Viral Infections Exacerbate FUS-ALS Phenotypes in iPSC-Derived Spinal Neurons in a Virus Species-Specific Manner
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) arises from an interplay of genetic mutations and environmental factors. ssRNA viruses are possible ALS risk factors, but testing their interaction with mutations such as in FUS, which encodes an RNA-binding protein, has been difficult due to the lack of a human disease model. Here, we use isogenic induced pluripotent stem cell (iPSC)-derived spinal neurons to investigate the interaction between ssRNA viruses and mutant FUS. We find that rabies virus (RABV) spreads ALS phenotypes, including the formation of stress granules with aberrant composition due to increased levels of FUS protein, as well as neurodegeneration and reduced restriction activity by FUS mutations. Consistent with this, iPSC-derived spinal neurons harboring mutant FUS are more sensitive to HIV-1 and Zika viruses. We demonstrate that RABV and HIV-1 exacerbate cytoplasmic mislocalization of FUS. Our results demonstrate that viral infections worsen ALS pathology in spinal neurons with genetic risk factors, suggesting a novel role for viruses in modulating patient phenotypes.
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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 | 0.001 | 0.001 |
| 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".