Scholarlink

<p>Annually, a substantial portion of the global population is affected by various neurological disorders. Despite advancements in scientific research, effective and approved treatment approaches for many of these conditions remain elusive. This review aims to thoroughly investigate dextrorotatory amino acids (D-AAs), highlighting their distinctive roles in neurological disorders and the analytical techniques employed for their detection in biological samples. D-AAs are integral to protein structure, and genetic mutations or environmental factors can influence disease progression through their involvement. Moreover, D-AAs are emerging as potential diagnostic biomarkers for neurological diseases. This study focuses on specific D-AAs, such as D-serine, D-alanine, D-glutamate, and D-aspartate, examining their role in neurological conditions, including neurodegenerative diseases, psychiatric conditions, cerebrovascular disorders, and epilepsy. Recent research underscores the importance of D-enantiomers in human physiology and pathology, suggesting innovative strategies for disease prevention and treatment, particularly concerning neurological disorders. Notably, D-serine, D-aspartate, D-glutamate, and D-alanine function as critical neurotransmitters for N-methyl-D-aspartate receptors. This review elaborates on various analytical methods for the detection of D-AAs in biological samples, including biosensors, chromatography, capillary electrophoresis, mass spectrometry, and nuclear magnetic resonance, among others. Despite these meaningful findings, future research must prioritize the development of advanced and precise techniques for detecting D-AAs to enhance their potential application as biomarkers. Furthermore, integrating machine learning algorithms into metabolomic workflows can advance diagnostic accuracy by detecting disease-specific D-AA profiles.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Detection and functional assessment of D-amino acids as potential biomarkers in neurological disorders

  • 期刊论文

  • 发表日期：

    2025年11月7日

查看全文
  • Marjan Talebi,
  • Seyedeh Elnaz Sharifi-Ardani,
  • Fatemeh Sadat Ghannadzadeh,
  • Melika Sattarpour,
  • Ayda Jahanseir,
  • Seyedali Hashemi,
  • Reza Jahani

摘要

Annually, a substantial portion of the global population is affected by various neurological disorders. Despite advancements in scientific research, effective and approved treatment approaches for many of these conditions remain elusive. This review aims to thoroughly investigate dextrorotatory amino acids (D-AAs), highlighting their distinctive roles in neurological disorders and the analytical techniques employed for their detection in biological samples. D-AAs are integral to protein structure, and genetic mutations or environmental factors can influence disease progression through their involvement. Moreover, D-AAs are emerging as potential diagnostic biomarkers for neurological diseases. This study focuses on specific D-AAs, such as D-serine, D-alanine, D-glutamate, and D-aspartate, examining their role in neurological conditions, including neurodegenerative diseases, psychiatric conditions, cerebrovascular disorders, and epilepsy. Recent research underscores the importance of D-enantiomers in human physiology and pathology, suggesting innovative strategies for disease prevention and treatment, particularly concerning neurological disorders. Notably, D-serine, D-aspartate, D-glutamate, and D-alanine function as critical neurotransmitters for N-methyl-D-aspartate receptors. This review elaborates on various analytical methods for the detection of D-AAs in biological samples, including biosensors, chromatography, capillary electrophoresis, mass spectrometry, and nuclear magnetic resonance, among others. Despite these meaningful findings, future research must prioritize the development of advanced and precise techniques for detecting D-AAs to enhance their potential application as biomarkers. Furthermore, integrating machine learning algorithms into metabolomic workflows can advance diagnostic accuracy by detecting disease-specific D-AA profiles.