It’s a Trap! Aldolase-Prescribed C<sub>4</sub>Deoxyradiofluorination Affords Intracellular Trapping and the Tracing of Fructose Metabolism by PET
Bibliographic record
Abstract
Fructose metabolism has been implicated in various diseases, including metabolic disorders, neurodegenerative disorders, cardiac disorders, and cancer. However, the limited availability of a quantitative imaging radiotracer has hindered its exploration in pathology and diagnostic imaging. Methods: We adopted a molecular design strategy based on the catalytic mechanism of aldolase, a key enzyme in fructolysis. We successfully synthesized a radiodeoxyfluorinated fructose analog, [18F]4-fluoro-4-deoxyfructose ([18F]4-FDF), in high molar activity. Results: Through heavy isotope tracing by mass spectrometry, we demonstrated that C4-deoxyfluorination of fructose led to effective trapping as fluorodeoxysorbitol and fluorodeoxyfructose-1-phosphate in vitro, unlike C1- and C6-fluorinated analogs that resulted in fluorolactate accumulation. This observation was consistent in vivo, where [18F]6-fluoro-6-deoxyfructose displayed substantial bone uptake due to metabolic processing whereas [18F]4-FDF did not. Importantly, [18F]4-FDF exhibited low uptake in healthy brain and heart tissues, known for their high glycolytic activity and background levels of [18F]FDG uptake. [18F]4-FDF PET/CT allowed for sensitive mapping of neuro- and cardioinflammatory responses to systemic lipopolysaccharide administration. Conclusion: Our study highlights the significance of aldolase-guided C4 radiodeoxyfluorination of fructose in enabling effective radiotracer trapping, overcoming limitations of C1 and C6 radioanalogs toward a clinically viable tool for imaging fructolysis in highly glycolytic tissues.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".