Evidence map›Paper›PMID 42424148›Full record

ArticleAngewandte Chemie (International ed. in English)2026

Subcellular Tandem-Activated Signal Amplification for Spatially Precise Molecular Imaging in Mitochondria.

Xueyan Feng, Deyu Yi, Lele Li, Mengyuan Li

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xueyan FengCollege of Energy Materials and Chemistry, Inner Mongolia University, Hohhot, China.
Deyu YiSchool of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, China.
Lele LiCAS Key Laboratory For Biomedical Effects of Nanomaterials, National Center for Nanoscience and Technology, Beijing, China.ORCID 0000-0001-8593-9292
Mengyuan LiSchool of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, China.ORCID 0000-0002-4664-1845

Funding

National Key Research and Development Program of China 2024YFA1209400National Natural Science Foundation of China 22307027National Natural Science Foundation of China 22388101National Natural Science Foundation of China 22574011
6 · The paper itself

Abstract

Despite significant advances in DNA-based signal amplification strategies for sensitive molecular imaging in live cells, achieving subcellular resolution remains challenging due to limited spatial precision. Here, we present a subcellular tandem-regulated, spatially selective signal amplification technology for molecular imaging in mitochondria. This platform integrates ribosomal RNA (rRNA)-activated target-aptamer recognition with enzyme-mediated cascade signal amplification, enabling in situ imaging of ATP within defined subcellular compartments (e.g., mitochondria) or membraneless regions (e.g., cytosol). The system facilitates in situ monitoring of ATP dynamics during drug intervention with enhanced spatial precision and sensitivity. Furthermore, by re-engineering the cascade-regulated sensor, we extended this approach to enable correlated imaging of mitochondrial ATP and microRNA. This strategy offers a powerful, modular tool for probing energy metabolism and regulatory networks across different subcellular environments.

Indexed as

MitochondriaMolecular ImagingAdenosine TriphosphateAptamers, NucleotideHumansMicroRNAsRNA, RibosomalAdenosine TriphosphateAptamers, NucleotideMicroRNAsRNA, RibosomalATP imagingdrug interventionsribosomal RNAsignal amplificationsubcellular compartment

Identifiers

PMID42424148
PMCPMC13573149

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.