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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Subtyping of Swine Influenza Viruses Using a High-Throughput Real-Time PCR Platform
|
|---|---|
| Published in |
Frontiers in Cellular and Infection Microbiology, May 2018
|
| DOI | 10.3389/fcimb.2018.00165 |
| Pubmed ID | |
| Authors |
Nicole B. Goecke, Jesper S. Krog, Charlotte K. Hjulsager, Kerstin Skovgaard, Timm C. Harder, Solvej Ø. Breum, Lars E. Larsen |
| Abstract |
Influenza A viruses (IAVs) are important human and animal pathogens with high impact on human and animal health. In Denmark, a passive surveillance program for IAV in pigs has been performed since 2011, where screening tests and subsequent subtyping are performed by reverse transcription quantitative real-time PCR (RT-qPCR). A disadvantage of the current subtyping system is that several assays are needed to cover the wide range of circulating subtypes, which makes the system expensive and time-consuming. Therefore, the aim of the present study was to develop a high-throughput method, which could improve surveillance of swine influenza viruses (swIAVs) and lower the costs of virus subtyping. Twelve qPCR assays specific for various hemagglutinin and neuraminidase gene lineages relevant for swIAV and six assays specific for the internal genes of IAV were developed and optimized for the high-throughput qPCR platform BioMark (Fluidigm). The qPCR assays were validated and optimized to run under the same reaction conditions using a 48.48 dynamic array (48.48DA). The sensitivity and specificity was assessed by testing virus isolates and field samples with known subtypes. The results revealed a performance of the swIAV 48.48DA similar to conventional real-time analysis, and furthermore, the specificity of swIAV 48.48DA was very high and without cross reactions between the assays. This high-throughput system provides a cost-effective alternative for subtyping of swIAVs. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 20% |
| Student > Master | 6 | 14% |
| Student > Ph. D. Student | 6 | 14% |
| Student > Bachelor | 3 | 7% |
| Other | 3 | 7% |
| Other | 6 | 14% |
| Unknown | 11 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Veterinary Science and Veterinary Medicine | 10 | 23% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Agricultural and Biological Sciences | 6 | 14% |
| Immunology and Microbiology | 3 | 7% |
| Psychology | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 14 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 June 2018.
All research outputs
#17,962,718
of 23,070,218 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#4,196
of 6,543 outputs
Outputs of similar age
#238,784
of 330,076 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#87
of 112 outputs
Altmetric has tracked 23,070,218 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,543 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,076 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.