L’estampe en partage

Manifestampe-Fédération nationale de l’estampe a organisé en mai dernier la troisième édition de la Fête de l’estampe, moment populaire à l’instar de la Fête de la musique. La manifestation a bénéficié du parrainage du ministère de la Culture et de la Communication. L’événement qui se déroule chaque année, partout en France, autour de la date du 26 mai, le jour même ou à partir de cette date, s’est révélé au printemps 2015 un indéniable succès. En 2013, elle avait déjà suscité la création de ..

A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

Estimating set similarity and detecting highly similar sets are fundamental problems in areas such as databases, machine learning, and information retrieval. MinHash is a well-known technique for approximating Jaccard similarity of sets and has been successfully used for many applications such as similarity search and large scale learning. Its two compressed versions, b-bit MinHash and Odd Sketch, can significantly reduce the memory usage of the original MinHash method, especially for estimating high similarities (i.e., similarities around 1). Although MinHash can be applied to static sets as well as streaming sets, of which elements are given in a streaming fashion and cardinality is unknown or even infinite, unfortunately, b-bit MinHash and Odd Sketch fail to deal with streaming data. To solve this problem, we design a memory efficient sketch method, MaxLogHash, to accurately estimate Jaccard similarities in streaming sets. Compared to MinHash, our method uses smaller sized registers (each register consists of less than 7 bits) to build a compact sketch for each set. We also provide a simple yet accurate estimator for inferring Jaccard similarity from MaxLogHash sketches. In addition, we derive formulas for bounding the estimation error and determine the smallest necessary memory usage (i.e., the number of registers used for a MaxLogHash sketch) for the desired accuracy. We conduct experiments on a variety of datasets, and experimental results show that our method MaxLogHash is about 5 times more memory efficient than MinHash with the same accuracy and computational cost for estimating high similarities

Public participation in national preparedness and response plans for pandemic influenza: toward an ethical contribution of public health policies

Faced with the threat of pandemic influenza, several countries have made the decision to put a number of measures in place which have been incorporated into national plans. In view of the magnitude of the powers and responsibilities that States assume in the event of a pandemic, a review of the various national preparedness and response plans for pandemic influenza brought to light a series of extremely important ethical concerns. Nevertheless, in spite of the recent emergence of literature focusing specifically on the ethical aspects of pandemics, too few studies explicitly examine public participation as one means of ethical contribution to public health policies. Thus this article seeks, in the first place, to present an analysis of the various national preparedness and response plans for pandemic influenza, and secondly, to outline the role that the plans envisage for ethics and more importantly for public participation

Data Science

International audienceLa data science, ou science des données, est la discipline qui traite de la collecte, de la préparation, de la gestion, de l'analyse, de l'interprétation et de la visualisation de grands ensembles de données complexes. Elle n'est pas seulement concernée par les outils et les méthodes pour obtenir, gérer et analyser les données ; elle consiste aussi à en extraire de la valeur et de la connaissance. Cet ouvrage présente les fondements scientifiques et les composantes essentielles de la science des données, à un niveau accessible aux étudiants de master et aux élèves ingénieurs. Notre souci a été de proposer un exposé cohérent reliant la théorie aux algorithmes développés dans ces domaines. Il s'adresse aux chercheurs et ingénieurs qui abordent les problématiques liées à la science des données, aux data scientists de PME qui utilisent en profondeur les outils d'apprentissage, mais aussi aux étudiants de master, doctorants ou encore futurs ingénieurs qui souhaitent un ouvrage de référence en data science. À qui s'adresse ce livre ? • Aux développeurs, statisticiens, étudiants et chefs de projets ayant à résoudre des problèmes de data science. • Aux data scientists, mais aussi à toute personne curieuse d'avoir une vue d'ensemble de l'état de l'art du machine learning

Practical Recommendations for Optimal Thromboprophylaxis in Patients with COVID-19: A Consensus Statement Based on Available Clinical Trials.

Coronavirus disease 2019 (COVID-19) has been shown to be strongly associated with increased risk for venous thromboembolism events (VTE) mainly in the inpatient but also in the outpatient setting. Pharmacologic thromboprophylaxis has been shown to offer significant benefits in terms of reducing not only VTE events but also mortality, especially in acutely ill patients with COVID-19. Although the main source of evidence is derived from observational studies with several limitations, thromboprophylaxis is currently recommended for all hospitalized patients with acceptable bleeding risk by all national and international guidelines. Recently, high quality data from randomized controlled trials (RCTs) further support the role of thromboprophylaxis and provide insights into the optimal thromboprophylaxis strategy. The aim of this statement is to systematically review all the available evidence derived from RCTs regarding thromboprophylaxis strategies in patients with COVID-19 in different settings (either inpatient or outpatient) and provide evidence-based guidance to practical questions in everyday clinical practice. Clinical questions accompanied by practical recommendations are provided based on data derived from 20 RCTs that were identified and included in the present study. Overall, the main conclusions are: (i) thromboprophylaxis should be administered in all hospitalized patients with COVID-19, (ii) an optimal dose of inpatient thromboprophylaxis is dependent upon the severity of COVID-19, (iii) thromboprophylaxis should be administered on an individualized basis in post-discharge patients with COVID-19 with high thrombotic risk, and (iv) thromboprophylaxis should not be routinely administered in outpatients. Changes regarding the dominant SARS-CoV-2 variants, the wide immunization status (increasing rates of vaccination and reinfections), and the availability of antiviral therapies and monoclonal antibodies might affect the characteristics of patients with COVID-19; thus, future studies will inform us about the thrombotic risk and the optimal therapeutic strategies for these patients

Genomic profiling distinguishes familial multiple and sporadic multiple meningiomas

<p>Abstract</p> <p>Background</p> <p>Meningiomas may occur either as familial tumors in two distinct disorders, familial multiple meningioma and neurofibromatosis 2 (NF2), or sporadically, as either single or multiple tumors in individuals with no family history. Meningiomas in NF2 and approximately 60% of sporadic meningiomas involve inactivation of the <it>NF2 </it>locus, encoding the tumor suppressor merlin on chromosome 22q. This study was undertaken to establish whether genomic profiling could distinguish familial multiple meningiomas from sporadic solitary and sporadic multiple meningiomas.</p> <p>Methods</p> <p>We compared 73 meningiomas presenting as sporadic solitary (64), sporadic multiple (5) and familial multiple (4) tumors using genomic profiling by array comparative genomic hybridization (array CGH).</p> <p>Results</p> <p>Sporadic solitary meningiomas revealed genomic rearrangements consistent with at least two mechanisms of tumor initiation, as unsupervised cluster analysis readily distinguished tumors with chromosome 22 deletion (associated with loss of the <it>NF2 </it>tumor suppressor) from those without chromosome 22 deletion. Whereas sporadic meningiomas without chromosome 22 loss exhibited fewer chromosomal imbalance events overall, tumors with chromosome 22 deletion further clustered into two major groups that largely, though not perfectly, matched with their benign (WHO Grade I) or advanced (WHO Grades II and III) histological grade, with the latter exhibiting a significantly greater degree of genomic imbalance (P < 0.001). Sporadic multiple meningiomas showed a frequency of genomic imbalance events comparable to the atypical grade solitary tumors. By contrast, familial multiple meningiomas displayed no imbalances, supporting a distinct mechanism for the origin for these tumors.</p> <p>Conclusion</p> <p>Genomic profiling can provide an unbiased adjunct to traditional meningioma classification and provides a basis for exploring the different genetic underpinnings of tumor initiation and progression. Most importantly, the striking difference observed between sporadic and familial multiple meningiomas indicates that genomic profiling can provide valuable information for differential diagnosis of subjects with multiple meningiomas and for considering the risk for tumor occurrence in their family members.</p

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality.

peer reviewedDespite advances in COVID-19 management, identifying patients evolving toward death remains challenging. To identify early predictors of mortality within 60 days of symptom onset (DSO), we performed immunovirological assessments on plasma from 279 individuals. On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain–specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation. A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA’s predictive accuracy was maintained at earlier time points, its quantitation can help us understand disease heterogeneity and identify patients who may benefit from new therapies