UV-B induced fibrillization of crystallin protein mixtures
Bibliographic record
Abstract
Environmental factors, mainly oxidative stress and exposure to sunlight, induce the oxidation, cross-linking, cleavage, and deamination of crystallin proteins, resulting in their aggregation and, ultimately, cataract formation. Various denaturants have been used to initiate the aggregation of crystallin proteins in vitro. All of these regimens, however, are obviously far from replicating conditions that exist in vivo that lead to cataract formation. In fact, it is our supposition that only UV-B radiation may mimic the observed in vivo cause of crystallin alteration leading to cataract formation. This means of inducing cataract formation may provide the most appropriate in vitro platform for in-depth study of the fundamental cataractous fibril properties and allow for testing of possible treatment strategies. Herein, we showed that cataractous fibrils can be formed using UV-B radiation from α:β:γ crystallin protein mixtures. Characterization of the properties of formed aggregates confirmed the development of amyloid-like fibrils, which are in cross-β-pattern and possibly in anti-parallel β-sheet arrangement. Furthermore, we were also able to confirm that the presence of the molecular chaperone, α-crystallin, was able to inhibit fibril formation, as observed for 'naturally' occurring fibrils. Finally, the time-dependent fibrillation profile was found to be similar to the gradual formation of age-related nuclear cataracts. This data provided evidence for the initiation of fibril formation from physiologically relevant crystallin mixtures using UV-B radiation, and that the formed fibrils had several traits similar to that expected from cataracts developing in vivo.
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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".