Detection of Cerebral Degeneration in Amyotrophic Lateral Sclerosis Using High-Field Magnetic Resonance Spectroscopy
Bibliographic record
Abstract
BACKGROUND: Clinical assessment is insensitive to the degree of cerebral involvement in amyotrophic lateral sclerosis (ALS). Regional brain concentrations N-acetylaspartylglutamate (NAA) plus myo-inositol (Ins), as measured by magnetic resonance spectroscopy, are respectively decreased and increased, suggesting that these compounds may provide a biomarker of the degree of cerebral involvement in ALS. OBJECTIVE: To test the hypothesis that the NAA/Ins ratio may provide an index of cerebral involvement in patients with ALS. DESIGN: High-field (3.0-T) magnetic resonance spectroscopy was performed to determine the NAA/creatine plus phosphocreatine (NAA/Cr), NAA/choline (NAA/Cho), Ins/Cr, and NAA/Ins ratios in the motor cortex. PARTICIPANTS: Seventeen patients with ALS and 15 healthy control subjects were studied. RESULTS: In patients with ALS, the greatest abnormality was a 22% decrease in NAA/Ins (71% sensitivity and 93% specificity, P = .001); Ins/Cr was increased 18% (88% sensitivity and 53% specificity, P = .04), NAA/Cr was decreased 10% (88% sensitivity and 47% specificity, P = .04), and NAA/Cho was decreased 14% (53% sensitivity and 87% specificity, P = .047). Correlation of the ALS Functional Rating Scale with NAA/Ins approached statistical significance (R = 0.43, P = .07). CONCLUSION: The NAA/Ins ratio may provide a meaningful biomarker in ALS given its optimal sensitivity and specificity profile.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".