MétaCan
Menu
Back to cohort

Polymorphism in the Y box controls level of cytokine‐mediated expression of HLA‐DRB1 genes

2001· article· en· W2041656911 on OpenAlexaff
S Sindwani, D. P. Singal

Bibliographic record

VenueTissue Antigens · 2001
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPromoterBiologyGeneHaplotypeCytokineAlleleGeneticsImmune systemHuman leukocyte antigenTumor necrosis factor alphaMolecular biologyGene expressionImmunologyAntigen

Abstract

fetched live from OpenAlex

The HLA class II molecules play an important role in immune response. The quality of immune response is dependent not only on the polymorphisms in the class II molecules, but also on the level of their cell-surface expression. In fact, it has been demonstrated that differences in the level of expression of DRB1 and DRB3 genes restricted and activated distinct CD4+ T lymphocytes. We and others have previously described allelic polymorphisms in the upstream regulatory regions of DRB genes, which affected DNA-protein interactions and resulted in significantly different promoter strengths. We showed that polymorphisms in both the X1 and Y box motifs affect level of constitutive expression of DRB1 genes in the DR1, DR51 and DR53 haplotype groups. In the present study, we examined the effect polymorphisms in the X1 box and the Y box on the cytokine (interferon-gamma (IFNgamma), tumor necrosis factor-alpha (TNFalpha) and granulocyte macrophage-colony-stimulating factor (GM-CSF))-mediated transcriptional activities of DRB1 promoters in these, i.e. DR1, DR51 and DR53, haplotype groups. The results demonstrate that the polymorphism in the X1 box does not affect cytokine-mediated strength of DRB1 gene promoters. In contrast, the polymorphism in the Y box, which affects the inverted CCAAT sequence, plays a dominant role on the cytokine-mediated transcriptional activity of DRB1 promoters.

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 score0.072
Threshold uncertainty score0.874

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)0.0010.000

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 head0.039
GPT teacher head0.264
Teacher spread0.225 · 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

Citations7
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueTissue AntigensSame topicT-cell and B-cell ImmunologyFrench-language works237,207