Evidence map›Paper›PMID 31068473›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Adaptable microfluidic system for single-cell pathogen classification and antimicrobial susceptibility testing.

Hui Li, Peter Torab, Kathleen E Mach, Christine Surrette, Matthew R England, David W Craft, Neal J Thomas, Joseph C Liao, Chris Puleo, Pak Kin Wong

Abstract readComment
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed.

  1. Article
  2. Article
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  4. Exploiting Device Deformability for Fluid and Particle Manipulation.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Single-Cell Microfluidics: A Primer for Microbiologists.The journal of physical chemistry. B · 2024
    Review
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Hui LiDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802.
Peter TorabDepartment of Mechanical Engineering, The Pennsylvania State University, University Park, PA 16802.
Kathleen E MachDepartment of Urology, Stanford University School of Medicine, Stanford, CA 94305.
Christine SurretteElectronics Organization, GE Global Research, Niskayuna, NY 12309.
Matthew R EnglandPathology and Laboratory Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA 17033.
David W CraftPathology and Laboratory Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA 17033.
Neal J ThomasDepartment of Pediatrics, College of Medicine, The Pennsylvania State University, Hershey, PA 17033.
Joseph C LiaoDepartment of Urology, Stanford University School of Medicine, Stanford, CA 94305.
Chris PuleoElectronics Organization, GE Global Research, Niskayuna, NY 12309.
Pak Kin WongDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802; pak@engr.psu.edu.

Funding

A Droplet-based single cell platform for pathogen identification and ASTR01AI117032 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LIAO, JOSEPH C, WANG, TZA-HUEI JEFF · 2015 to 2019
$5.7M
NIAID NIH HHS R01 AI117032
6 · The paper itself

Abstract

Infectious diseases caused by bacterial pathogens remain one of the most common causes of morbidity and mortality worldwide. Rapid microbiological analysis is required for prompt treatment of bacterial infections and to facilitate antibiotic stewardship. This study reports an adaptable microfluidic system for rapid pathogen classification and antimicrobial susceptibility testing (AST) at the single-cell level. By incorporating tunable microfluidic valves along with real-time optical detection, bacteria can be trapped and classified according to their physical shape and size for pathogen classification. By monitoring their growth in the presence of antibiotics at the single-cell level, antimicrobial susceptibility of the bacteria can be determined in as little as 30 minutes compared with days required for standard procedures. The microfluidic system is able to detect bacterial pathogens in urine, blood cultures, and whole blood and can analyze polymicrobial samples. We pilot a study of 25 clinical urine samples to demonstrate the clinical applicability of the microfluidic system. The platform demonstrated a sensitivity of 100% and specificity of 83.33% for pathogen classification and achieved 100% concordance for AST.

Indexed as

Anti-Infective AgentsMicrofluidicsAnti-Bacterial AgentsDysbiosisHumansMicrobial Sensitivity TestsAnti-Bacterial AgentsAnti-Infective Agentsantimicrobial susceptibility testingdiagnosticsinfectionmicrofluidicssingle-cell analysis

Identifiers

PMID31068473
PMCPMC6535027

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.