Intraspecific variability modulates interspecific variability in animal organismal stoichiometry

Interspecific differences in organismal stoichiometry (OS) have been documented in a wide range of animal taxa and are of significant interest for understanding evolutionary patterns in OS. In contrast, intraspecific variation in animal OS has generally been treated as analytical noise or random variation, even though available data suggest intraspecific variability in OS is widespread. Here, we assess how intraspecific variation in OS affects inferences about interspecific OS differences using two co‐occurring Neotropical fishes: Poecilia reticulata and Rivulus hartii. A wide range of OS has been observed within both species and has been attributed to environmental differences among stream systems. We assess the contributions of species identity, stream system, and the interactions between stream and species to variability in N:P, C:P, and C:N. Because predation pressure can impact the foraging ecology and life‐history traits of fishes, we compare predictors of OS between communities that include predators, and communities where predators are absent. We find that species identity is the strongest predictor of N:P, while stream or the interaction of stream and species contribute more to the overall variation in C:P and C:N. Interspecific differences in N:P, C:P, and C:N are therefore not consistent among streams. The relative contribution of stream or species to OS qualitatively changes between the two predation communities, but these differences do not have appreciable effects in interspecific patterns. We conclude that although species identity is a significant predictor of OS, intraspecific OS is sometimes sufficient to overwhelm or obfuscate interspecific differences in OS.     

Increased brain signal variability accompanies lower behavioral variability in development

As the brain matures, its responses become optimized. Behavioral measures show this through improved accuracy and decreased trial-to-trial variability. The question remains whether the supporting brain dynamics show a similar decrease in variability. We examined the relation between variability in single trial evoked electrical activity of the brain (measured with EEG) and performance of a face memory task in children (8–15 y) and young adults (20–33 y). Behaviorally, children showed slower, more variable response times (RT), and less accurate recognition than adults. However, brain signal variability increased with age, and showed strong negative correlations with intrasubject RT variability and positive correlations with accuracy. Thus, maturation appears to lead to a brain with greater functional variability, which is indicative of enhanced neural complexity. This variability may reflect a broader repertoire of metastable brain states and more fluid transitions among them that enable optimum responses. Our results suggest that the moment-to-moment variability in brain activity may be a critical index of the cognitive capacity of the brain.     

Control of variability

Genetic variability is an important component of the phenotypic variation within populations; however, there are often many other contributing factors, which receive little attention. Randomization techniques or grouping factors known to contribute to variability can do much to isolate, or at least accommodate, this variability. The European Centre for the Validation of Alternative Methods addressed some of these approaches in 1998, and others are considered in this article. However, laboratory animals are living beings that respond to scientific procedures, or indeed to subtle variations in husbandry conditions, which our senses do not equip us to comprehend readily. These variations may either bias our experimental results or introduce sufficient background noise to mask differences arising from the scientific procedures. In planning an experiment, it is important to devote adequate time considering such factors and developing appropriate strategies to handle them.     

Self-similarity in variability of human heart variability at various stages of ontogenesis

We consider the potential of applying wavelet analysis to fluctuations found in physiological systems. We focus on cardiac interbeat interval time series (RR-intervals) from a group of young adults and children and fetus heart beat rate time series (antepartum cardiotocography), because the wavelet analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. We show that all the signals analyzed are self-similar and propose a method for estimating this scaling feature.     

Stress and genetic variability

It was shown by D.K. Belyaev and the coworkers that stress can lead to changes in the degree of manifestation of genetic variation in a number of quantitative traits, such as fertility, growth rate and endocrine functions. The effects of emotional stress on the meiotic process in male mice were established. Stress inhibits both replication and repair of DNA at corresponding stages of meiosis. These are the reasons for an increase in X-Y and autosomal univalent frequency and recombination frequency in the 1-st and 2-nd chromosomes. Thus, stress leads to redistribution of recombination frequencies in the genome and produces the new spectrum of combination variation. The data presented support the concept of D.K. Belyaev that stress has substantial influence on the rate of evolution.     

Intraspecific trait variability matters

Intraspecific trait variability (ITV) plays a central part in various ecological processes, though using mean trait values may be sufficient in some instances. Ecologists need thus to find under which circumstances. Carlucci et al. (2014, this issue) bring new evidence on the importance of ITV for community assembly across a strong gradient. Sampling design may affect ITV quantification across gradients.     

心电波形变异性的研究

与心率变异性作类比,本文提出了心电波形变异性（ECWV）的概念。通过相关系数、KL变换指标、“棋盘”映射等波形指标对心电波形变异性进行了量化研究。本文研究表明,一些ECWV指标能够区分精神负荷和非负荷两种状态。心电波形变异性蕴含了丰富的信息,对它的深入研究有着积极的意义。     

Herpesvirus saimiri strain variability

Herpesvirus saimiri was isolated from 22 squirrel monkeys by cocultivation of peripheral lymphocytes with permissive owl monkey kidney monolayer cells. Comparison of virion DNA fragments produced from restriction endonuclease digestion was used as a sensitive measure of strain variability. Although all isolates contained similarities and common features, 19 of the 22 were readily distinguished. Three of the isolates, however, were indistinguishable and possibly were related epidemiologically. Distinct subtypes of H. saimiri were not evident by these criteria; Peruvian, Colombian, Guyanan, and Bolivian squirrel monkeys yielded isolates without characteristic features peculiar to the geographic region. Three of three colony-born squirrel monkeys that were tested yielded a strain of virus distinct from that obtained from the mother. In separate experiments, two of three animals chosen at random yielded a strain of virus different from that originally obtained 16 and 22 months previously; only one of the three animals examined yielded the same strain of virus 22 months after the original isolation. The degree of restriction endonuclease fragment variability among H. saimiri strains appeared to be greater than previously observed for other herpesviruses.     

Determinants of expression variability

The amount of tissue-specific expression variability (EV) across individuals is an essential characteristic of a gene and believed to have evolved, in part, under functional constraints. However, the determinants and functional implications of EV are only beginning to be investigated. Our analyses based on multiple expression profiles in 41 primary human tissues show that a gene’s EV is significantly correlated with a number of features pertaining to the genomic, epigenomic, regulatory, polymorphic, functional, structural and network characteristics of the gene. We found that (i) EV of a gene is encoded, in part, by its genomic context and is further influenced by the epigenome; (ii) strong promoters induce less variable expression; (iii) less variable gene loci evolve under purifying selection against copy number polymorphisms; (iv) genes that encode inherently disordered or highly interacting proteins exhibit lower variability; and (v) genes with less variable expression are enriched for house-keeping functions, while genes with highly variable expression tend to function in development and extra-cellular response and are associated with human diseases. Thus, our analysis reveals a number of potential mediators as well as functional and evolutionary correlates of EV, and provides new insights into the inherent variability in eukaryotic gene expression.     

Heart rate variability analysis

The expansion of heart rate variability analysis has been facilitated by the remarkable development of computer sciences and digital signal processing during the last thirty years. The beat-to-beat fluctuation of the heart rate originates from the momentary summing of sympathetic and parasympathetic influences on the sinus node. According to the extensive associations of the autonomic nervous system, several factors affect heart rate and its variability such as posture, respiration frequency, age, gender, physical or mental load, pain, numerous disease conditions, and different drugs. Heart rate variability can be quantitatively measured by time domain and frequency domain methods that are detailed in the paper. Non-linear methods have not spread in the clinical practice yet. Various cardiovascular and other pathologies as well as different forms of mental and physical load are associated with altered heart rate variability offering the possibility of predicting disease outcome and assessing stress.