A multifunctional, multi-pathway intracellular localization signal in Huntingtin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nuclear accumulation of the polyglutamine-expanded mutant huntingtin protein remains one of the most predictive cell biological phenotypes of Huntington's disease (HD) progression in patient brain samples and mouse models of the disease. Yet, the relationship between huntingtin nuclear import, neuronal dysfunction and toxicity is not fully understood and it remains unclear whether nuclear accumulation is required for disease onset. Here, we discuss several studies that have guided current understanding of this subject, and highlight our recent data detailing the discovery of a karyopherin β1/β2-type nuclear localization signal near the N-terminus of huntingtin. This signal can function through multiple pathways of nuclear import, and may also be responsible for huntingtin import into the primary cilium. This work represents a significant step forward in our knowledge of the regulatory pathways that govern huntingtin nuclear accumulation and will allow direct examination of both normal and mutant huntingtin nuclear function. This work also suggests a re-examination of the cell biology of any protein that contains a multi-pathway nuclear localization signal. The possibility of targeting huntingtin nuclear import therapeutically and the potential impacts of such a strategy for the treatment of HD are also discussed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it