Sex differences in the effects of maternal voluntary oral <i>Cannabis</i> consumption on the metabolic outcomes of high‐fat diet in adult offspring
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Given the recent rise in Cannabis legalisation, accessibility to Cannabis and consumption have increased during pregnancy. Therefore, there could be unintended developmental consequences. The endocannabinoid system plays a key role in fetal development and later-life energy homeostasis. We explored the long-term effects of maternal voluntary Cannabis consumption on the metabolic outcomes of a high-fat diet (HFD) in adult offspring. EXPERIMENTAL APPROACH: Δ9-tetrahydrocannabinol (THC) from gestational day 1.5 until postnatal day (PD) 10. Pregnancy and pup outcomes and active maternal behaviour were recorded. Male and female offspring (PD49) were placed on a 12-week HFD or control diet; their weight gain, adiposity, glucose tolerance, insulin sensitivity, circulating hormones and pancreatic structure were measured. KEY RESULTS: Perinatal Cannabis exposure (PCE) pup weight was initially reduced but restored by PD16. PCE did not influence weight gain or metabolic characteristics of male mice on a HFD. PCE female but not male offspring on a HFD had reduced accumulation of adipose tissue and lower insulin, leptin and resistin independent of body weight. PCE females on control diet also showed altered basal insulin sensitivity likely because of increased glucagon levels in parallel with reduced islets of Langerhans size and enhanced gene expression of cannabinoid 2 receptors in white adipose tissue. CONCLUSION AND IMPLICATIONS: PCE adversely affected glycaemic control in female offspring on control diet while it mitigated HFD-induced metabolic dysfunction. This raises concerns about the long-term effects of PCE on the metabolic health of 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".