Direct visualization of carbon nanotube degradation in primary cells by photothermal imaging
Bibliographic record
Abstract
Assessment of biodegradability of carbon nanotubes (CNTs) is a critically important aspect that needs to be solved before their translation into new biomedical tools. CNT biodegradation has been shown both in vitro and in vivo, but we are limited by the number of analytical techniques that can be used to follow the entire process. Photothermal imaging (PhI) is an innovative technique that enables the quantitative detection of nanometer-sized absorptive objects. In this study, we demonstrate that PhI allows the observation of the degradation process of functionalized multi-walled carbon nanotubes (MWCNTs) following their internalization by primary glial cells. The absence of interference from the biological matrix components, together with the possibility to combine PhI with other detection techniques (e.g. fluorescence, light or electron microscopy) validate the potential of this method to follow the fate and behavior of carbon nanostructures in a biological environment.
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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".