The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

Do different measures of early life socioeconomic circumstances predict adult mortality? Evidence from the British Whitehall II and French GAZEL studies

BACKGROUND: Father's occupational position, education and height have all been used to examine the effects of adverse early life socioeconomic circumstances on health, but it remains unknown whether they predict mortality equally well. METHODS: We used pooled data on 18,393 men and 7060 women from the Whitehall II and GAZEL cohorts to examine associations between early life socioeconomic circumstances and all-cause and cause-specific mortality. RESULTS: During the 20-y follow-up period, 1487 participants died. Education had a monotonic association with all mortality outcomes; the age, sex and cohort-adjusted HR for the lowest versus the highest educational group was 1.45 (95% CI 1.24 to 1.69) for all-cause mortality. There was evidence of a U-shaped association between height and all-cause, cancer and cardiovascular mortality robust to adjustment for the other indicators (HR 1.41, 95% CI 1.03 to 1.93 for those shorter than average and HR 1.36, 95% CI 0.98 to 1.88 for those taller than average for cardiovascular mortality). Greater all-cause and cancer mortality was observed in participants whose father's occupational position was manual rather than non-manual (HR 1.11, 95% CI 1.00 to 1.23 for all-cause mortality), but the risks were attenuated after adjusting for education and height. CONCLUSIONS: The association between early life socioeconomic circumstances and mortality depends on the socioeconomic indicator used and the cause of death examined. Height is not a straightforward measure of early life socioeconomic circumstances as taller people do not have a health advantage for all mortality outcomes.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Greenhouse Gas and Nitrogen Fertilizer Scenarios for U.S. Agriculture and Global Biofuels, June 2011

This analysis uses the 2011 FAPRI-CARD (Food and Agricultural Policy Research Institute–Center for Agricultural and Rural Development) baseline to evaluate the impact of four alternative scenarios on U.S. and world agricultural markets, as well as on world fertilizer use and world agricultural greenhouse gas emissions. A key assumption in the 2011 baseline is that ethanol support policies disappear in 2012. The baseline also assumes that existing biofuel mandates remain in place and are binding. Two of the scenarios are adverse supply shocks, the first being a 10% increase in the price of nitrogen fertilizer in the United States, and the second, a reversion of cropland into forestland. The third scenario examines how lower energy prices would impact world agriculture. The fourth scenario reintroduces biofuel tax credits and duties. Given that the baseline excludes these policies, the fourth scenario is an attempt to understand the impact of these policies under the market conditions that prevail in early 2011. A key to understanding the results of this fourth scenario is that in the absence of tax credits and duties, the mandate drives biofuel use. Therefore, when the tax credits and duties are reintroduced, the impacts are relatively small. In general, the results show that the entire international commodity market system is remarkably robust with respect to policy changes in one country or in one sector. The policy implication is that domestic policy changes implemented by a large agricultural producer like the United States can have fairly significant impacts on the aggregate world commodity markets. A second point that emerges from the results is that the law of unintended consequences is at work in world agriculture. For example, a U.S. nitrogen tax that might presumably be motivated for environmental benefit results in an increase in world greenhouse gas emissions. A similar situation occurs in the afforestation scenario in which crop production shifts from high-yielding land in the United States to low-yielding land and probably native vegetation in the rest of the world, resulting in an unintended increase in global greenhouse gas emissions.

Changes in chromosomal polymorphism and global warming: The case of Drosophila subobscura from Apatin (Serbia)

Abstract In this study, chromosomal inversion polymorphism data for a natural population of Drosophila subobscura from a swampy region near the town of Apatin (Serbia) were compared with data for the same population collected approximately 15 years earlier. The pattern of chromosomal inversion polymorphism changed over time. There were significant increases in the frequency of characteristic southern latitude ("warm" adapted) chromosomal arrangements and significant decreases in the frequency of characteristic northern latitude ("cold" adapted) chromosomal arrangements in the O and U chromosomes. The chromosomal arrangements O3+4 and O3+4+22 (derived from the O3+4 arrangement)showed significant increases in 2008 and 2009 with regard to the 1994 sample. There was also a significant increase (~50%) in the U1+2 arrangement, while U1+8+2 (a typical southern arrangement) was detected for the first time. Since the Apatin swampy population ofD. subobscura has existed for a long time in a stable habitat with high humidity that has not been changed by man our results indicate that natural selection has produced chromosomal changes in response to the increase in temperature that has occurred in the Balkan Peninsula of central southeastern European. Key words: chromosomal inversions, Drosophila subobscura, global warming, karyotypes.

Solid-phase synthesis and DNA binding studies of dichloroplatinum(II) conjugates of dicarba analogues of octreotide as a new anticancer drugs

The first dichloroplatinum(II) conjugates of dicarba analogues of octreotide , which is expected to act as a"tumour-targeting device", have been efficiently synthesized following a stepwise solid-phase approach; these compounds emulate the mechanism of cisplatin since they form a 1,2-intrastrand cross-link with two consecutive guanines of an oligonucleotide.