A Further Analysis and Commentary on: Profiling Changes in Cortical Astroglial Cells Following Chronic Stress
Bibliographic record
Abstract
The neuroplasticity hypothesis of depression proposes that major depressive disorders are related to decreased hippocampal and cortical neural plasticity, which is reversed by antidepressant treatment. Astroglial cells have emerged as key mediators of neural plasticity and are involved in the cause and treatment of depression and anxiety-like behaviors. One of the ways that astroglia modulate neuroplasticity is through the formation and maintenance of perineuronal nets (PNNs). Perineuronal nets are important extracellular matrix components that respond to stress and are implicated in anxiety-like behaviors. Normally, astroglial cells continuously turnover PNNs by degrading and donating PNN proteins; however, chronic stress slows PNN protein degradation and increases cortical PNN expression overall. In this report, we used weighted gene co-expression network analysis and eigengene analysis to further delineate the pathways and key regulators involved in the astroglial-PNN relationship following chronic stress. Our analyses indicate that chronic variable stress induces the expression of PNNs through inhibition of trophic pathways and key transcription factors in astroglial cells. These data further support the integral role of astroglial cells in the neuroplasticity hypothesis of depression through their modulation of anxiety-like behaviors and PNNs.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".