Cargando…
State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods
Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. Some techniques are considered gold standard methods. However, their limited sensitivity, specificity, and accuracy, and the need for costly reagents and...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470585/ https://www.ncbi.nlm.nih.gov/pubmed/34573887 http://dx.doi.org/10.3390/diagnostics11091545 |
_version_ | 1784574237732765696 |
---|---|
author | Ruenchit, Pichet |
author_facet | Ruenchit, Pichet |
author_sort | Ruenchit, Pichet |
collection | PubMed |
description | Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. Some techniques are considered gold standard methods. However, their limited sensitivity, specificity, and accuracy, and the need for costly reagents and high-skilled technicians are critical problems. New tools are therefore continually being developed to reduce pitfalls. Recently, three state-of-the-art techniques have emerged: DNA barcoding, geometric morphometrics, and artificial intelligence. Here, data related to the three approaches are reviewed. DNA barcoding involves an analysis of a barcode sequence. It was used to diagnose medical parasites and arthropods with 95.0% accuracy. However, this technique still requires costly reagents and equipment. Geometric morphometric analysis is the statistical analysis of the patterns of shape change of an anatomical structure. Its accuracy is approximately 94.0–100.0%, and unlike DNA barcoding, costly reagents and equipment are not required. Artificial intelligence technology involves the analysis of pictures using well-trained algorithms. It showed 98.8–99.0% precision. All three approaches use computer programs instead of human interpretation. They also have the potential to be high-throughput technologies since many samples can be analyzed at once. However, the limitation of using these techniques in real settings is species coverage. |
format | Online Article Text |
id | pubmed-8470585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84705852021-09-27 State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods Ruenchit, Pichet Diagnostics (Basel) Review Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. Some techniques are considered gold standard methods. However, their limited sensitivity, specificity, and accuracy, and the need for costly reagents and high-skilled technicians are critical problems. New tools are therefore continually being developed to reduce pitfalls. Recently, three state-of-the-art techniques have emerged: DNA barcoding, geometric morphometrics, and artificial intelligence. Here, data related to the three approaches are reviewed. DNA barcoding involves an analysis of a barcode sequence. It was used to diagnose medical parasites and arthropods with 95.0% accuracy. However, this technique still requires costly reagents and equipment. Geometric morphometric analysis is the statistical analysis of the patterns of shape change of an anatomical structure. Its accuracy is approximately 94.0–100.0%, and unlike DNA barcoding, costly reagents and equipment are not required. Artificial intelligence technology involves the analysis of pictures using well-trained algorithms. It showed 98.8–99.0% precision. All three approaches use computer programs instead of human interpretation. They also have the potential to be high-throughput technologies since many samples can be analyzed at once. However, the limitation of using these techniques in real settings is species coverage. MDPI 2021-08-26 /pmc/articles/PMC8470585/ /pubmed/34573887 http://dx.doi.org/10.3390/diagnostics11091545 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Ruenchit, Pichet State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods |
title | State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods |
title_full | State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods |
title_fullStr | State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods |
title_full_unstemmed | State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods |
title_short | State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods |
title_sort | state-of-the-art techniques for diagnosis of medical parasites and arthropods |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470585/ https://www.ncbi.nlm.nih.gov/pubmed/34573887 http://dx.doi.org/10.3390/diagnostics11091545 |
work_keys_str_mv | AT ruenchitpichet stateofthearttechniquesfordiagnosisofmedicalparasitesandarthropods |