10.57647/jtap.2026.2004.11

Analysis of Human Fingernails for Disease Diagnostics by Laser-Induced Breakdown Spectroscopy: An Advance Review

  1. Department of Physics, College of Science, Mustansiriyah University, Baghdad, Iraq

Received: 2025-10-13

Revised: 2025-11-05

Accepted: 2026-02-09

Published in Issue 2026-04-22

How to Cite

1.
Obaid SA, Zoory MJ, Mohamad HJ. Analysis of Human Fingernails for Disease Diagnostics by Laser-Induced Breakdown Spectroscopy: An Advance Review. J Theor Appl phys. 2026 Apr. 22;. Available from: https://oiccpress.com/jtap/article/view/8608

PDF views: 28

Abstract

This systematic review highlights the role of nail analysis as a biomarker for the metabolic, diagnostic, and management of chronic diseases such as diabetes mellitus (DM), thyroid disorders, osteoporosis, and environmental exposure to heavy metals. It combines multi-method insights and a range of techniques, such as X-ray fluorescence (XRF) spectroscopy, inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectrometry (AAS), and their comparison with Laser-Induced Breakdown Spectroscopy (LIBS). LIBS provides rapid, multi-element analysis with little or no sample preparation. This study is very beneficial because it provides a quick, simple, and affordable method of monitoring for diseases over time. LIBS is used as a strong analysis ability with nails as a permanent bio record and in early customized health checks because it works in both science and healthcare. The main challenges hindering the clinical transfer of LIBS are discussed, including matrix effects, spectral interferences, environmental interferences, and clinical validation through large-scale experiments and large sample numbers. Finally, the details are discussed for future prospects, focusing on the development of portable LIBS systems for point-of-care testing (POCT), the integration of AI-based diagnostic platforms, and the creation of global spectral databases for precision medicine.

Keywords

  • LIBS,,
  • Fingernails,
  • Elemental analysis,
  • Disease biomarkers

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