Evidence map›Paper›PMID 38994988›Full record

ArticleCells2024

Identification of Distinct, Quantitative Pattern Classes from Emergent Tissue-Scale hiPSC Bioelectric Properties.

Dennis Andre Norfleet, Anja J Melendez, Caroline Alting, Siya Kannan, Arina A Nikitina, Raquel Caldeira Botelho, Bo Yang, Melissa L Kemp

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cells, 2024. 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

8 authors.

Dennis Andre NorfleetThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 950 Atlantic Dr. NW, Atlanta, GA 30332, USA.
Anja J MelendezThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 950 Atlantic Dr. NW, Atlanta, GA 30332, USA.
Caroline AltingThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 950 Atlantic Dr. NW, Atlanta, GA 30332, USA.
Siya KannanThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 950 Atlantic Dr. NW, Atlanta, GA 30332, USA.
Arina A NikitinaSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Raquel Caldeira BotelhoThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 950 Atlantic Dr. NW, Atlanta, GA 30332, USA.
Bo YangGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Melissa L KempThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 950 Atlantic Dr. NW, Atlanta, GA 30332, USA.ORCID 0000-0003-3781-8802

Funding

Synthetic gene sensors and effectors to redirect organoid developmentR01EB030946 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BELTA, CALIN, KEMP, MELISSA LAMBETH · 2021 to 2024
$2.6M
National Science Foundation 0939511NIBIB NIH HHS 5R01EB030946NIBIB NIH HHS R01 EB030946
6 · The paper itself

Abstract

Bioelectric signals possess the ability to robustly control and manipulate patterning during embryogenesis and tissue-level regeneration. Endogenous local and global electric fields function as a spatial 'pre-pattern', controlling cell fates and tissue-scale anatomical boundaries; however, the mechanisms facilitating these robust multiscale outcomes are poorly characterized. Computational modeling addresses the need to predict in vitro patterning behavior and further elucidate the roles of cellular bioelectric signaling components in patterning outcomes. Here, we modified a previously designed image pattern recognition algorithm to distinguish unique spatial features of simulated non-excitable bioelectric patterns under distinct cell culture conditions. This algorithm was applied to comparisons between simulated patterns and experimental microscopy images of membrane potential (V

Indexed as

Induced Pluripotent Stem CellsMembrane PotentialsAlgorithmsCoculture TechniquesComputer SimulationHumansModels, Biologicalbioelectricitycell-cell communicationcomputational modelingemergenceimage pattern recognitionpluripotent stem cellssystems biologyvoltage membrane potential

Identifiers

PMID38994988
PMCPMC11240333

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.