Regulation of Social Stress and Neural Degeneration by Activity-Regulated Genes and Epigenetic Mechanisms in Dopaminergic Neurons
Bibliographic record
Abstract
Transcriptional and epigenetic regulation of both dopaminergic neurons and their accompanying glial cells is of great interest in the search for therapies for neurodegenerative disorders such as Parkinson's disease (PD). In this review, we collate transcriptional and epigenetic changes identified in adult Drosophila melanogaster dopaminergic neurons in response to either prolonged social deprivation or social enrichment, and compare them with changes identified in mammalian dopaminergic neurons during normal development, stress, injury, and neurodegeneration. Surprisingly, a small set of activity-regulated genes (ARG) encoding transcription factors, and a specific pattern of epigenetic marks on gene promoters, are conserved in dopaminergic neurons over the long evolutionary period between mammals and insects. In addition to their classical function as immediate early genes to mark acute neuronal activity, these ARG transcription factors are repurposed in both insects and mammals to respond to chronic perturbations such as social enrichment, social stress, nerve injury, and neurodegeneration. We suggest that these ARG transcription factors and epigenetic marks may represent important targets for future therapeutic intervention strategies in various neurodegenerative disorders including PD.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".