Evidence map›Paper›PMID 39727228›Full record

ReviewChemistryOpen2025

Innovative Progress of LSPR-Based Dark-Field Scattering Spectral Imaging in the Biomedical Assay at the Single-Particle Level.

Yang Shi, Lixiang Wang, Lingling Li, Chen Feng, Yue Cao

Abstract readReview
In one paragraph

Review in ChemistryOpen, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

5 authors.

Yang ShiDepartment of Forensic Medicine, Nanjing Medical University, Nanjing, 211166, PR China.
Lixiang WangDepartment of Forensic Medicine, Nanjing Medical University, Nanjing, 211166, PR China.
Lingling LiSchool of Pharmacy, Nanjing Medical University, Nanjing, 211166, PR China.
Chen FengDepartment of Forensic Medicine, Nanjing Medical University, Nanjing, 211166, PR China.
Yue CaoDepartment of Forensic Medicine, Nanjing Medical University, Nanjing, 211166, PR China.ORCID 0000-0002-0681-0069

Funding

2022 Chunhui Program of Ministry of Education HZKY20220178Nanjing Medical University NMUR2019007National Natural Science Foundation of China 21904068, 21906019, and 81922041Science and Technology Support Program of Jiangsu Province China BK20201351
6 · The paper itself

Abstract

The growing demand for detection and sensing in the biomedical field is placing higher demands on technology. In clinical testing, it is expected to be able to realize both rapid large-field imaging and analysis of single particles (or single molecules or single cells), and it is expected to be able to grasp both the unique individuality of single particles in time and space during the complex reaction process, as well as the regular correlation between single particles in the same population distribution. Supported and promoted by the theory of localized surface plasmon resonance (LSPR), dark-field microscopy, as a single-particle optical imaging technique with a very high signal-to-noise ratio, provides a powerful new means to address the above clinical detection needs. This review will focus on the innovative applications of dark-field microscopy in biomedical-related assays in the past five years, introducing the basic principles and listing the impressing works. We also summarize how dark-field microscopy has been combined with other techniques, including surface-enhanced Raman scattering, fluorescence, colorimetry, electrochemistry, etc., to witness the joint progress and promotion of detection methods in the future. It also provides an outlook on the current challenges and future trends in this field.

Indexed as

Optical ImagingSurface Plasmon ResonanceHumansMicroscopySpectrum Analysis, RamanBioassayDark-field microscopyLocalized surface plasmon resonanceScattering imagingSingle particle

Identifiers

PMID39727228
PMCPMC11891451

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.