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Record W2331785021 · doi:10.1021/jm2017336

Design, Synthesis, and Preliminary Biological Evaluation of 6-<i>O</i>-Glucose–Azomycin Adducts for Diagnosis and Therapy of Hypoxic Tumors

2012· article· en· W2331785021 on OpenAlexafffund
Piyush Kumar, Gennady V. Shustov, Hong Liang, V. Khlebnikov, Weizhong Zheng, Xiaohong Yang, Chris I. Cheeseman, Leonard I. Wiebe

Bibliographic record

VenueJournal of Medicinal Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsNAEJA-RGM Pharmaceuticals (Canada)University of Alberta
FundersCanadian Institutes of Health Research
KeywordsChemistryIn vivoIn vitroGlucose transporterHypoxia (environmental)PharmacologyGlucose uptakeDownregulation and upregulationToxicityLimitingCancer researchBiochemistryOxygenInsulinInternal medicineBiologyMedicine

Abstract

fetched live from OpenAlex

Several 2-nitroimidazole-based molecules (NIs) are used as clinical hypoxic tumor radiodiagnostics, but they are not effective as radiosensitizers/radiochemotherapeutics. These NIs permeate tumor cells nonselectively via diffusion, and in therapy, where high doses are required, their dose limiting toxicities preclude success. The synthesis and preliminary in vitro evaluations of three glucoazomycins, members of a novel class of C6-O-glucose-linked-azomycin conjugates that are putative substrates of glucose transport proteins (GLUTs) and possess hypoxia-selective radiosensitization features, are now reported. The hypoxia-dependent upregulation of several GLUTs provides a rational basis to develop these glucoazomycins because more selective uptake in hypoxic cells would decrease systemic toxicities at effective doses. Calculated partition coefficients (ClogP, -1.70 to -2.99) predict rapid in vivo clearance for low systemic toxicity. In vitro experimental data show that glucoazomycins are radiosensitizers and that they competitively inhibit glucose uptake.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.055
GPT teacher head0.304
Teacher spread0.249 · 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

Citations38
Published2012
Admission routes2
Has abstractyes

Explore more

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