Evidence map›Paper›PMID 38505634›Full record

ReviewBiophysics reviews2021

Stability and robustness properties of bioelectric networks: A computational approach.

Joel Grodstein, Michael Levin

Abstract readReview
In one paragraph

Review in Biophysics reviews, 2021. 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. Review
  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

2 authors.

Joel GrodsteinDepartment of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts 02155, USA.ORCID https://orcid.org/0000-0003-1200-2444

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Morphogenesis during development and regeneration requires cells to communicate and cooperate toward the construction of complex anatomical structures. One important set of mechanisms for coordinating growth and form occurs via developmental bioelectricity-the dynamics of cellular networks driving changes of resting membrane potential which interface with transcriptional and biomechanical downstream cascades. While many molecular details have been elucidated about the instructive processes mediated by ion channel-dependent signaling outside of the nervous system, future advances in regenerative medicine and bioengineering require the understanding of tissue, organ, or whole body-level properties. A key aspect of bioelectric networks is their robustness, which can drive correct, invariant patterning cues despite changing cell number and anatomical configuration of the underlying tissue network. Here, we computationally analyze the minimal models of bioelectric networks and use the example of the regenerating planarian flatworm, to reveal important system-level aspects of bioelectrically derived patterns. These analyses promote an understanding of the robustness of circuits controlling regeneration and suggest design properties that can be exploited for synthetic bioengineering.

Identifiers

PMID38505634
PMCPMC10903393

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.