Peptidylarginine deiminase 2 (PAD2) overexpression in transgenic mice leads to myelin loss in the central nervous system
Bibliographic record
Abstract
Demyelination in the central nervous system is the hallmark feature in multiple sclerosis (MS). The mechanism resulting in destabilization of myelin is a complex multi-faceted process, part of which involves deimination of myelin basic protein (MBP). Deimination, the conversion of protein-bound arginine to citrulline, is mediated by the peptidylarginine deiminase (PAD) family of enzymes, of which the PAD2 and PAD4 isoforms are present in myelin. To test the hypothesis that PAD contributes to destabilization of myelin in MS, we developed a transgenic mouse line (PD2) containing multiple copies of the cDNA encoding PAD2, under the control of the MBP promoter. Using previously established criteria, clinical signs were more severe in PD2 mice than in their normal littermates. The increase in PAD2 expression and activity in white matter was demonstrated by immunohistochemistry, reverse transcriptase-PCR, enzyme activity assays, and increased deimination of MBP. Light and electron microscopy revealed more severe focal demyelination and thinner myelin in the PD2 homozygous mice compared with heterozygous PD2 mice. Quantitation of the disease-associated molecules GFAP and CD68, as measured by immunoslot blots, were indicative of astrocytosis and macrophage activation. Concurrently, elevated levels of the pro-inflammatory cytokine TNF-alpha and nuclear histone deimination support initiation of demyelination by increased PAD activity. These data support the hypothesis that elevated PAD levels in white matter represents an early change that precedes demyelination.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".