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Down‐regulation of <i>ING4</i> is associated with initiation and progression of lung cancer

2010· article· en· W1504938069 on OpenAlexafffund
Qiushi Wang, Ming Li, Linyou Zhang, Yan Jin, Dandan Tong, Yang Yu, Jing Bai, Qi Huang, Fangli Liu, An Liu, Ki‐Young Lee, Song‐bin Fu

Bibliographic record

VenueHistopathology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsLung cancerBiologyImmunohistochemistryCancer researchCancerAdenocarcinomaPathologyCell cycleLymph nodeMetastasisMedicine

Abstract

fetched live from OpenAlex

AIMS: Tumour suppressor ING4 is one of ING family genes, which are involved in cell cycle arrest, gene transcription regulation, DNA repair and apoptosis. ING4 inhibition has been reported in various tumours, including gliomas, breast tumours, and stomach adenocarcinoma. The aim was to evaluate ING4 expression in lung cancers. METHOD AND RESULTS: By immunohistochemistry of 246 lung tumour tissues, reduced ING4 nuclear and cytoplasmic expression were both revealed in lung cancer and associated with tumour grade. Interestingly, compared with normal tissues, we found more tumours with ING4 expression in the cytoplasm higher than in the nucleus. Nuclear ING4 inhibition correlated with the tumour stage and lymph node metastasis. Consistent with these findings, semiquantitative reverse transcriptase-polymerase chain reaction and Western blotting demonstrated decreased ING4 mRNA and expression in 100% (50/50) tumour tissues. Furthermore, ING4 expression was lower in grade III than in grades I-II tumours. Reduced ING4 mRNA correlated with lymph node metastasis. CONCLUSIONS: Our results indicate that overall inhibition of ING4 expression and ING4 expression higher in cytoplasm than in nucleus of tumour cells may be involved in the initiation and progression of lung cancers, and thus, analysis for ING4 expression may be useful as a clinical diagnostic and prognostic tool for lung cancer.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.221

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 studies0.0000.000
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 head0.003
GPT teacher head0.231
Teacher spread0.228 · 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

Citations48
Published2010
Admission routes2
Has abstractyes

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