Evidence map›Paper›PMID 28609716›Full record

ArticleBiosensors & bioelectronics2017

Accelerating bacterial growth detection and antimicrobial susceptibility assessment in integrated picoliter droplet platform.

Aniruddha M Kaushik, Kuangwen Hsieh, Liben Chen, Dong Jin Shin, Joseph C Liao, Tza-Huei Wang

Open access · greenAbstract read
In one paragraph

Article in Biosensors & bioelectronics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
6.3field-weighted citation impact, top 3% of its field
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

58 citing papers in PubMed, 143 citations in OpenAlex.

  1. Review
  2. A digital droplet microarray for measuring tolerance to antibiotics.bioRxiv : the preprint server for biology · 2026
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  16. [Application of Droplet-Based Microfluidics in Microbial Research].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Aniruddha M KaushikDepartment of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, USA.
Kuangwen HsiehDepartment of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, USA.
Liben ChenDepartment of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, USA.
Dong Jin ShinDepartment of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, USA.
Joseph C LiaoDepartment of Urology, Stanford University School of Medicine, 300 Pasteur Dr. S-287, Stanford, CA, USA.
Tza-Huei WangDepartment of Mechanical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, USA. Electronic address: thwang@jhu.edu.
Johns Hopkins University · USStanford University · US

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

There remains an urgent need for rapid diagnostic methods that can evaluate antibiotic resistance for pathogenic bacteria in order to deliver targeted antibiotic treatments. Toward this end, we present a rapid and integrated single-cell biosensing platform, termed dropFAST, for bacterial growth detection and antimicrobial susceptibility assessment. DropFAST utilizes a rapid resazurin-based fluorescent growth assay coupled with stochastic confinement of bacteria in 20 pL droplets to detect signal from growing bacteria after 1h incubation, equivalent to 2-3 bacterial replications. Full integration of droplet generation, incubation, and detection into a single, uninterrupted stream also renders this platform uniquely suitable for in-line bacterial phenotypic growth assessment. To illustrate the concept of rapid digital antimicrobial susceptibility assessment, we employ the dropFAST platform to evaluate the antibacterial effect of gentamicin on E. coli growth.

Indexed as

Anti-Bacterial AgentsBiosensing TechniquesEquipment DesignEscherichia coliEscherichia coli InfectionsHumansMicrobial Sensitivity TestsMicrofluidic Analytical TechniquesSample SizeTime FactorsAnti-Bacterial AgentsAntimicrobial Susceptibility Test (AST)DropletMicrofluidicsPicoliter

Identifiers

PMID28609716
PMCPMC5615843
OpenAlexW2715938378

What OpenQuestion holds

Textmetadata
LicenceTDM
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.