Noninvasive Monitoring of the Fate of <sup>111</sup>In-Labeled Block Copolymer Micelles by High Resolution and High Sensitivity MicroSPECT/CT Imaging
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Bibliographic record
Abstract
The validation of high sensitivity and high resolution microSPECT/CT imaging for tracking the in vivo pathway and fate of an 111Indium-labeled (111In) amphiphilic diblock copolymer micelle formulation is presented. Heterobifunctional poly(ethylene glycol) was used to initiate cationic ring opening polymerization of epsilon-caprolactone, which was then conjugated to 2-(4-isothiocyanatobenzyl)-diethylenetriaminepentaacetic acid (p-SCN-Bn-DTPA) for chelation with 111In. The micelles were characterized in terms of their physicochemical properties including size, size distribution, zeta-potential, and radiochemical purity. Elimination kinetics and tissue deposition were evaluated in healthy mice following administration of 111In-micelles, 111In-DTPA-b-PCL unimers (i.e., administered under the critical micelle concentration) or 111In-Bn-DTPA. Healthy and MDA-MB-231 tumor-bearing mice were imaged using microSPECT/CT following iv administration of 111In-micelles or 111In-Bn-DTPA. Overall, incorporation of 111In onto the surface of thermodynamically stable micelles results in long plasma residence times for the radionuclide and preferential localization within the spleen (22 +/- 5% i.d/g), liver (13 +/- 3% i.d./g), and tumor (9 +/- 2% i.d./g). MicroSPECT/CT imaging provided noninvasive longitudinal visualization of circulation dynamics and tissue deposition. A strong correlation between image-based region of interest (ROI) analysis and biodistribution data was found, implying that nuclear imaging can be used as a noninvasive tool to accurately quantify tissue distribution. As well, the image-based assessment provided unique insight into the intratumoral distribution of the micelles in vivo.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it