Caffeine Reduces 11β-Hydroxysteroid Dehydrogenase Type 2 Expression in Human Trophoblast Cells through the Adenosine A2B Receptor
Bibliographic record
Abstract
Maternal caffeine consumption is associated with reduced fetal growth, but the underlying molecular mechanisms are unknown. Since there is evidence that decreased placental 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2) is linked to fetal growth restriction, we hypothesized that caffeine may inhibit fetal growth partly through down regulating placental 11β-HSD2. As a first step in examining this hypothesis, we studied the effects of caffeine on placental 11β-HSD2 activity and expression using our established primary human trophoblast cells as an in vitro model system. Given that maternal serum concentrations of paraxanthine (the primary metabolite of caffeine) were greater in women who gave birth to small-for-gestational age infants than to appropriately grown infants, we also studied the effects of paraxanthine. Our main findings were: (1) both caffeine and paraxanthine decreased placental 11β-HSD2 activity, protein and mRNA in a concentration-dependent manner; (2) this inhibitory effect was mediated by the adenosine A(2B) receptor, since siRNA-mediated knockdown of this receptor prevented caffeine- and paraxanthine-induced inhibition of placental 11β-HSD2; and (3) forskolin (an activator of adenyl cyclase and a known stimulator of 11β-HSD2) abrogated the inhibitory effects of both caffeine and paraxanthine, which provides evidence for a functional link between exposure to caffeine and paraxanthine, decreased intracellular levels of cAMP and reduced placental 11β-HSD2. Taken together, these findings reveal that placental 11β-HSD2 is a novel molecular target through which caffeine may adversely affect fetal growth. They also uncover a previously unappreciated role for the adenosine A(2B) receptor signaling in regulating placental 11β-HSD2, and consequently fetal development.
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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 | 0.000 | 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) | 0.002 | 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".