Sex-dependent perturbations in risky choice behavior and prefrontal tyrosine hydroxylase levels induced by repetitive mild traumatic brain injury
Bibliographic record
Abstract
Head trauma often impairs cognitive processes mediated within the prefrontal cortex (PFC), leading to impaired decision making and risk-taking behavior. Mild traumatic brain injury (mTBI) accounts for approximately 80 % of reported head injury cases. Most neurological symptoms of a single mTBI are transient; however, growing evidence suggests that repeated mTBI (rmTBI) results in more severe impairments that worsen with each subsequent injury. Although mTBI-induced disruption of risk/reward decision making has been characterized, the potential for rmTBI to exacerbate these effects and the neural mechanisms involved are unknown. Catecholamine neurotransmitters, dopamine (DA) and norepinephrine (NE), modulate PFC-mediated functions. Imbalances in catecholamine function have been associated with TBI and may underlie aberrant decision making. We used a closed head-controlled cortical impact (CH-CCI) model in rats to evaluate the effects of rmTBI on performance of a probabilistic discounting task of risk/reward decision making behavior and expression levels of catecholamine regulatory proteins within the PFC. RmTBI produced transient increases in risky choice preference in both male and female rats, with these effects persisting longer in females. Additionally, rmTBI increased expression of the catecholamine synthetic enzyme, tyrosine hydroxylase (TH), within the orbitofrontal (OFC) region of the PFC in females only. These results suggest females are more susceptible to rmTBI-induced disruption of risk/reward decision making behavior and dysregulation of catecholamine synthesis within the OFC. Together, using the CH-CCI model of rodent rmTBI to evaluate the effects of multiple insults on risk-taking behavior and PFC catecholamine regulation begins to differentiate how mTBI occurrences affect neuropathological outcomes across different sexes.
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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) | 0.002 | 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".