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Record W1981728331 · doi:10.1182/blood-2011-04-346528

Noninvasive bioluminescent imaging of primary patient acute lymphoblastic leukemia: a strategy for preclinical modeling

2011· article· en· W1981728331 on OpenAlexaff
David M. Barrett, Alix E. Seif, Carmine Carpenito, David T. Teachey, Jonathan D. Fish, Carl H. June, Stephan A. Grupp, Gregor S. D. Reid

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersNational Cancer Institute
KeywordsLeukemiaMedicineLimitingClinical endpointMinimal residual diseaseCancer researchImmunologyOncologyClinical trialPathology

Abstract

fetched live from OpenAlex

The efficient engraftment in immune-deficient mice achieved with both acute lymphoblastic leukemia (ALL) cell lines and primary samples has facilitated identification of the antileukemia activity of a wide variety of agents. Despite widespread usage, however, little is known about the early ALL localization and engraftment kinetics in this model, limiting experimental read-outs primarily to survival and endpoint analysis at high disease burden. In this study, we report that bioluminescent imaging can be reproducibly achieved with primary human ALL samples. This approach provides a noninvasive, longitudinal measure of leukemia burden and localization that enhances the sensitivity of treatment response detection and provides greater insight into the mechanism of action of antileukemia agents. In addition, this study reveals significant cell line- and species-related differences in leukemia migration, especially early in expansion, which may confound observations between various leukemia models. Overall, this study demonstrates that the use of bioluminescent primary ALL allows the detection and quantitation of treatment effects at earlier, previously unquantifiable disease burdens and thus provides the means to standardize and expedite the evaluation of anti-ALL activity in preclinical xenograft studies.

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 score0.008
Threshold uncertainty score0.798

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 head0.040
GPT teacher head0.282
Teacher spread0.242 · 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

Citations55
Published2011
Admission routes1
Has abstractyes

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