Evidence map›Paper›PMID 34330271›Full record

ArticleBMC biology2021

A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography.

Sergio Gabarre, Frank Vernaillen, Pieter Baatsen, Katlijn Vints, Christopher Cawthorne, Steven Boeynaems, Emiel Michiels, Dorien Vandael, Natalia V Gounko, Sebastian Munck

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2021. 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
2.0field-weighted citation impact, top 12% of its field
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, 8 citations in OpenAlex.

  1. Array tomography: trails to discovery.Methods in microscopy · 2024
    Article
  2. Article
  3. Volume electron microscopy.Nature reviews. Methods primers · 2022
    Article
  4. Review
  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

10 authors at 4 institutions in 2 countries.

Sergio GabarreVIB-KU Leuven Center for Brain & Disease Research, Electron Microscopy Platform & VIB BioImaging Core, O&N5 Herestraat 49 box 602, 3000, Leuven, Belgium.
Frank VernaillenVIB BioInformatics Core, Technologiepark 75, 9052, Ghent, Belgium.
Pieter BaatsenVIB-KU Leuven Center for Brain & Disease Research, Electron Microscopy Platform & VIB BioImaging Core, O&N5 Herestraat 49 box 602, 3000, Leuven, Belgium.
Katlijn VintsVIB-KU Leuven Center for Brain & Disease Research, Electron Microscopy Platform & VIB BioImaging Core, O&N5 Herestraat 49 box 602, 3000, Leuven, Belgium.
Christopher CawthorneMoSAIC-Molecular Small Animal Imaging Centre, KU Leuven, Leuven, Belgium.
Steven BoeynaemsDepartment of Genetics, Stanford University School of Medicine, Stanford, California, 94305, USA.
Emiel MichielsVIB Center for Brain and Disease Research, 3000, Leuven, Belgium.
Dorien VandaelVIB-KU Leuven Center for Brain & Disease Research, Electron Microscopy Platform & VIB BioImaging Core, O&N5 Herestraat 49 box 602, 3000, Leuven, Belgium.
Natalia V GounkoVIB-KU Leuven Center for Brain & Disease Research, Electron Microscopy Platform & VIB BioImaging Core, O&N5 Herestraat 49 box 602, 3000, Leuven, Belgium. natalia.gunko@kuleuven.vib.be.
Sebastian MunckKU Leuven Department of Neurosciences, Leuven Brain Institute, O&N5 Herestraat 49 box 602, 3000, Leuven, Belgium. sebastian.munck@kuleuven.vib.be.ORCID 0000-0002-5182-5358
VIB-KU Leuven Center for Brain & Disease Research · BEAllen Institute for Brain Science · USKU Leuven · BEStanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArray tomography (AT) is a high-resolution imaging method to resolve fine details at the organelle level and has the advantage that it can provide 3D volumes to show the tissue context. AT can be carried out in a correlative way, combing light and electron microscopy (LM, EM) techniques. However, the correlation between modalities can be a challenge and delineating specific regions of interest in consecutive sections can be time-consuming. Integrated light and electron microscopes (iLEMs) offer the possibility to provide well-correlated images and may pose an ideal solution for correlative AT. Here, we report a workflow to automate navigation between regions of interest.

resultsWe use a targeted approach that allows imaging specific tissue features, like organelles, cell processes, and nuclei at different scales to enable fast, directly correlated in situ AT using an integrated light and electron microscope (iLEM-AT). Our workflow is based on the detection of section boundaries on an initial transmitted light acquisition that serves as a reference space to compensate for changes in shape between sections, and we apply a stepwise refinement of localizations as the magnification increases from LM to EM. With minimal user interaction, this enables autonomous and speedy acquisition of regions containing cells and cellular organelles of interest correlated across different magnifications for LM and EM modalities, providing a more efficient way to obtain 3D images. We provide a proof of concept of our approach and the developed software tools using both Golgi neuronal impregnation staining and fluorescently labeled protein condensates in cells.

conclusionsOur method facilitates tracing and reconstructing cellular structures over multiple sections, is targeted at high resolution ILEMs, and can be integrated into existing devices, both commercial and custom-built systems.

Indexed as

Imaging, Three-DimensionalTomographyStaining and LabelingTomography, X-Ray ComputedWorkflow3D EMArray tomographyAuto-navigationCLEMCorrelationGolgi stainingIntegrated light and electron microscopeOpen sourceSmart microscopyworkflow

Identifiers

PMID34330271
PMCPMC8323292
OpenAlexW3183165731

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.