Pathological basis of diffusely abnormal white matter: insights from magnetic resonance imaging and histology
Bibliographic record
Abstract
BACKGROUND: The pathological basis of diffusely abnormal white matter (DAWM) in multiple sclerosis (MS) has not been elucidated in detail, but may be an important element in disability and clinical progression. METHODS: Fifty-three subjects with MS were examined with T₁, multi-echo T₂ and magnetization transfer (MT). Twenty-three samples of formalin-fixed MS brain tissue were examined with multi-echo T₂ and subsequently stained for myelin phospholipids using luxol fast blue, for axons using Bielschowsky, immunohistochemically for the myelin proteins myelin basic protein (MBP) and 2',3'-cyclic nucleotide 3' phosphohydrolase (CNP) and for astrocytes using glial fibrillary acidic protein (GFAP). Regions of interest in DAWM were compared with normal appearing white matter. RESULTS: Fourteen of 53 subjects with MS in the in vivo study showed the presence of DAWM. Subjects with DAWM were found to have a significantly lower Expanded Disability Status Scale (EDSS) and shorter disease duration (DD) when compared with subjects without DAWM (EDSS: 1.5 versus 3.0, p = 0.031; DD: 5.4 versus 10.3 years, p = 0.045). DAWM in vivo had reduced myelin water and MT ratio, and increased T₂ and water content. Histological analysis suggests DAWM, which shows a reduction of the myelin water fraction, is characterized by selective reduction of myelin phospholipids, but with a relative preservation of myelin proteins and axons. CONCLUSIONS: These findings suggest that the primary abnormality in DAWM is a reduction or perturbation of myelin phospholipids that correlates with a reduction of the myelin water fraction.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".