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Record W1967463201 · doi:10.1080/10425170701295856

Molecular cloning and expression analysis of chicken <i>MyD88</i> and <i>TRIF</i> genes

2007· article· en· W1967463201 on OpenAlexafffund
Sarah Wheaton, Melissa D. Lambourne, Aimie J. Sarson, Jennifer T. Brisbin, Ashraf Mayameei, Shayan Sharif

Bibliographic record

VenueDNA sequence · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of Guelph
FundersLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaNatural Sciences and Engineering Research Council of CanadaCanadian Poultry Research Council
KeywordsTRIFGeneBiologyOpen reading frameComplementary DNACloning (programming)Sequence analysisInnate immune systemGeneticsCoding regionPeptide sequenceToll-like receptorMolecular biologyReceptor

Abstract

fetched live from OpenAlex

Toll-like receptors (TLRs) trigger the innate immune system by responding to specific components of microorganisms. MyD88 and TRIF are Toll/interleukin (IL)-1 (TIR)-domain containing adapters, which play essential roles in TLR-mediated signalling via the MyD88-dependant and -independent pathways, respectively. Genes encoding several TLRs have been identified in the chicken genome, however, elements of their signalling pathways have not been well characterized. Here we describe the cloning of chicken MyD88 and TRIF orthologs, and examine the spatial and temporal expression of these genes. The chicken MyD88 cDNA was shown to have an open reading frame (ORF) of 1104 bp, encoding a predicted protein sequence of 368 aa, 8 aa short of a previously published coding sequence due to a premature stop codon. MyD88 gene expression was detected in each tissue tested except in muscle. The chicken TRIF cDNA possessed an ORF of 2205 bp, encoding a predicted protein sequence of 735 aa, which shared 37.3% similarity and 28.9% identity to human TRIF protein sequence. TRIF was ubiquitously expressed in all tissues.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.250
Teacher spread0.240 · 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.

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

Citations36
Published2007
Admission routes2
Has abstractyes

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