Chlortetracycline and Demeclocycline Inhibit Calpains and Protect Mouse Neurons against Glutamate Toxicity and Cerebral Ischemia
Bibliographic record
Abstract
Minocycline is a potent neuroprotective tetracycline in animal models of cerebral ischemia. We examined the protective properties of chlortetracycline (CTC) and demeclocycline (DMC) and showed that these two tetracyclines were also potent neuroprotective against glutamate-induced neuronal death in vitro and cerebral ischemia in vivo. However, CTC and DMC appeared to confer neuroprotection through a unique mechanism compared with minocycline. Rather than inhibiting microglial activation and caspase, CTC and DMC suppressed calpain activities. In addition, CTC and DMC only weakly antagonized N-methyl-D-aspartate (NMDA) receptor activities causing 16 and 14%, respectively, inhibition of NMDA-induced whole cell currents and partially blocked NMDA-induced Ca2+ influx, commonly regarded as the major trigger of neuronal death. In vitro and in vivo experiments demonstrated that the two compounds selectively inhibited the activities of calpain I and II activated following glutamate treatment and cerebral ischemia. In contrast, minocycline did not significantly inhibit calpain activity. Taken together, these results suggested that CTC and DMC provide neuroprotection through suppression of a rise in intracellular Ca2+ and inhibition of calpains.
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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) | 0.001 | 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) | 0.001 | 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".