Characterization of Oral Squamous Cell Carcinoma Associated Inflammation: A Pilot Study
Bibliographic record
Abstract
Background: Oral squamous cell carcinoma (OSCC) is a devastating disease that is usually associated with a dense associated inflammatory infiltrate. Characterizing tumor-associated inflammation is critical to understand the pathogenies of tumor development and progression. Methods: We have tested a protocol to analyze tissue and salivary immune cells and mediators of 37 patients with OSCC at different stages and compared to eight chronic periodontitis patients and 24 healthy controls. Tissue analysis was based on fluorescent immunohistochemistry (FIHC) and inflammatory mediators were analyzed using a Luminex-based 30-Plex panel. Immune cells were analyzed using multichannel flow cytometry including CD45, CD66b, CD3, CD4, CD8, CD25, CD56, CD68, CD138, PD-1, and PD-L1. Results: We show an increase in OSCC-associated inflammation characterized by increased pro-inflammatory cytokines including IL-6, IL-8, TNFα, and GMCSF and increased salivary immune cells. Conclusion: We described a new method to analyze salivary inflammatory markers that can be used in future studies to monitor disease progression and prognosis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.003 | 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".