Mechanisms and development of self–other distinction in dyads and groups

This opinion piece offers a commentary on the four papers that address the theme of the development of self and other understanding with a view to highlighting the important contribution of developmental research to understanding of mechanisms of social cognition. We discuss potential mechanisms linking self–other distinction and empathy, implications for grouping motor, affective and cognitive domains under a single mechanism, applications of these accounts for joint action and finally consider self–other distinction in group versus dyadic settings.     

Genetic structure of a wide-spectrum chicken gene pool

The genetic structure of 65 chicken populations was studied using 29 simple sequence repeat loci. Six main clusters which corresponded to geographical origins and histories were identified: Brown Egg Layers; predominantly Broilers; native Chinese breeds or breeds with recent Asian origin; predominantly breeds of European derivation; a small cluster containing populations with no common history and populations that had breeding history with White Leghorn. Another group of populations that shared their genome with several clusters was defined as 'Multi-clusters'. Gallus gallus gallus (Multi-clusters), one of the subspecies of the Red Jungle Fowl, which was previously suggested to be one of the ancestors of the domesticated chicken, has almost no shared loci with European and White Egg layer populations. In a further sub-clustering of the populations, discrimination between all the 65 populations was possible, and relationships between each were suggested. The genetic variation between populations was found to account for about 34% of the total genetic variation, 11% of the variation being between clusters and 23% being between populations within clusters. The suggested clusters may assist in future studies of genetic aspects of the chicken gene pool.     

On the variability of respiration in terrestrial ecosystems: moving beyond Q10

Respiration, which is the second most important carbon flux in ecosystems following gross primary productivity, is typically represented in biogeochemical models by simple temperature dependence equations. These equations were established in the 19th century and have been modified very little since then. Recent applications of these equations to data on soil respiration have produced highly variable apparent temperature sensitivities. This paper searches for reasons for this variability, ranging from biochemical reactions to ecosystem‐scale substrate supply. For a simple membrane‐bound enzymatic system that follows Michaelis–Menten kinetics, the temperature sensitivities of maximum enzyme activity (V_max) and the half‐saturation constant that reflects the affinity of the enzyme for the substrate (K_m) can cancel each other to produce no net temperature dependence of the enzyme. Alternatively, when diffusion of substrates covaries with temperature, then the combined temperature sensitivity can be higher than that of each individual process. We also present examples to show that soluble carbon substrate supply is likely to be important at scales ranging from transport across membranes, diffusion through soil water films, allocation to aboveground and belowground plant tissues, phenological patterns of carbon allocation and growth, and intersite differences in productivity. Robust models of soil respiration will require that the direct effects of substrate supply, temperature, and desiccation stress be separated from the indirect effects of temperature and soil water content on substrate diffusion and availability. We speculate that apparent Q₁₀ values of respiration that are significantly above about 2.5 probably indicate that some unidentified process of substrate supply is confounded with observed temperature variation.     

Biodiversity and ecosystem functioning: It is time for dispersal experiments

The experimental study of the relationship between biodiversity and ecosystem function has mainly addressed the effect of species and number of functional groups. In theory, this approach has mainly focused on how extinction affects function, whereas dispersal limitation of ecosystem function has been rarely discussed. A handful of seed introduction experiments, as well as numerous observations of the effects of long‐distance dispersal of alien species, indicate that ecosystem function may be strongly determined by dispersal limitation at the local, regional and/or global scales. We suggest that it is time to replace biodiversity manipulation experiments, based on random draw of species, with those addressing realistic scenarios of either extinction or dispersal. Experiments disentangling the dispersal limitation of ecosystem function should have to take into account the probability of arrival. The latter is defined as the probability that a propagule of a particular species will arrive at a particular community. Arrival probability depends on the dispersal ability and the number of propagules of a species, the distance a species needs to travel, and the permeability of the matrix landscape. Current databases, in particular those in northwestern and central Europe now enable robust estimation of arrival probability in plant communities. We suggest a general hypothesis claiming that dispersal limitation according to arrival probability will have ecosystem‐level effects different from those arising due to random arrival. This hypothesis may be rendered more region‐, landscape‐ or ecosystem‐specific by estimating arrival probabilities for different background conditions.     

Development and characterization of SSR markers in lychee (Litchi chinensis)

Sixteen microsatellite loci were isolated from lychee (Litchi chinensis), all of which exhibited polymorphism (two or three alleles per locus), with levels of heterozygosity ranging from 0.021 to 0.900. These loci can help assess the genetic structure of lychee.     

Microsatellite markers for Sachalin fir (Abies sachalinensis Masters)

We developed eight polymorphic microsatellite markers from the Sachalin fir (Abies sachalinensis Masters). The number of alleles per locus ranged from eight to 31, with an average of 21.4. The observed and expected heterozygosities ranged from 0.656 to 0.937 and from 0.710 to 0.945, respectively. These markers will be available for population genetic studies and parentage analysis.     

A genetic and spatial Bayesian analysis of mastitis resistance

A nationwide health card recording system for dairy cattle was introduced in Norway in 1975 (the Norwegian Cattle Health Services). The data base holds information on mastitis occurrences on an individual cow basis. A reduction in mastitis frequency across the population is desired, and for this purpose risk factors are investigated. In this paper a Bayesian proportional hazards model is used for modelling the time to first veterinary treatment of clinical mastitis, including both genetic and environmental covariates. Sire effects were modelled as shared random components, and veterinary district was included as an environmental effect with prior spatial smoothing. A non-informative smoothing prior was assumed for the baseline hazard, and Markov chain Monte Carlo methods (MCMC) were used for inference. We propose a new measure of quality for sires, in terms of their posterior probability of being among the, say 10% best sires. The probability is an easily interpretable measure that can be directly used to rank sires. Estimating these complex probabilities is straightforward in an MCMC setting. The results indicate considerable differences between sires with regards to their daughters disease resistance. A regional effect was also discovered with the lowest risk of disease in the south-eastern parts of Norway.     

Familial breast/ovarian cancer and BRCA1/2 genetic screening: the role of immunohistochemistry as an additional method in the selection of patients.

Only 20-25% of families screened for BRCA1/2 mutations are found positive. Because only a positive result is informative, we studied the role of BRCA1/2 immunohistochemistry as an additional method for patient selection. From 53 high-risk-affected probands, 18 (34%) had available paraffin blocks of their tumors and were selected for this study. Mutation screening was done by conformation-sensitive gel electrophoresis and multiplex ligation-dependent probe amplification. For immunohistochemistry, 21 neoplastic specimens (15 breast carcinomas, 5 ovary neoplasms, and 1 rectal adenocarcinoma) were analyzed with BRCA1 (monoclonal antibody, Ab-1, oncogene) and BRCA2 (polyclonal antibody, Ab-2, oncogene) antibodies. Absence of the BRCA1 protein was confirmed in negative tumors by Western blotting. Seven patients were positive for BRCA1/2 mutations: 5 for BRCA1 and 2 for BRCA2. Four out of five positive patients had tumors negative for BRCA1 immunostaining, and the remaining 13 BRCA1-negative patients had positive BRCA1 immunostaining in all tumor samples. Sensitivity to predict for BRCA1 mutation carriers was 80%, and specificity was 100%, with a positive predictive value of 100% and a negative predictive value of 93%. This correlation was statistically significant (p=0.001). No correlation was observed for BRCA2. If larger studies confirm these results, high-risk patients with BRCA1-negative tumors should be screened first for this gene.