Development of prostate specific membrane antigen targeted ultrasound microbubbles using bioorthogonal chemistry
Bibliographic record
Abstract
Prostate specific membrane antigen (PSMA) targeted microbubbles (MBs) were developed using bioorthogonal chemistry. Streptavidin-labeled MBs were treated with a biotinylated tetrazine (MBTz) and targeted to PSMA expressing cells using trans-cyclooctene (TCO)-functionalized anti-PSMA antibodies (TCO-anti-PSMA). The extent of MB binding to PSMA positive cells for two different targeting strategies was determined using an in vitro flow chamber. The initial approach involved pretargeting, where TCO-anti-PSMA was first incubated with PSMA expressing cells and followed by MBTz, which subsequently showed a 2.8 fold increase in the number of bound MBs compared to experiments performed in the absence of TCO-anti-PSMA. Using direct targeting, where TCO-anti-PSMA was linked to MBTz prior to initiation of the assay, a 5-fold increase in binding compared to controls was observed. The direct targeting approach was subsequently evaluated in vivo using a human xenograft tumor model and two different PSMA-targeting antibodies. The US signal enhancements observed were 1.6- and 5.9-fold greater than that for non-targeted MBs. The lead construct was also evaluated in a head-to-head study using mice bearing both PSMA positive or negative tumors in separate limbs. The human PSMA expressing tumors exhibited a 2-fold higher US signal compared to those tumors deficient in human PSMA. The results demonstrate both the feasibility of preparing PSMA-targeted MBs and the benefits of using bioorthogonal chemistry to create targeted US probes.
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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".