NF‐κB signaling inhibits ubiquitin carboxyl‐terminal hydrolase L1 gene expression
Bibliographic record
Abstract
Ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1) is a deubiquitinating enzyme that plays a regulatory role in targeting proteins for proteasomal degradation. UCH-L1 is highly expressed in neurons and has been demonstrated to promote cell viability and maintain neuronal integrity. Reduced UCH-L1 levels have been observed in various neurodegenerative diseases, and expression of UCH-L1 can rescue synaptic dysfunction and memory deficits in Alzheimer's Disease model mice. However, the mechanisms regulating UCH-L1 expression have not been determined. In this study, we cloned a 1782 bp of the 5' flanking region of the human UCH-L1 gene and identified a 43 bp fragment containing the transcription start site as the minimal region necessary for promoter activity. Sequence analysis revealed several putative regulatory elements including NF-κB, NFAT, CREB, NRSF, YY1, AP1, and STAT in the UCH-L1 promoter. A functional NF-κB response element was identified in the UCH-L1 promoter region. Expression of NF-κB suppressed UCH-L1 gene transcription. In the RelA knockout system where NF-κB activity is ablated, UCH-L1 expression was significantly increased. Furthermore, activation of NF-κB signaling by the inflammatory stimulator lipopolysaccharide and TNFα resulted in a decrease of UCH-L1 gene expression by inhibiting its transcription. As NF-κB is an important signaling module in inflammatory response, our study suggests a possibility that inflammation might compromise neuronal functions via the interaction of NF-κB and UCH-L1. A better understanding of the NF-κB-regulated UCH-L1 transcription will provide insights to the role of inflammatory responses in Alzheimer's disease and Parkinson's 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 | 0.001 |
| 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".