Development of a standardized flow cytometric method to conduct longitudinal analyses of intracellular CD3ζ expression in patients with head and neck cancer
Bibliographic record
Abstract
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common neoplasm in the world. The follow-up protocols currently available do not appear to diagnose treatment failures and recurrences early enough to provide the best treatment to improve the survival rates of patients. The identification of biomarkers may aid in diagnosing, monitoring the progression, or predicting treatment outcomes in HNSCC. The present study aimed to evaluate whether cluster of differentiation (CD) 3ζ chain expression may serve as a biomarker for the early detection of recurrent or persistent HNSCC. However, in a longitudinal study, a standardized method that allows consistent data comparisons in an inter-assay manner is critical. The present study reveals a method to monitor expression levels of CD3ζ over multiple time-points using flow cytometry. The present study validated the use of an internal control and normalization procedure for tracking alterations in CD3ζ expression in samples from patients with HNSCC, which were collected and assayed for a longitudinal study.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".