How MAIT cells control the growth of intracellular mycobacteria (P4381)
Bibliographic record
Abstract
Abstract Mucosal associated invariant T cells or MAIT cells have a semi-invariant TCR Vα chain and limited Vβ chains. In addition MAIT cell development is dependent upon the commensal microbiota and the expression of MR1, a highly conserved class Ib molecule of mammals. Mouse and human MAIT cells are activated in an MR1-restricted manner by cells infected with diverse strains for bacteria suggesting a widely shared antigen. Remarkably, human MR1 was recently shown to bind select bacterial vitamin B metabolites capable of activating MAIT cells in an MR1-restricted manner. This finding raised the interesting question of the importance of MR1 presentation of vitamin B metabolites for controlling bacterial infection. To address this question we have developed a mouse model whereby mycobacteria infected macrophages are co-cultured with purified MAIT cells, and control of intracellular bacterial growth is monitored. Using this assay, MAIT cell control of mycobacterial growth was found to depend upon IL-12 secretion by infected macrophages and IFN-γ secretion by MAIT cells. Interestingly, in the absence of infection, MAIT cells secreted IFN-γ in response to recombinant IL-12 alone or antigenic vitamin B metabolites. These findings demonstrate that MAIT cells can be activated by either TCR or non-TCR interactions. The contribution of these two pathways of MAIT cell activation in the context of mycobacterial infection is currently being investigated.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".