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Record W2097331724 · doi:10.1007/s11307-013-0641-z

Macromolecule Extravasation—Xenograft Size Matters: A Systematic Study Using Probe-Based Confocal Laser Endomicroscopy (pCLE)

2013· article· en· W2097331724 on OpenAlexafffund
Antje Dietrich, James Stewart, Melanie Huether, Mario Helm, Christina Schuetze, Hans‐Joachim Schnittler, David A. Jaffray, Leoni A. Kunz‐Schughart

Bibliographic record

VenueMolecular Imaging and Biology · 2013
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersTerry Fox FoundationNational Cancer InstituteBundesministerium für Bildung und ForschungDeutsche Forschungsgemeinschaft
KeywordsEndomicroscopyConfocalExtravasationMedicinePathologyBiomedical engineeringMedical physicsOpticsPhysics

Abstract

fetched live from OpenAlex

PURPOSE: Profound changes of the vasculature in tumors critically impact drug delivery and therapy response. We aimed at developing a procedure to monitor morphological and functional parameters of the vasculature in subcutaneous xenograft models commonly applied for therapy testing by using probe-based confocal laser endomicroscopy. PROCEDURES: By monitoring various normal and diseased tissues, we established an experimental and analytical set-up to systematically analyze tracer extravasation from the microvasculature. Application of the approach in two xenograft models (HCT-116 and SW620) was realized consecutively throughout tumor growth. RESULTS: The incidence of dilated vessels increased with xenograft size in both models while macromolecule extravasation and tracer accumulation in the tumor tissue, respectively, was significantly reduced throughout growth. The development of dilated/ultradilated vessels correlated with tracer extravasation only in the HCT-116 but not the SW620 model. The underlying mechanisms are still ambiguous and discussed. CONCLUSIONS: Our findings clearly indicate that both xenograft type and size matter for drug delivery and therapy testing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
GPT teacher head0.324
Teacher spread0.305 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

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