Impact of in-utero antiretroviral drug exposure on expression of membrane-associated transporters in mouse placenta and fetal brain
Bibliographic record
Abstract
OBJECTIVE: Although antiretroviral therapy (ART) during pregnancy is effective in limiting vertical HIV transmission, adverse outcomes persist amongst uninfected children exposed to antiretroviral drugs in utero. Membrane-associated drug transporters, metabolic enzymes, and tight junction proteins play important roles in adult antiretroviral drug disposition and toxicity; however, the fetal expression of these proteins in the context of ART, and their impact on in-utero antiretroviral drug distribution remain poorly understood. This study aimed to characterize the role of these proteins in modulating in-utero antiretroviral drug exposure. METHODS: Pregnant mice were exposed to an ART regimen consisting of lamivudine, abacavir, atazanavir, and ritonavir, at clinically relevant doses. Fetal brain, liver, placenta amniotic fluid, and maternal plasma were collected on gestational day 18.5 and concentration of antiretroviral drugs in fetal tissues was measured by LC/MS/MS, whereas transporter expression was assessed by qPCR. RESULTS: Abacavir and lamivudine were detected in fetal brain and amniotic fluid, whereas atazanavir and ritonavir were detected in amniotic fluid only. Robust mRNA expression of key transporters was observed in adult and fetal tissues, and sex differences were identified in the expression of Abcc1 and Slc29a1 in the placenta. Antiretroviral drug exposure was associated with a reduction in relative placental Abcg2, Abcc1, and Slc29a1 expression. CONCLUSION: These findings identify a novel effect of fetal sex and antiretroviral drug treatment on the expression of placental transporters in a mouse model, and characterize the penetration of lamivudine and abacavir into fetal brain, uncovering a potential role of transporters in modulating fetal exposure to antiretroviral drugs.
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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 | 0.000 | 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) | 0.000 | 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".