Iodine-124: A Promising Positron Emitter for Organic PET Chemistry
Bibliographic record
Abstract
The use of radiopharmaceuticals for molecular imaging of biochemical and physiological processes in vivo has evolved into an important diagnostic tool in modern nuclear medicine and medical research. Positron emission tomography (PET) is currently the most sophisticated molecular imaging methodology, mainly due to the unrivalled high sensitivity which allows for the studying of biochemistry in vivo on the molecular level. The most frequently used radionuclides for PET have relatively short half-lives (e.g. 11C: 20.4 min; 18F: 109.8 min) which may limit both the synthesis procedures and the time frame of PET studies. Iodine-124 (124I, t1/2 = 4.2 d) is an alternative long-lived PET radionuclide attracting increasing interest for long term clinical and small animal PET studies. The present review gives a survey on the use of 124I as promising PET radionuclide for molecular imaging. The first part describes the production of 124I. The second part covers basic radiochemistry with 124I focused on the synthesis of 124I-labeled compounds for molecular imaging purposes. The review concludes with a summary and an outlook on the future prospective of using the long-lived positron emitter 124I in the field of organic PET chemistry and molecular imaging.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".