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Record W4404581143 · doi:10.1016/j.jlb.2024.100236

Fluorescent DCFPYL (GUL-CY5) for detecting circulating tumor and immune cells containing cancer extracellular vesicles in early metastatic prostate cancer prognostication

2024· article· en· W4404581143 on OpenAlexaff
Omar Alawamry, Shuyang Feng, Minzhi Sheng, John J. Hayward, Kristen Cimolai, Nesan Bandali, Kezia Batino, Urban Emmenegger, Stanley K. Liu, John F. Trant, Hon S. Leong

Bibliographic record

VenueThe Journal of Liquid Biopsy · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversity of TorontoUniversity of WindsorSunnybrook Health Science Centre
Fundersnot available
KeywordsProstate cancerExtracellular vesiclesCancerCancer cellImmune systemCirculating tumor cellFluorescenceCancer researchExtracellularMicrovesiclesChemistryMetastasisBiologyMedicineCell biologyInternal medicineImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Introduction: Circulating tumor cell (CTCs) liquid biopsies for metastatic prostate cancer, are in need of clinically relevant biomarkers. We propose using the GUL probe (GUL-Cy5), which is already used in PSMA PET imaging. Additionally, we synthesized an isotype for GUL-Cy5, called tBu-Cy5, to quantitate non-specific binding. To validate GUL-Cy5, we used a commercial antibody specific for PSMA. These reagents were utilized with imaging flow cytometry (imFC) to characterize the probes (GUL-Cy5 and anti-PSMA mAb) and their distribution on CTCs and in immune cells.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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 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

Citations0
Published2024
Admission routes1
Has abstractno

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