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Modelling KNDy neurons and gonadotropin-releasing hormone pulse generation.
Plain, Zoe; Voliotis, Margaritis; McArdle, Craig A; Tsaneva-Atanasova, Krasimira.
Afiliação
  • Plain Z; Department of Mathematics and Living Systems Institute, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
  • Voliotis M; Department of Mathematics and Living Systems Institute, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
  • McArdle CA; University of Bristol, Bristol, UK.
  • Tsaneva-Atanasova K; Department of Mathematics and Living Systems Institute, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
Curr Opin Endocr Metab Res ; 27: 100407, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36632147
ABSTRACT
The pulsatile release of gonadotropin-releasing hormone (GnRH) and its frequency are crucial for healthy reproductive function. To understand what drives GnRH pulses, a combination of experimental and mathematical modelling approaches has been used. Early work focussed on the possibility that GnRH pulse generation is an intrinsic feature of GnRH neurons, with autocrine feedback generating pulsatility. However, there is now ample evidence suggesting that a network of upstream neurons secreting kisspeptin, neurokinin-B and dynorphin are the source of this GnRH pulse generator. The interplay of slow positive and negative feedback via neurokinin-B and dynorphin, respectively, allows the network to act as a relaxation oscillator, driving pulsatile secretion of kisspeptin, and consequently, of GnRH and LH. Here, we review the mathematical modelling approaches exploring both scenarios and suggest that with pulsatile GnRH secretion driven by the KNDy pulse generator, autocrine feedback still has the potential to modulate GnRH output.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article