PubMed · 16142121
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Pierre Joly. 2005. [Introductory speech].. https://doi.org/10.1016/s0003-4509(05)82285-0
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The Mediterranean population of tomato leaf curl New Delhi virus (ToLCNDV-ES) is characterized by a high genetic uniformity, distinguishing it from its Asian counterparts. ToLCNDV-ES is thought to have a monophyletic origin, likely resulting from a single recombination event, prior to its spread throughout the Mediterranean region. Following its first detection in southeastern France in 2020, ToLCNDV-ES re-emerged in France in 2022. Our analysis based on advanced long-read sequencing, circular DNA profiling, and phylogeny indicates both local persistence of French ToLCNDV-ES and multiple independent introduction events. Signatures of positive selection were identified in French ToLCNDV-ES populations, whereas no clear evidence of recombination was found. Bayesian time-structured phylogenetic analyses suggest that introductions in France occurred between 2018 and 2021 from the major ToLCNDV-ES clade, while several Italian ToLCNDV-ES isolates diverged prior to the virus introduction in the Mediterranean basin. Overall, this study demonstrates the value of an optimized long-read sequencing approach for resolving circular DNA virus diversity, and sheds light on the complex evolutionary history of ToLCNDV-ES in the Mediterranean Basin, particularly in southeastern France.
A large database (507 station-years) of daily suspended particulate matter (SPM) concentration and discharge data from 36 stations on river basins ranging from 600 km(2) to 600,000 km(2) in size (USA and Europe) was collected to assess the effects of SPM transport regime on bias and imprecision of flux estimates when using infrequent surveys and the discharge-weighted mean concentration method. By extracting individual SPM concentrations and corresponding discharge values from the database, sampling frequencies from 12 to 200 per year were simulated using Monte Carlo techniques. The resulting estimates of yearly SPM fluxes were compared to reference fluxes derived from the complete database. For each station and given frequency, bias was measured by the median of relative errors between estimated and reference fluxes, and imprecision by the difference between the upper and lower deciles of relative errors. Results show that the SPM transport regime of rivers affects the bias and imprecision of fluxes estimated by the discharge-weighted mean concentration method for given sampling frequencies (e.g. weekly, bimonthly, monthly). The percentage of annual SPM flux discharged in 2% of time (Ms(2)) is a robust indicator of SPM transport regime directly related to bias and imprecision. These errors are linked to the Ms(2) indicator for various sampling frequencies within a specific nomograph. For instance, based on a deviation of simulated flux estimates from reference fluxes lower than +/-20% and a bias lower than 1% or 2%, the required sampling intervals are less than 3 days for rivers with Ms(2) greater than 40% (basin size<10,000 km(2)), between 3 and 5 days for rivers with Ms(2) between 30 and 40% (basin size between 10,000 and 50,000 km(2)), between 5 and 12 days for Ms(2) from 20% to 30% (basin size between 50,000 and 200,000 km(2)), 12-20 days for Ms(2) in the 15-20% range (basin size between 200,000 and 500,000 km(2)).
This paper addresses the issue of how semantic information can be automatically assigned to compound terms, i.e. both a definition and a set of semantic relations. This is particularly crucial when elaborating multilingual databases and when developing cross-language information retrieval systems. The paper shows how morphosemantics can contribute in the constitution of multilingual lexical networks in biomedical corpora. It presents a system capable of labelling terms with morphologically related words, i.e. providing them with a definition, and grouping them according to synonymy, hyponymy and proximity relations. The approach requires the interaction of three techniques: (1) a language-specific morphosemantic parser, (2) a multilingual table defining basic relations between word roots and (3) a set of language-independent rules to draw up the list of related terms. This approach has been fully implemented for French, on an about 29,000 terms biomedical lexicon, resulting to more than 3000 lexical families. A validation of the results against a manually annotated file by experts of the domain is presented, followed by a discussion of our method.