Evidence map›Paper›PMID 31123534›Full record

ArticleBiomicrofluidics2019

A point of care platform based on microfluidic chip for nucleic acid extraction in less than 1 minute.

Jianzhong Zhang, Xiaosong Su, Jiasu Xu, Jin Wang, Juntian Zeng, Caiyu Li, Wendi Chen, Tingdong Li, Xiaoping Min, Dongxu Zhang and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in Biomicrofluidics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Sample-to-answer salivary miRNA testing: New frontiers in point-of-care diagnostic technologies.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
    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

14 authors at 1 institution in 1 country.

Jianzhong Zhang
Xiaosong Su
Jiasu Xu
Jin Wang
Juntian Zeng
Caiyu Li
Wendi Chen
Tingdong Li
Xiaoping Min
Dongxu Zhang
Shiyin Zhang
Shengxiang Ge
Jun Zhang
Ningshao Xia
Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In view of the complex procedure of nucleic acid extraction, there exists a huge challenge for the widespread use of point-of-care diagnostics for nucleic acid testing. To achieve point-of-care applications in a more rapid and cost-efficient manner, we designed a snake pipe-shaped microfluidic chip so as to accomplish reagents-prestored, time-saving, operation-simple nucleic acid extraction. All reagents needed for this process, including lysis buffer, wash buffer, elution buffer, and so on, were preloaded in the snake pipe and securely isolated by membrane valves, without the need for using any specialized equipment. By an integrated chip and a powerful ultrasonic, this device could complete virus nucleic acid extraction from sophisticated serum samples in less than 1 min. We used hepatitis B virus (HBV) and human immunodeficiency virus (HIV) mixed with different sources of serum as samples to be extracted. The coefficient of variation of HBV and HIV extraction on-chip was 1.32% and 2.74%, respectively, and there were no significant differences between on-chip and commercial instrument extraction (P > 0.05, α = 0.05) in different dilution ratios, which showed that the extraction device we established had excellent stability and sensitivity.

Identifiers

PMID31123534
PMCPMC6506337
OpenAlexW2944399188

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.