Cellular Detection of G‐Quadruplexes by Optical Imaging Methods
Bibliographic record
Abstract
G-quadruplexes (G4s) are higher-order nucleic acid structures that fold from guanine (G)-rich DNA and RNA strands. This field of research gains traction as a major chemical biology area since it aims at uncovering many key cellular mechanisms in which quadruplexes are involved. The wealth of knowledge acquired over the past three decades strongly supports pivotal roles of G4 in the regulation of gene expression at both transcriptional (DNA quadruplexes) and translational levels (RNA quadruplexes). Recent biochemical discoveries uncovered myriad of additional G4 actions: from chromosomal stability to the firing of replication origins, from telomere homeostasis to functional dysregulations underlying genetic diseases (including cancers and neurodegeneration). Here, we listed a repertoire of protocols that we have developed over the past years to visualize quadruplexes in cells. These achievements were made possible thanks to the discovery of a novel family of versatile quadruplex-selective fluorophores, the twice-as-smart quadruplex ligands named TASQ (for template-assembled synthetic G-quartet). The versatility of this probe allows for multiple imaging techniques in both fixed and live cells, including the use of the multiphoton microscopy, confocal microscopy, and real-time fluorescent image collection. © 2017 by John Wiley & Sons, Inc.
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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 | 0.001 | 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) | 0.001 | 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".