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Molecules
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Raman Spectroscopy: An Important Technique in Medicine, Agriculture, and Biochemistry
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Raman Spectroscopy: An Important Technique in Medicine, Agriculture, and Biochemistry

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: closed (1 August 2019) | Viewed by 14349

Special Issue Editor

Dr. Dmitry Kurouski

E-Mail Website
Guest Editor
Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA
Interests: nanoscale vibrational spectroscopy, including tip-enhanced Raman spectroscopy (TERS) and atomic force microscope infrared spectroscopy (AFM-IR); Raman-based plant disease diagnostics; electrochemistry; plasmonics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Raman spectroscopy (RS) is a modern analytical technique that provides information about molecular vibrations and consequently the structure of the analyzed specimen. The Raman effect is based on inelastic scattering of photons by molecules that are being excited to higher vibrational or rotational states. RS has been broadly used in various research fields ranging from forensic analysis of bodily fluids and food science to biochemistry and solid-state physics. In the last decade, several companies have developed hand-held Raman spectrometers. This has enabled utilization of RS directly in the field for applications, such as forensics, agriculture, and mineralogy.

In 1974, Fleischmann and co-authors reported that Raman spectra of pyridine adsorbed on a rough Ag surface had an unexpectedly high intensity. Inspired by this work, Van Duyne and Jeanmaire investigated the origin of such drastic enhancement of Raman spectra, suggesting that it could be caused by electrochemical interfacial field gradient. Several years later, Van Duyne and Schatz proposed “electromagnetic theory” of the surface-enhanced Raman scattering (SERS) effect. It has been suggested that SERS originated from the intensity anomaly, which occurred when the sum of the dipole induced in the adsorbed molecule was added to its image in the metal, at the limit of zero separation between the two. During the last decade, SERS has been actively developed into a robust tool that enables high sensitivity and specificity in the detection of analytes. These advantages, together with the development of inexpensive and effective SERS substrates, have caused SERS to be broadly used in various research fields, such as biochemistry, cell biology, and catalysis.

RS has been also coupled to scanning probe microscope, which resulted in development of tip-enhanced Raman spectroscopy (TERS), a technique that has nanoscale spatial resolution and single-molecule sensitivity. The substrate generality of TERS has already been utilized to investigate various topics in biology and surface chemistry, such as detecting cytochrome c oxidation in mitochondria, monitoring catalytic reactions, imaging mixed polymer surfaces, and identification of colorants directly in artwork.

This journal issue aims to attract interest of scientists to RS and related spectroscopic techniques. It also aims to demonstrate advantages and the most recent achievements of RS in medicine, agriculture and biochemistry.

Dr. Dmitry Kurouski
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Raman spectroscopy
  • Surface-enhanced Raman spectroscopy (SERS)
  • Tip-enhanced Raman spectroscopy (TERS)
  • Nanoparticles and SERS-substrates
  • Plasmonics
  • Disease and pathogen detection
  • Structural characterization

Published Papers (3 papers)

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Research

15 pages, 4473 KiB  
Article
Line Scan Raman Microspectroscopy for Label-Free Diagnosis of Human Pituitary Biopsies
by Daniela Bovenkamp, Alexander Micko, Jeremias Püls, Fabian Placzek, Romana Höftberger, Greisa Vila, Rainer Leitgeb, Wolfgang Drexler, Marco Andreana, Stefan Wolfsberger and Angelika Unterhuber
Molecules 2019, 24(19), 3577; https://doi.org/10.3390/molecules24193577 - 04 Oct 2019
Cited by 7 | Viewed by 3500
Abstract
Pituitary adenomas are neoplasia of the anterior pituitary gland and can be subdivided into hormone-producing tumors (lactotroph, corticotroph, gonadotroph, somatotroph, thyreotroph or plurihormonal) and hormone-inactive tumors (silent or null cell adenomas) based on their hormonal status. We therefore developed a line scan Raman [...] Read more.
Pituitary adenomas are neoplasia of the anterior pituitary gland and can be subdivided into hormone-producing tumors (lactotroph, corticotroph, gonadotroph, somatotroph, thyreotroph or plurihormonal) and hormone-inactive tumors (silent or null cell adenomas) based on their hormonal status. We therefore developed a line scan Raman microspectroscopy (LSRM) system to detect, discriminate and hyperspectrally visualize pituitary gland from pituitary adenomas based on molecular differences. By applying principal component analysis followed by a k-nearest neighbor algorithm, specific hormone states were identified and a clear discrimination between pituitary gland and various adenoma subtypes was achieved. The classifier yielded an accuracy of 95% for gland tissue and 84–99% for adenoma subtypes. With an overall accuracy of 92%, our LSRM system has proven its potential to differentiate pituitary gland from pituitary adenomas. LSRM images based on the presence of specific Raman bands were created, and such images provided additional insight into the spatial distribution of particular molecular compounds. Pathological states could be molecularly differentiated and characterized with texture analysis evaluating Grey Level Cooccurrence Matrices for each LSRM image, as well as correlation coefficients between LSRM images. Full article
(This article belongs to the Special Issue Raman Spectroscopy: An Important Technique in Medicine, Agriculture, and Biochemistry)
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11 pages, 2800 KiB  
Article
Detection of Pirimiphos-Methyl in Wheat Using Surface-Enhanced Raman Spectroscopy and Chemometric Methods
by Shizhuang Weng, Shuan Yu, Ronglu Dong, Jinling Zhao and Dong Liang
Molecules 2019, 24(9), 1691; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24091691 - 30 Apr 2019
Cited by 15 | Viewed by 3006
Abstract
Pesticide residue detection is a hot issue in the quality and safety of agricultural grains. A novel method for accurate detection of pirimiphos-methyl residues in wheat was developed using surface-enhanced Raman spectroscopy (SERS) and chemometric methods. A simple pretreatment method was conducted to [...] Read more.
Pesticide residue detection is a hot issue in the quality and safety of agricultural grains. A novel method for accurate detection of pirimiphos-methyl residues in wheat was developed using surface-enhanced Raman spectroscopy (SERS) and chemometric methods. A simple pretreatment method was conducted to extract pirimiphos-methyl residue from wheat samples, and highly effective gold nanorods were prepared for SERS measurement. Raman peaks assignment was calculated using density functional theory. The Raman signal of pirimiphos-methyl can be detected when the concentrations of residue in wheat extraction solution and contaminated wheat is as low as 0.2 mg/L and 0.25 mg/L, respectively. Quantification of pirimiphos-methyl was performed by applying regression models developed by partial least squares regression, support vector machine regression and random forest with principal component analysis using different preprocessed methods. As for the contaminated wheat samples, the relative deviation between gas chromatography-mass spectrometry value and predicted value is in the range of 0.10%–6.63%, and predicted recovery is 94.12%–106.63%, ranging from 23.93 mg/L to 0.25 mg/L. Results demonstrated that the proposed SERS method is an effective and efficient analytical tool for detecting pirimiphos-methyl in wheat with high accuracy and excellent sensitivity. Full article
(This article belongs to the Special Issue Raman Spectroscopy: An Important Technique in Medicine, Agriculture, and Biochemistry)
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14 pages, 2864 KiB  
Communication
A Noninvasive Accurate Measurement of Blood Glucose Levels with Raman Spectroscopy of Blood in Microvessels
by Nan Li, Hang Zang, Huimin Sun, Xianzhi Jiao, Kangkang Wang, Timon Cheng-Yi Liu and Yaoyong Meng
Molecules 2019, 24(8), 1500; https://0-doi-org.brum.beds.ac.uk/10.3390/molecules24081500 - 17 Apr 2019
Cited by 55 | Viewed by 7377
Abstract
Raman spectra of human skin obtained by laser excitation have been used to non-invasively detect blood glucose. In previous reports, however, Raman spectra thus obtained were mainly derived from the epidermis and interstitial fluid as a result of the shallow penetration depth of [...] Read more.
Raman spectra of human skin obtained by laser excitation have been used to non-invasively detect blood glucose. In previous reports, however, Raman spectra thus obtained were mainly derived from the epidermis and interstitial fluid as a result of the shallow penetration depth of lasers in skin. The physiological process by which glucose in microvessels penetrates into the interstitial fluid introduces a time delay, which inevitably introduces errors in transcutaneous measurements of blood glucose. We focused the laser directly on the microvessels in the superficial layer of the human nailfold, and acquired Raman spectra with multiple characteristic peaks of blood, which indicated that the spectra obtained predominantly originated from blood. Incorporating a multivariate approach combining principal component analysis (PCA) and back propagation artificial neural network (BP-ANN), we performed noninvasive blood glucose measurements on 12 randomly selected volunteers, respectively. The mean prediction performance of the 12 volunteers was obtained as an RMSEP of 0.45 mmol/L and R2 of 0.95. It was no time lag between the predicted blood glucose and the actual blood glucose in the oral glucose tolerance test (OGTT). We also applied the procedure to data from all 12 volunteers regarded as one set, and the total predicted performance was obtained with an RMSEP of 0.27 mmol/L and an R2 of 0.98, which is better than that of the individual model for each volunteer. This suggested that anatomical differences between volunteer fingernails do not reduce the prediction accuracy and 100% of the predicted glucose concentrations fall within Region A and B of the Clarke error grid, allowing acceptable predictions in a clinically relevant range. The Raman spectroscopy detection of blood glucose from microvessels is of great significance of non-invasive blood glucose detection of Raman spectroscopy. This innovative method may also facilitate non-invasive detection of other blood components. Full article
(This article belongs to the Special Issue Raman Spectroscopy: An Important Technique in Medicine, Agriculture, and Biochemistry)
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