MétaCan
Menu
Back to cohort
Record W3161219429 · doi:10.1115/1.4051184

Electroporation-Based Therapy for Brain Tumors: A Review

2021· review· en· W3161219429 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

VenueJournal of Biomechanical Engineering · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsElectroporationIrreversible electroporationIn vivoMedicineBlood–brain barrierElectrochemotherapyNeuroscienceBrain tumorGliomaCancer researchPathologyChemistryBiologyCentral nervous systemInternal medicine

Abstract

fetched live from OpenAlex

Electroporation-based therapy (EBT), as a high-voltage-pulse technology has been prevalent with favorable clinical outcomes in the treatment of various solid tumors. This review paper aims to promote the clinical translation of EBT for brain tumors. First, we briefly introduced the mechanism of pore formation in a cell membrane activated by external electric fields using a single cell model. Then, we summarized and discussed the current in vitro and in vivo preclinical studies, in terms of (1) the safety and effectiveness of EBT for brain tumors in animal models, and (2) the blood-brain barrier (BBB) disruption induced by EBT. Two therapeutic effects could be achieved in EBT for brain tumors simultaneously, i.e., the tumor ablation induced by irreversible electroporation (IRE) and transient BBB disruption induced by reversible electroporation (RE). The BBB disruption could potentially improve the uptake of antitumor drugs thereby enhancing brain tumor treatment. The challenges that hinder the application of EBT in the treatment of human brain tumors are discussed in the review paper as well.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.946
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.040
GPT teacher head0.372
Teacher spread0.332 · 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