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Ling J, Liang L, Liu X, Wu W, Yan Z, Zhou W, Jiang Y, Kuang L. Invasive Fusarium solani infection diagnosed by traditional microbial detection methods and metagenomic next-generation sequencing in a pediatric patient: a case report and literature review. Front Med (Lausanne) 2024; 11:1322700. [PMID: 39040893 PMCID: PMC11260673 DOI: 10.3389/fmed.2024.1322700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 06/19/2024] [Indexed: 07/24/2024] Open
Abstract
Fusarium solani, as an opportunistic pathogen, can infect individuals with immunosuppression, neutropenia, hematopoietic stem cell transplantation (HSCT), or other high-risk factors, leading to invasive or localized infections. Particularly in patients following allogeneic HSCT, Fusarium solani is more likely to cause invasive or disseminated infections. This study focuses on a pediatric patient who underwent HSCT for severe aplastic anemia. Although initial blood cultures were negative, an abnormality was detected in the 1,3-β-D-glucan test (G test) post-transplantation. To determine the causative agent, blood samples were subjected to metagenomic next-generation sequencing (mNGS) and blood cultures simultaneously. Surprisingly, the results of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and mNGS differed slightly, with mNGS identifying Nectria haematonectria, while MALDI-TOF MS based on culture showed Fusarium solani. To clarify the results, Sanger sequencing was performed for further detection, and the results were consistent with those of MALDI-TOF MS. Since the accuracy of Sanger sequencing is higher than that of mNGS, the diagnosis was revised to invasive Fusarium solani infection. With advancements in technology, various detection methods for invasive fungi have been developed in recent years, such as mNGS, which has high sensitivity. While traditional methods may be time-consuming, they are important due to their high specificity. Therefore, in clinical practice, it is essential to utilize both traditional and novel detection methods in a complementary manner to enhance the diagnosis of invasive fungal infections.
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Affiliation(s)
- Jiaji Ling
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Liting Liang
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Xingxin Liu
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Wenjing Wu
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Ziyi Yan
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Wei Zhou
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Yongmei Jiang
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Linghan Kuang
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
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Stoia D, De Sio L, Petronella F, Focsan M. Recent advances towards point-of-care devices for fungal detection: Emphasizing the role of plasmonic nanomaterials in current and future technologies. Biosens Bioelectron 2024; 255:116243. [PMID: 38547645 DOI: 10.1016/j.bios.2024.116243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/14/2024] [Accepted: 03/22/2024] [Indexed: 04/15/2024]
Abstract
Fungal infections are a significant global health problem, particularly affecting individuals with weakened immune systems. Moreover, as uncontrolled antibiotic and immunosuppressant use increases continuously, fungal infections have seen a dramatic increase, with some strains developing antibiotic resistance. Traditional approaches to identifying fungal strains often rely on morphological characteristics, thus owning limitations, such as struggles in identifying several strains or distinguishing between fungal strains with similar morphologies. This review explores the multifaceted impact of fungi infections on individuals, healthcare providers, and society, highlighting the often-underestimated economic burden and healthcare implications of these infections. In light of the serious constraints of traditional fungal identification methods, this review discusses the potential of plasmonic nanoparticle-based biosensors for fungal infection identification. These biosensors can enable rapid and precise fungal pathogen detection by exploiting several readout approaches, including various spectroscopic techniques, colorimetric and electrochemical assays, as well as lateral-flow immunoassay methods. Moreover, we report the remarkable impact of plasmonic Lab on a Chip technology and microfluidic devices, as they recently emerged as a class of advanced biosensors. Finally, we provide an overview of smartphone-based Point-of-Care devices and the associated technologies developed for detecting and identifying fungal pathogens.
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Affiliation(s)
- Daria Stoia
- Biomolecular Physics Department, Faculty of Physics, Babes-Bolyai University, 1 M. Kogalniceanu Street, 400084, Cluj-Napoca, Romania; Nanobiophotonics and Laser Microspectroscopy Centre, Interdisciplinary Research Institute on Bio-Nano-Sciences, Babes-Bolyai University, 42 Treboniu Laurian Street, 400271, Cluj-Napoca, Romania
| | - Luciano De Sio
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Corso della Repubblica 79, 04100, Latina, Italy
| | - Francesca Petronella
- National Research Council of Italy, Institute of Crystallography CNR-IC, Area della Ricerca Roma 1 Strada Provinciale 35d, n. 9, 00010, Montelibretti (RM), Italy.
| | - Monica Focsan
- Biomolecular Physics Department, Faculty of Physics, Babes-Bolyai University, 1 M. Kogalniceanu Street, 400084, Cluj-Napoca, Romania; Nanobiophotonics and Laser Microspectroscopy Centre, Interdisciplinary Research Institute on Bio-Nano-Sciences, Babes-Bolyai University, 42 Treboniu Laurian Street, 400271, Cluj-Napoca, Romania.
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Demirel E, Korkmaz B, Chang Y, Misra A, Tamerler C, Spencer P. Engineering Interfacial Integrity with Hydrolytic-Resistant, Self-Reinforcing Dentin Adhesive. Int J Mol Sci 2024; 25:7061. [PMID: 39000170 PMCID: PMC11241055 DOI: 10.3390/ijms25137061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 06/23/2024] [Accepted: 06/25/2024] [Indexed: 07/16/2024] Open
Abstract
The leading cause of composite restoration failure is secondary caries, and although caries is a multifactorial problem, weak, damage-prone adhesives play a pivotal role in the high susceptibility of composite restorations to secondary caries. Our group has developed synthetic resins that capitalize on free-radical polymerization and sol-gel reactions to provide dental adhesives with enhanced properties. The resins contain γ-methacryloxypropyltrimethoxysilane (MPS) as the Si-based compound. This study investigated the properties of methacrylate-based resins containing methacryloxymethyltrimethoxysilane (MMeS) as a short-chain alternative. The degree of conversion (DC), polymerization kinetics, water sorption, mechanical properties, and leachates of MMeS- and MPS-resins with 55 and 30 wt% BisGMA-crosslinker were determined. The formulations were used as model adhesives, and the adhesive/dentin (a/d) interfaces were analyzed using chemometrics-assisted micro-Raman spectroscopy. The properties of the 55 wt% formulations were comparable. In the 30 wt% BisGMA formulations, the MMeS-resin exhibited faster polymerization, lower DC, reduced leachates, and increased storage and loss moduli, glass transition (Tg), crosslink density, and heterogeneity. The spectroscopic results indicated a comparable spatial distribution of resin, mineralized, and demineralized dentin across the a/d interfaces. The hydrolytically stable experimental short-chain-silane-monomer dental adhesive provides enhanced mechanical properties through autonomous strengthening and offers a promising strategy for the development of restorative dental materials with extended service life.
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Affiliation(s)
- Erhan Demirel
- Institute for Bioengineering Research, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
| | - Burak Korkmaz
- Institute for Bioengineering Research, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
- Department of Chemistry, Faculty of Science and Letters, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
| | - Youngwoo Chang
- Department of Chemical and Petroleum Engineering, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
| | - Anil Misra
- Department of Civil and Environmental Engineering, Florida International University, Miami, FL 33174-1630, USA
| | - Candan Tamerler
- Institute for Bioengineering Research, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
- Department of Mechanical Engineering, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
- Bioengineering Program, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
| | - Paulette Spencer
- Institute for Bioengineering Research, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
- Department of Mechanical Engineering, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
- Bioengineering Program, University of Kansas, 1530 W. 15th Street, Lawrence, KS 66045-7608, USA
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Wasim M, Ghaffar U, Javed MR, Nawaz H, Majeed MI, Ijaz A, Ishtiaq S, Rehman N, Razaq R, Younas S, Bano A, Kanwal N, Imran M. Surface-Enhanced Raman Spectroscopy for Monitoring the Biochemical Changes Due to DNA Mutations Induced by CRISPR-Cas9 Genome Editing in the Aspergillus niger Fungus. ACS OMEGA 2024; 9:15202-15209. [PMID: 38585125 PMCID: PMC10993282 DOI: 10.1021/acsomega.3c09563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/22/2024] [Accepted: 03/04/2024] [Indexed: 04/09/2024]
Abstract
In this study, surface-enhanced Raman spectroscopy (SERS) technique, along with principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA), is used as a simple, quick, and cost-effective analysis method for identifying biochemical changes occurring due to induced mutations in the Aspergillus niger fungus strain. The goal of this study is to identify the biochemical changes in the mutated fungal cells (cell mass) as compared to the control/nonmutated cells. Furthermore, multivariate data analysis tools, including PCA and PLS-DA, are used to further confirm the differentiating SERS spectral features among fungal samples. The mutations are caused in A. niger by the clustered regularly interspaced palindromic repeat CRISPR-Cas9 genomic editing method to improve their biotechnological potential for the production of cellulase enzyme. SERS was employed to detect the changes in the cells of mutated A. niger fungal strains, including one mutant producing low levels of an enzyme and another mutant producing high levels of the enzyme as a result of mutation as compared with an unmutated fungal strain as a control sample. The distinctive features of SERS corresponding to nucleic acids and proteins appear at 546, 622, 655, 738, 802, 835, 959, 1025, 1157, 1245, 1331, 1398, and 1469 cm-1. Furthermore, PLS-DA is used to confirm the 89% accuracy, 87.7% precision, 87% sensitivity, and 88.9% specificity of this method, and the value of the area under the curve (AUROC) is 0.67. It has been shown that surface-enhanced Raman spectroscopy is an effective method for identifying and differentiating biochemical changes in genome-modified fungal samples.
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Affiliation(s)
- Muhammad Wasim
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Usman Ghaffar
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Rizwan Javed
- Biocatalysis
and Protein Engineering Research Group (BPERG), Department of Bioinformatics
and Biotechnology, Government College University
Faisalabad (GCUF), Allama
Iqbal Road, Faisalabad 38000, Pakistan
| | - Haq Nawaz
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Irfan Majeed
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Anam Ijaz
- Biocatalysis
and Protein Engineering Research Group (BPERG), Department of Bioinformatics
and Biotechnology, Government College University
Faisalabad (GCUF), Allama
Iqbal Road, Faisalabad 38000, Pakistan
| | - Shazra Ishtiaq
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Nimra Rehman
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Rabeea Razaq
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Sobia Younas
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Aqsa Bano
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Naeema Kanwal
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Imran
- Department
of Chemistry, Faculty of Science, King Khalid
University, P.O. Box 9004, Abha 61413, Saudi Arabia
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5
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He P, Dumont E, Göksel Y, Slipets R, Schmiegelow K, Chen Q, Zor K, Boisen A. SERS mapping combined with chemometrics, for accurate quantification of methotrexate from patient samples. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 305:123536. [PMID: 37862841 DOI: 10.1016/j.saa.2023.123536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/28/2023] [Accepted: 10/12/2023] [Indexed: 10/22/2023]
Abstract
Despite the technological development in Raman instrumentation that has democratized access to 2D sample scanning capabilities, most quantitative surface-enhanced Raman scattering (SERS) analyses are still performed by only acquiring a single or a few spectra per sample and performing univariate data analysis on those. This strategy can however reach its limit when analytes need to be detected and quantified in complex matrices. In that case, surface fouling and competition between the target analyte and interfering compounds can impair univariate SERS data analysis, underlining the need for a more in-depth data analysis strategy based on exploiting of full-spectrum information. In this paper, a multivariate data analysis strategy was developed, for analyzing SERS maps of methotrexate (MTX) from patient samples, including all steps from baseline correction, selection of wavelength, and the relevant pixels in the map (image threshold segmentation), as well as quantitative model construction based on partial-least squares regression. Among the different baseline correction methods evaluated, standard normal variable transformation and Savitzky-Golay smoothing proved to be more suitable, while the genetic algorithm wavelength screening method was able to screen out MTX-related SERS spectral regions more efficiently. Importantly, with the here-developed process, it was sufficient to use MTX-spiked commercial serum when building quantitative models, removing the need to work with MTX-spiked patient samples, and consequently enabling time- and resource-saving quantitative analyses. Besides, the developed multivariate data analysis approach showed superior performances compared with univariate analysis, with 30 % improved sensitivity (detection limit of 5.7 µM), 25 % higher reproducibility (average relative standard variation of 15.6 %), and 110 % better accuracy (average prediction error of -10.5 %).
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Affiliation(s)
- Peihuan He
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark; School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212100, PR China; School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China; School of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212100, PR China
| | - Elodie Dumont
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark; BioInnovation Institute Foundation, Copenhagen N, 2200, Denmark.
| | - Yaman Göksel
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark; BioInnovation Institute Foundation, Copenhagen N, 2200, Denmark
| | - Roman Slipets
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark; BioInnovation Institute Foundation, Copenhagen N, 2200, Denmark
| | - Kjeld Schmiegelow
- Department of Paediatrics and Adolescent Medicine, Rigshospitalet University Hospital, Copenhagen 2100, Denmark
| | - Quansheng Chen
- College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, PR China; School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
| | - Kinga Zor
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark; BioInnovation Institute Foundation, Copenhagen N, 2200, Denmark
| | - Anja Boisen
- Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics (IDUN), Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, 2800, Denmark; BioInnovation Institute Foundation, Copenhagen N, 2200, Denmark
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Huda NU, Wasim M, Nawaz H, Majeed MI, Javed MR, Rashid N, Iqbal MA, Tariq A, Hassan A, Akram MW, Jamil F, Imran M. Synthesis, Characterization, and Evaluation of Antifungal Activity of 1-Butyl-3-hexyl-1 H-imidazol-2(3 H)-selenone by Surface-Enhanced Raman Spectroscopy. ACS OMEGA 2023; 8:36460-36470. [PMID: 37810682 PMCID: PMC10552477 DOI: 10.1021/acsomega.3c05436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023]
Abstract
In the present research work, a selenium N-heterocyclic carbene (Se-NHC) complex/adduct was synthesized and characterized by using different analytical methods including FT-IR, 1HNMR, and 13CNMR. The antifungal activity of the Se-NHC complex against Aspergillus flavus (A. flavus) fungus was investigated with disc diffusion assay. Moreover, the biochemical changes occurring in this fungus due to exposure of different concentrations of the in-house synthesized compound are characterized by surface-enhanced Raman spectroscopy (SERS) and are illustrated in the form of SERS spectral peaks. SERS analysis yields valuable information about the probable mechanisms responsible for the antifungal effects of the Se-NHC complex. As demonstrated by the SERS spectra, this Se-NHC complex caused denaturation and conformational changes in the proteins as well as decomposition of the fungal cell membrane. The SERS spectra were analyzed using two chemometric tools such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). The fungal samples' SERS spectra were differentiated using PCA, while various groups of spectra were discriminated with ultrahigh sensitivity (98%), high specificity (99.7%), accuracy (100%), and area under the receiver operating characteristic curve (87%) using PLS-DA.
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Affiliation(s)
- Noor ul Huda
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Wasim
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Haq Nawaz
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Irfan Majeed
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Rizwan Javed
- Department
of Bioinformatics and Biotechnology, Government
College University Faisalabad (GCUF), Faisalabad 38000, Pakistan
| | - Nosheen Rashid
- Department
of Chemistry, University of Education, Faisalabad Campus, Faisalabad 38000, Pakistan
| | - Muhammad Adnan Iqbal
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Anam Tariq
- Department
of Biochemistry, Government College University
Faisalabad (GCUF), Faisalabad 38000, Pakistan
| | - Ahmad Hassan
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Waseem Akram
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Faisal Jamil
- Department
of Chemistry, University of Agriculture
Faisalabad, Faisalabad 38000, Pakistan
| | - Muhammad Imran
- Department
of Chemistry, Faculty of Science, King Khalid
University, P.O. Box 9004, Abha 61413, Saudi Arabia
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Xie X, Yu W, Chen Z, Wang L, Yang J, Liu S, Li L, Li Y, Huang Y. Early-stage oral cancer diagnosis by artificial intelligence-based SERS using Ag NWs@ZIF core-shell nanochains. NANOSCALE 2023; 15:13466-13472. [PMID: 37548371 DOI: 10.1039/d3nr02662k] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) has great potential in the early diagnosis of diseases by detecting the changes of volatile biomarkers in exhaled breath, because of its high sensitivity, rich chemical molecular fingerprint information, and immunity to humidity. Here, an accurate diagnosis of oral cancer (OC) is demonstrated using artificial intelligence (AI)-based SERS of exhaled breath in plasmonic-metal organic framework (MOF) nanoparticles. These plasmonic-MOF nanoparticles were prepared using a zeolitic imidazolate framework coated on Ag nanowires (Ag NWs@ZIF), which offers Raman enhancement from the plasmonic nanowires and gas enrichment from the ZIF shells. Then, the core-shell nanochains of Ag NWs@ZIF prepared with 0.5 mL Ag NWs were selected to capture gaseous methanethiol, which is a tumor biomarker, from the exhalation of OC patients. The substrate was used to collect a total of 400 SERS spectra of exhaled breath of simulated healthy people and simulated OC patients. The artificial neural network (ANN) model in the AI algorithm was trained with these SERS spectra and could classify them with an accuracy of 99%. Notably, the model predicted OC with an area under the curve (AUC) of 0.996 for the simulated OC breath samples. This work suggests the great potential of the combination of breath analysis and AI as a method for the early-stage diagnosis of oral cancer.
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Affiliation(s)
- Xin Xie
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Wenrou Yu
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Zhaoxian Chen
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Li Wang
- School of Optoelectronics Engineering, Chongqing University, Chongqing 401331, China
| | - Junjun Yang
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Shihong Liu
- Department of Geriatric Oncology and Department of Palliative Care, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Linze Li
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Yanxi Li
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Yingzhou Huang
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
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8
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Jin L, Yang J, You G, Ge C, Cao Y, Shen S, Wang D, Hui Q. A characteristic bacterial SERS marker for direct identification of Salmonella in real samples assisted by a high-performance SERS chip and a selective culture medium. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 301:122941. [PMID: 37302194 DOI: 10.1016/j.saa.2023.122941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 05/19/2023] [Accepted: 05/27/2023] [Indexed: 06/13/2023]
Abstract
Salmonella should be absent in pharmaceutical preparations and foods according to the regulations. However, up to now, rapid and convenient identification of Salmonella is still full of challenge. Herein, we reported a label-free surface-enhanced Raman scattering (SERS) method for direct identification of Salmonella spiked in drug samples based on a characteristic bacterial SERS marker assisted by a high-performance SERS chip and a selective culture medium. The SERS chip being fabricated through in situ growth of bimetallic Au-Ag nanocomposites on silicon wafer within 2 h, featured a high SERS activity (EF > 107), good uniformity and batch-to-batch consistency (RSD < 10 %), and satisfactory chemical stability. The directly-visualized SERS marker at 1222 cm-1 originated from bacterial metabolite hypoxanthine was robust and exclusive for discrimination of Salmonella with other bacterial species. Moreover, the method was successfully used for direct discrimination of Salmonella in mixed pathogens by using a selective culture medium, and could identify Salmonella contaminant at ∼1 CFU spiked level in a real sample (Wenxin granule, a botanical drug) after 12 h of enrichment. The combined results showed that developed SERS method is practical and reliable, and could be a promising alternative for rapid identification of Salmonella contamination in pharmaceutical and foods industries.
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Affiliation(s)
- Lei Jin
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China; Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou 325000, China.
| | - Jinmei Yang
- School of Biomedical Engineering, School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325001, China
| | - Guohui You
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Chaojie Ge
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Yanrong Cao
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Siyuan Shen
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Danyan Wang
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
| | - Qi Hui
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
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Pirnau A, Feher I, Sârbu C, Hategan AR, Guyon F, Magdas DA. Application of fuzzy algorithms in conjunction with 1 H-NMR spectroscopy to differentiate alcoholic beverages. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:1727-1735. [PMID: 36541578 DOI: 10.1002/jsfa.12402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/29/2022] [Accepted: 12/21/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Recent statistics from the European Commission indicate that wine is one of the commodities most commonly subject to food fraud. In this context, the development of reliable classification models to differentiate alcoholic beverages requires, besides sensitive analytical tools, the use of the most suitable data-processing methods like those based on advanced statistical tools or artificial intelligence. RESULTS The present study aims to establish a new, innovative approach for the differentiation of alcoholic beverages (wines and fruit distillates), which is able to increase the discrimination rate of the models that have been developed. A data dimensionality reduction step was applied to proton nuclear magnetic resonance (1 H-NMR) profiles. This stage consisted of the application of fuzzy principal component analysis (FPCA) prior to the development of classification models through discriminant analysis. The enhancement of the model's classification potential by the application of FPCA in comparison with principal component analysis (PCA) was discussed. CONCLUSION The association of 1 H-NMR spectroscopy and an appropriate statistical approach provided a very effective tool for the differentiation of alcoholic beverages. To develop reliable metabolomic approaches for the differentiation of wines and fruit distillates, 1 H-NMR spectroscopic data were exploited in conjunction with fuzzy algorithms to reduce data dimensionality. The study proved the greater efficiency of using FPCA scores in comparison with those obtained through the widely applied PCA. The proposed approach enabled wines to be distinguished perfectly according to their geographical origins, cultivar, and vintage, and this could be used for wine classification. Moreover, 100% correctly classified samples were also achieved for the botanical and geographical differentiation of fruit distillates. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Adrian Pirnau
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Ioana Feher
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Costel Sârbu
- Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, Cluj-Napoca, Romania
| | - Ariana Raluca Hategan
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | | | - Dana Alina Magdas
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
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10
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Liu Z, Meng D, Su G, Hu P, Song B, Wang Y, Wei J, Yang H, Yuan T, Chen B, Ou TH, Hossain S, Miller M, Liu F, Wu W. Ultrafast Early Warning of Heart Attacks through Plasmon-Enhanced Raman Spectroscopy using Collapsible Nanofingers and Machine Learning. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2204719. [PMID: 36333119 DOI: 10.1002/smll.202204719] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 10/03/2022] [Indexed: 06/16/2023]
Abstract
As the leading cause of death, heart attacks result in millions of deaths annually, with no end in sight. Early intervention is the only strategy for rescuing lives threatened by heart disease. However, the detection time of the fastest heart-attack detection system is >15 min, which is too long considering the rapid passage of life. In this study, a machine learning (ML)-driven system with a simple process, low-cost, short detection time (only 10 s), and high precision is developed. By utilizing a functionalized nanofinger structure, even a trace amount of biomarker leaked before a heart attack can be captured. Additionally, enhanced Raman profiles are constructed for predictive analytics. Five ML models are developed to harness the useful characteristics of each Raman spectrum and provide early warnings of heart attacks with >98% accuracy. Through the strategic combination of nanofingers and ML algorithms, the proposed warning system accurately provides alerts on silent heart-attack attempts seconds ahead of actual attacks.
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Affiliation(s)
- Zerui Liu
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Deming Meng
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Guangxu Su
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou, Zhejiang, 310023, China
| | - Pan Hu
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Boxiang Song
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wu Han, Hu Bei, 430074, China
| | - Yunxiang Wang
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Junhan Wei
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou, Zhejiang, 310023, China
| | - Hao Yang
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Tianyi Yuan
- Beijing Etown Academy, Beijing, 100176, China
| | - Buyun Chen
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Tse-Hsien Ou
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Sushmit Hossain
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Matthew Miller
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Fanxin Liu
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou, Zhejiang, 310023, China
| | - Wei Wu
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
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11
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Berus SM, Adamczyk-Popławska M, Goździk K, Przedpełska G, Szymborski TR, Stepanenko Y, Kamińska A. SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms. Int J Mol Sci 2022; 23:ijms232012576. [PMID: 36293436 PMCID: PMC9604117 DOI: 10.3390/ijms232012576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 10/14/2022] [Accepted: 10/17/2022] [Indexed: 11/16/2022] Open
Abstract
The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms (Lactobacillus spp. and Bifidobacterium spp.) and vaginal pathogens: bacteria (e.g., Gardnerella vaginalis, Prevotella bivia, Atopobium vaginae), fungi (e.g., Candida albicans, Candida glabrata), and protozoa (Trichomonas vaginalis). The obtained results proved that each microorganism has its unique spectral fingerprint that differentiates it from the rest. Moreover, the discrimination was obtained at a high level of explained information by subsequent factors, e.g., in the inter-species distinction of Candida spp. the first three factors explain 98% of the variance in block Y with 95% of data within the X matrix, while in differentiation between Lactobacillus spp. and Bifidobacterium spp. (natural flora) and pathogen (e.g., Candida glabrata) the information is explained at the level of 45% of the Y matrix with 94% of original data. PLSR gave us insight into discriminating variables based on which the marker bands representing specific compounds in the outer structure of microorganisms were found: for Lactobacillus spp. 1400 cm−1, for fungi 905 and 1209 cm−1, and for protozoa 805, 890, 1062, 1185, 1300, 1555, and 1610 cm−1. Then, they can be used as significant marker bands in the analysis of clinical subjects, e.g., vaginal swabs.
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Affiliation(s)
- Sylwia Magdalena Berus
- Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland
- Correspondence: (S.M.B.); (A.K.)
| | - Monika Adamczyk-Popławska
- Department of Molecular Virology, Faculty of Biology, University of Warsaw, Miecznikowa 1, 02-096 Warsaw, Poland
| | - Katarzyna Goździk
- Department of Parasitology, Faculty of Biology, University of Warsaw, Miecznikowa 1, 02-096 Warsaw, Poland
| | - Grażyna Przedpełska
- Department of Dermatology and Venerology, Infant Jesus Clinical Hospital, Koszykowa 82a, 02-008 Warsaw, Poland
| | - Tomasz R. Szymborski
- Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland
| | - Yuriy Stepanenko
- Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland
| | - Agnieszka Kamińska
- Institute of Physical Chemistry, Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland
- Correspondence: (S.M.B.); (A.K.)
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12
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Xia J, Li W, Sun M, Wang H. Application of SERS in the Detection of Fungi, Bacteria and Viruses. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:nano12203572. [PMID: 36296758 PMCID: PMC9609009 DOI: 10.3390/nano12203572] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/07/2022] [Accepted: 10/08/2022] [Indexed: 06/12/2023]
Abstract
In this review, we report the recent advances of SERS in fungi, bacteria, and viruses. Firstly, we briefly introduce the advantage of SERS over fluorescence on virus identification and detection. Secondly, we review the feasibility analysis of Raman/SERS spectrum analysis, identification, and fungal detection on SERS substrates of various nanostructures with a signal amplification mechanism. Thirdly, we focus on SERS spectra for nucleic acid, pathogens for the detection of viruses and bacteria, and furthermore introduce SERS-based microdevices, including SERS-based microfluidic devices, and three-dimensional nanostructured plasmonic substrates.
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Affiliation(s)
- Jiarui Xia
- Institute of Health Sciences, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, China Medical University, Shenyang 110001, China
| | - Wenwen Li
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China
| | - Mengtao Sun
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China
| | - Huiting Wang
- College of Chemistry, Liaoning University, Shenyang 110036, China
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13
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Formation of Gold Nanoparticle Self-Assembling Films in Various Polymer Matrices for SERS Substrates. MATERIALS 2022; 15:ma15155197. [PMID: 35897629 PMCID: PMC9332835 DOI: 10.3390/ma15155197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 02/04/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) is regarded as a versatile tool for studying the composition and structure of matter. This work has studied the preparation of a SERS substrate based on a self-assembling plasmonic nanoparticle film (SPF) in a polymer matrix. Several synthesis parameters for the SPF are investigated, including the size of the particles making up the film and the concentration and type of the self-assembling agent. The result of testing systems with different characteristics is discussed using a model substance (pseudoisocyanin iodide). These models can be useful in the study of biology and chemistry. Research results contain the optimal parameters for SPF synthesis, maximizing the SERS signal. The optimal procedure for SPF assembly is determined and used for the synthesis of composite SPFs within different polymer matrices. SPF in a polymer matrix is necessary for the routine use of the SERS substrate for various types of analytes, including solid samples or those sensitive to contamination. Polystyrene, polyvinyl alcohol (PVA), and polyethylene are investigated to obtain a polymer matrix for SPF, and various methods of incorporating SPF into a polymer matrix are being explored. It is found that films with the best signal enhancement and reproducibility were obtained in polystyrene. The minimum detectable concentration for the SERS substrate obtained is equal to 10−10 M. We prepared a SERS substrate with an analytical enhancement factor of 2.7 × 104, allowing an increase in the detection sensitivity of analyte solutions of five orders of magnitude.
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14
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Sun X. Glucose detection through surface-enhanced Raman spectroscopy: A review. Anal Chim Acta 2022; 1206:339226. [PMID: 35473867 DOI: 10.1016/j.aca.2021.339226] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 10/20/2021] [Accepted: 10/27/2021] [Indexed: 12/13/2022]
Abstract
Glucose detection is of vital importance to diabetes diagnosis and treatment. Optical approaches in glucose sensing have received much attention in recent years due to the relatively low cost, portable, and mini-invasive or non-invasive potentials. Surface enhanced Raman spectroscopy (SERS) endows the benefits of extremely high sensitivity because of enhanced signals and specificity due to the fingerprint of molecules of interest. However, the direct detection of glucose through SERS was challenging because of poor adsorption of glucose on bare metals and low cross section of glucose. In order to address these challenges, several approaches were proposed and utilized for glucose detection through SERS. This review article mainly focuses on the development of surface enhanced Raman scattering based glucose sensors in recent 10 years. The sensing mechanisms, rational design and sensing properties to glucose are reviewed. Two strategies are summarized as intrinsic sensing and extrinsic sensing. Four general categories for glucose sensing through SERS are discussed including SERS active platform, partition layer functionalized surface, boronic acid based sensors, and enzymatic reaction based biosensors. Finally, the challenges and outlook for SERS based glucose sensors are also presented.
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Affiliation(s)
- Xiangcheng Sun
- Department of Chemical Engineering, Rochester Institute of Technology, Rochester, NY, 14623, United States.
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15
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From lab to field: Surface-enhanced Raman scattering-based sensing strategies for on-site analysis. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2021.116488] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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16
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Cui L, Li HZ, Yang K, Zhu LJ, Xu F, Zhu YG. Raman biosensor and molecular tools for integrated monitoring of pathogens and antimicrobial resistance in wastewater. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116415] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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17
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Xu Y, Hassan MM, Sharma AS, Li H, Chen Q. Recent advancement in nano-optical strategies for detection of pathogenic bacteria and their metabolites in food safety. Crit Rev Food Sci Nutr 2021; 63:486-504. [PMID: 34281447 DOI: 10.1080/10408398.2021.1950117] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Pathogenic bacteria and their metabolites are the leading risk factor in food safety and are one of the major threats to human health because of the capability of triggering diseases with high morbidity and mortality. Nano-optical sensors for bacteria sensing have been greatly explored with the emergence of nanotechnology and artificial intelligence. In addition, with the rapid development of cross fusion technology, other technologies integrated nano-optical sensors show great potential in bacterial and their metabolites sensing. This review focus on nano-optical strategies for bacteria and their metabolites sensing in the field of food safety; based on surface-enhanced Raman scattering (SERS), fluorescence, and colorimetric biosensors, and their integration with the microfluidic platform, electrochemical platform, and nucleic acid amplification platform in the recent three years. Compared with the traditional techniques, nano optical-based sensors have greatly improved the sensitivity with reduced detection time and cost. However, challenges remain for the simple fabrication of biosensors and their practical application in complex matrices. Thus, bringing out improvements or novelty in the pretreatment methods will be a trend in the upcoming future.
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Affiliation(s)
- Yi Xu
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, People's Republic of China
| | - Md Mehedi Hassan
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, People's Republic of China
| | - Arumugam Selva Sharma
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, People's Republic of China
| | - Huanhuan Li
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, People's Republic of China
| | - Quansheng Chen
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, People's Republic of China
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18
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Tahir MA, Dina NE, Cheng H, Valev VK, Zhang L. Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis. NANOSCALE 2021; 13:11593-11634. [PMID: 34231627 DOI: 10.1039/d1nr00708d] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.
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Affiliation(s)
- Muhammad Ali Tahir
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200433, Peoples' Republic of China.
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19
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Dzurendová S, Shapaval V, Tafintseva V, Kohler A, Byrtusová D, Szotkowski M, Márová I, Zimmermann B. Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy. Int J Mol Sci 2021; 22:6710. [PMID: 34201486 PMCID: PMC8269384 DOI: 10.3390/ijms22136710] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 12/11/2022] Open
Abstract
Oleaginous filamentous fungi can accumulate large amount of cellular lipids and biopolymers and pigments and potentially serve as a major source of biochemicals for food, feed, chemical, pharmaceutical, and transport industries. We assessed suitability of Fourier transform (FT) Raman spectroscopy for screening and process monitoring of filamentous fungi in biotechnology. Six Mucoromycota strains were cultivated in microbioreactors under six growth conditions (three phosphate concentrations in the presence and absence of calcium). FT-Raman and FT-infrared (FTIR) spectroscopic data was assessed in respect to reference analyses of lipids, phosphorus, and carotenoids by using principal component analysis (PCA), multiblock or consensus PCA, partial least square regression (PLSR), and analysis of spectral variation due to different design factors by an ANOVA model. All main chemical biomass constituents were detected by FT-Raman spectroscopy, including lipids, proteins, cell wall carbohydrates, and polyphosphates, and carotenoids. FT-Raman spectra clearly show the effect of growth conditions on fungal biomass. PLSR models with high coefficients of determination (0.83-0.94) and low error (approximately 8%) for quantitative determination of total lipids, phosphates, and carotenoids were established. FT-Raman spectroscopy showed great potential for chemical analysis of biomass of oleaginous filamentous fungi. The study demonstrates that FT-Raman and FTIR spectroscopies provide complementary information on main fungal biomass constituents.
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Affiliation(s)
- Simona Dzurendová
- Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; (S.D.); (V.S.); (V.T.); (A.K.); (D.B.)
| | - Volha Shapaval
- Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; (S.D.); (V.S.); (V.T.); (A.K.); (D.B.)
| | - Valeria Tafintseva
- Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; (S.D.); (V.S.); (V.T.); (A.K.); (D.B.)
| | - Achim Kohler
- Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; (S.D.); (V.S.); (V.T.); (A.K.); (D.B.)
| | - Dana Byrtusová
- Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; (S.D.); (V.S.); (V.T.); (A.K.); (D.B.)
- Faculty of Chemistry, Brno University of Technology, Purkyňova 464/118, 61200 Brno, Czech Republic; (M.S.); (I.M.)
| | - Martin Szotkowski
- Faculty of Chemistry, Brno University of Technology, Purkyňova 464/118, 61200 Brno, Czech Republic; (M.S.); (I.M.)
| | - Ivana Márová
- Faculty of Chemistry, Brno University of Technology, Purkyňova 464/118, 61200 Brno, Czech Republic; (M.S.); (I.M.)
| | - Boris Zimmermann
- Faculty of Science and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 Ås, Norway; (S.D.); (V.S.); (V.T.); (A.K.); (D.B.)
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20
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Spencer P, Ye Q, Kamathewatta NJB, Woolfolk SK, Bohaty BS, Misra A, Tamerler C. Chemometrics-Assisted Raman Spectroscopy Characterization of Tunable Polymer-Peptide Hybrids for Dental Tissue Repair. FRONTIERS IN MATERIALS 2021; 8:681415. [PMID: 34113623 PMCID: PMC8186416 DOI: 10.3389/fmats.2021.681415] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The interfaces that biological tissues form with biomaterials are invariably defective and frequently the location where failure initiates. Characterizing the phenomena that lead to failure is confounded by several factors including heterogeneous material/tissue interfaces. To seamlessly analyze across these diverse structures presents a wealth of analytical challenges. This study aims to develop a molecular-level understanding of a peptide-functionalized adhesive/collagen hybrid biomaterial using Raman spectroscopy combined with chemometrics approach. An engineered hydroxyapatite-binding peptide (HABP) was copolymerized in dentin adhesive and dentin was demineralized to provide collagen matrices that were partially infiltrated with the peptide-functionalized adhesive. Partial infiltration led to pockets of exposed collagen-a condition that simulates defects in adhesive/dentin interfaces. The spectroscopic results indicate that co-polymerizable HABP tethered to the adhesive promoted remineralization of the defects. The spatial distribution of collagen, adhesive, and mineral as well as crystallinity of the mineral across this heterogeneous material/tissue interface was determined using micro-Raman spectroscopy combined with chemometrics approach. The success of this combined approach in the characterization of material/tissue interfaces stems from its ability to extract quality parameters that are related to the essential and relevant portions of the spectral data, after filtering out noise and non-relevant information. This ability is critical when it is not possible to separate components for analysis such as investigations focused on, in situ chemical characterization of interfaces. Extracting essential information from complex bio/material interfaces using data driven approaches will improve our understanding of heterogeneous material/tissue interfaces. This understanding will allow us to identify key parameters within the interfacial micro-environment that should be harnessed to develop durable biomaterials.
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Affiliation(s)
- Paulette Spencer
- Institute for Bioengineering Research, University of Kansas, Lawrence, KS, United States
- Department of Mechanical Engineering, University of Kansas, Lawrence, KS, United States
- Bioengineering Program, University of Kansas, Lawrence, KS, United States
- Correspondence: Paulette Spencer, , Qiang Ye,
| | - Qiang Ye
- Institute for Bioengineering Research, University of Kansas, Lawrence, KS, United States
- Correspondence: Paulette Spencer, , Qiang Ye,
| | - Nilan J. B. Kamathewatta
- Institute for Bioengineering Research, University of Kansas, Lawrence, KS, United States
- Bioengineering Program, University of Kansas, Lawrence, KS, United States
| | - Sarah K. Woolfolk
- Institute for Bioengineering Research, University of Kansas, Lawrence, KS, United States
- Bioengineering Program, University of Kansas, Lawrence, KS, United States
| | - Brenda S. Bohaty
- Department of Pediatric Dentistry, School of Dentistry, University of Missouri-Kansas City, Kansas City, MO, United States
| | - Anil Misra
- Institute for Bioengineering Research, University of Kansas, Lawrence, KS, United States
- Department of Civil Engineering, University of Kansas, Lawrence, KS, United States
| | - Candan Tamerler
- Institute for Bioengineering Research, University of Kansas, Lawrence, KS, United States
- Department of Mechanical Engineering, University of Kansas, Lawrence, KS, United States
- Bioengineering Program, University of Kansas, Lawrence, KS, United States
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21
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Leong YX, Lee YH, Koh CSL, Phan-Quang GC, Han X, Phang IY, Ling XY. Surface-Enhanced Raman Scattering (SERS) Taster: A Machine-Learning-Driven Multireceptor Platform for Multiplex Profiling of Wine Flavors. NANO LETTERS 2021; 21:2642-2649. [PMID: 33709720 DOI: 10.1021/acs.nanolett.1c00416] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Integrating machine learning with surface-enhanced Raman scattering (SERS) accelerates the development of practical sensing devices. Such integration, in combination with direct detection or indirect analyte capturing strategies, is key to achieving high predictive accuracies even in complex matrices. However, in-depth understanding of spectral variations arising from specific chemical interactions is essential to prevent model overfit. Herein, we design a machine-learning-driven "SERS taster" to simultaneously harness useful vibrational information from multiple receptors for enhanced multiplex profiling of five wine flavor molecules at parts-per-million levels. Our receptors employ numerous noncovalent interactions to capture chemical functionalities within flavor molecules. By strategically combining all receptor-flavor SERS spectra, we construct comprehensive "SERS superprofiles" for predictive analytics using chemometrics. We elucidate crucial molecular-level interactions in flavor identification and further demonstrate the differentiation of primary, secondary, and tertiary alcohol functionalities. Our SERS taster also achieves perfect accuracies in multiplex flavor quantification in an artificial wine matrix.
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Affiliation(s)
- Yong Xiang Leong
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
| | - Yih Hong Lee
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
| | - Charlynn Sher Lin Koh
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
| | - Gia Chuong Phan-Quang
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
| | - Xuemei Han
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
| | - In Yee Phang
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
| | - Xing Yi Ling
- Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
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22
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Dina NE, Gherman AMR, Colniță A, Marconi D, Sârbu C. Fuzzy characterization and classification of bacteria species detected at single-cell level by surface-enhanced Raman scattering. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 247:119149. [PMID: 33188974 DOI: 10.1016/j.saa.2020.119149] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 10/08/2020] [Accepted: 10/26/2020] [Indexed: 06/11/2023]
Abstract
Advanced chemometric methods, such as fuzzy c-means, a semi-supervised clustering method, and fuzzy linear discriminant analysis (FLDA), a new robust supervised classification method in combination with principal component analysis (PCA), namely PCA-FLDA, have been successfully applied for characterization and classification of bacterial species detected at single-cell level by surface-enhanced Raman scattering (SERS) spectroscopy. SERS spectra of three species (S. aureus, E. faecalis and P. aeruginosa) were recorded in an original fashion, using in situ laser induced silver spot as metallic substrate. The detection process of bacteria was isolated inside a hermetically sealed in-house built microfluidic device, connected to a syringe pump for injecting the analytes and a portable Raman spectrometer as detection tool. The obtained results (fuzzy partitions) and spectra of the prototypes (robust fuzzy spectra mean corresponding to each fuzzy partition) clearly demonstrated the efficiency and information power of the advanced fuzzy methods in bacteria characterization and classification based on SERS spectra, and allowed a rationale assigning to a specific group. Also, this powerful detection and classification methodology generates the premises for future investigations of Raman and other spectroscopic data obtained for various samples.
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Affiliation(s)
- Nicoleta Elena Dina
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania.
| | - Ana Maria Raluca Gherman
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Alia Colniță
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania.
| | - Daniel Marconi
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania
| | - Costel Sârbu
- Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 400028 Cluj-Napoca, Romania
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23
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Jin L, Wang S, Cheng Y. A Raman spectroscopy analysis method for rapidly determining saccharides and its application to monitoring the extraction process of Wenxin granule manufacturing procedure. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2020; 241:118603. [PMID: 32622050 DOI: 10.1016/j.saa.2020.118603] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 06/08/2020] [Accepted: 06/08/2020] [Indexed: 06/11/2023]
Abstract
Saccharides are the major constituents of many herbs, and they are often utilized as quality indicators of many botanical drugs, such as Chinese medicines. A method for the rapid determination of saccharides in the in-process extract solutions is beneficial for process monitoring and ensuring consistency in the quality of the end-products during the manufacturing of Chinese medicines. In this work, a method based on Raman spectroscopy and a competitive adaptive reweighted sampling-partial least squares (CARS-PLS) model was established for the rapid quantification of saccharides. The accuracy and precision of this method were confirmed by employing one monosaccharide (glucose), one oligosaccharide (maltotriose), and two polysaccharides (Codonopsis radix polysaccharides and Polygonati rhizome polysaccharides) as reference substances. The determined results correlated well with the reference values of the four substances with the coefficient of determination of prediction (Rp2) ≥ 0.9939 and the root-mean-square error of prediction (RMSEP) ≤ 1.1052 mg/mL. Then, the method was applied to monitoring the simulated extraction process for Wenxin granule manufacture using total saccharides as a quality indicator. The CARS-PLS model exhibited satisfactory fitting and predictive capability, with Rp2 and RMSEP values of 0.9743 and 1.4931 mg/mL, respectively. Our work demonstrated that Raman spectroscopy coupled with chemometrics can offer a reliable and nondestructive alternative for the determination of different types of saccharides, in addition to being useful for real-time monitoring of the extraction process during the manufacturing of Wenxin granules. The presented approach is expected to be applicable to other Chinese medicines.
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Affiliation(s)
- Lei Jin
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China
| | - Shufang Wang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China.
| | - Yiyu Cheng
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China.
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24
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Lorenz B, Ali N, Bocklitz T, Rösch P, Popp J. Discrimination between pathogenic and non-pathogenic E. coli strains by means of Raman microspectroscopy. Anal Bioanal Chem 2020; 412:8241-8247. [PMID: 33033893 PMCID: PMC7680742 DOI: 10.1007/s00216-020-02957-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/21/2020] [Accepted: 09/16/2020] [Indexed: 01/09/2023]
Abstract
Bacteria can be harmless commensals, beneficial probiotics, or harmful pathogens. Therefore, mankind is challenged to detect and identify bacteria in order to prevent or treat bacterial infections. Examples are identification of species for treatment of infection in clinics and E. coli cell counting for water quality monitoring. Finally, in some instances, the pathogenicity of a species is of interest. The main strategies to investigate pathogenicity are detection of target genes which encode virulence factors. Another strategy could be based on phenotypic identification. Raman spectroscopy is a promising phenotypic method, which offers high sensitivities and specificities for the identification of bacteria species. In this study, we evaluated whether Raman microspectroscopy could be used to determine the pathogenicity of E. coli strains. We used Raman spectra of seven non-pathogenic and seven pathogenic E. coli strains to train a PCA-SVM model. Then, the obtained model was tested by identifying the pathogenicity of three additional E. coli strains. The pathogenicity of these three strains could be correctly identified with a mean sensitivity of 77%, which is suitable for a fast screening of pathogenicity of single bacterial cells. Graphical abstract ![]()
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Affiliation(s)
- Björn Lorenz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany.,InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743, Jena, Germany
| | - Nairveen Ali
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany.,Leibniz Institute of Photonic Technology Jena Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Straße 9, 07745, Jena, Germany
| | - Thomas Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany.,Leibniz Institute of Photonic Technology Jena Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Straße 9, 07745, Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany. .,InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743, Jena, Germany.
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany.,InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743, Jena, Germany.,Leibniz Institute of Photonic Technology Jena Member of the Research Alliance "Leibniz Health Technologies", Albert-Einstein-Straße 9, 07745, Jena, Germany
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25
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Simion IM, MoŢ AC, Sârbu C. Finding specific peaks (markers) using fuzzy divisive hierarchical associative-clustering based on the chromatographic profiles of medicinal plant extracts obtained at various detection wavelengths. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:3260-3267. [PMID: 32930189 DOI: 10.1039/d0ay00295j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Advanced chemometric methods, such as fuzzy c-means (FCM), a fuzzy divisive hierarchical clustering algorithm (FDHC), and fuzzy divisive hierarchical associative-clustering (FDHAC), which offer the excellent possibility to associate each fuzzy partition of samples with a fuzzy set of characteristics (features), have been successfully applied in this study. FDHAC, a method that utilizes specific regions of chromatographic fingerprints or specific peaks as a fuzzy set of characteristics, was effectively applied to the characterization and classification of medicinal plant extracts according to their antioxidant capacities, using their chromatographic profiles monitored at 242, 260, 280, 320, 340, and 380 nm via HPLC with a multistep isocratic and gradient elution system and diode array detection (HPLC-DAD). What is quite new is the partitioning of the chromatographic retention time ranges and peaks (markers) and their association with different plant extract samples with high, moderate or low antioxidant capacity. Furthermore, the degrees of membership of fingerprints (fuzzy markers) are highly relevant with respect to the (dis)similarity of samples because they indicate both the positions and degrees of association of chromatographic peaks from different classes or individual samples. The obtained results clearly demonstrate the efficiency and information power of these advanced fuzzy methods for medicinal plant characterization and authentication, and this study generates the premise for a new chemometrics approach with high-impact for use in analytical chemistry and other fields.
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Affiliation(s)
- Ileana M Simion
- Department of Chemistry, Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, Arany Janos Str., No. 11, RO-400028 Cluj-Napoca, Romania.
| | - Augustin-C MoŢ
- Department of Chemistry, Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, Arany Janos Str., No. 11, RO-400028 Cluj-Napoca, Romania.
| | - Costel Sârbu
- Department of Chemistry, Babeş-Bolyai University, Faculty of Chemistry and Chemical Engineering, Arany Janos Str., No. 11, RO-400028 Cluj-Napoca, Romania.
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26
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Zhu Y, Zhang J, Li M, Ren H, Zhu C, Yan L, Zhao G, Zhang Q. Near-infrared spectroscopy coupled with chemometrics algorithms for the quantitative determination of the germinability of Clostridium perfringens in four different matrices. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2020; 232:117997. [PMID: 32062401 DOI: 10.1016/j.saa.2019.117997] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/21/2019] [Accepted: 12/25/2019] [Indexed: 06/10/2023]
Abstract
Clostridium perfringens (C. perfringens) has the ability to form metabolically-dormant spores that can survive food preservation processes and cause food spoilage and foodborne safety risks upon germination outgrowth. This study was conducted to investigate the effects of different AGFK concentrations (0, 50, 100, 200 mM/mL) on the spore germination of C. perfringens in four matrices, including Tris-HCl, FTG, milk, and chicken soup. C. perfringens spore germinability was investigated using near infrared spectroscopy (NIRS) combined with chemometrics. The spore germination rate (S), the OD600%, and the Ca2+-DPA% were measured using traditional spore germination methods. The results of spore germination assays showed that the optimum germination rate was obtained using 100 mM/L concentrations of AGFK in the FTG medium, and the S, OD600% and Ca2+-DPA% were 98.6%, 59.3% and 95%, respectively. The best prediction models for the S, OD600% and Ca2+-DPA% were obtained using SNV as the preprocessing method for the original spectra, with the competitive adaptive weighted resampling method (CARS) as the characteristic variables related to the selected spore germination methods from NIRS data. The results of the S showed that the optimum model was built by CARS-PLSR (RMSEV = 0.745, Rc = 0.897, RMSEP = 0.769, Rp = 0.883). For the OD600%, interval partial least squares regression (CARS-siPLS) was performed to optimize the models. The calibration yielded acceptable results (RMSEV = 0.218, Rc = 0.879, RMSEP = 0.257, Rp = 0.845). For the Ca2+-DPA%, the optimum model with CARS-siPLS yielded acceptable results (RMSEV = 44.7, Rc = 0.883, RMSEP = 50.2, Rp = 0.872). This indicated that quantitative determinations of the germinability of C. perfringens spores using NIR technology is feasible. A new method based on NIR was provided for rapid, automatic, and non-destructive determination of the germinability of C. perfringens spores.
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Affiliation(s)
- Yaodi Zhu
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
| | - Jiaye Zhang
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
| | - Miaoyun Li
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China.
| | - Hongrong Ren
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
| | - Chaozhi Zhu
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
| | - Longgnag Yan
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
| | - Gaiming Zhao
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
| | - Qiuhui Zhang
- College of Food Science and Technology, Henan Key Laboratory of Meat Processing and Quality Safety Control, Henan Agricultural University, Zhengzhou 450000, PR China
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27
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Langer J, Jimenez de Aberasturi D, Aizpurua J, Alvarez-Puebla RA, Auguié B, Baumberg JJ, Bazan GC, Bell SEJ, Boisen A, Brolo AG, Choo J, Cialla-May D, Deckert V, Fabris L, Faulds K, García de Abajo FJ, Goodacre R, Graham D, Haes AJ, Haynes CL, Huck C, Itoh T, Käll M, Kneipp J, Kotov NA, Kuang H, Le Ru EC, Lee HK, Li JF, Ling XY, Maier SA, Mayerhöfer T, Moskovits M, Murakoshi K, Nam JM, Nie S, Ozaki Y, Pastoriza-Santos I, Perez-Juste J, Popp J, Pucci A, Reich S, Ren B, Schatz GC, Shegai T, Schlücker S, Tay LL, Thomas KG, Tian ZQ, Van Duyne RP, Vo-Dinh T, Wang Y, Willets KA, Xu C, Xu H, Xu Y, Yamamoto YS, Zhao B, Liz-Marzán LM. Present and Future of Surface-Enhanced Raman Scattering. ACS NANO 2020; 14:28-117. [PMID: 31478375 PMCID: PMC6990571 DOI: 10.1021/acsnano.9b04224] [Citation(s) in RCA: 1394] [Impact Index Per Article: 348.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 09/03/2019] [Indexed: 04/14/2023]
Abstract
The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.
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Affiliation(s)
- Judith Langer
- CIC
biomaGUNE and CIBER-BBN, Paseo de Miramón 182, Donostia-San Sebastián 20014, Spain
| | | | - Javier Aizpurua
- Materials
Physics Center (CSIC-UPV/EHU), and Donostia
International Physics Center, Paseo Manuel de Lardizabal 5, Donostia-San
Sebastián 20018, Spain
| | - Ramon A. Alvarez-Puebla
- Departamento
de Química Física e Inorgánica and EMaS, Universitat Rovira i Virgili, Tarragona 43007, Spain
- ICREA-Institució
Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Baptiste Auguié
- School
of Chemical and Physical Sciences, Victoria
University of Wellington, PO Box 600, Wellington 6140, New Zealand
- The
MacDiarmid
Institute for Advanced Materials and Nanotechnology, PO Box 600, Wellington 6140, New Zealand
- The Dodd-Walls
Centre for Quantum and Photonic Technologies, PO Box 56, Dunedin 9054, New Zealand
| | - Jeremy J. Baumberg
- NanoPhotonics
Centre, Cavendish Laboratory, University
of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - Guillermo C. Bazan
- Department
of Materials and Chemistry and Biochemistry, University of California, Santa
Barbara, California 93106-9510, United States
| | - Steven E. J. Bell
- School
of Chemistry and Chemical Engineering, Queen’s
University of Belfast, Belfast BT9 5AG, United Kingdom
| | - Anja Boisen
- Department
of Micro- and Nanotechnology, The Danish National Research Foundation
and Villum Foundation’s Center for Intelligent Drug Delivery
and Sensing Using Microcontainers and Nanomechanics, Technical University of Denmark, Kongens Lyngby 2800, Denmark
| | - Alexandre G. Brolo
- Department
of Chemistry, University of Victoria, P.O. Box 3065, Victoria, BC V8W 3 V6, Canada
- Center
for Advanced Materials and Related Technologies, University of Victoria, Victoria, BC V8W 2Y2, Canada
| | - Jaebum Choo
- Department
of Chemistry, Chung-Ang University, Seoul 06974, South Korea
| | - Dana Cialla-May
- Leibniz
Institute of Photonic Technology Jena - Member of the research alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, Jena 07745, Germany
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena 07745, Germany
| | - Volker Deckert
- Leibniz
Institute of Photonic Technology Jena - Member of the research alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, Jena 07745, Germany
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena 07745, Germany
| | - Laura Fabris
- Department
of Materials Science and Engineering, Rutgers
University, 607 Taylor Road, Piscataway New Jersey 08854, United States
| | - Karen Faulds
- Department
of Pure and Applied Chemistry, University
of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, United Kingdom
| | - F. Javier García de Abajo
- ICREA-Institució
Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, Barcelona 08010, Spain
- The Barcelona
Institute of Science and Technology, Institut
de Ciencies Fotoniques, Castelldefels (Barcelona) 08860, Spain
| | - Royston Goodacre
- Department
of Biochemistry, Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB, United Kingdom
| | - Duncan Graham
- Department
of Pure and Applied Chemistry, University
of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, United Kingdom
| | - Amanda J. Haes
- Department
of Chemistry, University of Iowa, Iowa City, Iowa 52242, United States
| | - Christy L. Haynes
- Department
of Chemistry, University of Minnesota, 207 Pleasant Street SE, Minneapolis, Minnesota 55455, United States
| | - Christian Huck
- Kirchhoff
Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, Heidelberg 69120, Germany
| | - Tamitake Itoh
- Nano-Bioanalysis
Research Group, Health Research Institute, National Institute of Advanced Industrial Science and Technology, Takamatsu, Kagawa 761-0395, Japan
| | - Mikael Käll
- Department
of Physics, Chalmers University of Technology, Goteborg S412 96, Sweden
| | - Janina Kneipp
- Department
of Chemistry, Humboldt-Universität
zu Berlin, Brook-Taylor-Str. 2, Berlin-Adlershof 12489, Germany
| | - Nicholas A. Kotov
- Department
of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Hua Kuang
- Key Lab
of Synthetic and Biological Colloids, Ministry of Education, International
Joint Research Laboratory for Biointerface and Biodetection, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key
Laboratory of Food Science and Technology, Jiangnan University, JiangSu 214122, China
| | - Eric C. Le Ru
- School
of Chemical and Physical Sciences, Victoria
University of Wellington, PO Box 600, Wellington 6140, New Zealand
- The
MacDiarmid
Institute for Advanced Materials and Nanotechnology, PO Box 600, Wellington 6140, New Zealand
- The Dodd-Walls
Centre for Quantum and Photonic Technologies, PO Box 56, Dunedin 9054, New Zealand
| | - Hiang Kwee Lee
- Division
of Chemistry and Biological Chemistry, School of Physical and Mathematical
Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore
- Department
of Materials Science and Engineering, Stanford
University, Stanford, California 94305, United States
| | - Jian-Feng Li
- State Key
Laboratory of Physical Chemistry of Solid Surfaces, Collaborative
Innovation Center of Chemistry for Energy Materials, MOE Key Laboratory
of Spectrochemical Analysis & Instrumentation, Department of Chemistry,
College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Xing Yi Ling
- Division
of Chemistry and Biological Chemistry, School of Physical and Mathematical
Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore
| | - Stefan A. Maier
- Chair in
Hybrid Nanosystems, Nanoinstitute Munich, Faculty of Physics, Ludwig-Maximilians-Universität München, Munich 80539, Germany
| | - Thomas Mayerhöfer
- Leibniz
Institute of Photonic Technology Jena - Member of the research alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, Jena 07745, Germany
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena 07745, Germany
| | - Martin Moskovits
- Department
of Chemistry & Biochemistry, University
of California Santa Barbara, Santa Barbara, California 93106-9510, United States
| | - Kei Murakoshi
- Department
of Chemistry, Faculty of Science, Hokkaido
University, North 10 West 8, Kita-ku, Sapporo,
Hokkaido 060-0810, Japan
| | - Jwa-Min Nam
- Department
of Chemistry, Seoul National University, Seoul 08826, South Korea
| | - Shuming Nie
- Department of Bioengineering, University of Illinois at Urbana-Champaign, 1406 W. Green Street, Urbana, Illinois 61801, United States
| | - Yukihiro Ozaki
- Department
of Chemistry, School of Science and Technology, Kwansei Gakuin University, Sanda, Hyogo 669-1337, Japan
| | | | - Jorge Perez-Juste
- Departamento
de Química Física and CINBIO, University of Vigo, Vigo 36310, Spain
| | - Juergen Popp
- Leibniz
Institute of Photonic Technology Jena - Member of the research alliance “Leibniz Health Technologies”, Albert-Einstein-Str. 9, Jena 07745, Germany
- Institute
of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena 07745, Germany
| | - Annemarie Pucci
- Kirchhoff
Institute for Physics, University of Heidelberg, Im Neuenheimer Feld 227, Heidelberg 69120, Germany
| | - Stephanie Reich
- Department
of Physics, Freie Universität Berlin, Berlin 14195, Germany
| | - Bin Ren
- State Key
Laboratory of Physical Chemistry of Solid Surfaces, Collaborative
Innovation Center of Chemistry for Energy Materials, MOE Key Laboratory
of Spectrochemical Analysis & Instrumentation, Department of Chemistry,
College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - George C. Schatz
- Department
of Chemistry, Northwestern University, Evanston, Illinois 60208-3113, United States
| | - Timur Shegai
- Department
of Physics, Chalmers University of Technology, Goteborg S412 96, Sweden
| | - Sebastian Schlücker
- Physical
Chemistry I, Department of Chemistry and Center for Nanointegration
Duisburg-Essen, University of Duisburg-Essen, Essen 45141, Germany
| | - Li-Lin Tay
- National
Research Council Canada, Metrology Research
Centre, Ottawa K1A0R6, Canada
| | - K. George Thomas
- School
of Chemistry, Indian Institute of Science
Education and Research Thiruvananthapuram, Vithura Thiruvananthapuram 695551, India
| | - Zhong-Qun Tian
- State Key
Laboratory of Physical Chemistry of Solid Surfaces, Collaborative
Innovation Center of Chemistry for Energy Materials, MOE Key Laboratory
of Spectrochemical Analysis & Instrumentation, Department of Chemistry,
College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Richard P. Van Duyne
- Department
of Chemistry, Northwestern University, Evanston, Illinois 60208-3113, United States
| | - Tuan Vo-Dinh
- Fitzpatrick
Institute for Photonics, Department of Biomedical Engineering, and
Department of Chemistry, Duke University, 101 Science Drive, Box 90281, Durham, North Carolina 27708, United States
| | - Yue Wang
- Department
of Chemistry, College of Sciences, Northeastern
University, Shenyang 110819, China
| | - Katherine A. Willets
- Department
of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Chuanlai Xu
- Key Lab
of Synthetic and Biological Colloids, Ministry of Education, International
Joint Research Laboratory for Biointerface and Biodetection, Jiangnan University, Wuxi, Jiangsu 214122, China
- State Key
Laboratory of Food Science and Technology, Jiangnan University, JiangSu 214122, China
| | - Hongxing Xu
- School
of Physics and Technology and Institute for Advanced Studies, Wuhan University, Wuhan 430072, China
| | - Yikai Xu
- School
of Chemistry and Chemical Engineering, Queen’s
University of Belfast, Belfast BT9 5AG, United Kingdom
| | - Yuko S. Yamamoto
- School
of Materials Science, Japan Advanced Institute
of Science and Technology, Nomi, Ishikawa 923-1292, Japan
| | - Bing Zhao
- State Key
Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun 130012, China
| | - Luis M. Liz-Marzán
- CIC
biomaGUNE and CIBER-BBN, Paseo de Miramón 182, Donostia-San Sebastián 20014, Spain
- Ikerbasque,
Basque Foundation for Science, Bilbao 48013, Spain
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28
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Maeda Y, Sugiyama Y, Lim TK, Harada M, Yoshino T, Matsunaga T, Tanaka T. Rapid discrimination of fungal species by the colony fingerprinting. Biosens Bioelectron 2019; 146:111747. [PMID: 31586763 DOI: 10.1016/j.bios.2019.111747] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 09/20/2019] [Accepted: 09/30/2019] [Indexed: 12/20/2022]
Abstract
The contamination of foods and beverages by fungi is a severe health hazard. The rapid identification of fungi species in contaminated goods is important to avoid further contamination. To this end, we developed a fungal discrimination method based on the bioimage informatics approach of colony fingerprinting. This method involves imaging and visualizing microbial colonies (referred to as colony fingerprints) using a lens-less imaging system. Subsequently, the quantitative image features were extracted as discriminative parameters and subjected to analysis using machine learning approaches. Colony fingerprinting has been previously found to be a promising approach to discriminate bacteria. In the present proof-of-concept study, we tested whether this method is also useful for fungal discrimination. As a result, 5 fungi belonging to the Aspergillus, Penicilium, Eurotium, Alternaria, and Fusarium genera were successfully discriminated based on the extracted parameters, including the number of hyphae and their branches, and their intensity distributions on the images. The discrimination of 6 closely-related Aspergillus spp. was also demonstrated using additional parameters. The cultivation time required to generate the fungal colonies with a sufficient size for colony fingerprinting was less than 48 h, shorter than those for other discrimination methods, including MALDI-TOF-MS. In addition, colony fingerprinting did not require any cumbersome pre-treatment steps prior to discrimination. Colony fingerprinting is promising for the rapid and easy discrimination of fungi for use in the ensuring the safety of food manufacturing.
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Affiliation(s)
- Yoshiaki Maeda
- Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan
| | - Yui Sugiyama
- Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan
| | - Tae-Kyu Lim
- Malcom Co., Ltd, 4-15-10, Honmachi, Shibuya-ku, Tokyo, 151-0071, Japan
| | - Manabu Harada
- Malcom Co., Ltd, 4-15-10, Honmachi, Shibuya-ku, Tokyo, 151-0071, Japan
| | - Tomoko Yoshino
- Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan
| | - Tadashi Matsunaga
- Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan; Waseda Research Institute for Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, 169-8555, Japan
| | - Tsuyoshi Tanaka
- Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan.
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Gherman AMR, Dina NE, Chiș V, Wieser A, Haisch C. Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 222:117223. [PMID: 31177002 DOI: 10.1016/j.saa.2019.117223] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 05/29/2019] [Accepted: 05/29/2019] [Indexed: 06/09/2023]
Abstract
Candida species are becoming one of the pathogens developing antifungal resistance due to inappropriate treatment and overuse of antimycotic drugs in building construction and agriculture. Further, fungal infections are often difficult to detect, also due to slow in vitro growth of the organisms from clinical specimens. Thus, fast detection and discrimination of yeast cells in direct patient materials is essential for an adequate treatment and success rate. In this work, we investigated Candida species isolated from patients, by using surface-enhanced Raman scattering (SERS) combined with computational spectroscopy tools, aiming to detect and discriminate between the three considered species, Candida albicans, Candida glabrata, and Candida parapsilosis. Density functional theory (DFT) was used to calculate Raman spectra of yeasts' main cell wall components for elucidating the origin of the observed bands. Accurate assignments of normal modes helped for a better understanding of the interaction between silver nanoparticles with yeasts' cell wall. Further, SERS spectra were used as samples in a database on which we performed multivariate analyses. By Principal component analysis (PCA), we obtained a maximum variation of 79% between the three samples. Linear discriminant analysis (LDA) was successfully used to discriminate between the three species.
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Affiliation(s)
- Ana Maria Raluca Gherman
- Department of Molecular and Biomolecular Physics, National Institute of R&D of Isotopic and Molecular Technologies, Donat 67-103, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania
| | - Nicoleta Elena Dina
- Department of Molecular and Biomolecular Physics, National Institute of R&D of Isotopic and Molecular Technologies, Donat 67-103, 400293 Cluj-Napoca, Romania.
| | - Vasile Chiș
- Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania
| | - Andreas Wieser
- Max von Pettenkofer-Institut für Hygiene und Medizinische Mikrobiologie, Ludwig-Maximilians-University, Marchinoninistr. 17, 82377 Munich, Germany; Division of Infectious Diseases and Tropical Medicine, Medical Center of the University of Munich (LMU), Leopoldstr. 5, 80802 Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, D-80802 Munich, Germany
| | - Christoph Haisch
- Chair for Analytical Chemistry, Institute of Hydrochemistry, Technische Universität München, Marchioninistrasse 17, 81377 Munich, Germany
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Feher I, Magdas DA, Dehelean A, Sârbu C. Characterization and classification of wines according to geographical origin, vintage and specific variety based on elemental content: a new chemometric approach. Journal of Food Science and Technology 2019; 56:5225-5233. [PMID: 31749469 DOI: 10.1007/s13197-019-03991-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 07/24/2019] [Accepted: 07/30/2019] [Indexed: 10/26/2022]
Abstract
A highly informative chemometric approach using elemental data to distinguish and classify wine samples according to different criteria was successfully developed. The robust chemometric methods, such fuzzy principal component analysis (FPCA), FPCA combined with linear discriminant analysis (LDA), namely FPCA-LDA and mainly fuzzy divisive hierarchical associative-clustering (FDHAC), including also classical methods (HCA, PCA and PCA-LDA) were efficaciously applied for characterization and classification of white wines according to the geographical origin, vintage or specific variety. The correct rate of classification applying LDA was 100% in all cases, but more compact groups have been obtained for FPCA scores. A similar separation of samples resulted also when the FDHAC was employed. In addition, FDHAC offers an excellent possibility to associate each fuzzy partition of wine samples to a fuzzy set of specific characteristics, finding in this way very specific elemental contents and fuzzy markers according to the degrees of membership (DOMs).
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Affiliation(s)
- Ioana Feher
- 1National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania
| | - Dana Alina Magdas
- 1National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania
| | - Adriana Dehelean
- 1National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania
| | - Costel Sârbu
- 2Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 11 Arany János, 400028 Cluj-Napoca, Romania
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Enhancing Disease Diagnosis: Biomedical Applications of Surface-Enhanced Raman Scattering. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9061163] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Surface-enhanced Raman scattering (SERS) has recently gained increasing attention for the detection of trace quantities of biomolecules due to its excellent molecular specificity, ultrasensitivity, and quantitative multiplex ability. Specific single or multiple biomarkers in complex biological environments generate strong and distinct SERS spectral signals when they are in the vicinity of optically active nanoparticles (NPs). When multivariate chemometrics are applied to decipher underlying biomarker patterns, SERS provides qualitative and quantitative information on the inherent biochemical composition and properties that may be indicative of healthy or diseased states. Moreover, SERS allows for differentiation among many closely-related causative agents of diseases exhibiting similar symptoms to guide early prescription of appropriate, targeted and individualised therapeutics. This review provides an overview of recent progress made by the application of SERS in the diagnosis of cancers, microbial and respiratory infections. It is envisaged that recent technology development will help realise full benefits of SERS to gain deeper insights into the pathological pathways for various diseases at the molecular level.
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32
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Wang Y, Yan C, Li C, Lu Z, Ma C, Yan Y, Zhang Y. Charge Transfer Tuned by the Surrounding Dielectrics in TiO₂-Ag Composite Arrays. NANOMATERIALS (BASEL, SWITZERLAND) 2018; 8:E1019. [PMID: 30544495 PMCID: PMC6315537 DOI: 10.3390/nano8121019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 11/27/2018] [Accepted: 12/04/2018] [Indexed: 12/16/2022]
Abstract
TiO₂/Ag bilayer films sputtered onto a 2D polystyrene (PS) bead array in a magnetron sputtering system were found to form a nanocap-shaped nanostructure composed of a TiO₂-Ag composite on each PS bead, in which the Ag nanoparticles were trapped partially or fully in the TiO₂ matrix, depending on the TiO₂ thickness. X-ray Photoelectron Spectroscopy (XPS) results showed the opposite shifts of binding energy for Ti 2p and Ag 3d, indicating the transfer of electrons from metallic Ag to TiO₂ owing to the Ag-O-TiO₂ composite formation. UV-Vis absorption spectra showed the blue shifts of the surface plasma resonance peaks, and the maximum absorption peak intensity was obtained for TiO₂ at 30 nm. The surface-enhanced Raman scattering (SERS) peak intensity first increased and then decreased when the TiO₂ thickness changed. The observations of SERS, XPS, and UV-Vis absorption spectra were explained by the dependency of the charge-transfer process on TiO₂ thickness, which was ascribed to the changing dielectric properties in the metal/semiconductor system.
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Affiliation(s)
- Yaxin Wang
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Chao Yan
- Zhonggong Education and Technology Co., Ltd., Changchun 130000, China.
| | - Chunxiang Li
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Ziyang Lu
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Changchang Ma
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Yongsheng Yan
- School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Yongjun Zhang
- College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.
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Jia M, Li S, Zang L, Lu X, Zhang H. Analysis of Biomolecules Based on the Surface Enhanced Raman Spectroscopy. NANOMATERIALS (BASEL, SWITZERLAND) 2018; 8:E730. [PMID: 30223597 PMCID: PMC6165412 DOI: 10.3390/nano8090730] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 09/10/2018] [Accepted: 09/14/2018] [Indexed: 12/24/2022]
Abstract
Analyzing biomolecules is essential for disease diagnostics, food safety inspection, environmental monitoring and pharmaceutical development. Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for detecting biomolecules due to its high sensitivity, rapidness and specificity in identifying molecular structures. This review focuses on the SERS analysis of biomolecules originated from humans, animals, plants and microorganisms, combined with nanomaterials as SERS substrates and nanotags. Recent advances in SERS detection of target molecules were summarized with different detection strategies including label-free and label-mediated types. This comprehensive and critical summary of SERS analysis of biomolecules might help researchers from different scientific backgrounds spark new ideas and proposals.
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Affiliation(s)
- Min Jia
- Shandong Provincial Key Laboratory of Animal Resistance Biology, Institute of Biomedical Sciences, Key Laboratory of Food Nutrition and Safety of Shandong Normal University, College of Life Science, Shandong Normal University, Jinan 250014, China.
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University (BTBU), Beijing 100048, China.
| | - Shenmiao Li
- Food, Nutrition and Health Program, Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| | - Liguo Zang
- Shandong Provincial Key Laboratory of Animal Resistance Biology, Institute of Biomedical Sciences, Key Laboratory of Food Nutrition and Safety of Shandong Normal University, College of Life Science, Shandong Normal University, Jinan 250014, China.
| | - Xiaonan Lu
- Food, Nutrition and Health Program, Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| | - Hongyan Zhang
- Shandong Provincial Key Laboratory of Animal Resistance Biology, Institute of Biomedical Sciences, Key Laboratory of Food Nutrition and Safety of Shandong Normal University, College of Life Science, Shandong Normal University, Jinan 250014, China.
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