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Record W2269649834 · doi:10.1139/bcb-2013-0052

Recombinant human PDCD5 protein enhances chemosensitivity of breast cancer in vitro and in vivo

2013· article· en· W2269649834 on OpenAlexvenueno aff
Lanlan Wang, Changjun Wang, Bingnan Su, Quansheng Song, Yingmei Zhang, Yang Luo, Qi Li, Weifeng Tan, Dalong Ma, Lu Wang

Bibliographic record

VenueBiochemistry and Cell Biology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsnot available
FundersPeking University Health Science CenterNational Natural Science Foundation of China
KeywordsPaclitaxelIn vivoClonogenic assayBreast cancerApoptosisCancer researchCancer cellIn vitroCancerBreast cancer chemotherapyPharmacologyChemotherapyProgrammed cell deathMedicineChemistryBiologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Resistance to paclitaxel is common for treatment of breast cancer. Programmed cell death 5 (PDCD5) accelerates apoptosis in different cell types in response to various stimuli; moreover PDCD5 has been shown to be down-regulated in many tumors. In this study, protein levels of PDCD5 were found to be up-regulated in paclitaxel-treated MDA-MB-231 breast cancer cells. MTT, CCK-8, and clonogenic assays have shown that recombinant human PDCD5 (rhPDCD5) alone could not produce an obvious growth inhibition. However, upon paclitaxel triggering apoptosis, rhPDCD5 protein potentiated chemotherapeutic drugs-induced growth arrest in MDA-MB-231, SK-BR-3, and ZR-75-1 breast cancer cells. In vivo, we use a human breast cancer xenograft model to study. We found that rhPDCD5 dramatically improves the antitumor effects of paclitaxel treatment by intraperitoneal administration. These data suggest that rhPDCD5 has the potential to use as a therapeutic agent to enhance the paclitaxel sensitivity of breast cancer 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.226
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2013
Admission routes1
Has abstractyes

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