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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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.
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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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