Tip-enhanced Raman spectroscopy: plasmid-free vs. plasmid-embedded DNA
Bibliographic record
Abstract
Tip-enhanced Raman spectroscopy (TERS) provides greatly enhanced Raman signals along with ultra-high lateral spatial resolutions and has been demonstrated to be a technique of choice to study a variety of biochemical specimens such as DNA and RNA at the single chain level. However, the sensitivity of TERS to demonstrate the influence of the nanoscale environment on DNA properties has not been investigated. Herein, we used a gap-mode TERS as an ultra-sensitive label-free technique to investigate the influence of the local plasmid on the DNA properties of a β2-adrenergic receptor (β2AR). Remarkable lateral spatial resolutions down to 8 nm were also acquired for the collected Raman signals under ambient conditions. This approach offers not only a tool to examine the influence of the local nanoscale environment surrounding the DNA structure, but also the localization of the majority of nucleic acid base(s) present in selected regions on the DNA strand.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".