Highly sensitive protein detection via covalently linked aptamer to MoS<sub>2</sub> and exonuclease-assisted amplification strategy
Bibliographic record
Abstract
Abstract: Molybdenum disulfide (MoS 2 ) has shown highly attractive superiority as a platform for sensing. However, DNA physisorption on the surface of MoS 2 was susceptible to nonspecific probe displacement and false-positive signals. To solve these problems, we have developed a novel MoS 2 –aptamer nanosheet biosensor for detecting thrombin using a covalently linked aptamer to the MoS 2 nanosheet. Ten percent Tween 80 was used to prevent thrombin from nonspecific binding and to rapidly form thiol-DNA/gold nanoparticle (AuNP) conjugates. Furthermore, an MoS 2 and exonuclease coassisted signal amplification strategy was developed to improve the detection limit for thrombin. We used the hybridization of the aptamer molecules and the matched strand with a 5' terminal thiol to immobilize the aptamer molecules on the surface of AuNPs in [email protected] 2 nanocomposites. Exonuclease digested the single-strand aptamer and released the thrombin, which was then detected in the next recycle. With the coassisted amplification strategy, a 6 fM detection limit was achieved, showing that this method has higher sensitivity than most reported methods for thrombin detection. The results presented in this work show that this method of covalently attaching the aptamer and using the coassisted amplification is a promising technique for the detection of protein in medical diagnostics. Keywords: Molybdenum disulfide, aptamer, thrombin, protein detection, high sensitivity
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".