Hypoxia regulation of ATP13A2 (PARK9) gene transcription
Bibliographic record
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorders with a variable combination of motor and non-motor symptoms. Mutations in several genes including ATP13A2 (PARK9) are reported to be associated with PD. The underlying mechanism of PD is not well defined, however, both genetic and environmental causes contribute to it. ATP13A2 gene locates in chromosome 1 and contains 29 exons encoding for a protein of 1180 amino acids with 10 transmembrane domains. Abnormal gene expression has been implicated in neurodegenerative disorders. The transcriptional regulation of the ATP13A2 gene is unknown. In this report, we cloned and functionally characterized the human ATP13A2 gene promoter. We showed that the promoter region of the human ATP13A2 gene contains hypoxia response elements which can bind to transcription factor hypoxia-inducible factor 1α (HIF-1α). Hypoxia up-regulated ATP13A2 transcription via HIF-1α in HEK293 and dopaminergic MN9D cells. Our study indicates that hypoxia signaling plays a very important role in the regulation of human ATP13A2 gene expression. Further study is needed to determine the role of hypoxia in the pathogenesis of PD and its interaction with other PD causative genes, which will provide insights to the role of hypoxia and dysregulation of gene expression in Parkinson's disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".