Evidence map›Paper›PMID 18553098›Full record

ReviewHistochemistry and cell biology2008

Developments in cell biology for quantitative immunoelectron microscopy based on thin sections: a review.

Terry M Mayhew, John M Lucocq

Abstract readReview
In one paragraph

Review in Histochemistry and cell biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Erythroblast enucleation at a glance.Journal of cell science · 2024
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Imaging the Cardiac Extracellular Matrix.Advances in experimental medicine and biology · 2018
    Review
  7. Article
  8. Article
  9. Using electron microscopes to look into the lung.Histochemistry and cell biology · 2016
    Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Localization of carboxyl ester lipase in human pituitary gland and pituitary adenomas.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2010
    Article
  15. Quantitative assessment of specificity in immunoelectron microscopy.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2010
    Article
  16. Review
  17. A stereological approach for estimation of cellular immunogold labeling and its spatial distribution in oriented sections using the rotator.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2009
    Article
  18. Review
  19. 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

2 authors.

Terry M MayhewCentre for Integrated Systems Biology and Medicine, School of Biomedical Sciences, Queen's Medical Centre, E Floor, University of Nottingham, Nottingham, NG7 2UH, UK. terry.mayhew@nottingham.ac.uk
John M Lucocq

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative immunoelectron microscopy uses ultrathin sections and gold particle labelling to determine distributions of molecules across cell compartments. Here, we review a portfolio of new methods for comparing labelling distributions between different compartments in one study group (method 1) and between the same compartments in two or more groups (method 2). Specimen samples are selected unbiasedly and then observed and expected distributions of gold particles are estimated and compared by appropriate statistical procedures. The methods can be used to analyse gold label distributed between volume-occupying (organelle) and surface-occupying (membrane) compartments, but in method 1, membranes must be treated as organelles. With method 1, gold counts are combined with stereological estimators of compartment size to determine labelling density (LD). For volume-occupiers, LD can be expressed simply as golds per test point and, for surface-occupiers, as golds per test line intersection. Expected distributions are generated by randomly assigning gold particles to compartments and expressing observed/expected counts as a relative labelling index (RLI). Preferentially-labelled compartments are identified from their RLI values and by Chi-squared analysis of observed and expected distributions. For method 2, the raw gold particle counts distributed between compartments are simply compared across groups by contingency table and Chi-squared analysis. This identifies the main compartments responsible for the differences between group distributions. Finally, we discuss labelling efficiency (the number of gold particles per target molecule) and describe how it can be estimated for volume- or surface-occupiers by combining stereological data with biochemical determinations.

Indexed as

AnimalsDendritic CellsGold ColloidHumansImmunohistochemistryMicroscopy, ImmunoelectronMicrotomyStaining and LabelingGold Colloid

Identifiers

PMID18553098
PMCPMC2491712

What OpenQuestion holds

Textmetadata
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.