Identification of differentially expressed genes in pathways of cerebral neurotransmission of anovulatory mice

Polycystic ovary syndrome is the classic example of loss of functional cyclicity and anomalous feedback. In this case, the excessive extra-glandular production and conversion of androgens to estrogens are the pathophysiological basis of the chronic anovulation. The literature describes an experimental model of the polymicrocystic ovary in obese diabetic mice with insulin resistance. The fact that these animals exhibit obesity, insulin resistance, and infertility demonstrates their skill as an experimental model for polycystic ovary. A recent study using long protocol for up to 40 weeks showed that anovulatory and obese mice transplanted with adipose tissue from animals with normal weight have multiple changes in their phenotype. These changes include reduction of body weight, prevention of obesity, insulin level normalization, and insulin tolerance tests, preventing the elevation of steroids and especially the reversal of fertility restoration with anovulation. Considering that there are close relationships between the ovulation process and the central nervous system, we propose to evaluate the gene expression levels of 84 different genes involved in neurotransmission and insulin pathways in addition to examining the neurolipidosis differential murine brain before and after reversal of anovulation. The present study showed changes in gene expression of molecular markers in brain tissue of animals for brain neurotransmission pathways as well as pathways for insulin. GABAergic genes, muscarinic, serotonin receptors, receptor tyrosine kinase, and genes of interleukin 6 showed overexpression profile. There was also a change in the lipid content in anovulatory brain, obesity, and insulin resistant mice (Ob-/Ob-) compared with controls. The re-introduction of leptin in these animals appears to reverse, at least in part, this profile.Univ Fed Sao Paulo, Lab Ginecol Mol, Sao Paulo, SP, BrazilUniv Fed Sao Paulo, Lab Ginecol Mol, Sao Paulo, SP, BrazilWeb of Scienc

THERMODYNAMIC PROPERTIES CALCULATION USING A MULTIOBJECTIVE APPROACH IN ESTIMATING THE PARAMETERS OF THE GEOS3C EQUATION OF STATE

Since van der Waals' first publication, a lot of equations of state have been proposed to represent the PVT behavior of pure compounds, as is the case with GEOS3C, which is a new form of generalized cubic equation of state that uses a temperature function dependent on three adjustable empirical parameters. In order to obtain the parameters that lead to the lowest errors of vapor pressure and saturated liquid volume predictions, it is possible to turn this problem into a multiobjective optimization problem. In this context, a modified MOPSO algorithm was employed. This method has the main advantage to provide a set of solutions that show the existing conflict in the attempt to minimize the properties of interest. Substances from different chemical families were used to evaluate the methodology proposed in this work and comparisons against experimental data were made. Results showed that the values obtained through multiobjective optimization for GEOS3C adjustable parameters provide better or equivalent predictions for all calculated thermodynamic properties. In addition, it was possible to observe a correlation between the parameters in the viable regions of the Pareto fronts: C1 assuming a constant value, whereas C2 and C3 are linearly dependent on each othe