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Record W3081056070 · doi:10.1097/cco.0000000000000679

Mechanisms of invasion in glioblastoma

2020· review· en· W3081056070 on OpenAlexafffund
Tiffanie Chouleur, Michel L. Tremblay, Andréas Bikfalvi

Bibliographic record

VenueCurrent Opinion in Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchAgence Nationale de la Recherche
KeywordsGlioblastomaTumor microenvironmentBiologyNeuroscienceCancer researchMedicineTumor cells

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review provides an overview of recent updates in understanding the mechanisms by which glioblastoma cells interact with their cellular and molecular partners within the microenvironment. RECENT FINDINGS: We have now a better knowledge of the cell populations involved in Glioblastoma (GBM) invasion. Recent works discovered the role of new molecular players in GBM invasion, and, most importantly, better models are emerging which better recapitulate GBM invasion. SUMMARY: Invasive properties of glioblastoma make complete surgical resection impossible and highly invasive cells are responsible for tumor recurrence. In this review, we focus on recent updates describing how invasive cells progress in the surrounding tissue along brain structures. We also provide an overview of the current knowledge on key cells and molecular players within the microenvironment that contribute to the invasive process. VIDEO ABSTRACT.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.137
GPT teacher head0.439
Teacher spread0.302 · 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 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

Citations24
Published2020
Admission routes2
Has abstractyes

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