Animal models of memory have been considered as the subject of many scientific publications at least since the beginning of the twentieth century. In humans, memory is often accessed through spoken or written language, while in animals, cognitive functions must be accessed through different kind of behaviors in many specific, experimental models of memory and learning. Among them, the novel object recognition test can be evaluated by the differences in the exploration time of novel and familiar objects. Its application is not limited to a field of research and enables that various issues can be studied, such as the memory and learning, the preference for novelty, the influence of different brain regions in the process of recognition, and even the study of different drugs and their effects. This paper describes the novel object recognition paradigms in animals, as a valuable measure of cognition. The purpose of this work was to review the neurobiology and methodological modifications of the test commonly used in behavioral pharmacology.

Experimental evolution is a powerful tool to understand the adaptive potential of populations under environmental change. Here, we study the importance of the historical genetic background in the outcome of evolution at the genome-wide level. Using the natural clinal variation of Drosophila subobscura, we sampled populations from two contrasting latitudes (Adraga, Portugal and Groningen, Netherlands) and introduced them in a new common environment in the laboratory. We characterized the genome-wide temporal changes underlying the evolutionary dynamics of these populations, which had previously shown fast convergence at the phenotypic level, but not at chromosomal inversion frequencies. We found that initially differentiated populations did not converge either at genome-wide level or at candidate SNPs with signs of selection. In contrast, populations from Portugal showed convergence to the control population that derived from the same geographical origin and had been long-established in the laboratory. Candidate SNPs showed a variety of different allele frequency change patterns across generations, indicative of an underlying polygenic basis. We did not detect strong linkage around candidate SNPs, but rather a small but long-ranging effect. In conclusion, we found that history played a major role in genomic variation and evolution, with initially differentiated populations reaching the same adaptive outcome through different genetic routes.

Adaptation to increasingly warmer environments may be critical to avoid extinction. Whether and how these adaptive responses can arise is under debate. Though several studies have tackled evolutionary responses under different thermal selective regimes, very few have specifically addressed the underlying patterns of thermal adaptation under scenarios of progressive warming conditions. Also, considering how much past history affects such evolutionary response is critical. Here, we report a long-term experimental evolution study addressing the adaptive response of Drosophila subobscura populations with distinct biogeographical history to two thermal regimes. Our results showed clear differences between the historically differentiated populations, with adaptation to the warming conditions only evident in the low latitude populations. Furthermore, this adaptation was only detected after more than 30 generations of thermal evolution. Our findings show some evolutionary potential of Drosophila populations to respond to a warming environment, but the response was slow and population specific, emphasizing limitations to the ability of ectotherms to adapt to rapid thermal shifts.

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This paper describes our approach to participate on SemEval2016 Task12: Clinical TempEval. Our system was based on IBEnt, a framework to identify chemical entities and their relations in text using machine learning techniques. This system has two modules, one to identify chemical entities, and other to identify the pairs of entities that represent a chemical interaction in the same text. In this work we adapted both IBEnt modules to extract temporal expressions, event expressions and relations, by creating new CRF classifiers, lists and rules. The top result of our system was in phase2 for the identification of narrative container relations where it obtained the maximum score of precision (0.823) from all participants.

Cork oak (Quercus suber L.) is a valuable forest species in the western Mediterranean Basin due to its ecological value and the production of cork (a renewable natural material). Cork quality depends on the genetic background and cork oak environment, which has long been recognized. As no cork oak genetic trials with pedigree information were available, the inference of the genetic relatedness between individuals from molecular markers can potentially be applied to natural populations. This work aimed to investigate the potential of performing kinship prediction and pedigree reconstruction by SNP genotyping a natural cork oak population. A total of 494 trees located in Portugal were genotyped with 8K SNPs. The raw SNP set was filtered differently, producing four SNP sets that were further filtered by missing data, genotype frequency, and minor allele frequency. For each set, an identity by descent (IBD) matrix was generated to perform the relationship prediction, revealing from 22,114 to 23,859 relationships. Familial categories from the first to the third degree were able to be assigned. The feasibility of SNP genotyping for future studies on the kinship analysis and pedigree reconstruction of cork oak populations was demonstrated. The information produced may be used in further breeding and conservation programs for cork oak.

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Current rising temperatures are threatening biodiversity. It is therefore crucial to understand how climate change impacts on male and female fertility and whether evolutionary responses can help in coping with heat stress. We use experimental evolution to study male and female fertility during real-time evolution of two historically differentiated populations of Drosophila subobscura under different thermal selection regimes for 23 generations. We aim to (1) tease apart sex-specific differences in fertility after exposure to warming conditions during development, (2) test whether thermal selection can enhance fertility under thermal stress, and (3) address the role of historically distinct genetic backgrounds. Contrary to expectations, heat stress during development had a higher negative impact on female fertility than on male fertility. We did not find clear evidence for enhanced fertility in male or females evolving under warming conditions. Population history had a clear impact on fertility response under thermal stress, particularly in males with those from lower latitude presenting better performance than their higher latitude counterparts. We show that the impact of thermal stress on fertility varies between traits, sexes and genetic backgrounds. Incorporating these several levels of variation is crucial for a deeper understanding of how fertility evolves under climate change.