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Record W2567729469 · doi:10.1038/srep40187

Ameloblastin induces tumor suppressive phenotype and enhances chemosensitivity to doxorubicin via Src-Stat3 inactivation in osteosarcoma

2017· article· en· W2567729469 on OpenAlexfundno aff
Toshinori Ando, Yasusei Kudo, Shinji Iizuka, Takaaki Tsunematsu, Hanako Umehara, Madhu Shrestha, Toshihiro Matsuo, Tadahiko Kubo, Shouji Shimose, Koji Arihiro, Ikuko Ogawa, Mitsuo Ochi, Takashi Takata

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceUniversité de Montréal
KeywordsOsteosarcomaDoxorubicinPhenotypeProto-oncogene tyrosine-protein kinase SrcCancer researchSTAT3BiologyMedicineCell biologyChemotherapyGenePhosphorylationInternal medicineGenetics

Abstract

fetched live from OpenAlex

Ameloblastin (AMBN), the most abundant non-amelogenin enamel matrix protein, plays a role in ameloblast differentiation. Previously, we found that AMBN promoted osteogenic differentiation via the interaction between CD63 and integrin β1, leading to the inactivation of Src; however, how AMBN affects the malignant behavior of osteosarcoma is still unclear. Osteosarcoma affects the bone and is associated with poor prognosis because of the high rate of pulmonary metastases and drug resistance. Here we demonstrated that stable overexpression of AMBN induced apoptosis and suppressed colony formation and cell migration via the inactivation of Src-Stat3 pathway in human osteosarcoma cells. Moreover, AMBN induced chemosensitivity to doxorubicin. Thus, AMBN induced a tumor suppressive phenotype and chemosensitivity to doxorubicin via the AMBN-Src-Stat3 axis in osteosarcoma. Indeed, immunohistochemical expression of AMBN was significantly correlated with better outcome of osteosarcoma patients. Our findings suggest that AMBN can be a new prognostic marker and therapeutic target for osteosarcoma combined with conventional doxorubicin treatment.

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)0.001
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 score0.224
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.011
GPT teacher head0.273
Teacher spread0.261 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

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