Magnetic resonance imaging of blood–spinal cord barrier disruption in mice with experimental autoimmune encephalomyelitis
Bibliographic record
Abstract
Inflammation, demyelination, and blood-spinal cord barrier (BSB) breakdown occur in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis. The purpose of this study was to evaluate the utility of MRI for detecting lesions and BSB disruption in vivo during EAE in the mouse lumbar spinal cord, to determine how MR features of BSB disruption change during the course of disease, and to relate such changes to clinical signs and histological features of disease. Following induction of EAE in C57BL/6 mice, contrast-enhanced (CE) T(1)-weighted MR images were acquired to detect BSB disruption in the lumbar spinal cord at the early stage of disease, at peak disease, and at remission, and T(2)-weighted images were obtained to monitor spinal cord morphology. Following imaging the spinal cords were assessed in situ for general features of inflammation, BSB leakage, activated macrophages/microglia, and demyelination. No focal lesions were evident on T(2)-weighted MR images. BSB disruption was greatest at the onset of signs of disease, and decreased progressively thereafter. Inflammation and demyelination were pronounced at the initial stage of disease and at peak disease, and were decreased at remission. Nonuniform contrast enhancement indicated that breakdown of the BSB occurred predominantly within the white matter (WM) of the spinal cord.
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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 | 0.000 | 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) | 0.001 | 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".