4 resultados para Maximum stress criterion

em CentAUR: Central Archive University of Reading - UK


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Background and aims The Metabolic Syndrome (MetS) is associated with increased cardiovascular risk. Circulating microparticles (MP) are involved in the pathogenesis of atherothrombotic disorders and are raised in individual with CVD. We measured their level and cellular origin in subjects with MetS and analyzed their associations with 1/anthropometric and biological parameters of MetS, 2/inflammation and oxidative stress markers. Methods and results Eighty-eight subjects with the MetS according to the NCEP-ATPIII definition were enrolled in a bicentric study and compared to 27 healthy controls. AnnexinV-positive MP (TMP), MP derived from platelets (PMP), erythrocytes (ErMP), endothelial cells (EMP), leukocytes (LMP) and granulocytes (PNMP) were determined by flow cytometry. MetS subjects had significantly higher counts/μl of TMP (730.6 ± 49.7 vs 352.8 ± 35.6), PMP (416.0 ± 43.8 vs 250.5 ± 23.5), ErMP (243.8 ± 22.1 vs 73.6 ± 19.6) and EMP (7.8 ± 0.8 vs 4.0 ± 1.0) compared with controls. LMP and PNMP were not statistically different between groups. Multivariate analysis demonstrated that each criterion for the MetS influenced the number of TMP. Waist girth was a significant determinant of PMP and EMP level and blood pressure was correlated with EMP level. Glycemia positively correlated with PMP level whereas dyslipidemia influenced EMP and ErMP levels. Interestingly, the oxidative stress markers, plasma glutathione peroxydase and urinary 8-iso-prostaglandin F2 α, independently influenced TMP and PMP levels whereas inflammatory markers did not, irrespective of MP type. Conclusion Increased levels of TMP, PMP, ErMP and EMP are associated with individual metabolic abnormalities of MetS and oxidative stress. Whether MP assessment may represent a marker for risk stratification or a target for pharmacological intervention deserves further investigation.

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Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.

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The National Center for Atmospheric Research-Community Climate System Model (NCAR-CCSM) is used in a coupled atmosphere–ocean–sea-ice simulation of the Last Glacial Maximum (LGM, around 21,000 years ago) climate. In the tropics, the simulation shows a moderate cooling of 3 °C over land and 2 °C in the ocean in zonal average. This cooling is about 1 °C cooler than the CLIMAP sea surface temperatures (SSTs) but consistent with recent estimates of both land and sea surface temperature changes. Subtropical waters are cooled by 2–2.5 °C, also in agreement with recent estimates. The simulated oceanic thermohaline circulation at the LGM is not only shallower but also weaker than the modern with a migration of deep-water formation site in the North Atlantic as suggested by the paleoceanographic evidences. The simulated northward flow of Antarctic Bottom Water (AABW) is enhanced. These deep circulation changes are attributable to the increased surface density flux in the Southern Ocean caused by sea-ice expansion at the LGM. Both the Gulf Stream and the Kuroshio are intensified due to the overall increase of wind stress over the subtropical oceans. The intensified zonal wind stress and southward shift of its maximum in the Southern Ocean effectively enhances the transport of the Antarctic Circumpolar Current (ACC) by more than 50%. Simulated SSTs are lowered by up to 8 °C in the midlatitudes. Simulated conditions in the North Atlantic are warmer and with less sea-ice than indicated by CLIMAP again, in agreement with more recent estimates. The increased meridional SST gradient at the LGM results in an enhanced Hadley Circulation and increased midlatitude storm track precipitation. The increased baroclinic storm activity also intensifies the meridional atmospheric heat transport. A sensitivity experiment shows that about half of the simulated tropical cooling at the LGM originates from reduced atmospheric concentrations of greenhouse gases.

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Resilience of rice cropping systems to potential global climate change will partly depend on temperature tolerance of pollen germination (PG) and tube growth (PTG). Germination of pollen of high temperature susceptible Oryza glaberrima Steud. (cv. CG14) and O. sativa L. ssp. indica (cv. IR64) and high temperature tolerant O. sativa ssp. aus (cv. N22), was assessed on a 5.6-45.4°C temperature gradient system. Mean maximum PG was 85% at 27°C with 1488 μm PTG at 25°C. The hypothesis that in each pollen grain, minimum temperature requirements (Tn) and maximum temperature limits (Tx) for germination operate independently was accepted by comparing multiplicative and subtractive probability models. The maximum temperature limit for PG in 50% of grains (Tx(50)) was lowest (29.8°C) in IR64 compared with CG14 (34.3°C) and N22 (35.6°C). Standard deviation (sx) of Tx was also low in IR64 (2.3°C) suggesting that the mechanism of IR64's susceptibility to high temperatures may relate to PG. Optimum germination temperatures and thermal times for 1mm PTG were not linked to tolerating high temperatures at anthesis. However, the parameters Tx(50) and sx in the germination model define new pragmatic criteria for successful and resilient PG, preferable to the more traditional cardinal (maximum and minimum) temperatures.