Synthesis and Biological Evaluation of Iodoglucoazomycin (I‐GAZ), an Azomycin–Glucose Adduct with Putative Applications in Diagnostic Imaging and Radiotherapy of Hypoxic Tumors
Bibliographic record
Abstract
Iodoglucoazomycin (I-GAZ; N-(2-iodo-3-(6-O-glucosyl)propyl)-2-nitroimidazole), a non-glycosidic nitroimidazole-6-O-glucose adduct, was synthesized, radioiodinated, and evaluated as a substrate of glucose transporter 1 (GLUT1) for radiotheranostic (therapy+diagnostic) management of hypoxic tumors. Nucleophilic iodination of the nosylate synthon of I-GAZ followed by deprotection afforded I-GAZ in 74 % overall yield. I-GAZ was radioiodinated via 'exchange' labeling using [(123/131) I]iodide (50-70 % RCY) and then purified by Sep-Pak™ (>96 % RCP). [(131) I]I-GAZ was stable in 2 % ethanolic solution in sterile water for 14 days when stored at 5 °C. In cell culture, I-GAZ was found to be nontoxic to EMT-6 cells at concentrations <0.5 mm, and weakly radiosensitizing (SER 1.1 at 10 % survival of EMT-6 cells; 1.2 at 0.1 % survival in MCF-7 cells). The hypoxic/normoxic uptake ratio of [(123) I]I-GAZ in EMT-6 cells was 1.46 at 2 h, and under normoxic conditions the uptake of [(123) I]I-GAZ by EMT-6 cells was unaltered in the presence of 5 mm glucose. The biodistribution of [(131) I]I-GAZ in EMT-6 tumor-bearing Balb/c mice demonstrated rapid clearance from blood and extensive renal and hepatic excretion. Tumor/blood and tumor/muscle ratios reached ∼3 and 8, respectively, at 4 h post-injection. Regression analysis of the first order polynomial plots of the blood and tumor radioactivity concentrations supported a perfusion-excretion model with low hypoxia-dependent binding. [(131) I]I-GAZ was found to be stable in vivo, and did not deiodinate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".