Evidence map›Paper›PMID 41372487›Full record

ArticleScientific reports2025

Top-down perspectives on cell membrane potential and protein transcription.

Javier Cervera, Michael Levin, Salvador Mafe

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Javier CerveraDept. Termodinàmica, Facultat de Física, Universitat de València, Burjassot, Spain.
Michael LevinAllen Discovery Center at Tufts University, Medford, USA.
Salvador MafeDept. Termodinàmica, Facultat de Física, Universitat de València, Burjassot, Spain. smafe@uv.es.

Funding

John Templeton Foundation Grant 62212Ministerio de Ciencia e Innovacion project PID2022-139953NB-I00
6 · The paper itself

Abstract

We have explored a simple model for the multicellular interplay between bioelectricity and protein transcription using a top-down perspective that offers new insights complementary to the commonly used bottom-up descriptions. We model the non-excitable cell bioelectrical representation of the external environment, including the neighboring cells, using voltage-gated ion channels and intercellular junctions. The simulations make three predictions: (i) shifts in membrane potential allow transitions between gene expression states, (ii) in the case of different cell potential-gated transcriptions, depolarized cells cannot control the distinct gene expressions as effectively as polarized cells, and (iii) community effects should permit to extend the single-cell control to the multicellular level. Because the spatio-temporal distributions of instructive signaling ions and molecules depend on the local electric potentials, different multicellular potentials correlate with distinct downstream gene expression patterns. A central cell is able to measure the number of neighboring cells and learn their bioelectrical state from the downward-induced membrane potential changes, which suggests that multiscale bioelectricity can operate as a top-down mechanism in development and regeneration.

Indexed as

Membrane PotentialsModels, BiologicalTranscription, GeneticAnimalsCell MembraneGene Expression RegulationHumansIon ChannelsIon Channels

Identifiers

PMID41372487
PMCPMC12808214

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.