IL-2 Receptor Blockade Inhibits Late, But Not Early, IFN-γ and CD40 Ligand Expression in Human T Cells: Disruption of Both IL-12-Dependent and -Independent Pathways of IFN-γ Production
Bibliographic record
Abstract
mAbs directed against the alpha-chain (Tac/CD25) of the IL-2R are an emerging therapy in both transplantation and autoimmune disease. However, the mechanisms underlying their therapeutic efficacy have not been fully elucidated. Therefore, we examined the effect of IL-2R blockade on Th1 and Th2 cytokine production from human PBMC. Addition of a humanized anti-Tac Ab (HAT) to activated PBMC cultures inhibited IFN-gamma production from CD4 and CD8 T cells by 80-90%. HAT partially inhibited production of TNF-alpha and completely inhibited production of IL-4, IL-5, and IL-10. Furthermore, IL-12, a central regulatory cytokine that induces IFN-gamma, was undetectable in treated cultures. As T cell-dependent induction of IL-12 is regulated via CD40/CD40 ligand (CD40L) interactions, we examined the effect of HAT on CD40L expression. We found CD40L expression to be biphasic with an early (6 h) peak that is CD28/IL-2-independent, but a later peak (48 h) being CD28/IL-2-dependent and inhibited by HAT. Similarly, IFN-gamma production at 6 h was CD28/IL-2-independent but CD28/IL-2-dependent and inhibited by HAT at 48 h. Nonetheless, addition of rCD40L or exogenous IL-12 to HAT-treated cultures could not restore IFN-gamma production. The IFN-gamma deficit in such cultures appears to be due to a direct inhibition by HAT of IL-12-independent IFN-gamma production from T cells rather than altered expression of either the IL-12Rbeta1 or IL-12Rbeta2 chains. These data demonstrate that IL-2 plays a critical role in the regulation of Th1 and Th2 responses and impacts both IL-12-dependent and -independent IFN-gamma production.
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) | 0.001 | 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".