Evaluation of Hippocampal Neurogenesis in YAC128 Huntington’s Disease Transgenic Mice
Bibliographic record
Abstract
Given the capacity of the adult brain to generate new neurons (a process called neurogenesis), adult neuronal stem cells have been proposed as an endogenous source of healthy cells for the treatment of certain neurodegenerative diseases. However, it is not completely understood to what extent this process is altered in neurodegenerative conditions such as Huntington's Disease (HD). An increase in neurogenesis in the subventricular zone (SVZ) of HD patients has been previously reported. On the other hand, we and others found a dramatic decrease in neurogenesis in the dentate gyrus (DG) of the hippocampus of the most studied HD transgenic mouse models, the R6/2 and R6/1 lines. We are now examining neurogenesis in a transgenic model that expresses the full-length huntingtin gene with 128 CAG repeats, the YAC128 mice. We are analysing how disease progression in the YAC128 model affects each stage of the neurogenic process (i.e., proliferation, survival, migration, and differentiation) in the two neurogenic regions (SVZ and DG). Proliferation will be evaluated in end-stage, symptomatic, early-symptomatic and pre-symptomatic YAC128 mice by immunohistochemistry for a variety of exogenous and endogenous cell cycle markers. Cell survival, migration and differentiation will be assessed by immuno-labelling of immature and mature neurons. Since hippocampal neurogenesis is thought to be involved in cognitive processes, a reduction in it might contribute to the cognitive deficits and/or depression in HD. Furthermore, these results will ascertain how well the HD brain might sustain neuronal transplant therapies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".