IL-21 signalling via STAT3 primes human naïve B cells to respond to IL-2 to enhance their differentiation into plasmablasts
Bibliographic record
Abstract
B-cell responses are guided by the integration of signals through the B-cell receptor (BCR), CD40, and cytokine receptors. The common γ chain (γc)-binding cytokine interleukin (IL)-21 drives humoral immune responses via STAT3-dependent induction of transcription factors required for plasma cell generation. We investigated additional mechanisms by which IL-21/STAT3 signaling modulates human B-cell responses by studying patients with STAT3 mutations. IL-21 strongly induced CD25 (IL-2Rα) in normal, but not STAT3-deficient, CD40L-stimulated naïve B cells. Chromatin immunoprecipitation confirmed IL2RA as a direct target of STAT3. IL-21-induced CD25 expression was also impaired on B cells from patients with IL2RG or IL21R mutations, confirming a requirement for intact IL-21R signaling in this process. IL-2 increased plasmablast generation and immunoglobulin secretion from normal, but not CD25-deficient, naïve B cells stimulated with CD40L/IL-21. IL-2 and IL-21 were produced by T follicular helper cells, and neutralizing both cytokines abolished the B-cell helper capacity of these cells. Our results demonstrate that IL-21, via STAT3, sensitizes B cells to the stimulatory effects of IL-2. Thus, IL-2 may play an adjunctive role in IL-21-induced B-cell differentiation. Lack of this secondary effect of IL-21 may amplify the humoral immunodeficiency in patients with mutations in STAT3, IL2RG, or IL21R due to impaired responsiveness to IL-21.
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) | 0.002 | 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".