VEGF-A from Granuloma Macrophages Regulates Granulomatous Inflammation by a Non-angiogenic Pathway during Mycobacterial Infection
Bibliographic record
Abstract
Many autoimmune and infectious diseases are characterized by the formation of granulomas which are inflammatory lesions that consist of spatially organized immune cells. These sites protect the host and control pathogens like Mycobacterium tuberculosis (Mtb), but are highly inflammatory and cause pathology. Using bacille Calmette-Guerin (BCG) and Mtb infection in mice that induce sarcoid or caseating granulomas, we show that a subpopulation of granuloma macrophages produces vascular endothelial growth factor (VEGF-A), which recruits immune cells to the granuloma by a non-angiogenic pathway. Selective blockade of VEGF-A in myeloid cells, combined with granuloma transplantation, shows that granuloma VEGF-A regulates granulomatous inflammation. The severity of granuloma-related inflammation can be ameliorated by pharmaceutical or genetic inhibition of VEGF-A, which improves survival of mice infected with virulent Mtb without altering host protection. These data show that VEGF-A inhibitors could be used as a host-directed therapy against granulomatous diseases like tuberculosis and sarcoidosis, thereby expanding the value of already existing and approved anti-VEGF-A drugs.
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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".