Rapid Detection of Urinary Tract Infection in 10 min by Tracking Multiple Phenotypic Features in a 30 s Large-Volume Scattering Video of Urine Microscopy.
UTI screening
bacteria detection
machine learning
multiple phenotypic features
solution scattering imaging
Journal
ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031
Informations de publication
Date de publication:
26 08 2022
26 08 2022
Historique:
pubmed:
6
8
2022
medline:
30
8
2022
entrez:
5
8
2022
Statut:
ppublish
Résumé
Rapid point-of-care (POC) diagnosis of bacterial infection diseases provides clinical benefits of prompt initiation of antimicrobial therapy and reduction of the overuse/misuse of unnecessary antibiotics for nonbacterial infections. We present here a POC compatible method for rapid bacterial infection detection in 10 min. We use a large-volume solution scattering imaging (LVSi) system with low magnifications (1-2×) to visualize bacteria in clinical samples, thus eliminating the need for culture-based isolation and enrichment. We tracked multiple intrinsic phenotypic features of individual cells in a short video. By clustering these features with a simple machine learning algorithm, we can differentiate
Identifiants
pubmed: 35930733
doi: 10.1021/acssensors.2c00788
pmc: PMC9465977
mid: NIHMS1835071
doi:
Substances chimiques
Anti-Bacterial Agents
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
2262-2272Subventions
Organisme : NIAID NIH HHS
ID : R01 AI138993
Pays : United States
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