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- Menkveld, Albert J., et al.
(author)
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Nonstandard Errors
- 2024
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In: JOURNAL OF FINANCE. - : Wiley-Blackwell. - 0022-1082 .- 1540-6261. ; 79:3, s. 2339-2390
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Journal article (peer-reviewed)abstract
- In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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- Delgado, Luis Fernando, et al.
(author)
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Phylogeny-based comparative genomics of Vibrio vulnificus links genetic traits to pathogenicity
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Other publication (other academic/artistic)abstract
- Vibrio vulnificus is a natural part of the microbiome of brackish waters worldwide. It is also an opportunistic pathogen that can cause severe infections and septicemia via consumption of seafood or through wound infections. The species possess diverse virulence factors, yet its precise disease mechanism remains undefined. Comparative genomics between clinical and environmental isolates offers a means to identify key virulence genes, but the scarcity of environmental isolates for V. vulnificus has constituted a significant limitation. Here we sequenced genomes of 82 V. vulnificus isolates from water, sediment and seagrass surface from stations along the Baltic Sea coast and complemented these with 208 and 117 previously sequenced clinical and environmental genomes, respectively, in a comparative analysis. Phylogenetic reconstruction corroborated earlier analysis with four main lineages forming within the species. Strains from the Baltic Sea region were confined to certain phylogenetic lineages (L4 and sublineages L2c and L2e) whereas clinical and environmental strains were found in all lineages, indicting that the phylogenetic structure of V. vulnificus reflects adaptations to specific environmental conditions rather than pathogenicity. Employing orthologue enrichment analysis in a phylogenetic framework using the PhyloBOTL pipeline developed in this work revealed 58 significantly enriched orthologs in clinical compared to environmental isolates. These orthologs were grouped into 18 co-localisation clusters based on the corresponding genes’ proximity in the genomes. The co-localisation clusters entailed clusters with 1 genes previously linked with pathogenicity in V. vulnificus, such as genes for capsular polysaccharide (CPS) synthesis and biofilm formation, but also clusters with genes not previously associated with virulence in the species. Examples of the latter were genes for pilus biosynthesis of the usher-chaperone (CU) pathway, for spermidine synthesis, and for effector proteins of the Type VI secretion system. Finally we leveraged on the clinically enriched genes to design PCR primers for detection and surveillance of pathogenic V. vulnificus strains.
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- Riedinger, David J., et al.
(author)
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Control of Vibrio vulnificus proliferation in the Baltic Sea through eutrophication and algal bloom management
- 2024
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In: Communications Earth & Environment. - : Springer Nature. - 2662-4435. ; 5:1
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Journal article (peer-reviewed)abstract
- Due to climate change the pathogenic bacterium Vibrio vulnificus proliferates along brackish coastlines, posing risks to public health, tourism, and aquaculture. Here we investigated previously suggested regulation measures to reduce the prevalence of V. vulnificus, locally through seagrass and regionally through the reduction of eutrophication and consequential formation of algal blooms. Field samples collected in the summer of 2021 covered the salinity and eutrophication gradients of the Baltic Sea, one of the largest brackish areas worldwide. Physico-, biological- and hydrochemical parameters were measured and variables explaining V. vulnificus occurrence were identified by machine learning. The best V. vulnificus predictors were eutrophication-related features, such as particulate organic carbon and nitrogen, as well as occurrence of potential phytoplankton blooms and associated species. V. vulnificus abundance did not vary significantly between vegetated and non-vegetated areas. Thus, reducing nutrient inputs could be an effective method to control V. vulnificus populations in eutrophied brackish coasts.
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