Modeling portal-drained viscera and liver fluxes of essential amino acids in dairy cows.


Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
Dec 2019
Historique:
received: 14 01 2019
accepted: 08 06 2019
pubmed: 16 9 2019
medline: 22 1 2020
entrez: 16 9 2019
Statut: ppublish

Résumé

The objective of this work was to predict essential amino acid (EAA) use and release by the portal-drained viscera (PDV) and liver of dairy cows. Previously derived equations were tested using data assembled from the literature, refit to the data, and modifications were undertaken to determine the best model for each EAA. The refitted model has the same structure as the original equations but is parameterized using a database of group means, as the original equations were derived using a single study with individual cow data and found to be biased. The PDV clearance model predicted portal vein concentrations given inputs of absorbed and arterial fluxes of EAA with root mean squared errors (RMSE) ranging from 3.3 to 12.1% of the observed means, and concordance correlation coefficients (CCC) ranging from 0.86 to 0.99 when using previously reported parameters. The reparameterized model generated from the assembled data set resulted in predictions of EAA portal vein concentrations with RMSE ranging from 3.2 to 8.6% and CCC ranging from 0.93 to 1.00. Slope bias ranged from 12.4 to 55.3% of mean squared errors and was correlated with arterial EAA concentrations. Modifying the model to allow rate constants to vary as a function of arterial EAA concentrations reduced slope bias, resulting in RMSE ranging from 1.9 to 6.5% and CCC from 0.97 to 1.00. Alternatively, splitting the model to account for use of EAA from absorption separately from arterial use resulted in poorer predictions and biologically infeasible parameter estimates. The liver clearance model predicted hepatic vein concentrations from arterial and portal vein input fluxes with RMSE across EAA ranging from 1.9 to 6.8% and CCC ranging from 0.97 to 1.00 when using reported parameters. The reparameterized model generated from the assembled data set resulted in predictions of EAA hepatic vein concentrations with RMSE ranging from 1.9 to 6.7% and CCC ranging from 0.97 to 1.00. Significant slope bias was present for Arg, His, Lys, Phe, Thr, and Val. Altering the model to represent the clearance rate constant as a function of arterial concentrations resulted in RMSE ranging from 1.8 to 6.5% and CCC ranging from 0.97 to 1.00. The combination of PDV and liver clearance models provided predictions of total splanchnic use similar to those of an empirical model representing splanchnic use as a fractional proportion of absorption that had RMSE ranging from 3.0 to 8.6% and CCC ranging from 0.95 to 0.99, with significant slope bias for the majority of EAA.

Identifiants

pubmed: 31521362
pii: S0022-0302(19)30796-9
doi: 10.3168/jds.2019-16302
pii:
doi:

Substances chimiques

Amino Acids 0
Amino Acids, Essential 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

10964-10982

Informations de copyright

Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Auteurs

A J Fleming (AJ)

Department of Dairy Science, Virginia Tech, Blacksburg 24061. Electronic address: adelynm2@vt.edu.

H Lapierre (H)

Agricultural and Agri-Food Canada, Sherbrooke, QC, Canada J1M 0C8.

R Martineau (R)

Agricultural and Agri-Food Canada, Sherbrooke, QC, Canada J1M 0C8.

R R White (RR)

Department of Dairy Science, Virginia Tech, Blacksburg 24061.

M D Hanigan (MD)

Department of Dairy Science, Virginia Tech, Blacksburg 24061.

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Classifications MeSH