Characterization of GABAergic Marker Expression in the Chronic Unpredictable Stress Model of Depression
Bibliographic record
Abstract
Background Evidence continues to build suggesting that the GABAergic neurotransmitter system is altered in brains of patients with major depressive disorder. However, there is little information available related to the extent of these changes or the potential mechanisms associated with these alterations. As stress is a well-established precipitant to depressive episodes, we sought to explore the impact of chronic stress on GABAergic interneurons. Methods Using western blot analyses and quantitative real-time polymerase chain reaction, we assessed the effects of five-weeks of chronic unpredictable stress exposure on the expression of GABA-synthesizing enzymes (GAD65 and GAD67), calcium-binding proteins (calbindin, parvalbumin, and calretinin), and neuropeptides co-expressed in GABAergic neurons (somatostatin, neuropeptide Y, vasoactive intestinal peptide, and cholecystokinin) in the prefrontal cortex and hippocampus of rats. We also investigated the effects of corticosterone and dexamethasone exposure on these markers in vitro in primary cortical and hippocampal cultures. Results We found that chronic unpredictable stress induced significant reductions of GAD67 protein levels in both the prefrontal cortex and hippocampus of chronic unpredictable stress-exposed rats but did not detect changes in GAD65 protein expression. Similar protein expression changes were found in vitro in cortical neurons. In addition, our results provide clear evidence of reduced markers of interneuron population(s), namely somatostatin and neuropeptide Y, in the prefrontal cortex, suggesting these cell types may be selectively vulnerable to chronic stress. Conclusion Together, this work highlights that chronic stress induces regional and cell type-selective effects on GABAergic interneurons in rats. These findings provide additional supporting evidence that stress-induced GABA neuron dysfunction and cell vulnerability play critical roles in the pathophysiology of stress-related illnesses, including major depressive disorder.
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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) | 0.001 | 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".