scholarly journals Near-Infrared Spectroscopy Evaluations for the Differentiation of Carbapenem-Resistant from Susceptible Enterobacteriaceae Strains

Diagnostics ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 736
Author(s):  
Bushra Alharbi ◽  
Maggy Sikulu-Lord ◽  
Anton Lord ◽  
Hosam M. Zowawi ◽  
Ella Trembizki
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Accuracy ◽  
Bacterial Species ◽  
Carbapenem Resistance ◽  
Accurate Identification ◽  
E Coli ◽  
Carbapenem Resistant ◽  
Global Threat

Antimicrobial Resistance (AMR) caused by Carbapenem-Resistant Enterobacteriaceae (CRE) is a global threat. Accurate identification of these bacterial species with associated AMR is critical for their management. While highly accurate methods to detect CRE are available, they are costly, timely and require expert skills, making their application infeasible in low-resource settings. Here, we investigated the potential of Near-Infrared Spectroscopy (NIRS) for a range of applications: (i) the detection and differentiation of isolates of two pathogenic Enterobacteriaceae species, Klebsiella pneumoniae and Escherichia coli, and (ii) the differentiation of carbapenem resistant and susceptible K. pneumoniae. NIRS has successfully differentiated between K. pneumoniae and E. coli isolates with a predictive accuracy of 89.04% (95% CI; 88.7–89.4%). K. pneumoniae isolates harbouring carbapenem-resistance determinants were differentiated from susceptible K. pneumoniae strains with an accuracy of 85% (95% CI; 84.2–86.1%). To our knowledge, this is the largest proof of concept demonstration for the utility and feasibility of NIRS to rapidly differentiate between K. pneumoniae and E. coli as well as carbapenem-resistant K. pneumoniae from susceptible strains.

scholarly journals Near-infrared Spectroscopy evaluations for rapid differentiation of carbapenem resistant Enterobacteriaceae from susceptible strains

2020 ◽  
Author(s):  
Bushra Alharbi ◽  
Maggy T. Sikulu-Lord ◽  
Anton Lord ◽  
Hosam M Zowawi ◽  
Ella Trembizki
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Accuracy ◽  
Bacterial Species ◽  
Carbapenem Resistance ◽  
Accurate Identification ◽  
Carbapenem Resistant ◽  
Global Threat ◽  
Carbapenem Resistant Enterobacteriaceae

AbstractAntimicrobial resistance (AMR) caused by Carbapenem-Resistant Enterobacteriaceae (CRE) is a global threat. Accurate identification of these bacterial species with associated AMR is critical for their management. While highly accurate methods to detect CRE are available, they are costly, timely and require expert skills making their application infeasible in low-resource settings. Here, we investigated the potential of Near-infrared Spectroscopy (NIRS) for a range of applications; i) the detection and differentiation of isolates of two pathogenic Enterobacteriaceae species, Klebsiella pneumoniae and Escherichia coli and, ii) the differentiation of carbapenem resistant and susceptible K. pneumoniae. NIRS has successfully differentiated between K. pneumoniae and E. coli isolates with a predictive accuracy of 89.04% (95% CI; 88.7-89.4%). K. pneumoniae isolates harbouring carbapenem resistance determinants were differentiated from susceptible K. pneumoniae strains with an accuracy of 85% (95% CI; 84.2-86.1%). To our knowledge, this is the largest demonstration of a proof of concept for the utility and feasibility of NIRS for rapidly differentiating between K. pneumoniae from E.coli as well as from carbapenem resistant K. pneumoniae from susceptible strains.

Evaluation of aroma styles in flue-cured tobacco by near infrared spectroscopy combined with chemometric algorithms

2020 ◽  
Vol 28 (2) ◽  
pp. 93-102
Author(s):  
Fu Liao ◽  
Yongsheng Li ◽  
Wenmiao He ◽  
Jinxin Tie ◽  
Xianwei Hao ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Chemical Analysis ◽  
Sensory Evaluation ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Accuracy ◽  
Proposed Model ◽  
New Perspective ◽  
Chemometric Algorithms ◽  
Validation Strategy

Aroma style is a complex but critical sensory indicator of flue-cured tobacco. Near infrared spectroscopy was used to investigate the aroma style of flue-cured tobacco. A model screening-sensory validation strategy is herein proposed to overcome obstacles such as the subjectivity of sensory evaluation. Samples with exemplary styles and consistent opinion from a panel were selected as typical samples. Only typical samples were used for modeling. Other samples (atypical samples) were predicted through the proposed model. With references to sensory evaluation, the predictive accuracy reached to 100 and 79.0% for typical and atypical samples, respectively. This method provided a new perspective to evaluate the aroma styles of flue-cured tobacco by a combination of sensory evaluation and chemical analysis.

Curve fitting in Fourier transform near infrared spectroscopy used for the analysis of bacterial cells

2017 ◽  
Vol 25 (3) ◽  
pp. 151-164 ◽  
Author(s):  
Pavel Krepelka ◽  
Iveta Hynstova ◽  
Roman Pytel ◽  
Fernando Pérez-Rodríguez ◽  
Jean-Michel Roger ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Differential Evolution ◽  
Near Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Curve Fitting ◽  
Near Infrared ◽  
Bacterial Species ◽  
Lower Sensitivity ◽  
Data Set ◽  
Near Infrared Spectra

Infrared spectroscopy is a prominent molecular technique for bacterial analysis. Within its context, near infrared spectroscopy in particular brings benefits over other vibrational approaches; these advantages include, for example, lower sensitivity to water, high penetration depth and low cost. However, near infrared spectroscopy is not popular within microbiology, because the spectra of organic samples are difficult to interpret. We propose a comparison of spectral curve-fitting methods, namely, techniques that facilitate the interpretation of most peaks, simplify the spectra and improve the prediction of bacterial species from the relevant near infrared spectra. The performances of three common curve-fitting algorithms and the technique based on the differential evolution were compared via a synthesized experimental spectrum. Utilizing the obtained results, the spectra of three different bacterial species were curve fit by optimized algorithm. The proposed algorithm decomposed the spectra to specific absorption peaks, whose parameters were estimated via the differential evolution approach initialized through Levenberg-Marquardt optimization; subsequently, the spectra were classified with conventional procedures and using the parameters of the revealed peaks. On a limited data set, the correct classification rate computed by partial least squares discriminant analysis was 95%. When we employed the peak parameters for the classification, the rate corresponded to 91.7%. According to the Gaussian formula, the parameters comprise the spectral peak position, amplitude and width. The most important peaks for bacterial discrimination were identified by analysis of variance and interpreted as N–H stretching bonds in proteins, cis bonds and CH2 absorption in fatty acids. We examined some aspects of the behaviour of standard curve-fitting algorithms and proposed differential evolution to optimize the fitting process. Based on the correct use of these algorithms, the near infrared spectra of bacteria can be interpreted and the full potential of near infrared spectroscopy in microbiology exploited.

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