The Evaluation of Serum Il-6 Changes as Proliferative Cytokines in Patients With Nasopharyngeal Carcinoma Before and After the Ionizing Radiotherapy
Bibliographic record
Abstract
BACKGROUND: Nasopharyngeal carcinoma is a squamous cell malignancy derived from the nasopharyngeal epithelial layer. This study aimed to calculate the IL-6 levels in patients with nasopharyngeal carcinoma before and after radiotherapy, in the week I and week 3 during the radiotherapy, and 2 weeks after the radiotherapy.METHODS: The study was conducted in a prospective cohort on 16 people suffering from nasopharyngeal carcinoma and undergoing radiotherapy, i.e. 9 patients were in stage I of nasopharyngeal carcinoma and 7 people were in stage II of nasopharyngeal carcinoma. Each sample underwent the examination of IL-6 before the week I and week 3 during the radiotherapy, and 2 weeks after the radio¬therapy.RESULTS: The more they received the treatment with radiotherapy the greater was the decrease of serum IL-6. The percentages of the decrease of the levels of serum IL-6 was greater in those receiving the 3-week duration of radiotherapy (24.59%) compared to those who just received 1-week duration of radiotherapy (6.44%). The decrease of serum IL-6 would continue, although radio-therapy had ended; 2 weeks after the radio-therapy, the percentage of serum IL-6 decreased to 42.43% from the level of serum IL-6 before the radio-therapy.CONCLUSIONS: The research results indicated that there happened a significant decrease of serum IL-6 (p<0.05) after the treatment with the radio-therapy
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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 | 0.000 | 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".