Effects of Oligonucleotide Immobilization Density on Selectivity of Quantitative Transduction of Hybridization of Immobilized DNA
Bibliographic record
Abstract
Immobilized single-stranded DNA (ssDNA) can be used as a selective “reagent” to bind complementary nucleic acids for applications including detection of pathogenic organisms and genetic mutations. The density of ssDNA on a surface will determine nearest neighbor interactions, surface interactions, and charge density due to ionizable phosphate groups. This may result in a local ionic strength, pH, and dielectric constant at the surface that is substantially different from that in bulk electrolyte solution. It is the local conditions that influence the thermodynamics of hybridization, and this can be studied by the melt temperature ( T m ) of double-stranded DNA (dsDNA). Organosilane chemistry has been used to covalently immobilize hexaethylene glycol linkers and to control the subsequent density of dT 20 that was prepared by automated synthesis. Fiber-optic biosensors based on fused silica optical fibers that were coated with DNA were used in a total internal reflection fluorescence instrument to determine T m from the dissociation of duplexes of mixtures of fluorescein-labeled and unlabeled dA 20 and d(A 9 GA 10 ). Each thermal denaturation of dsDNA at the surface of the optical fibers was accompanied by a 2−3-fold reduction in standard enthalpy change, relative to values determined for denaturation in bulk solution. The experimental results suggest that the thermodynamic stability of duplexes that are immobilized on a surface is dependent on the density of immobilized DNA. Additionally, the deviation in T m arising as a result of the presence of a centrally located single base-pair mismatch was significantly larger for thermal denaturation occurring at the surface of the optical fibers (Δ T m = 6−10 °C) relative to that observed in bulk solution (Δ T m = 3.8−6.1 °C). These results suggest that hybridization at an interface occurs in a significantly different physical environment in comparison to hybridization in bulk solution, and that surface density can be tuned to design analytical figures of merit.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".