Does Epstein-Barr virus infection have an influence on the development of laryngeal carcinoma? Detection of EBV by Real-Time Polymerase Chain Reaction in tumour tissues of patients with laryngeal carcinoma
Bibliographic record
Abstract
UNLABELLED: Epstein-Barr virus (EBV) is a well-known carcinogenic virus, and the association of EBV with some tumours suggests that there may also be an association between laryngeal carcinoma and EBV. OBJECTIVE: The aim of this study is to determine the role of EBV in the aetiology of laryngeal carcinoma. METHOD: Prospective investigation the EBV with real time polymerase chain reaction in tumour tissues of 25 patients with laryngeal carcinoma and 17 patients with benign laryngeal lesions, and investigation of the relationship between the presence of viral DNA and patients' smoking habits, alcohol consumption, localization and differentiation of the tumour. RESULTS: There was no significant difference between the control group and patient group in terms of EBV polymerase chain reaction positivity (p > 0.05). Also we couldn't find a statistically significant relationship between EBV positivity and differentiation of the tumour, localization of the tumour, smoking and alcohol consumption habits (p > 0.05). CONCLUSION: Our results suggest that, although EBV is present in some of the squamous cell laryngeal carcinomas, its presence has no effect on the pathogenesis of laryngeal carcinomas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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) | 0.002 | 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".