Expression of Interleukin-8, Interleukin-10 and Epstein-Barr Viral-Load as Prognostic Indicator in Nasopharyngeal Carcinoma
Bibliographic record
Abstract
Interleukin-8 (IL-8) is angiogeneic chemokine that plays a potential role in both development and progression of many human malignancies including nasopharyngeal carcinoma (NPC). Epstein- Barr virus (EBV) is recognized to be an important etiologic agent of NPC as the viral gene products are frequently detected in NPC tissue along with the elevation of antibody titre to the viral protein (VCA-p18+ EBNA1) of IgA in the majority of patients. Elevated plasma of Viral Load is regarded as an important marker for the presence of the disease and for the monitoring of disease progression. However, other serum /plasma parameters such as the level of certain interleukins (IL-8 and IL-10) has also been implicated in NPC progression. The study aimed to investigate the correlations between plasma Viral Load and the level of interleukin (IL-8) and Interleukin (IL-10) in relating these parameters to the stages of NPC. In addition of Viral Load (VCA-p18+EBNA1) IgA, Interleukin-8 and Interleukin-10 before and after therapy will be investigated to seek the possible marker for disease progression. A total of 39 NPC patients and 29 healthy control individuals enrolled in this study. Plasma Viral Load was quantified using real-time quantitative PCR. The Level of plasma interleukins both IL-8 and IL-10 were analyzed using ELISA methods. Results indicated there was a significant decrease in viral load was detected in plasma of NPC patients following therapy. Plasma of viral load was shown to be a good prognosticator for disease progression. There were positive correlation between plasma of viral load and IL-8. These non invasive parameters expressed in blood, could be substitutes of viral load using brushing method, which is invasive. In conclusion that: Viral Load, (VCA-p18+EBNA1) IgA and IL-8 levels are promising markers for the presence of NPC and progression of the disease.
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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".