Evidence map›Paper›PMID 38047236›Full record

ArticleComputational and structural biotechnology journal2023

Automated high-content image-based characterization of microorganism behavioral diversity and distribution.

Carlotta Aurora Lupatelli, Agnes Attard, Marie-Line Kuhn, Celine Cohen, Philippe Thomen, Xavier Noblin, Eric Galiana

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2023. 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

7 authors.

Carlotta Aurora LupatelliUniversité Côte d'Azur, INRAE, CNRS, ISA, Sophia Antipolis, 06903, France.
Agnes AttardUniversité Côte d'Azur, INRAE, CNRS, ISA, Sophia Antipolis, 06903, France.
Marie-Line KuhnUniversité Côte d'Azur, INRAE, CNRS, ISA, Sophia Antipolis, 06903, France.
Celine CohenUniversité Côte d'Azur, CNRS, UMR 7010, INPHYNI, Nice 06200, France.
Philippe ThomenUniversité Côte d'Azur, CNRS, UMR 7010, INPHYNI, Nice 06200, France.
Xavier NoblinUniversité Côte d'Azur, CNRS, UMR 7010, INPHYNI, Nice 06200, France.
Eric GalianaUniversité Côte d'Azur, INRAE, CNRS, ISA, Sophia Antipolis, 06903, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microorganisms have evolved complex systems to respond to environmental signals. Gradients of particular molecules and elemental ions alter the behavior of microbes and their distribution within their environment. Microdevices coupled with automated image-based methods are now employed to analyze the instantaneous distribution and motion behaviors of microbial species in controlled environments at small temporal scales, mimicking, to some extent, macro conditions. Such technologies have so far been adopted for investigations mainly on individual species. Similar versatile approaches must now be developed for the characterization of multiple and complex interactions between a microbial community and its environment. Here, we provide a comprehensive step-by-step method for the characterization of species-specific behavior in a synthetic mixed microbial suspension in response to an environmental driver. By coupling accessible microfluidic devices with automated image analysis approaches, we evaluated the behavioral response of three morphologically different telluric species (

Indexed as

Automated image analysisCell trackingDistributionDriversMicro-environmentsMicroorganisms

Identifiers

PMID38047236
PMCPMC10692603

What OpenQuestion holds

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LicenceCC BY
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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.