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Record W2559888791 · doi:10.21873/anticanres.11235

Dynamin 2 Inhibitors as Novel Therapeutic Agents Against Cervical Cancer Cells

2016· article· en· W2559888791 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

VenueAnticancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersKorea Health Industry Development Institute
KeywordsDynaminHeLaCancer researchFibronectinApoptosisLamininCervical cancerCancerCancer cellChemistryIn vitroBiologyEndocytosisCell biologyMedicineCellExtracellular matrixInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

AIM: We investigated the feasibility of dynamin 2 as a potential treatment target in cervical cancer cells. MATERIALS AND METHODS: We performed tissue microarray for dynamin 2 expression in 208 patients with early cervical cancer and in vitro in HeLa cells with dynamin 2 inhibitors MiTMAB, OcTMAB, Dynasore, and DD-6. RESULTS: Tumor size greater than 2 cm or tumor invasion of more than half of the entire cervix was associated with expression of dynamin 2 compared to no expression (p=0.013, and p=0.045, respectively). All dynamin 2 inhibitors significantly reduced proliferation, increased apoptotic activity, and reduced matrix metallopeptidase 9 expression in HeLa cells. Dynasore and DD-6 reduced migration of HeLa cells on laminin 1-coated plates and DD-6 most strongly reduced migration performance on fibronectin-coated plates. CONCLUSION: Targeting dynamin 2 may be a promising new approach for the treatment of cervical 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.

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 score0.149
Threshold uncertainty score0.414

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 head0.048
GPT teacher head0.360
Teacher spread0.312 · 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