What's happening in <i>Neurology® Clinical Practice</i>
Bibliographic record
Abstract
spectroscopy studyBackground We investigated cerebral degeneration and neurochemistry in patients with amyotrophic lateral sclerosis (ALS) using magnetic resonance spectroscopy (MRS). MethodsWe prospectively studied 65 patients and 43 age-matched healthy controls.Participants were recruited from 4 centers as part of a study in the Canadian ALS Neuroimaging Consortium.All participants underwent single-voxel proton MRS using a protocol standardized across all sites.Metabolites reflecting neuronal integrity (total N-acetyl aspartyl moieties [tNAA]) and gliosis (myo-inositol [Ino]), as well as creatine (Cr) and choline (Cho), were quantified in the midline motor cortex and midline prefrontal cortex.Comparisons were made between patients with ALS and healthy controls.Metabolites were correlated with clinical measures of upper motor neuron dysfunction, disease progression rate, and cognitive performance. ResultsIn the motor cortex, tNAA/Cr, tNAA/Cho, and tNAA/Ino ratios were reduced in the ALS group compared with controls.Group differences in tNAA/Cr and tNAA/Cho in the prefrontal cortex displayed reduced ratios in ALS patients; however, these were not statistically significant.Reduced motor cortex ratios were associated with slower foot tapping rate, whereas only motor tNAA/Ino was associated with finger tapping rate.Disease progression rate was associated with motor tNAA/Cho.Verbal fluency, semantic fluency, and digit span forwards and backwards were associated with prefrontal tNAA/Cr. ConclusionThis study demonstrates that cerebral degeneration in ALS is more pronounced in the motor than prefrontal cortex, that multicenter MRS studies are feasible, and that motor tNAA/Ino shows promise as a potential biomarker.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".