A Mixed Biosensing Film Composed of Oligonucleotides and Poly (2-hydroxyethyl methacrylate) Brushes to Enhance Selectivity for Detection of Single Nucleotide Polymorphisms
Bibliographic record
Abstract
This work has explored the capability of a mixed film composed of oligonucleotides and oligomers to improve the selectivity for the detection of fully complementary oligonucleotide targets in comparison to partially complementary targets which have one and three base-pair mismatched sites. The intention was to introduce a “matrix isolation” effect on oligonucleotide probe molecules by surrounding the probes with oligomers, thereby reducing oligonucleotide-to-oligonucleotide and/or oligonucleotide-to-surface interactions. This resulted in a more homogeneous environment for probes, thereby minimizing the dispersity of energetics associated with formation of double-stranded hybrids. The mixed film was constructed by immobilizing pre-synthesized oligonucleotides onto a mixed aminosilane layer and then growing the oligomer portion by surface-initiated atom transfer radical polymerization (ATRP) of 2-hydroxy methacrylate (PHEMA). The performance of the mixed film was compared to films composed of only oligonucleotides in a series of hybridization and melt curve experiments. Surface characterization techniques were used to confirm the growth of the oligomer portion as well as the presence of both oligonucleotides and oligomer components. Polyatomic bismuth cluster ions as sources for time-of-flight secondary ion mass spectrometry experiments could detect both components of the mixed film at a high sensitivity even though the oligomer portion was at least 200-fold in excess.\nAt the various ionic strengths investigated, the mixed films were found to increase the selectivity for fully complementary targets over mismatched targets by increasing the sharpness of melt curves and melting temperature differences (delta Tm) by 2- to 3-fold, and by reducing non-specific adsorption. This resulted in improved resolution between the melt curves of fully and partially complementary targets. A fluorescence lifetime investigation of the Cy3 emission demonstrated that Cy3-labeled oligonucleotide probes experienced a more rigid microenvironment in the mixed films.\nThese experiments demonstrated that a mixed film composed of oligonucleotides and PHEMA can be prepared on silica-based substrates, and that they can improve the selectivity for SNP discrimination compared to conventional oligonucleotide films.
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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".