Mechanisms underlying macrophage polarization in spinal cord injury ‐ detrimental and beneficial influences on recovery
Bibliographic record
Abstract
Activated macrophages in the injured CNS can have detrimental and beneficial effects, which may be due to their polarization state. Macrophages can be polarized along a continuum to M1 cells which are pro‐inflammatory and cytotoxic, and M2 cells which are anti‐inflammatory and pro‐repair. Myelin phagocytosis in vitro can induce M1 polarized cells to shift to a M2 phenotype. However, although myelin phagocytosis occurs after spinal cord injury (SCI), macrophages remain predominantly M1 polarized. Our work shows that this failure to switch to a M2 phenotype in vivo after SCI despite on‐going phagocytosis is due in part to TNF. TNF which is upregulated after SCI prevents the myelin phagocytosis induced switch from M1 to M2 polarization. Our work also shows that iron loading of macrophages induces M2 polarized cells to switch to M1 cells and produce TNF. This is important because hemorrhage and cell death after SCI lead to the release of iron. These data indicate that TNF can prevent phagocytosis induced shift of M1 to M2, and increased intracellular iron can promote shift of M2 to M1 phenotype. The combined effect of these influences is detrimental to recovery after SCI.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".