Evidence map›Paper›PMID 20458060›Full record

ArticleThe journal of histochemistry and cytochemistry : official journal of the Histochemistry Society2010

Quantitative assessment of specificity in immunoelectron microscopy.

John Milton Lucocq, Christian Gawden-Bone

Open access · bronzeAbstract read
In one paragraph

Article in The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Using Diatom and Apicomplexan Models to Study the Heme Pathway ofInternational journal of molecular sciences · 2021
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. 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

2 authors at 2 institutions in 1 country.

John Milton LucocqDivision of Cell Biology and Immunology, School of Life Sciences, Wellcome Trust Biocentre, University of Dundee, Dundee, Scotland, UK. j.m.lucocq@dundee.ac.uk
Christian Gawden-Bone
University of Dundee · GBWellcome Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In immunoelectron microscopy (immuno-EM) on ultrathin sections, gold particles are used for localization of molecular components of cells. These particles are countable, and quantitative methods have been established to estimate and evaluate the density and distribution of "raw" gold particle counts from a single uncontrolled labeling experiment. However, these raw counts are composed of two distinct elements: particles that are specific (specific labeling) and particles that are not (nonspecific labeling) for the target component. So far, approaches for assessment of specific labeling and for correction of raw gold particle counts to reveal specific labeling densities and distributions have not attracted much attention. Here, we discuss experimental strategies for determining specificity in immuno-EM, and we present methods for quantitative assessment of (1) the probability that an observed gold particle is specific for the target, (2) the density of specific labeling, and (3) the distribution of specific labeling over a series of compartments. These methods should be of general utility for researchers investigating the distribution of cellular components using on-section immunogold labeling.

Indexed as

AnimalsHistocytological Preparation TechniquesHumansMicroscopy, ImmunoelectronProbabilitySensitivity and SpecificityStaining and Labeling

Identifiers

PMID20458060
PMCPMC2942744
OpenAlexW2160105265

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.