Time course and nature of brain atrophy in the MRL mouse model of central nervous system lupus
Bibliographic record
Abstract
OBJECTIVE: Similar to patients with systemic lupus erythematosus, autoimmune MRL/lpr mice spontaneously develop behavioral deficits and pathologic changes in the brain. Given that the disease-associated brain atrophy in this model is not well understood, the present study was undertaken to determine the time course of morphometric changes in major brain structures of autoimmune MRL/lpr mice. METHODS: Computerized planimetry and high-resolution magnetic resonance imaging (MRI) were used to compare the areas and volumes of brain structures in cohorts of mice that differ in severity of lupus-like disease. RESULTS: A thinner cerebral cortex and smaller cerebellum were observed in the MRL/lpr substrain, even before severe autoimmunity developed. With progression of the disease, the brain area of coronal sections became smaller and the growth of the hippocampus was retarded, which likely contributed to the increase in the ventricle area:brain area ratio. MRI revealed reduced volume across different brain regions, with the structures in the vicinity of the ventricular system particularly affected. The superior colliculus, periaqueductal gray matter, pons, and midbrain were among the regions most affected, whereas the volumes of the parietal-temporal lobe, parts of the cerebellum, and lateral ventricles in autoimmune MRL/lpr mice were comparable with values in congenic controls. CONCLUSION: These results suggest that morphologic alterations in the brains of MRL/lpr mice are a consequence of several factors, including spontaneous development of lupus-like disease. A periventricular pattern of parenchymal damage is consistent with the cerebrospinal fluid neurotoxicity, limbic system pathologic features, and deficits in emotional reactivity previously documented in this model.
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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 | 0.001 |
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".