Evidence map›Paper›PMID 33225318›Full record

ArticleCell reports. Physical science2020

Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning.

Yang Xu, Adil M Rather, Shuang Song, Jen-Chun Fang, Robert L Dupont, Ufuoma I Kara, Yun Chang, Joel A Paulson, Rongjun Qin, Xiaoping Bao and 1 more

Open access · goldAbstract read
In one paragraph

Article in Cell reports. Physical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

15 citing papers in PubMed, 76 citations in OpenAlex.

  1. Article
  2. Article
  3. Aquatic Functional Liquid Crystals: Design, Functionalization, and Molecular Simulation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  4. Review
  5. Article
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  11. Article
  12. Review
  13. Chiral nematic liquid crystal droplets as a basis for sensor systems.Molecular systems design & engineering · 2022
    Article
  14. Review
  15. Trends in biosensing platforms forCurrent opinion in colloid & interface science · 2021
    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

11 authors at 2 institutions in 1 country.

Yang XuWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
Adil M RatherWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
Shuang SongDepartment of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH 43210, USA.
Jen-Chun FangWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
Robert L DupontWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
Ufuoma I KaraWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
Yun ChangDavidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47907, USA.
Joel A PaulsonWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
Rongjun QinDepartment of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH 43210, USA.
Xiaoping BaoDavidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47907, USA.
Xiaoguang WangWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA.
The Ohio State University · USPurdue University West Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid, robust virus-detection techniques with ultrahigh sensitivity and selectivity are required for the outbreak of the pandemic coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Here, we report that the femtomolar concentrations of single-stranded ribonucleic acid (ssRNA) of SARS-CoV-2 trigger ordering transitions in liquid crystal (LC) films decorated with cationic surfactant and complementary 15-mer single-stranded deoxyribonucleic acid (ssDNA) probe. More importantly, the sensitivity of the LC to the SARS ssRNA, with a 3-bp mismatch compared to the SARS-CoV-2 ssRNA, is measured to decrease by seven orders of magnitude, suggesting that the LC ordering transitions depend strongly on the targeted oligonucleotide sequence. Finally, we design a LC-based diagnostic kit and a smartphone-based application (app) to enable automatic detection of SARS-CoV-2 ssRNA, which could be used for reliable self-test of SARS-CoV-2 at home without the need for complex equipment or procedures.

Indexed as

biosensorCOVID-19liquid crystalsmachine learningpoint-of-care detection kitRNASARS-CoV-2self-assembly

Identifiers

PMID33225318
PMCPMC7670228
OpenAlexW3094491965

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.