Multimodal Microscopy Distinguishes Extracellular Aggregation and Cellular Uptake of Single‐Walled Carbon Nanohorns
Bibliographic record
Abstract
The low toxicity, high surface area, and ease of functionalisation of carbon nanohorns (CNH) makes them attractive systems for cellular imaging, diagnostics and therapeutics. However, challenges remain for the biomedical translation of these and other nanomaterials. A significant task is tuning the surface chemistry to achieve optimal cellular interactions. Herein, we combine real-time fluorescent imaging of nanoparticle cellular uptake and real-time differential interference contrast (DIC) imaging of extracellular media to monitor a) nanoparticle/nanoparticle and b) nanoparticle/cell interactions for CNHs covalently modified with an OFF/ON near-IR dye, the fluorescence of which is switched OFF in extracellular environments and triggered upon cellular internalisation. CHN samples modified with different loadings of the hydrophobic dye are taken as a simple model of drug-loaded nanoparticle systems. The punctate fluorescence suggests the CNHs are delivered to lysosomes and other vesicles of the endocytic pathway. DIC imaging highlights the competition that exists for many particle types, between extracellular aggregation and cellular internalization, the efficiency of which would be dependent upon the amount of fluorophore loading. The results of this study illustrate how complementary real-time imaging methods together with physicochemical characterisation can be used to address the challenges involved in optimising nanoparticle/cell interactions for biomedical applications.
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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".