Simple, rapid and sensitive detection of Parkinson's disease related alpha-synuclein using a DNA aptamer assisted liquid crystal biosensor
Why this work is in the frame
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Bibliographic record
Abstract
Alpha-synuclein (αS) has been proposed as a potential biomarker for the diagnosis of Parkinson's disease (PD). However, the detection of αS using a simple, rapid and sensitive approach is still challenging. Herein, we construct a new type of biosensor for the detection of αS, combining the stimuli-responsiveness of liquid crystals (LCs) and the specific interaction of a DNA aptamer with proteins. In principle, the positively charged surfactant hexadecyltrimethylammonium bromide (CTAB) binds with the negatively charged DNA aptamer via electrostatic interactions; in the presence of αS, the DNA aptamer specifically binds with αS and releases CTAB, which is an amphiphilic molecule and subsequently assembles at the LC-aqueous interface, resulting in a homeotropic alignment of LCs with a dark optical signal. In the absence of αS, CTAB binds with the DNA aptamer without affecting the alignment of LCs, which shows planar anchoring with a bright optical signal. The response time of LCs towards αS is rapid and can be down to minutes. The LC biosensor established here has a good specificity for αS and can recognize αS even from a mixture of proteins. The LC biosensor also exhibits high sensitivity with a limit of detection of αS as low as 10 pM, which is comparable to that of the enzyme-linked immunosorbent assay. This work provides a new strategy for the detection of αS in a simple, rapid and sensitive manner, possessing promising potentials towards early diagnosis and clinical applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it