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Record W2098759281 · doi:10.1080/10495398.2011.580219

Single Nucleotide Polymorphisms Alter the Promoter Activity of Bovine MIF

2011· article· en· W2098759281 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Biotechnology · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMacrophage Migration Inhibitory Factor
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMacrophage migration inhibitory factorSingle-nucleotide polymorphismBiologyParatuberculosisGeneTranscription factorSNPPromoterCytokinePathogenesisImmunologyGeneticsMolecular biologyGene expressionGenotypeMycobacteriumBacteria

Abstract

fetched live from OpenAlex

Macrophage migration inhibitory factor (MIF) is a unique pro-inflammatory cytokine whose chief functions include modulating TLR4 expression, and suppressing the anti-inflammatory effects of glucocorticoids. Not surprisingly, MIF is involved in a number of inflammatory diseases and single nucleotide polymorphisms (SNPs) have been implicated in modulating disease severity. The objective of the present study was to determine if SNPs in 5' region of bovine MIF affects its promoter activity. Three SNPs were identified, -1078A>G, -395A>G, and -400G>C, all of which fall within predicted transcription factor binding regions. Reporter gene assays indicate that the identified SNPs have a significant effect of modulating MIF promoter activity. Finally, gene association analysis suggests a significant relationship of -395A>G with the susceptibility to Mycobacterium avium ssp. paratuberculosis infection, the causative agent of Johne's disease. Given the relationships revealed in the current study, it is clear that the role of MIF in bovine diseases such as Johne's disease merits further investigation.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.016
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.221
Teacher spread0.198 · 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