Minocycline attenuates T cell and microglia activity to impair cytokine production in T cell-microglia interaction
Bibliographic record
Abstract
Minocycline, a tetracycline with anti-inflammatory properties, has been reported to down-regulate the activity of microglia, whose activation occurs in inflammatory and degenerative diseases of the central nervous system, such as multiple sclerosis and Alzheimer's disease. In these disorders, a T cell component is also evident, and we have demonstrated previously that the interaction of activated T cells with microglia led to the substantial increase in tumor necrosis factor alpha (TNF-alpha) levels. Here, we report that minocycline decreases TNF-alpha levels produced in human T cell-microglia interaction. This effect is mediated by a direct action of minocycline on the activated T cells and on microglia, which resulted in the decreased ability of T cells to contact microglia. In correspondence, minocycline decreased the expression on T cells of the CD40 ligand (CD40L), a key molecule regulating the contact-mediated interaction of T cells with microglia. These results demonstrate that the mechanism of action of minocycline involves not only microglia but also T cells and their subsequent activation of microglia. The capacity of minocycline to down-regulate CD40L on T cells may provide a new means to target the CD40-CD40L pathway, which regulates several inflammatory processes.
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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 | 0.000 |
| 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) | 0.002 | 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".