PET Imaging of Fructose Metabolism in a Rodent Model of Neuroinflammation with 6-[18F]fluoro-6-deoxy-D-fructose
Bibliographic record
Abstract
Fluorine-18 labeled 6-fluoro-6-deoxy-D-fructose (6-[18F]FDF) targets the fructose-preferred facilitative hexose transporter GLUT5, which is expressed predominantly in brain microglia and activated in response to inflammatory stimuli. We hypothesize that 6-[18F]FDF will specifically image microglia following neuroinflammatory insult. 6-[18F]FDF and, for comparison, [18F]FDG were evaluated in unilateral intra-striatal lipopolysaccharide (LPS)-injected male and female rats (50 µg/animal) by longitudinal dynamic PET imaging in vivo. In LPS-injected rats, increased accumulation of 6-[18F]FDF was observed at 48 h post-LPS injection, with plateaued uptake (60–120 min) that was significantly higher in the ipsilateral vs. contralateral striatum (0.985 ± 0.047 and 0.819 ± 0.033 SUV, respectively; p = 0.002, n = 4M/3F). The ipsilateral–contralateral difference in striatal 6-[18F]FDF uptake expressed as binding potential (BPSRTM) peaked at 48 h (0.19 ± 0.11) and was significantly decreased at one and two weeks. In contrast, increased [18F]FDG uptake in the ipsilateral striatum was highest at one week post-LPS injection (BPSRTM = 0.25 ± 0.06, n = 4M). Iba-1 and GFAP immunohistochemistry confirmed LPS-induced activation of microglia and astrocytes, respectively, in ipsilateral striatum. This proof-of-concept study revealed an early response of 6-[18F]FDF to neuroinflammatory stimuli in rat brain. 6-[18F]FDF represents a potential PET radiotracer for imaging microglial GLUT5 density in brain with applications in neuroinflammatory and neurodegenerative diseases.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".