Stress granule assembly<i>in vivo</i>is deficient in the CNS of mutant TDP-43 ALS mice
Bibliographic record
Abstract
Responding effectively to external stress is crucial for neurons. Defective stress granule dynamics has been hypothesized as one of the pathways that renders motor neurons in amyotrophic lateral sclerosis (ALS) more prone to early death. Specifically, it is thought that stress granules seed the cytoplasmic TDP-43 inclusions that are observed in the neurons of most ALS patients, as well as ~50% of all frontotemporal dementia (FTD) patients. In this study, we tested this hypothesis in an intact mammalian nervous system. We established an in vivo heat stress paradigm in mice that effectively triggers the eIF2α pathway and the formation of stress granules in the CNS. In non-transgenic mice, we report an age-dependent decline in the formation of heat-induced stress granules, with 18-month-old animals showing a significant impairment. Furthermore, although neuronal stress granules were robustly observed in non-transgenic mice and SOD1G93A mice, they were largely absent in age-matched TDP-43M337V animals. The observed defect in stress granule formation in TDP-43M337V mice correlated with deficits in expression of key protein components typically required for phase separation. Lastly, while TDP-43 was not localized to stress granules, we observed complete nuclear depletion of TDP-43 in a subset of neurons, with the highest proportion being in the TDP-43M337V mice. Overall, our results indicate that mutant TDP-43 expression is associated with defective stress granule assembly and increased TDP-43 nuclear depletion in the mammalian nervous system, which could be relevant to ALS/FTD pathogenesis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".