N-Heterocyclic Carbene Self-Assembled Monolayers on Gold as Surface Plasmon Resonance Biosensors
Bibliographic record
Abstract
Surface plasmon resonance (SPR)-based biosensing is a powerful tool to study the recognition processes between biomolecules in real-time without need for labels. The use of thiol chemistry is a critical component in surface functionalization of various SPR biosensor surfaces on gold. However, its use is hampered by the high propensity for oxidation of the gold-thiol linkage even in ambient atmosphere, resulting in a short lifetime of SPR sensor chips unless strict precautions are taken. Herein, we describe an approach to overcome this limitation by employing highly robust self-assembled monolayers (SAMs) of alkylated N-heterocyclic carbenes (NHCs) on gold. An alkylated NHC sensor surface was developed and its biosensing capabilities were compared to a commercial thiol-based analogue-a hydrophobic association (HPA) chip-in terms of its ability to act as a reliable platform for biospecific interaction analysis under a wide range of conditions. The NHC-based SPR sensor outperforms related thiol-based sesnsors in several aspects, including lower nonspecific binding capacity, better chemical stability, higher reproducibility, shorter equilibration time, and longer life span. We also demonstrate that the NHC-based sensor can be used for rapid and efficient formation of a hybrid lipid bilayer for use in membrane interaction studies. Overall, this work identifies the great promise in designing NHC-based surfaces as a new technology platform for SPR-based biosensing.
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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".