Evidence map›Paper›PMID 38637669›Full record

ReviewCommunications chemistry2024

Multi-step FRET systems based on discrete supramolecular assemblies.

Dengli Chen, Tangxin Xiao, Éric Monflier, Leyong Wang

Abstract readReview
In one paragraph

Review in Communications chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Benzoyl-Xanthenoxanthenes: Versatile Chromophores for Light-Engaging Applications.Angewandte Chemie (International ed. in English) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
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.

Dengli ChenSchool of Petrochemical Engineering, Changzhou University, Changzhou, China.
Tangxin XiaoSchool of Petrochemical Engineering, Changzhou University, Changzhou, China. xiaotangxin@cczu.edu.cn.ORCID http://orcid.org/0000-0002-2864-9587
Éric MonflierUnité de Catalyse et Chimie du Solide (UCCS), Faculté des Sciences Jean Perrin, Univ. Artois, CNRS, Centrale Lille, Univ. Lille, UMR 8181, Lens, France. eric.monflier@univ-artois.fr.ORCID http://orcid.org/0000-0001-5865-0979
Leyong WangJiangsu Key Laboratory of Advanced Organic Materials, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China. lywang@nju.edu.cn.ORCID http://orcid.org/0000-0001-5775-3714

Funding

National Natural Science Foundation of China (National Science Foundation of China) 21702020National Natural Science Foundation of China (National Science Foundation of China) 21871136
6 · The paper itself

Abstract

Fluorescence resonance energy transfer (FRET) from the excited state of the donor to the ground state of the acceptor is one of the most important fluorescence mechanisms and has wide applications in light-harvesting systems, light-mediated therapy, bioimaging, optoelectronic devices, and information security fields. The phenomenon of sequential energy transfer in natural photosynthetic systems provides great inspiration for scientists to make full use of light energy. In recent years, discrete supramolecular assemblies (DSAs) have been successively constructed to incorporate donor and multiple acceptors, and to achieve multi-step FRET between them. This perspective describes recent advances in the fabrication and application of DSAs with multi-step FRET. These DSAs are categorized based on the non-covalent scaffolds, such as amphiphilic nanoparticles, host-guest assemblies, metal-coordination scaffolds, and biomolecular scaffolds. This perspective will also outline opportunities and future challenges in this research area.

Identifiers

PMID38637669
PMCPMC11026437

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Registered trials

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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.