Expression analysis of novel striatal-enriched genes in Huntington disease
Bibliographic record
Abstract
Selective degeneration of striatal neurons is a pathologic hallmark of Huntington disease (HD). The exact mechanism(s) behind this specific neurodegeneration is still unknown. Expression studies of diseased human post-mortem brain, as well as different mouse models exhibiting striatal degeneration, have demonstrated changes in the expression of many important genes with a large proportion of changes being observed in the striatal-enriched genes. These investigations have raised questions about how enrichment of particular transcripts in the striatum can lead to its selective vulnerability to neurodegeneration. Monitoring the expression changes of striatal-enriched genes during the course of the disease may be informative about their potential involvement in selective degeneration. In this study, we analyzed a Serial Analysis of Gene Expression (SAGE) database (www.mouseatlas.org) and compared the mouse striatum to 18 other brain regions to generate a novel list of striatal-enriched transcripts. These novel striatal-enriched transcripts were subsequently evaluated for expression changes in the YAC128 mouse model of HD, and differentially expressed transcripts were further examined in human post-mortem caudate samples. We identified transcripts with altered expression in YAC128 mice, which also showed consistent expression changes in human post-mortem tissue. The identification of novel striatal-enriched genes with altered expression in HD offers new avenues of study, leading towards a better understanding of specific pathways involved in the selective degeneration of striatal neurons in HD.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".