Glutamate, GABA and glutathione in adults with persistent post-concussive symptoms
Bibliographic record
Abstract
Persistent post-concussive symptoms (PPCS) are debilitating and endure beyond the usual recovery period after mild traumatic brain injury (mTBI). Altered neurotransmission, impaired energy metabolism and oxidative stress have been examined acutely post-injury but have not been explored extensively in those with persistent symptoms. Specifically, the antioxidant glutathione (GSH) and the excitatory and inhibitory metabolites, glutamate (Glu) and γ-aminobutyric acid (GABA), are seldom studied together in the clinical mTBI literature. While Glu can be measured using conventional magnetic resonance spectroscopy (MRS) methods at 3 Tesla, GABA and GSH require the use of advanced MRS methods. Here, we used the recently established Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) to simultaneously measure GSH and GABA and short-echo time point resolved spectroscopy (PRESS) to measure Glu to gain new insight into the pathophysiology of PPCS. Twenty-nine adults with PPCS (mean age: 45.69 years, s.d.: 10.73, 22 females, 7 males) and 29 age- and sex-matched controls (mean age: 43.69 years, s.d.: 11.00) completed magnetic resonance spectroscopy scans with voxels placed in the anterior cingulate and right sensorimotor cortex. Relative to controls, anterior cingulate Glu was significantly reduced in PPCS. Higher anterior cingulate GABA was significantly associated with a higher number of lifetime mTBIs, suggesting GABA may be upregulated with repeated incidence of mTBI. Furthermore, GSH in both regions of interest was positively associated with symptoms of sleepiness and headache burden. Collectively, our findings suggest that the antioxidant defense system is active in participants with PPCS, however this may be at the expense of other glutamatergic functions such as cortical excitation and energy metabolism.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".