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Rapid and specific SPRi detection of L. pneumophila in complex environmental water samples

Overview of attention for article published in Analytical & Bioanalytical Chemistry, May 2015
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  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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3 tweeters

Citations

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12 Dimensions

Readers on

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34 Mendeley
Title
Rapid and specific SPRi detection of L. pneumophila in complex environmental water samples
Published in
Analytical & Bioanalytical Chemistry, May 2015
DOI 10.1007/s00216-015-8726-y
Pubmed ID
Authors

Amir M. Foudeh, Hana Trigui, Nilmini Mendis, Sebastien P. Faucher, Teodor Veres, Maryam Tabrizian

Abstract

Legionellosis is a very devastating disease worldwide mainly due to unpredictable outbreaks in man-made water systems. Developing a highly specific and sensitive rapid detection system that detects only metabolically active bacteria is a main priority for water quality assessment. We previously developed a versatile technique for sensitive and specific detection of synthetic RNA. In the present work, we further investigated the performance of the developed biosensor for detection of Legionella pneumophila in complex environmental samples, particularly those containing protozoa. The specificity and sensitivity of the detection system were verified using total RNA extracted from L. pneumophila in spiked water co-cultured with amoebae. We demonstrated that the expression level of ribosomal RNA (rRNA) is extremely dependent on the environmental conditions. The presence of amoebae with L. pneumophila, especially in nutrition-deprived samples, increased the amount of L. pneumophila 15-fold after 1 week as measured through the expression of 16s rRNA. Using the developed surface plasmon resonance imaging (SPRi) detection method, we were also able to successfully detect L. pneumophila within 3 h, both in the presence and absence of amoebae in the complex environmental samples obtained from a cooling water tower. These findings suggest that the developed biosensing system is a viable method for rapid, real-time and effective detection not only for L. pneumophila in environmental samples but also to assess the risk associated with the use of water contaminated with other pathogens.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Portugal 1 3%
Unknown 32 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Student > Master 7 21%
Unspecified 5 15%
Researcher 5 15%
Student > Doctoral Student 4 12%
Other 4 12%
Readers by discipline Count As %
Unspecified 10 29%
Engineering 7 21%
Agricultural and Biological Sciences 6 18%
Environmental Science 3 9%
Immunology and Microbiology 2 6%
Other 6 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 03 July 2015.
All research outputs
#7,342,842
of 12,230,555 outputs
Outputs from Analytical & Bioanalytical Chemistry
#2,247
of 4,657 outputs
Outputs of similar age
#114,481
of 225,175 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#48
of 235 outputs
Altmetric has tracked 12,230,555 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,657 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 49th percentile – i.e., 49% 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 225,175 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 235 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.