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Record W4383555638 · doi:10.30683/1929-2279.2023.12.7

Epigenetic Carcinogenesis and Malignancy: The Significance of Migratory Potential

2023· article· en· W4383555638 on OpenAlexvenueno aff
Patrick A. Riley

Bibliographic record

VenueJournal of cancer research updates · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
Fundersnot available
KeywordsMulticellular organismEpigeneticsCarcinogenesisBiologyPhenotypeMalignancyCell divisionEpigenesisCell biologyCellCancer researchGeneticsGene expressionGeneDNA methylation

Abstract

fetched live from OpenAlex

The essential feature of the malignant phenotype is the ability of the affected cells to transgress the normal territorial limits that delineate tissue boundaries. This brief review outlines the process underlying the acquisition of this property based on evidence consistent with the notion that the mechanism of carcinogenesis involves defective epigenetic transmission. The resulting failure of vertical transmission of the differentiated pattern of gene expression in proliferative stem cells which leads to faulty copying of the epigenetic information at each cell division generates widespread genetic abnormalities; a process which is essentially equivalent to a greatly elevated mutation rate. The outcome from the point of view of the affected cell and its progeny would be expected to interfere negatively with the proliferation rate. To some extent this proliferative disadvantage is offset by the altruistic factor necessary for permitting coexistence of different cell types in multicellular organisms but the crucial property which renders certain cells malignant is their ability to transgress tissue boundaries. Affected cells possessing this malignant phenotype are able to penetrate this barrier and enter microenvironmental zones where they are able to proliferate without competition. The competitive growth process is outlined using a simple microenvironmental model.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.037
GPT teacher head0.370
Teacher spread0.333 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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