Statin treatment affects cytokine release and phagocytic activity in primary cultured microglia through two separable mechanisms
Bibliographic record
Abstract
BACKGROUND: As the primary immune cells of the central nervous system, microglia contribute to development, homeostasis, and plasticity of the central nervous system, in addition to their well characterized roles in the foreign body and inflammatory responses. Increasingly, inappropriate activation of microglia is being reported as a component of inflammation in neurodegenerative and neuropsychiatric disorders. The statin class of cholesterol-lowering drugs have been observed to have anti-inflammatory and protective effects in both neurodegenerative diseases and ischemic stroke, and are suggested to act by attenuating microglial activity. RESULTS: We sought to investigate the effects of simvastatin treatment on the secretory profile and phagocytic activity of primary cultured rat microglia, and to dissect the mechanism of action of simvastatin on microglial activity. Simvastatin treatment altered the release of cytokines and trophic factors from microglia, including interleukin-1-β, tumour necrosis factor-α, and brain derived neurotrophic factor in a cholesterol-dependent manner. Conversely, simvastatin inhibited phagocytosis in microglia in a cholesterol-independent manner. CONCLUSIONS: The disparity in cholesterol dependence of cytokine release and phagocytosis suggests the two effects occur through distinct molecular mechanisms. These two pathways may provide an opportunity for further refinement of pharmacotherapies for neuroinflammatory, neurodegenerative, and neuropsychiatric disorders.
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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) | 0.001 | 0.001 |
| 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".