Laser-Assisted Surface Modification of Hybrid Hydrogels to Prevent Bacterial Contamination and Protein Fouling
Bibliographic record
Abstract
Silicone hydrogels have been extensively studied in the fields of contact lenses, tissue engineering, and drug delivery due to their good biocompatibility, high oxygen permeability, and proper light transmission. However, their applications in biomedical devices are limited by protein adsorption and bacterial contamination because of the hydrophobic surface of silicone, which will cause more irreversible protein adsorption. Several physical methods can be applied to create a hydrophilic surface on hydrogels, such as spin coating, physical vapor deposition, dip coating, drop casting, etc. Compared to the conventional methods, the matrix assisted pulsed laser evaporation (MAPLE) is suitable to produce biopolymer/polymer film with a contamination-free manner. In this thesis, hydrophilic polymer, polyethylene glycol (PEG) and polyvinylpyrrolidone (PVP), were deposited by MAPLE with a pulsed Nd:YAG 532 nm laser for the surface hydrophilicity modification. The polymer coatings were characterized by Fourier transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM). Our results demonstrate that protein adsorption decreases 28.2% and 18.7% with the surface modifications by PEG and PVP, respectively. In addition, the polymer coated silicone hydrogels do not impose toxic effect on mouse NIH/3T3 cells.\nNormally, protein fouling can lead to biofilm contamination caused by the growth of bacteria. Therefore, we further deposit hybrid nanocomposite on silicone hydrogels to inhibit the growth of bacteria. Silver nanoparticles incorporating with PVP (Ag-PVP NPs) were developed through a photochemical method without addition of reductive reagents. On the other hand, sol-gel method was applied to incorporate ZnO nanoparticles into PEG (ZnO-PEG NPs). MAPLE process was applied to deposit the two different nanocomposites on the silicone hydrogels, respectively. Our results indicate that the silicone hydrogels with Ag-PVP nanocomposite coating can reduce 28.2% of the protein adsorption compared to silicone hydrogels without coating, while ZnO-PEG coating is able to reduce 30% protein adsorption. The cytotoxicity study shows that the nanocomposite coated silicone hydrogels do not impose toxic effect on mouse NIH/3T3 cells. In addition, MAPLE-deposited Ag-PVP and ZnO-PEG nanocomposite coatings can inhibit bacterial growth significantly. Our result show that Ag-PVP nanocomposite coating can eliminate almost all the E.coli after 8 hours’ culturing; the relative numbers of E.coli on the ZnO-PEG coated silicone hydrogel approach to zero when the culturing time is 4 hours. In addition, the thickness and roughness of Ag-PVP film over time were measured by AFM. The result shows that MAPLE process is a time dependent (linear) deposition, and it is able to create homogenous thin films (roughness is lower than 30 nm). MAPLE shows good ability to control the thickness in the deposition of organic molecules and nanoparticles, which maintains the chemical backbone of polymers, and prevents contamination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".