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Record W3033397665

Inhibiting ULK1 kinase decreases autophagy and cell viability in high-grade serous ovarian cancer spheroids.

2020· article· en· W3033397665 on OpenAlexaff
Bipradeb Singha, Jeremi Laski, Yudith Ramos Valdés, Elaine Liu, Gabriel E. DiMattia, Trevor G. Shepherd

Bibliographic record

VenuePubMed · 2020
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsOvarian Cancer CanadaWestern University
Fundersnot available
KeywordsAutophagyCancer researchULK1Ovarian cancerGene knockdownSpheroidViability assayChemistryCancer cellBiologyKinaseCell biologyProtein kinase ACellCancerMedicineCell cultureInternal medicineApoptosisAMPKBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

mRNA expression is negatively correlated with patient survival among stage III and stage IV serous ovarian cancer patients. As we observed using established HGSOC cell lines, cultured spheroids using our new, patient-derived HGSOC cells were also sensitive to ULK1 inhibition and demonstrated reduced cell viability to MRT68921 treatment. These results demonstrate the importance of ULK1 for autophagy induction in HGSOC spheroids and therefore justifies further evaluation of MRT68921, and other novel ULK1 inhibitors, as potential therapeutics against metastatic HGSOC.

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 head0.021
GPT teacher head0.240
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

Citations29
Published2020
Admission routes1
Has abstractyes

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