Evidence map›Paper›PMID 24287532›Full record

ArticleSensors (Basel, Switzerland)2013

A label-free microfluidic biosensor for activity detection of single microalgae cells based on chlorophyll fluorescence.

Junsheng Wang, Jinyang Sun, Yongxin Song, Yongyi Xu, Xinxiang Pan, Yeqing Sun, Dongqing Li

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Application of microfluidic chips in anticancer drug screening.Bosnian journal of basic medical sciences · 2022
    Review
  7. Microfluidic Microalgae System: A Review.Molecules (Basel, Switzerland) · 2022
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. 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

7 authors.

Junsheng WangCollege of Information and Science Technology, Dalian Maritime University, Dalian 116026, China. yqsun@dlmu.edu.cn.
Jinyang Sun
Yongxin Song
Yongyi Xu
Xinxiang Pan
Yeqing Sun
Dongqing Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detection of living microalgae cells is very important for ballast water treatment and analysis. Chlorophyll fluorescence is an indicator of photosynthetic activity and hence the living status of plant cells. In this paper, we developed a novel microfluidic biosensor system that can quickly and accurately detect the viability of single microalgae cells based on chlorophyll fluorescence. The system is composed of a laser diode as an excitation light source, a photodiode detector, a signal analysis circuit, and a microfluidic chip as a microalgae cell transportation platform. To demonstrate the utility of this system, six different living and dead algae samples (Karenia mikimotoi Hansen, Chlorella vulgaris, Nitzschia closterium, Platymonas subcordiformis, Pyramidomonas delicatula and Dunaliella salina) were tested. The developed biosensor can distinguish clearly between the living microalgae cells and the dead microalgae cells. The smallest microalgae cells that can be detected by using this biosensor are 3 μm ones. Even smaller microalgae cells could be detected by increasing the excitation light power. The developed microfluidic biosensor has great potential for in situ ballast water analysis.

Indexed as

Biosensing TechniquesChlorophyllFluorescenceMicroalgaeMicrofluidicsWater Pollutants, ChemicalWater PurificationChlorophyllWater Pollutants, Chemical

Identifiers

PMID24287532
PMCPMC3892884

What OpenQuestion holds

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Registered trials

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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.