Low carbon technology performance vs infrastructure vulnerability: Analysis through the local and global properties space

Renewable energy technologies, necessary for low-carbon infrastructure networks, are being adopted to help reduce fossil fuel dependence and meet carbon mitigation targets. The evolution of these technologies has progressed based on the enhancement of technology-specific performance criteria, without explicitly considering the wider system (global) impacts. This paper presents a methodology for simultaneously assessing local (technology) and global (infrastructure) performance, allowing key technological interventions to be evaluated with respect to their effect on the vulnerability of wider infrastructure systems. We use exposure of low carbon infrastructure to critical material supply disruption (criticality) to demonstrate the methodology. A series of local performance changes are analyzed; and by extension of this approach, a method for assessing the combined criticality of multiple materials for one specific technology is proposed. Via a case study of wind turbines at both the material (magnets) and technology (turbine generators) levels, we demonstrate that analysis of a given intervention at different levels can lead to differing conclusions regarding the effect on vulnerability. Infrastructure design decisions should take a systemic approach; without these multilevel considerations, strategic goals aimed to help meet low-carbon targets, that is, through long-term infrastructure transitions, could be significantly jeopardized

Limited Phylogenetic Overlap Between Fluoroquinolone-Resistant Escherichia coli Isolated on Dairy Farms and those Causing Bacteriuria in Humans Living in the Same Geographical Region

BACKGROUND: Our primary aim was to test whether cattle-associated fluoroquinolone-resistant (FQ-R) Escherichia coli found on dairy farms are closely phylogenetically related to those causing bacteriuria in humans living in the same 50 × 50 km geographical region suggestive of farm–human sharing. Another aim was to identify risk factors for the presence of FQ-R E. coli on dairy farms. METHODS: FQ-R E. coli were isolated during 2017–18 from 42 dairy farms and from community urine samples. Forty-two cattle and 489 human urinary isolates were subjected to WGS, allowing phylogenetic comparisons. Risk factors were identified using a Bayesian regularization approach. RESULTS: Of 489 FQ-R human isolates, 255 were also third-generation-cephalosporin-resistant, with strong genetic linkage between aac(6’)Ib-cr and bla(CTX-M-15). We identified possible farm–human sharing for pairs of ST744 and ST162 isolates, but minimal core genome SNP distances were larger between farm–human pairs of ST744 and ST162 isolates (71 and 63 SNPs, respectively) than between pairs of isolates from different farms (7 and 3 SNPs, respectively). Total farm fluoroquinolone use showed a positive association with the odds of isolating FQ-R E. coli, while total dry cow therapy use showed a negative association. CONCLUSIONS: This work suggests that FQ-R E. coli found on dairy farms have a limited impact on community bacteriuria within the local human population. Reducing fluoroquinolone use may reduce the on-farm prevalence of FQ-R E. coli and this reduction may be greater when dry cow therapy is targeted to the ecology of resistant E. coli on the farm

Differentiation of lymphocytic‐plasmacytic enteropathy and small cell lymphoma in cats using histology‐guided mass spectrometry

BackgroundDifferentiation of lymphocytic-plasmacytic enteropathy (LPE) from small cell lymphoma (SCL) in cats can be challenging.Hypothesis/objectiveHistology-guided mass spectrometry (HGMS) is a suitable method for the differentiation of LPE from SCL in cats.AnimalsForty-one cats with LPE and 52 cats with SCL.MethodsThis is a retrospective clinicopathologic study. Duodenal tissue samples of 17 cats with LPE and 22 cats with SCL were subjected to HGMS, and the acquired data were used to develop a linear discriminate analysis (LDA) machine learning algorithm. The algorithm was subsequently validated using a separate set of 24 cats with LPE and 30 cats with SCL. Cases were classified as LPE or SCL based on a consensus by an expert panel consisting of 5-7 board-certified veterinary specialists. Histopathology, immunohistochemistry, and clonality testing were available for all cats. The panel consensus classification served as a reference for the calculation of test performance parameters.ResultsRelative sensitivity, specificity, and accuracy of HGMS were 86.7% (95% confidence interval [CI]: 74.5%-98.8%), 91.7% (95% CI: 80.6%-100%), and 88.9% (95% CI: 80.5%-97.3%), respectively. Comparatively, the clonality testing had a sensitivity, specificity, and accuracy of 85.7% (95% CI: 72.8%-98.7%), 33.3% (95% CI: 14.5%-52.2%), and 61.5% (95% CI: 48.3%-74.8%) relative to the panel decision.Conclusions and clinical importanceHistology-guided mass spectrometry was a reliable technique for the differentiation of LPE from SCL in duodenal formalin-fixed paraffin-embedded samples of cats and might have advantages over tests currently considered state of the art

Global impact of the first coronavirus disease 2019 (COVID-19) pandemic wave on vascular services

This online structured survey has demonstrated the global impact of the COVID-19 pandemic on vascular services. The majority of centres have documented marked reductions in operating and services provided to vascular patients. In the months during recovery from the resource restrictions imposed during the pandemic peaks, there will be a significant vascular disease burden awaiting surgeons. One of the most affected specialtie

Students' participation in collaborative research should be recognised

Letter to the editor