<sup>68</sup>Ga Small Peptide Imaging: Comparison of NOTA and PCTA
Bibliographic record
Abstract
In this study, a bifunctional version of the chelate PCTA was compared to the analogous NOTA derivative for peptide conjugation, (68)Ga radiolabeling, and small peptide imaging. Both p-SCN-Bn-PCTA and p-SCN-Bn-NOTA were conjugated to cyclo-RGDyK. The resulting conjugates, PCTA-RGD and NOTA-RGD, retained their affinity for the peptide target, the α(v)β(3) receptor. Both PCTA-RGD and NOTA-RGD could be radiolabeled with (68)Ga in >95% radiochemical yield (RCY) at room temperature within 5 min. For PCTA-RGD, higher effective specific activities, up to 55 MBq/nmol, could be achieved in 95% RCY with gentle heating at 40 °C. The (68)Ga-radiolabeled conjugates were >90% stable in serum and in the presence of excess apo-transferrin over 4 h; (68)Ga-PCTA-RGD did have slightly lower stability than (68)Ga-NOTA-RGD, 93 ± 2% compared to 98 ± 1%, at the 4 h time point. Finally, the tumor and nontarget organ uptake and clearance of (68)Ga-radiolabeled PCTA-RGD and NOTA-RGD was compared in mice bearing HT-29 colorectal tumor xenografts. Activity cleared quickly from the blood and muscle tissue with >90% and >70% of the initial activity cleared within the first 40 min, respectively. The majority of activity was observed in the kidney, liver, and tumor tissue. The observed tumor uptake was specific with up to 75% of the tumor uptake blocked when the mice were preinjected with 160 nmol (100 μg) of unlabeled peptide. Uptake observed in the blocked tumors was not significantly different than the background activity observed in muscle tissue. The only significant difference between the two (68)Ga-radiolabeled bioconjugates in vivo was the kidney uptake. (68)Ga-radiolabeled PCTA-RGD had significantly lower (p < 0.05) kidney uptake (1.1 ± 0.5%) at 2 h postinjection compared to (68)Ga-radiolabeled NOTA-RGD (2.7 ± 1.3%). Overall, (68)Ga-radiolabeled PCTA-RGD and NOTA-RGD performed similarly, but the lower kidney uptake for (68)Ga-radiolabeled PCTA-RGD may be advantageous in some imaging applications.
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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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".