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Record W2416575465 · doi:10.1515/hmbci-2015-0003

The direct and indirect effects of corticosterone and primary adipose tissue on MCF7 breast cancer cell cycle progression

2015· article· en· W2416575465 on OpenAlexaff
Yaniv Shpilberg, Michael K. Connor, Michael C. Riddell

Bibliographic record

VenueHormone Molecular Biology and Clinical Investigation · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsYork University
Fundersnot available
KeywordsAdipose tissueBreast cancerInternal medicineTumor microenvironmentEndocrinologyCell cycleCancerCancer researchRetinoblastomaCancer cellHormoneCell growthCorticosteroneMedicineBiologyChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Breast cancer is the second leading cause of cancer-related mortality in women. Glucocorticoids (GCs) have the potential to directly affect breast cancer or indirectly via changes to the tumor growth microenvironment a breast cancer is exposed to. The role of GCs in breast cancer progression by direct and indirect means are not fully understood. AIM: To study the direct and indirect effects of GCs on breast cancer cell cycle regulation. METHODS: MCF7 breast cancer cells were incubated with increasing concentrations of corticosterone (CORT) to investigate the direct effects. In addition, MCF7 cells were cultured in conditioned media (CM) from primary adipose tissue excised from CORT-supplemented lean and obese male rats. RESULTS: CORT alone resulted in dose-dependent increases in p27 and hypophosphorylated retinoblastoma protein (Rb) which was accompanied by a reduction in the number of cells in S-phase. CM prepared from adipose tissue overrode these direct CORT effects, suggesting that the tumor growth microenvironment created in the CM dominates MCF7 cell cycle regulation. CONCLUSIONS: The direct inhibitory effects of CORT on cancer cell cycle progression are largely limited by the hormone's effects on adipose tissue biology.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.425

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.312
Teacher spread0.300 · 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 designBench or experimental
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

Citations6
Published2015
Admission routes1
Has abstractyes

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