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Record W1965335659 · doi:10.1002/jcb.21485

Chromatin organization and nuclear microenvironments in cancer cells

2007· review· en· W1965335659 on OpenAlexaff
Shihua He, Katherine Dunn, Paula S. Espino, Bojan Drobic, Lin Li, Jenny Yu, Jianmin Sun, Hou Yu Chen, Susan Pritchard, James Davie

Bibliographic record

VenueJournal of Cellular Biochemistry · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChromatinCell biologyCancer cellScaffold/matrix attachment regionCancerChemistryChromatin remodelingComputational biologyBiologyDNAGenetics

Abstract

fetched live from OpenAlex

Nuclear morphometric descriptors such as nuclear size, shape, DNA content and chromatin organization are used by pathologists as diagnostic markers for cancer. However, our knowledge of events resulting in changes in nuclear shape and chromatin organization in cancer cells is limited. Nuclear matrix proteins, which include lamins, transcription factors (Sp1) and histone modifying enzymes (histone deacetylases), and histone modifications (histone H3 phosphorylation) have roles in organizing chromatin in the interphase nucleus, regulating gene expression programs and determining nuclear shape. Histone H3 phosphorylation, a downstream target of the Ras-mitogen activated protein kinase pathway, is involved in neoplastic transformation. This article will review genetic and epigenetic events that alter chromatin organization in cancer cells and the role of the nuclear matrix in determining nuclear morphology.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.260
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

Citations60
Published2007
Admission routes1
Has abstractyes

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