IL‐7 downregulates IL‐7Rα expression in human CD8 T cells by two independent mechanisms
Bibliographic record
Abstract
Interleukin (IL)-7 is an essential nonredundant cytokine, and throughout the lifespan of a T-cell signaling via the IL-7 receptor influences cell survival, proliferation and differentiation. It is therefore no surprise that expression of the IL-7 receptor alpha-chain (CD127) is tightly regulated. We have previously shown that IL-7 downregulates expression of CD127 at the cell surface and now elucidate the kinetics of that suppression and demonstrate that IL-7 downregulates CD127 transcripts and surface protein in primary human CD8 T cells by two separate pathways. We show that IL-7 induces the initial reduction in cell-surface CD127 protein independent of transcriptional suppression, which is delayed by 40-60 min. Although IL-7-mediated downregulation of CD127 transcripts is dependent on Janus kinase (JAK)/STAT5, the early downregulation of surface CD127 protein is independent of JAK activity. The data further illustrate that low levels of IL-7 induce smaller and transient decreases in CD127 transcripts and surface protein, whereas higher concentrations induce more profound and sustained suppression. Such flexibility in receptor expression likely allows for fine-tuned immune responses in human CD8 T cells in different microenvironments and in response to different immunological challenges.
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".