Cocaine-induced neuron subtype mitochondrial dynamics through Egr3 transcriptional regulation
Bibliographic record
Abstract
Mitochondrial function is required for brain energy homeostasis and neuroadaptation. Recent studies demonstrate that cocaine affects mitochondrial dynamics and morphological characteristics within the nucleus accumbens (NAc). Further, mitochondria are differentially regulated by cocaine in dopamine receptor-1 containing medium spiny neurons (D1-MSNs) vs dopamine receptor-2 (D2)-MSNs. However, there is little understanding into cocaine-induced transcriptional mechanisms and their role in regulating mitochondrial processes. Here, we demonstrate that cocaine enhances binding of the transcription factor, early growth response factor 3 (Egr3), to nuclear genes involved in mitochondrial function and dynamics. Moreover, cocaine exposure regulates mRNA of these mitochondria-associated nuclear genes in both contingent or noncontingent cocaine administration and in both rodent models and human postmortem tissue. Interestingly, several mitochondrial nuclear genes showed distinct profiles of expression in D1-MSNs vs D2-MSNs, with cocaine exposure generally increasing mitochondrial-associated nuclear gene expression in D1-MSNs vs suppression in D2-MSNs. Further, blunting Egr3 expression in D1-MSNs blocks cocaine-enhancement of the mitochondrial-associated transcriptional coactivator, peroxisome proliferator-activated receptor gamma coactivator (PGC1α), and the mitochondrial fission molecule, dynamin related protein 1 (Drp1). Finally, reduction of D1-MSN Egr3 expression attenuates cocaine-induced enhancement of small-sized mitochondria, causally demonstrating that Egr3 regulates mitochondrial morphological adaptations. Collectively, these studies demonstrate cocaine exposure impacts mitochondrial dynamics and morphology by Egr3 transcriptional regulation of mitochondria-related nuclear gene transcripts; indicating roles for these molecular mechanisms in neuronal function and plasticity occurring with cocaine exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".