Impact of Th-17 Cytokines on the Regulation of Transporters in Human Placental Explants
Bibliographic record
Abstract
Activated T helper 17 (Th-17) cytokines play a role in the pathophysiology of autoimmune and infectious diseases. While these diseases affect many women of childbearing age, little is known about the effect of these cytokines on placental transporters. As several pro-inflammatory cytokines impact the expression of ABC and SLC placental transporters, we hypothesized that these transporters may be similarly altered by elevated levels of circulating Th-17 cytokines. Cultured term human villous explants were treated with IL-17A, IL-22, or IL-23, alone or in combination. Samples were analyzed using qRT-PCR and Western blotting. The mRNA expression of OATP2B1 was significantly downregulated in explants by all individual cytokines and combination treatments, while decreased protein expression was seen with IL-23 and combination (p < 0.01). Combination treatment decreased the mRNA expression of BCRP and OAT4 but increased that of OCT3 (p < 0.01). Decreased accumulation of the OATP substrate, cascade blue, was seen in IL-23-treated choriocarcinoma JAr cells (p < 0.01). Elevated Th-17 cytokines, which are seen in infectious and autoimmune diseases, affect the expression and activity of OATP2B1, as well as mRNA expression of placental BCRP, OAT4, and OCT3. This dysregulation could impact the fetal exposure to endogenous and exogenous substrates.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".