Evidence map›Paper›PMID 38131774›Full record

ArticleBiosensors2023

The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis.

Lu Zhou, Ambra Vestri, Valentina Marchesano, Massimo Rippa, Domenico Sagnelli, Gerardo Picazio, Giovanna Fusco, Jiaguang Han, Jun Zhou, Lucia Petti

Abstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
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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

10 authors.

Lu ZhouInstitute of Applied Sciences and Intelligent Systems of CNR, 80072 Pozzuoli, Italy.
Ambra VestriInstitute of Applied Sciences and Intelligent Systems of CNR, 80072 Pozzuoli, Italy.ORCID 0000-0001-9877-7341
Valentina MarchesanoInstitute of Applied Sciences and Intelligent Systems of CNR, 80072 Pozzuoli, Italy.
Massimo RippaInstitute of Applied Sciences and Intelligent Systems of CNR, 80072 Pozzuoli, Italy.ORCID 0000-0002-1993-4589
Domenico SagnelliInstitute of Applied Sciences and Intelligent Systems of CNR, 80072 Pozzuoli, Italy.
Gerardo PicazioIstituto Zooprofilattico Sperimentale del Mezzogiorno, 80055 Portici, Italy.ORCID 0000-0002-0671-7091
Giovanna FuscoIstituto Zooprofilattico Sperimentale del Mezzogiorno, 80055 Portici, Italy.ORCID 0000-0003-3139-7672
Jiaguang HanCenter for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China.
Jun ZhouDepartment of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, Ningbo 315211, China.
Lucia PettiInstitute of Applied Sciences and Intelligent Systems of CNR, 80072 Pozzuoli, Italy.

Funding

Regione Campania funding the project "SERSCov-Advanced Nanobiosensing platforms for diagnostics and POC surveillance" funded by POR Campania FESR 2014/2020 CUP B53C22003100002
6 · The paper itself

Abstract

The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic stability. Consequently, the development of a convenient, reliable and affordable approach for detecting and identifying SARS-CoV-2 and its emerging new variants is crucial. The fingerprint and signal amplification characteristics of surface-enhanced Raman spectroscopy (SERS) could serve as an assay scheme for SARS-CoV-2. Here, we report a machine learning-based label-free SERS technique for the rapid and accurate detection and identification of SARS-CoV-2. The SERS spectra collected from samples of four types of coronaviruses on gold nanoparticles film, fabricated using a Langmuir-Blodgett self-assembly, can provide more spectroscopic signatures of the viruses and exhibit low limits of detection (<100 TCID

Indexed as

COVID-19Metal NanoparticlesGoldHumansPrincipal Component AnalysisSARS-CoV-2Spectrum Analysis, RamanGoldprincipal component analysisSARS-CoV-2surface-enhanced Raman scattering

Identifiers

PMID38131774
PMCPMC10741931

What OpenQuestion holds

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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.