MétaCan
Menu
Back to cohort
Record W4394213598 · doi:10.6084/m9.figshare.13105875

Diosmetin enhances the sensitivity of radiotherapy by suppressing homologous recombination in endometrial cancer

2020· dataset· en· W4394213598 on OpenAlexaff
Zhiyi Hu, Bailian Cai, Mengfei Wang, Xiaoli Wen, Anke Geng, Xiang Hu, Renhao Xue, Zhiyong Mao, Ying Jiang, Xiaoping Wan

Bibliographic record

VenueFigshare · 2020
Typedataset
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicBioactive Compounds and Antitumor Agents
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsEndometrial cancerHomologous recombinationSensitivity (control systems)Homologous chromosomeCancer researchRadiation therapyChemistryInternal medicineOncologyCancerMedicineBiochemistryGeneElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

Radiotherapy is an essential treatment for endometrial cancer (EC), especially in advanced, metastatic, and recurrent cases. Combining radiotherapy, which mainly causes DNA double-strand breaks (DSBs), with small molecules targeting aberrantly activated homologous recombination (HR) repair pathways holds great potential for treating ECs in advanced stages. Here, we demonstrate that diosmetin (DIO), a natural flavonoid, suppresses HR, therefore inhibiting cell proliferation and enhancing the sensitivity of EC to radiotherapy. Clonogenic experiments revealed that combining DIO and X-ray significantly inhibited the viability of EC cells compared to cells treated with diosmetin or X-ray alone. The survival fraction of EC cells decreased to 40% when combining 0.4 Gy X-ray and 4 μM DIO; however, each treatment alone only caused death in approximately 15% and 22% of cancer cells, respectively. Further mechanistic studies showed that diosmetin inhibited the recruitment of RPA2 and RAD51, two critical factors involved in the HR repair pathway, upon the occurrence of DSBs. Thus, we propose that a combination of diosmetin and irradiation is a promising therapeutic strategy for treating endometrial 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.065
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0650.000

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 head0.148
GPT teacher head0.440
Teacher spread0.292 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicBioactive Compounds and Antitumor AgentsFrench-language works237,207