Dual-Labelled Nanoparticles Inform on the Stability of Fluorescent Labels In Vivo
Bibliographic record
Abstract
Fluorescent labelling is commonly used to monitor the biodistribution of nanomedicines. However, meaningful interpretation of the results requires that the fluorescent label remains attached to the nanomedicine. In this work, we explore the stability of three fluorophores (BODIPY650, Cyanine 5 and AZ647) attached to polymeric hydrophobic biodegradable anchors. Using dual-labelled poly(ethylene glycol)-b-poly(lactic acid) (PEG-PLA) nanoparticles that are both radioactive and fluorescent, we investigated how the properties of the fluorophores impact the stability of the labelling in vitro and in vivo. Results suggest that the more hydrophilic dye (AZ647) is released faster from nanoparticles, and that this instability results in misinterpretation of in vivo data. While hydrophobic dyes are likely more suitable to track nanoparticles in biological environments, quenching of the fluorescence inside the nanoparticles can also introduce artefacts. Altogether, this work raises awareness about the importance of stable labelling methods when investigating the biological fate of nanomedicines.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".