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Blood-Brain Barrier Disruption in the Treatment of Brain Tumors

2010· article· en· W161606654 on OpenAlexafffund
Marie Blanchette, David Fortin

Bibliographic record

VenueMethods in molecular biology · 2010
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsEvans BlueBlood–brain barrierMedicineCentral nervous systemAlbuminPharmacologyPathologyNeuroscienceInternal medicinePsychology

Abstract

fetched live from OpenAlex

Standard chemotherapy administered systemically has a limited efficacy in the treatment of brain tumors. One of the major obstacles in the treatment of brain neoplasias is the impediment to delivery across the intact blood-brain barrier (BBB). Many innovative approaches have been developed to circumvent this obstacle. One such strategy is BBB disruption (BBBD), which successfully increases the delivery of antineoplastic agents to the central nervous system (CNS). This chapter describes the application of the BBBD technique in rats. Different methods to evaluate and measure BBB permeability following hyperosmolar mannitol infusion including Evans blue staining, albumin immunohistochemistry, and dynamic magnetic resonance imaging are also described.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.021
GPT teacher head0.406
Teacher spread0.385 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations62
Published2010
Admission routes2
Has abstractyes

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