Raman Spectroscopy: Emerging Technologies and Applications in Biological and Biomedical Fields

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (20 September 2021) | Viewed by 3021

Special Issue Editors


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Guest Editor
National Research Council - Institute for Photonics and Nanotechnologies (IFN – CNR ) - Department of Physics - Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy
Interests: Raman spectroscopy; Raman imaging; clinical spectroscopy; biophotonics; nanomedicine; biosensors; chemometrics; cancer; calcifications
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Guest Editor
Istituti Clinici Scientifici Maugeri IRCCS, 27100 Pavia, Italy
Interests: biomedical spectroscopy; clinical spectroscopy; Alzheimer’s disease; breast cancer; nanomedicine; raman spectroscopy
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Health & Life Sciences, Teesside University, Campus Heart, Southfield Rd, Middlesbrough TS1 3BX, UK
Interests: plasmonic nanomaterials; Raman spectroscopy; SERS and SESORS detection; biosensors; cancer diagnostics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Raman spectroscopy (RS) has already been proven to be a formidable tool for the study of complex biological processes, detection of specific endogenous biomarkers, assessment of pathological conditions, and disease-site tracking with exogenous contrast agents for diagnostic purposes. RS research has encouraged cross-disciplinary interaction between researchers from different fields,  including physicists, engineers, chemists, biochemists, biologists, biostatisticians, and medical doctors, leading to the development of several Raman-based methods and technologies covering numerous applications in the biomedical field. The field is now also benefitting from the use of the new analytical methods provided by artificial intelligence. These new approaches allow the rapid and accurate analysis of the large volume of data typically generated during the study of biological samples by vibrational spectroscopy.

This Special Issue aims to collect research papers and review articles focused on the evolution of Raman spectroscopy with the aim of answering technological and analytical needs in the biological and medical fields.

To sustain and stimulate the involvement of young and emerging researchers (less than 40 years old at the time of submission), we strongly encourage their participation in a prominent role (first author and/or corresponding author, shared or not with a senior author).

The Special Issue topics include, but are not limited to:

  • Tools and technologies: spontaneous RS, Raman imaging, stimulated RS (e.g., SRS and CARS), nano-enhanced RS (e.g., SERS), deep RS (e.g., SORS and SESORS), RS probes designed or applied to biological/biomedical applications;
  • Applications from biochemical studies to in vivo studies, from cells and tissues to biofluids; and
  • Biostatistical and chemometric tools

You may choose our Joint Special Issue in Optics.

Dr. Renzo Vanna
Dr. Carlo Morasso
Dr. Priyanka Dey
Guest Editors

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. Applied Sciences 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 2400 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
  • Raman Imaging
  • clinical spectroscopy
  • CRS
  • SERS
  • SORS
  • SESORS
  • artificial intelligence
  • vibrational spectroscopy
  • diagnosis
  • nanotechnology

Published Papers (1 paper)

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Research

14 pages, 3299 KiB  
Article
Assessment of Skin Deep Layer Biochemical Profile Using Spatially Offset Raman Spectroscopy
by Martha Z. Vardaki, Konstantinos Seretis, Georgios Gaitanis, Ioannis D. Bassukas and Nikolaos Kourkoumelis
Appl. Sci. 2021, 11(20), 9498; https://0-doi-org.brum.beds.ac.uk/10.3390/app11209498 - 13 Oct 2021
Cited by 10 | Viewed by 2089
Abstract
Skin cancer is currently the most common type of cancer with millions of cases diagnosed worldwide yearly. The current gold standard for clinical diagnosis of skin cancer is an invasive and relatively time-consuming procedure, consisting of visual examination followed by biopsy collection and [...] Read more.
Skin cancer is currently the most common type of cancer with millions of cases diagnosed worldwide yearly. The current gold standard for clinical diagnosis of skin cancer is an invasive and relatively time-consuming procedure, consisting of visual examination followed by biopsy collection and histopathological analysis. Raman spectroscopy has been shown to efficiently aid the non-invasive diagnosis of skin cancer when probing the surface of the skin. In this study, we employ a recent development of Raman spectroscopy (Spatially Offset Raman Spectroscopy, SORS) which is able to look deeper in tissue and create a deep layer biochemical profile of the skin in areas where cancer lesions subtly evolve. After optimizing the measurement parameters on skin tissue phantoms, we then adopted SORS on human skin tissue from different anatomical areas to investigate the contribution of the different skin layers to the recorded Raman signal. Our results show that using a diffuse beam with zero offset to probe a sampling volume where the lesion is typically included (surface to epidermis-dermis junction), provides the optimum signal-to-noise ratio (SNR) and may be employed in future skin cancer screening applications. Full article
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