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Record W4320731120 · doi:10.3390/ijms24043766

‘Toxic Masculinity’: What Is Known about the Role of Androgen Receptors in Head and Neck Squamous Cell Carcinoma

2023· review· en· W4320731120 on OpenAlexfundno aff
Josipa Čonkaš, Maja Sabol, Petar Ozretić

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicToxin Mechanisms and Immunotoxins
Canadian institutionsnot available
FundersHrvatska Zaklada za ZnanostTerry Fox Foundation
KeywordsHead and neck squamous-cell carcinomaHead and neckAndrogen receptorMasculinityReceptorBasal cellCancer researchInternal medicineOncologyAndrogenMedicineBiologyHormoneHead and neck cancerCancerSociologySurgeryGender studies

Abstract

fetched live from OpenAlex

Head and neck squamous cell carcinoma (HNSCC), the most prevalent cancer in the head and neck region, develops from the mucosal epithelium of the upper aerodigestive tract. Its development directly correlates with alcohol and/or tobacco consumption and infection with human papillomavirus. Interestingly, the relative risk for HNSCC is up to five times higher in males, so it is considered that the endocrine microenvironment is another risk factor. A gender-specific risk for HNSCC suggests either the existence of specific risk factors that affect only males or that females have defensive hormonal and metabolic features. In this review, we summarized the current knowledge about the role of both nuclear and membrane androgen receptors (nAR and mARs, respectively) in HNSCC. As expected, the significance of nAR is much better known; it was shown that increased nAR expression was observed in HNSCC, while treatment with dihydrotestosterone increased proliferation, migration, and invasion of HNSCC cells. For only three out of five currently known mARs-TRPM8, CaV1.2, and OXER1-it was shown either their increased expression in various types of HNSCC or that their increased activity enhanced the migration and invasion of HNSCC cells. The primary treatments for HNSCC are surgery and radiotherapy, but targeted immunotherapies are on the rise. On the other hand, given the evidence of elevated nAR expression in HNSCC, this receptor represents a potential target for antiandrogen therapy. Moreover, there is still plenty of room for further examination of mARs' role in HNSCC diagnosis, prognosis, and treatment.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.298
Teacher spread0.274 · 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 designOther design
Domainnot available
GenreReview

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

Citations10
Published2023
Admission routes1
Has abstractyes

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