In utero exposure to venlafaxine, a serotonin–norepinephrine reuptake inhibitor, increases cardiac anomalies and alters placental and heart serotonin signaling in the rat
Bibliographic record
Abstract
Background Human studies are inconsistent with respect to an association between treatment with selective serotonin and serotonin–norepinephrine reuptake inhibitors (SSRI/SNRIs) and an increase in the incidence of congenital heart defects. Here we tested the hypothesis that in utero exposure to venlafaxine, a highly prescribed SNRI, increases the incidence of fetal heart defects and alters placental and fetal heart serotonin signaling in the rat. Methods Timed‐pregnant Sprague Dawley rats were gavaged daily with venlafaxine hydrochloride (0, 3, 10, 30, or 100 mg/kg/day) from gestation day 8 to 20. On gestation day 21, fetuses were examined for external and internal malformations; placentas and fetal hearts were collected for the analysis of gene expression. Results Venlafaxine had no effect on the number of live fetuses, fetal body weights, or external morphology in the absence of maternal toxicity. However, venlafaxine significantly increased the placental index (fetal body/placental weight ratio) and the incidence of fetal cardiac anomalies. Venlafaxine exposure decreased placental expression of the serotonin transporter (SERT/Slc6a4) at the transcript and protein levels. In contrast, venlafaxine increased SERT expression in the hearts of female, but not male, fetuses. Expression of the serotonin 2B receptor (5‐HT2B/Htr2b) and of fibroblast growth factor 8 was induced in fetal hearts. Conclusion In utero venlafaxine exposure altered the placental index and induced fetal cardiac anomalies in rats. We propose that the increased incidence of cardiac anomalies is mediated through alterations in serotonin signaling in the placenta and fetal heart. Birth Defects Research (Part A), 2016. © 2016 Wiley Periodicals, Inc. Birth Defects Research (Part A) 106:1044–1055, 2016. © 2016 Wiley Periodicals, Inc.
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) | 0.002 | 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".