Evidence map›Paper›PMID 23245876›Full record

ArticleVeterinary research2012

The interpretation of disease phenotypes to identify TSE strains in mice: characterisation of BSE using PrPSc distribution patterns in the brain.

Erica Corda, Katy E Beck, Rosemary E Sallis, Christopher M Vickery, Margaret Denyer, Paul R Webb, Susan J Bellworthy, Yvonne I Spencer, Marion M Simmons, John Spiropoulos

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Article in Veterinary research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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

10 authors.

Erica CordaAnimal Health and Veterinary Laboratories Agency, Woodham Lane, New Haw, Addlestone, Surrey, KT15 3NB, United Kingdom. John.Spiropoulos@ahvla.gsi.gov.uk.
Katy E Beck
Rosemary E Sallis
Christopher M Vickery
Margaret Denyer
Paul R Webb
Susan J Bellworthy
Yvonne I Spencer
Marion M Simmons
John Spiropoulos

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In individual animals affected by transmissible spongiform encephalopathies, different disease phenotypes can be identified which are attributed to different strains of the agent. In the absence of reliable technology to fully characterise the agent, classification of disease phenotype has been used as a strain typing tool which can be applied in any host. This approach uses standardised data on biological parameters, established for a single host, to allow comparison of different prion sources. Traditionally prion strain characterisation in wild type mice is based on incubation periods and lesion profiles after the stabilisation of the agent into the new host which requires serial passages. Such analysis can take many years, due to prolonged incubation periods. The current study demonstrates that the PrPSc patterns produced by one serial passage in wild type mice of bovine or ovine BSE were consistent, stable and showed minimal and predictable differences from mouse-stabilised reference strains. This biological property makes PrPSc deposition pattern mapping a powerful tool in the identification and definition of TSE strains on primary isolation, making the process of characterisation faster and cheaper than a serial passage protocol. It can be applied to individual mice and therefore it is better suited to identify strain diversity within single inocula in case of co-infections or identify strains in cases where insufficient mice succumb to disease for robust lesion profiles to be constructed. The detailed description presented in this study provides a reference document for identifying BSE in wild type mice.

Indexed as

AnimalsBrainCattleEncephalopathy, Bovine SpongiformImmunohistochemistryMiceParaffin EmbeddingPrion DiseasesPrPSc ProteinsRetrospective StudiesSheepPrPSc Proteins

Identifiers

PMID23245876
PMCPMC3567960

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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.