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Record W3089028593 · doi:10.2967/jnumed.120.249367

Repurposing <sup>11</sup>C-PS13 for PET Imaging of Cyclooxygenase-1 in Ovarian Cancer Xenograft Mouse Models

2020· article· en· W3089028593 on OpenAlexaff
Amanda J. Boyle, Junchao Tong, Sami S. Zoghbi, Victor W. Pike, Robert B. Innis, Neil Vasdev

Bibliographic record

VenueJournal of Nuclear Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institutes of Health
KeywordsBiodistributionOvarian cancerCyclooxygenaseMedicineIn vivoPositron emission tomographyEx vivoCancerMetastasisCancer researchChemistryNuclear medicineInternal medicineBiology

Abstract

fetched live from OpenAlex

Cyclooxygenase-1 (COX-1), a biomarker for neuroinflammation, is implicated in the progression and prognosis of ovarian cancer (OvCa). This study considered the repurposing of <sup>11</sup>C-labeled 1,5-bis(4-methoxyphenyl)-3-(2,2,2-trifluoroethoxy)-1<i>H</i>-1,2,4-triazole (<sup>11</sup>C-PS13), a COX-1 PET neuroimaging radiopharmaceutical, in OvCa xenograft mouse models. <b>Methods:</b><sup>11</sup>C-PS13 was evaluated in ICRscid mice with subcutaneous or intraperitoneal human OVCAR-3 OvCa xenografts by dynamic PET/MRI, ex vivo biodistribution, and radiometabolite analysis of plasma and tumor. <b>Results:</b> OVCAR-3 xenografts were well visualized with <sup>11</sup>C-PS13 in xenograft mouse models. Time–activity curves revealed a steady accumulation of tumor radioactivity that plateaued from 40 to 60 min and was significantly reduced by pretreatment with ketoprofen (3.56 ± 0.81 and 1.30 ± 0.18 percentage injected dose/g without and with pretreatment, respectively, <i>P</i> = 0.01). Radiometabolite analysis showed that intact <sup>11</sup>C-PS13 accounted for more than 80% of radioactivity in the tumor, with less than 20% in plasma, at 40 min after injection. <b>Conclusion:</b><sup>11</sup>C-PS13 shows promise for PET imaging of COX-1 in OvCa, and rapid translation for clinical cancer research should be considered.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.280
Teacher spread0.256 · 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 designSimulation or modeling
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

Citations9
Published2020
Admission routes1
Has abstractyes

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