Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
Mais filtros

Base de dados
Tipo de documento
Intervalo de ano de publicação
1.
Biosensors (Basel) ; 13(6)2023 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-37366973

RESUMO

The urea breath test is a non-invasive diagnostic method for Helicobacter pylori infections, which relies on the change in the proportion of 13CO2 in exhaled air. Nondispersive infrared sensors are commonly used for the urea breath test in laboratory equipment, but Raman spectroscopy demonstrated potential for more accurate measurements. The accuracy of the Helicobacter pylori detection via the urea breath test using 13CO2 as a biomarker is affected by measurement errors, including equipment error and δ13C measurement uncertainty. We present a Raman scattering-based gas analyzer capable of δ13C measurements in exhaled air. The technical details of the various measurement conditions have been discussed. Standard gas samples were measured. 12CO2 and 13CO2 calibration coefficients were determined. The Raman spectrum of the exhaled air was measured and the δ13C change (in the process of the urea breath test) was calculated. The total error measured was 6% and does not exceed the limit of 10% that was analytically calculated.


Assuntos
Infecções por Helicobacter , Helicobacter pylori , Humanos , Infecções por Helicobacter/diagnóstico , Ureia , Análise Espectral Raman , Dióxido de Carbono , Testes Respiratórios/métodos , Isótopos de Carbono , Sensibilidade e Especificidade
2.
Biosensors (Basel) ; 12(12)2022 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-36551032

RESUMO

We demonstrate the possibility of applying surface-enhanced Raman spectroscopy (SERS) combined with machine learning technology to detect and differentiate influenza type A and B viruses in a buffer environment. The SERS spectra of the influenza viruses do not possess specific peaks that allow for their straight classification and detection. Machine learning technologies (particularly, the support vector machine method) enabled the differentiation of samples containing influenza A and B viruses using SERS with an accuracy of 93% at a concentration of 200 µg/mL. The minimum detectable concentration of the virus in the sample using the proposed approach was ~0.05 µg/mL of protein (according to the Lowry protein assay), and the detection accuracy of a sample with this pathogen concentration was 84%.


Assuntos
Herpesvirus Cercopitecino 1 , Vírus da Influenza A , Influenza Humana , Orthomyxoviridae , Humanos , Análise Espectral Raman/métodos , Influenza Humana/diagnóstico
3.
Opt Lett ; 43(2): 218-221, 2018 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-29328242

RESUMO

We report on an efficient diode-pumped continuous-wave erbium-doped monoclinic double tungstate laser. It is based on a 1 at. % Er3+:KLu(WO4)2 (Er:KLuW) crystal cut along the Ng optical indicatrix axis. The Er:KLuW microchip laser, diode pumped at 0.98 µm, generates 268 mW at 1.610 µm with a slope efficiency of 30%. The output is linearly polarized (E||Nm), and the laser beam is nearly diffraction limited (Mp,m2<1.1). Spectroscopic properties of Er3+ in KLuW are also presented. The stimulated-emission cross-section σSE is 0.46×10-20 cm2 at ∼1.609 µm for E||Nm. The microchip Er:KLuW laser outperforms the commercial Er,Yb:glass.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA