GM-CSF is a marker of compartmentalised intrathecal inflammation in multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Granulocyte-macrophage colony stimulating factor (GM-CSF) is a pro-inflammatory cytokine secreted by various immune cells. Several studies have demonstrated an expansion of GM-CSF producing T cells in the blood or CSF of people with MS (pwMS). However, whether this equates to greater concentrations of circulating cytokine remains unknown as quantification is difficult with traditional assays. OBJECTIVE: To determine whether GM-CSF can be quantified and whether GM-CSF levels are elevated in pwMS. METHODS: We employed Single Molecule Array (Simoa) to measure GM-CSF in both CSF and blood. We then investigated relationships between GM-CSF levels and measures of blood-CSF-barrier integrity. RESULTS: GM-CSF was quantifiable in all samples and was significantly higher in the CSF of pwMS compared with controls. No association was found between CSF GM-CSF levels and Q-Albumin - a measure of blood-CSF-barrier integrity. CSF GM-CSF correlated with measures of intrathecal inflammation, and these relationships were greater in primary progressive MS compared with relapsing-remitting MS. CONCLUSION: GM-CSF levels are elevated specifically in the CSF of pwMS. Our results suggest that elevated cytokine levels may reflect (at least partial) intrathecal production, as opposed to simple diffusion across a dysfunctional blood-CSF-barrier.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".