Complement Factor H, a Marker of Self Protects against Experimental Autoimmune Encephalomyelitis
Bibliographic record
Abstract
The CNS innate immune response is a "double-edged sword" representing a fine balance between protective antipathogen responses and detrimental neurocytotoxic effects. Hence, it is important to identify the key regulatory mechanisms involved in the control of CNS innate immunity and which could be harnessed to explore novel therapeutic avenues. In analogy to the newly described neuroimmune regulatory proteins also known as "don't eat me" signals (CD200, CD47, CD22, fractalkine, semaphorins), we herein identify the key role of complement regulator factor H (fH) in controlling neuroinflammation initiated in an acute mouse model of Ab-dependent experimental autoimmune encephalomyelitis. Mouse fH was found to be abundantly expressed by primary cultured neurons and neuronal cell lines (N1E115 and Neuro2a) at a level comparable to BV2 microglia and CLTT astrocytes. Mouse neurons expressed other complement regulators crry and low levels of CD55. In the brain, the expression of fH was localized to neuronal bodies and axons, endothelial cells, microglia but not oligodendrocytes and myelin sheaths and was dramatically reduced in inflammatory experimental autoimmune encephalomyelitis settings. When exogenous human fH was administered to disease Ab-dependent experimental autoimmune encephalomyelitis animals, there was a significant decrease in clinical score, inflammation, and demyelination, as compared with PBS-injected animals. We found that the accumulation of human fH in the brain parenchyma protected neurons from complement opsonization, axonal injury, and leukocyte infiltration. Our data argue for a key regulatory activity of fH in neuroprotection and provide novel therapeutic avenues for CNS chronic inflammatory diseases.
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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 | 0.000 | 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 | 0.001 |
| 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".