Early regional cuprizone‐induced demyelination in a rat model revealed with MRI
Bibliographic record
Abstract
The cuprizone model of demyelination is well established in the mouse as a tool for the study of the mechanisms of both demyelination and remyelination. It is often desirable, however, to have a larger model, such as the rat, especially for imaging‐based studies, yet initial work has failed to show demyelination in cuprizone‐fed rats. Several recent studies have demonstrated demyelination in the rat, but only in the corpus callosum. In this study, we acquired high‐resolution, three‐dimensional images of the whole brain every 2 weeks, using a T1‐weighted magnetization‐prepared rapid acquisition gradient echo imaging sequence, optimized for myelin contrast, in order to assess myelination across the entire rat brain over a period of 8 weeks on a 1% cuprizone diet. We observed a consistent pattern of demyelination, beginning in the cerebellum by 4 weeks and involving more rostral regions of the brain by 8 weeks on the cuprizone diet, with validation using Luxol fast blue histology. This imaging technique permits the effects of cuprizone‐induced demyelination to be followed longitudinally in a single animal, over the entire brain. In turn, this may facilitate the establishment of the cuprizone model of demyelination in the rat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".