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Record W3203033389 · doi:10.30683/1927-7229.2020.09.08

Curcumin Inhibits Retinoblastoma Cell Proliferation by miR-26a Targeting the Tumor Suppressor Gene Rb1 in Y79 Cells

2021· article· en· W3203033389 on OpenAlexvenueno aff
Jing Bai, Duo Guo, Xiangyi Liu

Bibliographic record

VenueJournal of Analytical Oncology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsnot available
Fundersnot available
KeywordsRetinoblastomaCarcinogenesisCell growthCancer researchRetinoblastoma proteinSuppressorTumor suppressor geneBiologyGeneMolecular biologyCell biologyCell cycleGenetics

Abstract

fetched live from OpenAlex

The retinoblastoma (Rb1) gene is one of the most important tumor suppressor genes. Dysfunction of Rb protein drives tumorigenesis by overcoming barriers to cellular proliferation. Consequently, factors modulating Rb function are of great clinical import. Here, we show that miR-26a was differentially expressed in human retinoblastoma cells, tissues and serums from retinoblastoma patients, compared with human retinal microvascular endothelial cells, non-tumor tissues and serums from healthy children, and that it tightly regulated the expression of Rb1 by specifically targeting a conserved sequence motif in its UTR, leading to low expression of Rb1. In vitro experiments determined that miR-26a directly participated in the regulation of cell proliferation of human Y79 RB cells. Our results also suggest that curcumin modulated the miR-26a expression profile, thereby exerting its anti-proliferation effects on Y79 RB cells via up-regulation of Rb1. To our knowledge, these data indicate for the first time that miR-26a directly regulates cell proliferation by targeting Rb1 in retinoblastoma and that miR-26a could be a potential therapeutic approach for retinoblastoma.

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 score0.014
Threshold uncertainty score0.443

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 head0.009
GPT teacher head0.262
Teacher spread0.254 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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