Protection against Staphylococcus aureus colonization and infection by B-and T-cell-mediated mechanisms

© 2018 Zhang et al. Staphylococcus aureus is a major cause of morbidity and mortality worldwide. S. aureus colonizes 20 to 80% of humans at any one time and causes a variety of illnesses. Strains that are resistant to common antibiotics further complicate management. S. aureus vaccine development has been unsuccessful so far, largely due to the incomplete understanding of the mechanisms of protection against this pathogen. Here, we studied the role of different aspects of adaptive immunity induced by an S. aureus vaccine in protection against S. aureus bacteremia, dermonecrosis, skin abscess, and gastrointestinal (GI) colonization. We show that, depending on the challenge model, the contributions of vaccine-induced S. aureus-specific antibody and Th1 and Th17 responses to protection are different: antibodies play a major role in reducing mortality during S. aureus bacteremia, whereas Th1 or Th17 responses are essential for prevention of S. aureus skin abscesses and the clearance of bacteria from the GI tract. Both antibody-and T-cell-mediated mechanisms contribute to prevention of S. aureus dermonecrosis. Engagement of all three immune pathways results in the most robust protection under each pathological condition. Therefore, our results suggest that eliciting multipronged humoral and cellular responses to S. aureus antigens may be critical to achieve effective and comprehensive immune defense against this pathogen. IMPORTANCE S. aureus is a leading cause of healthcare-and community-associated bacterial infections. S. aureus causes various illnesses, including bacteremia, meningitis, endocarditis, pneumonia, osteomyelitis, sepsis, and skin and soft tissue infections. S. aureus colonizes between 20 and 80% of humans; carriers are at increased risk for infection and transmission to others. The spread of multidrug-resistant strains limits antibiotic treatment options. Vaccine development against S. aureus has been unsuccessful to date, likely due to an inadequate understanding about the mechanisms of immune defense against this pathogen. The significance of our work is in illustrating the necessity of generating multipronged B-cell, Th1-, and Th17-mediated responses to S. aureus antigens in conferring enhanced and broad protection against S. aureus invasive infection, skin and soft tissue infection, and mucosal colonization. Our work thus, provides important insights for future vaccine development against this pathogen

Elastic differential evolution for automatic data clustering

In many practical applications, it is crucial to perform automatic data clustering without knowing the number of clusters in advance. The evolutionary computation paradigm is good at dealing with this task, but the existing algorithms encounter several deficiencies, such as the encoding redundancy and the cross-dimension learning error. In this article, we propose a novel elastic differential evolution algorithm to solve automatic data clustering. Unlike traditional methods, the proposed algorithm considers each clustering layout as a whole and adapts the cluster number and cluster centroids inherently through the variable-length encoding and the evolution operators. The encoding scheme contains no redundancy. To enable the individuals of different lengths to exchange information properly, we develop a subspace crossover and a two-phase mutation operator. The operators employ the basic method of differential evolution and, in addition, they consider the spatial information of cluster layouts to generate offspring solutions. Particularly, each dimension of the parameter vector interacts with its correlated dimensions, which not only adapts the cluster number but also avoids the cross-dimension learning error. The experimental results show that our algorithm outperforms the state-of-the-art algorithms that it is able to identify the correct number of clusters and obtain a good cluster validation value

Valley-Polarized Interlayer Conduction of Anisotropic Dirac Fermions in SrMnBi2

We report the valley-selective interlayer conduction of SrMnBi2 under in-plane magnetic fields. The c-axis resistivity of SrMnBi2 shows clear angular magnetoresistance oscillations indicating coherent interlayer conduction. Strong fourfold variation of the coherent peak in the c-axis resistivity reveals that the contribution of each Dirac valley is significantly modulated by the in-plane field orientation. This originates from anisotropic Dirac Fermi surfaces with strong disparity in the momentum-dependent interlayer coupling. Furthermore, we found a signature of broken valley symmetry at high magnetic fields. These findings demonstrate that a quasi-two-dimensional anisotropic Dirac system can host a valley-polarized interlayer current through magnetic valley control. © 2014 American Physical Society.open1

An agile vehicle-based dynamic user equilibrium scheme for urban traffic signal control

Traffic Signal Control (TSC) is a fundamental task in modern intelligent transport systems. TSC is often formulated as a bi-level optimization problem, comprised by the signal timing at the upper level and the Dynamic User Equilibrium (DUE) traffic assignment at the lower level. Since DUE is non-convex, existing methods either formulate approximation models or adopt traffic simulators. However, approximation models may oversimplify the practical situations, while traffic simulators are usually time-consuming. This paper formulates a vehicle-based DUE (vDUE) model and proposes an agile method that can simultaneously maintain the computational simplicity and the traffic dynamics for the traffic assignment. Further, an agile TSC system is built by combining the vDUE at the lower level for the traffic assignment with an adaptive differential evolution algorithm at the upper level for the signal timing optimization. To enhance the effectiveness of optimization, the TSC problem formulation is also improved to make it better characterize the practical requirements. In the experiments undertaken, comparisons of different TSC methods are carried out on both real-world and synthetic transportation networks. The experimental results validate the effectiveness of the proposed agile TSC system in various traffic situations

Maximizing lifetime of range-adjustable wireless sensor networks: a neighborhood-based estimation of distribution algorithm

Sensor activity scheduling is critical for prolonging the lifetime of wireless sensor networks (WSNs). However, most existing methods assume sensors to have one fixed sensing range. Prevalence of sensors with adjustable sensing ranges posts two new challenges to the topic: 1) expanded search space, due to the rise in the number of possible activation modes and 2) more complex energy allocation, as the sensors differ in the energy consumption rate when using different sensing ranges. These two challenges make it hard to directly solve the lifetime maximization problem of WSNs with range-adjustable sensors (LM-RASs). This article proposes a neighborhood-based estimation of distribution algorithm (NEDA) to address it in a recursive manner. In NEDA, each individual represents a coverage scheme in which the sensors are selectively activated to monitor all the targets. A linear programming (LP) model is built to assign activation time to the schemes in the population so that their sum, the network lifetime, can be maximized conditioned on the current population. Using the activation time derived from LP as individual fitness, the NEDA is driven to seek coverage schemes promising for prolonging the network lifetime. The network lifetime is thus optimized by repeating the steps of the coverage scheme evolution and LP model solving. To encourage the search for diverse coverage schemes, a neighborhood sampling strategy is introduced. Besides, a heuristic repair strategy is designed to fine-tune the existing schemes for further improving the search efficiency. Experimental results on WSNs of different scales show that NEDA outperforms state-of-the-art approaches. It is also expected that NEDA can serve as a potential framework for solving other flexible LP problems that share the same structure with LM-RAS

A Dynamic Stochastic Model for DNA Replication Initiation in Early Embryos

Background: Eukaryotic cells seem unable to monitor replication completion during normal S phase, yet must ensure a reliable replication completion time. This is an acute problem in early Xenopus embryos since DNA replication origins are located and activated stochastically, leading to the random completion problem. DNA combing, kinetic modelling and other studies using Xenopus egg extracts have suggested that potential origins are much more abundant than actual initiation events and that the time-dependent rate of initiation, I(t), markedly increases through S phase to ensure the rapid completion of unreplicated gaps and a narrow distribution of completion times. However, the molecular mechanism that underlies this increase has remained obscure.Methodology/Principal Findings: Using both previous and novel DNA combing data we have confirmed that I(t) increases through S phase but have also established that it progressively decreases before the end of S phase. To explore plausible biochemical scenarios that might explain these features, we have performed comparisons between numerical simulations and DNA combing data. Several simple models were tested: i) recycling of a limiting replication fork component from completed replicons; ii) time-dependent increase in origin efficiency; iii) time-dependent increase in availability of an initially limiting factor, e. g. by nuclear import. None of these potential mechanisms could on its own account for the data. We propose a model that combines time-dependent changes in availability of a replication factor and a fork-density dependent affinity of this factor for potential origins. This novel model quantitatively and robustly accounted for the observed changes in initiation rate and fork density.Conclusions/Significance: This work provides a refined temporal profile of replication initiation rates and a robust, dynamic model that quantitatively explains replication origin usage during early embryonic S phase. These results have significant implications for the organisation of replication origins in higher eukaryotes

An Antireflective Nanostructure Array Fabricated by Nanosilver Colloidal Lithography on a Silicon Substrate

An alternative method is presented for fabricating an antireflective nanostructure array using nanosilver colloidal lithography. Spin coating was used to produce the multilayered silver nanoparticles, which grew by self-assembly and were transformed into randomly distributed nanosilver islands through the thermodynamic action of dewetting and Oswald ripening. The average size and coverage rate of the islands increased with concentration in the range of 50–90 nm and 40–65%, respectively. The nanosilver islands were critically affected by concentration and spin speed. The effects of these two parameters were investigated, after etching and wet removal of nanosilver residues. The reflection nearly disappeared in the ultraviolet wavelength range and was 17% of the reflection of a bare silicon wafer in the visible range

Allogeneic hematopoietic stem cell transplantation in China: where we are and where to go

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is an effective and sometimes the only curative therapy for patients with certain hematological diseases. Allo-HSCT has been practiced in China for approximately 30 years, and great improvements have been made within the past decade, particularly in fields such as the haploidentical HSCT system, strategies to overcome relapse and GVHD, and modified HSCT for elderly patients. This review will describe the current situation and provide a prospective of these unique aspects of Allo-HSCT in China