Nicotine Directly Induces Endoplasmic Reticulum Stress Response in Rat Placental Trophoblast Giant Cells
Bibliographic record
Abstract
Nicotine exposure during pregnancy leads to placental insufficiency impairing both fetal and neonatal development. Previous studies from our laboratory have demonstrated that in rats, nicotine augmented endoplasmic reticulum (ER) stress in association with placental insufficiency; however, the underlying mechanisms remain elusive. Therefore, we sought to investigate the possible direct effect of nicotine on ER stress in Rcho-1 rat placental trophoblast giant (TG) cells during differentiation. Protein and/or mRNA expression of markers involved in ER stress (eg, phosphorylated PERK, eIF2α, CHOP, and BiP/GRP78) and TG cell differentiation and function (eg, Pl-1, placental growth factor [Pgf], Hsd11b1, and Hsd11b2) were quantified via Western blot or real-time polymerase chain reaction. Nicotine treatment led to dose-dependent increases in the phosphorylation of PERK[Thr981] and eIF2α[Ser51], whereas pretreatment with a nicotinic acetylcholine receptor (nAChR) antagonist (mecamylamine hydrochloride) blocked the induction of PERK phosphorylation, verifying the direct involvement of nicotine and nAChR binding. We next investigated select target genes known to play essential roles in placental TG cell differentiation and function (Pl-1, Pgf, Hsd11b1, and Hsd11b2), and found that nicotine significantly augmented the mRNA levels of Hsd11b1 in a dose-dependent manner. Furthermore, using tauroursodeoxycholic acid, a safe bile acid known to improve protein chaperoning and folding, we were able to prevent nicotine-induced increases in both PERK phosphorylation and Hsd11b1 mRNA levels, revealing a potential novel therapeutic approach to reverse the deleterious effects of nicotine exposure in pregnancy. Collectively, these results implicate that nicotine, acting through its receptor, can directly augment ER stress and impair placental function.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".