Evidence map›Paper›PMID 37019439›Full record

ArticleNano letters2023

Passive Recording of Bioelectrical Signals from Non-Excitable Cells by Fluorescent Mirroring.

Rosalia Moreddu, Alessio Boschi, Marta d'Amora, Aliaksandr Hubarevich, Michele Dipalo, Francesco De Angelis

Abstract read
In one paragraph

Article in Nano letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
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

6 authors.

Rosalia MoredduPlasmon Nanotechnologies Unit, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.ORCID 0000-0002-0332-1606
Alessio BoschiPlasmon Nanotechnologies Unit, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.
Marta d'AmoraPlasmon Nanotechnologies Unit, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.
Aliaksandr HubarevichPlasmon Nanotechnologies Unit, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.
Michele DipaloPlasmon Nanotechnologies Unit, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.ORCID 0000-0002-1823-8231
Francesco De AngelisPlasmon Nanotechnologies Unit, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.ORCID 0000-0001-6053-2488

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bioelectrical variations trigger different cell responses, including migration, mitosis, and mutation. At the tissue level, these actions result in phenomena such as wound healing, proliferation, and pathogenesis. Monitoring these mechanisms dynamically is highly desirable in diagnostics and drug testing. However, existing technologies are invasive: either they require physical access to the intracellular compartments, or they imply direct contact with the cellular medium. Here, we present a novel approach for the passive recording of electrical signals from non-excitable cells adhering to 3D microelectrodes, based on optical mirroring. Preliminary results yielded a fluorescence intensity output increase of the 5,8% in the presence of a HEK-293 cell on the electrode compared to bare microelectrodes. At present, this technology may be employed to evaluate cell-substrate adhesion and monitor cell proliferation. Further refinements could allow extrapolating quantitative data on surface charges and resting potential to investigate the electrical phenomena involved in cell migration and cancer progression.

Indexed as

NeoplasmsCell AdhesionHEK293 CellsHumansMembrane PotentialsMicroelectrodesbioelectricitycell−surface adhesionfluorescenceHEK-293non−excitable cells

Identifiers

PMID37019439
PMCPMC10141418

What OpenQuestion holds

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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.