Delta 9-Tetrahydrocannabinol Signaling Through Cannabinoid Receptor 1 Alters Trophoblast Differentiation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cannabis use during pregnancy is increasing. In rodent models of delta-9 tetrahydrocannabinol (Δ9-THC) exposure during pregnancy, placental pathology, including compromised labyrinth development, is reported. Cannabinoid receptor 1 (CB1/ Cnr1 ) is the primary mediator of Δ9-THC action, with its expression reportedly limited to the placental junctional zone in the rodent. Given a Δ9-THC-induced labyrinth-specific pathology, we predicted more diverse expression. This study aimed to elucidate the spatiotemporal expression of CB1/ Cnr1 in the rodent and assess whether it mediates Δ9-THC-induced alterations in trophoblast differentiation. Results revealed CB1 expression in all maternal blood-facing trophoblast cells. Furthermore, Δ9-THC exposure (at levels matching those reported in maternal serum) had a more significant effect on the expression of markers associated with differentiating trophoblast cells than on proliferating trophoblast stem (TS) cells. Δ9-THC impacted mouse (m) TS cell differentiation in a CB1-dependent manner, reducing the expression of syncytiotrophoblast (SynT) markers, driving differentiation along the junctional zone/trophoblast giant cell pathway. mTS cells without Cnr1/ CB1 (mTS Cnr1 KO ) did not express markers of SynT cells or the differentiated junctional zone cell types. However, at a higher than physiologically relevant concentration, Δ9-THC (15 μM) induced Gcm1 (SynT) expression in mTS Cnr1 KO cells. This study reveals a mechanism by which Δ9-THC may impact placental growth.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it