Mutant huntingtin induces neuronal apoptosis via derepressing the non-canonical poly(A) polymerase PAPD5
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs that play crucial roles in post-transcriptional gene regulation. Poly(A) RNA polymerase D5 (PAPD5) catalyzes the addition of adenosine to the 3' end of miRNAs. In this study, we demonstrate that the Yin Yang 1 protein, a transcriptional repressor of PAPD5, is recruited to both RNA foci and protein aggregates, resulting in an upregulation of PAPD5 expression in Huntington's disease (HD). Additionally, we identify a subset of PAPD5-regulated miRNAs with increased adenylation and reduced expression in our disease model. We focus on miR-7-5p and find that its reduction causes the activation of the TAB2-mediated TAK1-MKK4-JNK pro-apoptotic pathway. This pathway is also activated in induced pluripotent stem cell-derived striatal neurons and post-mortem striatal tissues isolated from HD patients. In addition, we discover that a small molecule PAPD5 inhibitor, BCH001, can mitigate cell death and neurodegeneration in our disease models. This study highlights the importance of PAPD5-mediated miRNA dysfunction in HD pathogenesis and suggests a potential therapeutic direction for 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) | 0.000 | 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".