999 resultados para Climate signal
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BACKGROUND: Characteristic symptoms of malaria include recurrent fever attacks and neurodegeneration, signs that are also found in patients with a hyperactive Nalp3 inflammasome. Plasmodium species produce a crystal called hemozoin that is generated by detoxification of heme after hemoglobin degradation in infected red blood cells. Thus, we hypothesized that hemozoin could activate the Nalp3 inflammasome, due to its particulate nature reminiscent of other inflammasome-activating agents. METHODOLOGY/PRINCIPAL FINDINGS: We found that hemozoin acts as a proinflammatory danger signal that activates the Nalp3 inflammasome, causing the release of IL-1beta. Similar to other Nalp3-activating particles, hemozoin activity is blocked by inhibiting phagocytosis, K(+) efflux and NADPH oxidase. In vivo, intraperitoneal injection of hemozoin results in acute peritonitis, which is impaired in Nalp3-, caspase-1- and IL-1R-deficient mice. Likewise, the pathogenesis of cerebral malaria is dampened in Nalp3-deficient mice infected with Plasmodium berghei sporozoites, while parasitemia remains unchanged. SIGNIFICANCE/CONCLUSIONS: The potent pro-inflammatory effect of hemozoin through inflammasome activation may possibly be implicated in plasmodium-associated pathologies such as cerebral malaria.
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The Iowa Department of Transportation (DOT) is responsible for approximately 4,100 bridges and structures that are a part of the state’s primary highway system, which includes the Interstate, US, and Iowa highway routes. A pilot study was conducted for six bridges in two Iowa river basins—the Cedar River Basin and the South Skunk River Basin—to develop a methodology to evaluate their vulnerability to climate change and extreme weather. The six bridges had been either closed or severely stressed by record streamflow within the past seven years. An innovative methodology was developed to generate streamflow scenarios given climate change projections. The methodology selected appropriate rainfall projection data to feed into a streamflow model that generated continuous peak annual streamflow series for 1960 through 2100, which were used as input to PeakFQ to estimate return intervals for floods. The methodology evaluated the plausibility of rainfall projections and credibility of streamflow simulation while remaining consistent with U.S. Geological Survey (USGS) protocol for estimating the return interval for floods. The results were conveyed in an innovative graph that combined historical and scenario-based design metrics for use in bridge vulnerability analysis and engineering design. The pilot results determined the annual peak streamflow response to climate change likely will be basin-size dependent, four of the six pilot study bridges would be exposed to increased frequency of extreme streamflow and would have higher frequency of overtopping, the proposed design for replacing the Interstate 35 bridges over the South Skunk River south of Ames, Iowa is resilient to climate change, and some Iowa DOT bridge design policies could be reviewed to consider incorporating climate change information.
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Climate change may pose challenges and opportunities to viticulture, and much research has focused in studying the likely impacts on grapes and wine production in different regions worldwide. This study assesses the vulnerability and adaptive capacity of the viticulture sector under changing climate conditions, based on a case study in El Penedès region, Catalonia. Farm assets, livelihood strategies, farmer-market interactions and climate changes perceptions are analysed through semi-structured interviews with different types of wineries and growers. Both types of actors are equally exposed to biophysical stressors but unevenly affected by socioeconomic changes. While wineries are vulnerable because of the current economic crisis and the lack of diversification of their work, which may affect their income or production, growers are mainly affected by the low prices of their products and the lack of fix contracts. These socioeconomic stressors strongly condition their capacity to adapt to climate change, meaning that growers prioritize their immediate income problems, rather than future socioeconomic or climate threats. Therefore, growers undertake reactive adaptation to climate changing conditions, mainly based on ancient knowledge, whilst wineries combine both reactive and anticipatory adaptation practices. These circumstances should be addressed in order to allow better anticipatory adaptation to be implemented, thus avoiding future climate threats.
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In the context of observed climate change impacts and their effect on agriculture and crop production, this study intends to assess the vulnerability of rural livelihoods through a study case in Karnataka, India. The social approach of climate change vulnerability in this study case includes defining and exploring factors that determine farmers’ vulnerability in four villages. Key informant interviews, farmer workshops and structured household interviews were used for data collection. To analyse the data, we adapted and applied three vulnerability indices: Livelihood Vulnerability Index (LVI), LVI-IPCC and the Livelihood Effect Index (LEI), and used descriptive statistical methods. The data was analysed at two scales: whole sample-level and household level. The results from applying the indices for the whole-sample level show that this community's vulnerability to climate change is moderate, whereas the household-level results show that most of the households' vulnerability is high-very high, while 15 key drivers of vulnerability were identified. Results and limitations of the study are discussed under the rural livelihoods framework, in which the indices are based, allowing a better understanding of the social behaviouraltrends, as well as an holistic and integrated view of the climate change, agriculture, and livelihoods processes shaping vulnerability. We conclude that these indices, although a straightforward method to assess vulnerability, have limitations that could account for inaccuracies and inability to be standardised for benchmarking, therefore we stress the need for further research.
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Glucagon-like peptide-1 (GLP-1) is a gastrointestinal hormone that potentiates glucose-induced insulin secretion by pancreatic beta cells. The mechanisms of interaction between GLP-1 and glucose signaling pathways are not well understood. Here we studied the coupling of the cloned GLP-1 receptor, expressed in fibroblasts or in COS cells, to intracellular second messengers and compared this signaling with that of the endogenous receptor expressed in insulinoma cell lines. Binding of GLP-1 to the cloned receptor stimulated formation of cAMP with the same dose dependence and similar kinetics, compared with the endogenous receptor of insulinoma cells. Compared with forskolin-induced cAMP accumulation, that induced by GLP-1 proceeded with the same initial kinetics but rapidly reached a plateau, suggesting fast desensitization of the receptor. Coupling to the phospholipase C pathway was assessed by measuring inositol phosphate production and variations in the intracellular calcium concentration. No GLP-1-induced production of inositol phosphates could be measured in the different cell types studied. A rise in the intracellular calcium concentration was nevertheless observed in transfected COS cells but was much smaller than that observed in response to norepinephrine in cells also expressing the alpha 1B-adrenergic receptor. Importantly, no such increase in the intracellular calcium concentration could be observed in transfected fibroblasts or insulinoma cells, which, however, responded well to thrombin or carbachol, respectively. Together, our data show that interaction between GLP-1 and glucose signaling pathways in beta cells may be mediated uniquely by an increase in the intracellular cAMP concentration, with the consequent activation of protein kinase A and phosphorylation of elements of the glucose-sensing apparatus or of the insulin granule exocytic machinery.
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Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range and spatial resolution of data used in making these models, different rates of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolution and geographic extent. Here, we assess whether climate-change induced habitat losses predicted at the European scale (10x10' grid cells) are also predicted from local scale data and modeling (25x25m grid cells) in two regions of the Swiss Alps. We show that local-scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European-scale model to lose all their suitable habitats in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10x10' cells. The greatest prediction discrepancy for alpine species occurs in the area with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations.
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Changes in technology have an impact on standard practice, materials, and equipment. The traffic signal industry is constantly producing more energy-efficient and durable equipment, better communications, and more sophisticated detection and monitoring capabilities. Accordingly, this project provides an update to the traffic signal content within the Statewide Urban Design and Specifications (SUDAS) Design Manual and Standard Specifications. This work was completed through a technical advisory committee with a variety of participants representing contractors, the Iowa Department of Transportation, cities, consultants, vendors, and university research and support staff.
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Summary Due to their conic shape and the reduction of area with increasing elevation, mountain ecosystems were early identified as potentially very sensitive to global warming. Moreover, mountain systems may experience unprecedented rates of warming during the next century, two or three times higher than that records of the 20th century. In this context, species distribution models (SDM) have become important tools for rapid assessment of the impact of accelerated land use and climate change on the distribution plant species. In my study, I developed and tested new predictor variables for species distribution models (SDM), specific to current and future geographic projections of plant species in a mountain system, using the Western Swiss Alps as model region. Since meso- and micro-topography are relevant to explain geographic patterns of plant species in mountain environments, I assessed the effect of scale on predictor variables and geographic projections of SDM. I also developed a methodological framework of space-for-time evaluation to test the robustness of SDM when projected in a future changing climate. Finally, I used a cellular automaton to run dynamic simulations of plant migration under climate change in a mountain landscape, including realistic distance of seed dispersal. Results of future projections for the 21st century were also discussed in perspective of vegetation changes monitored during the 20th century. Overall, I showed in this study that, based on the most severe A1 climate change scenario and realistic dispersal simulations of plant dispersal, species extinctions in the Western Swiss Alps could affect nearly one third (28.5%) of the 284 species modeled by 2100. With the less severe 61 scenario, only 4.6% of species are predicted to become extinct. However, even with B1, 54% (153 species) may still loose more than 80% of their initial surface. Results of monitoring of past vegetation changes suggested that plant species can react quickly to the warmer conditions as far as competition is low However, in subalpine grasslands, competition of already present species is probably important and limit establishment of newly arrived species. Results from future simulations also showed that heavy extinctions of alpine plants may start already in 2040, but the latest in 2080. My study also highlighted the importance of fine scale and regional. assessments of climate change impact on mountain vegetation, using more direct predictor variables. Indeed, predictions at the continental scale may fail to predict local refugees or local extinctions, as well as loss of connectivity between local populations. On the other hand, migrations of low-elevation species to higher altitude may be difficult to predict at the local scale. Résumé La forme conique des montagnes ainsi que la diminution de surface dans les hautes altitudes sont reconnues pour exposer plus sensiblement les écosystèmes de montagne au réchauffement global. En outre, les systèmes de montagne seront sans doute soumis durant le 21ème siècle à un réchauffement deux à trois fois plus rapide que celui mesuré durant le 20ème siècle. Dans ce contexte, les modèles prédictifs de distribution géographique de la végétation se sont imposés comme des outils puissants pour de rapides évaluations de l'impact des changements climatiques et de la transformation du paysage par l'homme sur la végétation. Dans mon étude, j'ai développé de nouvelles variables prédictives pour les modèles de distribution, spécifiques à la projection géographique présente et future des plantes dans un système de montagne, en utilisant les Préalpes vaudoises comme zone d'échantillonnage. La méso- et la microtopographie étant particulièrement adaptées pour expliquer les patrons de distribution géographique des plantes dans un environnement montagneux, j'ai testé les effets d'échelle sur les variables prédictives et sur les projections des modèles de distribution. J'ai aussi développé un cadre méthodologique pour tester la robustesse potentielle des modèles lors de projections pour le futur. Finalement, j'ai utilisé un automate cellulaire pour simuler de manière dynamique la migration future des plantes dans le paysage et dans quatre scénarios de changement climatique pour le 21ème siècle. J'ai intégré dans ces simulations des mécanismes et des distances plus réalistes de dispersion de graines. J'ai pu montrer, avec les simulations les plus réalistes, que près du tiers des 284 espèces considérées (28.5%) pourraient être menacées d'extinction en 2100 dans le cas du plus sévère scénario de changement climatique A1. Pour le moins sévère des scénarios B1, seulement 4.6% des espèces sont menacées d'extinctions, mais 54% (153 espèces) risquent de perdre plus 80% de leur habitat initial. Les résultats de monitoring des changements de végétation dans le passé montrent que les plantes peuvent réagir rapidement au réchauffement climatique si la compétition est faible. Dans les prairies subalpines, les espèces déjà présentes limitent certainement l'arrivée de nouvelles espèces par effet de compétition. Les résultats de simulation pour le futur prédisent le début d'extinctions massives dans les Préalpes à partir de 2040, au plus tard en 2080. Mon travail démontre aussi l'importance d'études régionales à échelle fine pour évaluer l'impact des changements climatiques sur la végétation, en intégrant des variables plus directes. En effet, les études à échelle continentale ne tiennent pas compte des micro-refuges, des extinctions locales ni des pertes de connectivité entre populations locales. Malgré cela, la migration des plantes de basses altitudes reste difficile à prédire à l'échelle locale sans modélisation plus globale.
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PURPOSE: The macromolecule signal plays a key role in the precision and the accuracy of the metabolite quantification in short-TE (1) H MR spectroscopy. Macromolecules have been reported at 1.5 Tesla (T) to depend on the cerebral studied region and to be age specific. As metabolite concentrations vary locally, information about the profile of the macromolecule signal in different tissues may be of crucial importance. METHODS: The aim of this study was to investigate, at 7T for healthy subjects, the neurochemical profile differences provided by macromolecule signal measured in two different tissues in the occipital lobe, predominantly composed of white matter tissue or of grey matter tissue. RESULTS: White matter-rich macromolecule signal was relatively lower than the gray matter-rich macromolecule signal from 1.5 to 1.8 ppm and from 2.3 to 2.5 ppm with mean difference over these regions of 7% and 12% (relative to the reference peak at 0.9 ppm), respectively. The neurochemical profiles, when using either of the two macromolecule signals, were similar for 11 reliably quantified metabolites (CRLB < 20%) with relatively small concentration differences (< 0.3 μmol/g), except Glu (± 0.8 μmol/g). CONCLUSION: Given the small quantification differences, we conclude that a general macromolecule baseline provides a sufficiently accurate neurochemical profile in occipital lobe at 7T in healthy human brain.
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The objective of this work was to assess the potential impact of climate change on the spatial distribution of coffee nematodes (races of Meloidogyne incognita) and leaf miner (Leucoptera coffeella), using a Geographic Information System. Assessment of the impacts of climate change on pest infestations and disease epidemics in crops is needed as a basis for revising management practices to minimize crop losses as climatic conditions shift. Future scenarios focused on the decades of the 2020's, 2050's, and 2080's (scenarios A2 and B2) were obtained from five General Circulation Models available on Data Distribution Centre from Intergovernmental Panel on Climate Change. Geographic distribution maps were prepared using models to predict the number of generations of the nematodes and leaf miner. Maps obtained in scenario A2 allowed prediction of an increased infestation of the nematode and of the pest, due to greater number of generations per month, than occurred under the climatological normal from 1961-1990. The number of generations also increased in the B2 scenario, but was lower than in the A2 scenario for both organisms.
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Abstract
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Upward migration of plant species due to climate change has become evident in several European mountain ranges. It is still, however, unclear whether certain plant traits increase the probability that a species will colonize mountain summits or vanish, and whether these traits differ with elevation. Here, we used data from a repeat survey of the occurrence of plant species on 120 summits, ranging from 2449 to 3418 m asl, in south-eastern Switzerland to identify plant traits that increase the probability of colonization or extinction in the 20th century. Species numbers increased across all plant traits considered. With some traits, however, numbers increased proportionally more. The most successful colonizers seemed to prefer warmer temperatures and well-developed soils. They produced achene fruits and/or seeds with pappus appendages. Conversely, cushion plants and species with capsule fruits were less efficient as colonizers. Observed changes in traits along the elevation gradient mainly corresponded to the natural distribution of traits. Extinctions did not seem to be clearly related to any trait. Our study showed that plant traits varied along both temporal and elevational gradients. While seeds with pappus seemed to be advantageous for colonization, most of the trait changes also mirrored previous gradients of traits along elevation and hence illustrated the general upward migration of plant species. An understanding of the trait characteristics of colonizing species is crucial for predicting future changes in mountain vegetation under climate change.