Screening π-Extended Ruthenium(II) Complexes for the Photoinduced Oxidative Modulation of Amyloid-β Peptide Aggregation
Bibliographic record
Abstract
Controlling the aggregation of amyloid-β (Aβ) peptides offers a promising strategy to mitigate Alzheimer’s disease (AD). Herein, we introduce a series of photoactivatable Ru(II) complexes ( Ru1–8 ) designed to efficiently generate singlet oxygen ( 1 O 2 ) and subsequently oxidatively modify the Aβ peptide. Upon light activation, these complexes rapidly direct Aβ 1–42 aggregation toward high molecular weight amorphous species, with Ru1 demonstrating the most pronounced effect. Transmission electron microscopy (TEM) revealed that the amorphous aggregates formed immediately and persist over time. Complementary assays, including bicinchoninic acid (BCA) quantification and Western blotting, demonstrated rapid photoinduced aggregation and a decrease of soluble peptide upon photoactivation, while proteinase-K digestion showed that the resulting amorphous species are more susceptible to proteolysis in comparison to canonical fibrils. Control experiments under anaerobic conditions and in the presence of an 1 O 2 scavenger suggest that these effects are oxygen-dependent. Notably, photoactivation of Ru1 in the presence of preformed fibrils results in a morphology change to degradable amorphous aggregates, providing both preventive and disruptive activity. Together, these findings establish photoactivatable Ru1 as a light-controlled chemical tool capable of redirecting Aβ aggregation, enhancing aggregate protease degradation, and offering a versatile platform for therapeutic exploration.
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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".