Evidence map›Paper›PMID 23133351›Full record

ArticlePLoS computational biology2012

Integrating cellular metabolism into a multiscale whole-body model.

Markus Krauss, Stephan Schaller, Steffen Borchers, Rolf Findeisen, Jörg Lippert, Lars Kuepfer

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
5.4field-weighted citation impact, top 3% 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

55 citing papers in PubMed, 126 citations in OpenAlex.

  1. Review
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  7. Quantitative systems pharmacology of the eye: Tools and data for ocular QSP.CPT: pharmacometrics & systems pharmacology · 2023
    Review
  8. Prediction ofFrontiers in pharmacology · 2023
    Article
  9. Review
  10. Review
  11. Review
  12. Frontiers in toxicology · 2022
    Article
  13. A dynamic multi-tissue model to study human metabolism.NPJ systems biology and applications · 2021
    Article
  14. Metabolic modelling approaches for describing and engineering microbial communities.Computational and structural biotechnology journal · 2021
    Review
  15. Review
  16. Review
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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

6 authors at 4 institutions in 1 country.

Markus KraussBayer Technology Services GmbH, Computational Systems Biology, Leverkusen, Germany.
Stephan Schaller
Steffen Borchers
Rolf Findeisen
Jörg Lippert
Lars Kuepfer
Bayer (Germany) · DEMax Planck Society · DEOtto-von-Guericke University Magdeburg · DERWTH Aachen University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

Indexed as

Models, BiologicalAcetaminophenAllopurinolAmmoniaChemical and Drug Induced Liver InjuryComputational BiologyComputer SimulationHepatocytesHumansHyperuricemiaInactivation, MetabolicLiverMetabolismUreaUrea Cycle Disorders, InbornUric AcidAcetaminophenAllopurinolAmmoniaUreaUric Acid

Identifiers

PMID23133351
PMCPMC3486908
OpenAlexW1963859554

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.