Ermin deficiency leads to compromised myelin, inflammatory milieu, and susceptibility to demyelinating insult
Bibliographic record
Abstract
Ermin is an actin-binding protein found almost exclusively in the central nervous system (CNS) as a component of myelin sheaths. Although Ermin has been predicted to play a role in the formation and stability of myelin sheaths, this has not been directly examined in vivo. Here, we show that Ermin is essential for myelin sheath integrity and normal saltatory conduction. Loss of Ermin in mice caused de-compacted and fragmented myelin sheaths and led to slower conduction along with progressive neurological deficits. RNA sequencing of the corpus callosum, the largest white matter structure in the CNS, pointed to inflammatory activation in aged Ermin-deficient mice, which was corroborated by increased levels of microgliosis and astrogliosis. The inflammatory milieu and myelin abnormalities were further associated with increased susceptibility to immune-mediated demyelination insult in Ermin knockout mice. Supporting a possible role of Ermin deficiency in inflammatory white matter disorders, a rare inactivating mutation in the ERMN gene was identified in multiple sclerosis patients. Our findings demonstrate a critical role for Ermin in maintaining myelin integrity. Given its near-exclusive expression in myelinating oligodendrocytes, Ermin deficiency represents a compelling "inside-out" model of inflammatory dysmyelination and may offer a new paradigm for the development of myelin stability-targeted therapies.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".