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Record W2383268398 · doi:10.1177/172460081002500105

Human Kallikrein 14 (Klk14) Expression in Salivary Gland Tumors

2010· article· en· W2383268398 on OpenAlexaff
Nelly N. Hashem, Thomas W. Mara, Mohamed Mohamed, Irene Zhang, Kevin Fung, Keith Kwan, Thomas D. Daley, Eleftherios P. Diamandis, Mark Darling

Bibliographic record

VenueThe International Journal of Biological Markers · 2010
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsUniversity of TorontoLondon Health Sciences CentreMount Sinai HospitalWestern University
Fundersnot available
KeywordsSalivary glandPathologyImmunoperoxidaseBiologyKallikreinCarcinomaMedicineImmunologyAntibodyMonoclonal antibody

Abstract

fetched live from OpenAlex

OBJECTIVE: To analyze the expression of human kallikrein 14 (KLK14) in salivary gland tumors. METHODS: A standard immunoperoxidase staining technique was used to assess the expression profile of KLK14 in normal salivary glands and tumors including pleomorphic adenoma (PA; n=17), adenoid cystic carcinoma (ACC; n=13) and mucoepidermoid carcinoma (MEC; n=9). Tumor stage, grade, patient age and gender, and site of occurrence were recorded. These clinical parameters were correlated with KLK14 levels in malignant tumors. The expression profiles for KLK3, 5, 6, 8 and 13 were also retrieved. RESULTS: Normal salivary glands, PA, ACC and MEC showed strong expression of KLK14 in ductal and non-ductal cells. Both PA and ACC showed higher KLK14 levels than normal glands and MEC tissues. There were no statistically significant associations between levels of KLK14 and clinical parameters. CONCLUSIONS: The differences in the levels of KLK14 suggest that KLKs may aid in the differential diagnosis of salivary gland tumors. The coexpression of KLKs suggests their possible involvement in an enzymatic pathway activated in salivary gland. KLK14 may be a promising new biomarker in salivary gland tumors.

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.

How this classification was reachedexpand

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.300
Teacher spread0.276 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe International Journal of Biological MarkersSame topicCoagulation, Bradykinin, Polyphosphates, and AngioedemaFrench-language works237,207