Interferon-gamma and the regulation of neuroinflammation
Bibliographic record
Abstract
Inflammation of the central nervous system (CNS) is important in many human diseases, and is regulated by a multitude of factors, including the cytokine interferon-gamma (IFNgamma). The importance of IFNgamma is highlighted in experimental autoimmune encephalomyelitis (EAE), an animal model of CNS inflammation. Mice lacking IFNgamma show exaggerated disease, with a different pattern of chemokine expression than the wild-type. We administered IFNgamma to the CNS using intrathecal injection of a replication-defective adenoviral vector to ask about direct actions of IFNgamma on chemokine expression without the confounding factors present during CNS inflammation. AdIFNgamma induced expression of CXCL10 and CCL5, two chemokines strikingly absent in Ifng-/- EAE. Chemokine expression was not associated with inflammation, though when an infectious stimulus was administered, an influx of immune cells to the CNS was seen. Using AdIFNgamma to restore IFNgamma to Ifng-/- mice with EAE had a disease-limiting effect. We used vectors encoding CXCL10 or CCL5, to replace these chemokines which are absent during Ifng-/- EAE, attempting to modulate the disease into a form resembling that of the wild-type. AdCCL5 treatment showed a mild reduction in EAE severity in the Ifng-/-, though AdCXCL10 treatment had no effect. A principal inducer of IFNgamma is interleukin-18 (IL 18), and IFNgamma induces IL18-binding protein (IL18bp) which inhibits IL18, establishing a negative feedback loop. We found that ILl8bp expression is upregulated in wild-type mice with EAE, but not in the Ifng-/-, suggesting that the exaggerated disease of the Ifng -/- may be due in part to unrestrained actions of ILI8. Treatment with a vector encoding IL18bp (AdIL18bp) significantly inhibited EAE, without restricting immune cell entry to the CNS. Cytokine expression was shifted away from a pattern favouring Th17 development. AdIL18bp treatment inhibited EAE in Ifng-/- mice, indicating that IFNgamma was not required for this activity. We used a vector encoding M3, a chemokine-binding protein derived from MHV-68, to reduce EAE severity, showing the first use of a viral chemokine-binding protein in EAE.
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 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".