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Record W2156567043 · doi:10.1093/carcin/bgv028

Mechanisms of environmental chemicals that enable the cancer hallmark of evasion of growth suppression

2015· review· en· W2156567043 on OpenAlexaffabout
Rita Nahta, Fahd Al‐Mulla, Rabeah Al‐Temaimi, Amedeo Amedei, Rafaela Andrade-Vieira, Sarah Bay, Dustin G. Brown, Gloria M. Calaf, Robert C. Castellino, Karine Cohen-Solal, Annamaria Colacci, Nichola Cruickshanks, Paul Dent, Riccardo Di Fiore, Stefano Forte, Gary S. Goldberg, Roslida Abd Hamid, Harini Krishnan, Dale W. Laird, Ahmed Lasfar, Paola A. Marignani, Lorenzo Memeo, Chiara Mondello, Christian C. Naus, Richard Ponce‐Cusi, Jayadev Raju, Debasish Roy, Rabindra Roy, Elizabeth P. Ryan, Hosni Salem, A. Ivana Scovassi, Neetu Singh, Monica Vaccari, Renza Vento, Jan Vondráček, Mark Wade, Jordan Woodrick, William H. Bisson

Bibliographic record

VenueCarcinogenesis · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of British ColumbiaWestern UniversityHealth CanadaDalhousie University
FundersNational Institute of Environmental Health SciencesNational Cancer Institute
KeywordsEvasion (ethics)CancerGrowth inhibitionCancer cellBiologyRetinoblastomaRetinoblastoma proteinGrowth factorCell growthCell biologyCancer researchImmunologyBiochemistryGeneticsGeneImmune systemCell cycle

Abstract

fetched live from OpenAlex

As part of the Halifax Project, this review brings attention to the potential effects of environmental chemicals on important molecular and cellular regulators of the cancer hallmark of evading growth suppression. Specifically, we review the mechanisms by which cancer cells escape the growth-inhibitory signals of p53, retinoblastoma protein, transforming growth factor-beta, gap junctions and contact inhibition. We discuss the effects of selected environmental chemicals on these mechanisms of growth inhibition and cross-reference the effects of these chemicals in other classical cancer hallmarks.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.289
Teacher spread0.250 · 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 designNot applicable
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

Citations61
Published2015
Admission routes2
Has abstractyes

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