On the carbodiimide conjugation of DNA to mercapto-undecanoic acid-terminated SAMs on gold: an electrochemical and fluorescence imaging study
Bibliographic record
Abstract
Bioconjugation of DNA to alkylthiol self-assembled monolayer (SAM)-modified gold surfaces via carbodiimide chemistry was studied using fluorophore labeled DNA. The extent and distribution of modification of the mercaptoundecanoic acid (MUA) SAM on a single-crystal gold bead electrode was characterized using in situ electrochemical fluorescence imaging. The uniformity of bioconjugation and the influence of the underlying surface crystallography were measured. The conditions for bioconjugation of dilute solution (1 μmol/L) of an amine and fluorophore labelled DNA (NH 2 -DNA-TYE665) to the N-hydroxysuccinimide (NHS)-ester activated MUA SAM were found to be successful using high concentrations of NHS and 1-ethyl-3-(3-dimethylamino propyl carbodiimide). The resulting DNA surface coverage was dependent on the underlying surface crystallography with larger coverages measured from surfaces composed of higher index planes than the atomically smoother low index planes. Some control over the DNA surface coverage was achieved by manipulating the labeling conditions, but reproducible surface modifications were challenging to achieve. The reproducibility of surface modification was shown to be a result of variance in the bioconjugation process rather than the quality of the electrode surfaces used or the initial MUA SAM as determined by capacitance. The presence of nonspecifically adsorbed DNA was observed using fluorescence imaging during electrochemistry, which made quantitative optimization difficult. Average measurements of the interfacial capacitance or the fluorescence intensity did not reveal the presence of this nonideal adsorbed DNA highlighting the need for more comprehensive surface analysis of bioconjugated electrode surfaces when prepared with carboiimide chemistry.
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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".