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Record W3083913249 · doi:10.7150/jca.44037

MiR-137 promotes anoikis through modulating the AKT signaling pathways in Pancreatic Cancer

2020· article· en· W3083913249 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cancer · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsPancreas Centre (Canada)
FundersGuizhou Medical UniversityNational Natural Science Foundation of China
KeywordsAnoikisPancreatic cancerCancer researchProtein kinase BmicroRNAPTENCancer cellBiologyCancerSignal transductionPI3K/AKT/mTOR pathwayCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

and vivo. According to bioinformation analysis of clinical databases, we predicted that paxillin (PXN) was a target of miR-137. Further, TCGA analysis revealed that PXN was closely associated with the development of PC. Through loss-of-function studies, we demonstrated that PXN was a functional target of miR-137 on anoikis of PC cells. Moreover, we found that PXN promoted the activation of the AKT signaling pathways which was involving in the cancer cells anoikis. Together, our findings reveal that miR-137 plays a novel role during anoikis and may serve as a potential target for the detection and treatment of PC.

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.

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)0.000
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 score0.013
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.026
GPT teacher head0.284
Teacher spread0.258 · 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