Huntingtin reduction results in altered nuclear structure and heterochromatic instability
Bibliographic record
Abstract
Huntington's disease (HD), a fatal neurodegenerative disease, arises due to a CAG repeat expansion in the huntingtin (HTT) gene. Non-pathogenic wild type HTT (wtHTT) is essential for neurodevelopment as well as many vital cellular functions within the adult brain; however, the consequences of wtHTT reduction in adulthood and particularly in extrastriatal regions of the brain have not been well characterized. Understanding the implications of wtHTT loss is essential as numerous genetic therapies for HD non-specifically reduce the expression levels of both mutant and wtHTT. The aim of the current study was to characterize the effect of wtHTT reduction from the whole cell to synaptic level in primary hippocampal neurons using conventional and super-resolution imaging methods. Our results identified the nucleus as an organelle that is particularly vulnerable to wtHTT reduction, with hippocampal neurons exhibiting increased nuclear size relative to the soma, DNA decompaction and a progressive loss of heterochromatin, and biphasic changes in nuclear pCREB signaling following siRNA-mediated wtHTT knockdown. Other structural assessments including dendritic complexity, spine density and synaptic morphology appeared to be largely unaffected in our wtHTT-lowered cells. These findings highlight the nucleus as an organelle that may be particularly sensitive to huntingtin-lowering in the mammalian brain.
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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 | 0.000 | 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".