Evidence map›Paper›PMID 34677410›Full record

ArticleMetabolites2021

Simulating Metabolic Flexibility in Low Energy Expenditure Conditions Using Genome-Scale Metabolic Models.

Andrea Cabbia, Peter A J Hilbers, Natal A W van Riel

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 93% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 0 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Andrea CabbiaDepartment of Biomedical Engineering, Computational Biology, Eindhoven University of Technology, Groene Loper 5, 5612 AE Eindhoven, The Netherlands.ORCID 0000-0003-4275-1454
Peter A J HilbersDepartment of Biomedical Engineering, Computational Biology, Eindhoven University of Technology, Groene Loper 5, 5612 AE Eindhoven, The Netherlands.ORCID 0000-0002-8805-5633
Natal A W van RielDepartment of Biomedical Engineering, Computational Biology, Eindhoven University of Technology, Groene Loper 5, 5612 AE Eindhoven, The Netherlands.ORCID 0000-0001-9375-4730
Eindhoven University of Technology · NLAmsterdam University Medical Centers · NL

Funding

Horizon 2020 Framework Programme Marie Sklodowska-Curie grant agreement 675003
6 · The paper itself

Abstract

Metabolic flexibility is the ability of an organism to adapt its energy source based on nutrient availability and energy requirements. In humans, this ability has been linked to cardio-metabolic health and healthy aging. Genome-scale metabolic models have been employed to simulate metabolic flexibility by computing the Respiratory Quotient (RQ), which is defined as the ratio of carbon dioxide produced to oxygen consumed, and varies between values of 0.7 for pure fat metabolism and 1.0 for pure carbohydrate metabolism. While the nutritional determinants of metabolic flexibility are known, the role of low energy expenditure and sedentary behavior in the development of metabolic inflexibility is less studied. In this study, we present a new description of metabolic flexibility in genome-scale metabolic models which accounts for energy expenditure, and we study the interactions between physical activity and nutrition in a set of patient-derived models of skeletal muscle metabolism in older adults. The simulations show that fuel choice is sensitive to ATP consumption rate in all models tested. The ability to adapt fuel utilization to energy demands is an intrinsic property of the metabolic network.

Indexed as

energy expendituremetabolic flexibilityrespiratory quotient

Identifiers

PMID34677410
PMCPMC8537358
OpenAlexW3164254441

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.