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Record W2766149686 · doi:10.3390/pharmaceutics9040049

The Role of PXR Genotype and Transporter Expression in the Placental Transport of Lopinavir in Mice

2017· article· en· W2766149686 on OpenAlexafffund
Sarabjit Gahir, Micheline Piquette‐Miller

Bibliographic record

VenuePharmaceutics · 2017
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPregnane X receptorFetusEndocrinologyInternal medicineBiologyCYP3A4PlacentaTransporterAndrologyPregnancyMedicineMetabolismNuclear receptorCytochrome P450BiochemistryTranscription factorGenetics

Abstract

fetched live from OpenAlex

Lopinavir (LPV), an antiretroviral protease inhibitor frequently prescribed in HIV-positive pregnancies, is a substrate of Abcb1 and Abcc2. As differences in placental expression of these transporters were seen in Pregnane X Receptor (PXR) −/− mice, we examined the impact of placental transporter expression and fetal PXR genotype on the fetal accumulation of LPV. PXR +/− dams bearing PXR +/+, PXR +/−, and PXR −/− fetuses were generated by mating PXR +/− female mice with PXR +/− males. On gestational day 17, dams were administered 10 mg/kg LPV (i.v.) and sacrificed 30 min post injection. Concentrations of LPV in maternal plasma and fetal tissue were measured by LC-MS/MS, and transporter expression was determined by quantitative RT-PCR. As compared to the PXR +/+ fetal units, placental expression of Abcb1a, Abcc2, and Abcg2 mRNA were two- to three-fold higher in PXR −/− fetuses (p < 0.05). Two-fold higher fetal:maternal LPV concentration ratios were also seen in the PXR +/+ as compared to the PXR −/− fetuses (p < 0.05), and this significantly correlated to the placental expression of Abcb1a (r = 0.495; p < 0.005). Individual differences in the expression of placental transporters due to genetic or environmental factors can impact fetal exposure to their substrates.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.365
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2017
Admission routes2
Has abstractyes

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