Modification of Aβ Peptide Aggregation via Covalent Binding of a Series of Ru(III) Complexes
Bibliographic record
Abstract
Alzheimer’s disease (AD) is the most common form of dementia, leading to loss of cognition and eventually death. The disease is characterized by the formation of extracellular aggregates of the amyloid-beta (A) peptide and neurofibrillary tangles of tau protein inside cells, and oxidative stress. In this study, we investigate a series of Ru(III) complexes (Ru-N) derived from NAMI-A in which the imidazole ligand has been substituted for pyridine derivatives, as potential therapeutics for AD. The ability of the Ru-N series to bind to A was evaluated by NMR and ESI-MS, and their influence on the A peptide aggregation process was investigated via electrophoresis gel/western blot, TEM, turbidity, and Bradford assays. The complexes were shown to bind covalently to the A peptide, likely via a His residue. Upon binding, the complexes promote the formation of soluble high molecular weight aggregates, in comparison to peptide precipitation for peptide alone. In addition, TEM analysis supports both amorphous and fibrillar aggregate morphology for Ru-N treatments, while only large amorphous aggregates are observed for peptide alone. Overall, our results show that the Ru-N complexes modulate A peptide aggregation, however, the change in the size of the pyridine ligand does not substantially alter the A aggregation process.
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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) | 0.000 | 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 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".