[Primary study of relationship between serum level of VEGF and non-Hodgkin's lymphoma in children and adolescent patients].
Bibliographic record
Abstract
BACKGROUND & OBJECTIVE: Angiogenesis is an important mechanism in morbility of malignant tumor, vascular endothelial growth factor (VEGF) is the key factor. This study was to investigate the serum level of VEGF in children and adolescent patients with non-Hodgkin's lymphoma (NHL). METHODS: The serum levels of VEGF(sVEGF) in 24 pretreated NHL patients were detected by ELISA. sVEGF in 10 of the 24 patients who received complete response after treatment were also detected by ELISA. RESULTS: The average serum VEGF level was 745.79 ng/L (40.64-3623.09 ng/L)in 24 NHL patients. It was higher than normal [(294.20+/-23.40) ng/L]. sVEGF in 18 of the patients were higher than the standard, while in 6 of the patients were lower than the standard. The average serum VEGF level was 289.54 ng/L (35.11-826.8 ng/L) in 10 of The CR patients, 8 cases of them had a high VEGF level before treatment but a nearly normal level after first CR. And 2 cases of them had normal level during the course. CONCLUSIONS: The serum level of VEGF in NHL patients was higher than normals. The high serum level of VEGF has a tendency to drop to the normal standard after receiving CR. From the clinical data, a high serum level was not found associated with stage, gender, PS. score, IPI score, serum LDH and "B" symptoms et al.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".