Spectral photokinetic conversion of the fluorescent probes BSB and K114 for improved detection of amyloid assemblies
Bibliographic record
Abstract
Cross-β-sheet-rich protein fibrils are infamous for their accumulation in the brains of patients diagnosed with a number of neurodegenerative diseases, including Alzheimer's disease (AD). Disease-relevant fibrils are a result of deviation of the proteins from their native structure to a misfolded state resulting in aggregation and formation of fibrils. In this study, we explored the phenomenon of light-induced fluorescence enhancement of amyloid assemblies stained with two amyloid probes (BSB and K114) using Bombyx mori silk and human AD brain sections. The photoconversion effect, accompanied by an increase in fluorescence intensity and spectral blue-shift, was highly dependent on the chemical structures of the dyes, pH, presence of glycerol and the type of amyloid. The degree of intensity and spectral change over time in response to high laser exposure were quantified and analyzed using custom-written analysis tools. Our findings provide further insight into possible mechanisms of amyloid-mediated photoconversion kinetics of K114 and BSB, and may provide more insight into the molecular nature of various amyloid assemblies.
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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".