Breakdown of CTL Tolerance to Self HLA-B*2705 Induced by Exposure to <i>Chlamydia</i> <i>trachomatis</i>
Bibliographic record
Abstract
There is a strong association between seronegative arthritis and HLA B27, but it is still unresolved whether the contribution of B27 to disease pathogenesis is solely as a restriction element for an arthritogenic peptide, or whether B27 itself serves as an autoantigen. This study uses transgenic rats to address the question as to whether exposure to an arthritogenic pathogen can alter tolerance to B27. Unlike their nontransgenic counterparts, B27-transgenic rats are tolerant of B27 immunization using either B27(+) splenocytes or plasmid DNA and do not develop anti-B27 CTL. However, if splenocytes from such immunized animals are exposed to Chlamydia in vitro, CTL are generated that lyse B27(+) targets. No killing was seen with targets transfected with control B7, B14, B40, or B44. This phenomenon was not observed with immunization by nontransgenic splenocytes, or HLA-A2 DNA alone. Using targets expressing mutated B27, we show that the epitope for autoreactive CTL recognition of B27 involves the Lys(70) amino acid residue in the alpha(1) domain of the MHC class I molecule. The generation of CTL with specificity for B27 under these conditions demonstrates that tolerance to B27 can be subverted by CHLAMYDIA: This indicates a dynamic interrelationship between the pathogen and B27, which may have important implications for B27-related spondyloarthropathies triggered by intracellular bacteria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".