In Vitro Detection of UV‐Induced Damage of the Cornea, Lens and RPE
Bibliographic record
Abstract
Abstract Purpose UV‐A and UV‐B radiation from sunlight is a major source of ocular oxidative damage. This paper describes in vitro methods that can be used to detect ocular damage from UV radiation. Methods Human corneal epithelial cells, lens epithelial cells, and RPE cells were cultured and Ultraviolet A/Ultraviolet B blocking filters and UVB‐only blocking filters were placed between the cells and a UV light source. Cells were irradiated with UV radiations at various energy levels, with and without filters. Cell viability after exposure was determined using the metabolic dye alamarBlue and by evaluating changes in nuclei, mitochondria, membrane permeability, and cell membranes using the fluorescent dyes Hoechst 33342, rhodamine 123, calcein AM, ethidium homodimer‐1, and annexin V. Images of the cells were taken with a Zeiss 510 confocal laser scanning microscope Results The alamarBlue assay results of UV‐exposed cells without filters showed energy level‐dependent decreases in cellular viability. However, UV treated cells with 400 nm LP filter protection showed the equivalent viability to untreated cells at all energy levels. Also, UV irradiated cells with 320 nm LP filter showed lower cell viability than the unexposed control cells, yet higher viability than UV‐exposed cells without filters in an energy level‐dependent manner. The confocal microscopy results also showed that UV radiation can cause significant dose‐dependent degradations of nuclei and mitochondria in ocular cells. The annexin V staining also showed an increased number of apoptotic cells after UV irradiation. Conclusion UV‐induced damage can be evaluated to test the effectiveness of UV‐absorbing contact lenses and intraocular lenses with bioassays that measure change in in vitro cells
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 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 | 0.000 |
| 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) | 0.000 | 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".