Lymphoid Cell Infiltration into Epstein‐Barr Virus‐positive Nasopharyngeal Carcinomas
Bibliographic record
Abstract
OBJECTIVES: A pilot study was designed to analyze lymphoid cell infiltration in Epstein-Barr virus-positive (EBV+) nasopharyngeal carcinomas (NPCs) and to determine whether this pattern of infiltration is consistent with non-EBV+ head and neck carcinomas or with solid EBV+ tumors in other locations. STUDY DESIGN: We performed a retrospective analysis of archived NPCs and oral cavity carcinomas. METHODS: Immunohistochemical staining of the archive material for various markers (CD3, CD8, UCHL-1, S-100, and intercellular adhesion molecule) was performed. Polymerase chain reaction techniques to establish the presence of the EBV genome were used. Cells in different locations were counted under a light microscope by 2 of the authors. RESULTS: The infiltration pattern of NPCs was different from that of oral cavity carcinomas. Stromal infiltration was significantly denser in oral cavity carcinomas. Tumor nest infiltration was more pronounced in NPCs. The pattern of infiltration was comparable with what has been described for other solid EBV+ tumors. CONCLUSIONS: The immune response to NPCs is likely to be strongly influenced by the presence of the EBV genome. The pattern of infiltration is similar to that of other non-head and neck EBV+ solid tumors and different from that of EBV- head and neck carcinomas.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".