Mycobacterium tuberculosis in the adjuvant modulates the balance of Th immune response to self-antigen of the CNS without influencing a “core” repertoire of specific T cells
Bibliographic record
Abstract
In the present study, we use modified CDR3 beta-chain spectratyping (immunoscope) to dissect the effect of Mycobacterium tuberculosis (MT)-derived proteins on individual PLP139-151-specific cells in the SJL mouse strain. In this model, the immunoscope technique allows the characterization of a public TCR that involves rearrangement of Vbeta10 and Jbeta1.1 and a semi-private TCR characterized by rearrangement of Vbeta4 and Jbeta1.6. Both rearrangements are specific for PLP139-151 and sequences of the CDR3 region of the two beta-chains show a conserved motif for the public rearrangement and related but more variable sequences for the semi-private rearrangement. MT-derived proteins promote increase of IFN-gamma-secreting cells. However, we observe that the presence and amount of MT used during immunization have no effect on the frequency of usage, polarization and in vivo expansion of cells carrying the studied rearrangements. Rather, the strong Th1-promoting effect of adjuvant is possibly due to recruitment toward Th1 of a wider spectrum of TCR repertoires. Therefore, instead of having a comprehensive effect on the entire repertoire, MT modulates the immune response by affecting a subset of antigen-specific T cells whose polarization can be adapted to the environment. This step establishes the final balance between Th1 and Th2 and may be essential for the enhancement or protection of disease.
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 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".