Gold Nanorods Decorated by Conjugated Microporous Polymers for Infrared Responsive Cytostatic Drug Delivery
Bibliographic record
Abstract
Near-infrared (NIR) controlled drug delivery systems have drawn a lot of attention throughout the past few decades due to the deep penetration depth and comparatively minor side effects of the stimulus. In this study, we introduce an innovative approach for gastric cancer treatment by combining photothermal infrared-sensitive gold nanorods (AuNRs) with a conjugated microporous polymer (CMP) to create a drug delivery system tailored for transporting the cytostatic drug 5-fluorouracil (5-FU). CMPs are fully conjugated networks with high internal surface areas that can be precisely tailored to the adsorption and transport of active compounds through the right choice of chemical functionalities. By incorporation of surfactant-stabilized AuNRs into the CMP synthesis in dimethylformamide (DMF) the surfactant shell is destabilized and subsequently replaced by the CMP. Particularly, low initial surfactant concentrations led to uniform distribution of the AuNRs in the polymer matrix. Importantly, the integrated AuNRs maintain their plasmonic properties, as was confirmed via electron energy loss spectroscopy. Therefore, the significant photothermal properties are translated to the hybrid material as shown in a proof-of-principle experiment. Further, in an approximated gastric environment, 5-FU release studies were conducted with and without NIR stimulus. Thereby it was observed that increased Brownian motion due to the NIR irradiation not only accelerates the release but also increases the total released amount by influencing the adsorption-desorption equilibrium. This remarkable level of control of the release process underlines the immense potential of this hybrid material for precise and targeted drug delivery.
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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".