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Polymerase Chain Reaction Screening for DNA Viruses in Paraffin-Embedded Brains from Dogs with Necrotizing Meningoencephalitis, Necrotizing Leukoencephalitis, and Granulomatous Meningoencephalitis

2005· article· en· W4251740787 on OpenAlexaff
Scott J. Schatzberg, Nicholas J. Haley, Stephen C. Barr, Alexander de Lahunta, Nicholas Sharp

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsD-Wave Systems (Canada)
Fundersnot available
KeywordsMeningoencephalitisCanine parvovirusVirologyParvovirusPolymerase chain reactionMedicineVirusPathologyBiology

Abstract

fetched live from OpenAlex

Abstract The objective of this investigation was to determine whether or not herpesvirus (herpes-), adenovirus (adeno-), or canine parvovirus DNA is present in the brains of dogs with necrotizing meningoencephalitis (NME), necrotizing leukoencephalitis (NLE), and granulomatous meningoencephalitis (GME). Paraffin-embedded brain specimens from 12 histopathologically confirmed dogs with NME, 3 with NLE, and 7 with GME were screened for viral DNA with degenerate herpes- and adenovirus polymerase chain reaction (PCR) and a canine parvovirus-specific PCR. Positive-control specimens included genomic viral DNA and paraffin-embedded tissues from dogs with confirmed herpes-, adeno-, or canine parvovirus infections. Herpes-, adeno-, or canine parvovirus DNA was amplified by PCR from the corresponding positive-control specimens. Negative controls included 7 dogs with various brain disorders and produced no viral amplicons. The 22 dogs with NME, NLE, and GME were negative for viral DNA. Additional studies testing for other viruses or inherited genetic mutations are warranted to gain insight into the etiologies of NME, NLE, and GME. We discuss potential etiologies and provide a clinical and histopathologic overview of these common canine encephalitides.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.340
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations76
Published2005
Admission routes1
Has abstractyes

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