Using principal component analysis and support vector machine to predict protein structural class for low-similarity sequences via PSSM

The accurate identification of protein structure class solely using extracted information from protein sequence is a complicated task in the current computational biology. Prediction of protein structural class for low-similarity sequences remains a challenging problem. In this study, the new computational method has been developed to predict protein structural class by fusing the sequence information and evolution information to represent a protein sample. To evaluate the performance of the proposed method, jackknife cross-validation tests are performed on two widely used benchmark data-sets, 1189 and 25PDB with sequence similarity lower than 40 and 25%, respectively. Comparison of our results with other methods shows that the proposed method by us is very promising and may provide a cost-effective alternative to predict protein structural class in particular for low-similarity data-sets.     

Population-response model for vibrotactile spatial summation

A computational model based on previous physiological and psychophysical data is presented for the human Pacinian (P) psychophysical channel. The model can predict the probability of detection in simple psychophysical tasks, and hence psychometric functions and thresholds. The model simulates stimulating variable and fixed glabrous skin sites with different-sized contactors and includes spatial variation of monkey P-fiber sensitivities. Therefore, it is especially suitable for studying spatial summation, i.e. the improvement of threshold with increasing contactor area. Selective contributions of neural integration (n.i.) and probability summation (p.s.) are also incorporated into the model. Model predictions are compared to psychophysical results of Gescheider et al. (). The performance of the model regarding the effects of contactor size is very good. In addition to predicting approximately 3?dB improvement of thresholds when the contactor area is doubled, the model also reveals nonlinear contributions of p.s. and n.i. Furthermore, the model asserts that thresholds are largely governed by neural integration when small contactors are used. These and other findings discussed in the article show that the presented model is a helpful tool for formulating testable hypotheses. Although the model can also simulate some temporal summation effects, simulation results do not conform well to previous data on temporal response properties. Thus, the model needs to be refined in that respect.     

Distribution of duck broods relative to habitat characteristics in the Prairie Pothole Region

Conservation programs for breeding ducks in the Prairie Pothole Region (PPR) of the United States and Canada require effective means of evaluating and characterizing breeding habitat across large landscapes. Extensive surveys of the distribution of duck broods in late-summer could help identify wetland basins with greater probabilities of occupancy. Broods are difficult to detect, however, rendering presence–absence data from single-visit surveys difficult to interpret, particularly when probability of detection is related to habitat features. Multiple-visit occupancy surveys offer a potential solution. From 20 July to 5 August 2007–2009, we conducted a 3-visit survey of wetland basins located on 167 10.4-km² study plots in the PPR. Our survey focused on broods of the 5 most common breeding duck species (Anas spp.). Our main objectives were to investigate ecological relationships between occupancy of wetland basins by broods and habitat characteristics and to examine if habitat-specific detection was of enough concern to warrant multi-survey approaches in the future. We surveyed 3,226 wetland basins during the study. Probability of occupancy of a wetland basin by a brood was positively related to the log of wet area for all 5 study species and was greater on wetlands located on plots with a greater proportion of herbaceous perennial cover for 4 of 5 species. For example, the median probability of occupancy for gadwall (Anas strepera) increased from 0.08 (90% Credible Interval [CrI]: 0.07, 0.10) to 0.28 (90% CrI: 0.23, 0.33) as wet area increased from 0.19 ha to 2.12 ha, and increased from 0.12 (90% CrI: 0.09, 0.16) to 0.20 (90% CrI: 0.16, 0.25) as proportion of perennial grass cover on the study plot increased from 0.03 to 0.99. Because occupancy and detection were both related to attributes of wetland basins, we concluded that the multiple-visit survey was a useful approach for identifying habitat relationships of duck broods. Our results indicated that most broods of the study species were found in 10.4-km² landscapes with greater densities of small- to mid-sized wetland basins and a greater proportion of herbaceous perennial vegetation. Our study provided new empirical support that could be used to help target conservation actions to the most productive landscapes for breeding ducks. © 2012 The Wildlife Society.     

A method for the quantification of bacterial protein in the presence of Jarosite

A variation on Peterson's modification of the Lowry method for microbial protein determination was developed in which 10% (w/v) oxalic acid was used to remove jarosite. This allowed the quantification of Thiobacillus ferrooxidans entrapped in solid jarosite or in aqueous suspensions containing jarosite. The quantity of protein measured was not affected by the amount of jarosite in the culture, the concentration of oxalic acid, or the time of exposure (up to 72 h) of the sample to oxalic acid. An application of this method was demonstrated in the quantification of biomass immobilized in jarosite on the surface of polystyrene beads in an inverse fluidized bed bioreactor used for the rapid microbial oxidation of ferrous iron.     

Discovery of aryl ureas and aryl amides as potent and selective histamine H3 receptor antagonists for the treatment of obesity (Part I)

A series of structurally novel aryl ureas was derived from optimization of the HTS lead as selective histamine H₃ receptor (H₃R) antagonists. The SAR was explored and the data obtained set up the starting point and foundation for further optimization. The most potent tool compounds, as exemplified by compounds 2l, 5b, 5d, and 5e, displayed antagonism potencies in the subnanomolar range in in vitro human-H₃R FLIPR assays and rhesus monkey H₃R binding assays.     

Spatial summation in the tactile sensory system: Probability summation and neural integration

Psychophysical thresholds for the detection of a 300-Hz burst of vibration applied to the thenar eminence were measured for stimuli applied to the skin through 1.5?cm² and through 0.05?cm² contactors. Thresholds were approximately 13?dB lower when the area of the contactor was 1.5?cm² than when it was 0.05?cm². The difference between the thresholds measured with the large and small contactors was significantly reduced when only the lowest thresholds obtained in the testing sessions were considered. This result supports the hypothesis that one component of spatial summation in the P channel is probability summation. In addition, threshold measurements within a session were less variable when measured with the 1.5?cm² contactor. We conclude that spatial summation in the P channel is a joint function of two processes that occur as the areal extent of the stimulus increases: probability summation in which the probability of exceeding the psychophysical detection threshold increases as the number of receptors of varying sensitivities increases, and neural integration in which neural activity originating from separate receptors is combined within the central nervous system rendering the channel more sensitive to the stimulus.     

A framework for estimating the sensitivity of eDNA surveys

Imperfect sensitivity, or imperfect detection, is a feature of all survey methods that needs to be accounted for when interpreting survey results. Detection of environmental DNA (eDNA) is increasingly being used to infer species distributions, yet the sensitivity of the technique has not been fully evaluated. Sensitivity, or the probability of detecting target DNA given it is present at a site, will depend on both the survey method and the concentration and dispersion of target DNA molecules at a site. We present a model to estimate target DNA concentration and dispersion at survey sites and to estimate the sensitivity of an eDNA survey method. We fitted this model to data from a species‐specific eDNA survey for Oriental weatherloach, Misgurnus anguillicaudatus, at three sites sampled in both autumn and spring. The concentration of target DNA molecules was similar at all three sites in autumn but much higher at two sites in spring. Our analysis showed the survey method had ≥95% sensitivity at sites where target DNA concentrations were ≥11 molecules per litre. We show how these data can be used to compare sampling schemes that differ in the number of field samples collected per site and number of PCR replicates per sample to achieve ≥95% sensitivity at a given target DNA concentration. These models allow researchers to quantify the sensitivity of eDNA survey methods to optimize the probability of detecting target species, and to compare DNA concentrations spatially and temporarily.     

The effects of demographic stochasticity and parameter uncertainty on predicting the establishment of introduced species

Invasive species are a serious threat to biodiversity worldwide and predicting whether an introduced species will first establish and then become invasive can be useful to preserve ecosystem services. Establishment is influenced by multiple factors, such as the interactions between the introduced individuals and the resident community, and demographic and environmental stochasticity. Field observations are often incomplete or biased. This, together with an imperfect knowledge of the ecological traits of the introduced species, makes the prediction of establishment challenging. Methods that consider the combined effects of these factors on our ability to predict the establishment of an introduced species are currently lacking. We develop an inference framework to assess the combined effects of demographic stochasticity and parameter uncertainty on our ability to predict the probability of establishment following the introduction of a small number of individuals. We find that even moderate levels of demographic stochasticity influence both the probability of establishment, and, crucially, our ability to correctly predict that probability. We also find that estimation of the demographic parameters of an introduced species is fundamental to obtain precise estimates of the interaction parameters. For typical values of demographic stochasticity, the drop in our ability to predict an establishment can be 30% when having priors on the demographic parameters compared to having their accurate values. The results from our study illustrate how demographic stochasticity may bias the prediction of the probability of establishment. Our method can be applied to estimate probability of establishment of introduced species in field scenarios, where time series data and prior information on the demographic traits of the introduced species are available.     

Estimating Neospora caninum prevalence in wildlife populations using Bayesian inference

Prevalence of disease in wildlife populations, which is necessary for developing disease models and conducting epidemiologic analyses, is often understudied. Laboratory tests used to screen for diseases in wildlife populations often are validated only for domestic animals. Consequently, the use of these tests for wildlife populations may lead to inaccurate estimates of disease prevalence. We demonstrate the use of Bayesian latent class analysis (LCA) in determining the specificity and sensitivity of a competitive enzyme‐linked immunosorbent assay (cELISA; VMRD^®, Inc.) serologic test used to identify exposure to Neospora caninum (hereafter N. caninum) in three wildlife populations in southeastern Ohio, USA. True prevalence of N. caninum exposure in these populations was estimated to range from 0.1% to 3.1% in American bison (Bison bison), 51.0% to 53.8% in Père David's deer (Elaphurus davidianus), and 40.0% to 45.9% in white‐tailed deer (Odocoileus virginianus). The accuracy of the cELISA in American bison and Père David's deer was estimated to be close to the 96% sensitivity and 99% specificity reported by the manufacturer. Sensitivity in white‐tailed deer, however, ranged from 78.9% to 99.9%. Apparent prevalence of N. caninum from the test results is not equal to the true prevalence in white‐tailed deer and Père David's deer populations. Even when these species inhabit the same community, the true prevalence in the two deer populations differed from the true prevalence in the American bison population. Variances in prevalence for some species suggest differences in the epidemiology of N. caninum for these colocated populations. Bayesian LCA methods could be used as in this example to overcome some of the constraints on validating tests in wildlife species. The ability to accurately evaluate disease status and prevalence in a population improves our understanding of the epidemiology of multihost pathogen systems at the community level.