Evidence map›Paper›PMID 29849125›Full record

ReviewLaboratory investigation; a journal of technical methods and pathology2018

Principles and approaches for reproducible scoring of tissue stains in research.

David K Meyerholz, Amanda P Beck

Abstract readReview
PubMed Publisher
In one paragraph

Review in Laboratory investigation; a journal of technical methods and pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 219 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
219citing papers in PubMed, 3 pooled it
–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

219 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. A Phase II Study of Abemaciclib for Patients with Retinoblastoma-Positive, Metastatic Triple-Negative Breast Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Glycolysis-enhancing αAlzheimer's research & therapy · 2026
    Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Lewis Y (LeImmunologic research · 2026
    Article
  19. Artificial intelligence-enabled histological analysis in pre-clinical respiratory disease models: a scoping review.European respiratory review : an official journal of the European Respiratory Society · 2026
    Article
  20. Article

159 more citing papers are in PubMed but not listed here.

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.

David K MeyerholzDepartment of Pathology, University of Iowa Carver College of Medicine, Iowa City, IA, USA. david-meyerholz@uiowa.edu.ORCID http://orcid.org/0000-0003-1552-3253
Amanda P BeckDepartment of Pathology, Albert Einstein College of Medicine, Bronx, NY, USA. amanda.beck@einstein.yu.edu.

Funding

Vector Core-Core 2P30DK054759 · NIDDK · UNIVERSITY OF IOWA · PI Amy Leanne Ryan · 1998 to 2026
$30.5M
NIDDK NIH HHS P30 DK054759
6 · The paper itself

Abstract

Evaluation of tissues is a common and important aspect of translational research studies. Labeling techniques such as immunohistochemistry can stain cells/tissues to enhance identification of specific cell types, cellular activation states, and protein expression. While qualitative evaluation of labeled tissues has merit, use of semiquantitative and quantitative scoring approaches can greatly enhance the rigor of the tissue data. Adhering to key principles for reproducible scoring can enhance the quality and reproducibility of the tissue data so as to maximize its biological relevance and scientific impact.

Indexed as

ImmunohistochemistryStaining and LabelingColoring AgentsHumansReproducibility of ResultsSpecimen HandlingColoring Agents

Identifiers

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.