Evidence map›Paper›PMID 31598281›Full record

ArticleRoyal Society open science2019

Label-free sensitive detection of influenza virus using PZT discs with a synthetic sialylglycopolymer receptor layer.

Alexander S Erofeev, Petr V Gorelkin, Dmitry V Kolesov, Gleb A Kiselev, Evgeniy V Dubrovin, Igor V Yaminsky

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 26 citations in OpenAlex.

  1. Batteryless wireless magnetostrictive FeSensors and actuators. A, Physical · 2023
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  10. Glycan Nanobiosensors.Nanomaterials (Basel, Switzerland) · 2020
    Review
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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

6 authors at 3 institutions in 1 country.

Alexander S ErofeevLomonosov Moscow State University, 1, Leninskie Gory, Moscow 119991, Russia.ORCID 0000-0002-6631-821X
Petr V GorelkinMedical Nanotechnology LLC, Skolkovo, Russia.
Dmitry V KolesovFSBSI Institute of General Pathology and Pathophysiology, 8, Baltiyskaya st., Moscow 125315, Russia.
Gleb A KiselevAdvanced Technologies Center, 4-5-47, Stroiteley Street, Moscow 119311, Russia.
Evgeniy V DubrovinLomonosov Moscow State University, 1, Leninskie Gory, Moscow 119991, Russia.
Igor V YaminskyLomonosov Moscow State University, 1, Leninskie Gory, Moscow 119991, Russia.
Lomonosov Moscow State University · RUNational University of Science and Technology · RUResearch Institute of General Pathology and Pathophysiology, the Russian Academy of Medical Sciences · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We describe rapid, label-free detection of Influenza A viruses using the first radial mode of oscillations of lead zirconate titanate (PZT) piezoelectric discs with a 2 mm radius and 100 µm thickness fabricated from a piezoelectric membrane. The discs are modified with a synthetic sialylglycopolymer receptor layer, and the coated discs are inserted in a flowing virus suspension. Label-free detection of the virus is achieved by monitoring the disc radial mode resonance frequency shift. Piezo transducers with sialylglycopolymer sensor layers exhibited a long lifetime, a high sensitivity and the possibility of regeneration. We demonstrate positive, label-free detection of Influenza A viruses at concentrations below 10

Indexed as

biosensorinfluenzamicroelectromechanical systemssialylglycopolymervirus detection

Identifiers

PMID31598281
PMCPMC6774986
OpenAlexW2974112594

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.