Periadolescent oxytocin treatment increased neurogenesis in a sex-dependent manner and ameliorated maternal corticosterone effects in adult offspring
Bibliographic record
Abstract
Perinatal depression (PND) affects 15% of mothers and selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for PND. Perinatal SSRI exposure have been controversially linked to increased risk of autism spectrum disorder (ASD) in children. Oxytocin (OT) is under investigation as a treatment for ASD, but OT is a large neuropeptide that has difficulty crossing the blood-brain barrier (BBB). TriozanTM is a nanoformulation that can facilitate OT across the BBB. Here, we hypothesize that using a model of de novo postpartum depression, maternal treatments will alter adult offspring social behaviour, neuroinflammation, and neurogenesis in a sex-specific manner and that OT may reverse the effects of maternal treatments. Corticosterone (CORT; 40mg/kg, s.c) was given to dams to model de novo postpartum depression, with or without the SSRI, fluoxetine (FLX; 10mg/kg, s.c.) for 21 days. Offspring were then treated with either OT (0.5 mg/kg), OT+TriozanTM (OT+T; 0.25mg/mL; adjusted to 0.5mg/kg), or vehicle for 10 days prior to adolescence (PD25-34). OT treatment increased neurogenesis only in adult males, regardless of maternal treatment and increased social investigation in both sexes although this depended on maternal CORT. Maternal CORT shifted the IL-6:IL:10 ratio towards proinflammation and increased neurogenesis in both sexes, whereas OT, independent of formulation, reversed these effects. These findings underscore that preadolescent exposure to OT can reverse some of the long-lasting effects of postpartum maternal CORT in adult offspring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".