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Record W2093282527 · doi:10.1158/0008-5472.can-03-2558

Normal Cells Control the Growth of Neighboring Transformed Cells Independent of Gap Junctional Communication and Src Activity

2004· article· en· W2093282527 on OpenAlexaff
David B. Alexander, Hitoshi Ichikawa, John F. Bechberger, Virginijus Valiūnas, Misao Ohki, Christian C. Naus, Takehiko Kunimoto, Hiroyuki Tsuda, W. Todd Miller, Gary S. Goldberg

Bibliographic record

VenueCancer Research · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsUniversity of British Columbia
FundersNational Cancer InstituteNational Institutes of Health
KeywordsCell biologyBiologyProto-oncogene tyrosine-protein kinase SrcCancer cellGrowth factorCadherinTranscription factorGap junctionIntracellularSignal transductionCellCancerReceptorGeneticsGene

Abstract

fetched live from OpenAlex

The growth of many types of cancer cells can be controlled by surrounding normal cells. However, mechanisms underlying this phenomenon have not been defined. We used a layered culture system to investigate how nontransformed cells suppress the growth of neighboring transformed cells. Direct physical contact between transformed and nontransformed cells was required for growth suppression of transformed cells in this system; communication by diffusible factors was not sufficient. However, significant gap junctional communication was not required, indicating that other intercellular junctions mediated this growth regulatory response. We also report that the Src kinase activity in transformed cells was not directly inhibited by contact with nontransformed cells. Instead, nontransformed cells increased the expression of serum deprivation-response protein and the transcription factor four and a half LIM domain 1 in tumor cells. In addition, these results suggest mechanisms by which normal cells may block Wnt signaling, inhibit insulin-like growth factor activity, and promote host recognition of neighboring tumor cells.

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 score0.008
Threshold uncertainty score0.181

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 head0.035
GPT teacher head0.328
Teacher spread0.293 · 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

Citations64
Published2004
Admission routes1
Has abstractyes

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