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Water quality monitoring requires a rapid and sensitive method that can detect multiple hazardous pollutants at trace levels. This study aims to develop a new generation of biosensors using a low-cost fiber-optic Raman device. An automatic measurement system was thus conceived, built and successfully tested with toxic substances of three different...
Contexts in source publication
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... assignment of Raman bands in the reference bacterial spectrum makes it possible to highlight the bands of molecules that may be impacted by the pollutants ( Figure 4A). ...
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... analysis of the spectral signature of E. coli cells exposed to the different concentrations of norfloxacin shows Raman bands impacted by this toxicant ( Figure 4B). The effects concern the DNA and RNA bands at 785 and 850 cm −1 , the DNA −PO 2 phosphate groups at 1070 and 1150 cm −1 , amides II (band at 1330 cm −1 ), amides I and lipids (band at 1650 cm −1 ). ...
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... differences in the molecular fingerprint of the bacteria result from physiological changes provoked by reactions to the antibiotic. These bands, highlighted in Figure 4B, allow the best discrimination of the spectra according to the different concentrations of antibiotic. ...
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... loadings of the three independent components (ICs) show that the variability in the spectra is a function of antibiotic concentration ( Figure 4D). It can first be seen that the distribution of the spectra according to these components makes it possible to distinguish the different concentration groups (3D representations, Figure 4C). ...
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... loadings of the three independent components (ICs) show that the variability in the spectra is a function of antibiotic concentration ( Figure 4D). It can first be seen that the distribution of the spectra according to these components makes it possible to distinguish the different concentration groups (3D representations, Figure 4C). This selection was made computationally by observing the distribution of spectra for each of the ICs. ...
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... were selected for which the variability of the inter-group spectra (i.e., as a function of concentrations) was the lowest possible, while maximizing the mean difference with the other groups. The variability of the spectra according to these IC components was also analyzed by ANOVA ( Figure 4E). The results show a distribution of groups consistent with a dose-response effect of the substance, which is well underlined by the ANOVA results on the IC6 specific to lipids and amides I (band at 1650-1680 cm −1 ). ...
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... observed variations are related to known mechanisms of the functioning of this antibiotic [51]. The spectra of bacteria exposed to increasing concentrations of norfloxacin show a decrease in the intensity of the bands corresponding to DNA and RNA (Loading IC5, Figure 4D). Norfloxacin belongs to a family of second-generation quinolones and acts, in particular, by inhibiting DNA gyrase and type IV topoisomerases at the DNA segmentation stage. ...
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... factorial discriminant analysis (sFDA) was performed on the scores of independent components from the ICA procedure to assess the level of correct prediction in assigning spectra to a particular group ( Figure 4F). Correct classification percentages for the control and the different norfloxacin concentrations (0.25, 2.5 and 25 mg.L −1 ) were 97, 99, 82 and 93%, respectively. ...
Citations
... A spectrometer is a basic optical detection instrument that can obtain the spectral information of the measured object. At present, various spectrometers have been widely used in color measurement, gas composition analysis, agricultural medicine, food safety and other fields [1][2][3][4][5][6], and have become among the most important optical detection instruments. Among them, the Raman spectrometer [7][8][9], which is composed of a probe and a spectrometer, is a rapidly developed instrument in recent years. ...
Raman spectroscopy, measured by a Raman spectrometer, is usually disturbed by the instrument response function and noise, which leads to certain measurement error and further affects the accuracy of substance identification. In this paper, we propose a spectral reconstruction method which combines the existing maximum a posteriori (MAP) method and deep learning (DL) to recover the degraded Raman spectrum. The proposed method first employs the MAP method to reconstruct the measured Raman spectra, so as to obtain preliminary estimated Raman spectra. Then, a convolutional neural network (CNN) is trained by using the preliminary estimated Raman spectra and the real Raman spectra to learn the mapping from the preliminary estimated Raman spectra to the real Raman spectra, so as to achieve a better spectral reconstruction effect than merely using the MAP method or a CNN. To prove the effectiveness of the proposed spectral reconstruction method, we employed the proposed method and some traditional spectral reconstruction methods to reconstruct the simulated and measured Raman spectra, respectively. The experimental results show that compared with traditional methods, the estimated Raman spectra reconstructed by the proposed method are closer to the real Raman spectra.
... A transducer converts a biochemical signal, resulting from the interaction of a biological component, into a measurable signal. Thus, when the interaction between the analyte and the bioreceptor occurs, a quantifiable signal is generated, which can be optical, electrochemical, thermometric, piezoelectric, magnetic, or micromechanical [4][5][6]. ...
The coronavirus pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has accelerated the development of biosensors based on new materials and techniques. Here, we present our effort to develop a fast and affordable optical biosensor using photoluminescence spectroscopy for anti-SARS-CoV-2 antibody detection. The biosensor was fabricated with a thin layer of the semiconductor polymer Poly[(9,9-di-n-octylfluorenyl-2,7-diyl)-alt-2,2′-bithiophene-5,5′-diyl)] (F8T2) as a signal transducer material. We mounted the biosensors by depositing a layer of F8T2 and an engineered version of RBD from the SARS-CoV-2 spike protein with a tag to promote hydrophobic interaction between the protein and the polymeric surface. We validated the biosensor sensitivity with decreasing anti-RBD polyclonal IgG concentrations and challenged the biosensor specificity with human serum samples from both COVID-19 negative and positive individuals. The antibody binding to the immobilized antigen shifted the F8T2 photoluminescence spectrum even at the low concentration of 0.0125 µg/mL. A volume as small as one drop of serum (100 µL) was sufficient to distinguish a positive from a negative sample without requiring multiple washing steps and secondary antibody reactions.
