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Record W1857555449 · doi:10.1186/s12864-015-1884-7

Transcriptomic responses to prion disease in rats

2015· article· en· W1857555449 on OpenAlexafffund
Allen Herbst, Anthony Ness, Chad Johnson, Debbie McKenzie, Judd M. Aiken

Bibliographic record

VenueBMC Genomics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of Alberta
FundersAlberta Prion Research InstituteAlberta InnovatesAlberta Innovates Bio Solutions
KeywordsBiologyNeurodegenerationTranscriptomeDiseasePrion proteinGeneVirologyGeneticsGene expressionPathologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Prions diseases are fatal neurodegenerative diseases of mammals. While the molecular responses to prion infection have been extensively characterized in the laboratory mouse, little is known in other rodents. To explore these responses and make comparisons, we generated a prion disease in the laboratory rat by successive passage beginning with mouse RML prions. RESULTS: We describe the accumulation of rat prions, associated pathology and the transcriptional impact throughout the disease course. Comparative transcriptional profiling between laboratory mice and rats suggests that similar molecular and cellular processes are unfolding in response to prion infection. At the level of individual transcripts, however, variability exists between mice and rats and many genes deregulated by prion infection in mice are not affected in rats. CONCLUSION: Our findings detail the molecular responses to prion disease in the rat and highlight the usefulness of comparative approaches to understanding neurodegeneration and prion diseases in particular.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.033
GPT teacher head0.278
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations9
Published2015
Admission routes2
Has abstractyes

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