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Record W3035408975 · doi:10.1038/s41392-020-0187-x

The mechanisms of sorafenib resistance in hepatocellular carcinoma: theoretical basis and therapeutic aspects

2020· review· en· W3035408975 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

VenueSignal Transduction and Targeted Therapy · 2020
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSorafenibHepatocellular carcinomaResistance (ecology)MedicineOncologyBioinformaticsInternal medicineCancer researchComputational biologyBiology

Abstract

fetched live from OpenAlex

Sorafenib is a multikinase inhibitor capable of facilitating apoptosis, mitigating angiogenesis and suppressing tumor cell proliferation. In late-stage hepatocellular carcinoma (HCC), sorafenib is currently an effective first-line therapy. Unfortunately, the development of drug resistance to sorafenib is becoming increasingly common. This study aims to identify factors contributing to resistance and ways to mitigate resistance. Recent studies have shown that epigenetics, transport processes, regulated cell death, and the tumor microenvironment are involved in the development of sorafenib resistance in HCC and subsequent HCC progression. This study summarizes discoveries achieved recently in terms of the principles of sorafenib resistance and outlines approaches suitable for improving therapeutic outcomes for HCC patients.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.053
GPT teacher head0.267
Teacher spread0.214 · 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