Influence of ionic strength and pH on the interaction between high-affinity heparin and antithrombin

Binding constants for the binding of high-affinity heparin to antithrombin at different ionic strengths were determined by fluorescence titrations and were also estimated from dissociation curves of the heparin-antithrombin complex. These curves were monitored by near-ultraviolet circular dichroism or fluorescence. The dependence of the binding constant on the activity of NaCl suggested that maximally 5–6 charged groups are directly involved in the interaction between the two macromolecules. Major pH-dependent changes of the interaction, as evident by changes of the spectroscopic properties of the complex between the molecules, were found to occur below pH 5.5 and above pH 8.5. The acid change, which was irreversible, was most likely caused by an irreversible conformational change of antithrombin. At alkaline pH, however, the gross conformation of antithrombin was stable up to pH 12, while the affinity of high-affinity heparin for antithrombin began to decrease markedly at pH 8.5. The dissociation curve, which was reversible, had a midpoint around pH 9.5. This is compatible with the loss of affinity being caused by either a local conformational change, by ionization of tyrosine or by titration of one or more amino groups.     

Plant litter feedback and population dynamics in an annual plant,<Emphasis Type="Italic"> Cardamine pensylvanica</Emphasis>

The presence of litter has the potential to alter the population dynamics of plants. In this paper, we explore the effects of litter on population dynamics using a simple experimental laboratory system with populations of the annual crucifer, Cardamine pensylvanica. Using a factorial experiment with four densities and three litter levels, we determined the effect of litter on biomass and plant fecundity, and the life stages responsible for these changes in yield. Although litter had significant effects on seed germination and on seedling survivorship, we show, using a population dynamics model, that these effects were not demographically significant. Rather, the potential effect of litter on population dynamics resulted almost entirely from its effect on biomass. Persistent litter suppressed plant biomass and apparently removed the direct density effect present in the absence of litter. Thus, litter changed the shape of the recruitment curve from slightly humped to asymptotic. In addition to changing the shape of the recruitment curve, litter reduced the carrying capacity of the populations. Thus, the population dynamics model indicated that not all statistically significant responses were dynamically significant. Given the potential complexity of litter effects, simple population models provide a powerful tool for understanding the potential consequences of short-term responses. Received: 8 September 1999 / Accepted: 5 April 2000     

Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series

1. The growing pace of environmental change has increased the need for large‐scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.
2. We used multi‐annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.
3. We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full‐analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.
4. This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.

     

Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

Analysis of Multiply Matched Retrospective Studies When Risk Factor Under Study is Discrete,With Two or More Levels

The odds ratio is known to closely approximate the relative risk when the disease is rare. Logistic regression models are often used to estimate such odds ratios, but here a different model is used which avoids the assumptions implicit in logistic modelling; it also has the advantage of providing a test of homogeneity for odds rat os in situations where the logistic model cannot.     

Joint multiple quantitative trait loci mapping for allometries of body compositions and metabolic traits to body weights in broiler

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F₂ population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.     

Body size and area‐incidence relationships: is there a general pattern?

Aim This paper tests firstly for the existence of a general relationship between body size of terrestrial animals and their incidence across habitat patches of increasing size, and secondly for differences in this relationship between insects and vertebrates. Location The analysis was based on the occupancy pattern of 50 species from 15 different landscapes in a variety of ecosystems ranging from Central European grassland to Asian tropical forest. Methods The area‐occupancy relationship was described by incidence functions that were calculated using logistic regression. A correlation analysis between body size of the species and the patch area referring to the two given points of the incidence function was performed. In order to test for an effect of taxon (insects vs. vertebrates), an analysis of covariance was conducted. Results In all species, the incidence was found to increase with increasing patch area. The macroecological analysis showed a significant relationship between the incidence in habitat patches and the body size of terrestrial animals. The area requirement was found to increase linearly with increasing body size on a log‐log scale. This relationship did not differ significantly between insects and vertebrates. Conclusions The approach highlighted in this paper is to associate incidence functions with body size. The results suggest that body size is a general but rather rough predictor for the area requirements of animals. The relationship seems valid for a wide range of body sizes of terrestrial animals. However, further studies including isolation of habitats as well as additional species traits into the macroecological analysis of incidence functions are needed.