Long-Term Impact of Early-Life Stress on Serotonin Connectivity
Bibliographic record
Abstract
BACKGROUND: Chronic childhood stress is a prominent risk factor for developing affective disorders, yet mechanisms underlying this association remain unclear. Maintenance of optimal serotonin (5-HT) levels during early postnatal development is critical for the maturation of brain circuits. Understanding the long-lasting effects of early-life stress (ELS) on serotonin-modulated brain connectivity is crucial to develop treatments for affective disorders arising from childhood stress. METHODS: Using a mouse model of chronic developmental stress, we determined the long-lasting consequences of ELS on 5-HT circuits and behavior in females and males. Using FosTRAP mice, we cross-correlated regional c-Fos density to determine brain-wide functional connectivity of the raphe nucleus. We next performed in vivo fiber photometry to establish ELS-induced deficits in 5-HT dynamics and optogenetics to stimulate 5-HT release to improve behavior. RESULTS: Adult female and male mice exposed to ELS showed heightened anxiety-like behavior. ELS further enhanced susceptibility to acute stress by disrupting the brain-wide functional connectivity of the raphe nucleus and the activity of 5-HT neuron population, in conjunction with increased orbitofrontal cortex (OFC) activity and disrupted 5-HT release in medial OFC. Optogenetic stimulation of 5-HT terminals in the medial OFC elicited an anxiolytic effect in ELS mice in a sex-dependent manner. CONCLUSIONS: These findings suggest a significant disruption in 5-HT-modulated brain connectivity in response to ELS, with implications for sex-dependent vulnerability. The anxiolytic effect of the raphe-medial OFC circuit stimulation has potential implications for developing targeted stimulation-based treatments for affective disorders that arise from early life adversities.
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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".