Myelin water measurement in the spinal cord
Bibliographic record
Abstract
The desire to monitor the spatial-temporal characteristics of myelination in the spinal cord (SC), in the context of pathological change in demyelinating diseases or proposed neuroregenerative protocols, has led to an interest in noninvasive image-based myelin measurement methods. We present one strategy: a magnetic resonance-based measure that capitalizes on the characteristics of T(2) relaxation of water compartmentalized within tissue. In this study, 32-echo relaxation studies for measuring the myelin water fraction (MWF) were applied in healthy control SC in vivo using a sagittal inversion recovery multiecho sequence, and findings were supported with supplemental studies in bovine SC samples in vitro. Mean human MWF varied according the level of the SC examined: cervical, thoracic, and lumbar MWF was found to be 21.8 (SD=2.1)%, 24.3 (3.6)%, and 11.4 (6.4)%, respectively. Noteworthy reductions were observed in areas consistent with the expected locations of the cervical and lumbar enlargements. Average bovine MWF was 30.0 (2.7)% in white matter and 8.2 (0.4)% in gray matter. The potential applications of T(2) measurement in SC, both in characterizing disease processes like multiple sclerosis and in monitoring neuroregenerative therapies, should encourage future research in this area.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".