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Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms
Candida is the largest genus of medically significant fungi. Although most of its members are commensals, residing harmlessly in human bodies, some are opportunistic and dangerously invasive. These have the ability to cause severe nosocomial candidiasis and candidemia that affect the viscera and blo...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10608220/ https://www.ncbi.nlm.nih.gov/pubmed/37895480 http://dx.doi.org/10.3390/life13102099 |
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author | Lorenzo-Villegas, Dionisio Lorenzo Gohil, Namra Vinay Lamo, Paula Gurajala, Swathi Bagiu, Iulia Cristina Vulcanescu, Dan Dumitru Horhat, Florin George Sorop, Virgiliu Bogdan Diaconu, Mircea Sorop, Madalina Ioana Oprisoni, Andrada Horhat, Razvan Mihai Susan, Monica MohanaSundaram, ArunSundar |
author_facet | Lorenzo-Villegas, Dionisio Lorenzo Gohil, Namra Vinay Lamo, Paula Gurajala, Swathi Bagiu, Iulia Cristina Vulcanescu, Dan Dumitru Horhat, Florin George Sorop, Virgiliu Bogdan Diaconu, Mircea Sorop, Madalina Ioana Oprisoni, Andrada Horhat, Razvan Mihai Susan, Monica MohanaSundaram, ArunSundar |
author_sort | Lorenzo-Villegas, Dionisio Lorenzo |
collection | PubMed |
description | Candida is the largest genus of medically significant fungi. Although most of its members are commensals, residing harmlessly in human bodies, some are opportunistic and dangerously invasive. These have the ability to cause severe nosocomial candidiasis and candidemia that affect the viscera and bloodstream. A prompt diagnosis will lead to a successful treatment modality. The smart solution of biosensing technologies for rapid and precise detection of Candida species has made remarkable progress. The development of point-of-care (POC) biosensor devices involves sensor precision down to pico-/femtogram level, cost-effectiveness, portability, rapidity, and user-friendliness. However, futuristic diagnostics will depend on exploiting technologies such as multiplexing for high-throughput screening, CRISPR, artificial intelligence (AI), neural networks, the Internet of Things (IoT), and cloud computing of medical databases. This review gives an insight into different biosensor technologies designed for the detection of medically significant Candida species, especially Candida albicans and C. auris, and their applications in the medical setting. |
format | Online Article Text |
id | pubmed-10608220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106082202023-10-28 Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms Lorenzo-Villegas, Dionisio Lorenzo Gohil, Namra Vinay Lamo, Paula Gurajala, Swathi Bagiu, Iulia Cristina Vulcanescu, Dan Dumitru Horhat, Florin George Sorop, Virgiliu Bogdan Diaconu, Mircea Sorop, Madalina Ioana Oprisoni, Andrada Horhat, Razvan Mihai Susan, Monica MohanaSundaram, ArunSundar Life (Basel) Review Candida is the largest genus of medically significant fungi. Although most of its members are commensals, residing harmlessly in human bodies, some are opportunistic and dangerously invasive. These have the ability to cause severe nosocomial candidiasis and candidemia that affect the viscera and bloodstream. A prompt diagnosis will lead to a successful treatment modality. The smart solution of biosensing technologies for rapid and precise detection of Candida species has made remarkable progress. The development of point-of-care (POC) biosensor devices involves sensor precision down to pico-/femtogram level, cost-effectiveness, portability, rapidity, and user-friendliness. However, futuristic diagnostics will depend on exploiting technologies such as multiplexing for high-throughput screening, CRISPR, artificial intelligence (AI), neural networks, the Internet of Things (IoT), and cloud computing of medical databases. This review gives an insight into different biosensor technologies designed for the detection of medically significant Candida species, especially Candida albicans and C. auris, and their applications in the medical setting. MDPI 2023-10-22 /pmc/articles/PMC10608220/ /pubmed/37895480 http://dx.doi.org/10.3390/life13102099 Text en © 2023 by the authors. 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 Lorenzo-Villegas, Dionisio Lorenzo Gohil, Namra Vinay Lamo, Paula Gurajala, Swathi Bagiu, Iulia Cristina Vulcanescu, Dan Dumitru Horhat, Florin George Sorop, Virgiliu Bogdan Diaconu, Mircea Sorop, Madalina Ioana Oprisoni, Andrada Horhat, Razvan Mihai Susan, Monica MohanaSundaram, ArunSundar Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms |
title | Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms |
title_full | Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms |
title_fullStr | Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms |
title_full_unstemmed | Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms |
title_short | Innovative Biosensing Approaches for Swift Identification of Candida Species, Intrusive Pathogenic Organisms |
title_sort | innovative biosensing approaches for swift identification of candida species, intrusive pathogenic organisms |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10608220/ https://www.ncbi.nlm.nih.gov/pubmed/37895480 http://dx.doi.org/10.3390/life13102099 |
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