Dataset Information

Lai2007_O2_Transport_Metabolism

ABSTRACT: This file describes the SBML version of the mathematical model in the following journal article: Linking Pulmonary Oxygen Uptake, Muscle Oxygen Utilization and Cellular Metabolism during Exercise, Ann Biomed Eng. 2007 Jun;35(6):956-69. (Pubmed ID: 17380394). This mathematical model simulates oxygen transport and metabolism in skeletal muscle in response to a step change from a warm-up steady state to a higher work rate corresponding to exercise at different levels of intensity: moderate (M), heavy (H) and very heavy (VH). The model parameter values are listed in the tables of this article. The parameter values that are independent of the exercise level are reported in Table 2. The parameter values that depend on the exercise level are reported in Tables 1A, 3 and 4. The model simulations (Figures 2, 3, 4 and 5) were obtained for a representative subject with a set of parameter values different from those in Table 1A, 3 and 4. In the sbml model, these model parameters are used to simulate exercise at a very heavy (VH) intensity for the representative subject. Additionally, the parameter values needed to simulate exercise at moderate (M) and heavy (H) intensity are reported in the list of parameters of the file. The model simulates dynamics of (1) the concentrations of free (F) and total (T) oxygen concentration in blood (CFcap, CTcap) and tissue (CFtis, CTtis), Adenosine Triphosphate (ATP), Adenosine Diphosphate (ADP), Phosphocreatine (PCr) and Creatine (Cr); (2) the metabolic flux of oxidative phosphorylation, creatine kinase and ATPase; (3) the oxygen uptake in blood and oxygen transport rate from blood to tissue during exercise. The simulation also computes muscle oxygen saturation (StO2m) and relative muscle oxygen saturation (RStO2m) in order to compare simulated and experimental responses of human muscle oxygenation during exercise. The model was successfully tested with Roadrunner of the Systems Biology Workbench (SBW). The model simulations obtained with Roadrunner match those obtained with the mathematical model represented in Fortran and Matlab for relative and absolute tolerance smaller than 10-7. To allow for simulations at varying levels of exercise, the parameter exercise_level was introduced. A value of 1 means medium, 2 heavy and 3 very heavy exercise. Setting this parameter assigns the parameters Vmax, KatpaseE, dQMm and tauQm with the relevant parameters. The warmup steady state is influenced by the parameter changes for this representative subject and the model has to be brought into steady state after each change of exercise level. This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Nov��re N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.

SUBMITTER: Nicola Lai

PROVIDER: BIOMD0000000248 | BioModels | 2024-09-02

REPOSITORIES: BioModels

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	BIOMD0000000248?filename=BIOMD0000000248-biopax2.owl	Owl
	BIOMD0000000248?filename=BIOMD0000000248-biopax3.owl	Owl
	BIOMD0000000248?filename=BIOMD0000000248.m	Other
	BIOMD0000000248?filename=BIOMD0000000248.pdf	Pdf
	BIOMD0000000248?filename=BIOMD0000000248.png	Other

Items per page:

1 - 5 of 11

Publications

Linking pulmonary oxygen uptake, muscle oxygen utilization and cellular metabolism during exercise.

Lai Nicola N Camesasca Marco M Saidel Gerald M GM Dash Ranjan K RK Cabrera Marco E ME

Annals of biomedical engineering 20070323 6

The energy demand imposed by physical exercise on the components of the oxygen transport and utilization system requires a close link between cellular and external respiration in order to maintain ATP homeostasis. Invasive and non-invasive experimental approaches have been used to elucidate mechanisms regulating the balance between oxygen supply and consumption during exercise. Such approaches suggest that the mechanism controlling the various subsystems coupling internal to external respiration ...[more]

PMID: 17380394

Publication: 1/3

Similar Datasets

Project description:The methylome and transcriptome signatures following exercise that are physiologically and metabolically relevant to sporting contexts such as team sports or health prescription scenarios (e.g. high intensity interval training/HIIT) has not been investigated. To explore this, we performed two different sport/exercise relevant high-intensity running protocols in 5 male sport team members using a repeated measures design of: 1) Change of direction (COD) versus; 2) straight line (ST) exercise with a wash-out period of at least 2 weeks between trials. Skeletal muscle biopsies collected from the vastus lateralis 30 minutes and 24 hours post exercise, were assayed using 850K methylation arrays and a comparative analysis with recent (subject-unmatched) sprint and acute aerobic exercise meta-analysis transcriptomes was performed. Despite COD and ST exercise being matched for classically defined intensity measures (speed x distance and number of accelerations/decelerations), COD exercise elicited greater movement (GPS-Playerload), physiological (HR), metabolic (lactate) as well as central and peripheral (differential RPE) measures compared with ST exercise, suggesting COD exercise evoked a higher exercise intensity. The exercise response alone across both conditions evoked extensive alterations in the methylome 30 mins and 24 hrs post exercise, particularly in MAPK, AMPK and axon guidance pathways. COD evoked a considerably greater hypomethylated signature across the genome compared with ST exercise, particularly at 30 minutes post exercise, enriched in: Protein binding, MAPK, AMPK, insulin, and axon guidance pathways. Comparative methylome analysis with sprint running transcriptomes identified considerable overlap, with 49% of genes that were altered at the expression level also differentially methylated after COD exercise. After differential methylated region analysis, we observed that VEGFA and its downstream nuclear transcription factor, NR4A1 had enriched hypomethylation within their promoter regions. VEGFA and NR4A1 were also significantly upregulated in the sprint transcriptome and meta-analysis of exercise transcriptomes. We confirmed increased gene expression of VEGFA, and considerably larger increases in the expression of canonical metabolic genes, PPARGC1A (that encodes PGC1-α) and NR4A3 in COD vs. ST exercise. Overall, we demonstrate that increased physiological/metabolic load via change of direction exercise in human skeletal muscle evokes considerable epigenetic modifications that are associated with changes in expression of genes responsible for adaptation to exercise.