Antibody-Fab and -Fc features promote Mycobacterium tuberculosis restriction
Bibliographic record
Abstract
Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), a leading cause of death by an infectious disease globally, has no efficacious vaccine. Antibodies are implicated in M. tuberculosis control, but the mechanisms of action remain poorly understood. We assembled a library of monoclonal antibodies (mAb) and screened for M. tuberculosis-restrictive activity in mice, identifying protective antibodies targeting diverse antigens. To dissect the mechanism of mAb-mediated M. tuberculosis restriction, we optimized a protective lipoarabinomannan-specific mAb, generating Fc variants. In vivo analysis of these Fc variants revealed a role for Fc-effector function in M. tuberculosis restriction. Restrictive Fc variants altered distribution of M. tuberculosis across innate immune cells. Single-cell transcriptomics highlighted distinctly activated pathways within innate immune cell subpopulations, identifying early activation of neutrophils as a key signature of mAb-mediated M. tuberculosis restriction. Therefore, antibody-mediated restriction of M. tuberculosis is associated with reorganization of the tissue-level immune response to infection and depends on the collaboration of antibody Fab and Fc.
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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 | 0.000 |
| 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".