Cannabinoids and the placenta: Receptors, signaling and outcomes
Bibliographic record
Abstract
Cannabis use during pregnancy is increasing. The improvement of pregnancy-related symptoms including morning sickness and management of mood and stress are among the most reported reasons for its use. Δ9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD) are the most abundant cannabinoids found within the cannabis flower. The concentration of these components has drastically increased in the past 20 years. Additionally, many edibles contain only one cannabinoid and are marketed to achieve a specific goal, meaning there are an increasing number of pregnancies that are exposed to isolated cannabinoids. Both Δ9-THC and CBD cross the placenta and can impact the fetus directly, but the receptors through which cannabinoids act are also expressed throughout the placenta, suggesting that the effects of in-utero cannabinoid exposure may include indirect effects from the placenta. In-utero cannabis research focuses on short and long-term fetal health and development; however, these studies include little to no placenta analysis. Prenatal cannabinoid exposure is linked to small for gestational age and fetal growth-restricted babies. Compromised placental development is also associated with fetal growth restriction and the few studies (clinical and animal models) that included placental analysis, identify changes in placental vasculature and function in these cannabinoid-exposed pregnancies. In vitro studies further support cannabinoid impact on cell function in the different populations that comprise the placenta. In this article, we aim to summarize how phytocannabinoids can impact placental development and function. Specifically, the cannabinoids and their actions at the different receptors are described, with receptor localization throughout the human and murine placenta discussed. Findings from studies that included placental analysis and how cannabinoid signaling may modulate critical developmental processing including cell proliferation, angiogenesis and migration are described. Considering the current research, prenatal cannabinoid exposure may significantly impact placental development, and, as such, identifying windows of placental vulnerability for each cannabinoid will be critical to elucidate the etiology of fetal outcome studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".