Maternal oxytocin administration mitigates nociceptive, social, and epigenetic impairments in adolescent offspring exposed to perinatal trauma
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) alter brain development, leading to vulnerability for chronic pain, mental health disorders, and suicidality. These effects often emerge during adolescence. Importantly, ACEs can occur prenatally, including when exposed to in utero intimate partner violence (IPV) or postnatally as maternal neglect. Maternal social support has demonstrated promise in the mitigation of ACE-related deficits. Oxytocin, which has a role in social-bonding and stress regulation, serves as a suitable surrogate for social support in preclinical studies. Therefore, we aimed to explore the effects of oxytocin on alleviating social deficits, nociception, and epigenetic changes resulting from models that aimed to mimic the stress normally induced following exposure to two ACEs: IPV in utero and maternal neglect. During pregnancy, dams were randomly assigned to experience the model of IPV or a sham insult. Following birth, offspring from the IPV group underwent 10 days of maternal separation. Dams received three days of oxytocin therapy while nursing. In adolescence, half of the offspring underwent a plantar surgery to induce pain. Overall, in adolescence, rats exposed to the ACEs exhibited increased nociceptive sensitivity and aberrant social interactions, particularly among males, further suggesting that ACEs can increase an individual's risk for chronic pain. The ACEs changed gene expression related to social behaviour and neuroplasticity. Maternal oxytocin normalized pain, social, and gene changes, while oxytocin levels in offspring correlated with nociceptive sensitivity. Although ACEs have enduring consequences, the outcomes are modifiable, and oxytocin may be a robust and implementable therapeutic capable of attenuating early adversity.
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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".