Confidence bands for low-dose risk estimation with quantal response data

We study the use of simultaneous confidence bands for low-dose risk estimation with quantal response data, and derive methods for estimating simultaneous upper confidence limits on predicted extra risk under a multistage model. By inverting the upper bands on extra risk, we obtain simultaneous lower bounds on the benchmark dose (BMD). Monte Carlo evaluations explore characteristics of the simultaneous limits under this setting, and a suite of actual data sets are used to compare existing methods for placing lower limits on the BMD.     

Population genetics and the evolution of geographic range limits in an annual plant

Abstract Theoretical models of species' geographic range limits have identified both demographic and evolutionary mechanisms that prevent range expansion. Stable range limits have been paradoxical for evolutionary biologists because they represent locations where populations chronically fail to respond to selection. Distinguishing among the proposed causes of species' range limits requires insight into both current and historical population dynamics. The tools of molecular population genetics provide a window into the stability of range limits, historical demography, and rates of gene flow. Here we evaluate alternative range limit models using a multilocus data set based on DNA sequences and microsatellites along with field demographic data from the annual plant Clarkia xantiana ssp. xantiana. Our data suggest that central and peripheral populations have very large historical and current effective population sizes and that there is little evidence for population size changes or bottlenecks associated with colonization in peripheral populations. Whereas range limit populations appear to have been stable, central populations exhibit a signature of population expansion and have contributed asymmetrically to the genetic diversity of peripheral populations via migration. Overall, our results discount strictly demographic models of range limits and more strongly support evolutionary genetic models of range limits, where adaptation is prevented by a lack of genetic variation or maladaptive gene flow.     

Grading of laboratories on CD4+ T-lymphocyte evaluations based on acceptable data boundaries defined by the measurement error

BACKGROUND: We addressed the definition of limits of error of %CD4+ and CD4+ counts (AbsCD4+) typical of laboratories of excellence, as well as the grading of laboratories based on the decision to take these limits as boundaries of unacceptable data. METHODS: We studied the 99.9% confidence intervals of the means of 24 human immunodeficiency virus (HIV)+ and HIV- blood samples analyzed by 18 laboratories of the Liguria Region Quality Assessment Program (Liguria Region QALI). Regression equations of lower (L1) and upper (L2) confidence limits over the means of data cleared of unusual results were used to interpolate limits of error for mean values in the tested range. RESULTS: L1 and L2 were symmetric around the mean and a single absolute difference (Abs Res) between the limits and the mean was found. Abs Res significantly increased over mean values (P = 0.0005 for %CD4+, P < 0.0001 for AbsCD4+). Limits were compatible with errors shown with blind replicates. Unacceptable results, outside the limits, accounted for 25% and 30% of %CD4+ and for 18% and 35% AbsCD4+ in the Liguria Region QALI and in the Piemonte Region QA Program, respectively. Limits interpolated over the median showed a similar grading. A comparable fraction of unacceptable data was also found with the method used in the U.K. National External Quality Assessment Scheme (NEQAS) immune monitoring scheme. CONCLUSIONS: We propose the general use of these regression equations to determine bounds for unacceptable data in proficiency testing and to identify laboratories of excellence.     

Evaluating the potential causes of range limits of birds of the Colombian Andes

Aim To evaluate how factors acting at different spatial scales influence range limits in bird species of the Colombian Andes. Location Andes Mountains of Colombia. Methods We used Maxent , a climate envelope model (CEM), and environmental and geographic information to study range‐filling (i.e. the extent to which a species occurs in all the areas in which it is predicted to occur) in 70 range‐restricted bird species of the Colombian Andes. Environmental data were taken from the WorldClim database, and species occurrence data were taken from museum data collated by the BioMap project, an observational database, and the literature. We evaluated how climate and geographic barriers may shape range limits at two scales. Results At a broad extent (i.e. across the three main cordilleras within the Colombian Andes), we find that CEMs predict there to be suitable environmental conditions for particular species in regions where the species is absent, possibly as a result of dispersal limitation or biotic interactions. In contrast, at a finer scale (within a given cordillera), species generally occur across the entire area predicted to be suitable by a given CEM. Geographic discontinuities within cordilleras do not generally correspond to range limits; instead, range limits correspond to changes in environmental conditions. Main conclusions Our results suggest that different mechanisms influence the presence of species at different scales. Dispersal limitation, potentially combined with species interactions, may influence range limits at a broad extent (the entire Colombian Andes), while strong environmental gradients correspond to range limits at a finer scale (within a cordillera).     

Multiplicity-adjusted inferences in risk assessment: benchmark analysis with quantal response data

A primary objective in quantitative risk or safety assessment is characterization of the severity and likelihood of an adverse effect caused by a chemical toxin or pharmaceutical agent. In many cases data are not available at low doses or low exposures to the agent, and inferences at those doses must be based on the high-dose data. A modern method for making low-dose inferences is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this short note, we discuss approaches for doing so with quantal response data.     

Limitation of growth rate by two complementary nutrients: some elementary but neglected considerations

Experimental data in the literature show that the yield of biomass from a particular nutrient when that nutrient limits growth rate is often significantly different than the yield from the nutrient when some complementary nutrient limits growth rate. This article explores some possible consequences for bioreactor dynamics of dependence of yield coefficients on the identity of the nutrient that limits growth rate.     

Structural and Psycho-Social Limits to Climate Change Adaptation in the Great Barrier Reef Region

Adaptation, as a strategy to respond to climate change, has limits: there are conditions under which adaptation strategies fail to alleviate impacts from climate change. Research has primarily focused on identifying absolute bio-physical limits. This paper contributes empirical insight to an emerging literature on the social limits to adaptation. Such limits arise from the ways in which societies perceive, experience and respond to climate change. Using qualitative data from multi-stakeholder workshops and key-informant interviews with representatives of the fisheries and tourism sectors of the Great Barrier Reef region, we identify psycho-social and structural limits associated with key adaptation strategies, and examine how these are perceived as more or less absolute across levels of organisation. We find that actors experience social limits to adaptation when: i) the effort of pursuing a strategy exceeds the benefits of desired adaptation outcomes; ii) the particular strategy does not address the actual source of vulnerability, and; iii) the benefits derived from adaptation are undermined by external factors. We also find that social limits are not necessarily more absolute at higher levels of organisation: respondents perceived considerable opportunities to address some psycho-social limits at the national-international interface, while they considered some social limits at the local and regional levels to be effectively absolute.     

A macroevolutionary perspective on species range limits

Understanding the factors that determine the geographic range limits of species is important for many questions in ecology, evolution and conservation biology. These limits arise from complex interactions among ecology and dispersal ability of species and the physical environment, but many of the underlying traits can be conserved among related species and clades. Thus, the range limits of species are likely to be influenced by their macroevolutionary history. Using palaeontological and biogeographic data for marine bivalves, we find that the range limits of genera are significantly related to their constituent species richness, but the effects of age are weak and inconsistent. In addition, we find a significant phylogenetic signal in the range limits at both genus and family levels, although the strength of this effect shows interoceanic variation. This phylogenetic conservatism of range limits gives rise to an evolutionary pattern where wide-ranging lineages have clusters of species within the biogeographic provinces, with a few extending across major boundaries.     

Computed ABC Analysis for Rational Selection of Most Informative Variables in Multivariate Data

Objective

Multivariate data sets often differ in several factors or derived statistical parameters, which have to be selected for a valid interpretation. Basing this selection on traditional statistical limits leads occasionally to the perception of losing information from a data set. This paper proposes a novel method for calculating precise limits for the selection of parameter sets.

Methods

The algorithm is based on an ABC analysis and calculates these limits on the basis of the mathematical properties of the distribution of the analyzed items. The limits im-plement the aim of any ABC analysis, i.e., comparing the increase in yield to the required additional effort. In particular, the limit for set A, the “important few”, is optimized in a way that both, the effort and the yield for the other sets (B and C), are minimized and the additional gain is optimized.

Results

As a typical example from biomedical research, the feasibility of the ABC analysis as an objective replacement for classical subjective limits to select highly relevant variance components of pain thresholds is presented. The proposed method improved the biological inter-pretation of the results and increased the fraction of valid information that was obtained from the experimental data.

Conclusions

The method is applicable to many further biomedical problems in-cluding the creation of diagnostic complex biomarkers or short screening tests from comprehensive test batteries. Thus, the ABC analysis can be proposed as a mathematically valid replacement for traditional limits to maximize the information obtained from multivariate research data.     

Some Limitations of Public Sequence Data for Phylogenetic Inference (in Plants)

The GenBank database contains essentially all of the nucleotide sequence data generated for published molecular systematic studies, but for the majority of taxa these data remain sparse. GenBank has value for phylogenetic methods that leverage data–mining and rapidly improving computational methods, but the limits imposed by the sparse structure of the data are not well understood. Here we present a tree representing 13,093 land plant genera—an estimated 80% of extant plant diversity—to illustrate the potential of public sequence data for broad phylogenetic inference in plants, and we explore the limits to inference imposed by the structure of these data using theoretical foundations from phylogenetic data decisiveness. We find that despite very high levels of missing data (over 96%), the present data retain the potential to inform over 86.3% of all possible phylogenetic relationships. Most of these relationships, however, are informed by small amounts of data—approximately half are informed by fewer than four loci, and more than 99% are informed by fewer than fifteen. We also apply an information theoretic measure of branch support to assess the strength of phylogenetic signal in the data, revealing many poorly supported branches concentrated near the tips of the tree, where data are sparse and the limiting effects of this sparseness are stronger. We argue that limits to phylogenetic inference and signal imposed by low data coverage may pose significant challenges for comprehensive phylogenetic inference at the species level. Computational requirements provide additional limits for large reconstructions, but these may be overcome by methodological advances, whereas insufficient data coverage can only be remedied by additional sampling effort. We conclude that public databases have exceptional value for modern systematics and evolutionary biology, and that a continued emphasis on expanding taxonomic and genomic coverage will play a critical role in developing these resources to their full potential.     

Setting Risk-Based Occupational Exposure Limits for No-Threshold Carcinogens

Several regulators have recently issued so-called risk-based occupational exposure limits for carcinogenic substances, and also reported estimates of the risk of fatality that exposure to the limit value would give rise to. This practice provides an opportunity to study how differences in the exposure limits set by different regulators are influenced by differences in the scientific judgment (what is the risk at different levels?) and in the policy judgment (how should large risks be accepted?). Based on a broad search, a list was compiled of exposure limits for carcinogens that the respective regulator associates with a numerical risk estimate. For benzene, such data was available from six regulators. The differences in estimates of the risk/exposure relationship and in risk tolerance were about equal in size for benzene, while the range for acceptability was somewhat wider. A similar pattern was observed, although less clearly, for substances with data from only two or three regulators. It is concluded that the science factor and the policy factor both contribute to differences in exposure limits for carcinogens. It was not possible to judge which of these two factors has the larger influence.     

The limits to population density in birds and mammals

We address two fundamental ecological questions: what are the limits to animal population density and what determines those limits? We develop simple alternative models to predict population limits in relation to body mass. A model assuming that within‐species area use increases with the square of daily travel distance broadly predicts the scaling of empirical extremes of minimum density across birds and mammals. Consistent with model predictions, the estimated density range for a given mass, ‘population scope’, is greater for birds than for mammals. However, unlike mammals and carnivorous birds, expected broad relationships between body mass and density extremes are not supported by data on herbivorous and omnivorous birds. Our results suggest that simple constraints on mobility and energy use/supply are major determinants of the scaling of density limits, but further understanding of interactions between dietary constraints and density limits are needed to predict future wildlife population responses to anthropogenic threats.     

Sedimentation velocity analytical ultracentrifugation and SEDFIT/c(s): limits of quantitation for a monoclonal antibody system

Sedimentation velocity analytical ultracentrifugation (SV-AUC) has emerged in the biopharmaceutical industry as a technique to detect small quantities of protein aggregates. However, the limits of detection and quantitation of these aggregates are not yet well understood. Although diverse factors (molecule, instrument, technique, and software dependent) preclude an all-encompassing measurement of these limits for the complete system, it is possible to use simulated data to determine the quantitation limits of the data analysis software aspect. The current study examines the performance of the SEDFIT/c(s) data analysis tool with simulated antibody monomer/dimer and monomer/aggregate systems. Under completely ideal conditions (zero noise, known meniscus, and shape factor homogeneity), the software limit of quantitation was 0.01% for the monomer/aggregate system and 0.03% for the less well-resolved monomer/dimer system. Under more realistic conditions (0.005 OD root mean square [RMS] noise, shape factor variability, and long solution column), the software limits of quantitation were 0.2 and 0.6% (0.002 and 0.006 OD) for the monomer/aggregate and monomer/dimer systems, respectively. Interestingly, diminished quantitation accuracy at very low levels of oligomer was not accompanied by deterioration of fit quality (as measured by root mean square deviation [RMSD] and residuals bitmap images).     

HERSIM: a microcomputer program designed to compute the limits of conversion for real homogeneous isothermal enzymic reactors

HERSIM is a program written in BASIC designed to aid the investigatorinterested in determining the substrate conversion in a realhomogeneous isothermal enzymic reactor, for various kineticequations. The program runs after tracer data relative to aDirac impulse to the reactor have been entered, and computesthe two limits of real conversion: total segregation and maximummixedness. The kinetic constants of the reacting system areinput as data, and the variation of conversion with reactortemperature between given limits is computed as accurately asrequested. Received on November 6, 1986; accepted on March 4, 1987     

Estimating the product‐moment correlation in samples with censoring on both variables

Bivariate samples may be subject to censoring of both random variables. For example, for two toxins measured in batches of wheat grain, there may be specific detection limits. Alternatively, censoring may be incomplete over a certain domain, with the probability of detection depending on the toxin level. In either case, data are not missing at random, and the missing data pattern bears some information on the parameters of the underlying model (informative missingness), which can be exploited for a fully efficient analysis. Estimation (after suitable data transformation) of the correlation in such samples is the subject of the present paper. We consider several estimators. The first is based on the tetrachoric correlation. It is simple to compute, but does not exploit the full information. The other two estimators exploit all information and use full maximum likelihood, but involve heavier computations. The one assumes fixed detection limits, while the other involves a logistic model for the probability of detection. For a real data set, a logistic model for the probability of detection fitted markedly better than a model with fixed detection limits, suggesting that censoring is not complete.     

Estimating long-term survival temperatures at the assemblage level in the marine environment: towards macrophysiology

Defining ecologically relevant upper temperature limits of species is important in the context of environmental change. The approach used in the present paper estimates the relationship between rates of temperature change and upper temperature limits for survival in order to evaluate the maximum long-term survival temperature (Ts). This new approach integrates both the exposure time and the exposure temperature in the evaluation of temperature limits. Using data previously published for different temperate and Antarctic marine environments, we calculated Ts in each environment, which allowed us to calculate a new index: the Warming Allowance (WA). This index is defined as the maximum environmental temperature increase which an ectotherm in a given environment can tolerate, possibly with a decrease in performance but without endangering survival over seasonal or lifetime time-scales. It is calculated as the difference between maximum long-term survival temperature (Ts) and mean maximum habitat temperature. It provides a measure of how close a species, assemblage or fauna are living to their temperature limits for long-term survival and hence their vulnerability to environmental warming. In contrast to data for terrestrial environments showing that warming tolerance increases with latitude, results here for marine environments show a less clear pattern as the smallest WA value was for the Peru upwelling system. The method applied here, relating upper temperature limits to rate of experimental warming, has potential for wide application in the identification of faunas with little capacity to survive environmental warming.     

Environmental marginality and geographic range limits: a case study with Arabidopsis lyrata ssp. lyrata

Understanding the factors that govern the distribution of species is a central goal of evolutionary ecology. It is commonly assumed that geographic range limits reflect ecological niche limits and that species experience increasingly marginal conditions towards the edge of their ranges. Using spatial data and ecological niche models we tested these hypotheses in Arabidopsis lyrata. Specifically, we asked whether range limits coincide with predicted niche limits in this system and whether the suitability of sites declines towards the edge of the species’ range in North America. We further explored patterns of environmental change towards the edge of the range and asked whether genome‐wide patterns of genetic diversity decline with increasing peripherality and environmental marginality. Our results suggest that latitudinal range limits coincide with niche limits. Populations experienced increasingly marginal environments towards these limits – though patterns of environmental change were more complex than most theoretical models for range limits assume. Genomic diversity declined towards the edge of the species’ range and with increasing distance from the estimated centre of the species’ niche in environmental space, but not with the suitability of sites based on niche model predictions. Thus while latitudinal range limits in this system are broadly associated with niche limits, the link between environmental conditions and genetic diversity (and thus the adaptive potential of populations) is less clear.     

Heart rate monitoring on the stroke unit. What does heart beat tell about prognosis? An observational study

Background  

Guidelines recommend maintaining the heart rate (HR) of acute stroke patients within physiological limits; data on the frequency and predictors of significant deviations from these limits are scarce.     

Third Party Intervention in the Commission on the Limits of the Continental Shelf Regarding a Submission Involving a Dispute

The Commission on the Limits of the Continental Shelf (CLCS) was established in accordance with Article 76 of the Law of the Sea Convention. CLCS has the mandate to consider data submitted by coastal states concerning the outer limits of their continental shelf in areas where those limits extend beyond 200 nautical miles and to make recommendations to the submitting state on matters related to the establishment of the limits. For third parties that have actual or potential disputes, unresolved borders, or unresolved land or maritime disputes with the submitting state, the recommendations of the CLCS can be very sensitive. The focus of this article is on the practice of third parties in responding to submissions and how third parties have constructed their Notifications.