Granulocyte–macrophage colony‐stimulating factor–stimulated human macrophages demonstrate enhanced functions contributing to T‐cell activation
Bibliographic record
Abstract
Abstract Granulocyte–macrophage colony‐stimulating factor (GM‐CSF) has been implicated in numerous chronic inflammatory diseases, including multiple sclerosis (MS). GM‐CSF impacts multiple properties and functions of myeloid cells via species‐specific mechanisms. Therefore, we assessed the effect of GM‐CSF on different human myeloid cell populations found in MS lesions: monocyte‐derived macrophages (MDMs) and microglia. We previously reported a greater number of interleukin (IL)‐15 + myeloid cells in the brain of patients with MS than in controls. Therefore, we investigated whether GM‐CSF exerts its deleterious effects in MS by increasing IL‐15 expression on myeloid cells. We found that GM‐CSF increased the proportion of IL‐15 + cells and/or IL‐15 levels on nonpolarized, M1‐polarized and M2‐polarized MDMs from healthy donors and patients with MS. GM‐CSF also increased IL‐15 levels on human adult microglia. When cocultured with GM‐CSF–stimulated MDMs, activated autologous CD8 + T lymphocytes secreted and expressed significantly higher levels of effector molecules (e.g. interferon‐γ and GM‐CSF) compared with cocultures with unstimulated MDMs. However, neutralizing IL‐15 did not attenuate enhanced effector molecule expression on CD8 + T lymphocytes triggered by GM‐CSF–stimulated MDMs. We showed that GM‐CSF stimulation of MDMs increased their expression of CD80 and ICAM‐1 and their secretion of IL‐6, IL‐27 and tumor necrosis factor. These molecules could participate in boosting the effector properties of CD8 + T lymphocytes independently of IL‐15. By contrast, GM‐CSF did not alter CD80, IL‐27, tumor necrosis factor and chemokine (C–X–C motif) ligand 10 expression/secretion by human microglia. Therefore, our results underline the distinct impact of GM‐CSF on human myeloid cells abundantly present in MS lesions.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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) | 0.005 | 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 teacher head, 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".