Astrocytes Induce Hemeoxygenase-1 Expression in Microglia: A Feasible Mechanism for Preventing Excessive Brain Inflammation
Bibliographic record
Abstract
Microglia are the major inflammatory cells in the brain, in which microglial inflammatory responses are modulated by interactions with other brain cells. Here, we show that astrocytes, the most abundant cells in the brain, can secrete one or more factors capable of modulating microglial activation by regulating the microglial levels of reactive oxygen species (ROS). Treatment of microglia with astrocyte culture-conditioned media (ACM) increased the expression level and activity of hemeoxygenase-1 (HO-1). ACM also induced nuclear translocation of the nuclear factor E2-related factor 2 transcription factor, increased the binding activity of the antioxidant response element (ARE), and enhanced HO-1 promoter activity in an ARE-dependent manner. Furthermore, treatment with ACM suppressed interferon-gamma (IFN-gamma)-induced ROS production, leading to reduced inducible nitric oxide synthase (iNOS) expression and nitric oxide (NO) release. In agreement with these results, mimickers of HO-1 products, such as bilirubin, ferrous iron, and a carbon monoxide-releasing molecule, reduced IFN-gamma-induced iNOS expression and/or NO release. Finally, we found that the active component(s) in ACM was heat labile and smaller than 3 kDa. Together, these results suggest that astrocytes could cooperate with microglia to prevent excessive inflammatory responses in the brain by regulating microglial expression of HO-1 and production of ROS.
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 | 0.000 |
| 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".