A power-law distribution of inter-spike intervals in renal sympathetic nerve activity in salt-sensitive hypertension-induced chronic heart failure

To assess sympathetic variability in chronic heart failure (CHF), we evaluated a distribution of inter-spike intervals (ISIs) in renal sympathetic nerve activity (RSNA) in salt-sensitive hypertension-induced CHF (DSSH-CHF) rats. Dahl salt-sensitive rats were fed an 8% NaCl diet for 9 weeks to induce salt-sensitive hypertension-induced CHF. ISIs in RSNA were obtained from chronically instrumented conscious rats, and counts (frequency) and ranks of ISIs in RSNA were plotted with a histogram. We found that ISIs in RSNA followed a power-law distribution in rats, and the power-law distribution of ISIs for RSNA in DSSH-CHF rats was significantly different from that in normal rats. These results indicated that sympathetic variability may be significantly different between salt-sensitive hypertension-induced CHF and healthy individuals, which suggests that sympathetic variability may be used to predict abnormality of the sympathetic regulatory system.     

A measure of explained variation for event history data

Summary There is no shortage of proposed measures of prognostic value of survival models in the statistical literature. They come under different names, including explained variation, correlation, explained randomness, and information gain, but their goal is common: to define something analogous to the coefficient of determination R² in linear regression. None however have been uniformly accepted, none have been extended to general event history data, including recurrent events, and many cannot incorporate time‐varying effects or covariates. We present here a measure specifically tailored for use with general dynamic event history regression models. The measure is applicable and interpretable in discrete or continuous time; with tied data or otherwise; with time‐varying, time‐fixed, or dynamic covariates; with time‐varying or time‐constant effects; with single or multiple event times; with parametric or semiparametric models; and under general independent censoring/observation. For single‐event survival data with neither censoring nor time dependency it reduces to the concordance index. We give expressions for its population value and the variance of the estimator and explore its use in simulations and applications. A web link to R software is provided.     

A collaborative cytogenetics study to measure and minimize interlaboratory variation

Six cytogenetics laboratories joined in a collaborative study of rat chromosome aberrations to measure interlaboratory variation in results of standardized procedures and to devise methods to minimize interlaboratory differences. A preliminary workshop was held to resolve scoring differences, to develop a joint protocol and common glossary, and to reach agreement on uniform reporting methods. Osborne-Mendel rats from a common source were sent to each laboratory. Triethylenemelamine (TEM) was used at doses of 100, 200, 300 and 400 μg/kg to induce clastogenic effects; results were compared to those of a control group of untreated animals. Femoral bone marrow cells were evaluated with the scorers unaware of the dosage. Final results showed highly significant dose effects with the test compound, and most laboratories showed a similar pattern of dose response. This study illustrates that rat cytogenetic analysis can be an effective test system for evaluation of a compound for mutagenic potential, particularly for the index reflecting the proportion of abnormal cells, but that results should be interpreted cautiously when arbitrary values are assigned for some of the categories being analyzed, as was done in this project for the category of severely damaged cells.     

A continental measure of urbanness predicts avian response to local urbanization

Understanding species-specific relationships with their environment is essential for ecology, biogeography and conservation biology. Moreover, understanding how these relationships change with spatial scale is critical to mitigating potential threats to biodiversity. But methods which measure inter-specific variation in response to environmental parameters that are also generalizable across multiple spatial scales are scarce. We used broad-scale avian citizen science data, over continental Australia, integrated with remotely-sensed products, to produce a measure of urban-tolerance for a given species at a continental-scale. We then compared these urban-tolerances to modelled responses to urbanization at a local-scale, based on systematic sampling within four small cities. For 49 species which had sufficient data for modelling, we found a significant relationship (R² = 0.51) between continental-scale urbanness and local-scale urbanness. We also found that relatively few citizen science observations (~250) are necessary for reliable estimates of continental-scale species-specific urban scores to predict local-scale response to urbanization. Our approach demonstrates the applicability of broad-scale citizen science data, contrasting both the spatial grain and extent of standard point-count surveys generally only conducted at small spatial scales. Continental-scale responses in Australia are representative of small-scale responses to urbanization among four small cities in Australia, suggesting that our method of producing species-specific urban scores is robust and may be generalized to other locations lacking appropriate data.     

A critique of the collaborative cytogenetics study to measure and minimize interlaboratory variation.

A statistical reanalysis was performed on the data fecently reported on a 6-laboratory, collaborative cytogenetic study to measure and minimize interlaboratory variation. Three of the laboratories had mean values significantly different from the others on most of the 6 indexes of chemically-induced aberration; one laboratory with values higher and two with values lower. Furthermore, relative variability of the values around the means was consistently lower in one of the 6 participating laborabories. The results of the reanalysis of this collaborative study demonstrates that significant interlaboratory differences exist and that these should be adjusted or diminished before rat cytogenetic analysis can be an effective test system for evaluation of a compound for mutagenic potential.     

A haplotype method detects diverse scenarios of local adaptation from genomic sequence variation

Identifying genomic targets of population‐specific positive selection is a major goal in several areas of basic and applied biology. However, it is unclear how often such selection should act on new mutations versus standing genetic variation or recurrent mutation, and furthermore, favoured alleles may either become fixed or remain variable in the population. Very few population genetic statistics are sensitive to all of these modes of selection. Here, we introduce and evaluate the Comparative Haplotype Identity statistic (χ_MD), which assesses whether pairwise haplotype sharing at a locus in one population is unusually large compared with another population, relative to genomewide trends. Using simulations that emulate human and Drosophila genetic variation, we find that χ_MD is sensitive to a wide range of selection scenarios, and for some very challenging cases (e.g. partial soft sweeps), it outperforms other two‐population statistics. We also find that, as with F_ST, our haplotype approach has the ability to detect surprisingly ancient selective sweeps. Particularly for the scenarios resembling human variation, we find that χ_MD outperforms other frequency‐ and haplotype‐based statistics for soft and/or partial selective sweeps. Applying χ_MD and other between‐population statistics to published population genomic data from D. melanogaster, we find both shared and unique genes and functional categories identified by each statistic. The broad utility and computational simplicity of χ_MD will make it an especially valuable tool in the search for genes targeted by local adaptation.     

A distance-type measure approach to the analysis of copy number variation in DNA sequencing data

Background

The next generation sequencing technology allows us to obtain a large amount of short DNA sequence (DNA-seq) reads at a genome-wide level. DNA-seq data have been increasingly collected during the recent years. Count-type data analysis is a widely used approach for DNA-seq data. However, the related data pre-processing is based on the moving window method, in which a window size need to be defined in order to obtain count-type data. Furthermore, useful information can be reduced after data pre-processing for count-type data.

Results

In this study, we propose to analyze DNA-seq data based on the related distance-type measure. Distances are measured in base pairs (bps) between two adjacent alignments of short reads mapped to a reference genome. Our experimental data based simulation study confirms the advantages of distance-type measure approach in both detection power and detection accuracy. Furthermore, we propose artificial censoring for the distance data so that distances larger than a given value are considered potential outliers. Our purpose is to simplify the pre-processing of DNA-seq data. Statistically, we consider a mixture of right censored geometric distributions to model the distance data. Additionally, to reduce the GC-content bias, we extend the mixture model to a mixture of generalized linear models (GLMs). The estimation of model can be achieved by the Newton-Raphson algorithm as well as the Expectation-Maximization (E-M) algorithm. We have conducted simulations to evaluate the performance of our approach. Based on the rank based inverse normal transformation of distance data, we can obtain the related z-values for a follow-up analysis. For an illustration, an application to the DNA-seq data from a pair of normal and tumor cell lines is presented with a change-point analysis of z-values to detect DNA copy number alterations.

Conclusion

Our distance-type measure approach is novel. It does not require either a fixed or a sliding window procedure for generating count-type data. Its advantages have been demonstrated by our simulation studies and its practical usefulness has been illustrated by an experimental data application.

     

Inverted central auditory hierarchies for encoding local intervals and global temporal patterns

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Trait dimensionality explains widespread variation in local adaptation

All species are locked in a continual struggle to adapt to local ecological conditions. In cases where species fail to locally adapt, they face reduced population growth rates, or even local extinction. Traditional explanations for limited local adaptation focus on maladaptive gene flow or homogeneous environmental conditions. These classical explanations have, however, failed to explain variation in the magnitude of local adaptation observed across taxa. Here we show that variable levels of local adaptation are better explained by trait dimensionality. First, we develop and analyse mathematical models that predict levels of local adaptation will increase with the number of traits experiencing spatially variable selection. Next, we test this prediction by estimating the relationship between dimensionality and local adaptation using data from 35 published reciprocal transplant studies. This analysis reveals a strong correlation between dimensionality and degree of local adaptation, and thus provides empirical support for the predictions of our model.     

Odontometric variation among local populations of Kenyan olive baboons

This is a first report on a survey of local variations in genetic marker frequencies and morphometric features on Kenyan olive baboons. Data on dental casts of the upper dentitions of 207 baboons (115 males and 92 females) are analyzed with univariate and multivariate techniques. The materials represent 18 troops captured at 4 different localities. In general, levels of variability within and between localities are not great. The most marked variations present are in the premolar teeth. Females show greater variation than males. There are suggestive correlations between morphometric distance and geographic distance (positive) and morphometric distance and altitude difference (negative). There are some differences between this olive baboon sample and that of Swindler, McCoy & Hornbeck (1967) which lies close to a zone of olive-yellow baboon hybridization (Maples, 1972).     

Power-law inter-spike interval distributions infer a conditional maximization of entropy in cortical neurons

The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI), which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously) and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE) solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates) at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains.     

Testing the niche variation hypothesis with a measure of body condition

Individual variation and fitness are cornerstones of evolution by natural selection. The niche variation hypothesis (NVH) posits that when interspecific competition is relaxed, intraspecific competition should drive niche expansion by selection favoring use of novel resources and that among‐individual variation should confer a selective advantage. Population‐level niche expansion could be achieved by all individuals using all available resources, or by each individual using a unique combination of resources, thereby increasing among‐individual dietary niche variation. Although individual variation can lead to species‐level evolutionary and ecological change, observed variation does not ensure a beneficial outcome. We used carbon and nitrogen stable isotope analysis of claw keratin and a Bayesian stable isotope mixing model to estimate the summer (July–September) assimilated diet of individual female black Ursus americanus and brown U. arctos bears. We quantified variation in dietary niche in both populations, and assessed diet relative to percentage body fat. We hypothesized that if the NVH held, percentage body fat would be similar for individuals of the same species across much of the dietary range of observed proportional salmon contributions to individual bear diets. Although we found greater differences in dietary niches between than within species, we observed greater among‐individual dietary variation in the brown bear population. Moreover, we found that within each species individual female bears achieved similar ranges of percentage body fat at various levels of salmon in the diet. Our results provide support for the NVH. Linking individual dietary niches to measures of physiological condition related to fitness can offer new insights into eco‐evolutionary processes related to food resource use.     

Lost letter measure of variation in altruistic behaviour in 20 neighbourhoods

Altruistic behaviour varies across human populations and this variation is likely to be partly explained by variation in the ecological context of the populations. We hypothesise that area level socio-economic characteristics will determine the levels of altruism found in individuals living in an area and we use a lost letter experiment to measure altruism across 20 neighbourhoods with a wide range of income deprivation scores in London, UK. The results show a strong negative effect of neighbourhood income deprivation on altruistic behaviour, with letters dropped in the poorest neighbourhoods having 91% lower odds of being returned than letters dropped in the wealthiest neighbourhoods. We suggest that measures of altruism are strongly context dependant.     

Clustering of gene expression data using a local shape-based similarity measure

MOTIVATION: Microarray technology enables the study of gene expression in large scale. The application of methods for data analysis then allows for grouping genes that show a similar expression profile and that are thus likely to be co-regulated. A relationship among genes at the biological level often presents itself by locally similar and potentially time-shifted patterns in their expression profiles. RESULTS: Here, we propose a new method (CLARITY; Clustering with Local shApe-based similaRITY) for the analysis of microarray time course experiments that uses a local shape-based similarity measure based on Spearman rank correlation. This measure does not require a normalization of the expression data and is comparably robust towards noise. It is also able to detect similar and even time-shifted sub-profiles. To this end, we implemented an approach motivated by the BLAST algorithm for sequence alignment.We used CLARITY to cluster the times series of gene expression data during the mitotic cell cycle of the yeast Saccharomyces cerevisiae. The obtained clusters were related to the MIPS functional classification to assess their biological significance. We found that several clusters were significantly enriched with genes that share similar or related functions.     

Sources of variation in interbirth intervals among captive bonnet macaques (Macaca radiata)

Female fitness is a function of variation in the length of females' reproductive careers, the viability of their offspring, and the frequency with which they give birth. Infant loss shortens interbirth intervals in most primate species, but we know considerably less about other factors that contribute to variation in the length of interbirth intervals within groups. In one large captive group of bonnet macaques, maternal parity, age, experience, family size, and recent reproductive history are all associated with variation in the length of intervals that follow the birth of surviving infants. Primiparous females have the longest interbirth intervals, while multiparous females who have produced surviving infants in the past and have raised their last infant successfully have the shortest interbirth intervals. Infant sex and maternal rank have no direct effect upon the length of interbirth intervals. One of the underlying causes of variation in the length of interbirth intervals after surviving births seems to be variation in the timing of conceptions among females. Females who conceive early in the mating season tend to have shorter interbirth intervals than other females. However, females who are multiparous, experienced, and have recently raised infants have late conceptions and short interbirth intervals.     

Determination of the inter-spike times of neurons receiving randomly arriving post-synaptik potentials

Stein's model for a neuron receiving randomly arriving post-synaptic potentials is studied from an analytic viewpoint, using some recent results in the theory of first passage times for temporally homogeneous Markov processes. The case when the only input is excitatory can be treated exactly. It is shown that the moments of the firing time are guaranteed to be finite so that the differential-difference equation for the expectation (and higher moments) of the time for the membrane potential to first reach threshold from resting level can be written down. Analytic solutions are obtained in a number of cases with main emphasis on the case when the threshold is twice the epsp magnitude. An invariance principie is formulated wherein at a given mean input frequency and for a given decay parameter, the distribution of firing times depends only on the ratio of threshld to epsp magnitude. For the case where this ratio is two, the variation in the mean discharge rate is obtained as a function of mean input frequency. The results are compared with the experimental data for the Poisson monosynaptic excitation of cat motoneurons by Redmanet al. Agreement between theoretical and experimental values is excellent at input frequencies near 102 sec^-1, and theory underestimates the firing rate below that input frequency. Reasons for the discrepancy are discussed at length including the uncertainties in the neuronal parameters and the dependence of epsp magnitude on mean input frequency. The problem of including an inhibitory input process together with excitation is treated by an approximation procedure when the inhibition is considerably weaker than the excitation. At the input frequency investigated it is shown that when inhibition “half as weak” as the excitation occurs, the mean discharge frequency is approximately halved. In the final section a method of estimating neuronal parameters from the moments of the experimental inter-spike time distribution is outlined.