The essential role of IL-7 signalling in CD8+ T-cell activity (57.17)
Bibliographic record
Abstract
Abstract Anti-viral CD8+ T-cell responses become impaired in HIV infection in part due to decreased T-cell survival, function and memory cell development; aspects mediated largely by interleukin-7 (IL-7). In progressive HIV infection, decreased T-cell expression of the IL-7 receptor α (CD127) and impaired IL-7 signalling, despite increased IL-7 production, may contribute to failing T-cell activity. Here we examine the effects of IL-7 on a panel of signalling pathways and investigates how IL-7 signalling pathways are associated with IL-7-related activities in CD8+ T-cells. Low concentrations of IL-7 (10 pg/ml) are capable of inducing maximum activation of the Jak-STAT and PI3K signalling pathways, while higher concentrations (500-1000 pg/ml) were required to induce Bcl-2 production and glucose uptake. Even higher concentrations of IL-7 (10,000 pg/ml) were needed to induce cell proliferation and perforin release. Inhibition of Jak activation reduced IL-7-induced Bcl-2, perforin production and proliferation. The activation of intracellular signalling pathways by IL-7 in human CD8+ T-cells and how they are associated with IL-7-induced functions has been extensively studied. Furthermore, the kinetic and optimal concentrations of IL-7 required for the induction of these functional outcomes suggest a complex control of IL-7-associated functions. This may provide insight in immune restoration therapies in HIV infection, where IL-7 signalling and functions are impaired.
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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) | 0.006 | 0.003 |
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".