Enteropathogenic Escherichia coli

peer reviewedSerogroup O80 was detected in 40% of 104 enteropathogenic Escherichia coli isolates from calves with diarrhea from 42 farms in Belgium during 2008‒2015. These isolates harbored the eae-ξ and fliCH2 genes, similar to the O80 attaching-effacing Shigatoxigenic E. coli isolates found in humans in France. This strain might be emerging

Hybrid multicriteria fuzzy classification of network traffic patterns, anomalies, and protocols

© 2017, Springer-Verlag London Ltd., part of Springer Nature. Traffic classification in computer networks has very significant roles in network operation, management, and security. Examples include controlling the flow of information, allocating resources effectively, provisioning quality of service, detecting intrusions, and blocking malicious and unauthorized access. This problem has attracted a growing attention over years and a number of techniques have been proposed ranging from traditional port-based and payload inspection of TCP/IP packets to supervised, unsupervised, and semi-supervised machine learning paradigms. With the increasing complexity of network environments and support for emerging mobility services and applications, more robust and accurate techniques need to be investigated. In this paper, we propose a new supervised hybrid machine-learning approach for ubiquitous traffic classification based on multicriteria fuzzy decision trees with attribute selection. Moreover, our approach can handle well the imbalanced datasets and zero-day applications (i.e., those without previously known traffic patterns). Evaluating the proposed methodology on several benchmark real-world traffic datasets of different nature demonstrated its capability to effectively discriminate a variety of traffic patterns, anomalies, and protocols for unencrypted and encrypted traffic flows. Comparing with other methods, the performance of the proposed methodology showed remarkably better classification accuracy

TB or Not TB: That Is No Longer the Question

Tuberculosis (TB) remains a devastating infectious disease and, with the emergence of multidrug-resistant forms, represents a major global threat. Much of our understanding of pathogenic and immunologic mechanisms in TB has derived from studies in experimental animals. However, it is becoming increasingly clear in TB as well as in other inflammatory diseases that there are substantial differences in immunological responses of humans not found or predicted by animal studies. Thus, it is critically important to understand mechanisms of pathogenesis and immunological protection in humans. In this review, we will address the key immunological question: What are the necessary and sufficient immune responses required for protection against TB infection and disease in people-specifically protection against infection, protection against the establishment of latency or persistence, and protection against transitioning from latent infection to active disease

Ofatumumab versus Teriflunomide in Multiple Sclerosis

BACKGROUND: Ofatumumab, a subcutaneous anti-CD20 monoclonal antibody, selectively depletes B cells. Teriflunomide, an oral inhibitor of pyrimidine synthesis, reduces T-cell and B-cell activation. The relative effects of these two drugs in patients with multiple sclerosis are not known. METHODS: In two double-blind, double-dummy, phase 3 trials, we randomly assigned patients with relapsing multiple sclerosis to receive subcutaneous ofatumumab (20 mg every 4 weeks after 20-mg loading doses at days 1, 7, and 14) or oral teriflunomide (14 mg daily) for up to 30 months. The primary end point was the annualized relapse rate. Secondary end points included disability worsening confirmed at 3 months or 6 months, disability improvement confirmed at 6 months, the number of gadolinium-enhancing lesions per T1-weighted magnetic resonance imaging (MRI) scan, the annualized rate of new or enlarging lesions on T2-weighted MRI, serum neurofilament light chain levels at month 3, and change in brain volume. RESULTS: Overall, 946 patients were assigned to receive ofatumumab and 936 to receive teriflunomide; the median follow-up was 1.6 years. The annualized relapse rates in the ofatumumab and teriflunomide groups were 0.11 and 0.22, respectively, in trial 1 (difference, -0.11; 95% confidence interval [CI], -0.16 to -0.06; P<0.001) and 0.10 and 0.25 in trial 2 (difference, -0.15; 95% CI, -0.20 to -0.09; P<0.001). In the pooled trials, the percentage of patients with disability worsening confirmed at 3 months was 10.9% with ofatumumab and 15.0% with teriflunomide (hazard ratio, 0.66; P = 0.002); the percentage with disability worsening confirmed at 6 months was 8.1% and 12.0%, respectively (hazard ratio, 0.68; P = 0.01); and the percentage with disability improvement confirmed at 6 months was 11.0% and 8.1% (hazard ratio, 1.35; P = 0.09). The number of gadolinium-enhancing lesions per T1-weighted MRI scan, the annualized rate of lesions on T2-weighted MRI, and serum neurofilament light chain levels, but not the change in brain volume, were in the same direction as the primary end point. Injection-related reactions occurred in 20.2% in the ofatumumab group and in 15.0% in the teriflunomide group (placebo injections). Serious infections occurred in 2.5% and 1.8% of the patients in the respective groups. CONCLUSIONS: Among patients with multiple sclerosis, ofatumumab was associated with lower annualized relapse rates than teriflunomide. (Funded by Novartis; ASCLEPIOS I and II ClinicalTrials.gov numbers, NCT02792218 and NCT02792231.)