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An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle

After intercourse/insemination, large numbers of sperm are deposited in the female reproductive tract (FRT), triggering a massive recruitment of neutrophils (PMNs) into the FRT, possibly to eliminate excessive sperm via phagocytosis. Some bovine oviductal fluid components (BOFCs) have been shown to...

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Autores principales: Kowsar, Rasoul, Keshtegar, Behrooz, Marey, Mohamed. A., Miyamoto, Akio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493678/
https://www.ncbi.nlm.nih.gov/pubmed/28667317
http://dx.doi.org/10.1038/s41598-017-04841-z
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author Kowsar, Rasoul
Keshtegar, Behrooz
Marey, Mohamed. A.
Miyamoto, Akio
author_facet Kowsar, Rasoul
Keshtegar, Behrooz
Marey, Mohamed. A.
Miyamoto, Akio
author_sort Kowsar, Rasoul
collection PubMed
description After intercourse/insemination, large numbers of sperm are deposited in the female reproductive tract (FRT), triggering a massive recruitment of neutrophils (PMNs) into the FRT, possibly to eliminate excessive sperm via phagocytosis. Some bovine oviductal fluid components (BOFCs) have been shown to regulate in vitro sperm phagocytosis (spermophagy) by PMNs. The modeling approach-based logistic regression (LR) and autoregressive logistic regression (ALR) can be used to predict the behavior of complex biological systems. We, first, compared the LR and ALR models using in vitro data to find which of them provides a better prediction of in vitro spermophagy in bovine. Then, the best model was used to identify and classify the reciprocal effects of BOFCs in regulating spermophagy. The ALR model was calibrated using an iterative procedure with a dynamical search direction. The superoxide production data were used to illustrate the accuracy in validating logit model-based ALR and LR. The ALR model was more accurate than the LR model. Based on in vitro data, the ALR predicted that the regulation of spermophagy by PMNs in bovine oviduct is more sensitive to alpha-1 acid glycoprotein (AGP), PGE2, bovine serum albumin (BSA), and to the combination of AGP or BSA with other BOFCs.
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spelling pubmed-54936782017-07-05 An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle Kowsar, Rasoul Keshtegar, Behrooz Marey, Mohamed. A. Miyamoto, Akio Sci Rep Article After intercourse/insemination, large numbers of sperm are deposited in the female reproductive tract (FRT), triggering a massive recruitment of neutrophils (PMNs) into the FRT, possibly to eliminate excessive sperm via phagocytosis. Some bovine oviductal fluid components (BOFCs) have been shown to regulate in vitro sperm phagocytosis (spermophagy) by PMNs. The modeling approach-based logistic regression (LR) and autoregressive logistic regression (ALR) can be used to predict the behavior of complex biological systems. We, first, compared the LR and ALR models using in vitro data to find which of them provides a better prediction of in vitro spermophagy in bovine. Then, the best model was used to identify and classify the reciprocal effects of BOFCs in regulating spermophagy. The ALR model was calibrated using an iterative procedure with a dynamical search direction. The superoxide production data were used to illustrate the accuracy in validating logit model-based ALR and LR. The ALR model was more accurate than the LR model. Based on in vitro data, the ALR predicted that the regulation of spermophagy by PMNs in bovine oviduct is more sensitive to alpha-1 acid glycoprotein (AGP), PGE2, bovine serum albumin (BSA), and to the combination of AGP or BSA with other BOFCs. Nature Publishing Group UK 2017-06-30 /pmc/articles/PMC5493678/ /pubmed/28667317 http://dx.doi.org/10.1038/s41598-017-04841-z Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Kowsar, Rasoul
Keshtegar, Behrooz
Marey, Mohamed. A.
Miyamoto, Akio
An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
title An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
title_full An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
title_fullStr An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
title_full_unstemmed An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
title_short An autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
title_sort autoregressive logistic model to predict the reciprocal effects of oviductal fluid components on in vitro spermophagy by neutrophils in cattle
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493678/
https://www.ncbi.nlm.nih.gov/pubmed/28667317
http://dx.doi.org/10.1038/s41598-017-04841-z
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