Evidence map›Paper›PMID 28429122›Full record

ReviewHistochemistry and cell biology2017

Quantifying Golgi structure using EM: combining volume-SEM and stereology for higher throughput.

Sophie Ferguson, Anna M Steyer, Terry M Mayhew, Yannick Schwab, John Milton Lucocq

Abstract readReview
In one paragraph

Review in Histochemistry and cell biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Indirect Correlative Light and Electron Microscopy (iCLEM): A Novel Pipeline for Multiscale Quantification of Structure From Molecules to Organs.Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada · 2024
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Stereology as the 3D tool to quantitate lung architecture.Histochemistry and cell biology · 2021
    Review
  13. In focus in HCB.Histochemistry and cell biology · 2019
    Article
  14. Article
  15. Review
  16. In focus in HCB.Histochemistry and cell biology · 2017
    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

5 authors.

Sophie FergusonStructural Cell Biology Group, School of Medicine, University of St Andrews, North Haugh, Fife, KY16 9TF, Scotland, UK.ORCID http://orcid.org/0000-0002-4649-7214
Anna M SteyerCell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117, Heidelberg, Germany.
Terry M MayhewSchool of Life Sciences, Queen's Medical Centre, University of Nottingham, Nottingham, NG7 2UH, UK.
Yannick SchwabCell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117, Heidelberg, Germany.
John Milton LucocqStructural Cell Biology Group, School of Medicine, University of St Andrews, North Haugh, Fife, KY16 9TF, Scotland, UK. jml7@st-andrews.ac.uk.ORCID http://orcid.org/0000-0002-5191-0093

Funding

Wellcome Trust
6 · The paper itself

Abstract

Investigating organelles such as the Golgi complex depends increasingly on high-throughput quantitative morphological analyses from multiple experimental or genetic conditions. Light microscopy (LM) has been an effective tool for screening but fails to reveal fine details of Golgi structures such as vesicles, tubules and cisternae. Electron microscopy (EM) has sufficient resolution but traditional transmission EM (TEM) methods are slow and inefficient. Newer volume scanning EM (volume-SEM) methods now have the potential to speed up 3D analysis by automated sectioning and imaging. However, they produce large arrays of sections and/or images, which require labour-intensive 3D reconstruction for quantitation on limited cell numbers. Here, we show that the information storage, digital waste and workload involved in using volume-SEM can be reduced substantially using sampling-based stereology. Using the Golgi as an example, we describe how Golgi populations can be sensed quantitatively using single random slices and how accurate quantitative structural data on Golgi organelles of individual cells can be obtained using only 5-10 sections/images taken from a volume-SEM series (thereby sensing population parameters and cell-cell variability). The approach will be useful in techniques such as correlative LM and EM (CLEM) where small samples of cells are treated and where there may be variable responses. For Golgi study, we outline a series of stereological estimators that are suited to these analyses and suggest workflows, which have the potential to enhance the speed and relevance of data acquisition in volume-SEM.

Indexed as

AnimalsGolgi ApparatusHistocytological Preparation TechniquesHumansImaging, Three-DimensionalMicroscopy, Electron, ScanningFIBSEMGolgiQuantificationSamplingSBF-SEMStereologyVolume-SEM

Identifiers

PMID28429122
PMCPMC5429891

What OpenQuestion holds

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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.