Wild‐type and mutant SOD1 localizes to RNA‐rich structures in cells and mice but does not bind RNA
Bibliographic record
Abstract
Many of the genes whose mutation causes Amyotrophic Lateral Sclerosis (ALS) are RNA-binding proteins which localize to stress granules, while others impact the assembly, stability, and elimination of stress granules. This has led to the hypothesis that alterations in the dynamics of stress granules and RNA biology cause ALS. Genetic mutations in Superoxide Dismutase 1 (SOD1) also cause ALS. Evidence demonstrates that SOD1 harboring ALS-linked mutations is recruited to stress granules, induces changes in alternative splicing, and could be an RNA-binding protein. Whether SOD1 inclusions contain RNA in disease models and whether SOD1 directly binds RNA remains uncertain. We applied methods including cross-linking immunoprecipitation and in vitro gel shift assays to detect binding of SOD1 to RNA in vitro, in cells with and without stress granules, and in mice expressing human SOD1 G93A. We find that SOD1 localizes to RNA-rich structures including stress granules, and SOD1 inclusions in mice contain mRNA. However, we find no evidence that SOD1 directly binds RNA. This suggests that SOD1 may impact stress granules, alternative splicing and RNA biology without binding directly to RNA.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".