Improving nanoparticle diffusion through tumor collagen matrix by photo-thermal gold nanorods
Bibliographic record
Abstract
Collagen (I) impairs the targeting of nanoparticles to tumor cells by obstructing their diffusion inside dense tumor interstitial matrix. This potentially makes large nanoparticles (>50 nm) reside near the tumor vessels and thereby compromises their functionality. Here we propose a strategy to locally improve nanoparticle transport inside collagen (I) component of the tumor tissue. We first used heat generating gold nanorods to alter collagen (I) matrix by local temperature elevation. We then explored this impact on the transport of 50 nm and 120 nm inorganic nanoparticles inside collagen (I). We demonstrated an increase in average diffusivity of 50 nm and 120 nm in the denatured collagen (I) by ∼14 and ∼21 fold, respectively, compared to intact untreated collagen (I) matrix. This study shows how nanoparticle-mediated hyperthermia inside tumor tissue can improve the transport of large nanoparticles through collagen (I) matrix. The ability to increase nanoparticles diffusion inside tumor stroma allows their targeting or other functionalities to take effect, thereby significantly improving cancer therapeutic or diagnostic outcome.
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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".