Astrocytes play a key role in activation of microglia by persistent Borna disease virus infection
Bibliographic record
Abstract
Neonatal Borna disease virus (BDV) infection of the rat brain is associated with microglial activation and damage to certain neuronal populations. Since persistent BDV infection of neurons is nonlytic in vitro, activated microglia have been suggested to be responsible for neuronal cell death in vivo. However, the mechanisms of activation of microglia in neonatally BDV-infected rat brains remain unclear. Our previous studies have shown that activation of microglia by BDV in culture requires the presence of astrocytes as neither the virus nor BDV-infected neurons alone activate microglia. Here, we evaluated the mechanisms whereby astrocytes can contribute to activation of microglia in neuron-glia-microglia mixed cultures. We found that persistent infection of neuronal cells leads to activation of uninfected astrocytes as measured by elevated expression of RANTES. Activation of astrocytes then produces activation of microglia as evidenced by increased formation of round-shaped, MHCI-, MHCII- and IL-6-positive microglia cells. Our analysis of possible molecular mechanisms of activation of astrocytes and/or microglia in culture indicates that the mediators of activation may be soluble heat-resistant, low molecular weight factors. The findings indicate that astrocytes may mediate activation of microglia by BDV-infected neurons. The data are consistent with the hypothesis that microglia activation in the absence of neuronal damage may represent initial steps in the gradual neurodegeneration observed in brains of neonatally BDV-infected rats.
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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 | 0.000 |
| 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".