Small unilamellar vesicles: a platform technology for molecular imaging of brain tumors
Bibliographic record
Abstract
Molecular imaging enables the non-invasive investigation of cellular and molecular processes. Although there are challenges to overcome, the development of targeted contrast agents to increase the sensitivity of molecular imaging techniques is essential for their clinical translation. In this study, spontaneously forming, small unilamellar vesicles (sULVs) (30 nm diameter) were used as a platform to build a bimodal (i.e., optical and magnetic resonance imaging (MRI)) targeted contrast agent for the molecular imaging of brain tumors. sULVs were loaded with a gadolinium (Gd) chelated lipid (Gd-DPTA-BOA), functionalized with targeting antibodies (anti-EGFR monoclonal and anti-IGFBP7 single domain), and incorporated a near infrared dye (Cy5.5). The resultant sULVs were characterized in vitro using small angle neutron scattering (SANS), phantom MRI and dynamic light scattering (DLS). Antibody targeted and nontargeted Gd loaded sULVs labeled with Cy5.5 were assessed in vivo in a brain tumor model in mice using time domain optical imaging and MRI. The results demonstrated that a spontaneously forming, nanosized ULVs loaded with a high payload of Gd can selectively target and image, using MR and optical imaging, brain tumor vessels when functionalized with anti-IGFBP7 single domain antibodies. The unique features of these targeted sULVs make them promising molecular MRI contrast agents.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".