Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

Approximate Linear Confidence and Curvature of a Kinetic Model of Dodecanedioic Acid in Humans

Academic Article
Publication Date:
2005
abstract:
Dicarboxylic acids with an even number of carbon atoms have been proposed as an alternate energy substrate for enteral or parenteral nutrition in the acutely ill patient, due to their water solubility and their yielding TCA cycle intermediates upon ?-oxidation. In the present work, a nonlinear compartmental model of the kinetics of dodecanedioic acid is developed, and its parameters are estimated from time concentration experimental observations obtained from six healthy volunteers undergoing a per os administration of 3 g of the substance. Although the model is linear in the transfer of the free substance from plasma to the tissues, the exchange between gut and plasma compartments is represented as a saturable function. Albumin binding is then incorporated to obtain the final model in terms of the measured total concentrations. Estimates of the model's structural parameters were computed for each experimental subject, and the usual single-subject approximate confidence regions for the parameters were derived by inversion of the Hessian at the optimum. To verify the applicability of this approximation, the nonlinearity of the expectation surface at the optimum was measured by computing the normal (intrinsic) component of curvature. Because the model curvature was excessive in all subjects, the usual approximation could not be trusted to provide acceptable approximations to the parameter confidence regions. A suitable Monte Carlo simulation yielded empirical joint parameter distributions from which the approximate parameter variances could finally be obtained.
Iris type:
01.01 Articolo in rivista
Keywords:
mathematical models; metabolism; kinetics; nonlinear parameter estimation; confidence regions
List of contributors:
DE GAETANO, Andrea; Panunzi, Simona
Authors of the University:
DE GAETANO ANDREA
PANUNZI SIMONA
Handle:
https://iris.cnr.it/handle/20.500.14243/454975
Published in:
ENDOCRINOLOGY AND METABOLISM (ONLINE)
Journal
  • Overview

Overview

URL

http://ajpendo.physiology.org/content/289/5/E915.abstract
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)