Evidence map›Paper›PMID 36824447›Full record

ArticleHardwareX2023

An open-source microscopy framework for simultaneous control of image acquisition, reconstruction, and analysis.

Xavier Casas Moreno, Mariline Mendes Silva, Johannes Roos, Francesca Pennacchietti, Nils Norlin, Ilaria Testa

Abstract read
In one paragraph

Article in HardwareX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Live-cell imaging powered by computation.Nature reviews. Molecular cell biology · 2024
    Review
  4. Article
  5. Article
  6. 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

6 authors.

Xavier Casas MorenoScience for Life Laboratory, Department of Applied Physics, KTH Royal Institute of Technology, 171 65 Stockholm Sweden.
Mariline Mendes SilvaScience for Life Laboratory, Department of Applied Physics, KTH Royal Institute of Technology, 171 65 Stockholm Sweden.
Johannes RoosInterdisciplinary Institute for Neuroscience, CNRS UMR 5297, 33000 Bordeaux, France.
Francesca PennacchiettiScience for Life Laboratory, Department of Applied Physics, KTH Royal Institute of Technology, 171 65 Stockholm Sweden.
Nils NorlinDepartment of Experimental Medical Science, Lund University Bioimaging Centre (LBIC), 221 00 Lund University, Sweden.
Ilaria TestaScience for Life Laboratory, Department of Applied Physics, KTH Royal Institute of Technology, 171 65 Stockholm Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a computational framework to simultaneously perform image acquisition, reconstruction, and analysis in the context of open-source microscopy automation. The setup features multiple computer units intersecting software with hardware devices and achieves automation using python scripts. In practice, script files are executed in the acquisition computer and can perform any experiment by modifying the state of the hardware devices and accessing experimental data. The presented framework achieves concurrency by using multiple instances of ImSwitch and napari working simultaneously. ImSwitch is a flexible and modular open-source software package for microscope control, and napari is a multidimensional image viewer for scientific image analysis. The presented framework implements a system based on file watching, where multiple units monitor a filesystem that acts as the synchronization primitive. The proposed solution is valid for any microscope setup, supporting various biological applications. The only necessary element is a shared filesystem, common in any standard laboratory, even in resource-constrained settings. The file watcher functionality in Python can be easily integrated into other python-based software. We demonstrate the proposed solution by performing tiling experiments using the molecular nanoscale live imaging with sectioning ability (MoNaLISA) microscope, a high-throughput super-resolution microscope based on reversible saturable optical fluorescence transitions (RESOLFT).

Indexed as

AutomationRESOLFTSoftware

Identifiers

PMID36824447
PMCPMC9941414

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.