Computational multivariate modelling of electrical activity of the porcine uterus during spontaneous and hormone-induced oestrus.


Journal

Experimental physiology
ISSN: 1469-445X
Titre abrégé: Exp Physiol
Pays: England
ID NLM: 9002940

Informations de publication

Date de publication:
03 2019
Historique:
received: 29 10 2018
accepted: 03 01 2019
pubmed: 8 1 2019
medline: 27 8 2019
entrez: 8 1 2019
Statut: ppublish

Résumé

What is the central question of this study? Does oestrous cycle synchronization influence myoelectrical activity of porcine myometrium? What is the main finding and its importance? Exogenous hormones used to synchronize oestrus in pigs altered myoelectrical activity, which was effectively modelled. Higher-order multivariate statistic modelling provided evidence of similar activity in both types of oestrus, but a larger order of EMG signals during induced oestrus. Higher-order statistical analysis of the probabilistic model suggests the beginning of the early follicular phase and the mid-luteal phase to be most important in evaluation of the natural patterns of myoelectrical activity. Higher-order multivariate cumulants are more informative than classical statistics in characterization of myoelectrical activity changes in porcine myometrium. In pig production units, control of the oestrous cycle and synchronization of ovulation have become routine herd management procedures. During the oestrous cycle, in both induced and spontaneous conditions, the ovaries and the uterus undergo hormone-dominated physiological changes, which are consistent with the hypothesis that there is a functional role of uterine contractions in promoting fertilization. We have used electromyography to determine whether the use of exogenous hormones, such as equine chorionic gonadotrophin and human chorionic gonadotrophin, which have the potential to control the timing of ovulation in female pigs, changes the multivariate relationships between parameters of electrical bursts and modulates the patterns of myoelectrical activity. We used the mathematical approach of higher-order multivariate cumulants in complex modelling of the myometrial electrical activity. The experiment was conducted on 12 mature Polish Landrace sows, and uterine activity was recorded during both spontaneous and induced oestrous cycles. The burst parameters were determined using six features in the time domain and, after Fast Fourier transformation, in the frequency domain. Evaluation of myoelectrical activity patterns was conducted based on classical univariate statistical methods and multivariate probabilistic modelling. The classical statistical approach indicated weaker myoelectrical activity after hormonal stimulation, whereas the higher-order multivariate statistical model showed evidence of similar status of activity and a larger order of signals during induced oestrus. Routine oestrous cycle synchronization affects the multivariate probabilistic model of myometrial electrical activity.

Identifiants

pubmed: 30615243
doi: 10.1113/EP087451
doi:

Substances chimiques

Chorionic Gonadotropin 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Pagination

322-333

Informations de copyright

© 2019 The Authors. Experimental Physiology © 2019 The Physiological Society.

Auteurs

Malgorzata Domino (M)

Department of Large Animal Diseases with Clinic, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - Szkola Glowna Gospodarstwa Wiejskiego, Nowoursynowska 100, 02-797, Warsaw, Poland.
Veterinary Research Centre and Center for Biomedical Research, Faculty of Veterinary Medicine, WULS - SGGW, Nowoursynowska 100, 02-797, Warsaw, Poland.

Krzysztof Domino (K)

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100, Gliwice, Poland.

Bartosz Pawlinski (B)

Department of Large Animal Diseases with Clinic, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - Szkola Glowna Gospodarstwa Wiejskiego, Nowoursynowska 100, 02-797, Warsaw, Poland.
Veterinary Research Centre and Center for Biomedical Research, Faculty of Veterinary Medicine, WULS - SGGW, Nowoursynowska 100, 02-797, Warsaw, Poland.

Maria Sady (M)

Department of Large Animal Diseases with Clinic, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - Szkola Glowna Gospodarstwa Wiejskiego, Nowoursynowska 100, 02-797, Warsaw, Poland.
Veterinary Research Centre and Center for Biomedical Research, Faculty of Veterinary Medicine, WULS - SGGW, Nowoursynowska 100, 02-797, Warsaw, Poland.

Magdalena Gajewska (M)

Veterinary Research Centre and Center for Biomedical Research, Faculty of Veterinary Medicine, WULS - SGGW, Nowoursynowska 100, 02-797, Warsaw, Poland.

Zdzislaw Gajewski (Z)

Department of Large Animal Diseases with Clinic, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - Szkola Glowna Gospodarstwa Wiejskiego, Nowoursynowska 100, 02-797, Warsaw, Poland.
Veterinary Research Centre and Center for Biomedical Research, Faculty of Veterinary Medicine, WULS - SGGW, Nowoursynowska 100, 02-797, Warsaw, Poland.

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