Granulocyte colony-stimulating factor worsens the outcome of experimental Klebsiella pneumoniae pneumonia through direct interaction with the bacteria

Besides its well-established effects on granulocytopoiesis, granulocyte colony-stimulating factor (G-CSF) has been shown to have direct effects on the recruitment and bactericidal ability of neutrophils, resulting in improved survival of experimentally infected animals. We studied the effect of G-CSF on the course of experimental pneumonia induced by Klebsiella pneumoniae, an important gram-negative bacillary pulmonary pathogen. Using a highly reproducible murine model, we here show the paradoxical finding that mortality from infection was significantly increased when animals received G-CSF before induction of pneumonia. Administration of G-CSF promoted replication of bacteria in the liver and spleen, thus indicating an impairment rather than an enhancement of antibacterial mechanisms. By contrast, a monoclonal antibody against Klebsiella K2 capsule significantly reduced bacterial multiplication in the lung, liver, and spleen, and abrogated the increased mortality caused by G-CSF. In vitro studies showed a direct effect of G-CSF on K pneumoniae resulting in increased capsular polysaccharide (CPS) production. When bacteria were coincubated with therapeutically achievable concentrations of G-CSF, phagocytic uptake and killing by neutrophils was impaired. Western blot analysis showed three binding sites of G-CSF to K pneumoniae. Binding of 125I-G-CSF to K pneumoniae was displaced by an excess of unlabeled G-CSF, whereas an unrelated cytokine, interleukin-1alpha, did not compete with G-CSF binding to the bacteria. Thus, in this model, the direct effect of G-CSF on a bacterial virulence factor, CPS production, outweighed any beneficial effect of G-CSF on recruitment and stimulation of leukocytes.     

Hull-form stochastic optimization via computational-cost reduction methods

In this paper, analytical functions for the estimation of the temperature-dependent behaviors of poorly and highly dispersed graphene oxide reinforced nanocomposite (GORNC) materials are studied in the framework of a machine learning-based approach. The validity of the presented models is shown comparing the results achieved from this modeling with those reported in the open literature. Also, the application of the obtained functions in solving the thermal buckling problem of beams constructed from such nanocomposites is demonstrated based on an energy-based method incorporated with a shear deformable beam hypothesis. The verification of the results indicates that the presented mechanical model can approximate the buckling behaviors of nanocomposite beams with remarkable precision. It can be realized from the results that the temperature plays an indispensable role in the determination of the buckling load which can be endured by the nanocomposite structure.

     

Valuation of online social networks taking into account users’ interconnectedness

Online social networks have been gaining increasing economic importance in light of the rising number of their users. Numerous recent acquisitions priced at enormous amounts have illustrated this development and revealed the need for adequate business valuation models. The value of an online social network is largely determined by the value of its users, the relationships between these users, and the resulting network effects. Therefore, the interconnectedness of a user within the network has to be considered explicitly to get a reasonable estimate for its economic value. Established standard business valuation models, however, do not account for these aspects sufficiently. Thus, we propose an economic model for the valuation of online social networks, which takes into account the users’ interconnectedness within the network. Furthermore, we analyze different centrality measures, which can be used to quantify users’ interconnectedness in online social networks and propose a measure which is based on the PageRank-algorithm. Finally, the practical application of the model is illustrated by an example of the European online social network XING.com.     

Sensitivity analysis for simulation-based decision making: Application to a hospital emergency service design

An increasing concern of decision makers when dealing with system design is preparation for a wide range of potentially uncertain operating conditions. This paper provides a novel multiobjective approach for simulation-driven decision making that accounts for not only the conventional average system performance indices, but also (i) upper-tail, or extreme, values of these indices, and (ii) measures of their sensitivity to uncertainty in model parameters. The proposed approach is applied to a hospital emergency department service design case study wherein different design alternatives are compared using total time-in-system performance metric under multiple uncertain operating conditions.     

Activation of hydrogen storage materials in the Li–Mg–N–H system: Effect on storage properties

We investigate the thermodynamics, kinetics, and capacity of the hydrogen storage reaction: Li₂Mg(NH)₂ + 2H₂  Mg(NH₂)₂ + 2LiH. Starting with LiNH₂ and MgH₂, two distinct procedures have been previously proposed for activating samples to induce the reversible storage reaction. We clarify here the impact of these two activation procedures on the resulting capacity for the Li–Mg–N–H reaction. Additionally, we measure the temperature-dependent kinetic absorption data for this hydrogen storage system. Finally, our experiments confirm the previously reported formation enthalpy (ΔH), hydrogen capacity, and pressure–composition–isotherm (PCI) data, and suggest that this system represents a kinetically (but not thermodynamically) limited system for vehicular on-board storage applications.     

Structural Investigation and Molecular Modeling Studies of Strobilurin-Based Fungicides Active against the Rice Blast Pathogen Pyricularia oryzae

The increasing emergence of fungicide-resistant pathogens requires urgent solutions for crop disease management. Here, we describe a structural investigation of new fungicides obtained by combining strobilurin and succinate dehydrogenase inhibitor pharmacophores. We identified compounds endowed with very good activity against wild-type Pyricularia oryzae, combined in some cases with promising activity against strobilurin-resistant strains. The first three-dimensional model of P. oryzae cytochrome bc1 complex containing azoxystrobin as a ligand was developed. The model was validated with a set of commercially available strobilurins, and it well explains both the resistance mechanism to strobilurins mediated by the mutation G143A and the activity of metyltetraprole against strobilurin-resistant strains. The obtained results shed light on the key recognition determinants of strobilurin-like derivatives in the cytochrome bc1 active site and will guide the further rational design of new fungicides able to overcome resistance caused by G143A mutation in the rice blast pathogen.     

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.     

A low-cost real time virtual system for postural stability assessment at home

Background and objective

The degeneration of the balance control system in the elderly and in many pathologies requires measuring the equilibrium conditions very often. In clinical practice, equilibrium control is commonly evaluated by using a force platform (stabilometric platform) in a clinical environment.In this paper, we demonstrate how a simple movement analysis system, based on a 3D video camera and a 3D real time model reconstruction of the human body, can be used to collect information usually recorded by a physical stabilometric platform.

Methods

The algorithm used to reconstruct the human body model as a set of spheres is described and discussed. Moreover, experimental measurements and comparisons with data collected by a physical stabilometric platform are also reported. The measurements were collected on a set of 6 healthy subjects to whom a change in equilibrium condition was stimulated by performing an equilibrium task.

Results

The experimental results showed that more than 95% of data collected by the proposed method were not significantly different from those collected by the classic platform, thus confirming the usefulness of the proposed system.

Conclusions

The proposed virtual balance assessment system can be implemented at low cost (about 500$) and, for this reason, can be considered a home use medical device. On the contrary, astabilometric platform has a cost of about 10,000$ and requires periodical calibration. The proposed system does not require periodical calibration, as is necessary for stabilometric force platforms, and it is easy to use. In future, the proposed system with little integration can be used, besides being an emulator of a stabilometric platform, also to recognize and track, in real time, head, legs, arms and trunk, that is to collect information actually obtained by sophisticated optoelectronic systems.     

Good Enough is Good Enough: Overcoming Disaster Response Organizations’ Slow Social Media Data Adoption

Organizations that respond to disasters hold unreasonable standards for data arising from technology-enabled citizen contributions. This has strong negative potential for the ability of these responding organizations to incorporate these data into appropriate decision points. We argue that the landscape of the use of social media data in crisis response is varied, with pockets of use and acceptance among organizations. In this paper we present findings from interviews conducted with representatives from large international disaster response organizations concerning their use of social media data in crisis response. We found that emergency responders already operate with less than reliable, or “good enough,” information in offline practice, and that social media data are useful to responders, but only in specific crisis situations. Also, responders do use social media, but only within their known community and extended network. This shows that trust first begins with people and not data. Lastly, we demonstrate the barriers used by responding organizations have gone beyond discussions of trustworthiness and data quality to that of more operational issues.     

A local landscape mapping method for protein structure prediction in the HP model

The hydrophobic-polar (HP) model has been widely studied in the field of protein structure prediction both for theoretical purposes and as a benchmark for new optimization strategies. In this work we present results of the recently proposed Hybrid Monte Carlo Ant Colony Optimization heuristic in the HP model using a fragment assembly-like strategy. Moreover we extend that method introducing a general framework for optimization in the HP model, called Local Landscape Mapping, and we test it using the pull moves set to generate solutions. We describe the heuristic and compare results obtained on well known HP instances in the 3-dimensional cubic lattice to those obtained with standard Ant Colony optimization and Simulated Annealing. Fragment assembly-like tests were performed using a modified objective function to prevent the creation of overlapping walks. Results show that our method performs better than the other heuristics in all benchmark instances when the fragment assembly-like strategy is used while in the case of pull moves-based neighborhood its performance is comparable to that of simulated annealing.