Compressive behaviour of soft contact lenses and its effect on refractive power on the eye and handling off the eye

Eumelanin-Enhanced Photothermal Disinfection of Contact Lenses Using a Sustainable Marine Nanoplatform Engineered with Electrospun Nanofibers

Bacterial keratitis (BK) is a severe eye infection commonly associated with Staphylococcus aureus (S. aureus), posing a significant risk to vision, especially among contact lens wearers. This research introduces a novel smart nanoplatform (deMS@cNF), developed from demineralized mussel shells (deMS) and reinforced with chitin (CT) nanofibrils, specifically designed for portable photothermal disinfection of contact lenses. The nanoplatform leverages the photothermal properties of eumelanin in mussel shells (MS), which, when activated by a simple bike flashlight, rapidly heats to temperatures up to 95 °C, effectively destroying bacterial contamination. In vitro tests demonstrate that the nanoplatform is biocompatible and non-toxic, making it suitable for medical applications. This study highlights an innovative approach to converting marine biowaste into a safe, effective, and low-cost portable method for disinfecting contact lenses, showcasing the potential of the deMS@cNF platform for broader antimicrobial applications.

Influence of High Strain Dynamic Loading on HEMA-DMAEMA Hydrogel Storage Modulus and Time Dependence

Hydrogels have been extensively studied for biomedical applications such as drug delivery, tissue-engineered scaffolds, and biosensors. There is a gap in the literature pertaining to the mechanical properties of hydrogel materials subjected to high-strain dynamic-loading conditions even though empirical data of this type are needed to advance the design of innovative biomedical designs and inform numerical models. For this work, HEMA-DMAEMA hydrogels are fabricated using a photopolymerization approach. Hydrogels are subjected to high-compression oscillatory dynamic mechanical loading at strain rates equal to 50%, 60%, and 70%, and storage and loss moduli are observed over time, e.g., 72 h and 5, 10, and 15 days. As expected, the increased strains resulted in lower storage and loss moduli, which could be attributed to a breakdown in the hydrogel network attributed to several mechanisms, e.g., increased network disruption, chain scission or slippage, and partial plastic deformation. This study helps to advance our understanding of hydrogels subjected to high strain rates to understand their viscoelastic behavior, i.e., strain rate sensitivity, energy dissipation mechanisms, and deformation kinetics, which are needed for the accurate modeling and prediction of hydrogel behavior in real-world applications.

FEA-Based Stress-Strain Barometers as Forecasters for Corneal Refractive Power Change in Orthokeratology

PURPOSE

To improve the effectivity of patient-specific finite element analysis (FEA) to predict refractive power change (RPC) in rigid Ortho-K contact lens fitting. Novel eyelid boundary detection is introduced to the FEA model to better model the effects of the lid on lens performance, and stress and strain outcomes are investigated to identify the most effective FEA components to use in modelling.

METHODS

The current study utilises fully anonymised records of 249 eyes, 132 right eyes, and 117 left eyes from subjects aged 14.1 ± 4.0 years on average (range 9 to 38 years), which were selected for secondary analysis processing. A set of custom-built MATLAB codes was built to automate the process from reading Medmont E300 height and distance files to processing and displaying FEA stress and strain outcomes. Measurements from before and after contact lens wear were handled to obtain the corneal surface change in shape and power. Tangential refractive power maps were constructed from which changes in refractive power pre- and post-Ortho-K wear were determined as the refractive power change (RPC). A total of 249 patient-specific FEA with innovative eyelid boundary detection and 3D construction analyses were automatically built and run for every anterior eye and lens combination while the lens was located in its clinically detected position. Maps of four stress components: contact pressure, Mises stress, pressure, and maximum principal stress were created in addition to maximum principal logarithmic strain maps. Stress and strain components were compared to the clinical RPC maps using the two-dimensional (2D) normalised cross-correlation and structural similarity (SSIM) index measure.

RESULTS

On the one hand, the maximum principal logarithmic strain recorded the highest moderate 2D cross-correlation area of 8.6 ± 10.3%, and contact pressure recorded the lowest area of 6.6 ± 9%. Mises stress recorded the second highest moderate 2D cross-correlation area with 8.3 ± 10.4%. On the other hand, when the SSIM index was used to compare the areas that were most similar to the clinical RPC, maximum principal stress was the most similar, with an average strong similarity percentage area of 26.5 ± 3.3%, and contact pressure was the least strong similarity area of 10.3 ± 7.3%. Regarding the moderate similarity areas, all components were recorded at around 34.4% similarity area except the contact pressure, which was down to 32.7 ± 5.8%.

CONCLUSIONS

FEA is an increasingly effective tool in being able to predict the refractive outcome of Ortho-K treatment. Its accuracy depends on identifying which clinical and modelling metrics contribute to the most accurate prediction of RPC with minimal ocular complications. In terms of clinical metrics, age, Intra-ocular pressure (IOP), central corneal thickness (CCT), surface topography, lens decentration and the 3D eyelid effect are all important for effective modelling. In terms of FEA components, maximum principal stress was found to be the best FEA barometer that can be used to predict the performance of Ortho-K lenses. In contrast, contact pressure provided the worst stress performance. In terms of strain, the maximum principal logarithmic strain was an effective strain barometer.