Hypoxia-activated microglial mediators of neuronal survival are differentially regulated by tetracyclines
Bibliographic record
Abstract
The tetracycline derivatives minocycline (MINO) and doxycycline (DOXY) have been shown to be neuroprotective in in vivo and in vitro models of stroke. This neuroprotection is thought to be due to the suppression of microglial activation. However, the specific molecular parameters in microglia of the tetracyclines' effect are not understood. We subjected cultured rat microglial and neuronal cells to in vitro hypoxia and examined the effects of MINO and DOXY pre-treatments. Our data showed that MINO and DOXY protect against hypoxia-induced neuronal death by a mechanism dependent on regulation of microglial factors, but likely unrelated to regulation of microglial proliferation/viability. Both MINO and DOXY suppressed the hypoxic activation of ED-1, a marker for microglial activation. Morphological analyses of hypoxic microglia using the microglial marker Iba1 revealed that treatment with MINO and DOXY caused a higher percentage of microglia to remain in a non-activated state. MINO suppressed the hypoxic upregulation of pro-inflammatory agents nitric oxide (NO), interleukin-1 beta (IL-1beta), and tumor necrosis factor alpha (TNF-alpha), while DOXY down-regulated only NO and IL-1beta. In contrast, the hypoxic activation of pro-survival/neuroprotective microglial proteins, such as brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF), were unaffected by tetracycline treatments. Taken together, these results suggest that MINO and DOXY may provide neuroprotection against stroke by selectively down-regulating microglial toxic factors while maintaining functional pro-survival factors.
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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".