BDNF Overexpression in the Forebrain Rescues Huntington's Disease Phenotypes in YAC128 Mice
Bibliographic record
Abstract
Huntington's disease (HD) is caused by an expansion of the polyglutamine tract at the N terminus of huntingtin. This mutation reduces levels of BDNF in the striatum, likely by inhibiting cortical Bdnf gene expression and anterograde transport of BDNF from the cerebral cortex to the striatum. Substantial evidence suggests that this reduction of striatal BDNF plays a crucial role in HD pathogenesis. Here we report that overexpression of BDNF in the forebrain rescues many disease phenotypes in YAC128 mice that express a full-length human huntingtin mutant with a 128-glutamine tract. The Bdnf transgene, under the control of the promoter for α subunit of Ca(2+)/calmodulin-dependent protein kinase II, greatly increased BDNF levels in the cerebral cortex and striatum. BDNF overexpression in YAC128 mice prevented loss and atrophy of striatal neurons and motor dysfunction, normalized expression of the striatal dopamine receptor D2 and enkephalin, and improved procedural learning. Furthermore, quantitative analyses of Golgi-impregnated neurons revealed a decreased spine density and abnormal spine morphology in striatal neurons of YAC128 mice, which was also reversed by increasing BDNF levels in the striatum. These results demonstrate that reduced striatal BDNF plays a crucial role in the HD pathogenesis and suggest that attempts to restore striatal BDNF level may have therapeutic effects to the disease.
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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) | 0.001 | 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 | 0.001 |
| 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 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".