A Longitudinal Study of Sex Differences in a <scp>TDP</scp> ‐43 Mouse Model Reveals <scp>STI1</scp> Regulation of <scp>TDP</scp> ‐43 Proteinopathy and Motor Deficits
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a disease influenced by a complex interplay of age, genetics, and sex. Most ALS cases are sporadic, and individuals with this disease show elevated levels of TDP-43 in their central nervous system and aggregated cytoplasmic inclusions containing TDP-43 in neurons. Misfolded and aggregated proteins like TDP-43 can be refolded or marked for degradation by molecular chaperones and their co-chaperone partners. In this study, we use a mouse model of ALS that mildly overexpresses human wild-type TDP-43 in neurons to explore how aging affects the onset of motor abnormalities and proteinopathy in male and female mice. We found that the age-dependent onset of motor symptoms is more pronounced in male mice, despite both sexes sharing similar TDP-43 pathology. Further, we found that reducing the activity of STI1, an Hsp90 co-chaperone, was associated with reduced mislocalized TDP-43 in the brain and spinal cord and partially rescued some motor deficits. By contrast, overexpressing STI1 seemed to be deleterious, exacerbating the levels of C-terminal TDP-43 fragments in the cytoplasm, worsening motor abnormalities and reducing lifespan. Our findings reveal that sex is a key biological factor in an ALS mouse model of TDP-43 overexpression and provide novel insights on the role of STI1 and proteostasis in mediating TDP-43 pathology.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".