Zebrafish as a predictive screening model to assess macrophage clearance of liposomes in vivo
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Macrophage recognition of nanoparticles is highly influenced by particle size and surface modification. Due to the lack of appropriate in vivo screening models, it is still challenging and time-consuming to characterize and optimize nanomedicines regarding this undesired clearance mechanism. Therefore, we validate zebrafish embryos as an emerging vertebrate screening tool to assess the macrophage sequestration of surface modified particulate formulations with varying particle size under realistic biological conditions. Liposomes with different PEG molecular weights (PEG350-PEG5000) at different PEG densities (3.0-10.0 mol%) and particle sizes between 60 and 120 nm were used as a well-established reference system showing various degrees of macrophage uptake. The results of in vitro experiments, zebrafish embryos, and in vivo rodent biodistribution studies were consistent, highlighting the validity of the newly introduced zebrafish macrophage clearance model. We hereby present a strategy for efficient, systematic and rapid nanomedicine optimization in order to facilitate the preclinical development of nanotherapeutics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it