Evidence map›Paper›PMID 36677107›Full record

ArticleMicromachines2022

Microfluidic Chip for Detection of Drug Resistance at the Single-cell Level.

Kena Song, Zhangqing Yu, Xiangyang Zu, Lei Huang, Dongliao Fu, Jingru Yao, Zhigang Hu, Yun Xue

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.6field-weighted citation impact, top 39% 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

10 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
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  9. Article
  10. Sensing of Antibiotic-Bacteria Interactions.Antibiotics (Basel, Switzerland) · 2023
    Review
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

8 authors at 2 institutions in 1 country.

Kena SongCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Zhangqing YuCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Xiangyang ZuCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Lei HuangCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Dongliao FuCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Jingru YaoChongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 401331, China.
Zhigang HuCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Yun XueCollege of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Henan University of Science and Technology · CNChongqing University · CN

Funding

National Natural Science Foundation of China 12104134
6 · The paper itself

Abstract

Drug-resistant bacterial strains seriously threaten human health. Rapid screening of antibiotics is urgently required to improve clinical treatment. Conventional methods of antimicrobial susceptibility testing rely on turbidimetry that is evident only after several days of incubation. The lengthy time of the assay can delay clinical treatment. Here, we proposed a single-cell level rapid system based on a microfluidic chip. The detection period of 30 min to 2 h was significantly shorter than the conventional turbidity-based method. To promote detection efficiency, 16 independent channels were designed, permitting the simultaneous screening of 16 drugs in the microfluidic chip. Prepositioning of drugs in the chip permitted prolonged transportation and storage. This may allow for the widespread use of the novel system, particularly in the regions where medical facilities are scarce. The growth curves were reported rapidly through a custom code in Matlab after tracking and photographing the bacteria during microscopy examination. The capability of the proposed system was validated by antimicrobial susceptibility testing trials with standard strains. The system provides a potentially useful detection tool for drug-resistant bacteria.

Indexed as

antimicrobial susceptibility testing (AST)drug prepositioningmicrofluidic chipsingle-cell level

Identifiers

PMID36677107
PMCPMC9861505
OpenAlexW4313245138

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.