Abnormal expression of cortical cell cycle regulators underlying anxiety and depressive-like behavior in mice exposed to chronic stress
Bibliographic record
Abstract
Background The cell cycle is a critical mechanism for proper cellular growth, development and viability. The p16INK4a and p21Waf1/Cip1 are important regulators of the cell cycle progression in response to internal and external stimuli (e.g., stress). Accumulating evidence indicates that the prefrontal cortex (PFC) is particularly vulnerable to stress, where stress induces, among others, molecular and morphological alterations, reflecting behavioral changes. Here, we investigated if the p16INK4a and p21Waf1/Cip1 expression are associated with behavioral outcomes. Methods Prefrontal cortex mRNA and protein levels of p16INK4A and p21Waf1/Cip1 of mice (six independent groups of C57BL/6J, eight mice/group, 50% female) exposed from 0 to 35 days of chronic restraint stress (CRS) were quantified by qPCR and Western Blot, respectively. Correlation analyses were used to investigate the associations between cyclin-dependent kinase inhibitors (CKIs) expression and anxiety- and depression-like behaviors. Results Our results showed that the PFC activated the cell cycle regulation pathways mediated by both CKIs p16INK4A and p21Waf1/Cip1 in mice exposed to CRS, with overall decreased mRNA expression and increased protein expression. Moreover, correlation analysis revealed that mRNA and protein levels are statistically significant correlated with anxiety and depressive-like behavior showing a greater effect in males than females. Conclusion Our present study extends the existing literature providing evidence that PFC cells respond to chronic stress exposure by overexpressing CKIs. Furthermore, our findings indicated that abnormal expression of p16INK4A and p21Waf1/Cip1 may significantly contribute to non-adaptive behavioral responses.
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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 | 0.001 | 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".