Distribution of Galanin Receptor-2 Immunoreactive Neurones in the Ovine Hypothalamus: No Evidence for Involvement in the Control of Gonadotrophin-Releasing Hormone Secretion
ABSTRACT Galanin is a small neuropeptide that mediates its effects via three receptor isoforms: galanin receptor-1, galanin receptor-2 and galanin receptor-3 (Gal-R1, Gal-R2 and Gal-R3). Galanin is thought to be an important intermediate in signalling in the hypothalamic-pituitary-gonadal axis and has been widely detected in the ovine hypothalamus. The expression of galanin and Gal-R1 has been reported to fluctuate during the reproductive cycle. Although the distribution of Gal-R1 has been determined in the ovine hypothalamus, the distribution of Gal-R2 was hitherto unknown. Using immunohistological and immunofluorescence techniques, we have mapped the distribution of Gal-R2 in the ovine hypothalamus, collected during the follicular phase of the oestrous cycle and examined colocalisation of Gal-R2 with oestrogen receptor alpha (ERalpha) and gonadotrophin-releasing hormone (GnRH). Gal-R2 was expressed in several regions of the hypothalamus (supraoptic nucleus, paraventricular nucleus, ventromedial nucleus, arcuate nucleus) but not as widely expressed as Gal-R1. Areas of Gal-R2 expression overlapped with those reported for Gal-R1. We observed that, in certain defined regions of the hypothalamus, up to 50% of neurones that express Gal-R2 also express ERalpha. No neurones coexpressed Gal-R2 and GnRH. Thus, we conclude that, in follicular phase animals, this receptor plays little or no role in direct intermediary signal transmission in GnRH-mediated control of the reproductive cycle.
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ABSTRACT: The neurotransmitters/neuromodulators galanin (GAL) and galanin-like peptide (GALP) are known to operate through three G protein-coupled receptors, GALR1, GALR2 and GALR3. The aim of this study was to investigate changes in expression of mRNA for galanin, GALP and GALR1-3 in the hypothalamus and pituitary gland, of male and female sheep, to determine how expression changed in association with growth and the attainment of reproductive competence. Tissue samples from the hypothalami and pituitary glands were analysed from late foetal and pre-pubertal lambs and adult sheep. Although mRNA for galanin and GALR1-3 was present in both tissues, at all ages and in both genders, quantification of GALP mRNA was not possible due to its low levels of expression. mRNA expression for both galanin and its receptors was seen to change significantly in both tissues as a function of age. Specifically, hypothalamic galanin mRNA expression increased with age in the male, but decreased with age in the female pituitary gland. mRNA expression for all receptors increased between foetal and pre-pubertal age groups and decreased significantly between pre-pubertal and adult animals. The results indicate that the expression of mRNA for galanin and its receptors changes dynamically with age and those significant differences exist with regard to tissue type and gender. These changes suggest that galaninergic neuroendocrine systems could be involved in the regulation of ovine growth and or the development of reproductive competence. The roles played by these systems in the sheep, however, may differ from other species, in particular the neuroendocrine link between nutrition and reproduction and GALR1's role in pituitary signalling.Reproduction 11/2008; 137(1):141-50. DOI:10.1530/REP-08-0266
Conference Paper: Optimal Control with Multiple Objectives: The H2 Case[Show abstract] [Hide abstract]
ABSTRACT: Most control system design problems involve making tradeoffs among competing objectives. In this paper we consider the control system synthesis problem that arises when the objective is to find a controller such that seveal closed loop transfer functions are small in an appropriate sense. To be more precise, given a linear-time invariant plant, the objective is to find all stabilizing compensators that are noninferior (or Pareto-optimal) with respect to a vector-valued H 2 performance criterion. It is shown that this multiple criteria Optimization problem can be reduced to a simultaneous model matching problem in a Hilbert space. Moreover, state-space formulas are given to solve this model matching problem. We also show that in some particular cases non-inferior controllers have the same order as that of the given plant, and in these cases the above state-space formulae can be further simplified.American Control Conference, 1989; 07/1989
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ABSTRACT: The long-term cellular effects of estrogens are mediated by nuclear estrogen receptors which act as transcription factors to regulate gene expression. Hypothalamic targets of estrogen action include luteinizing hormone-releasing hormone-secreting neurons controlling reproduction in vertebrates. Microarray analysis and qRT-PCR studies were performed on GT1-7, immortalized LHRH neurons after 17beta-estradiol treatment to reveal the nature of estrogen-regulated genes and the time course of changes in their expression profile. More than 1000 transcripts showed robust responses to estrogen treatment and the majority of responding genes were up-regulated. Early-responding genes showed altered expression 0.5-2h after estrogen exposure, whereas late-responding genes changed after 24-48h treatment. Up-regulated genes encoded transcription factors, molecules involved in cellular movement, cell death, immune response, neurotransmitter and neuropeptide receptors, ion channels and transporters. The 17beta-estradiol modulation of 12 genes - representing characteristic gene clusters - has been confirmed by qRT-PCR. Our studies highlighted diverse gene networks, cell regulatory mechanisms and metabolic pathways through which estrogen may alter gene expression in immortalized LHRH neurons. The findings also support the notion that genomic effects of estrogen targeting in vivo directly the LHRH neuronal network of mammals play an important role in the central feedback regulation of the reproductive axis by estrogen.Neurochemistry International 12/2008; 54(2):119-34. DOI:10.1016/j.neuint.2008.11.003 · 2.65 Impact Factor