Spatial and Temporal Requirements for huntingtin (<i>Htt</i>) in Neuronal Migration and Survival during Brain Development
Bibliographic record
Abstract
Huntington's disease (HD), caused by an expanded triplet repeat in the huntingtin (Htt) gene, results in extensive neuropathology, but study of the Htt gene in CNS development through gene knockout is problematic as the knockout leads to embryonic lethality in mice. Here, we report that the knockdown of Htt expression in neuroepithelial cells of neocortex results in disturbed cell migration, reduced proliferation, and increased cell death that is relatively specific to early neural development. In the cerebellum, however, Htt knockdown results in cell death but not perturbed migration. The cell death phenotype in cortex can be partially reversed with co-knockdown of Casp9, indicating that mitochondria-mediated cell apoptotic processes are involved in the neuronal death. The timing of knockdown during early development is also an important variable. These results indicate a spatial and temporal requirement for Htt expression in neural development. Although it is uncertain whether the loss of wild-type huntingtin function contributes to pathogenesis in Huntington's disease, these results clearly contraindicate the use of nonspecific knockdown of Htt as a therapeutic measure in HD, particularly in utero.
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) | 0.000 | 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 | 0.000 | 0.000 |
| 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".