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Cited by 707

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Detection of human papilloma virus in paraffin-embedded tissue using the polymerase chain reaction.

Open access
Shibata, D K, Arnheim, N, Martin, W J·1988·The Journal of experimental medicine

Abstract

Human papilloma virus (HPV) DNA sequences have been detected in paraffin-embedded tissue using an enzymatic in vitro amplification technique known as the polymerase chain reaction. Amplification of a HPV DNA sequence before its detection with a cDNA probe significantly increases the rapidity as well as the sensitivity of detection such that a single 5-10-micron thick paraffin-embedded tissue section can be analyzed within 24 h. The assay specifically detected HPV 16 or 18 without crossreactivity with HPV 6 or 11. As few as 20 viral copies could be detected. The rapid and sensitive analysis of HPV in normal and pathological tissues using this technique may contribute significantly to identifying the role of HPV as a risk factor in carcinoma.

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Crossref · 10.1084/jem.167.1.225

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Metadata

Authors
Shibata, D. K., Arnheim, N., & Martin, W. J.
Venue
The Journal of experimental medicine
Published
1988-01-01
Volume
167
Issue
1
Pages
225-230
ISSN
  • 0022-1007 (ISSN-L)
  • 1540-9538
OpenAlex
W1986432875
Cited by
707
References
1
FWCI
98.08
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Detection of human papilloma virus in paraffin-embedded tissue using the polymerase chain reaction. https://app.cochat.ai/papers/10.1084/jem.167.1.225
The paper
Shibata, D. K., Arnheim, N., & Martin, W. J. (1988). Detection of human papilloma virus in paraffin-embedded tissue using the polymerase chain reaction. The Journal of experimental medicine. https://doi.org/10.1084/jem.167.1.225

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.