The evolution of senescence from a comparative perspective

Summary 1. Comparative studies of ageing address the evolutionary lability of the rate of ageing as an indication of potential for, and constraints on, the extension of life span. 2. Experimental studies on ageing have focused on damage induced by reactive oxygen species (ROS) and other stresses, and on the mechanisms to prevent or repair this damage. Research on animal models has revealed genes with large effects on life span. However, the relevance of some animal models to human ageing is unclear and it is not known whether evolved differences in ageing involve such major gene effects. 3. Studies on the demography of populations of vertebrates in the wild show that animals suffer from senescence in nature. Variation in the rate of ageing is consistent with evolutionary theory in that senescence is delayed in populations that suffer relatively low extrinsic mortality. 4. Populations of longer-lived individuals suffer a higher proportion of ageing-related mortality, and thus stronger selection against early ageing. The presence of ageing-related deaths in these populations suggests a lack of suitable mechanisms that would further extend life span. 5. Similar patterns of ageing-related mortality in wild and captive or domesticated populations indicate that most ageing-related death is caused by intrinsic factors, such as tumours and cardiovascular failure, rather than increasing vulnerability to extrinsic causes of mortality. 6. Studies of several wild populations of long-lived birds suggest that ageing-related mortality is often catastrophic, with individuals maintaining high levels of condition until shortly before their demise. 7. Comparative studies of many species suggest connections between early development and the pattern of ageing later in life, consistent with laboratory studies on variation within individual species. The physiological connections across the life span are not well understood. 8. Comparative studies have provided important insights into the ageing process. However, we still lack information on important issues, including the causes of death in natural populations, the relationship of within-and between-population variation in the rate of ageing, the genetic basis of variation in rate of ageing in natural populations, and detailed longitudinal studies of individual health and reproductive success in relation to age at death

Expansion of the calcium hypothesis of brain aging and Alzheimer's disease: minding the store

-dependent processes and, through somewhat different pathways, in accelerated functional decline during aging and AD

Spatial autocorrelation and the selection of simultaneous autoregressive models

ABSTRACT Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and inference from statistical models. Here, we test the performance of three different simultaneous autoregressive (SAR) model types (spatial error = SAR err , lagged = SAR lag and mixed = SAR mix ) and common ordinary least squares (OLS) regression when accounting for spatial autocorrelation in species distribution data using four artificial data sets with known (but different) spatial autocorrelation structures. Methods We evaluate the performance of SAR models by examining spatial patterns in model residuals (with correlograms and residual maps), by comparing model parameter estimates with true values, and by assessing their type I error control with calibration curves. We calculate a total of 3240 SAR models and illustrate how the best models [in terms of minimum residual spatial autocorrelation (minRSA), maximum model fit ( R 2 ), or Akaike information criterion (AIC)] can be identified using model selection procedures. Results Our study shows that the performance of SAR models depends on model specification (i.e. model type, neighbourhood distance, coding styles of spatial weights matrices) and on the kind of spatial autocorrelation present. SAR model parameter estimates might not be more precise than those from OLS regressions in all cases. SAR err models were the most reliable SAR models and performed well in all cases (independent of the kind of spatial autocorrelation induced and whether models were selected by minRSA, R 2 or AIC), whereas OLS, SAR lag and SAR mix models showed weak type I error control and/or unpredictable biases in parameter estimates. Main conclusions SAR err models are recommended for use when dealing with spatially autocorrelated species distribution data. SAR lag and SAR mix might not always give better estimates of model coefficients than OLS, and can thus generate bias. Other spatial modelling techniques should be assessed comprehensively to test their predictive performance and accuracy for biogeographical and macroecological research

famoz : a software for parentage analysis using dominant, codominant and uniparentally inherited markers

Abstract FAMOZ (an acronym for father/mother) is a software useful in reconstructing parentage for dominant, codominant and uniparentally inherited markers. It is written in C and TclTk languages and is available for Unix, Linux and Windows systems at http://www.pierroton.inra.fr/ genetics/labo/Software/Famoz/index.html. Parameters and assumptions used in the calculations are few and simple. Exclusion and identity probabilities, log-likelihoods of any genetic relationship, potential father and parent or parent pair, half-and full-sibship are calculated based on real or simulated data. Error rates for genotypic mistyping can be introduced. Simulations can be done to build statistical tests for parentage assignment

Large-area topography analysis and near-field Raman spectroscopy using bent fibre probes

Summary We present a method for combined far-field Raman imaging, topography analysis and near-field spectroscopy. Surfaceenhanced Raman spectra of Rhodamine 6G (R6G) deposited on silver nanoparticles were recorded using a bent fibre aperture-type near-field scanning optical microscope (NSOM) operated in illumination mode. Special measures were taken to enable optical normal-force detection for control of the tip-sample distance. Comparisons between far-field Raman images of R6G-covered Ag particle aggregates with topographic images recorded using atomic force microscopy (AFM) indicate saturation effects due to resonance excitation