Temporal expression of G-protein-coupled receptor 54 (GPR54), gonadotropin-releasing hormones (GnRH), and dopamine receptor D2 (drd2) in pubertal female grey mullet, Mugil cephalus.

The G-protein-coupled receptor 54 (muGPR54) cDNA was cloned from the brain of the grey mullet, and its expression level, as well as those of the gonadotropin-releasing hormones (GnRH1, GnRH2, GnRH3) and dopamine receptor D2 (drd2), in the brain, pituitary and ovary of pubertal fish (early, intermediate, advanced) were determined by real-time quantitative RT-PCR (QPCR). The muGPR54 cDNA has an open reading frame of 1140 bp with a predicted 380 amino acid peptide, containing seven putative transmembrane domains and putative N-glycosylation and protein kinase C phosphorylation sites. QPCR results showed that the early stage of puberty in grey mullet is characterized by significantly high levels of expression of GPR54, GnRH and drd2 in the brain relative to the intermediate and advanced stages, except for GnRH1 that increased at the advanced stage of puberty. In the pituitary, drd2 expression declined significantly at the advanced stage relative to levels at the intermediate stage. Ovarian expression of GPR54 significantly increased from the intermediate stage of puberty relative to the early stage while that of GnRH1 acutely increased at the advanced stage of puberty. The ovarian expression of drd2 decreased as puberty progressed, but the changes were not significant. The results suggest the possible role of GPR54 and GnRH in positively regulating pubertal development in grey mullet and the dopaminergic inhibition of reproductive function mediated by drd2.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.