Regulation of Transporters by Nuclear Hormone Receptors: Implications during Inflammation
Bibliographic record
Abstract
Membrane transporters play a critical role in the absorption, distribution, and elimination of both endogenous substrates and xenobiotics. Defects in transporter function can lead to altered drug disposition including toxicity or loss of efficacy. Inflammation is one condition during which variable drug response has been demonstrated, and this can be attributed, at least in part, to changes in the expression of transporter genes. Thus, knowledge of the mechanisms behind transporter regulation can significantly contribute to our ability to predict variations in drug disposition among individuals and during inflammatory disease. The discovery of several xenobiotic-activated nuclear hormone receptors during the past decade including the pregnane X receptor, constitutive androstane receptor, and farnesoid X receptor has contributed greatly toward this endeavor. These receptors regulate the expression of transporters such as P-glycoprotein, MRP2, MRP3, BCRP, and OATP2 (Oatp1a1/OATP1B1), all of which undergo altered expression during an inflammatory response. Nuclear receptors may therefore play an important role in mediating this effect. This review presents what is currently known about the role of nuclear receptors in transporter regulation during inflammation. The use of this knowledge toward understanding interindividual variation in drug response and drug interactions during inflammation as well toward the development of therapeutics to treat transporter-related diseases will also be discussed.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".