Fitting an Optical Fiber Background with a Weighted Savitzky–Golay Smoothing Filter for Raman Spectroscopy

2018 ◽  
Vol 72 (11) ◽  
pp. 1632-1644 ◽  
Author(s):  
Jie Huang ◽  
Tielin Shi ◽  
Bo Gong ◽  
Xiaoping Li ◽  
Guanglan Liao ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Optical Fiber ◽  
Raman Spectra ◽  
Pearson Correlation ◽  
Similarity Index ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Spectrum ◽  
Background Spectrum ◽  
Filter Model ◽  
Smoothing Filter

The Raman background arising from optical fiber materials poses a critical problem for fiber optic surface-enhanced Raman spectroscopy (SERS). A novel filter is developed to fit the optical fiber background from the measured SERS spectrum of the target sample. The general model of the filter is built by incorporating a weighted term of matching the similarity between the estimated background spectrum and the measured background spectrum into the classic Savitzky–Golay (SG) smoothing filter model. Through respectively selecting Euclidean cosine coefficient (ECos) and Pearson correlation coefficient (PCor) as the similarity index, two different models of the weighted SG smoothing filter are derived and named as SG-ECos and SG-PCor accordingly. Furthermore, the algorithm is presented, implemented, successfully applied to experimentally measured SERS spectra of rhodamine 6G and crystal violet, and validated with mathematically simulated Raman spectra. Experimental and simulation results show that the SG-ECos filter is effective, fast, flexible, and of certain anti-noise capability in background fitting. It is suggested that the proposed filter may be also applicable for other Raman spectra measurements to remove spectral contaminants originated from sampling substrates such as glass slides.

Surface-enhanced Raman spectroscopy measurement of cancerous cells with optical fiber sensor

2014 ◽  
Vol 12 (s1) ◽  
pp. S13001-313003 ◽  
Author(s):  
Shupeng Liu Shupeng Liu ◽  
Lianxin Li Lianxin Li ◽  
Zhenyi Chen Zhenyi Chen ◽  
Na Chen Na Chen ◽  
Zhangmin Dai Zhangmin Dai ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Optical Fiber ◽  
Optical Fiber Sensor ◽  
Surface Enhanced Raman Spectroscopy ◽  
Fiber Sensor ◽  
Spectroscopy Measurement ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Cancerous Cells

Micron Surface-Enhanced Raman Spectroscopy of Intact Biological Organisms and Model Systems

1994 ◽  
Vol 48 (5) ◽  
pp. 545-548 ◽  
Author(s):  
Elizabeth A. Todd ◽  
Michael D. Morris
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectra ◽  
Biological Membranes ◽  
Surface Enhanced Raman Spectroscopy ◽  
Model Systems ◽  
Zebrafish Embryos ◽  
Filter Membrane ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Biological Organisms

Surface-enhanced Raman spectra have been obtained within intact zebrafish embryos and inside the 500-fL pores of a Nucleopore filter membrane with the use of coated microelectrodes with 1–3 μm active silver tip diameters. The spectra obtained demonstrate the microelectrode's ability to penetrate biological membranes as well as restricted volumes.

scholarly journals SERS study on myeloperoxidase and its immunocomplex: Identification of binding interactions

2010 ◽  
Vol 24 (3-4) ◽  
pp. 183-190
Author(s):  
Elisabeth S. Papazoglou ◽  
Sundar Babu ◽  
David R. Hansberry ◽  
Sakya Mohapatra ◽  
Chirag Patel
Keyword(s):  
Amino Acids ◽  
Raman Spectroscopy ◽  
Conformational Changes ◽  
Surface Enhanced Raman Spectroscopy ◽  
Biological Molecules ◽  
Sers Spectrum ◽  
Amino Acid Residues ◽  
Igg Antibodies ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Surface Enhanced Raman Spectroscopy (SERS) has demonstrated significant benefit in the identification of biological molecules. In this paper we have examined how to identify and differentiate the 150 kDa protein myeloperoxidase (MPO) from its corresponding antibody (Ab) and their immunocomplex through the use of SERS. The SERS signal of these biological molecules was enabled by 40 nm gold nanoparticles. The SERS spectra for both MPO and the Ab (an IgG molecule) demonstrated results consistent with previous published work on the Raman spectra of MPO and IgG antibodies. The immunocomplex SERS spectra showed peak shifts and intensity variations that could be attributed to conformational changes that occur during immunocomplex formation. Several key spectral areas have been identified which correspond to specific amino acids being shielded from undergoing resonance while new amino acid residues are made visible in the SERS spectrum of the immunocomplex and could be a result of conformational binding. These results indicate that SERS can be used to identify binding events and distinguish an immunocomplex from its individual components.

scholarly journals Deep Convolutional Neural Networks as a Unified Solution for Raman Spectroscopy-Based Classification in Biomedical Applications

2021 ◽  
Author(s):  
Mohammadrahim Kazemzadeh ◽  
Colin Hisey ◽  
Kamran Zargar ◽  
Peter Xu ◽  
Neil Broderick
Keyword(s):  
Machine Learning ◽  
Raman Spectroscopy ◽  
Raman Spectra ◽  
Biomedical Applications ◽  
Data Augmentation ◽  
Surface Enhanced Raman Spectroscopy ◽  
Machine Learning Algorithms ◽  
Cancer Tissue ◽  
Deep Convolutional Neural Networks ◽  
Surface Enhanced Raman

<div>Machine learning has shown great potential for classifying diverse samples in biomedical applications based on their Raman spectra. However, the acquired spectra typically require several preprocessing steps before standard machine learning algorithms can accurately and reliably classify them. To simplify this workflow and enable future growth of this technology, we present a unified solution for classifying biological Raman spectra without any need of prepossessing, including denoising and baseline establishment. This method is developed based on a custom version of a convolutional neural network (CNN) elicited from ResNet architecture, combined with our proposed data augmentation technique. The superiority of this method compared to conventional classification techniques is shown by applying it to Raman spectra of different grades of bladder cancer tissue and surface enhanced Raman spectroscopy (SERS) spectra of various strains of E. Coli extracellular vesicles (EVs). These results show that our method is far more robust compared to its conventional counterparts when dealing with the various kinds of spectral baselines produced by different Raman spectrometers.</div>

scholarly journals Identifying and detecting Entomopathogenic fungi using Surface-enhanced Raman spectroscopy / Identificação e detecção de fungos entomopatogênicos utilizando Superficie-enhanced Raman espalhamento

2021 ◽  
Vol 4 (4) ◽  
pp. 4833-4851
Author(s):  
Javier Christian Ramirez Perez ◽  
Tatiana Alves Dos Reis ◽  
Marcia de Almeida Rizzutto
Keyword(s):  
Raman Spectroscopy ◽  
Entomopathogenic Fungi ◽  
Insect Pests ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Spectrum ◽  
Natural Ecosystem ◽  
Fungal Entomopathogens ◽  
Short Period ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

In the natural ecosystem, fungal entomopathogens are the most efficient biocontrol agents against insect pests. In this study we offer an alternative for conventional fungal diagnostic, Surface-enhanced Raman spectroscopy (SERS) technique combine with principal component analysis (PCA) for detection and identification three entomopathogenic fungi, namely, IBCB 66 Beauveria bassiana, IBCB 130 Isaria fumosorosea, and IBCB 425 Metarhizium anisopliae. Using a simple preparation approach, highly active silver nanoparticles suitable for detecting complex biomolecules were produced for application in the SERS technique. Entomopathogens fungi produced highly enhanced and reproducible Raman signals based on their biochemical composition due to the high density of hot spots at the confluence of silver nano-aggregates, allowing the three entomopathogens species to be differentiated in the SERS spectrum fingerprint region, 550-1700 cm-1. The SERS method, along with PCA analysis, accounted for over 99 % of total variance and allowed for very high probability discrimination between the three entomopathogens, allowing taxonomic affiliation to be determined in a short period of time.  These findings suggest that the SERS methodology can be used to develop a new, fast, accurate, and cost-effective diagnostic method for fungal entomopathogens.

scholarly journals Simultaneous FTIR and Raman Spectroscopy in Endometrial Atypical Hyperplasia and Cancer

2020 ◽  
Vol 21 (14) ◽  
pp. 4828
Author(s):  
Edyta Barnas ◽  
Joanna Skret-Magierlo ◽  
Andrzej Skret ◽  
Ewa Kaznowska ◽  
Joanna Depciuch ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Endometrial Cancer ◽  
Raman Spectra ◽  
Pearson Correlation ◽  
Objective Evaluation ◽  
Atypical Hyperplasia ◽  
Multidimensional Analysis ◽  
Control Group ◽  
Cancer Tissues ◽  
Ftir And Raman Spectroscopy

Currently, endometrial carcinoma (EC) is the most common genital cancer in high-income countries. Some types of endometrial hyperplasia (EH) may be progressing to this malignancy. The diagnosis of EC and EH is based on time consuming histopathology evaluation, which is subjective and causes discrepancies in reassessment. Therefore, there is a need to create methods of objective evaluation allowing the diagnosis of early changes. The study aimed to simultaneously asses Fourier Transform Infrared (FTIR) and Raman spectroscopy combined with multidimensional analysis to identify the tissues of endometrial cancer, atypical hyperplasia and the normal control group, and differentiate them. The results of FTIR and Raman spectroscopy revealed quantitative and qualitative changes in the nucleic acid and protein in the groups of cancer and atypical hyperplasia, in comparison with the control group. Changes in the lipid region were also observed in Raman spectra. Pearson correlation coefficient demonstrated a statistically significant correlation between Raman spectra for the cancer and atypical hyperplasia groups (0.747, p < 0.05) and for atypical hyperplasia and the controls (0.507, p < 0.05), while FTIR spectra demonstrated a statistically significant positive correlation for the same group as in Raman data and for the control and cancer groups (0.966, p < 0.05). To summarize, the method of spectroscopy enables differentiation of atypical hyperplasia and endometrial cancer tissues from the physiological endometrial tissue.

Raman Spectroscopy over Optical Fibers with the Use of a Near-IR FT Spectrometer

1988 ◽  
Vol 42 (8) ◽  
pp. 1558-1563 ◽  
Author(s):  
D. D. Archibald ◽  
L. T. Lin ◽  
D. E. Honigs
Keyword(s):  
Raman Spectroscopy ◽  
Optical Fiber ◽  
Optical Fibers ◽  
Scattered Light ◽  
Background Spectrum ◽  
Excitation Light ◽  
Analyte Signal ◽  
Near Ir ◽  
Potential Applications ◽  
Ft Ir

A commercial Fourier transform infrared (FT-IR) spectrometer was modified for remote near-IR Raman spectroscopy. In one configuration, a single optical fiber was used to guide the excitation light to the specimen and to collect scattered light from the specimen. In an alternative configuration, separate fibers were used for excitation and collection. The optical fiber probes were used to record the Raman spectra of both liquid and solid specimens. The Raman scattering of the optical fibers interfered with the analyte signal. This fiber interference was affected by the optical properties of the specimen and the optical sampling configuration. These interferences were partially removed by subtracting a background spectrum. Potential applications and improvements are discussed.

Potential-Averaged Surface-Enhanced Raman Spectroscopy

1996 ◽  
Vol 50 (12) ◽  
pp. 1569-1577 ◽  
Author(s):  
Z. Q. Tian ◽  
W. H. Li ◽  
B. W. Mao ◽  
S. Z. Zou ◽  
J. S. Gao
Keyword(s):  
Raman Spectroscopy ◽  
Active Sites ◽  
Single Channel ◽  
Pulse Height ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Spectrum ◽  
Surface Species ◽  
Electrode Potentials ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

This paper describes a novel technique called potential-averaged surface-enhanced Raman spectroscopy (PASERS) which has several advantages over SERS. A PASERS spectrum is acquired when the electrode is rapidly modulated between two potentials by applying a square-wave voltage. The potential-averaged SERS spectrum contains all the information on the surface species at the two modulated potentials, and each individual SERS spectrum can then be extracted by deconvolution. By properly choosing the two modulating potentials, one can obtain SERS spectra of surface species at electrode potentials where SERS-active sites are normally unstable. PASERS also leads to a unique way of studying complex interfacial kinetic processes by controlling the voltage pulse height, frequency, and shape. Moreover, the measurement of time-resolved spectra in the very low vibrational frequency region can be achieved by PASERS with the use of a conventional scanning spectrometer with a single-channel detector. In this paper, the main advantages of PASERS are illustrated by studying two typical SERS systems, i.e., thiocyanate ion and thiourea adsorbed at silver electrodes, respectively. It is shown that the potential-averaging method can be applied as a common method to many other existing spectroelectrochemical techniques.

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