Short echo-time Magnetic Resonance Spectroscopy in ALS, simultaneous quantification of glutamate and GABA at 3 T
Bibliographic record
Abstract
Cortical hyperexcitability has been found in early Amyotrophic Lateral Sclerosis (ALS) and is hypothesized to be a key factor in pathogenesis. The current pilot study aimed to investigate cortical inhibitory/excitatory balance in ALS using short-echo Magnetic Resonance Spectroscopy (MRS). Patients suffering from ALS were scanned on a 3 T Trio Siemens MR scanner using Spin Echo Full Intensity Acquired Localized (SPECIAL) Magnetic Resonance Spectroscopy in primary motor cortex and the occipital lobe. Data was compared to a group of healthy subjects. Nine patients completed the scan. MRS data was of an excellent quality allowing for quantification of a range of metabolites of interest in ALS. In motor cortex, patients had Glutamate/GABA and GABA/Cr- ratios comparable to healthy subjects. However, Glutamate/Cr (p = 0.002) and the neuronal marker N-acetyl-aspartate (NAA/Cr) (p = 0.034) were low, possibly due to grey-matter atrophy, whereas Glutathione/Cr (p = 0.04) was elevated. In patients, NAA levels correlated significantly with both hand strength (p = 0.027) and disease severity (p = 0.016). In summary SPECIAL MRS at 3 T allows of reliable quantification of a range of metabolites of interest in ALS, including both excitatory and inhibitory neurotransmitters. The method is a promising new technique as a biomarker for future studies on ALS pathophysiology and monitoring of disease progression.
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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 | 0.001 | 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".