Interleukin-23-Induced Interleukin-23 Receptor Subunit Expression Is Mediated by the Janus Kinase/Signal Transducer and Activation of Transcription Pathway in Human CD4 T Cells
Bibliographic record
Abstract
Interleukin (IL)-23 plays a critical role in the development of the T helper (Th) cell response and is responsible for the maintenance of the IL-17 producing subset of Th cells, Th17. IL-23 is a heterodimeric cytokine composed of IL-23p19 and IL-12p40 subunits, and the signaling pathway for IL-23 involves 2 receptor chains: IL-12Rβ1 and IL-23Rα. The IL-23 receptor complex is expressed on a number of cells, including natural killer cells, monocytes, macrophages, dendritic cells, and CD4 T cells. Currently, the molecular mechanisms governing expression of the IL-23 receptor chains, IL-23Rα and IL-12Rβ1, are not well understood. Our results show that IL-23 induces upregulation of IL-23Rα and IL-12Rβ1 expression in human CD4 T cells. Further, we demonstrate that inhibition of the Janus kinase/signal transducer and activation of transcription (JAK/STAT) pathway by SD-1029, a JAK2 inhibitor, 5'-deoxy-5'-(methylthio) adenosine, a STAT1 inhibitor, and STAT3 VII, a STAT3 inhibitor, were able to block IL-23-induced expression of IL-23 receptor subunits in the human SUPT-1 T cell line and in primary CD4 human T cells. Taken together, our results suggest a positive feedback regulation of the IL-23 receptor via IL-23-mediated activation of the JAK/STAT pathway.
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) | 0.000 | 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 | 0.001 |
| 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".