Evidence map›Paper›PMID 39474142›Full record

ArticleEnvironment & health (Washington, D.C.)2024

Efficient V-Shaped Substrate for Surface and Volume Enhanced Raman Spectroscopic Analysis of Bioaerosol: Prevention from Potential Health Risk.

Juan Liu, Yangyang Liu, Yunyun Zhang, Xuejun Ruan, Hanyun Cheng, Qiuyue Ge, Liwu Zhang

Abstract read
In one paragraph

Article in Environment & health (Washington, D.C.), 2024. 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. Article
  2. Article
  3. Silver Nanoparticle-Induced Nephrotoxicity in Zebrafish (International journal of molecular sciences · 2025
    Article
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

7 authors.

Juan LiuShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China.
Yangyang LiuShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China.
Yunyun ZhangForiin Technology (Shanghai) Co., Ltd., Shanghai 200433, China.
Xuejun RuanShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China.
Hanyun ChengShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China.
Qiuyue GeShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China.
Liwu ZhangShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China.ORCID https://orcid.org/0000-0002-0765-8660

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bioaerosols pose a great threat to human life and health, and developing highly efficient and accurate identification and analysis methodologies for bioaerosols provides prerequisite knowledge to evaluate their toxicity on human health. In this paper, a rapid and economical method is proposed for the detection of bioaerosols based on surface-enhanced Raman scattering (SERS). The SERS substrate was prepared using an anodic aluminum oxide (AAO) template with an inverted conical (V-shaped) nanopore array structure that was subsequently deposited with Ag nanoparticles (AgNPs) through magnetron sputtering. This tailored nanostructure essentially enables the differentiated and efficient detection of

Identifiers

PMID39474142
PMCPMC11504271

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.