Altruism in a volatile world

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this record.The evolution of altruism – costly self-sacrifice in the service of others – has puzzled biologists since The Origin of Species. For half a century, attempts to understand altruism have been built on the insight that altruists may help relatives to have extra offspring in order to spread shared genes . This theory – known as inclusive fitness – is founded on a simple inequality termed ‘Hamilton’s rule’. However, explanations of altruism have typically ignored the stochasticity of natural environments, which will not necessarily favour genotypes that produce the greatest average reproductive success. Moreover, empirical data across many taxa reveal associations between altruism and environmental stochasticity, a pattern not predicted by standard interpretations of Hamilton’s rule. Here, we derive Hamilton’s rule with explicit stochasticity, leading to novel predictions about the evolution of altruism. We show that of offspring produced by relatives. Consequently, costly altruism can evolve even if it has a net negative effect on the average reproductive success of related recipients. The selective pressure on volatility suppressing altruism is proportional to the coefficient of variation in population fitness, and is therefore diminished by its own success. Our results formalise the hitherto elusive link between bet-hedging and altruism, and reveal missing fitness effects in the evolution of animal societies.PK was supported by the National Geographic Society (GEF-NE 145-15) and a University of Bristol Research Studentship; ADH was supported by the Natural Environment Research Council (NE/L011921/1); ANR was supported by a European Research Council Consolidator Grant (award no. 682253); and SS was supported by the Natural Environment Research Council (NE/M012913/2)

Estimation of PM10-bound As, Cd, Ni and Pb levels by means of statistical modelling: PLSR and ANN approaches

Air quality assessment regarding metals and metalloids using experimental measurements is expensive and time consuming due to the cost and time required for the analytical determination of the levels of these pollutants. According to the European Union (EU) Air Quality Framework Directive (Directive 2008/50/EC), other alternatives, such as objective estimation techniques, can be considered for ambient air quality assessment in zones and agglomerations where the level of pollutants is below a certain concentration value known as the lower assessment threshold. These conditions occur in urban areas in Cantabria (northern Spain). This work aims to estimate the levels of As, Cd, Ni and Pb in airborne PM10 at two urban sites in the Cantabria region (Castro Urdiales and Reinosa) using statistical models as objective estimation techniques. These models were developed based on three different approaches: partial least squares regression (PLSR), artificial neural networks (ANNs) and an alternative approach consisting of principal component analysis (PCA) coupled with ANNs (PCA-ANN). Additionally, these models were externally validated using previously unseen data. The results show that the models developed in this work based on PLSR and ANNs fulfil the EU uncertainty requirements for objective estimation techniques and provide an acceptable estimation of the mean values. As a consequence, they could be considered as an alternative to experimental measurements for air quality assessment regarding the aforementioned pollutants in the study areas while saving time and resources.The authors gratefully acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness through the Project CMT2010-16068. The authors also thank the Regional Environment Ministry of the Cantabria Government for providing the PM10 samples at the Castro Urdiales and Reinosa sites

Toxicity testing of human assisted reproduction devices using the mouse embryo assay.

Contains fulltext : 81090.pdf (publisher's version ) (Closed access)Systems to assess the toxicity of materials used in human assisted reproduction currently lack efficiency and/or sufficient discriminatory power. The development of 1-cell CBA/B6 F1 hybrid mouse embryos to blastocysts, expressed as blastocyst rate (BR), is used to measure toxicity. The embryos were divided into control and test groups, and were exposed to either control medium or to a potentially toxic test medium. Inferences on toxicity were based on differences in BR between the two groups. The mouse embryo assay followed a stratified (mouse), randomized (embryo), and balanced (equal number of embryos per group and per mouse) design. The number of embryos needed was calculated using power analysis. The basal BR of the hybrid strain was determined in a historical population. Sixty-nine mouse embryos per group were required to detect toxic materials with sufficient sensitivity and to account for the considerable inter-mouse variation in blastocyst development. Fifty-two samples, divided over batches of seven different products were tested before use in the study IVF centre and five of these were found to be toxic. This test system, presented as the Nijmegen mouse embryo assay (NMEA), can be used to detect embryo-toxic materials in daily IVF practice, and this report may provide a starting point for standardization