Gametocytes infectiousness to mosquitoes: variable selection using random forests, and zero inflated models

Malaria control strategies aiming at reducing disease transmission intensity may impact both oocyst intensity and infection prevalence in the mosquito vector. Thus far, mathematical models failed to identify a clear relationship between Plasmodium falciparum gametocytes and their infectiousness to mosquitoes. Natural isolates of gametocytes are genetically diverse and biologically complex. Infectiousness to mosquitoes relies on multiple parameters such as density, sex-ratio, maturity, parasite genotypes and host immune factors. In this article, we investigated how density and genetic diversity of gametocytes impact on the success of transmission in the mosquito vector. We analyzed data for which the number of covariates plus attendant interactions is at least of order of the sample size, precluding usage of classical models such as general linear models. We then considered the variable importance from random forests to address the problem of selecting the most influent variables. The selected covariates were assessed in the zero inflated negative binomial model which accommodates both over-dispersion and the sources of non infected mosquitoes. We found that the most important covariates related to infection prevalence and parasite intensity are gametocyte density and multiplicity of infection

CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer

While existing makeup style transfer models perform an image synthesis whose results cannot be explicitly controlled, the ability to modify makeup color continuously is a desirable property for virtual try-on applications. We propose a new formulation for the makeup style transfer task, with the objective to learn a color controllable makeup style synthesis. We introduce CA-GAN, a generative model that learns to modify the color of specific objects (e.g. lips or eyes) in the image to an arbitrary target color while preserving background. Since color labels are rare and costly to acquire, our method leverages weakly supervised learning for conditional GANs. This enables to learn a controllable synthesis of complex objects, and only requires a weak proxy of the image attribute that we desire to modify. Finally, we present for the first time a quantitative analysis of makeup style transfer and color control performance

Global Sensitivity Analysis: a tool to analyse LCA variability of energy systems

International audiencePolicy makers are nowadays debating about the future electricity mixes that should be deployed. The environmental impacts of electricity generation systems is one of the central issue for this debate. They have been widely assessed over the past decades, in particular with the LCA approach. Several literature reviews have shown the large variability associated with these results. It leads sometimes policy makers to consider LCA as an inconclusive method. Improving the understanding of the LCA results variability origins is a key issue to extend the use of LCA as a decision support tool. One approach to adress variability are sensitivity analysis (SA). However, when dealing with environmental impact assessment, most SAs remain at a local level or evaluate the variation of the input parameters one factor at a time. These approaches only partially reflect the LCA results variability, indeed, it does not consider the full range of input parameters interval and their probability distribution. To overcome these limitations, Global Sensitivity Analysis (GSA) approach has been developped in statistics. It enables apportioning the results variability of a model to its different input parameter variability, by varying all of them simultaneously according to their probability distributions. This link between result variability and parameter variability is quantitatively evaluated by the calculation of the so called Sobol indices. While it has been applied in only a few analyses in the field of environmental impact assessment, this statistical tool is yet to be embedded in LCA methodology. Thereby, this paper aims at proposing a method to implement GSA in the LCA field to adress the results variability issue related to energy pathways

Oligodendroglial Argonaute protein Ago2 associates with molecules of the Mbp mRNA localization machinery and is a downstream target of Fyn kinase

Oligodendrocytes myelinate neuronal axons in the central nervous system (CNS) facilitating rapid transmission of action potentials by saltatory conduction. Myelin basic protein (MBP) is an essential component of myelin and its absence results in severe hypomyelination in the CNS of rodents. Mbp mRNA is not translated immediately after exit from the nucleus in the cytoplasm, but is transported to the plasma membrane in RNA transport granules in a translationally silenced state. We have previously identified the small non-coding RNA 715 (sncRNA715) as an inhibitor of Mbp translation associated with RNA granules. Argonaute (Ago) proteins and small RNAs form the minimal core of the RNA induced silencing complex and together recognize target mRNAs to be translationally inhibited or degraded. Recently, tyrosine phosphorylation of Ago2 was reported to be a regulator of small RNA binding. The oligodendroglial non-receptor tyrosine kinase Fyn is activated by neuronal signals and stimulates the translation of Mbp mRNA at the axon-glial contact site. Here we analyzed the expression of Ago proteins in oligodendrocytes, if they associate with Mbp mRNA transport granules and are tyrosine phosphorylated by Fyn. We show that all Ago proteins (Ago1-4) are expressed by oligodendrocytes and that Ago2 colocalizes with hnRNP A2 in granular cytoplasmic structures. Ago2 associates with hnRNP A2, Mbp mRNA, sncRNA715 and Fyn kinase and is tyrosine phosphorylated in response to Fyn activity. Our findings suggest an involvement of Ago2 in the translational regulation of Mbp. The identification of Ago proteins as Fyn targets will foster further research to understand in more molecular detail how Fyn activity regulates Mbp translation

Parrains et voisins? Espace et parrainage en banlieue parisienne au XIXe siècle

Située à proximité de Paris, Aubervilliers, au cours du XIXe siècle, connaît une forte croissance de sa population et une transformation de son tissu social avec l’arrivée de migrants et l’orientation des activités économiques vers l’industrie au détriment de l’agriculture traditionnelle. Dans le cadre d’une réfl exion générale concernant la place du parrainage dans la construction des liens sociaux et particulièrement de la sociabilité communautaire à l’échelle locale, la distribution spatiale des parrains et marraines des enfants baptisés dans l’unique église paroissiale de la localité a été analysée sur trois siècles, afi n de montrer la fi n progressive du parrainage entre voisins appartenant à une même communauté, la paroisse, entre XVIIIe siècle et XIXe siècle, et l’élargissement du bassin de recrutement des parents spirituels, celui-ci témoignant du recul de l’esprit communautaire ancien. Au XIXe siècle, quand les choix dans la parenté n’amènent pas à aller quérir des parrains loin d’Aubervilliers, d’autres types de parrains voisins apparaissent: les gens du quartier, voire les voisins d’immeuble, prennent alors une place importante, notamment dans le quartier ouvrier peuplé de migrants de Quatre Chemins-Champ Blanc, au sud de la commune. Il ressort ainsi de l’analyse détaillée des baptêmes de 1881 que l’espace de la banlieue était loin d’être uniforme. Par beaucoup d’aspects dont le parrainage, Aubervilliers était bien une «périphérie» de Paris (cf. la proportion de parrains et marraines vivant dans la capitale), mais en son sein plusieurs quartiers, où des logiques de choix diff érentes étaient mises en oeuvre au moment des baptêmes, coexistaient

Séptimo Congreso de la Asociación de Estudios Bolivianos (AEB)

Del 29 de julio al 1º de agosto se desarrolló en la ciudad de Sucre, el séptimo congreso de la Asociación de Estudios Bolivianos (AEB). La AEB es una organización sin fines de lucro que nació en New Orleans (Estados Unidos) y que agrupa a investigadores especializados en Bolivia, procedentes de todas partes del mundo. El propósito de la Asociación, según sus documentos de presentación institucional, es promover la investigación y el conocimiento sobre Bolivia proporcionando un foro interdisci..

Extending Resource Monotones using Kan Extensions

In this paper we generalize the framework proposed by Gour and Tomamichel regarding extensions of monotones for resource theories. A monotone for a resource theory assigns a real number to each resource in the theory signifying the utility or the value of the resource. Gour and Tomamichel studied the problem of extending monotones using set-theoretical framework when a resource theory embeds fully and faithfully into the larger theory. One can generalize the problem of computing monotone extensions to scenarios when there exists a functorial transformation of one resource theory to another instead of just a full and faithful inclusion. In this article, we show that (point-wise) Kan extensions provide a precise categorical framework to describe and compute such extensions of monotones. To set up monontone extensions using Kan extensions, we introduce partitioned categories (pCat) as a framework for resource theories and pCat functors to formalize relationship between resource theories. We describe monotones as pCat functors into $([0,\infty], \leq)$, and describe extending monotones along any pCat functor using Kan extensions. We show how our framework works by applying it to extend entanglement monotones for bipartite pure states to bipartite mixed states, to extend classical divergences to the quantum setting, and to extend a non-uniformity monotone from classical probabilistic theory to quantum theory.Comment: Accepted at Applied Category Theory 2022, 19 page

Gametocytes infectiousness to mosquitoes: variable selection using random forests, and zero inflated models

Malaria control strategies aiming at reducing disease transmission intensity may impact both oocyst intensity and infection prevalence in the mosquito vector. Thus far, mathematical models failed to identify a clear relationship between Plasmodium falciparum gametocytes and their infectiousness to mosquitoes. Natural isolates of gametocytes are genetically diverse and biologically complex. Infectiousness to mosquitoes relies on multiple parameters such as density, sex-ratio, maturity, parasite genotypes and host immune factors. In this article, we investigated how density and genetic diversity of gametocytes impact on the success of transmission in the mosquito vector. We analyzed data for which the number of covariates plus attendant interactions is at least of order of the sample size, precluding usage of classical models such as general linear models. We then considered the variable importance from random forests to address the problem of selecting the most influent variables. The selected covariates were assessed in the zero inflated negative binomial model which accommodates both over-dispersion and the sources of non infected mosquitoes. We found that the most important covariates related to infection prevalence and parasite intensity are gametocyte density and multiplicity of infection