N-Acetyl-Aspartate in the Dorsolateral Prefrontal Cortex Long After Concussion in Youth
Bibliographic record
Abstract
OBJECTIVE: Despite increasing interest in the neurobiological effects of concussion in youth, a paucity of information is available regarding outcomes long after injury. The objective of this study was to determine the association between a history of concussion and the putative neuronal marker N-acetyl-aspartate (NAA) in the dorsolateral prefrontal cortex (DLPFC) in youth. SETTING: Outpatient clinic in a children's hospital. PARTICIPANTS: Youth with concussion (N = 35, mean = 2.63, SD = 1.07 years postinjury) and youth with a nonconcussive orthopedic injury (N = 17) participated. DESIGN: A cross-sectional proton magnetic resonance spectroscopy (H-MRS) study. MAIN MEASURES: The primary outcome measure was NAA concentration in the right and left DLPFCs. RESULTS: We observed lower levels of NAA in the right DLPFC in youth with past concussion (F = 3.31, df = 4,51, P = .018) than in orthopedic controls but not in the left DLPFC (F = 2.04, df = 4,51, P = .105). The effect of lower NAA concentrations in the right DLPFC was primarily driven by youth with a single prior concussion versus those with multiple concussions. NAA in the left DLPFC, but not in right DLPFC, was associated with worse emotional symptoms in youth with concussion. CONCLUSION: The presence of lower levels of DLPFC NAA suggests potential association of concussion in youth, although further investigation is needed, given that the result is driven by those with a single (and not multiple) concussion. Exploration of applying MRS in other brain regions is also warranted.
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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 | 0.001 |
| 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".