Intracellular Detection of ATP Using an Aptamer Beacon Covalently Linked to Graphene Oxide Resisting Nonspecific Probe Displacement
Bibliographic record
Abstract
Fluorescent aptamer probes physisorbed on graphene oxide (GO) have recently emerged as a useful sensing platform. A signal is generated by analyte-induced probe desorption. To address nonspecific probe displacement and the false positive signal, we herein report a covalently linked aptamer probe for adenosine triphosphate (ATP) detection. A fluorophore and amino dual modified aptamer was linked to the carboxyl group on GO with a coupling efficiency of ∼50%. The linearity, specificity, stability, and regeneration of the covalent sensor were systematically studied and compared to the physisorbed probe. Both sensors have similar sensitivity, but the covalent one is more resistant to nonspecific probe displacement by proteins. The covalent sensor has a dynamic range from 0.125 to 2 mM ATP in buffer at room temperature and is resistance to DNase I. Intracellular ATP imaging was demonstrated using the covalent sensor, which generated a higher fluorescence signal than the physisorbed sensor. After the cells were stimulated with 5 mM Ca(2+) for ATP production, the intracellular signal enhanced by 31.8%. This work highlights the advantages of covalent aptamer sensors using GO as both a quencher and a delivery vehicle for intracellular metabolite detection.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".