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Record W1990682246 · doi:10.3390/ijms13055982

The Role of Receptor for Advanced Glycation End Products (RAGE) in the Proliferation of Hepatocellular Carcinoma

2012· article· en· W1990682246 on OpenAlexaff
Al-Madhagi Yaser, Yan Huang, Rong-Rong Zhou, Guan-Sheng Hu, Mei-Fang Xiao, Zhe-Bing Huang, Chao-Jun Duan, Wei Tian, Daolin Tang, Xuegong Fan

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsRage (emotion)GlycationHepatocellular carcinomaReceptorCancer researchAdvanced glycation end-productChemistryInternal medicineMedicineCell biologyBiochemistryBiologyNeuroscience

Abstract

fetched live from OpenAlex

The receptor for advanced glycation end products (RAGE) is oncogenic and overexpressed in human cancers, but its role in hepatocellular carcinoma remains unclear. Here we demonstrated that RAGE is overexpressed in primary hepatocellular carcinoma (PHC) compared to adjacent para-neoplastic liver samples. Serum endogenous secretory RAGE levels were also increased in PHC patients (p < 0.01). Moreover, we demonstrated that RAGE regulates cellular proliferation in Hepatocellular carcinoma (HCC). Knockdown of RAGE by specific siRNA inhibited cellular growth in the hepatocellular carcinoma cell line, Huh7, whereas the RAGE ligand, high mobility group box 1 protein (HMGB1) increased cellular proliferation. In addition, knockdown of RAGE by siRNA arrested cells in the G1 phase and inhibited DNA synthesis (p < 0.01), while HMGB1 protein decreased the number of cells in the G1 phase and increased the number in the S phase (p < 0.05). Furthermore, quantitative real time RT-PCR (qRT-PCR) and Western Blot results demonstrated that RAGE and HMGB1 positively regulate NF-κB p65 expression in Huh7 cells. These studies suggest that RAGE and RAGE ligands are important targets for therapeutic intervention in hepatocellular carcinoma.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.151

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
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 head0.017
GPT teacher head0.311
Teacher spread0.294 · 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

Citations65
Published2012
Admission routes1
Has abstractyes

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