Evidence mapPaperPMID 38248397Full record

ArticleBiosensors2023

Nanoisland SERS-Substrates for Specific Detection and Quantification of Influenza A Virus.

Gleb Zhdanov, Alexandra Gambaryan, Assel Akhmetova, Igor Yaminsky, Vladimir Kukushkin, Elena Zavyalova

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 22% 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, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. 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

6 authors at 3 institutions in 1 country.

Gleb ZhdanovChemistry Department of Lomonosov Moscow State University, 119991 Moscow, Russia.ORCID 0000-0003-4082-9684
Alexandra GambaryanChumakov Federal Scientific Centre for Research and Development of Immune and Biological Products RAS, 108819 Moscow, Russia.ORCID 0000-0002-1892-0548
Assel AkhmetovaPhysics Department of Lomonosov Moscow State University, 119991 Moscow, Russia.
Igor YaminskyPhysics Department of Lomonosov Moscow State University, 119991 Moscow, Russia.
Vladimir KukushkinOsipyan Institute of Solid State Physics of the Russian Academy of Science, 142432 Chernogolovka, Russia.ORCID 0000-0001-6731-9508
Elena ZavyalovaChemistry Department of Lomonosov Moscow State University, 119991 Moscow, Russia.ORCID 0000-0001-5260-1973
Lomonosov Moscow State University · RUMoscow Institute of Physics and Technology · RUOsipyan Institute of Solid State Physics RAS · RU

Funding

Russian Science Foundation № 19-72-30003, https://rscf.ru/project/19-72-30003/
6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy (SERS)-based aptasensors for virus determination have attracted a lot of interest recently. This approach provides both specificity due to an aptamer component and a low limit of detection due to signal enhancement by a SERS substrate. The most successful SERS-based aptasensors have a limit of detection (LoD) of 10-100 viral particles per mL (VP/mL) that is advantageous compared to polymerase chain reactions. These characteristics of the sensors require the use of complex substrates. Previously, we described silver nanoisland SERS-substrate with a reproducible and uniform surface, demonstrating high potency for industrial production and a suboptimal LoD of 4 × 10

Indexed as

Influenza A virusMetal NanoparticlesChromiumSilverSpectrum Analysis, RamanChromiumSilveraptameraptasensorinfluenzananoislandSERS

Identifiers

PMID38248397
PMCPMC10813417
OpenAlexW4390403487

What Socratic 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 Socratic graph.