Phenotypic and transcriptional changes in lens epithelial cells following acute and fractionated ionizing radiation exposure
Bibliographic record
Abstract
PURPOSE: Exposure to ionizing radiation is one of the known risk factors for the development of lens opacities. It is believed that radiation interactions with lens epithelial cells (LEC) are the underlying cause of cataract development, however, the exact mechanisms have yet to be identified. The aim of this study was to investigate how different radiation dose and fractionation impact normal LEC function. MATERIALS AND METHODS: A human derived LEC cell line (HLE-B3) was exposed to a single acute x-ray dose (0.25 Gy) and 6 fractionated doses (total dose of 0.05, 0.1, 0.25, 0.5, 1, and 2 Gy divided over 5 equal fractions). LEC were examined for proliferation using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and migration using a Boyden chamber assay at various time points (0.25, 0.5, 1, 2, 4, 7, 9, 11, and 14 d) post-irradiation. Transcriptomic analysis through RNA sequencing was also performed to identify differentially expressed genes and regulatory networks in cells following 4 different acute exposures and 1 fractionated exposure. RESULTS: Exposure to an acute dose of 0.25 Gy significantly increased proliferation and migration rates, peaking at 7 d post irradiation (20% and 240% greater than controls, respectively), before returning to baseline levels by day 14. Fractionated exposures had minimal effects up to a dose of 0.5 Gy, but significantly reduced proliferation and migration after 1 and 2 Gy by up to 50%. The largest transcriptional response occurred 12 h after an acute 0.25 Gy dose, with 362 genes up-regulated and 288 genes down-regulated. A unique panel of differentially expressed genes was observed between moderate versus high dose exposures, suggesting a dose-dependent transcriptional response in LEC that is more pronounced at lower doses. Gene ontology and upstream regulator analysis identified multiple biological processes and molecular functions implicated in the radiation response, in particular differentiation, motility, receptor/ligand binding, cell signaling and epithelial-mesenchymal cell transition. CONCLUSIONS: Overall, this research provides novel insights into the dose and fractionation effects on functional changes and transcriptional regulatory networks in LEC, furthering our understanding of the mechanisms behind radiation induced cataracts.
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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".