Evidence map›Paper›PMID 9015709›Full record

ArticleThe Histochemical journal1996

Keratin antigen retrieval in oral mucosal biopsies using microwave processing.

G R Ogden, D Lunny, E B Lane

Abstract read
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In one paragraph

Article in The Histochemical journal, 1996. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 55% 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

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

G R OgdenDepartment of Dental Surgery and Periodontology, University of Dundee, UK.
D Lunny
E B Lane
University of Dundee · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In immunohistochemistry, it is well known that the majority of monoclonal antibodies to keratins work best on fresh frozen tissue specimens, yet in clinical practice most biopsies are routinely fixed in formaldehyde. This seriously limits the range of keratins that can be reliably assessed in retrospective studies (particularly where only rare archival material exists) and where subtle changes during tissue differentiation may be important. Antigen retrieval using exposure to microwave radiation is one technique that has been applied successfully to other tumour markers (e.g., p53). However, few papers have used this method when immunolabelling for keratins, in spite of the widespread use of antikeratin antibodies as markers of differentiation. The effect of keratin antigen retrieval using microwave processing was assessed on a range of oral mucosal biopsies, since the oral cavity displays a wide range of keratins. A panel of six well characterized antibodies was chosen: LP34 (Ck1, 5, 6, 18), LH1 (Ck10), LL025 (Ck16), A53 BA2 (Ck19), AE8 (Ck13), and E3 (Ck17). For each specimen, one piece was stored in liquid nitrogen and another piece fixed in formalin. Tissue sections were cut from each and, using the peroxidase avidin biotin technique, keratin expression was recorded for a frozen section, a dewaxed section, and a microwave-heated dewaxed section. Although overall there was a 25% improvement in identification of keratins after microwaving, some antibodies performed better than others. Given that keratins have been shown to be of value in tumour diagnosis, this study suggests that microwave processing of archival material can be a valuable adjunct to such analysis.

Indexed as

MicrowavesAntibodiesBiopsyHumansKeratinsMouth MucosaMouth NeoplasmsAntibodiesKeratins

Identifiers

PMID9015709
OpenAlexW2024533628

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.