Lipoproteins Are Responsible for the Pro-Inflammatory Property of Staphylococcus aureus Extracellular Vesicles

Staphylococcal aureus (S. aureus), a Gram-positive bacteria, is known to cause various infections. Extracellular vesicles (EVs) are a heterogeneous array of membranous structures secreted by cells from all three domains of life, i.e., eukaryotes, bacteria, and archaea. Bacterial EVs are implied to be involved in both bacteria–bacteria and bacteria–host interactions during infections. It is still unclear how S. aureus EVs interact with host cells and induce inflammatory responses. In this study, EVs were isolated from S. aureus and mutant strains deficient in either prelipoprotein lipidation (Δlgt) or major surface proteins (ΔsrtAB). Their immunostimulatory capacities were assessed both in vitro and in vivo. We found that S. aureus EVs induced pro-inflammatory responses both in vitro and in vivo. However, this activity was dependent on lipidated lipoproteins (Lpp), since EVs isolated from the Δlgt showed no stimulation. On the other hand, EVs isolated from the ΔsrtAB mutant showed full immune stimulation, indicating the cell wall anchoring of surface proteins did not play a role in immune stimulation. The immune stimulation of S. aureus EVs was mediated mainly by monocytes/macrophages and was TLR2 dependent. In this study, we demonstrated that not only free Lpp but also EV-imbedded Lpp had high pro-inflammatory activity.     

Controlling protein translocation through nanopores with bio-inspired fluid walls

Synthetic nanopores have been used to study individual biomolecules in high throughput, but their performance as sensors does not match that of biological ion channels. Challenges include control of nanopore diameters and surface chemistry, modification of the translocation times of single-molecule analytes through nanopores, and prevention of non-specific interactions with pore walls. Here, inspired by the olfactory sensilla of insect antennae, we show that coating nanopores with a fluid lipid bilayer tailors their surface chemistry and allows fine-tuning and dynamic variation of pore diameters in subnanometre increments. Incorporation of mobile ligands in the lipid bilayer conferred specificity and slowed the translocation of targeted proteins sufficiently to time-resolve translocation events of individual proteins. Lipid coatings also prevented pores from clogging, eliminated non-specific binding and enabled the translocation of amyloid-beta (Aβ) oligomers and fibrils. Through combined analysis of their translocation time, volume, charge, shape and ligand affinity, different proteins were identified.     

H ∞ Control of T-S Fuzzy Singularly Perturbed Systems Using Multiple Lyapunov Functions

In this paper, H _∞ controller synthesis of T-S fuzzy singularly perturbed systems based on fuzzy and non-fuzzy multiple Lyapunov functions is discussed. By assuming some lower bounds for the grades of fuzzy membership functions and using the elimination lemma, the design conditions are presented in the form of linear matrix inequalities (LMIs). Considering ε as the singular perturbation parameter, it is shown that the ε-dependent controller in the absence of disturbances, results in an asymptotically stable closed-loop system, and in the presence of disturbances, satisfies the H _∞-norm condition for all ε∈(0,ε ^?]. The resulting LMIs are feasible for larger values of ε ^? compared to those of the previous methods. Moreover, for the case that the value of ε is not available for feedback, Finsler’s lemma is used to separate the controller gains and the ε-dependent Lyapunov matrix, and to achieve an ε-independent control. An example is presented to illustrate the validity of the design techniques.     

Feedback linearization of discrete-time nonlinear uncertain plants via first-principles-based serial neuro-gray-box models

In this paper, discrete-time control schemes based on feedback linearization of serial gray-box models are considered for partially known nonlinear processes. These techniques combine the benefits of feedback linearization, neural networks, and serial gray-box modeling, which result in larger dynamic operating ranges, better extrapolation properties, and fewer data acquisition efforts in comparison with the corresponding black-box-based schemes. First-principles-based serial gray-box models are classified into invertible and non-invertible structures for training purposes, and an improved approximate feedback linearization scheme based on Taylor series terms of a non-affine gray-box model is proposed. Moreover, an affine gray-box model is developed for applying the exact feedback linearization scheme. Simulation results on a fermentation process show that the proposed methods yield significant improvement in modeling and control performance in comparison with that of the black-box feedback linearization schemes.     

Multi-user Opportunistic Spectrum Access with Channel Impairments

In this paper, we study the impact of sensing error and channel fading on the decision process of a multiple secondary user network in a primary network whose channel occupancy states are modelled as a Bernoulli process. We present a randomized access strategy to maximize total secondary network throughput. The proposed method guarantees that the probability of collision between primary and secondary users in each channel is less than the predefined value of P_c = ξ. To find the optimal access strategy, we formulate secondary network throughput as an optimization problem. Then, using the KKT method to find the solution, we break the original problem into multiple sub-problems. Then, we employ an iterative algorithm and a sifting technique to reduce the number of sub-problems and find the final solution. The solution contains both the SUs access strategies and their detector operating points. In other words, we present a solution for the cross layer design in cognitive radio networks. At the end, we compare our results with two other heuristic strategies (1) equi-probable strategy and (2) weighted strategy and show that the proposed method outperforms them in terms of total throughput.     

Molecular Mechanisms of Treatment Resistance in Glioblastoma

Glioblastoma is the most common malignant primary brain tumor in adults and is almost invariably fatal. Despite our growing understanding of the various mechanisms underlying treatment failure, the standard-of-care therapy has not changed over the last two decades, signifying a great unmet need. The challenges of treating glioblastoma are many and include inadequate drug or agent delivery across the blood–brain barrier, abundant intra- and intertumoral heterogeneity, redundant signaling pathways, and an immunosuppressive microenvironment. Here, we review the innate and adaptive molecular mechanisms underlying glioblastoma’s treatment resistance, emphasizing the intrinsic challenges therapeutic interventions must overcome—namely, the blood–brain barrier, tumoral heterogeneity, and microenvironment—and the mechanisms of resistance to conventional treatments, targeted therapy, and immunotherapy.     

Impact of monitoring technology in assisted living: outcome pilot.

This paper describes a study designed to assess the acceptance and some psychosocial impacts of monitoring technology in assisted living. Monitoring systems were installed in 22 assisted living units to track the activities of daily living (ADLs) and key alert conditions of residents (15 of whom were nonmemory care residents). Activity reports and alert notifications were sent to professional caregivers who provided care to residents participating in the study. Diagnostic use of the monitoring data was assessed. Nonmemory care residents were surveyed and assessed using the Satisfaction With Life Scale (SWLS) instrument. Pre- and post-installation SWLS scores were compared. Older adult participants accepted monitoring. The results suggest that monitoring technologies could provide care coordination tools that are accepted by residents and may have a positive impact on their quality of life.     

Preparation and characterization of carvedilol-loaded poly(d,l) lactide nanoparticles/microparticles as a sustained-release system

Carvedilol poly(d,l)-lactide nanoparticles/microparticles were prepared. The size and morphology of the developed particles were optimized to study the carvedilol release profile by studying the effect of organic solvents and polymer amount through atomic force microscopy analysis. Spherical particles were obtained with a minimum size of 125?nm in the case of acetone and a maximum size of 970?nm in the case of dichloromethane affording microparticles formation. The interaction was confirmed by differential scanning calorimeter and Fourier transform infrared. The in vitro release profile of the multicompartment system (pure carvedilol, loaded nanoparticles and microparticles) has shown a sustained release with Korsmeyer–Peppas with T lag model.