The endocannabinoidome in human placenta: Possible contribution to the pathogenesis of preeclampsia
Bibliographic record
Abstract
Preeclampsia (PE) was first reported thousands of years ago, yet there is still a shortage of biomarkers to determine the severity and type of PE. The importance of the expanded endocannabinoid system, or endocannabinoidome (eCBome), has emerged recently in placental physiology and pathology, though the potential alterations of the eCBome in PE have not been fully explored. Analysis by qRT-PCR using placental samples of normotensive and PE women demonstrate for the first time the presence of ABHD4, GDE1, and DAGLβ in both normotensive and PE placental tissues. Interestingly, NAPE-PLD, FAAH-1, DAGLα, MAGL, and ABHD6 mRNA levels were increased in the placental tissues of PE patients. Quantification in plasma and placental tissues showed a decrease for anandamide (AEA), N-oleoylethanolamine (OEA), and N-docosahexaenoylethanolamine (DHEA) in the placenta, accompanied only by a decrease in plasma levels of AEA. In addition, a strong negative correlation was obtained between OEA and the biomarker of PE, soluble fms-like tyrosine kinase-1. Given the inflammatory nature of PE and the anti-inflammatory role of OEA and DHEA, the decrease in the local levels of these mediators may underlie the inflammatory component of this pathology. Additionally, lower AEA levels in both placenta and plasma may contribute to the atypical alterations of the spiral arteries in PE due to the vasorelaxation effects of AEA. These results add new information to the role of the eCBome members in placental development, while also pointing to a potential role as biomarkers of PE.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".