TRPM7 inhibitor carvacrol protects brain from neonatal hypoxic-ischemic injury
Bibliographic record
Abstract
BACKGROUND: Our previous study found that suppression of TRPM7 reduced neuronal death in adult rat ischemic brain injury. It was reported that carvacrol blocked TRPM7 and attenuated brain injury in an adult rat MCAO model. The effects of carvacrol on neonatal stroke remain unknown. This study investigated the effects of carvacrol on neuronal injury and behavioral impairment after hypoxia-ischemia in neonatal mice and the potential signaling pathway underlying these effects. RESULTS: Carvacrol inhibited TRPM7 current in HEK293 cells over-expressing TRPM7 and TRPM7-like current in hippocampal neurons in a dose-dependent manner. Carvacrol (>200 μM) reduced OGD-induced neuronal injury in cortical neurons. 24 hours after HI, TRPM7 protein level in the ipsilateral hemisphere was significantly higher than in the contralateral hemisphere. Carvacrol (30 and 50 mg/kg) pre-treatment reduced brain infarct volume 24 hours after HI in a dose-dependent manner. Carvacrol pre-treatment also improved neurobehavioral outcomes. Furthermore, animals pre-treated with carvacrol had fewer TUNEL-positive cells in the brain compared to vehicle-treated animals 3 days after HI. Carvacrol pre-treatment also increased Bcl-2/Bax and p-Akt/t-Akt protein ratios and decreased cleaved caspase-3 protein expression 24 hours after HI. CONCLUSIONS: Carvacrol pre-treatment protects against neonatal hypoxic-ischemic brain injury by reducing brain infarct volume, promoting pro-survival signaling and inhibiting pro-apoptotic signaling, as well as improving behavioral outcomes. The neuroprotective effect may be mediated by the inhibition of TRPM7 channel function. Carvacrol is a potential drug development target for the treatment of neonatal stroke.
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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 | 0.001 |
| 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".