A Reactive and Specific Sensor for Activity-Based <sup>19</sup>F-MRI Sensing of Zn<sup>2+</sup>
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The rapid fluctuations of metal ion levels in biological systems are faster than the time needed to map fluorinated sensors designed for the 19 F-MRI of cations. An attractive modular solution might come from the activity-based sensing approach. Here, we propose a highly reactive but still ultimately specific synthetic fluorinated sensor for 19 F-MRI mapping of labile Zn 2+ . The sensor comprises a dipicolylamine scaffold for Zn 2+ recognition conjugated to a fluorophenyl acetate entity. Upon binding to Zn 2+, the synthetic sensor is readily hydrolyzed, and the frequency of its 19 F-functional group in 19 F-NMR is shifted by 12 ppm, allowing the display of the Zn 2+ distribution as an artificial MRI-colored map highlighting its specificity compared to other metal ions. The irreversible Zn 2+ -induced hydrolysis results in a “turn-on” 19 F-MRI, potentially detecting the cation even upon a transient elevation of its levels. We envision that additional metal-ion sensors can be developed based on the principles demonstrated in this work, expanding the molecular toolbox currently used for 19 F-MRI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".