Evidence map›Paper›PMID 32210148›Full record

ReviewMicromachines2020

Microfluidic Systems Applied in Solid-State Nanopore Sensors.

Jiye Fu, Linlin Wu, Yi Qiao, Jing Tu, Zuhong Lu

Abstract readReview
In one paragraph

Review in Micromachines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Integrated In-Plane Nanofluidic Devices for Resistive-Pulse Sensing.Annual review of analytical chemistry (Palo Alto, Calif.) · 2024
    Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Article
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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

5 authors.

Jiye FuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Linlin WuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Yi QiaoState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Jing TuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Zuhong LuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.

Funding

National Key R&D Program of China 2016YFA0501602National Key R&D Program of China 2017YFE0130600
6 · The paper itself

Abstract

Microfluidic system, as a kind of miniature integrated operating platform, has been applied to solid-state nanopore sensors after many years of experimental study. In the process of introducing microfluidic into solid-state nanopore sensors, many novel device structures are designed due to the abundance of analytes and the diversity of detection methods. Here we review the fundamental setup of nanopore-based microfluidic systems and the developments and advancements that have been taking place in the field. The microfluidic systems with a multichannel strategy to elevate the throughput and efficiency of nanopore sensors are then presented. Multifunctional detection represented by optical-electrical detection, which is realized by microfluidic integration, is also described. A high integration microfluidic system with nanopore is further discussed, which shows the prototype of commercialization.

Indexed as

integrationmicrofluidic systemmultichanneloptical detectionsolid-state nanopore

Identifiers

PMID32210148
PMCPMC7142662

What OpenQuestion holds

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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.