182 research outputs found
Alpha-1 Antitrypsin is Markedly Decreased Following Pulmonary F. tularensis Challenge
Neutrophils form the first line of defense during infection and are indispensable in this function. The neutrophil elastase is a key effector molecule of the innate immune system with potent antimicrobial activity against Gram-negative bacteria, spirochaetes, and fungi. However, the release of neutrophil elastase during bacterial infection must be checked otherwise its release in the extracellular milieu will result in damage to surrounding tissues. Alpha-1 antitrypsin is a small glycoprotein clade A serpine serine protease inhibitor and has been shown to increase in humans following bacterial and viral infection. Francisella tularensis is a Gram-negative facultative intracellular bacterium and the causative agent of tularemia. Type A strains are the most virulent with an infectious dose as low as 10 colony forming units and a mortality rate of 30â60% among untreated cases of pneumonic tularemia. We report here significant reduction of this major inhibitor of the neutrophil elastase in plasma of F. tularensis LVS and F. tularensis (type A) SCHU S4 infected animals following pulmonary challenge. Associated with an imbalance of proteaseâantiprotease function at the alveolar level in lungs of infected animals, increased elastase activity was observed in lung lavage fluids accompanied by decrease lung function, i.e., loss of lung elastance with concomitant increase of pulmonary hysteresivity. Consistent with a competent acute phase response following F. tularensis LVS and F. tularensis (type A) SCHU S4 pulmonary challenge and proposed up-regulation of plasma haptoglobin during the course of the acute phase reaction, haptoglobin was observed significantly increased. These data suggest that unchecked neutrophil serine protease activity may arise from F. tularensis targeted reduction of plasma Îą(1)-antitrysin promoting lung tissue damage facilitating increased dissemination of this bacterium in infected animals
Harnessing gene expression to identify the genetic basis of drug resistance
The advent of cost-effective genotyping and sequencing methods have recently made it possible to ask questions that address the genetic basis of phenotypic diversity and how natural variants interact with the environment. We developed Camelot (CAusal Modelling with Expression Linkage for cOmplex Traits), a statistical method that integrates genotype, gene expression and phenotype data to automatically build models that both predict complex quantitative phenotypes and identify genes that actively influence these traits. Camelot integrates genotype and gene expression data, both generated under a reference condition, to predict the response to entirely different conditions. We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug-free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel geneâdrug interactions. Our approach is robust, applicable to other phenotypes and species, and has potential for applications in personalized medicine, for example, in predicting how an individual will respond to a previously unseen drug
A Homogeneous Actor-Based Monitor Language for Adaptive Behaviour
This paper describes a structured approach to encoding monitors in an actor language. Within a configuration of actors, each of which publishes a history, a monitor is an independent actor that triggers an action based on patterns occurring in the histories. We define a monitor language based on linear temporal logic and show how it can be homogeneously embedded within an actor language. The approach is demonstrated through a number of examples and evaluated in terms of a real-world actor-based simulation
Estimating the Continuous-Time Dynamics of Energy and Fat Metabolism in Mice
The mouse has become the most popular organism for investigating molecular mechanisms of body weight regulation. But understanding the physiological context by which a molecule exerts its effect on body weight requires knowledge of energy intake, energy expenditure, and fuel selection. Furthermore, measurements of these variables made at an isolated time point cannot explain why body weight has its present value since body weight is determined by the past history of energy and macronutrient imbalance. While food intake and body weight changes can be frequently measured over several weeks (the relevant time scale for mice), correspondingly frequent measurements of energy expenditure and fuel selection are not currently feasible. To address this issue, we developed a mathematical method based on the law of energy conservation that uses the measured time course of body weight and food intake to estimate the underlying continuous-time dynamics of energy output and net fat oxidation. We applied our methodology to male C57BL/6 mice consuming various ad libitum diets during weight gain and loss over several weeks and present the first continuous-time estimates of energy output and net fat oxidation rates underlying the observed body composition changes. We show that transient energy and fat imbalances in the first several days following a diet switch can account for a significant fraction of the total body weight change. We also discovered a time-invariant curve relating body fat and fat-free masses in male C57BL/6 mice, and the shape of this curve determines how diet, fuel selection, and body composition are interrelated
Prey availability and temporal partitioning modulate felid coexistence in Neotropical forests
Carnivores have long been used as model organisms to examine mechanisms that allow coexistence among ecologically similar species. Interactions between carnivores, including competition and predation, comprise important processes regulating local community structure and diversity. We use data from an intensive camera-trapping monitoring program across eight Neotropical forest sites to describe the patterns of spatiotemporal organization of a guild of five sympatric cat species: jaguar (Panthera onca), puma (Puma concolor), ocelot (Leopardus pardalis), jaguarundi (Herpailurus yagouaroundi) and margay (Leopardus wiedii). For the three largest cat species, we developed multi-stage occupancy models accounting for habitat characteristics (landscape complexity and prey availability) and models accounting for species interactions (occupancy estimates of potential competitor cat species). Patterns of habitat-use were best explained by prey availability, rather than habitat structure or species interactions, with no evidence of negative associations of jaguar on puma and ocelot occupancy or puma on ocelot occupancy. We further explore temporal activity patterns and overlap of all five felid species. We observed a moderate temporal overlap between jaguar, puma and ocelot, with differences in their activity peaks, whereas higher temporal partitioning was observed between jaguarundi and both ocelot and margay. Lastly, we conducted temporal overlap analysis and calculated species activity levels across study sites to explore if shifts in daily activity within species can be explained by varying levels of local competition pressure. Activity patterns of ocelots, jaguarundis and margays were similarly bimodal across sites, but pumas exhibited irregular activity patterns, most likely as a response to jaguar activity. Activity levels were similar among sites and observed differences were unrelated to competition or intraguild killing risk. Our study reveals apparent spatial and temporal partitioning for most of the species pairs analyzed, with prey abundance being more important than species interactions in governing the local occurrence and spatial distribution of Neotropical forest felids
The specificity and the development of social-emotional competence in a multi-ethnic-classroom
<p>Abstract</p> <p>Background</p> <p>Ethnic diversity in schools increases due to globalization. Thus, the children's social-emotional competence development must be considered in the context of a multi-ethnic classroom.</p> <p>Methods</p> <p>In this study, the social-emotional competence of 65 Asian-American and Latin-American children was observed at the beginning and the end of their kindergarten year.</p> <p>Results</p> <p>Initially, significant differences existed among these ethnic groups in respect to moral reasoning. Furthermore, the male children showed more dysregulated aggression but the female children implemented more moral reasoning than their male counterparts. These ethnic specificities did not disappear over the course of the year. In addition, a significant change in avoidance strategies as well as expressed emotions in the narrative took place over the course of one year.</p> <p>Conclusion</p> <p>Ethnic specificity in social-emotional competence does exist independent of gender at the beginning as well as at the end of the kindergarten year in a multi-ethnic kindergarten classroom.</p
A social and ecological assessment of tropical land uses at multiple scales: the Sustainable amazon network
Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede AmazĂ´nia SustentĂĄvel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far
Calorie for calorie, dietary fat restriction results in more body fat loss than carbohydrate restriction in people with obesity
Š 2015 Elsevier Inc. Dietary carbohydrate restriction has been purported to cause endocrine adaptations that promote body fat loss more than dietary fat restriction. We selectively restricted dietary carbohydrate versus fat for 6 days following a 5-day baseline diet in 19 adults with obesity confined to a metabolic ward where they exercised daily. Subjects received both isocaloric diets in random order during each of two inpatient stays. Body fat loss was calculated as the difference between daily fat intake and net fat oxidation measured while residing in a metabolic chamber. Whereas carbohydrate restriction led to sustained increases in fat oxidation and loss of 53 ¹ 6 g/day of body fat, fat oxidation was unchanged by fat restriction, leading to 89 ¹ 6 g/day of fat loss, and was significantly greater than carbohydrate restriction (p = 0.002). Mathematical model simulations agreed with these data, but predicted that the body acts to minimize body fat differences with prolonged isocaloric diets varying in carbohydrate and fat
Rapid Plant Identification Using Species- and Group-Specific Primers Targeting Chloroplast DNA
Plant identification is challenging when no morphologically assignable parts are available. There is a lack of broadly applicable methods for identifying plants in this situation, for example when roots grow in mixture and for decayed or semi-digested plant material. These difficulties have also impeded the progress made in ecological disciplines such as soil- and trophic ecology. Here, a PCR-based approach is presented which allows identifying a variety of plant taxa commonly occurring in Central European agricultural land. Based on the trnT-F cpDNA region, PCR assays were developed to identify two plant families (Poaceae and Apiaceae), the genera Trifolium and Plantago, and nine plant species: Achillea millefolium, Fagopyrum esculentum, Lolium perenne, Lupinus angustifolius, Phaseolus coccineus, Sinapis alba, Taraxacum officinale, Triticum aestivum, and Zea mays. These assays allowed identification of plants based on size-specific amplicons ranging from 116 bp to 381 bp. Their specificity and sensitivity was consistently high, enabling the detection of small amounts of plant DNA, for example, in decaying plant material and in the intestine or faeces of herbivores. To increase the efficacy of identifying plant species from large number of samples, specific primers were combined in multiplex PCRs, allowing screening for multiple species within a single reaction. The molecular assays outlined here will be applicable manifold, such as for root- and leaf litter identification, botanical trace evidence, and the analysis of herbivory
Pervasive gaps in Amazonian ecological research.
This is the final version. Available from Elsevier via the DOI in this record.âŻData and code availability:
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Metadata have been deposited at Zenodo and are publicly available as of the date of publication. DOIs are listed in the key resources table.
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All original code has been deposited at Zenodo and is publicly available as of the date of publication. DOIs are listed in the key resources table.
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Any additional information required to reanalyse the data reported in this paper is available from the lead contact upon request.Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%-18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.Conselho Nacional de Desenvolvimento CientĂfico (CNPq)Conselho Nacional de Desenvolvimento CientĂfico (CNPq)SĂŁo Paulo Research Foundation (FAPESP)SĂŁo Paulo Research Foundation (FAPESP)SĂŁo Paulo Research Foundation (FAPESP)SĂŁo Paulo Research Foundation (FAPESP)Natural Environment Research Council (NERC)University of Bristol (PolicyBristol)University of Bristol Climate and Net Zero Impact AwardsUniversity of Bristol Elizabeth Blackwell Institute Rapid Research FundingNatural Environment Research Council (NERC)European Unionâs Horizon 202
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