Evidence map›Paper›PMID 41701291›Full record

ArticleJournal of mathematical biology2026

Infinitesimal homeostasis in mass-action systems.

Jiaxin Jin, Grzegorz A Rempala

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

2 authors.

Jiaxin Jin *Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
Grzegorz A Rempala *Department of Mathematics, The Ohio State University, Columbus, OH, 43210, USA. rempala.3@osu.edu.ORCID http://orcid.org/0000-0002-6307-4555

Funding

Directorate for Mathematical and Physical Sciences 1853587Directorate for Mathematical and Physical Sciences 2310816
6 · The paper itself

Abstract

Homeostasis occurs in a biological system when a chosen output variable remains approximately constant despite changes in an input variable. In this work we specifically focus on biological systems that may be represented as chemical reaction networks and consider their infinitesimal homeostasis, where the derivative of the input-output function is zero. The specific challenge of chemical reaction networks is that they often obey various conservation laws complicating the standard input-output analysis. We derive several results that allow us to verify the existence of infinitesimal homeostasis points both in the absence of conservation and under conservation laws where conserved quantities serve as input parameters. In particular, we introduce the notion of infinitesimal concentration robustness, where the output variable remains nearly constant despite fluctuations in the conserved quantities. We provide several examples of chemical networks that illustrate our results both in deterministic and stochastic settings.

Indexed as

HomeostasisModels, BiologicalAnimalsMathematical ConceptsMetabolic Networks and PathwaysStochastic ProcessesSystems BiologyBiochemistryChemical Reaction NetworkHomeostasisInput-Output Network

Identifiers

PMID41701291
PMCPMC12913314

What OpenQuestion holds

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Registered trials

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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.