Kinetics of IL-7 and IL-15 Levels after Allogeneic Peripheral Blood Stem Cell Transplantation following Nonmyeloablative Conditioning
Bibliographic record
Abstract
BACKGROUND: We analysed kinetics of IL-7 and IL-15 levels in 70 patients given peripheral blood stem cells after nonmyeloablative conditioning. METHODS: EDTA-anticoagulated plasma and serum samples were obtained before conditioning and about once per week after transplantation until day 100. Samples were aliquoted and stored at -80°C within 3 hours after collection until measurement of cytokines. IL-7 and IL-15 levels were measured by ELISAs. RESULTS: Median IL-7 plasma levels remained below 6 pg/L throughout the first 100 days, although IL-7 plasma levels were significantly higher on days 7 (5.1 pg/mL, P=0.002), 14 (5.2 pg/mL, P<0.001), and 28 (5.1 pg/mL, P=0.03) (but not thereafter) than before transplantation (median value of 3.8 pg/mL). Median IL-15 serum levels were significantly higher on days 7 (12.5 pg/mL, P<0.001), 14 (10.5 pg/mL, P<0.001), and 28 (6.2 pg/mL, P<0.001) than before transplantation (median value of 2.4 pg/mL). Importantly, IL-7 and IL-15 levels on days 7 or 14 after transplantation did not predict grade II-IV acute GVHD. CONCLUSIONS: These data suggest that IL-7 and IL-15 levels remain relatively low after nonmyeloablative transplantation, and that IL-7 and IL-15 levels early after nonmyeloablative transplantation do not predict for acute GVHD.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".