quality and dataset quality, identifying data that are too noisy to identify meaningful correlations between the measured variables.     

Use of data from bacteria to interpret data on DNA damage processing in mammalian cells

The most important reason for determining the changes in base sequence in the processing of DNA damage is to determine mechanisms. Currently, much more is known about these mechanisms in prokaryotes, partly because the experiments are easier and quicker to do in bacteria, and partly because of the wealth of well characterized bacterial mutants deficient in various DNA repair pathways. This paper summarizes some information on the mechanisms in bacteria that are involved in the induction by various agents of base change mutations, 1- and 2-base deletions or additions that cause frameshifts, and more complicated insertions and deletions that involve up to tens of base pairs. For gross DNA rearrangements such as large deletions involving hundreds or thousands of base pairs, there is actually more information available in mammalian cells than in bacterial cells. It is suggested that deletions of several kilobases or more in bacteria are not easy to detect because they have a high probability of deleting both the gene under study and an adjacent essential gene, forming a nonviable cell. In mammalian cells, the large size (30-40-kb pairs) of the average gene, including both introns and exons, means that a large deletion is more likely to be confined to a single gene and less likely to lead to a nonviable cell.     

Inquiry-based laboratory course improves students' ability to design experiments and interpret data

We redesigned our intermediate-level organismal physiology laboratory course to center on student-designed experiments in plant and human physiology. Our primary goals were to improve the ability of students to design experiments and analyze data. We assessed these abilities at the beginning and end of the semester by giving students an evaluation tool consisting of an experimental scenario, data, and four questions of increasing complexity. To control for nontreatment influences, the improvement scores (final minus initial score for each question) of students taking both the laboratory and the companion lecture course were compared with those of students taking the lecture course only. The laboratory + lecture group improved more than the lecture-only group for the most challenging question. This evidence suggests that our inquiry-based curriculum is achieving its primary goals. The evaluation tool that we developed may be useful to others interested in measuring experimental analysis abilities in their students.     

Combining Drosophila melanogaster somatic-mutation-recombination and electron-spin-resonance-spectroscopy data to interpret epidemiologic observations on chromium carcinogenicity

The aim of this study was to investigate the relationship between endothelial dysfunction and low density lipoprotein (LDL) size and susceptibility to oxidation in nephrotic rats with or without deficiency of vitamin E and selenium. Four groups of male Wistar rats were studied: control (C), vitamin E and selenium deficient control (DefC), nephrotic (NS), and vitamin E and selenium deficient NS (DefNS). Nephrotic syndrome was induced by puromycin aminonucleoside. The molar ratio of vitamin E/LDL-cholesterol was significantly lower in DefNS, DefC rats, and NS vs. C rats. In comparison with control animals, vasodilation and LDL oxidability were significantly lower in nephrotic animals. LDL size was similar in all groups. Abnormal endothelial function in response to acetylcholine and carbachol was observed in NS animals compared to control rats. Relaxation response was inversely associated with an increase in LDL susceptibility to oxidation and with a lower molar ratio of vitamin E/LDL-c. LDL oxidability and LDL-c were the only variables independently associated with vasodilation. These results suggest that endothelial dysfunction of NS may be a consequence of the increased LDL susceptibility to oxidation, secondary to antioxidant deficiency.     

Use of keyword hierarchies to interpret gene expression patterns

MOTIVATION: High-density microarray technology permits the quantitative and simultaneous monitoring of thousands of genes. The interpretation challenge is to extract relevant information from this large amount of data. A growing variety of statistical analysis approaches are available to identify clusters of genes that share common expression characteristics, but provide no information regarding the biological similarities of genes within clusters. The published literature provides a potential source of information to assist in interpretation of clustering results. RESULTS: We describe a data mining method that uses indexing terms ('keywords') from the published literature linked to specific genes to present a view of the conceptual similarity of genes within a cluster or group of interest. The method takes advantage of the hierarchical nature of Medical Subject Headings used to index citations in the MEDLINE database, and the registry numbers applied to enzymes.     

Using biplots to interpret gene expression patterns in plants

Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments.     

Intelligent data analysis to interpret major risk factors for diabetic patients with and without ischemic stroke in a small population

This study proposes an intelligent data analysis approach to investigate and interpret the distinctive factors of diabetes mellitus patients with and without ischemic (non-embolic type) stroke in a small population. The database consists of a total of 16 features collected from 44 diabetic patients. Features include age, gender, duration of diabetes, cholesterol, high density lipoprotein, triglyceride levels, neuropathy, nephropathy, retinopathy, peripheral vascular disease, myocardial infarction rate, glucose level, medication and blood pressure. Metric and non-metric features are distinguished. First, the mean and covariance of the data are estimated and the correlated components are observed. Second, major components are extracted by principal component analysis. Finally, as common examples of local and global classification approach, a k-nearest neighbor and a high-degree polynomial classifier such as multilayer perceptron are employed for classification with all the components and major components case. Macrovascular changes emerged as the principal distinctive factors of ischemic-stroke in diabetes mellitus. Microvascular changes were generally ineffective discriminators. Recommendations were made according to the rules of evidence-based medicine. Briefly, this case study, based on a small population, supports theories of stroke in diabetes mellitus patients and also concludes that the use of intelligent data analysis improves personalized preventive intervention.     

Analytical decomposition can help to interpret ankle joint moment-angle relationship

Moment-angle relationship (dynamic joint stiffness)--the relationship between changes in joint moment and changes in joint angle--is useful for demonstrating interaction of kinematics and kinetics during gait. However, the individual contributors of dynamic joint stiffness are not well studied and understood, which has thus far limited its clinical application. In this study, ankle dynamic joint stiffness was analyzed and decomposed into three components in thirty able-bodied children during the stance phase of the gait. To verify the accuracy of the decomposition, the sum of decomposed components was compared to stiffness computed from experimental data, and good to very good agreement was found. Component 1, the term associated with changes in ground reaction force moment, was the dominant contribution to ankle dynamic joint stiffness. Retrospective data from eight children with juvenile idiopathic arthritis and idiopathic toe-walking was examined to explore the potential utility of analytical decomposition in pathological gait. Compared to controls, component 1 was the source of highest deviation in both pathological groups. Specifically, ankle dynamic joint stiffness differences can be further identified via two sub-components of component 1 which are based on magnitudes and rates of change of the ground reaction force and of its moment arm, and differences between the two patient groups and controls were most evident and interpretable here. Findings of the current study indicate that analytical decomposition can help identify the individual contributors to joint stiffness and clarify the sources of differences in patient groups.     

A soft-modeling approach to interpret thermodynamic and conformational transitions of polynucleotides

Multivariate outputs from the experimental monitoring of biochemical processes are usually difficult to interpret applying methods based on a priori chemical models. Curve resolution methods are model-free procedures, generally known as soft-modeling methods, which obtain the concentration profiles and instrumental responses of each individual species involved in a multivariate monitored process without making any kind of external assumption. Of the curve resolution methods available, the alternating least squares (ALS) is proposed here because of its ability to operate on one or on several matrices. Furthermore, ALS allows the introduction of information related to the internal data structure and to the general features of the concentration profiles and instrumental responses through the input of suitable constraints in the iterative resolution procedure. The ALS potential is tested on several data sets coming from the multivariate spectrometric monitoring of polyuridylic (polyU), polycytidylic (polyC), and polyadenylic (polyA) protonation equilibria in dioxane/water 30% (v/v). Information concerning the evolution of the concentration profiles and the spectra of each individual species involved in the acid-base equilibria, the presence and pattern of polyelectrolyte effects, and the presence of conformational transitions associated or not with the proton uptake process is presented.     

Size-structure-based models of forest dynamics to interpret population- and community-level mechanisms

Functional size-structure-based models of forest tree population dynamics present a unifying explanation for population-level patterns and tree community organization. Density-dependent regulation can be explicitly replaced by the effect of size-structure-dependent suppression on demographic processes in functional size-structure models. This suppression effect sufficiently explains various patterns reported for crowded evenaged populations. Further, it stabilizes natural forest populations of overlapping generations at a stationary state with balanced recruitment and mortality. The spatial heterogeneity of light resources created by tree size structure offers an opportunity for multiple species to coexist by means of trade-offs between demographic parameters. The energy correlation of tree species diversity at a geographic scale is also attributable to the architectural feature of forests. Recipient of the Botanical Society Award of Young Scientists, 1992.     

Multi-bead-and-spring model to interpret protein detachment studied by AFM force spectroscopy

This article deals with the detachment of molecules (fibrinogen) from a surface studied experimentally with an atomic force microscope. The detachment (or rupture) forces are measured as a function of the retraction velocity and exhibit a clear dependence on this parameter, even though the interaction between the molecules and the surface are nonspecific. To interpret these data, a mechanical multi-bead-and-spring model is developed. It consists of one to several parallel, "molecular" springs connected to an extra spring representing the cantilever that is moved at constant velocity. The free end of each molecular spring terminates with a particle that interacts with the surface through a Lennard-Jones potential. This Brownian dynamics model is used to analyze the experimental findings. In the framework of this model, it appears that the fibrinogen molecule must be ascribed a stiffness much smaller than that of the cantilever. In addition, several bonds between the molecule and the surface must be taken into account for the range of the molecule-surface interaction not to be unrealistically small. In future work, this model will be extended to more complex mechanisms such as the detachment of cells from a surface.     

Ecologists should not use statistical significance tests to interpret simulation model results

Simulation models are widely used to represent the dynamics of ecological systems. A common question with such models is how changes to a parameter value or functional form in the model alter the results. Some authors have chosen to answer that question using frequentist statistical hypothesis tests (e.g. ANOVA). This is inappropriate for two reasons. First, p‐values are determined by statistical power (i.e. replication), which can be arbitrarily high in a simulation context, producing minuscule p‐values regardless of the effect size. Second, the null hypothesis of no difference between treatments (e.g. parameter values) is known a priori to be false, invalidating the premise of the test. Use of p‐values is troublesome (rather than simply irrelevant) because small p‐values lend a false sense of importance to observed differences. We argue that modelers should abandon this practice and focus on evaluating the magnitude of differences between simulations. Synthesis Researchers analyzing field or lab data often test ecological hypotheses using frequentist statistics (t‐tests, ANOVA, etc.) that focus on p‐values. Field and lab data usually have limited sample sizes, and p‐values are valuable for quantifying the probability of making incorrect inferences in that situation. However, modern ecologists increasingly rely on simulation models to address complex questions, and those who were trained in frequentist statistics often apply the hypothesis‐testing approach inappropriately to their simulation results. Our paper explains why p‐values are not informative for interpreting simulation models, and suggests better ways to evaluate the ecological significance of model results.     

The use of mean pool abundances to interpret 15N tracer experiments

A pulse dilution ¹⁵N technique was used in the field to determine the effect of the ammonium to nitrate ratio in a fertilizer application on the uptake of ammonium and nitrate by ryegrass and on gross rates of mineralization and nitrification. Two experiments were performed, corresponding approximately to the first and second cuts of grass. Where no substantial recent immobilization of inorganic nitrogen had occurred, mineralization was insensitive to the form of nitrogen applied, ranging from 2.1–2.6 kg N ha^-1 d^-1. The immobilization of ammonium increased as the proportion of ammonium in the application increased. In the second experiment there was evidence that high rates of immobilization in the first experiment were associated with high rates of mineralization in the second. The implication was that some nitrogen immobilized in the first experiment was re-mineralized during the second. Whether this was nitrogen taken up, stored in roots and released following defoliation was not clear. Nitrification rates in this soil were low (0.1–0.63 kg N ha^-1 d^-1), and as a result, varying the ratio of ammonium to nitrate applied markedly altered the relative uptake of ammonium and nitrate. In the first experiment, where temperatures were low, preferential uptake of ammonium occurred, but where >90% of the uptake was as ammonium, a reduction in yield and nitrogen uptake was observed. In the second experiment, where temperatures and growth rates were higher, the proportion of ammonium to nitrate taken up had no effect on yield or nitrogen uptake.