Serum IL-13 levels at diagnosis and remission in children with malignant lymphoma
Bibliographic record
Abstract
Interleukin (IL)-13 has been reported to have a role in the pathogenesis of lymphoma through recent molecular studies predominantly in adult patients. As malignant lymphomas in children differ from adult counterparts in terms of histology and response to treatment, we aimed to determine the serum IL-13 levels of patients with lymphoma; its relation with clinical-laboratory parameters and to look for any correlation of serum IL-13 levels with different prognostic factors in children. Twenty-eight patients with malignant lymphoma and 20 age-matched healthy controls were included in the study. The median serum IL-13 level at diagnosis (range 0.59-68 pg/ml, median 3.40 pg/ml) was higher than that in remission (range 0.14-12.2 pg/ml, median 1.60 pg/ml) in the HL group (p < 0.05). Remarkably, median serum IL-13 level of patients with nodular sclerosis at diagnosis was higher than those with mixed-cellularity (p < 0.05) and declined to normal limits during remission (p < 0.05). In Burkitt's lymphoma (BL) subgroup, the median (range 2.94-154 pg/ml, median 4.5 pg/ml) was high and declined to normal levels during remission (range 0.55-11.30 pg/ml, median 1.57 pg/ml) and the difference was significant (p < 0.05). In terms of prognostic factors, serum IL-13 levels were found to be associated with white blood cells counts only in HL group. Although the number of patients is limited in our study, we found that the serum IL-13 levels exhibit variances in different histopathologic groups. IL-13 might have a role in histopathogenesis of lymphoma, but seems to have no prognostic significance. Nevertheless, more molecular studies are needed to evaluate the pathogenesis of HL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".