Genetic polymorphisms in placental transporters: implications for fetal drug exposure to oral antidiabetic agents
Bibliographic record
Abstract
INTRODUCTION: The prevalence of diabetes among women of childbearing age is increasing. This will inevitably increase the number of pregnancies complicated by diabetes. The management of diabetes mellitus often necessitates the use of oral antidiabetic drugs including biguanides, sulfonylureas, metiglinide analogs and thiazolidinediones. However, a significant concern with the use of these agents in pregnancy is the potential for developmental toxicity. Various antidiabetic drugs have been identified as substrates for transporters present in the syncytiotrophoblast. Therefore, the extent of transfer and fetal exposure to oral antidiabetic drugs used in pregnancy may be altered by polymorphisms in genes encoding these transport proteins. AREAS COVERED: This review covers current research examining genetic polymorphisms in transporters expressed in the syncytiotrophoblast and evidence supporting the involvement of these transporters in the transport of oral antidiabetic agents. The aim is to provide insight into how the transfer of antidiabetic drugs across the placental trophoblast may be altered by polymorphisms in drug transporters. EXPERT OPINION: There is a paucity of studies examining the influence of polymorphisms on transporter activity in the placenta and how the transfer of oral antidiabetics may be altered. Further research employing in vivo models is required to allow for the prediction of the potential consequences of polymorphisms on placental transporter expression and function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".