Myrcene as a potential natural treatment in mild traumatic brain injury: Neurosensory changes
Bibliographic record
Abstract
Mild traumatic brain injury (mTBI) represents a significant public health concern, often resulting in long-term cognitive, emotional, and behavioral impairments. Despite its prevalence, effective therapeutic strategies for mitigating mTBI consequences remain limited. For the first time, this study seeks to explore the potential neuroprotective properties of myrcene, a natural compound with promising implications for intervention. Myrcene, a monoterpene abundant in various plant species, exhibits notable anti-inflammatory, antioxidant, and neuroprotective properties. Preclinical studies have shown its efficacy in mitigating neuroinflammation, reducing oxidative stress, and enhancing neuronal survival, suggesting its potential utility in ameliorating mTBI-induced neuronal damage. Among the various sequelae of mTBI, alterations in pain, motor coordination, general well-being, aggression, sociability behaviors, and depression are prominent, highlighting the urgent need for effective therapeutic strategies. Given the absence of options and the promising neuroprotective attributes of myrcene, this study investigated myrcene efficacy in reducing mTBI consequences in a mouse model through a multi-disciplinary approach using behavioral tests, brain tissue immunofluorescence, and LC-MS analysis of endocannabinoids in microdialysates from the prelimbic cortex of treated mice. Our results support the potential effect of myrcene treatment on pain, quality of life, and mood regulation, while rebalancing morphological and neurochemical changes by regulating endocannabinoid levels. • This study presents the first multidisciplinary evaluation of myrcene in mTBI treatment. • Chronic myrcene reduces pain sensitivity, improves well-being and coordination, and lessens aggression post-mTBI. • Myrcene restores hippocampal PV expression and reduces c-Fos activity after injury. • Neurochemical balance is reestablished via modulation of GABA, Glu, Gly, and endocannabinoids.
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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) | 0.003 | 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".