MétaCan
Menu
← Back to cohort
Record W4285741313

Sex steroid modulation of macrophages within the prostate tumor microenvironment.

2022· article· en· W4285741313 on OpenAlexaff
Zohra Berrehail, Clovis Boibessot, Typhaine Gris, France‐Hélène Joncas, Fanny Gaignier, Chantal Guillemette, Louis Lacombe, Yves Fradet, Paul Toren

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsProstate cancerProstateCD163Tumor microenvironmentTestosterone (patch)EstrogenImmune systemDehydroepiandrosteroneInternal medicineAndrogenCancer researchEndocrinologyEx vivoMacrophageMedicineBiologyIn vivoCancerImmunologyHormoneIn vitro
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The role of androgens and other sex steroids is known to influence the prognosis and progression of prostate cancer through different disease states. While androgens are generally regarded as immunosuppressive and estrogens as inflammatory, the specific influence of sex steroids on the immune microenvironment of prostate tumors remains incompletely understood. MATERIAL AND METHODS: culture of patient prostate tissue, we evaluated the influence of androgen, estrogen, and progesterone on immune cells of the prostate microenvironment. RESULTS: cultured prostate biopsies. Finally, in a murine prostate cancer model of long-term sex steroids we observed significant differences in tumor growth in mice implanted with estrogen and DHEA diffusion tubes. CONCLUSIONS: Our results highlight the complex influence of sex steroids on the immune cell composition of prostate tumors. Understanding this biology may help to further personalized therapy and improve patient outcomes.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.020
GPT teacher head0.242
Teacher spread0.222 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicProstate Cancer Treatment and Research→French-language works237,207→