Innate Response Activator B Cells Aggravate Atherosclerosis by Stimulating T Helper-1 Adaptive Immunity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Atherosclerotic lesions grow via the accumulation of leukocytes and oxidized lipoproteins in the vessel wall. Leukocytes can attenuate or augment atherosclerosis through the release of cytokines, chemokines, and other mediators. Deciphering how leukocytes develop, oppose, and complement each other's function and shape the course of disease can illuminate our understanding of atherosclerosis. Innate response activator (IRA) B cells are a recently described population of granulocyte macrophage colony-stimulating factor-secreting cells of hitherto unknown function in atherosclerosis. METHODS AND RESULTS: Here, we show that IRA B cells arise during atherosclerosis in mice and humans. In response to a high-cholesterol diet, IRA B cell numbers increase preferentially in secondary lymphoid organs via Myd88-dependent signaling. Mixed chimeric mice lacking B cell-derived granulocyte macrophage colony-stimulating factor develop smaller lesions with fewer macrophages and effector T cells. Mechanistically, IRA B cells promote the expansion of classic dendritic cells, which then generate interferon γ-producing T helper-1 cells. This IRA B cell-dependent T helper-1 skewing manifests in an IgG1-to-IgG2c isotype switch in the immunoglobulin response against oxidized lipoproteins. CONCLUSIONS: Granulocyte macrophage colony-stimulating factor-producing IRA B cells alter adaptive immune processes and shift the leukocyte response toward a T helper-1-associated milieu that aggravates atherosclerosis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it