Modulation of microglial functions by methyl jasmonate
Bibliographic record
Abstract
Neuroinflammation contributes to the neurodegenerative processes in Alzheimer's disease (AD); therefore, characterization of novel drug candidates aimed at combatting inflammation in the central nervous system is one of the potential avenues for the development of effective AD treatment and prevention strategies. Non-neuronal microglial cells orchestrate neuroinflammatory reactions, and their adverse activation has been linked to AD pathogenesis. Methyl jasmonate (MJ) has anti-cancer properties and has also been shown to reduce peripheral inflammation in pre-clinical models. Recently, anti-neuroinflammatory activity of MJ was demonstrated in mice, but the exact cellular and molecular mechanisms responsible for this beneficial effect are unknown. We hypothesized that MJ can regulate select microglial functions, and used two different in vitro models of microglia to test this hypothesis. MJ inhibited the production of damaging reactive oxygen species by differentiated human HL-60 promyelocytic leukemia cells without reducing their viability. MJ also selectively upregulated phagocytic activity of murine BV-2 microglia, but had no effect on nitric oxide secretion by these cells. Since microglial phagocytosis can be beneficial for clearance of amyloid β aggregates in AD, the observed upregulation of phagocytic activity by MJ, combined with its inhibitory effect on reactive oxygen species production, supports continued studies of MJ as a candidate drug for managing adverse neuroinflammation in AD.
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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".