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Sensing Circulating Markers for Metabolic Syndrome

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

Deadline for manuscript submissions: 30 September 2024 | Viewed by 7004

Special Issue Editors

The Henry Samueli School of Engineering, University of California Irvine, 2200 Engineering Hall, Irvine, CA 92697, USA
Interests: MEMS; BioMEMS; medical devices; neural engineering; cardiovascular engineering
Special Issues, Collections and Topics in MDPI journals

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The Henry Samueli School of Engineering, University of California Irvine, 2200 Engineering Hall, Irvine, CA 92697, USA
Interests: self-assembly of biological and biomimetic nanoscale materials based on amino acids and on nucleic acids using computational and theoretical methods
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical Engineering, The University of Texas at Tyler, Tyler, TX 75799, USA
Interests: plasmonics; photonic crystal; metastructure; grating; chalcogenides; optofluidics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolic syndrome (MetS) has been prevailing pandemically. It is a cluster of biochemical pathways that come together, increasing the risk for cardiovascular disease and others, such as type 2 diabetes and cancer. The concurrent conditions in MetS may include increase in blood pressure and blood sugar, excess waist fat, or abnormal cholesterol levels. MetS has been increasingly common, and up to one third of Americans now have it. However, the diagnosis of MetS is complicated. The disease often goes unnoticed and thus untreated. Therefore, early detection would increase chances of MetS management, and consequently help increase the quality of life and longevity. Circulating markers found in blood, urine, saliva, or sweat samples have been investigated for diagnosis of those at risk in developing MetS. Besides, recent advances in  engineering and micro/nanofabrication may open opportunities to develop novel biosensors and systems for point-of-care and home healthcare devices. These will be beneficial for MetS diagnostics and will help reduce the risk of cardiovascular disease, kidney disease, diabetes, and cancer, bringing both social and economical impacts.

In this context, we invite submissions to this Special Issue “Sensing circulating markers for metabolic syndrome” as review articles, original research papers, and short communications covering a broad field of technologies for detecting and studying metabolic syndrome.

Contributions may include, but are not limited to:

  • Printed biosensors and microfabrication;
  • Nano biosensors;
  • Aptamer-based sensors;
  • Enzyme-based biosensors;
  • Immunosensors;
  • Lab-on-a-chip and multiplex sensors;
  • Wearables and patch-based sensing systems;
  • Biosensing systems with smartphone and/or cloud communications;
  • Advanced bio-signal processing and analytics for MetS detection and studies.

Dr. Hung Cao
Dr. Anh Hung Nguyen
Dr. Shawana Tabassum
Guest Editors

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

  • metabolic syndrome
  • biosensors
  • microfluidics
  • lab-on-a-chip
  • wearables

Published Papers (2 papers)

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Review

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30 pages, 3545 KiB  
Review
Towards Multiplexed and Multimodal Biosensor Platforms in Real-Time Monitoring of Metabolic Disorders
by Sung Sik Chu, Hung Anh Nguyen, Jimmy Zhang, Shawana Tabassum and Hung Cao
Sensors 2022, 22(14), 5200; https://doi.org/10.3390/s22145200 - 12 Jul 2022
Cited by 5 | Viewed by 3739
Abstract
Metabolic syndrome (MS) is a cluster of conditions that increases the probability of heart disease, stroke, and diabetes, and is very common worldwide. While the exact cause of MS has yet to be understood, there is evidence indicating the relationship between MS and [...] Read more.
Metabolic syndrome (MS) is a cluster of conditions that increases the probability of heart disease, stroke, and diabetes, and is very common worldwide. While the exact cause of MS has yet to be understood, there is evidence indicating the relationship between MS and the dysregulation of the immune system. The resultant biomarkers that are expressed in the process are gaining relevance in the early detection of related MS. However, sensing only a single analyte has its limitations because one analyte can be involved with various conditions. Thus, for MS, which generally results from the co-existence of multiple complications, a multi-analyte sensing platform is necessary for precise diagnosis. In this review, we summarize various types of biomarkers related to MS and the non-invasively accessible biofluids that are available for sensing. Then two types of widely used sensing platform, the electrochemical and optical, are discussed in terms of multimodal biosensing, figure-of-merit (FOM), sensitivity, and specificity for early diagnosis of MS. This provides a thorough insight into the current status of the available platforms and how the electrochemical and optical modalities can complement each other for a more reliable sensing platform for MS. Full article
(This article belongs to the Special Issue Sensing Circulating Markers for Metabolic Syndrome)
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Other

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7 pages, 1312 KiB  
Letter
Highly Reproducible Surface-Enhanced Raman Scattering Detection of Alternariol Using Silver-Embedded Silica Nanoparticles
by Eunil Hahm, Yoon-Hee Kim, Xuan-Hung Pham and Bong-Hyun Jun
Sensors 2020, 20(12), 3523; https://0-doi-org.brum.beds.ac.uk/10.3390/s20123523 - 22 Jun 2020
Cited by 15 | Viewed by 2519
Abstract
Alternariol (AOH) is a mycotoxin from fungi that has been found in processed foods due to its high thermal stability. To address the complexity and costs of conventional AOH detection methods, we propose an alternative based on surface-enhanced Raman scattering (SERS) and specially [...] Read more.
Alternariol (AOH) is a mycotoxin from fungi that has been found in processed foods due to its high thermal stability. To address the complexity and costs of conventional AOH detection methods, we propose an alternative based on surface-enhanced Raman scattering (SERS) and specially designed nanoparticle substrate. Herein, silver-embedded silica (SiO2@Ag) nanoparticles with a highly reproducible SERS signal were successfully developed for detecting AOH. Silica nanoparticles (~145 nm) were used as a template to deposit silver nanoparticles (~17 nm), thereby generating SiO2@Ag. The SiO2@Ag nanoparticles showed a good linearity between SERS signal intensity and AOH concentrations from 16 to 1000 nM with a limit of detection of 4.83 nM. Additionally, the SERS signal of the SiO2@Ag nanoparticles was highly reproducible, with relative standard deviations of 2.33–5.95% in the AOH concentration range from 10 to 10,000 nM, demonstrating the reliability of the proposed SERS method. Full article
(This article belongs to the Special Issue Sensing Circulating Markers for Metabolic Syndrome)
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