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Fiorini, S.

Publications and source records attributed to Fiorini, S..

3 recordsLinked to original sources

Comparative seasonal abundance and diversity of populations of the Pseudomonas syringae and Soft Rot Pectobacteriaceae species complexes throughout the Durance River catchment from its French Alps sources to its delta

Rivers, creeks, streams are integrators of biological, chemical and physical processes occurring in a catchment linking land cover from the headwaters to the outlet. The dynamics of human and animal pathogens in catchments have been widely studied in a large variety of contexts allowing the optimization of disease risk reduction. In parallel, there is an emerging awareness that crop pathogens might also be disseminated via surface waters especially when they are used for irrigation. However, there are no studies on the extent to which potential plant pathogens are present - nor about their dynamics - along the full course of a catchment. Here we have compared the seasonal dynamics of populations of the Pseudomonas syringae (Psy) and the Soft Rot Pectobacteriaceae (SRP) species complexes along a 270 km stretch of the Durance River from the upstream alpine reaches to the downstream agricultural production areas at the confluence with the Rhone River at Avignon. Among 168 samples collected at 21 sites in fall, winter, spring and summer of 2016 and 2017, Psy strains were detected at all sampling sites and in 156 of the samples at population densities up to 105 bacteria L-1. In contrast, SRP strains were detected in 98 of the samples, mostly from the southern part of the river, at population densities that did not exceed 3 x 104 bacteria L-1. Among the biological and chemical parameters that were characterized at each sampling site, temperature was the only factor that explained a significant amount of the variability in population size for both species complexes. Psy densities decreased with increasing temperature whereas SRP densities increased with increasing temperature. River-borne populations of SRP were composed mainly of Pectobacterium versatile and P. aquaticum that have little known epidemiological importance. Only a few strains of Pectobacterium and Dickeya species reputed for their epidemiological impact were observed. In contrast, Psy populations at all sites were dominated by a genetic lineage of phylogroup 2 known from other studies for its broad host range and its geographic and habitat ubiquity. Our observations suggest that surveillance of river water for SRP could be leveraged to signal diagnostic and management reactions to avoid disease outbreaks. In contrast, the constant presence of Psy throughout the catchment in absence of regular and widespread disease outbreaks due to this group of bacteria suggests that surveillance should focus on future changes in land use, river water conditions and agronomic practices that could destabilize the mechanisms currently holding Psy outbreaks in check.

ecology↗

From behaviour to complex communities: Resilience to anthropogenic noise in a fish-induced trophic cascade

Sound emissions from human activities represent a pervasive environmental stressor. Individual responses in terms of behaviour, physiology or anatomy are well documented but whether they propagate through nested ecological interactions to alter complex communities needs to be better understood. This is even more relevant for freshwater ecosystems that harbour a disproportionate fraction of biodiversity but receive less attention than marine and terrestrial systems. We conducted a mesocosm investigation to study the effect of chronic exposure to motorboat noise on the dynamics of a freshwater community including phytoplankton, zooplankton, and roach as a planktivorous fish. As expected under the trophic cascade hypothesis, roach predation induced structural changes in the planktonic communities. Surprisingly, although roach changed their feeding behaviour in response to noise, the dynamics of the roach-dominated planktonic communities did not differ between noisy and noiseless mesocosms. This suggests that the top-down structuring influence of roach on planktonic communities might be resilient to noise and reveals the difficulties on extrapolating impacts form individual responses to complex communities.

ecology↗

Predicting diabetes second-line therapy initiation in the Australian population via timespan-guided neural attention network

IntroductionThe first line of treatment for people with diabetes is metformin. However, over the course of the disease metformin may fail to achieve appropriate glycemic control, and a second-line therapy becomes necessary. In this paper we introduce Tangle, a timespan-guided neural attention model that can accurately and timely predict the upcoming need for a second-line diabetes therapy from administrative data in the Australian adult population. The method could be used to design automatic therapy review recommendations for patients and their providers without the need to collect clinical measures. DataWe analyzed seven years of deidentified records (2008-2014) of the 10% publicly available linked sample of Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) electronic databases of Australia. MethodsBy design, Tangle can inherit the representational power of pre-trained word embedding, such as GloVe, to encode sequences of claims with the related MBS codes. The proposed attention mechanism can also natively exploit the information hidden in the timespan between two successive claims (measured in number of days). We compared the proposed method against state-of-the-art sequence classification methods. ResultsTangle outperforms state-of-the-art recurrent neural networks, including attention-based models. In particular, when the proposed timespan-guided attention strategy is coupled with pre-trained embedding methods, the model performance reaches an Area Under the ROC Curve of 90%, an improvement of almost 10 percentage points over an attentionless recurrent architecture. ImplementationTangle is implemented in Python using Keras and it is hosted on GitHub at https://github.com/samuelefiorini/tangle.

bioengineering↗