Nfe2l1 dysfunction alters Parkinson’s disease-related gene expression and impairs neuronal differentiation under ubiquitin stress in neuronal differentiated P19 Cells
Bibliographic record
Abstract
Proteostasis is essential for neuronal health, and its disruption is implicated in neurodegenerative diseases such as Parkinson's disease (PD). Nfe2l1, a key regulator of proteostasis and ubiquitination, plays a significant role in neuronal health, yet its molecular functions in neuronal cells remain unclear. Our study investigates the role of Nfe2l1 in RA-induced neuronal differentiation of P19 cells under proteasome inhibition. This condition significantly increased Nfe2l1 expression at both protein and RNA levels in wild-type and differentiated cells. In differentiated cells under proteasome inhibition, RNA sequencing revealed an enrichment of neurodegenerative pathways, particularly those associated with PD. Proteasome inhibition led to the upregulation of several PD-related genes, including Atf6, Camk2d, and Sod1. However, Nfe2l1 knockdown in differentiated cells significantly reduced the expression of these genes, highlighting the role of Nfe2l1 in the regulation of PD-related pathways. Knockdown of Nfe2l1 also decreased Neat1, a long non-coding RNA associated with PD pathology, and downregulated the neuronal marker Map2, indicating impaired neuronal differentiation. Furthermore, Nfe2l1 knockdown increased ubiquitination under proteasome inhibition, emphasizing its role in protein degradation and neuronal homeostasis under stress. These findings highlight Nfe2l1 as a critical regulator in neuronal cells and reveal its potential role in maintaining proteostasis and involvement in neurodegenerative disease mechanisms, such as PD.
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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".