Pulmonary inflammation induced by office dust and the relation to 1 → 3-β-glucan using different extraction techniques

It is observed that 1?→?3-β-glucan, a major cell wall component of fungi, induces pulmonary inflammation. There is inconsistency in determining the correlation between the levels of glucan measured by current extraction methods and the respiratory inflammation observed in individuals or lab animals exposed to environmental dust samples. The glucan-specific limulus amebocyte lysate (G-LAL) method was used after extraction with dimethyl sulfoxide (DMSO) or sodium hydroxide (NaOH) to analyze the glucan content of office dust samples collected from a water-damaged building. C3HeB/FeJ mice, an endotoxin-sensitive strain, were treated with different dust samples (2.5?mg?kg^?1 body weight) or saline (vehicle control) by pharyngeal aspiration. At 1?day after aspiration, bronchoalveolar lavage (BAL) was performed, and lung inflammation and injury were assessed by measuring: (1) neutrophil (PMN) infiltration, (2) inflammatory cytokine (IL-6, IL-10, MCP-1, IFN-γ, TNF-α, and IL12-p70) levels, and (3) albumin and lactate dehydrogenase in recovered BAL fluid. Both DMSO and NaOH extraction increased the detection of glucan by approximately 20-fold compared to water extraction. However, only the DMSO extraction method showed a statistically significant positive correlation between 1?→?3-β-glucan and albumin levels, total numbers of BAL, polymorphonuclear leukocytes (PMNs) cells recovered, levels of TNF-α, MCP-1, and IL-6. In conclusion, 1?→?3-β-glucan is a potent inflammatory agent in dust samples and DMSO extraction for glucan analysis may prove useful in understanding the impact of environmental contamination by glucans on lung disease.     

Heavy Metals in Terrestrial Macroinvertebrates: Species Differences Within and Between Trophic Levels

Whole animal concentrations of Pb, Zn and Cd were measured in herbivorous (1 snail species; 1 dipteran larva species), herbivorous + detritivorous (2 slug species), detritivorous (3 woodlouse species; 3 earthworm species), and carnivorous (1 carabid beetle species; 1 lithobiid centipede species) terrestrial macroinvertebrates collected at a disused Pb/Zn mine site. No evidence was found for an accretion of any metal during transference from herbivores to carnivores; the highest metal concentrations were, in fact, generally found in detritivores. The lack of metal bio-amplification during food chain transference is probably due to the sequestration of metals (notably Pb and Zn) in insoluble inorganic-rich granules within certain target organs and cells.

Earthworms and woodlice, respectively, showed major differences in metal concentrations. These differences between closely related species frequently exceeded differences between unrelated species occupying different trophic levels, and may be attributable to a combination of ill-defined ecological and physiological differences that ensure habitat and resource partitioning.     

Evaluating the impacts of multiple generalist fungal pathogens on temperate tree seedling survival

Host-specific mortality driven by natural enemies is a widely discussed mechanism for explaining plant diversity. In principle, populations of plant species can be regulated by distinct host-specific natural enemies that have weak or nonexistent effects on heterospecific competitors, preventing any single species from becoming dominant and thus promoting diversity. Two of the first steps in exploring the role of natural enemies in diversity regulation are to (1) identify potential enemies and (2) evaluate their levels of host specificity by determining if interactions between any one host and its enemy have equivalent survival impacts on co-occurring host species. We developed a bioinformatics framework to evaluate impacts of potential pathogens on seedling survival, for both single and multiple infections. Importantly, we consider scenarios not only if there are specialist pathogens for each plant, but also when generalist pathogens have differential effects on multiple host species, and when co-infection has species-specific effects. We then applied this analytical framework to a field experiment using molecular techniques to detect potential fungal pathogens on co-occurring tree seedling hosts. Combinatorial complexity created by 160 plant-fungus interactions was reduced to eight combinations that affect seedling survival. Potential fungal pathogens had broad host ranges, but seedling species were each regulated by different combinations of fungi or by generalist fungi that had differential effects on multiple plant species. Soil moisture can have the potential to shift the nature of the interactions in some plant-fungal combinations from neutral to detrimental. Reassessing the assumption of single-enemy-single-host interactions broadens the mechanisms through which natural enemies can influence plant diversity.     

A new approach to the "apparent survival" problem: estimating true survival rates from mark-recapture studies

Survival estimates generated from live capture-mark-recapture studies may be negatively biased due to the permanent emigration of marked individuals from the study area. In the absence of a robust analytical solution, researchers typically sidestep this problem by simply reporting estimates using the term "apparent survival." Here, we present a hierarchical Bayesian multistate model designed to estimate true survival by accounting for predicted rates of permanent emigration. Initially we use dispersal kernels to generate spatial projections of dispersal probability around each capture location. From these projections, we estimate emigration probability for each marked individual and use the resulting values to generate bias-adjusted survival estimates from individual capture histories. When tested using simulated data sets featuring variable detection probabilities, survival rates, and dispersal patterns, the model consistently eliminated negative biases shown by apparent survival estimates from standard models. When applied to a case study concerning juvenile survival in the endangered Cape Sable Seaside Sparrow (Ammodramus maritimus mirabilis), bias-adjusted survival estimates increased more than twofold above apparent survival estimates. Our approach is applicable to any capture-mark-recapture study design and should be particularly valuable for organisms with dispersive juvenile life stages.     

Older adult falls at a metropolitan airport: 2009-2010

IntroductionWe investigated falls at a metropolitan airport to determine fall incidence, identify potential causes of these falls, and suggest opportunities for mitigation.MethodsWe used deidentified incident reports of all falls requiring EMS response that occurred at the airport during 2009 and 2010.ResultsOn average, one fall occurred every 2.3 days. Ninety-six percent (96%) of falls occurred in terminals. Of all falls, 44% occurred on escalators, making escalators the most common location. Seventy-two percent (72%) of fallers were females; 43% were ≥ 65 years; 92% of all falls resulted in a documented injury; 37% of falls resulted in transport to hospital emergency departments. Escalator fall risks include carrying bags (due to changes in baggage fees), using cells phones, not using handrails, and compromised strength and balance.Conclusions and ImpactDiverting at-risk passengers to elevators could significantly reduce the overall falls. Interventions targeting escalator falls have the greatest promise for reducing falls at this airport.     

Effect of hyposalinity on the photophysiology of <Emphasis Type="Italic">Siderastrea radians</Emphasis>

Tolerance to hyposalinity of the scleractinian coral S. radians was examined in a mesocosm study. Colonies of S. radians were collected from five basins in Florida Bay, USA, which occur along a northeast-to-southwest salinity gradient. Salinity treatments were based on historical salinity records for these basins. Photophysiology of the endosymbiont Symbiodinium spp. (maximum quantum yield; F _v/F _m) was measured as an indicator of holobiont stress to hyposalinity. Colonies from each basin were assigned four salinity treatments [The Practical Salinity Scale (PSS) was used to determine salinity. Units are not assigned to salinity values because it is a ratio and has no unit as defined by UNESCO (UNESCO Technical papers no. 45, IAPSO Pub. Sci. No. 32, Paris, France, 1985)] (30, 20, 15, and 10) and salinities were reduced 2 per day from ambient (30) to simulate a natural salinity decrease. Colonies treated with salinities of 20 and 15 showed no decrease in F _v/F _m versus controls (i.e. 30), up to 5 days after reaching their target salinity. This indicates a greater ability to withstand reduced salinity for relatively extended periods of time in S. radians compared to other reef species. Within 1 day after salinity of 10 was reached, there was a significant reduction in F _v/F _m, indicating a critical threshold for hyposaline tolerance. At the lowest treatment salinity (10), F _v/F _m for the more estuarine, northeast-basin colonies were significantly higher than the most marine southwest-basin colonies (Twin Key Basin). Our results suggest that historical salinity ranges within basins determine coral population salinity tolerances.     

Animal social networks: an introduction

Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

Predicting arsenic concentrations in groundwater of San Luis Valley,Colorado: implications for individual-level lifetime exposure assessment

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83–0.92 for samples collected from the same well 15–25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.     

The basics of acidification: baseline variability of pH on Australian coral reefs

Ocean acidification is one of the key threats facing coral reef ecosystems, but there are few estimates of spatial and temporal variability in pH among reef habitats. The present study documents levels of spatial variability in pH among coral reef habitats (9 to 10), among locations separated by 100’s km of latitude and between east (Great Barrier Reef, GBR) and west (Ningaloo Reef) coasts of Australia. Differences were found in pH between inshore and offshore waters along Ningaloo Reef (means 8.45, 8.53, respectively). Replicate assessments here ranged from 8.22 to 8.64. On the GBR, the range of values over all habitats and replicates was 0.39 pH units (7.98 to 8.37). There were minor but significant differences of 0.05 pH units between 5 consecutive days for habitats on average. Highest pH was recorded in filamentous algal beds maintained by the damselfish Dischistodus perspicillatus. Lowest pH was found in water extracted from sand-dwelling goby holes. While there were marked changes in pH over a 48-h sampling period among 4 habitats at Lizard Island (GBR), there was little evidence of a diel trend. Understanding how pH varies at scales that are relevant to organisms that live on shallow coral reefs is crucial for the design and interpretation of experiments that test the effects on organisms of the changes in water chemistry predicted to affect oceans in the future.