Nanoparticle Uptake in a Spontaneous and Immunocompetent Woodchuck Liver Cancer Model
Bibliographic record
Abstract
There is a tremendous focus on the application of nanomaterials for the treatment of cancer. Nonprimate models are conventionally used to assess the biomedical utility of nanomaterials. However, these animals often lack an intact immunological background, and the tumors in these animals do not develop spontaneously. We introduce a preclinical woodchuck hepatitis virus-induced liver cancer model as a platform for nanoparticle (NP)-based in vivo experiments. Liver cancer development in these out-bred animals occurs as a result of persistent viral infection, mimicking human hepatitis B virus-induced HCC development. We highlight how this model addresses key gaps associated with other commonly used tumor models. We employed this model to (1) track organ biodistribution of gold NPs after intravenous administration, (2) examine their subcellular localization in the liver, (3) determine clearance kinetics, and (4) characterize the identity of hepatic macrophages that take up NPs using RNA-sequencing (RNA-seq). We found that the liver and spleen were the primary sites of NP accumulation. Subcellular analyses revealed accumulation of NPs in the lysosomes of CD14+ cells. Through RNA-seq, we uncovered that immunosuppressive macrophages within the woodchuck liver are the major cell type that take up injected NPs. The woodchuck-HCC model has the potential to be an invaluable tool to examine NP-based immune modifiers that promote host anti-tumor immunity.
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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".