Isolation and characterization of a protochordate histocompatibility locus

Histocompatibility--the ability of an organism to distinguish its own cells and tissue from those of another--is a universal phenomenon in the Metazoa. In vertebrates, histocompatibility is a function of the immune system controlled by a highly polymorphic major histocompatibility complex (MHC), which encodes proteins that target foreign molecules for immune cell recognition. The association of the MHC and immune function suggests an evolutionary relationship between metazoan histocompatibility and the origins of vertebrate immunity. However, the MHC of vertebrates is the only functionally characterized histocompatibility system; the mechanisms underlying this process in non-vertebrates are unknown. A primitive chordate, the ascidian Botryllus schlosseri, also undergoes a histocompatibility reaction controlled by a highly polymorphic locus. Here we describe the isolation of a candidate gene encoding an immunoglobulin superfamily member that, by itself, predicts the outcome of histocompatibility reactions. This is the first non-vertebrate histocompatibility gene described, and may provide insights into the evolution of vertebrate adaptive immunity.     

Generation time and temporal scaling of bird population dynamics

Theoretical studies have shown that variation in density regulation strongly influences population dynamics, yet our understanding of factors influencing the strength of density dependence in natural populations still is limited. Consequently, few general hypotheses have been advanced to explain the large differences between species in the magnitude of population fluctuations. One reason for this is that the detection of density regulation in population time series is complicated by time lags induced by the life history of species that make it difficult to separate the relative contributions of intrinsic and extrinsic factors to the population dynamics. Here we use population time series for 23 bird species to estimate parameters of a stochastic density-dependent age-structured model. We show that both the strength of total density dependence in the life history and the magnitude of environmental stochasticity, including transient fluctuations in age structure, increase with generation time. These results indicate that the relationships between demographic and life-history traits in birds translate into distinct population dynamical patterns that are apparent only on a scale of generations.     

Nelson–Siegel,Affine and Quadratic Yield Curve Specifications: Which One is Better at Forecasting?

In this paper we compare the in‐sample fit and out‐of‐sample forecasting performance of no‐arbitrage quadratic, essentially affine and dynamic Nelson–Siegel term structure models. In total, 11 model variants are evaluated, comprising five quadratic, four affine and two Nelson–Siegel models. Recursive re‐estimation and out‐of‐sample 1‐, 6‐ and 12‐month‐ahead forecasts are generated and evaluated using monthly US data for yields observed at maturities of 1, 6, 12, 24, 60 and 120 months. Our results indicate that quadratic models provide the best in‐sample fit, while the best out‐of‐sample performance is generated by three‐factor affine models and the dynamic Nelson–Siegel model variants. Statistical tests fail to identify one single best forecasting model class. Copyright © 2011 John Wiley & Sons, Ltd.     

高光谱数据组分信息的盲分解方法

将基于独立成分分析(independent component analysis,ICA)技术的盲分解方法(blind signal separation,BSS)应用于遥感混合像元的定量分解,解决了幅度不确定性问题,实现了从高光谱数据中同时得到定量的组分光谱信息和组分权重信息。通过数值模拟实验提出了光谱反演区间的选择方法,进一步完善了该算法,且讨论了算法的稳健性。以陕西省横山县为试验区,从HYPERION高光谱影像中反演了各像元的植被覆盖度,并利用SPOT5影像进行了精度验证,结果表明该方法具有较高的精度。     

Effect of chlorpromazine and reserpine on the blood platelets of rabbit

Zusammenfassung Chlorpromazin und Reserpin verursachen 5HT-Freisetzung von Thrombocyten. Chlorpromazin verursacht auch morphologische, elektronenoptisch sichtbare Veränderungen der Thrombocyten.

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This investigation was supported in part by The Finnish Council of Medical Research and by U.S. Public Health Service Research Grant M-5832, from the National Institute of Mental Health.