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Record W3200909637 · doi:10.1016/j.gendis.2021.08.006

The IL13α 2R paves the way for anti-glioma nanotherapy

2021· review· en· W3200909637 on OpenAlexfundno aff
Ilya V. Ulasov, Anton V. Borovjagin, Anastasia Laevskaya, Мargarita Kamynina, Peter Timashev, Laura Cerchia, Elena A. Rozhkova

Bibliographic record

VenueGenes & Diseases · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsnot available
FundersArgonne National LaboratoryBasic Energy SciencesOntario Institute for Regenerative MedicineMinistry of Science and Higher Education of the Russian FederationOffice of ScienceMinistry of Education and Science of the Russian FederationU.S. Department of Energy
KeywordsGliomaGlioblastomaMedicineOncologyOverall survivalTargeted therapyNeuroscienceCancer researchBioinformaticsInternal medicineBiologyCancer

Abstract

fetched live from OpenAlex

Glioblastoma (GBM) is one of the most aggressive (grade IV) gliomas characterized by a high rate of recurrence, resistance to therapy and a grim survival prognosis. The long-awaited improvement in GBM patients' survival rates essentially depends on advances in the development of new therapeutic approaches. Recent preclinical studies show that nanoscale materials could greatly contribute to the improvement of diagnosis and management of brain cancers. In the current review, we will discuss how specific features of glioma pathobiology can be employed for designing efficient targeting approaches. Moreover, we will summarize the main evidence for the potential of the IL-13R alpha 2 receptor (IL13α2R) targeting in GBM early diagnosis and experimental therapy.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.380
Teacher spread0.362 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2021
Admission routes1
Has abstractyes

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