IFNγ Enhances Microglial Reactions to Hippocampal Axonal Degeneration
Bibliographic record
Abstract
Glial reactivity is implicated in CNS repair and regenerative responses. Microglia, the cells responding earliest to axonal injury, produce tumor necrosis factor-alpha (TNFalpha), a cytokine with both cytopathic and neuroprotective effects. We have studied activation of hippocampal microglia to produce TNFalpha in response to transection of perforant path axons in SJL/J mice. TNFalpha mRNA was produced in a transient manner, peaking at 2 d and falling again by 5 d after lesioning. This was unlike other markers of glial reactivity, such as Mac-1 upregulation, which were sustained over longer time periods. Message for the immune cytokine interferon-gamma (IFNgamma) was undetectable, and glial reactivity to axonal lesions occurred as normal in IFNgamma-deficient mice. Microglial responses to lesion-induced neuronal injury were markedly enhanced in myelin basic protein promoter-driven transgenic mice, in which IFNgamma was endogenously produced in hippocampus. The kinetics of TNFalpha downregulation 5 d after lesion was not affected by transgenic IFNgamma, indicating that IFNgamma acts as an amplifier and not an inducer of response. These results are discussed in the context of a regenerative role for TNFalpha in the CNS, which is innately regulated and potentiated by IFNgamma.
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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".