Graphene oxide nanosheets enhancing the photothermal response of a cellular barrier exposed to near infrared light
Bibliographic record
Abstract
Abstract Recent developments in targeted photothermal therapy focus on integrating near‐infrared (NIR) light and biocompatible nanostructures. It is yet unclear if graphene oxide nanosheets (GO) can assist in the photothermal response of cellular barriers under NIR irradiation. Herein, this study investigates the photothermal response of a cellular barrier treated with different concentrations of GO under the irradiation of NIR light. The synthesized GO nanosheets show good stability in aqueous media. No toxic effects are imposed onto human umbilical vein endothelial cells (HUVECs) when the cells are treated with GO up to 20 μg/mL for 1 day. In addition, the in vitro cellular barrier model with intercellular tight junctions is formed by using HUVECs, which have a high transepithelial electrical resistance (TEER) value of 89.3 Ω · cm2. Under the irradiation of NIR light (980 nm), the photothermal response on the cellular barrier is enhanced by introducing GO, which has been verified by the decrease of TEER value and the increase in the transport of dextran. The results indicate that the thermal response of a cellular barrier exposed to NIR light is non‐linearly enhanced with increasing concentration of GO.
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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) | 0.001 | 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 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".