Differential expression of IGF-I mRNA and peptide in the male and female gonad during early development of a bony fish, the tilapia Oreochromis niloticus

Insulin-like growth factor I (IGF-I) plays a key role in the complex system that regulates bony fish growth, differentiation, and reproduction. The major source of circulating IGF-I is liver, but IGF-I-producing cells also occur in other organs, including the gonads. Because no data are available on the potential production sites of IGF-I in gonad development, developmental stages of monosex breedings of male and female tilapia from 0 day postfertilization (DPF) to 90 DPF were investigated for the production sites of IGF-I at the peptide (immunohistochemistry) and mRNA (in situ hybridization) level. IGF-I mRNA first appeared in somatic cells of the male and female gonad anlage at 7 DPF followed by IGF-I peptide around 9-10 DPF. Gonad anlagen were detected from 7 DPF. Starting at 7 DPF, IGF-I peptide but no IGF-I mRNA was observed in male and female primordial germ cells (PGCs) provided that IGF-I mRNA was not under the detection level, this observation may suggest that IGF-I originates from the somatic cells and is transferred to the PGCs or is of maternal origin. While in female germ cells IGF-I mRNA and peptide appeared at 29 DPF, in male germ cells both were detected as late as at 51-53 DPF. It is assumed that the production of IGF-I in the germ cells is linked to the onset of meiosis that in tilapia ovary starts at around 28 DPF and in testes at around 52-53 DPF. In adult testis, IGF-I mRNA and peptide occurred in the majority of spermatogonia and spermatocytes as well as in Leydig cells, the latter indicating a role of IGF-I in the synthesis of male sex steroids. In adult ovary, IGF-I mRNA and IGF-I peptide were always present in small and previtellogenic oocytes but only IGF-I peptide infrequently occurred in oocytes at the later stages. IGF-I expression appeared in numerous granulosa and some theca cells of follicles at the lipid stage and persisted in follicles with mature oocytes. The results suggest a crucial role of local IGF-I in the formation, differentiation and function of tilapia gonads.

A Mechanistic Latent Variable Model for Estimating Drug Concentrations in the Male Genital Tract

The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.