ORCID Profile
0000-0001-9726-3082
Current Organisations
Université Sorbonne Paris Cité
,
Assistance Publique Hôpitaux de Paris
,
Institut Pasteur
,
Beihang University
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Publisher: Wiley
Date: 07-01-2015
DOI: 10.1002/QJ.2501
Publisher: Elsevier BV
Date: 04-2017
Publisher: Informa UK Limited
Date: 08-03-2021
Publisher: Elsevier BV
Date: 12-2020
Publisher: IEEE
Date: 04-2013
Publisher: Elsevier BV
Date: 07-2020
Publisher: Informa UK Limited
Date: 17-01-2022
Publisher: Elsevier BV
Date: 07-2020
Publisher: Informa UK Limited
Date: 15-12-2022
Publisher: American Society for Microbiology
Date: 28-04-2020
Abstract: In less than a decade, C. auris has emerged in health care settings worldwide this species is capable of colonizing skin and causing outbreaks of invasive candidiasis. In contrast to other Candida species, C. auris is unique in its ability to spread via nosocomial transmission and its high rates of drug resistance. As part of the public health response, whole-genome sequencing has played a major role in characterizing transmission dynamics and detecting new C. auris introductions. Through a global collaboration, we assessed genome evolution of isolates of C. auris from 19 countries. Here, we described estimated timing of the expansion of each C. auris clade and of fluconazole resistance, characterized discrete phylogeographic population structure of each clade, and compared genome data to sensitivity measurements to describe how antifungal resistance mechanisms vary across the population. These efforts are critical for a sustained, robust public health response that effectively utilizes molecular epidemiology.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Springer Nature Switzerland
Date: 2023
Publisher: AIP Publishing
Date: 06-05-2014
DOI: 10.1063/1.4875260
Abstract: Various definitions of coherent structures exist in turbulence research, but a common assumption is that coherent structures have correlated spectral phases. As a result, randomization of phases is believed, generally, to remove coherent structures from the measured data. Here, we reexamine these assumptions using atmospheric turbulence measurements. Small-scale coherent structures are detected in the usual way using the wavelet transform. A considerable percentage of the detected structures are not phase correlated, although some of them are clearly organized in space and time. At larger scales, structures have even higher degree of spatiotemporal coherence but are also associated with weak phase correlation. A series of specific ex les are shown to demonstrate this. These results warn about the vague terminology and assumptions around coherent structures, particularly for complex real-world turbulence.
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 07-2018
Publisher: IEEE
Date: 06-2012
Publisher: Elsevier BV
Date: 10-2022
Publisher: American Meteorological Society
Date: 27-02-2014
Abstract: Time series are characterized by a myriad of different shapes and structures. A number of events that appear in atmospheric time series result from as yet unidentified physical mechanisms. This is particularly the case for stable boundary layers, where the usual statistical turbulence approaches do not work well and increasing evidence relates the bulk of their dynamics to generally unknown in idual events. This study explores the possibility of extracting and classifying events from time series without previous knowledge of their generating mechanisms. The goal is to group large numbers of events in a useful way that will open a pathway for the detailed study of their characteristics, and help to gain understanding of events with previously unknown origin. A two-step method is developed that extracts events from background fluctuations and groups dynamically similar events into clusters. The method is tested on artificial time series with different levels of complexity and on atmospheric turbulence time series. The results indicate that the method successfully recognizes and classifies various events of unknown origin and even distinguishes different physical characteristics based only on a single-variable time series. The method is simple and highly flexible, and it does not assume any knowledge about the shape geometries, litudes, or underlying physical mechanisms. Therefore, with proper modifications, it can be applied to time series from a wider range of research areas.
Publisher: Springer Science and Business Media LLC
Date: 23-08-2023
Publisher: Elsevier BV
Date: 07-2022
Publisher: Public Library of Science (PLoS)
Date: 18-05-2018
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 10-2023
Publisher: Cold Spring Harbor Laboratory
Date: 07-01-2020
DOI: 10.1101/2020.01.06.896548
Abstract: Candida auris has emerged globally as a multidrug-resistant yeast that can spread via nosocomial transmission. An initial phylogenetic study of isolates from Japan, India, Pakistan, South Africa, and Venezuela revealed four populations (Clades I, II, III, and IV) corresponding to these geographic regions. Since this description, C. auris has been reported in over 30 additional countries. To trace this global emergence, we compared the genomes of 304 C. auris isolates from 19 countries on six continents. We found that four predominant clades persist across wide geographic locations. We observed phylogeographic mixing in most clades Clade IV, with isolates mainly from South America, demonstrated the strongest phylogeographic substructure. C. auris isolates from two clades with opposite mating types were detected contemporaneously in a single healthcare facility in Kenya. We estimated a Bayesian molecular clock phylogeny and dated the origin of each clade within the last 339 years outbreak-causing clusters from Clades I, III, and IV originated 34-35 years ago. We observed high rates of antifungal resistance in Clade I, including four isolates resistant to all three major classes of antifungals. Mutations that contribute to resistance varied between the clades, with Y132F in ERG11 as the most widespread mutation associated with azole resistance and S639P in FKS1 for echinocandin resistance. Copy number variants in ERG11 predominantly appeared in Clade III and were associated with fluconazole resistance. These results provide a global context for the phylogeography, population structure, and mechanisms associated with antifungal resistance in C. auris . In less than a decade, C. auris has emerged in healthcare settings worldwide this species is capable of colonizing skin and causing outbreaks of invasive candidiasis. In contrast to other Candida species, C. auris is unique in its ability to spread via nosocomial transmission and its high rates of drug resistance. As part of the public health response, whole-genome sequencing has played a major role in characterizing transmission dynamics and detecting new C. auris introductions. Through a global collaboration, we assessed genome evolution of isolates of C. auris from 19 countries. Here, we described estimated timing of the expansion of each C. auris clade and of fluconazole resistance, characterized discrete phylogeographic population structure of each clade, and compared genome data to sensitivity measurements to describe how antifungal resistance mechanisms vary across the population. These efforts are critical for a sustained, robust public health response that effectively utilizes molecular epidemiology.
Publisher: Elsevier BV
Date: 07-2022
Publisher: Cambridge University Press (CUP)
Date: 26-02-2015
Publisher: Cold Spring Harbor Laboratory
Date: 20-09-2017
DOI: 10.1101/191668
Abstract: The pathogenic fungus Cryptococcus neoformans exhibits morphological changes in cell size during lung infection, producing both typical size 5 to 7 µm cells and large titan cells ( 10 µm and up to 100 µm). We found and optimized in vitro conditions that produce titan cells in order to identify the ancestry of titan cells, the environmental determinants, and the key gene regulators of titan cell formation. Titan cells generated in vitro harbor the main characteristics of titan cells produced in vivo including their large cell size ( µm), polyploidy with a single nucleus, large vacuole, dense capsule, and thick cell wall. Here we show titan cells derived from the enlargement of progenitor cells in the population independent of yeast growth rate. Change in the incubation medium, hypoxia, nutrient starvation and low pH were the main factors that trigger titan cell formation, while quorum sensing factors like the initial inoculum concentration, pantothenic acid, and the quorum sensing peptide Qsp1p also impacted titan cell formation. Inhibition of ergosterol, protein and nucleic acid biosynthesis altered titan cell formation, as did serum, phospholipids and anti-capsular antibodies in our settings. We explored genetic factors important for titan cell formation using three approaches. Using H99-derivative strains with natural genetic differences, we showed that titan cell formation was dependent on LMP1 and SGF29 genes. By screening a gene deletion collection, we also confirmed that GPR4/5-RIM101 , and CAC1 genes were required to generate titan cells and that the PKR1 , TSP2 , USV101 genes negatively regulated titan cell formation. Furthermore, analysis of spontaneous Pkr1 loss-of-function clinical isolates confirmed the important role of the Pkr1 protein as a negative regulator of titan cell formation. Through development of a standardized and robust in vitro assay, our results provide new insights into titan cell biogenesis with the identification of multiple important factors athways. Cryptococcus neoformans is a yeast that is capable of morphological change upon interaction with the host. Particularly, in the lungs of infected mice, a subpopulation of yeast enlarges, producing cells up to 100 µm in cell body diameter – referred to as titan cells. Along with their large size, the titan cells have other unique characteristics such as thickened cell wall, dense capsule, polyploidization, large vacuole with peripheral nucleus and cellular organelles. The generation of a large number of such cells outside the lungs of mice has been described but was not reproducible nor standardized. Here we report standardized, reproducible, robust conditions for generation of titan cells and explored the environmental and genetic factors underlying the genesis of these cells. We showed that titan cells were generated upon stresses such as change in the incubation medium, nutrient deprivation, hypoxia and low pH. Using collections of well characterized reference strains and clinical isolates, we validated with our model that the cAMP/PKA/Rim101 pathway is a major genetic determinant of titan cell formation. This study opens the way for a more comprehensive picture of the ontology of morphological changes in Cryptococcus neoformans and its impact on pathobiology of this deadly pathogen.
Publisher: MDPI AG
Date: 25-08-2023
Abstract: ChatGPT, a state-of-the-art large language model (LLM), is revolutionizing the AI field by exhibiting humanlike skills in a range of tasks that include understanding and answering natural language questions, translating languages, writing code, passing professional exams, and even composing poetry, among its other abilities. ChatGPT has gained an immense popularity since its launch, amassing 100 million active monthly users in just two months, thereby establishing itself as the fastest-growing consumer application to date. This paper discusses the reasons for its success as well as the future prospects of similar large language models (LLMs), with an emphasis on their potential impact on forecasting, a specialized and domain-specific field. This is achieved by first comparing the correctness of the answers of the standard ChatGPT and a custom one, trained using published papers from a subfield of forecasting where the answers to the questions asked are known, allowing us to determine their correctness compared to those of the two ChatGPT versions. Then, we also compare the responses of the two versions on how judgmental adjustments to the statistical/ML forecasts should be applied by firms to improve their accuracy. The paper concludes by considering the future of LLMs and their impact on all aspects of our life and work, as well as on the field of forecasting specifically. Finally, the conclusion section is generated by ChatGPT, which was provided with a condensed version of this paper and asked to write a four-paragraph conclusion.
No related grants have been discovered for Alexandre Alanio.