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Record W2898585836 · doi:10.1136/jim-2018-000874

Statins: A New Approach to Combat Temozolomide Chemoresistance in Glioblastoma

2018· review· en· W2898585836 on OpenAlexafffund
Shahla Shojaei, Javad Alizadeh, James A. Thliveris, Navid Koleini, Elissavet Kardami, Grant M. Hatch, Fred Y. Xu, Sabine Hombach‐Klonisch, Thomas Klonisch, Saeid Ghavami

Bibliographic record

VenueJournal of Investigative Medicine · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaCancer Research SocietyManitoba Health Research Council
KeywordsTemozolomideGlioblastomaMedicineCancerCancer researchAdjuvantAdjuvant therapyCancer therapyApoptosisOncologyPharmacologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Patients with glioblastoma multiforme (GBM) have an average life expectancy of approximately 15 months. Recently, statins have emerged as a potential adjuvant cancer therapy due to their ability to inhibit cell proliferation and induce apoptosis in many types of cancer. The exact mechanisms that mediate the inhibitory actions of statins in cancer cells are largely unknown. The purpose of this proceeding paper is to discuss some of the known anticancer effects of statins, while focusing on GBM therapy that includes adjunct therapy of statins with chemotherapeutic agents.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.061
GPT teacher head0.334
Teacher spread0.273 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2018
Admission routes2
Has abstractyes

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