Preparation of technetium‐99m bifunctional chelate complexes using a microfluidic reactor: a comparative study with conventional and microwave labeling methods
Bibliographic record
Abstract
A series of reactions between the technetium tricarbonyl core, [99mTc(CO)3(OH2)3]+ and both the bifunctional chelate dithiazole valeric acid (DTV) and insulin derivatized with DTV were performed using microfluidic, microwave, and conventional labeling methods. At low concentrations of ligand, the microfluidic reactor resulted in higher yields than both the microwave and conventional reactions. The labeling of DTV at a concentration of 0.01 mg/ml (32.2 µm) and 100 °C did not occur using conventional techniques, whereas the yield after 7.85 min was 61% in the microfluidic reactor and 18% in the microwave reactor. The labeling of a DTV–insulin conjugate (2.1 mg/ml, 330 µm) at 37 °C was conducted using conventional methods producing the desired product in 21% yield in 15.7 min compared with 40% of the desired product in the identically formulated microfluidic reactor. In addition to the higher radiochemical yield, the radiochemical purity was significantly improved in the microfluidic reactor. The microfluidic reactor offers a number of advantages over conventional and microwave methods and is worthy of further exploration as a method to prepare molecular imaging probes derived from Tc‐99m. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".