Short-interval intracortical inhibition and facilitation in amyotrophic lateral sclerosis related to disease phenotype
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between short-interval intracortical inhibition (SICI), short-interval intracortical facilitation (SICF) and amyotrophic lateral sclerosis (ALS) phenotype, using threshold-tracking transcranial magnetic stimulation (TMS). METHODS: A new paired-pulse TMS protocol was applied to 49 patients with ALS and 49 age-matched healthy controls. Motor evoked potentials (MEPs) were recorded from first dorsal interosseus muscle, while paired pulses were delivered at interstimulus intervals (ISI) of 1.0, 2.5 or 3.0 ms, with stimuli related to the resting motor threshold for a 200 µV MEP. For each ISI, 6 SICI and 3 SICF pulse pairs with different conditioning stimuli were randomised and interleaved with test-alone stimuli. RESULTS: ALS phenotypes were characterised as Pyramidal (n = 12, with prominent upper motor neuron signs), Classic (n = 20, with limb onset), or Bulbar (n = 17). Compared with healthy controls, Bulbar patients had significantly less inhibition at all ISIs, while SICI in Pyramidal patients was normal, and in Classic patients intermediate. The only SICF abnormalities independent of the changes in SICI were less facilitation in Pyramidal patients at ISIs 1 and 3 ms. CONCLUSION: Changes in SICI and SICF depend on ALS phenotype. SIGNIFICANCE: ALS phenotypes should be matched between treatment and placebo arms of clinical trials.
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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) | 0.002 | 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".