Evidence map›Paper›PMID 35554901›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Diagnostic Method for COVID-19 Using Sugar Chain-Immobilized Nanoparticles and Saliva Specimens.

Yasuo Suda, Yasuhisa Tajima, Jun-Ichiro Nishi, Takashi Kajiya

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
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

4 authors at 2 institutions in 1 country.

Yasuo SudaDepartment of Chemistry and Biotechnology, Graduate School of Science and Engineering, Kagoshima University, Kagoshima, Japan. ysuda@sudxbiotec.jp.
Yasuhisa TajimaDivision of Infectious Disease, Hamamatsu Medical Center, Shizuoka, Japan.
Jun-Ichiro NishiDepartment of Microbiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan.
Takashi KajiyaClinical Research Center, Tenyoukai Central Hospital, Kagoshima, Japan.
Kagoshima University · JPHamamatsu Medical Center · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of viruses that infects animals or plants, and determination of their quantity are essential for the diagnosis of infectious disease and for the determination of a strategy in the treatment of virus-derived diseases. However, the concentration of viruses existing in a living body (in bodily fluid), food, drinking water, river water, and so on. is not high enough to be detected using conventional diagnostic methods. For example, since the concentration of influenza virus released from an infected person is less than the detection limit of conventional simple examination kits (rapid kit) or even a PCR process at the initial stage of infection, it is difficult to detect the presence of influenza virus which will lead to influenza disease. Our technology allows for safe, efficient, and selective concentration of viruses without troublesome ultracentrifugation, using sugar chain-immobilized metal nanoparticles based on the binding interaction between viruses and sugar chains. For COVID-19, we have developed and commercialized two molecular diagnosis kits: SUDx SARS-CoV-2 detection kit, and SGNP nCoV/Flu PCR detection kit, for the Japanese market in 2020.

Indexed as

COVID-19Influenza, HumanNanoparticlesAnimalsHumansSalivaSARS-CoV-2Sensitivity and SpecificitySugarsSugarsCopy numberIsolationLigandSGNPSMGNPSpike domainSugar chain

Identifiers

PMID35554901
OpenAlexW4285171519

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.