Use of generalised additive models to categorise continuous variables in clinical prediction

13 P.

The Role of the Demand for Environmental Quality in Driving Transitions to Low-Polluting Energy Sources

4 p.

The Demand for Environmental Quality in Driving Transitions to Low Polluting Energy Sources

38 p.

Is inbreeding avoidance driving female mate choice in Verreaux's sifaka lemurs?

Females of different species might exert female mate choice for different reasons, one of them the aim of avoiding inbreeding. In this study I examine the implication of inbreeding avoidance as a mechanism driving female mate choice in Verreaux’s sifaka lemurs (Propithecus verreauxi). In fact, in this species females are dominant and appear to be able to choose certain males to mate with, while observations indicate that rank, body size, canine size and proportions of fights won are not factors influencing female mate choice. So I hypothesized that females mate choice is driven by inbreeding avoidance in Verreaux’s sifaka lemurs. Tissue and fecal samples were collected in the Kirindy Mitea National Park in western Madagascar as a source of DNA. Parentage was assigned for a sample of the population and relatedness coefficients between dams and sires were estimated and compared to those of between random female and male pairs, dams and other candidate sires within the population and within the groups were the offspring were conceived. I found that there were no significant differences in none of the comparisons which means that Verreaux’s sifaka females do not mate more with males that are more distantly related to them. I concluded that inbreeding avoidance does not appear to be the main force driving female mate choice in Verreaux’s sifaka lemurs and I addressed explanations for these findings. With this study I contribute to our knowledge of female mate choice in lemurs.

Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates

In a multi-target complex network, the links (L-ij) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K-i, K-m, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

158 p.