Transcriptional profiling of the cortico-accumbal pathway reveals sex-specific alterations underlying stress susceptibility
Bibliographic record
Abstract
Abstract Anxiety and depressive disorders, including major depressive disorder (MDD), affect millions of people every year, imposing significant socio-economic burdens. In this scenario, current treatments for MDD show limited efficacy, highlighting the need to better understand its molecular mechanisms. The medial prefrontal cortex (mPFC) has been identified as a critical brain region in MDD pathology, displaying altered activity and morphology. This study targets the mPFC-to-nucleus accumbens (NAc) pathway, which is implicated in the regulation of emotional behavior. We used a pathway-specific approach to uncover transcriptional profiles in mPFC neurons projecting to the NAc in stressed male and female mice. Using the RiboTag technique and RNA sequencing, we identified sex-specific gene expression changes, revealing potential roles in stress susceptibility. Differential expression and weighted gene co-expression network analyses revealed distinct transcriptional responses to chronic stress in males and females. Key findings include the identification of the X-linked lymphocyte-regulated 4B ( Xlr4b ) gene, within a highly relevant gene module, as a stress susceptibility driver in males. By experimentally overexpressing the Xlr4b gene, we characterized its crucial role in regulating neuronal firing and influencing arborization patterns to promote anxiety-like behavior in a sex-specific fashion. These findings suggest that chronic stress induces unique and shared transcriptional alterations in mPFC neurons projecting to the NAc. Some of these alterations change the morphological and functional properties of neuronal pathways ultimately contributing to the differential manifestation of anxiety-like and depressive-like behaviors in male and female mice.
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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 | 0.000 |
| 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".