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Record W2105589914 · doi:10.1002/hed.21468

Prognostic significance of nuclear pSTAT3 in oral cancer

2010· article· en· W2105589914 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 · 2010
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsImmunohistochemistryCancer researchStage (stratigraphy)MedicineProportional hazards modelMetastasisCancerHazard ratioOncologyInternal medicineClinical significanceCellPathologyBiologyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Aberrant nuclear accumulation of proteins influences tumor development and may predict biologic aggressiveness and disease prognosis. This study determined the prognostic significance of pSTAT3 (phosphorylayed signal transducer and activator of transcription 3) in oral squamous cell carcinomas (OSCCs). METHODS AND RESULTS: Using immunohistochemistry, a significant increase in nuclear accumulation of pSTAT3 was observed in 49 of 90 leukoplakias (54.4%) and 63/94 OSCCs (67%) (p(trend) < .001). Increased pSTAT3 was associated with tumor stage (p = .01), nodal metastasis (p = .0018), and tobacco consumption (p = .004). Kaplan-Meier analysis demonstrated that OSCC with increased nuclear pSTAT3 showed significantly reduced disease-free survival (13 months), compared with the patients with no nuclear pSTAT3 expression (64 months, p = .019). Cox regression analysis revealed nuclear pSTAT3 as the most significant predictor of poor prognosis (p = .024, hazard ratio [HR] = 2.7). CONCLUSIONS: Increased nuclear accumulation of pSTAT3 occurs in early premalignant stages and is a marker for poor prognosis of OSCC.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score1.000

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)0.0010.000

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 head0.331
Teacher spread0.301 · 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