Neonatal BCG Vaccination Engages the Vasculature to Elicit γδ T Cell–Mediated Protec-tion against Tuberculosis
Bibliographic record
Abstract
Abstract The Bacillus Calmette–Guérin (BCG) vaccine remains the only approved vaccine against tuber-culosis (TB). Although its efficacy against pulmonary TB in adults is limited, BCG provides re-markable protection against miliary TB when administered during infancy. Despite more than 100 million infants worldwide receiving BCG annually, the mechanisms underlying its neonatal protective effects remain poorly defined. Here, we demonstrate that subcutaneous neonatal BCG vaccination (BCG-sc) induces a marked expansion of γδ T cells producing IL-17 and IL-22, which mediated protection against subsequent Mycobacterium tuberculosis ( Mtb ) experimental infection. A similar expansion of γδ T cells was observed in a longitudinal cohort of infants, from birth to three months of infants followed after intradermal BCG vaccination. Mechanistical-ly, BCG-mediated protection in neonates was linked to its early vascular dissemination through the distinct structure of neonatal skin, resembling the protective effects of intravenous BCG in adults. Moreover, neonatal BCG-sc vaccination generated a distinct BCG-induced microbiome signature, characterized by enrichment of Prevotellaceae , Tannerellaceae , and Bifidobacteriaceae , which was associated with protection. Together, these findings identify γδ T cells as key mediators of early-life BCG-induced immunity and highlight the role of the gut–lung axis in long-term protection against TB from infancy into adulthood.
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 | 0.001 |
| 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".