Evidence map›Paper›PMID 28884446›Full record

ArticleBulletin of mathematical biology2017

Analysis of Homeostatic Mechanisms in Biochemical Networks.

Michael Reed, Janet Best, Martin Golubitsky, Ian Stewart, H Frederik Nijhout

Open access · greenAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

15 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
  2. Article
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  4. Minimal motifs for habituating systems.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Homeostasis in networks with multiple inputs.Journal of mathematical biology · 2024
    Article
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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

5 authors at 3 institutions in 2 countries.

Michael ReedDepartment of Mathematics, Duke University, Durham, NC, 27708, USA. reed@math.duke.edu.
Janet BestDepartment of Mathematics, The Ohio State University, Columbus, OH, 43210, USA.
Martin GolubitskyDepartment of Mathematics, The Ohio State University, Columbus, OH, 43210, USA.
Ian StewartMathematics Institute, University of Warwick, Coventry, CV47AL, UK.
H Frederik NijhoutDepartment of Biology, Duke University, Durham, NC, 27708, USA.
Duke University · USThe Ohio State University · USUniversity of Warwick · GB

Funding

An In Vivo Voltammetric Serotonin Biomarker for Antidepressant EfficacyR01MH106563 · NIMH · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI HASHEMI, PARASTOO · 2016 to 2020
$1.6M
Voltammetric determination of neuronal serotonin and histamine co-regulationR21MH109959 · NIMH · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI HASHEMI, PARASTOO · 2016 to 2017
$424k
NIMH NIH HHS R01 MH106563NIMH NIH HHS R21 MH109959
6 · The paper itself

Abstract

Cell metabolism is an extremely complicated dynamical system that maintains important cellular functions despite large changes in inputs. This "homeostasis" does not mean that the dynamical system is rigid and fixed. Typically, large changes in external variables cause large changes in some internal variables so that, through various regulatory mechanisms, certain other internal variables (concentrations or velocities) remain approximately constant over a finite range of inputs. Outside that range, the mechanisms cease to function and concentrations change rapidly with changes in inputs. In this paper we analyze four different common biochemical homeostatic mechanisms: feedforward excitation, feedback inhibition, kinetic homeostasis, and parallel inhibition. We show that all four mechanisms can occur in a single biological network, using folate and methionine metabolism as an example. Golubitsky and Stewart have proposed a method to find homeostatic nodes in networks. We show that their method works for two of these mechanisms but not the other two. We discuss the many interesting mathematical and biological questions that emerge from this analysis, and we explain why understanding homeostatic control is crucial for precision medicine.

Indexed as

HomeostasisMetabolic Networks and PathwaysModels, BiologicalComputer SimulationFeedback, PhysiologicalFolic AcidHumansKineticsMathematical ConceptsMethionineSystems BiologyFolic AcidMethionineBiochemistryHomeostasisMotifsNetworks

Identifiers

PMID28884446
PMCPMC5842936
OpenAlexW2754429301

What OpenQuestion holds

Textmetadata
LicenceTDM
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.