Evidence map›Paper›PMID 34677326›Full record

ArticleBiosensors2021

Sub-Part-Per-Billion Level Sensing of Fentanyl Residues from Wastewater Using Portable Surface-Enhanced Raman Scattering Sensing.

Boxin Zhang, Xingwei Hou, Cheng Zhen, Alan X Wang

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

14 citing papers in PubMed, 29 citations in OpenAlex.

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  12. Interpol Review of Drug Analysis 2019-2022.Forensic science international. Synergy · 2023
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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

4 authors at 1 institution in 1 country.

Boxin ZhangSchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA.
Xingwei HouSchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA.
Cheng ZhenSchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA.
Alan X WangSchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA.
Oregon State University · US

Funding

National Institutes of Health 1R21DA0437131National Institutes of Health 1R41DA051094-01U.S. Department of Agriculture 2017-67021-26606U.S. Department of Agriculture 2020-33610-31688
6 · The paper itself

Abstract

Detection of illicit drug residues from wastewater provides a new route toward community-level assessment of drug abuse that is critical to public health. However, traditional chemistry analytical tools such as high-performance liquid chromatography in tandem with mass spectrometry (HPLC-MS) cannot meet the large-scale testing requirement in terms of cost, promptness, and convenience of use. In this article, we demonstrated ultra-sensitive and portable surface-enhanced Raman scattering sensing (SERS) of fentanyl, a synthetic opioid, from sewage water and achieved quantitative analysis through principal component analysis and partial least-squares regression. The SERS substrates adopted in this application were synthesized by in situ growth of silver nanoparticles on diatomaceous earth films, which show ultra-high sensitivity down to 10 parts per trillion in artificially contaminated tap water in the lab using a commercial portable Raman spectrometer. Based on training data from artificially contaminated tap water, we predicted the fentanyl concentration in the sewage water from a wastewater treatment plant to be 0.8 parts per billion (ppb). As a comparison, the HPLC-MS confirmed the fentanyl concentration was below 1 ppb but failed to provide a specific value of the concentration since the concentration was too low. In addition, we further proved the validity of our SERS sensing technique by comparing SERS results from multiple sewage water treatment plants, and the results are consistent with the public health data from our local health authority. Such SERS sensing technique with ultra-high sensitivity down to sub-ppb level proved its feasibility for point-of-care detection of illicit drugs from sewage water, which is crucial to assess public health.

Indexed as

FentanylMetal NanoparticlesLimit of DetectionSewageSilverSpectrum Analysis, RamanWastewaterFentanylSewageSilverWastewaterfentanylplasmonic nanoparticlespoint of carepublic healthsurface-enhanced Raman scattering

Identifiers

PMID34677326
PMCPMC8534101
OpenAlexW3206926536

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.