AI Article Synopsis

  • The COVID-19 pandemic outbreak led to the need for effective detection methods, with RT-PCR being the most common but having limitations like high false negatives.
  • Researchers proposed using Raman spectroscopy combined with machine learning (SVM) to analyze serum samples from COVID-19 patients, suspected cases, and healthy controls for better diagnostic accuracy.
  • The study achieved high classification accuracy rates of 87% and 90% when distinguishing between COVID-19 and suspected cases, as well as between COVID-19 and healthy individuals, suggesting Raman spectroscopy could be a reliable screening method.

Article Abstract

The outbreak of COVID-19 coronavirus disease around the end of 2019 has become a pandemic. The preferred method for COVID-19 detection is the real-time polymerase chain reaction (RT-PCR)-based technique; however, it also has certain limitations, such as sample-dependent procedures with a relatively high false negative ratio. We propose a safe and efficient method for screening COVID-19 based on Raman spectroscopy. A total of 177 serum samples are collected from 63 confirmed COVID-19 patients, 59 suspected cases, and 55 healthy individuals as a control group. Raman spectroscopy is adopted to analyze these samples, and a machine learning support-vector machine (SVM) method is applied to the spectrum dataset to build a diagnostic algorithm. Furthermore, 20 independent individuals, including 5 asymptomatic COVID-19 patients and 5 symptomatic COVID-19 patients, 5 suspected patients, and 5 healthy patients, were sampled for external validation. In these three groups-confirmed COVID-19, suspected, and healthy individuals-the distribution of statistically significant points of difference showed highly consistency for intergroups after repeated sampling processes. The classification accuracy between the COVID-19 cases and the suspected cases is 0.87 (95% confidence interval [CI]: 0.85-0.88), and the accuracy between the COVID-19 and the healthy controls is 0.90 (95% CI: 0.89-0.91), while the accuracy between the suspected cases and the healthy control group is 0.68 (95% CI: 0.67-0.73). For the independent test dataset, we apply the obtained SVM model to the classification of the independent test dataset to have all the results correctly classified. Our model showed that the serum-level classification results were all correct for independent test dataset. Our results suggest that Raman spectroscopy could be a safe and efficient technique for COVID-19 screening.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8014023PMC
http://dx.doi.org/10.1002/jrs.6080DOI Listing

Publication Analysis

Top Keywords

raman spectroscopy
16
covid-19 patients
12
suspected cases
12
independent test
12
test dataset
12
covid-19
11
screening covid-19
8
safe efficient
8
patients suspected
8
cases healthy
8

Similar Publications

An optical biosensor is a specialized analytical device that utilizes the principles of optics and light in bimolecular processes. Localized surface plasmon resonance (LSPR) is a phenomenon in the realm of nanophotonics that occurs when metallic nanoparticles (NPs) or nanostructures interact with incident light. Conversely, surface-enhanced Raman spectroscopy (SERS) is an influential analytical technique based on Raman scattering, wherein it amplifies the Raman signals of molecules when they are situated near specific and specially designed nanostructures.

View Article and Find Full Text PDF

Hematite (α-FeO) nanoparticles have been synthesized from waste source of iron which contains a prominent amount of iron (93.2 %) and investigated the effect of low temperature calcination. The two-step synthesis method involved preparing ferrous sulfate through acid leaching process followed by oxidation and calcination at temperatures ranging from 200 to 400 °C to produce the desired α-FeO in nano form.

View Article and Find Full Text PDF

The van der Waals thiophosphate GaPS presents additional opportunities for gallium-based semiconductors, but limited research on phonon interactions has hindered optimization on thermal properties. This research undertakes a comprehensive investigation into the anharmonic phonon scattering within GaPS. The findings reveal pronounced anharmonic scattering, with both cubic and quartic phonon scatterings significantly influencing phonon redshift and broadening.

View Article and Find Full Text PDF

Green synthesis of low-cost graphene oxide-nano zerovalent iron composite from solid waste for photocatalytic removal of antibiotics.

iScience

December 2024

Enviromicrobiology, Ecotoxicology and Ecotechnology Research Laboratory (3E-MicroToxTech Lab), Department of Ecological Studies, University of Kalyani, Kalyani, Nadia 741235 West Bengal, India.

This study develops a graphene oxide-nano zerovalent iron (GO-nZVI) composite for the efficient removal of tetracycline and ciprofloxacin from water. The composite was synthesized using sugarcane bagasse as the matrix for graphene oxide (GO) and Sal leaf extract to reduce iron into nano zerovalent iron (nZVI). Microscopic analysis confirmed multiple GO layers with nZVI particles on their surface, while XRD and Raman spectroscopy verified the crystalline nature of the composite.

View Article and Find Full Text PDF

Detecting small concentrations of nitro-compounds surface-enhanced Raman spectroscopy (SERS) is reported. In particular, explosive analogues, such as 4-nitrophenol, 1-nitronaphthalene, and 5-nitroisoquinoline, and an explosive material (picric acid) are investigated and prepared by measurements using two different methods. One method involved mixing the analyte with plasmonic silver nanoparticles (Ag NPs) in a solution, followed by subsequent drop-casting of the mixture onto a silicon substrate.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!