Rigidity-Dependent Emission: Inspired Selection of an ATP-Specific Polyvalent Hydrogen Binding-Lighted Fluorophore for Intracellular Amplified Imaging
Bibliographic record
Abstract
ATP, a small molecule with high intracellular concentration (mM level), provides a fuel to power signal amplification, which is meaningful for biosensing. However, traditional ATP-powered amplification is based on ATP/aptamer recognition, which is susceptible to the complex biological microenvironment (e.g., nuclease). In this work, we communicate a signaling manner termed as ATP-specific polyvalent hydrogen binding (APHB), which is mimetic to ATP/aptamer binding but can avoid interference from biomolecules. The key in APHB is a functional fluorophore that can selectively bind with ATP via polyvalent hydrogen, and the fluorescence was lighted with the changes of the molecular structure from flexibility to rigidity. By designing, synthesizing, and screening a series of compounds, we successfully obtained an ATP-specific binding-lighted fluorophore (ABF). Experimental verification and a complex analogue demonstrated that two melamine brackets in the ABF dominate the polyvalent hydrogen binding between the ABF and ATP. Then, to achieve amplification biosensing, fibroblast activation protein (FAP) in activated hepatic stellate cells was taken as a model target, and a nanobeacon consisting of an ABF, a quencher, and an FAP-activated polymer shell was constructed. Benefiting from the ATP-powered amplification, the FAP was sensitively detected and imaged, and the potential relationship between differentiation of hepatocytes and FAP concentration was first revealed, highlighting the great potential of APHB-mediated signaling for intracellular sensing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".