Efflux in Fungi: La Pièce de Résistance

Pathogens must be able to overcome both host defenses and antimicrobial treatment in order to successfully infect and maintain colonization of the host. One way fungi accomplish this feat and overcome intercellular toxin accumulation is efflux pumps, in particular ATP-binding cassette transporters and transporters of the major facilitator superfamily. Members of these two superfamilies remove many toxic compounds by coupling transport with ATP hydrolysis or a proton gradient, respectively. Fungal genomes encode a plethora of members of these families of transporters compared to other organisms. In this review we discuss the role these two fungal superfamilies of transporters play in virulence and resistance to antifungal agents. These efflux transporters are responsible not only for export of compounds involved in pathogenesis such as secondary metabolites, but also export of host-derived antimicrobial compounds. In addition, we examine the current knowledge of these transporters in resistance of pathogens to clinically relevant antifungal agents

Diagnostic challenge in a Tunisian patient with Familial Mediterranean Fever, sacroiliitis and coxitis

AbstractIntroductionFamilial Mediterranean Fever (FMF) is a hereditary auto inflammatory disease. The most common joint attack is an acute large joint monoarthritis most often affecting the knee or hip and lasting for several days. Rarely, a more protracted arthritis may occur.Case reportHerein, we describe a 47-year-old man with FMF in whom a few years elapsed before a definitive diagnosis could be made. The patient presented, since the age of 25, with a history of recurrent episodes of fever, abdominal pain, bloody diarrhea and intermittent attacks of acute bi-arthritis of hips. At the age of 40, he was referred under the suspicion of Spondylarthritis (SpA); in view of an inflammatory back pain, talalgia and bilateral coxitis. The result of blood tests suggested the presence of a high level of inflammation without leukocytosis. Human leukocyte antigen (HLA-B27) was negative. X-ray and computerized tomography of the pelvis showed an overall bilateral joint space narrowing of the hips and grade 3 bilateral sacroiliitis. During the hospitalization, he developed an acute episode of fever, abdominal pain and muscle contracture, spontaneously resolved in 12h. We suspected FMF based on the clinical course and family history, as one of his brothers had suffered similar abdominal crises since childhood. Molecular analysis for FMF was done, and demonstrated a homozygote mutation of M649V. A definitive diagnosis of FMF was then made. Oral administration of colchicine was followed by a remission.ConclusionClinicians should consider FMF with sacroiliitis and coxitis in the differential diagnosis of spondyloarthritis

S&D pattern deployment at organizational level : a prototype for remote healthcare system

The analysis of security incidents and frauds has shown that several vulnerabilities of IT systems are due to loopholes in the policies and procedures adopted by organizations as well as in their structure. Organizations have thus to address security and dependability issues by analyzing their organizational setting. In this paper, we present a methodology to support the deployment of Security & Dependability patterns according to their position in the Enterprise Architecture and the underlying system infrastructures. The methodology discriminates the pattern deployment process between recommendations and guidelines. Recommendations concretize the deployment with refined software and/or hardware related patterns, whereas guidelines specify the organizational patterns in terms of the system-to-be, proposing human-resource and/or policy solutions. To make the discussion more concrete, we illustrate the framework with a case study on an emergency scenario within a remote healthcare system

Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models

Latent factor models, EM algorithm, Conditional heteroskedasticity, HMM, Time series segmentation, Forecasting, 62H25, 62M05, 62M10, 62P20,