Biology of moderately halophilic aerobic bacteria

The moderately halophilic heterotrophic aerobic bacteria form a diverse group of microorganisms. The property of halophilism is widespread within the bacterial domain. Bacterial halophiles are abundant in environments such as salt lakes, saline soils, and salted food products. Most species keep their intracellular ionic concentrations at low levels while synthesizing or accumulating organic solutes to provide osmotic equilibrium of the cytoplasm with the surrounding medium. Complex mechanisms of adjustment of the intracellular environments and the properties of the cytoplasmic membrane enable rapid adaptation to changes in the salt concentration of the environment. Approaches to the study of genetic processes have recently been developed for several moderate halophiles, opening the way toward an understanding of haloadaptation at the molecular level. The new information obtained is also expected to contribute to the development of novel biotechnological uses for these organisms

In vitro and in silico assessment of the developability of a designed monoclonal antibody library.

Despite major advances in antibody discovery technologies, the successful development of monoclonal antibodies (mAbs) into effective therapeutic and diagnostic agents can often be impeded by developability liabilities, such as poor expression, low solubility, high viscosity and aggregation. Therefore, strategies to predict at the early phases of antibody development the risk of late-stage failure of antibody candidates are highly valuable. In this work, we employ the in silico solubility predictor CamSol to design a library of 17 variants of a humanized mAb predicted to span a broad range of solubility values, and we examine their developability potential with a battery of commonly used in vitro and in silico assays. Our results demonstrate the ability of CamSol to rationally enhance mAb developability, and provide a quantitative comparison of in vitro developability measurements with each other and with more resource-intensive solubility measurements, as well as with in silico predictors that offer a potentially faster and cheaper alternative. We observed a strong correlation between predicted and experimentally determined solubility values, as well as with measurements obtained using a panel of in vitro developability assays that probe non-specific interactions. These results indicate that computational methods have the potential to reduce or eliminate the need of carrying out laborious in vitro quality controls for large numbers of lead candidates. Overall, our study provides support to the emerging view that the implementation of in silico tools in antibody discovery campaigns can ensure rapid and early selection of antibodies with optimal developability potential

The incidence of colon cancer among patients diagnosed with left colonic or sigmoid acute diverticulitis is higher than in the general population

Considering the low incidence of colon cancer after an initial episode of colonic diverticulitis in some categories of patients, some authors suggested to exempt them from colonoscopy. However, this incidence has never been compared to that of a reference population, and predictors of cancer are still poorly investigated. We aimed to determine the 1-year incidence of colon cancer at the site of diverticulitis in patients diagnosed with left colonic or sigmoid acute diverticulitis, to compare this incidence to a reference population to state whether endoscopy is required or not, and to identify predicting factors of cancer to better target subpopulations needing that examination

AI4SAFE-IoT: an AI-powered secure architecture for edge layer of Internet of things

© 2020, Springer-Verlag London Ltd., part of Springer Nature. With the increasing use of the Internet of things (IoT) in diverse domains, security concerns and IoT threats are constantly rising. The computational and memory limitations of IoT devices have resulted in emerging vulnerabilities in most IoT-run environments. Due to the low processing ability, IoT devices are often not capable of running complex defensive mechanisms. Lack of an architecture for a safer IoT environment is referred to as the most important barrier in developing a secure IoT system. In this paper, we propose a secure architecture for IoT edge layer infrastructure, called AI4SAFE-IoT. This architecture is built upon AI-powered security modules at the edge layer for protecting IoT infrastructure. Cyber threat attribution, intelligent web application firewall, cyber threat hunting, and cyber threat intelligence are the main modules proposed in our architecture. The proposed modules detect, attribute, and further identify the stage of an attack life cycle based on the Cyber Kill Chain model. In the proposed architecture, we define each security module and show its functionality against different threats in real-world applications. Moreover, due to the integration of AI security modules in a different layer of AI4SAFE-IoT, each threat in the edge layer will be handled by its corresponding security module delivered by a service. We compared the proposed architecture with the existing models and discussed our architecture independence of the underlying IoT layer and its comparatively low overhead according to delivering security as service for the edge layer of IoT architecture instead of embed implementation. Overall, we evaluated our proposed architecture based on the IoT service management score. The proposed architecture obtained 84.7 out of 100 which is the highest score among peer IoT edge layer security architectures

The versatility and adaptation of bacteria from the genus <em>Stenotrophomonas</em>

The genus Stenotrophomonas comprises at least eight species. These bacteria are found throughout the environment, particularly in close association with plants. Strains of the most predominant species, Stenotrophomonas maltophilia, have an extraordinary range of activities that include beneficial effects for plant growth and health, the breakdown of natural and man-made pollutants that are central to bioremediation and phytoremediation strategies and the production of biomolecules of economic value, as well as detrimental effects, such as multidrug resistance, in human pathogenic strains. Here, we discuss the versatility of the bacteria in the genus Stenotrophomonas and the insight that comparative genomic analysis of clinical and endophytic isolates of S. maltophilia has brought to our understanding of the adaptation of this genus to various niches