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Serotonin level as a potent diabetes biomarker based on electrochemical sensing: a new approach in a zebra fish model

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Abstract

Serotonin (5-HT) levels have been associated with several exclusively metabolic disorders. Herein, a new approach for 5-HT level as a novel biomarker of diabetes mellitus is considered using a simple nanocomposite and HPLC method. Reduced graphene oxide (rGO) comprising gold nanoparticles (AuNPs) was decorated with 18-crown-6 (18.Cr.6) to fabricate a simple nanocomposite (rGO-AuNPs-18.Cr.6). The nanocomposite was positioned on a glassy carbon electrode (GCE) to form an electrochemical sensor for the biomarker 5-HT in the presence of L-tryptophan (L-Trp), dopamine (DA), ascorbic acid (AA), urea, and glucose. The nanocomposite exhibited efficient catalytic activity for 5-HT detection by square-wave voltammetry (SWV). The proposed sensor displayed high selectivity, excellent reproducibility, notable anti-interference ability, and long-term stability even after 2 months. SWV defined a linear range of 5-HT concentration from 0.4 to 10 μg L−1. A diabetic animal model (diabetic zebrafish model) was then applied to investigate 5-HT as a novel biomarker of diabetes. A limit of detection (LOD) of about 0.33 μg L−1 was found for the diabetic group and 0.15 μg L−1 for the control group. The average levels of 5-HT obtained were 9 and 2 μg L−1 for control and diabetic groups, respectively. The recovery, relative standard deviation (RSD), and relative error (RE) were found to be about 97%, less than 2%, and around 3%, respectively. The significant reduction in 5-HT level in the diabetic group compared to the control group proved that the biomarker 5-HT can be applied for the early diagnosis of diabetes mellitus.

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Acknowledgments

This work was supported by the Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences (Grant No. 1396-01-100-2249). The authors would like to express special thanks to Dr. Farshad Sharifi for his valuable insight.

Authorship contribution statement

K. Khoshnevisan: conceptualization, formal analysis, investigation, methodology, resources, design, software, validation, visualization, writing original draft, writing/review and editing. H. Baharifar: data curation, investigation, methodology, resources, software, validation, visualization, writing original draft. F. Torabi: data curation, software, investigation, validation, resources. M. Sadeghi Afjeh: investigation, data curation, methodology, resources, validation, software. H. Maleki: data curation, design, software, investigation. E. Honarvarfard: investigation, writing/review and editing, software, design. H. Mohammadi: formal analysis, resources, investigation. SM. Sajjadi-Jazi: investigation, data curation, resources, writing original draft. S. Mahmoudi-Kohan: investigation, data curation, software. F. Faridbod: conceptualization, supervision, investigation, resources, visualization. B. Larijani: funding acquisition, project administration, resources, supervision. FS: investigation, conceptualization, visualization. R. Faridi Majidi: investigation, visualization, conceptualization. M.R. Khorramizadeh: conceptualization, funding acquisition, investigation, project administration, resources, supervision, visualization, writing/review and editing.

Funding

This study was financially supported by the Iran National Committee for Medical Research Development (NIMAD), Tehran, Iran (Grant No. 971040).

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Author notes

  1. Kamyar Khoshnevisan and Hadi Baharifar contributed equally to this work.

Authors and Affiliations

  1. Biosensor Research Center, Endocrinology & Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, 1411713137, Iran

    Kamyar Khoshnevisan & Mohammad Reza Khorramizadeh

  2. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, 1411713137, Iran

    Kamyar Khoshnevisan, Mahsa Sadeghi Afjeh, Sayed Mahmoud Sajjadi-Jazi, Bagher Larijani & Mohammad Reza Khorramizadeh

  3. Zebrafish Core Facility, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, 1411713137, Iran

    Kamyar Khoshnevisan, Hassan Mohammadi & Mohammad Reza Khorramizadeh

  4. Department of Medical Nanotechnology, Applied Biophotonics Research Center, Science and Research Branch, Islamic Azad University, Tehran, 1477893855, Iran

    Hadi Baharifar

  5. School of Chemistry, College of Science, University of Tehran, Tehran, 1417466191, Iran

    Farzad Torabi, Sadegh Mahmoudi-Kohan & Farnoush Faridbod

  6. Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran, 1417466191, Iran

    Farzad Torabi, Sadegh Mahmoudi-Kohan & Farnoush Faridbod

  7. Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, 1417755469, Iran

    Hassan Maleki & Reza Faridi Majidi

  8. Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, 13699-5810, USA

    Elham Honarvarfard

  9. Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, 1411713137, Iran

    Sayed Mahmoud Sajjadi-Jazi

  10. Department of Immunology, School of Medicine, Guilan University of Medical Sciences, Rasht, 41887-94755, Iran

    Farshid Saadat

Authors
  1. Kamyar Khoshnevisan
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  2. Hadi Baharifar
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  3. Farzad Torabi
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  4. Mahsa Sadeghi Afjeh
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  9. Sadegh Mahmoudi-Kohan
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Correspondence to Kamyar Khoshnevisan or Mohammad Reza Khorramizadeh.

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Khoshnevisan, K., Baharifar, H., Torabi, F. et al. Serotonin level as a potent diabetes biomarker based on electrochemical sensing: a new approach in a zebra fish model. Anal Bioanal Chem 413, 1615–1627 (2021). https://doi.org/10.1007/s00216-020-03122-5

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