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Record W2911634249 · doi:10.3390/ph12010031

2-Nitroimidazole-Furanoside Derivatives for Hypoxia Imaging—Investigation of Nucleoside Transporter Interaction, 18F-Labeling and Preclinical PET Imaging

2019· article· en· W2911634249 on OpenAlexaff
Florian Maier, Anna Schweifer, Vijaya L. Damaraju, Carol E. Cass, Gregory D. Bowden, Walter Ehrlichmann, Manfred Kneilling, Bernd J. Pichler, Friedrich Hammerschmidt, Gerald Reischl

Bibliographic record

VenuePharmaceuticals · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of Alberta
FundersAstraZeneca
KeywordsNucleosideHypoxia (environmental)NitroimidazoleMedicinePet imagingTransporterPharmacologyPositron emission tomographyNuclear medicinePathologyChemistryBiochemistryGene

Abstract

fetched live from OpenAlex

The benefits of PET imaging of tumor hypoxia in patient management has been demonstrated in many examples and with various tracers over the last years. Although, the optimal hypoxia imaging agent has yet to be found, 2-nitroimidazole (azomycin) sugar derivatives—mimicking nucleosides—have proven their potential with [18F]FAZA ([18F]fluoro-azomycin-α-arabinoside) as a prominent representative in clinical use. Still, for all of these tracers, cellular uptake by passive diffusion is postulated with the disadvantage of slow kinetics and low tumor-to-background ratios. We recently evaluated [18F]fluoro-azomycin-β-deoxyriboside (β-[18F]FAZDR), with a structure more similar to nucleosides than [18F]FAZA and possible interaction with nucleoside transporters. For a deeper insight, we comparatively studied the interaction of FAZA, β-FAZA, α-FAZDR and β-FAZDR with nucleoside transporters (SLC29A1/2 and SLC28A1/2/3) in vitro, showing variable interactions of the compounds. The highest interactions being for β-FAZDR (IC50 124 ± 33 µM for SLC28A3), but also for FAZA with the non-nucleosidic α-configuration, the interactions were remarkable (290 ± 44 µM {SLC28A1}; 640 ± 10 µM {SLC28A2}). An improved synthesis was developed for β-FAZA. For a PET study in tumor-bearing mice, α-[18F]FAZDR was synthesized (radiochemical yield: 15.9 ± 9.0% (n = 3), max. 10.3 GBq, molar activity > 50 GBq/µmol) and compared to β-[18F]FAZDR and [18F]FMISO, the hypoxia imaging gold standard. We observed highest tumor-to-muscle ratios (TMR) for β-[18F]FAZDR already at 1 h p.i. (2.52 ± 0.94, n = 4) in comparison to [18F]FMISO (1.37 ± 0.11, n = 5) and α-[18F]FAZDR (1.93 ± 0.39, n = 4), with possible mediation by the involvement of nucleoside transporters. After 3 h p.i., TMR were not significantly different for all 3 tracers (2.5–3.0). Highest clearance from tumor tissue was observed for β-[18F]FAZDR (56.6 ± 6.8%, 2 h p.i.), followed by α-[18F]FAZDR (34.2 ± 7.5%) and [18F]FMISO (11.8 ± 6.5%). In conclusion, both isomers of [18F]FAZDR showed their potential as PET hypoxia tracers. Differences in uptake behavior may be attributed to a potential variable involvement of transport mechanisms.

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 score0.080
Threshold uncertainty score0.775

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 head0.032
GPT teacher head0.349
Teacher spread0.316 · 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
Published2019
Admission routes1
Has abstractyes

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