GM-CSF upregulates IL-15 expression on specific human myeloid cells.
Bibliographic record
Abstract
Abstract Although the salience of the immune system in multiple sclerosis (MS) pathology has been established, the mechanisms and mediators involved are incompletely characterized. We have identified IL-15, which aids in the development, activation, and survival of immune cells, as a relevant contributor to MS neuropathology. We previously showed that greater proportions of myeloid cells, including peripheral monocytes and brain macrophages/microglia, from MS patients express IL-15 versus controls. Thus, we aim to identify the factors that contribute to these elevated IL-15 levels in the context of MS. Primary human monocytes from MS patients and age/sex matched healthy donors are treated with M-CSF to trigger differentiation into macrophages (considered M0 macrophages) prior to being polarized into M1 or M2 macrophages. While a small proportion of M0 macrophages express IL-15, M2 polarization significantly enhances the percentage of IL-15+ macrophages. In contrast, M1 polarization does not affect IL-15 levels although it significantly increases MHCI and CD80 expression. GM-CSF is produced by pathogenic encephalitogenic T cells; monocytes and macrophages express the corresponding receptor (GM-CSF receptor). GM-CSF induces a major increase in the proportion of IL-15+ M0 and M2 macrophages from both donor groups. In contrast, GM-CSF does not modify IL-15 expression by monocytes although it induces STAT5 phosphorylation. In conclusion, GM-CSF is a potent trigger for IL-15 expression on M0/M2 macrophages but not monocytes. Moreover, M2 polarization of macrophages increases IL-15 expression. Identification of IL-15 triggers and further characterization of IL-15+ immune cells may provide novel targets for therapies for MS patients.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".