Hyperbranched Polyglycerols as Trimodal Imaging Agents: Design, Biocompatibility, and Tumor Uptake
Bibliographic record
Abstract
Combining various imaging modalities often leads to complementary information and synergistic advantages. A trimodal long-circulating imaging agent tagged with radioactive, magnetic resonance, and fluorescence markers is able to combine the high sensitivity of SPECT with the high resolution of MRI over hours and days. The fluorescence marker helps to confirm the in vivo imaging information at the microscopic level, in the context of the tumor microenvironment. To make a trimodal long-circulating probe, high-molecular-weight hyperbranched polyglycerols (HPG) were modified with a suitable ligand for (111)In radiolabeling and Gd coordination, and additionally tagged with a fluorescent dye. The resulting radiopharmaceutical and contrast agent was nontoxic and hemocompatible. Measured radioactively, its total tumor uptake increased from 2.6% at 24 h to 7.3% at 72 h, which is twice the increase expected due to tumor growth in this time period. Both in vivo MRI and subsequent histological analyses of the same tumors confirmed maximum HPG accumulation at 3 days post injection. Furthermore, Gd-derivatized HPG has an excellent contrast enhancement on T1-weighted MRI at 10× lower molar concentrations than commercially available Galbumin. HPG derivatized with gadolinium, radioactivity, and fluorescence are thus long-circulating macromolecules with great potential for imaging of healthy and leaky blood vessels using overlapping multimodal approaches and for the passive targeting of tumors.
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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 | 0.000 | 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 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".