RNA-binding protein altered expression and mislocalization in multiple sclerosis
Bibliographic record
Abstract
Abstract Objective Nuclear depletion and mislocalization of RNA-binding proteins (RBPs) trans-activation response DNA-binding protein of 43 kDa (TDP-43) and fused in sarcoma (FUS) are thought to contribute to the pathogenesis of a number of disorders, including amyotrophic lateral sclerosis (ALS). We recently found that TDP-43 as well as polypyrimidine tract binding protein (PTB) have decreased expression and mislocalization in oligodendrocytes in demyelinated lesions in an experimental mouse model of multiple sclerosis (MS) caused by Theiler’s murine encephalomyelitis virus infection. Methods The latter finding prompted us to investigate TDP-43, FUS, and PTB in the demyelinated lesions of MS and in in vitro cultured human brain-derived oligodendrocytes. Results We found: i) mislocalized TDP-43 in oligodendrocytes in active lesions in some MS patients; ii) decreased PTB1 expression in oligodendrocytes in mixed active/inactive demyelinating lesions; iii) decreased nuclear expression of PTB2 in neurons in cortical demyelinating lesions; iv) nuclear depletion of TDP-43 in oligodendrocytes under metabolic stress induced by low glucose/low nutrient conditions compared to optimal culture conditions. Conclusion TDP-43 has been found to have a key role in oligodendrocyte function and viability, while PTB is important in neuronal differentiation, suggesting that altered expression and mislocalization of these RBPs in MS lesions may contribute to the pathogenesis of demyelination and neurodegeneration. Our findings also identify nucleocytoplasmic transport as a target for treatment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".