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Record W2990546299 · doi:10.3390/pharmaceutics11120624

Impact of Viral Inflammation on the Expression of Renal Drug Transporters in Pregnant Rats

2019· article· en· W2990546299 on OpenAlexafffund
Navaz Karimian Pour, Eliza R. McColl, Micheline Piquette‐Miller

Bibliographic record

VenuePharmaceutics · 2019
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsInflammationDrugTransporterPharmacologyMedicineVirologyImmunologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

Inflammation impacts the expression and function of drug transporters at term-gestation; however, the impact of inflammation on the expression of drug transporters at mid-gestation is largely unknown. Since renal drug transporters play a key role in the clearance of many drugs prescribed during pregnancy, our objective was to study the impact of the viral mimetic poly I:C on the expression of renal transporters in pregnant rats at mid-gestation. Poly I:C (10 mg/kg) or saline was administered intraperitoneally to pregnant Sprague-Dawley rats on gestational day 14. Expression of renal transporters was measured at 6, 24, and 48 h by qRT-PCR and Western blot. The mRNA levels of Mdr1a, Mrp4, Oct2, Octn1, Octn2, Mate1, Oat1-3, Urat1, Oatp4c1, Ent1, and Pept2 were significantly lower in the poly I:C group at 6 h. At 24 h, only the mRNA levels of Oct2, Oatp4c1, and Ent1 were decreased compared to saline. Poly I:C significantly decreased protein expression of Urat1 at 24 h, and P-gp, Oct2, Mate1, Oat1, Oat3 at 48 h,. Poly I:C imposed significant reductions in the expression of several key renal transporters at mid-gestation in pregnant rats. Thus, viral infection may impact renal excretion of drug transporter substrates, potentially leading to drug-disease interactions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.213

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 head0.362
Teacher spread0.324 · 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 designBench or experimental
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

Citations19
Published2019
Admission routes2
Has abstractyes

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