Limited influence of local and landscape factors on finescale gene flow in two pond‐breeding amphibians

Dispersal and gene flow within animal populations are influenced by the composition and configuration of the landscape. In this study, we evaluated hypotheses about the impact of natural and anthropogenic factors on genetic differentiation in two amphibian species, the spotted salamander (Ambystoma maculatum) and the wood frog (Lithobates sylvaticus) in a commercial forest in central Maine. We conducted this analysis at two scales: a local level, focused on factors measured at each breeding pond, and a landscape level, focused on factors measured between ponds. We investigated the effects of a number of environmental factors in six categories including Productivity, Physical, Land Composition, Land Configuration, Isolation and Location. Embryos were sampled from 56 spotted salamander breeding ponds and 39 wood frog breeding ponds. We used a hierarchical Bayesian approach in the program GESTE at each breeding pond and a random forest algorithm in conjunction with a network analysis between the ponds. We found overall high genetic connectivity across distances up to 17 km for both species and a limited effect of natural and anthropogenic factors on gene flow. We found the null models best explained patterns of genetic differentiation at a local level and found several factors at the landscape level that weakly influenced gene flow. This research indicates multiscale investigations that incorporate local and landscape factors are valuable for understanding patterns of gene flow. Our findings suggest that dispersal rates in this system are high enough to minimize genetic structuring and that current forestry practices do not significantly impede dispersal.     

Accounting for dispersal and biotic interactions to disentangle the drivers of species distributions and their abundances

Although abiotic factors, together with dispersal and biotic interactions, are often suggested to explain the distribution of species and their abundances, species distribution models usually focus on abiotic factors only. We propose an integrative framework linking ecological theory, empirical data and statistical models to understand the distribution of species and their abundances together with the underlying community assembly dynamics. We illustrate our approach with 21 plant species in the French Alps. We show that a spatially nested modelling framework significantly improves the model's performance and that the spatial variations of species presence-absence and abundances are predominantly explained by different factors. We also show that incorporating abiotic, dispersal and biotic factors into the same model bring new insights to our understanding of community assembly. This approach, at the crossroads between community ecology and biogeography, is a promising avenue for a better understanding of species co-existence and biodiversity distribution.     

Aminoglycosides and other factors promoting stop codon readthrough in human cells

Enhanced stop codon readthrough is a potential treatment strategy for diseases caused by nonsense mutations. Here, we compare readthrough levels induced by three types of factors: aminoglycoside antibiotics, suppressor tRNAs, and factors decreasing translation termination efficiency. We show that the highest levels of readthrough were obtained by prolonged treatment with aminoglycosides and suppressor tRNAs, whereas prolonged depletion of release factors induced only a moderate increase in readthrough. We discuss the benefits and inconvenients of the three types of factors for their use in the therapy of diseases caused by premature stop codons.     

Understanding Confounding Effects in Linguistic Coordination: An Information-Theoretic Approach

We suggest an information-theoretic approach for measuring stylistic coordination in dialogues. The proposed measure has a simple predictive interpretation and can account for various confounding factors through proper conditioning. We revisit some of the previous studies that reported strong signatures of stylistic accommodation, and find that a significant part of the observed coordination can be attributed to a simple confounding effect—length coordination. Specifically, longer utterances tend to be followed by longer responses, which gives rise to spurious correlations in the other stylistic features. We propose a test to distinguish correlations in length due to contextual factors (topic of conversation, user verbosity, etc.) and turn-by-turn coordination. We also suggest a test to identify whether stylistic coordination persists even after accounting for length coordination and contextual factors.     

A statistical model for iTRAQ data analysis

We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change. We demonstrate the model's utility based on an analysis of iTRAQ data derived from a spike-in study.     

Scale-dependence in species-area relationships

Species-area relationships (SARs) are among the most studied phenomena in ecology, and are important both to our basic understanding of biodiversity and to improving our ability to conserve it. But despite many advances to date, our knowledge of how various factors contribute to SARs is limited, searches for single causal factors are often inconclusive, and true predictive power remains elusive. We believe that progress in these areas has been impeded by 1) an emphasis on single-factor approaches and thinking of factors underlying SARs as mutually exclusive hypotheses rather than potentially interacting processes, and 2) failure to place SAR-generating factors in a scale-dependent framework. We here review mathematical, ecological, and evolutionary factors contributing to species-area relationships, synthesizing major hypotheses from the literature in a scale-dependent context. We then highlight new research directions and unanswered questions raised by this scale-dependent synthesis.     

Inhibition of HIV-1 replication with stable RNAi-mediated knockdown of autophagy factors

Autophagy is a cellular process leading to the degradation of cytoplasmic components such as organelles and intracellular pathogens. It has been shown that HIV-1 relies on several components of the autophagy pathway for its replication, but the virus also blocks late steps of autophagy to prevent its degradation. We generated stable knockdown T cell lines for 12 autophagy factors and analyzed the impact on HIV-1 replication. RNAi-mediated knockdown of 5 autophagy factors resulted in inhibition of HIV-1 replication. Autophagy analysis confirmed a specific defect in the autophagy pathway for 4 of these 5 factors. We also scored the impact on cell viability, but no gross effects were observed. Upon simultaneous knockdown of 2 autophagy factors (Atg16 and Atg5), an additive inhibitory effect was scored on HIV-1 replication. Stable knockdown of several autophagy factors inhibit HIV-1 replication without any apparent cytotoxicity. We therefore propose that targeting of the autophagy pathway can be a novel therapeutic approach against HIV-1.     

A Multiscale Approach to the Migration of Cancer Stem Cells: Mathematical Modelling and Simulations

We propose a multiscale model for the invasion of the extracellular matrix by two types of cancer cells, the differentiated cancer cells and the cancer stem cells. We investigate the epithelial mesenchymal-like transition between them being driven primarily by the epidermal growth factors. We moreover take into account the transdifferentiation program of the cancer stem cells towards the cancer-associated fibroblast cells as well as the fibroblast-driven remodelling of the extracellular matrix. The proposed haptotaxis model combines the macroscopic phenomenon of the invasion of the extracellular matrix by both types of cancer cells with the microscopic dynamics of the epidermal growth factors. We analyse our model in a component-wise manner and compare our findings with the literature. We investigate pathological situations regarding the epidermal growth factors and accordingly propose “mathematical-treatment” scenarios to control the aggressiveness of the tumour.     

在生理学研究中如何正确把握试验设计三要素

目的：为从事生理学研究的科研工作者制订科学完善的试验设计方案提供一些有效的技术方法。方法：通过正面阐述三要素和正确把握每个要素的关键点;再通过分析已发表的学术论文中未妥善把握三要素的案例,为生理学研究工作者在制订课题设计方案时能正确把握三要素提供具有可操作性的方法。结果：呈现出试验设计三要素的具体内容,即"受试对象"、"影响因素"和"试验效应",并且,为如何正确把握每个要素提供具体措施。结论：试验设计的三要素是从事试验研究的"物质基础",正确把握它们是制订出科学完善试验设计方案的重要环节之一。     

Detecting the influence of climatic variables on species distributions: a test using GIS niche-based models along a steep longitudinal environmental gradient

Aim  To investigate the influence of climate variables in shaping species distributions across a steep longitudinal environmental gradient.
Location  The state of Oklahoma, south-central United States.
Methods  We used Geographical Information Systems (GIS) niche-based models to predict the geographic distributions of six pairs of closely related amphibian and reptile species across a steep longitudinal environmental gradient. We compared results from modelling with actual distributions to determine whether species distributions were primarily limited by environmental factors, and to assess the potential roles of competition and historical factors in influencing distributions.
Results  For all species pairs, GIS models predicted an overlap zone in which both species should occur, although in reality in some cases this area was occupied by only one of the species. We found that environmental factors clearly influence the distributions of most species pairs. We also found evidence suggesting that competition and evolutionary history play a role in determining the distributions of some species pairs.
Main conclusions  Niche-based GIS modelling is a useful tool for investigating species distribution patterns and the factors affecting them. Our results showed that environmental factors strongly influenced species distributions, and that competition and historical factors may also be involved in some cases. Furthermore, results suggested additional lines of research, such as ecological comparisons among populations occurring inside and outside predicted overlap zones, which may provide more direct insight into the roles of competitive interactions and historical factors in shaping species distributions.     

Extrinsic versus intrinsic factors in the decline and extinction of Australian marsupials

Recent attempts to explain the susceptibility of vertebrates to declines worldwide have largely focused on intrinsic factors such as body size, reproductive potential, ecological specialization, geographical range and phylogenetic longevity. Here, we use a database of 145 Australian marsupial species to test the effects of both intrinsic and extrinsic factors in a multivariate comparative approach. We model five intrinsic (body size, habitat specialization, diet, reproductive rate and range size) and four extrinsic (climate and range overlap with introduced foxes, sheep and rabbits) factors. We use quantitative measures of geographical range contraction as indices of decline. We also develop a new modelling approach of phylogenetically independent contrasts combined with imputation of missing values to deal simultaneously with phylogenetic structuring and missing data. One extrinsic variable-geographical range overlap with sheep-was the only consistent predictor of declines. Habitat specialization was independently but less consistently associated with declines. This suggests that extrinsic factors largely determine interspecific variation in extinction risk among Australian marsupials, and that the intrinsic factors that are consistently associated with extinction risk in other vertebrates are less important in this group. We conclude that recent anthropogenic changes have been profound enough to affect species on a continent-wide scale, regardless of their intrinsic biology.     

Relative contributions of offspring quality and environmental quality to adult field performance

Determinants of adult performance, such as growth and survival, are influenced by extrinsic, environmental and intrinsic, phenotypic factors. The relative importance of extrinsic and intrinsic factors, while ecologically relevant, is rarely estimated simultaneously. We estimate the relative contributions of offspring size (intrinsic) and various environmental factors (extrinsic) on adult performance in the marine colonial bryozoan Watersipora subtorquata. We used a variance partitioning approach for both new and previously published data, enabling us to examine the performance of over 1000 individuals in the field. We found offspring size to explain relatively little variation in adult performance. Of the environmental factors taken to account, temporal variation and an environmental gradient had the strongest influences.     

Analysis of Covariance Models for Data From Observational Field Studies

Abstract We outline the features of a general class of statistical models (i.e., analysis of covariance [ANCOVA] models) that has proven to be effective for the analysis of data from observational studies. In observational studies, treatments are assigned by Nature in a decidedly nonrandom manner; consequently, many of the crucial assumptions and safeguards of the classic experimental design either fail or are absent. Hence, inferences (causal or associative) are more difficult to justify. Typically, investigators can expect the primary factors of interest, which are usually called environmental exposures rather than treatments, to be involved in complex interactions with each other and with other factors, and these factors will be confounded with still other factors. We provide examples illustrating the application of ANCOVA models to adjust for confounding factors and complex interactions, thereby providing relatively clean estimates of association between exposure and response. We summarize information on available software and supporting literature for implementing ANCOVA models for the analysis of cross-sectional and longitudinal observational field data. We conclude with a brief discussion of critical model fitting issues, including proper specification of the functional form of continuous covariates and problems associated with overfitted models and misspecified models that lack important covariates.