LED-based interferometric reflectance imaging sensor for the detection of amyloid-β aggregation
Bibliographic record
Abstract
Self-aggregation of amyloid-β (Aβ) plays an important role in the pathogenesis of Alzheimer's disease (AD). Small molecule inhibitors of Aβ fibril formation reduce the Aβ-mediated neurotocixity. In this report, the interaction of amyloid-β (Aβ) with well-described modulators, (-)epigallocatechin-3-gallate (EGCG) and Zn(ii), was detected using a LED-based interferometric reflectance imaging sensor (LED-IRIS) in a high-throughput and real-time format. Nucleation-based fibril growth strategy was employed, as the "seeds" of Aβ were prepared in the presence of EGCG and Zn(ii). The seeds were then covalently immobilized on the chip surface. Using microfluidics, Aβ oligomers were exposed onto the seeds resulting in the elongation of fibrils, which was detected as the increase in the spot height. Monitoring the changes on the chip surface enabled to detect the efficacy of modulators to inhibit or facilitate the growth of Aβ fibrils. The proof-of-concept study reported here introduces a novel platform to facilitate the screening of small molecules towards the discovery of promising AD therapeutics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".