MétaCan
Menu
Back to cohort
Record W2027136090 · doi:10.1002/hed.21699

Frequency of cells expressing CD44, a Head and Neck cancer stem cell marker: Correlation with tumor aggressiveness

2011· article· en· W2027136090 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHead & Neck · 2011
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsCD44Head and neck squamous-cell carcinomaMedicineFlow cytometryStem cellCancer stem cellStem cell markerStage (stratigraphy)Head and neck cancerCellCancerInternal medicineOncologyPathologyCancer researchBiologyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: We previously identified by flow cytometry a Lineage-CD44+ (Lin-CD44+) subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma (HNSCC). We now correlate clinical and histologic factors with Lin-CD44+ cell frequency. METHODS: The study included 31 patients with HNSCC, of whom 87% had stage IV disease. The frequency of Lin-CD44+ cells and the success of xenografting patient tumors in mice were correlated with clinical and pathologic data. RESULTS: The mean frequency of Lin-CD44+ cells was 25% (0.4%-81%). It was 36% in patients who had recurrence versus 15% for those without recurrence (p = .04). Successful xenograft implantation occurred in 53%. Seventy-five percent of patients with successful xenografts had recurrence versus 21% of patients with unsuccessful xenografts (p = .003). CONCLUSIONS: Successful xenograft implantation and a high frequency of Lin-CD44+ cells correlate with known poor prognostic factors such as advanced T classification and recurrence. These findings may support the stem cell concept in HNSCC.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.264
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it