Evidence map›Paper›PMID 32964289›Full record

ArticleWorld journal of microbiology & biotechnology2020

Development and application of a colloidal carbon test strip for the detection of antibodies against Mycoplasma bovis.

Feng Shi, Yang Zhao, Yixiao Sun, Chuangfu Chen

Abstract read
In one paragraph

Article in World journal of microbiology & biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

4 authors.

Feng ShiCollege of Life Science, Shihezi University, Shihezi, Xinjiang, 832003, P. R. China. shifeng2314@yeah.net.ORCID http://orcid.org/0000-0002-2407-1239
Yang ZhaoCollege of Animal Science and Technology, Shihezi University, Shihezi, Xinjiang, 832003, P. R. China.
Yixiao SunCollege of Life Science, Shihezi University, Shihezi, Xinjiang, 832003, P. R. China.
Chuangfu ChenCollege of Animal Science and Technology, Shihezi University, Shihezi, Xinjiang, 832003, P. R. China. ccf-xb@163.com.

Funding

Shihezi University 2017AA003
6 · The paper itself

Abstract

Mycoplasma bovis (M. bovis) is an important bovine mycoplasma implicated in economically important clinical diseases, such as respiratory diseases, otitis media, and mastitis. The prevalence of M. bovis-associated mastitis in both cattle and buffaloes has been increasingly recognized as a global problem. High morbidity rates and consequential economic losses have been devastating to the affected cattle and buffalo farms, especially those in developing countries. Therefore, a rapid and accurate method is urgently needed to detect M. bovis. In this study, a rapid and simple lateral flow strip for detecting antibodies against M. bovis was established that used carbon nanoparticles (CNPs) as the labelled materials. The results from the test strip were highly consistent with those from ELISA. The test showed high specificity (100%) and no cross-reaction with other bovine pathogens. The detection sensitivity of the test was also relatively high (97.67%). All the results indicated that the colloidal carbon test strip could serve as a simple, rapid, sensitive, and specific diagnostic method for detecting antibodies against M. bovis at cattle farms.

Indexed as

AnimalsAntibodies, BacterialCarbonCattleCattle DiseasesEnzyme-Linked Immunosorbent AssayLimit of DetectionMycoplasma bovisMycoplasma InfectionsNanotubes, CarbonPovidoneReagent StripsAntibodies, BacterialCarboncarbon colloidNanotubes, CarbonPovidoneReagent StripsColloidal carbonELISALateral flowMycoplasma bovisVisual detection

Identifiers

PMID32964289
PMCPMC7508640

What OpenQuestion holds

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Registered trials

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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.