Evidence map›Paper›PMID 29520142›Full record

ArticleInternational journal of nanomedicine2018

Combined use of vancomycin-modified Ag-coated magnetic nanoparticles and secondary enhanced nanoparticles for rapid surface-enhanced Raman scattering detection of bacteria.

Chongwen Wang, Bing Gu, Qiqi Liu, Yuanfeng Pang, Rui Xiao, Shengqi Wang

Abstract read
In one paragraph

Article in International journal of nanomedicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

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  12. New Insight into Assembled FeInternational journal of molecular sciences · 2022
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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

6 authors.

Chongwen Wang *Beijing Key Laboratory of New Molecular Diagnosis Technologies for Infectious Diseases, Beijing Institute of Radiation Medicine, Beijing, People's Republic of China.
Bing Gu *Medical Technology School, Xuzhou Medical University, Xuzhou, People's Republic of China.
Qiqi Liu *Beijing Key Laboratory of New Molecular Diagnosis Technologies for Infectious Diseases, Beijing Institute of Radiation Medicine, Beijing, People's Republic of China.
Yuanfeng PangCollege of Life Sciences and Bio-Engineering, Beijing University of Technology, Beijing, People's Republic of China.
Rui XiaoBeijing Key Laboratory of New Molecular Diagnosis Technologies for Infectious Diseases, Beijing Institute of Radiation Medicine, Beijing, People's Republic of China.
Shengqi WangBeijing Key Laboratory of New Molecular Diagnosis Technologies for Infectious Diseases, Beijing Institute of Radiation Medicine, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPathogenic bacteria have always been a significant threat to human health. The detection of pathogens needs to be rapid, accurate, and convenient.

methodsWe present a sensitive surface-enhanced Raman scattering (SERS) biosensor based on the combination of vancomycin-modified Ag-coated magnetic nanoparticles (Fe

resultsThe dominant merits of our dual enhanced strategy included high bacterial-capture efficiency (>65%) within a wide pH range (pH 3.0-11.0), a short assay time (<30 min), and a low detection limit (5×10

conclusionThis method has great potential for field applications in food safety, environmental monitoring, and infectious disease diagnosis.

Indexed as

BacteriaAnimalsBacteremiaBiosensing TechniquesHumansLimit of DetectionMagneticsMetal NanoparticlesMilkSilverSpectrum Analysis, RamanVancomycinSilverVancomycinAu@Ag nanoparticlesFe3O4@Ag magnetic nanoparticlerapid bacteria detectionsurface-enhanced Raman scatteringvancomycin-modified

Identifiers

PMID29520142
PMCPMC5834169

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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.