β-Glucan Induces Protective Trained Immunity against Mycobacterium tuberculosis Infection: A Key Role for IL-1
Bibliographic record
Abstract
β-glucan is a potent inducer of epigenetic and functional reprogramming of innate immune cells, a process called "trained immunity," resulting in an enhanced host response against secondary infections. We investigate whether β-glucan exposure confers protection against pulmonary Mycobacterium tuberculosis (Mtb) infection. β-glucan induces trained immunity via histone modifications at gene promoters in human monocytes, which is accompanied by the enhanced production of proinflammatory cytokines upon secondary Mtb challenge and inhibition of Mtb growth. Mice treated with β-glucan are significantly protected against pulmonary Mtb infection, which is associated with the expansion of hematopoietic stem and progenitor cells in the bone marrow and increased myelopoiesis. The protective signature of β-glucan is mediated via IL-1 signaling, as β-glucan shows no protection in mice lacking a functional IL-1 receptor (IL1R −/− ). The administration of β-glucan may be used as a novel strategy in the treatment of mycobacterial infections and possibly as an adjuvant to improve anti-tuberculosis vaccines.
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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) | 0.001 | 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) | 0.003 | 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".