Ultrahigh-resolution MRI Reveals Extensive Cortical Demyelination in a Nonhuman Primate Model of Multiple Sclerosis
Bibliographic record
Abstract
Cortical lesions are a primary driver of disability in multiple sclerosis (MS). However, noninvasive detection of cortical lesions with in vivo magnetic resonance imaging (MRI) remains challenging. Experimental autoimmune encephalomyelitis (EAE) in the common marmoset is a relevant animal model of MS for investigating the pathophysiological mechanisms leading to brain damage. This study aimed to characterize cortical lesions in marmosets with EAE using ultrahigh-field (7 T) MRI and histological analysis. Tissue preparation was optimized to enable the acquisition of high-spatial resolution (50-μm isotropic) T2*-weighted images. A total of 14 animals were scanned in this study, and 70% of the diseased animals presented at least one cortical lesion on postmortem imaging. Cortical lesions identified on MRI were verified with myelin proteolipid protein immunostaining. An optimized T2*-weighted sequence was developed for in vivo imaging and shown to capture 65% of cortical lesions detected postmortem. Immunostaining confirmed extensive demyelination with preserved neuronal somata in several cortical areas of EAE animals. Overall, this study demonstrates the relevance and feasibility of the marmoset EAE model to study cortical lesions, among the most important yet least understood features of MS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".