Evidence map›Paper›PMID 36296112›Full record

ArticleMicromachines2022

A Sensitive and Portable Double-Layer Microfluidic Biochip for Harmful Algae Detection.

Ping Li, Le Qiang, Yingkuan Han, Yujin Chu, Jiaoyan Qiu, Fangteng Song, Min Wang, Qihang He, Yunhong Zhang, Mingyuan Sun and 5 more

Open access · goldAbstract read
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. 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

15 authors at 3 institutions in 1 country.

Ping LiInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Le QiangInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Yingkuan HanInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Yujin ChuInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Jiaoyan QiuInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Fangteng SongInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Min WangInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Qihang HeInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Yunhong ZhangInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Mingyuan SunInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Caiwen LiCAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China.
Shuqun SongCAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China.
Yun LiuCAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China.
Lin HanInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.ORCID 0000-0003-0461-2031
Yu ZhangInstitute of Marine Science and Technology, Shandong University, Qingdao 266000, China.
Shandong University of Science and Technology · CNChinese Academy of Sciences · CNStomatology Hospital · CN

Funding

Qingdao National Laboratory for Marine Science and Technology No. 2021QNLM040001-2the National Key R&D Plan of China Grant No. 2019YFC1407800
6 · The paper itself

Abstract

Harmful algal blooms (HABs) are common disastrous ecological anomalies in coastal waters. An effective algae monitoring approach is important for natural disaster warning and environmental governance. However, conducting rapid and sensitive detection of multiple algae is still challenging. Here, we designed an ultrasensitive, rapid and portable double-layer microfluidic biochip for the simultaneous quantitative detection of six species of algae. Specific DNA probes based on the 18S ribosomal DNA (18S rDNA) gene fragments of HABs were designed and labeled with the fluorescent molecule cyanine-3 (Cy3). The biochip had multiple graphene oxide (GO) nanosheets-based reaction units, in which GO nanosheets were applied to transfer target DNA to the fluorescence signal through a photoluminescence detection system. The entire detection process of multiple algae was completed within 45 min with the linear range of fluorescence recovery of 0.1 fM-100 nM, and the detection limit reached 108 aM. The proposed approach has a simple detection process and high detection performance and is feasible to conduct accurate detection with matched portable detection equipment. It will have promising applications in marine natural disaster monitoring and environmental care.

Indexed as

environmental warningharmful algal bloommicrofluidic biochipnuclei acids sensingphotoluminescence detection

Identifiers

PMID36296112
PMCPMC9611269
OpenAlexW4306761598

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.