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Record W4389792538 · doi:10.3390/ijms242417490

BIRC5 Gene Polymorphisms Are Associated with a Higher Stage of Local and Regional Disease in Oral and Oropharyngeal Squamous Cell Carcinomas

2023· article· en· W4389792538 on OpenAlexfundno aff
Ivan Mumlek, Petar Ozretić, Maja Sabol, Matko Leović, Ljubica Glavaš‐Obrovac, Dinko Leović, Vesna Musani

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsnot available
FundersHrvatska Akademija znanosti i umjetnostiTerry Fox Foundation
KeywordsSurvivinHead and neck squamous-cell carcinomaOncologyBasal cellStage (stratigraphy)DiseaseInternal medicineMedicineCancer researchGeneOverall survivalSurvival rateRadiation therapyBiologyCancerHead and neck cancerGenetics

Abstract

fetched live from OpenAlex

Oral squamous cell carcinoma (OSCC) and oropharyngeal squamous cell carcinoma (OPSCC) are the most common types of cancers in the head and neck region (HNSCC). Despite very aggressive treatment modalities, the five-year survival rate has not changed for decades and is still around 60%. The search for potential specific biomarkers of aggressiveness or outcome indicators could be of great benefit in improving the treatment of these patients. One of the potential biomarkers is survivin, the protein product of the BIRC5 gene. In this study, we investigated the occurrence of BIRC5 gene polymorphisms in 48 patients with OSCC and OPSCC compared with healthy controls. A total of 18 polymorphisms were found, 11 of which occurred in HNSCC with a minor allele frequency (MAF) of more than 5%. Five polymorphisms (rs3764383, rs9904341, rs2071214, rs2239680, rs2661694) were significantly associated with tumor size, tumor stage, and advanced regional disease, but had no impact on survival.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes1
Has abstractyes

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