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Novel Optical Sensors for Biomedical Applications—2nd Edition
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Novel Optical Sensors for Biomedical Applications—2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 710

Special Issue Editor

Prof. Dr. Benjamin L. Miller

E-Mail Website
Guest Editor
Department of Dermatology, University of Rochester, Rochester, NY 14642, USA
Interests: optical biosensors; integrated photonics; interferometry; photonic crystals; developing world diagnostics; tissue chips
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I am pleased to invite you to submit manuscripts for a Special Issue of the journal Sensors on “Novel Optical Sensors for Biomedical Applications—2nd Edition”. The field of optical sensors has undergone rapid growth in recent years, with new concepts including miniaturization, multiplex analysis, photonic structures, and optically responsive materials appearing regularly. At the same time, the fields of genomics, proteomics, and metabolomics are providing a wealth of new molecules to detect.

Owing to the success of the first volume, we are developing a second one. This Special Issue is intended to highlight research focused on the development and use of new optical sensors for medical diagnostics, biomedical research, and allied endeavours. Papers describing new optical diagnostics methods for point-of-care, field-use, and resource-limited applications are encouraged, as are those reporting novel assays, multiplex testing systems, “lab on a chip” sensors, and spectroscopic methods. Both applications-focused and fundamental contributions (with likely downstream applications in biomedicine) are welcome.

Prof. Dr. Benjamin L. Miller
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sensors 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 2600 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

  • optical sensing
  • point-of-care diagnostics
  • developing world diagnostics
  • integrated photonics for sensing
  • plasmonics
  • multiplex detection
  • spectroscopy
  • lab-on-a-chip devices

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Published Papers (2 papers)

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Research

16 pages, 3933 KiB  
Article
Monitoring Biochemical Changes of Neuroblastoma Cells in Early Stages After X-Ray Exposure by Using Fourier-Transform Infrared Spectroscopy
by Rosario Esposito, Marianna Portaccio, Roberta Meschini, Ines Delfino and Maria Lepore
Sensors 2024, 24(23), 7459; https://doi.org/10.3390/s24237459 - 22 Nov 2024
Abstract
X-ray radiation treatments are largely adopted in radiotherapy, and Fourier-transform infrared microspectroscopy (μ-FTIR) has already been demonstrated to be a useful instrument for monitoring radiotherapy effects. Previous works in this field have focused on studying the changes occurring in cells when they are [...] Read more.
X-ray radiation treatments are largely adopted in radiotherapy, and Fourier-transform infrared microspectroscopy (μ-FTIR) has already been demonstrated to be a useful instrument for monitoring radiotherapy effects. Previous works in this field have focused on studying the changes occurring in cells when they are fixed immediately after the irradiation or 24 and 48 h later. In the present paper, changes occurring in SH-SY5Y neuroblastoma cells in the first hours after the irradiation are examined to obtain information on the processes taking place in this not-yet-investigated time window by using μ-FTIR. For this purpose, cell samples were fixed immediately after X-ray exposure, and 2 and 4 h after irradiation and investigated along with unexposed cells. Different data analysis procedures were implemented to estimate the changes in lipid, protein, and DNA spectral contributions. The present investigation on the effects of X-ray in the first hours after the exposure is helpful for better describing the processes occurring in this time window that offer the possibility of a timely check on the efficacy of X-ray treatments and can potentially be applied for planning personalized treatment as required by the most advanced medical therapy. Full article
(This article belongs to the Special Issue Novel Optical Sensors for Biomedical Applications—2nd Edition)
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20 pages, 7387 KiB  
Article
Skin Phototype Classification with Machine Learning Based on Broadband Optical Measurements
by Xun Yu, Keat Ghee Ong and Michael Aaron McGeehan
Sensors 2024, 24(22), 7397; https://doi.org/10.3390/s24227397 - 20 Nov 2024
Viewed by 265
Abstract
The Fitzpatrick Skin Phototype Classification (FSPC) scale is widely used to categorize skin types but has limitations such as the underrepresentation of darker skin phototypes, low classification resolution, and subjectivity. These limitations may contribute to dermatological care disparities in patients with darker skin [...] Read more.
The Fitzpatrick Skin Phototype Classification (FSPC) scale is widely used to categorize skin types but has limitations such as the underrepresentation of darker skin phototypes, low classification resolution, and subjectivity. These limitations may contribute to dermatological care disparities in patients with darker skin phototypes, including the misdiagnosis of wound healing progression and escalated dermatological disease severity. This study introduces (1) an optical sensor measuring reflected light across 410–940 nm, (2) an unsupervised K-means algorithm for skin phototype classification using broadband optical data, and (3) methods to optimize classification across the Near-ultraviolet-A, Visible, and Near-infrared spectra. The differentiation capability of the algorithm was compared to human assessment based on FSPC in a diverse participant population (n = 30) spanning an even distribution of the full FSPC scale. The FSPC assessment distinguished between light and dark skin phototypes (e.g., FSPC I vs. VI) at 560, 585, and 645 nm but struggled with more similar phototypes (e.g., I vs. II). The K-means algorithm demonstrated stronger differentiation across a broader range of wavelengths, resulting in better classification resolution and supporting its use as a quantifiable and reproducible method for skin type classification. We also demonstrate the optimization of this method for specific bandwidths of interest and their associated clinical implications. Full article
(This article belongs to the Special Issue Novel Optical Sensors for Biomedical Applications—2nd Edition)
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