Fabrication, Visualization and Analysis of Fluorescein Sodium Encapsulated PLGA@CS Nanoparticles as Model for Photothermomechanical Drug Delivery Using Pulsed 532 nm Laser
Bibliographic record
Abstract
PLGA/CS nanoparticles containing fluorescein sodium as drug model were synthesized and characterized to investigate the feasibility of laser-induced drug delivery using pulse 532 nm. The main objective was to investigate the photothermally-induced mechanical force for transporting the nanoparticles. An argon laser was used to excite the fluorescence of the samples after irradiation. The preliminary results indicated that the drug nanoparticles encapsulated trapped by the cavitation bubbles can be transported by photothermomechanical effect. Different regions of interactions are defined and while in our case, the thermoelastic does not apply due to higher fluences, vaporization and laser-induced thermal breakdown (LITB) including the plasma formation and shock waves played an important and major role. Threshold fluences of 2.8, 18 and 102 Jcm-2 corresponding to 0.28, 1.8 and 10 GWcm-2 and 3.8, 30, and 171 MPa are determined for ablation, vaporization and LITB mechanisms respectively. The secondary microbubbles due to explosion of the primary transient cavitation bubbles played a key role in delivery process. Despite the dominant argon laser brightness, the laser-induced fluorescence spectroscopy (LIFS) demonstrated the fluorescence emission of the cavitation bubbles carrying due to the drug nanoparticles entrapped within the biogelatin after exposure to laser radiation, the irradiation, which confirms the possibility of transport of drug nanoparticles by laser cavitation. Finally, it is suggested that the nature of such photothermal and photo non-thermal mechanical effects is governed and influenced by determining and criticizing in terms of the type of nanomaterial as well as their synthesis process engineering and fabrication as they can be made case sensitive by selecting different types of materials for a specific application.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".