On-Strand Aldehyde Capture by an Indanone Building Block:A Modular Aldol Approach for Fluorescent Molecular RotorNucleobase Surrogates
Bibliographic record
Abstract
Fluorescent molecular rotors (FMRs) are critical tools for monitoring nucleic acid structure and function. Many valuable probes are capable of sitespecific insertion into oligonucleotides, although the methods of doing so can be arduous and lack modularity. Development of modular and more user amenable insertion methods is thus crucial to expand the biotechnological applications of oligonucleotides in what is a rapidly expanding field. Herein we report the utility of 6-hydroxy-indanone (6HI) with a glycol backbone for on-strand aldehyde capture as a modular aldol approach with synthetic ease for site-specific insertion of internal FMRs. The 6HI phosphoramidite is produced in two steps and inserted into DNA using solid-phase synthesis. On-strand aldol with aromatic aldehydes containing N-donors proceeds in quantitative yield via sodium hydroxide to create a highly functional and unique library of FMR chalcones with emissions that span the visible region (em 490- 680 nm). The FMRs provide turn-on fluorescence (Irel, 2-75-fold) upon hybridization with probe brightness up to 15,000 cm-1M-1 . The library also contains FRET pairs and dual emission probes, suitable for ratiometric sensing. The simplicity and functionality of the 6HI building block permits its future wide-spread use in a range of biosensing applications.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".