Landberg2009 - Alkylresorcinol Dose Response

  public model
Model Identifier
BIOMD0000000948
Short description
Pharmacokinetic model of alkylresorcinols. Both plasma AR concentrations and urinary metabolites in 24-h samples showed a dose-response relation to increased AR intake, which strongly supports the hypothesis that ARs and their metabolites may be useful as biomarkers of whole-grain wheat and rye intakes.
Format
SBML (L2V4)
Related Publication
  • Dose response of whole-grain biomarkers: alkylresorcinols in human plasma and their metabolites in urine in relation to intake.
  • Landberg R, Aman P, Friberg LE, Vessby B, Adlercreutz H, Kamal-Eldin A
  • The American journal of clinical nutrition , 1/ 2009 , Volume 89 , Issue 1 , pages: 290-296 , PubMed ID: 19056600
  • Department of Food Science, Swedish University of Agriculture Science, Uppsala, Sweden. rikard.landberg@lmv.slu.se
  • Alkylresorcinols (ARs), phenolic lipids almost exclusively present in the outer parts of wheat and rye grains in commonly consumed foods, have been proposed as specific dietary biomarkers of whole-grain wheat and rye intakes.The objective was to assess the dose response of plasma ARs and the excretion of 2 recently discovered AR metabolites in 24-h urine samples in relation to AR intake and to establish a pharmacokinetic model for predicting plasma AR concentration.Sixteen subjects were given rye bran flakes containing 11, 22, or 44 mg total ARs 3 times daily during week-long intervention periods separated by 1-wk washout periods in a nonblinded randomized crossover design. Blood samples were collected at baseline, after the 1-wk run-in period, and after each treatment and washout period. Two 24-h urine samples were collected at baseline and after each treatment period.Plasma AR concentrations and daily excretion of 2 urinary AR metabolites increased with increasing AR dose (P < 0.001). Recovery of urinary metabolites in 24-h samples decreased with increasing doses from approximately 90% to approximately 45% in the range tested. A one-compartment model with 2 absorption compartments with different lag times and absorption rate constants adequately predicted plasma AR concentrations at the end of each intervention period.Both plasma AR concentrations and urinary metabolites in 24-h samples showed a dose-response relation to increased AR intake, which strongly supports the hypothesis that ARs and their metabolites may be useful as biomarkers of whole-grain wheat and rye intakes.
Contributors
Matthew Roberts, Krishna Kumar Tiwari

Metadata information

isDescribedBy
PubMed 19056600
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model
hasPart
KEGG Compound Resorcinol
ChEBI 5-alkylresorcinol
is

Curation status
Curated


Tags
Name Description Size Actions

Model files

Landberg2009.xml SBML L2V4 representation of Landberg2009 - Alkylresorcinol Dose Response 29.03 KB Preview | Download

Additional files

Landberg2009.sedml SEDML file for the model 1.70 KB Preview | Download
Landberg2009.cps COPASI file 48.53 KB Preview | Download
figure2.jpg Attempt at reproducing figure 3. 14.95 KB Preview | Download

  • Model originally submitted by : Matthew Roberts
  • Submitted: 21-May-2018 15:31:34
  • Last Modified: 12-May-2020 05:35:25
Revisions
  • Version: 5 public model Download this version
    • Submitted on: 12-May-2020 05:35:25
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Automatically added model identifier BIOMD0000000948
  • Version: 3 public model Download this version
    • Submitted on: 21-May-2018 15:31:34
    • Submitted by: Matthew Roberts
    • With comment: Uploaded COPASI and curated figure to facilitate the curation process in the future.
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
AR A1

Resorcinol ; 5-alkylresorcinol
0.0 nmol
AR A2

5-alkylresorcinol ; Resorcinol
0.0 nmol
AR Central

Resorcinol ; 5-alkylresorcinol
0.01 nmol
AR Dose

5-alkylresorcinol ; Resorcinol
485.0 nmol
F1 0.0 nmol
F2 0.0 nmol
Reactions
Reactions Rate Parameters
k_a_1*AR_A1

k_a_1*AR_A1
k_a_1 = 0.3
F2*AR_Dose

F2*AR_Dose
[]
k_a_2*AR_A2

k_a_2*AR_A2
k_a_2 = 1.8
Central*base

Central*base
base = 0.32
Central*CL_V*AR_Central

Central*CL_V*AR_Central
CL_V = 20.0
F1*AR_Dose

F1*AR_Dose
[]
Lag_time_1 = 0.9; Lag_time_2 = 4.7
Lag_time_2 = 4.7
Curator's comment:
(added: 12 May 2020, 05:35:10, updated: 12 May 2020, 05:35:10)
Figure 3 results are reproduced here. Model encoded and annotated using COPASI. Plotting done using MATLAB.