1. |
- Bravo, L, et al.
(author)
-
- 2021
-
swepub:Mat__t
|
|
2. |
- Tabiri, S, et al.
(author)
-
- 2021
-
swepub:Mat__t
|
|
3. |
|
|
4. |
- El-Wekil, Mohamed M., et al.
(author)
-
An innovative dual recognition aptasensor for specific detection of Staphylococcus aureus based on Au/Fe3O4 binary hybrid
- 2022
-
In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12:1
-
Journal article (peer-reviewed)abstract
- Pathogenic bacteria cause disease outbreaks and threaten human health, prompting the research on advanced detection assays. Herein, we developed a selective molecular imprinted aptasensor for sensitive and prompt quantitation of Staphylococcus aureus (S. aureus) bacteria. The aptasensor was constructed by immobilization of aptamer on gold nanoparticles modified magnetic nanoparticles (apt-AuNPs@ Fe3O4). A functional monomer (o-phenylenediamine, o-phen) was electro-polymerized on the surface of the as-synthesized nanocomposite in the presence of a template (S. aureus). After removing S. aureus, the formed imprinted sites were available to extract pathogenic bacteria from complicated matrices. The surface morphology of the as-fabricated nanocomposites was characterized using different spectroscopic and electrochemical methods. Moreover, we thoroughly evaluated factors affecting the synthesis and determination procedures. The molecular imprinted aptasensor exhibited a wide linear range of 10(1)-10(7) CFU mL(-1) with a Limit of Detection, LOD (signal to noise = 3) of 1 CFU mL(-1). The aptasensor detected S. aureus in milk, conduit water, and apple juice samples with good recoveries % and satisfactory relative standard deviations (RSDs %) values.
|
|
5. |
|
|
6. |
- Kattge, Jens, et al.
(author)
-
TRY plant trait database - enhanced coverage and open access
- 2020
-
In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
-
Journal article (peer-reviewed)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
|
|
7. |
|
|