Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence microscopy

Chatzimichail, Stelios; Turner, Piers; Feehily, Conor; Farrar, Alison; Crook, Derrick; Andersson, Monique; Oakley, Sarah; Barrett, Lucinda; El Sayyed, Hafez; Kyropoulos, Jingwen; Nellåker, Christoffer; Stoesser, Nicole; Kapanidis, Achillefs N.

doi:10.1039/d4lc00325j

Lab Chip

2024

DOI: 10.1039/d4lc00325j

|View full text |Cite

Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence microscopy

Stelios Chatzimichail,

Piers Turner,

Conor Feehily

et al.

Abstract: A microfluidic device utilizing adaptive channels was developed for efficient capture and rapid identification of 7 species of bacteria using molecular barcoding and fluorescence imaging.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Review of the detection of pathogenic Escherichia coli based-microchip technology

Xue,

Zhang

2024

ANAL. SCI.

View full text Add to dashboard Cite

Review of the detection of pathogenic Escherichia coli based-microchip technology

Xue,

Zhang

2024

ANAL. SCI.

View full text Add to dashboard Cite

The role of artificial intelligence in the diagnosis, imaging, and treatment of thoracic empyema

Zumla,

Ahmed,

Bakhri

2024

Current Opinion in Pulmonary Medicine

View full text Add to dashboard Cite

Purpose of review The management of thoracic empyema is often complicated by diagnostic delays, recurrence, treatment failures and infections with antibiotic resistant bacteria. The emergence of artificial intelligence (AI) in healthcare, particularly in clinical decision support, imaging, and diagnostic microbiology raises great expectations in addressing these challenges. Recent findings Machine learning (ML) and AI models have been applied to CT scans and chest X-rays to identify and classify pleural effusions and empyema with greater accuracy. AI-based analyses can identify complex imaging features that are often missed by the human eye, improving diagnostic precision. AI-driven decision-support algorithms could reduce time to diagnosis, improve antibiotic stewardship, and enhance more precise and less invasive surgical therapy, significantly improving clinical outcomes and reducing inpatient hospital stays. Summary ML and AI can analyse large datasets and recognize complex patterns and thus have the potential to enhance diagnostic accuracy, preop planning for thoracic surgery, and optimize surgical treatment strategies, antibiotic therapy, antibiotic stewardship, monitoring complications, and long-term patient management outcomes.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence microscopy

Abstract: A microfluidic device utilizing adaptive channels was developed for efficient capture and rapid identification of 7 species of bacteria using molecular barcoding and fluorescence imaging.

Cited by 2 publications

References 36 publications

Review of the detection of pathogenic Escherichia coli based-microchip technology

Review of the detection of pathogenic Escherichia coli based-microchip technology

The role of artificial intelligence in the diagnosis, imaging, and treatment of thoracic empyema

Contact Info

Product

Resources

About