Although selenium nanoparticles (SeNPs) have gained attention in the scientific community mostly through investigation of their anticancer activity, a great potential of this nanomaterial was recognized recently regarding its antimicrobial activity. The particle form, size, and surface chemistry have been recognized as crucial parameters determining the interaction of nanomaterials with biological entities. Furthermore, considering a narrow boundary between beneficial and toxic effects for selenium per se, it is clear that investigations of biomedical applications of SeNPs are very demanding and must be done with great precautions. The goal of this work is to evaluate the effects of SeNPs surface chemistry and structure on antimicrobial activity against several common bacterial strains, including Staphylococcus aureus (ATCC 6538), Enterococcus faecalis (ATCC 29212), Bacillus subtilis (ATCC 6633), and Kocuria rhizophila (ATCC 9341), as well as Escherichia coli (ATCC 8739), Salmonella Abony (NCTC 6017), Klebsiella pneumoniae (NCIMB 9111) and Pseudomonas aeruginosa (ATCC 9027), and the standard yeast strain Candida albicans (ATCC 10231). Three types of SeNPs were synthesized by chemical reduction approach using different stabilizers and reducing agents: (i) bovine serum albumin (BSA) + ascorbic acid, (ii) chitosan + ascorbic acid, and (iii) with glucose. A thorough physicochemical characterization of the obtained SeNPs was performed to determine the effects of varying synthesis parameters on their morphology, size, structure, and surface chemistry. All SeNPs were amorphous, with spherical morphology and size in the range 70–300 nm. However, the SeNPs obtained under different synthesis conditions, i.e. by using different stabilizers as well as reducing agents, exhibited different antimicrobial activity as well as cytotoxicity which are crucial for their applications. In this paper, the antimicrobial screening of the selected systems is presented, which was determined by the broth microdilution method, and inhibitory influence on the production of monomicrobial and dual-species biofilm was evaluated. The potential mechanism of action of different systems is proposed. Additionally, the cytotoxicity of SeNPs was examined on the MRC-5 cell line, in the same concentration interval as for antimicrobial testing. It was shown that formulation SeNPs-BSA expressed a significantly lower cytotoxic effect than the other two formulations.

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Antimicrobial resistance (AMR) has emerged as a major threat to public health globally. Accurate and rapid detection of resistance to antimicrobial drugs, and subsequent appropriate antimicrobial treatment, combined with antimicrobial stewardship, are essential for controlling the emergence and spread of AMR. This article reviews common antimicrobial susceptibility testing (AST) methods and relevant issues concerning the advantages and disadvantages of each method. Although accurate, classic technologies used in clinical microbiology to profile antimicrobial susceptibility are time-consuming and relatively expensive. As a result, physicians often prescribe empirical antimicrobial therapies and broad-spectrum antibiotics. Although recently developed AST systems have shown advantages over traditional methods in terms of testing speed and the potential for providing a deeper insight into resistance mechanisms, extensive validation is required to translate these methodologies to clinical practice. With a continuous increase in antimicrobial resistance, additional efforts are needed to develop innovative, rapid, accurate, and portable diagnostic tools for AST. The wide implementation of novel devices would enable the identification of the optimal treatment approaches and the surveillance of antibiotic resistance in health, agriculture, and the environment, allowing monitoring and better tackling the emergence of AMR.

Replacement policy, one of the key factors determining the effectiveness of a cache, becomes even more important with latest technological trends toward highly associative caches. The state-of-the-art processors employ various policies such as Random, Least Recently Used (LRU), Round-Robin, and PLRU (Pseudo LRU), indicating that there is no common wisdom about the best one. Optimal yet unattainable policy would replace cache memory block whose next reference is the farthest away in the future, among all memory blocks present in the set.In our quest for replacement policy as close to optimal as possible, we thoroughly explored the design space of existing replacement mechanisms using SimpleScalar toolset and SPEC CPU2000 benchmark suite, across wide range of cache sizes and organizations. In order to better understand the behavior of different policies, we introduced new measures, such as cumulative distribution of cache hits in the LRU stack. We also dynamically monitored the number of cache misses, per each 100000 instructions.Our results show that the PLRU techniques can approximate and even outperform LRU with much lower complexity, for a wide range of cache organizations. However, a relatively large gap between LRU and optimal replacement policy, of up to 50%, indicates that new research aimed to close the gap is necessary. The cumulative distribution of cache hits in the LRU stack indicates a very good potential for way prediction using LRU information, since the percentage of hits to the bottom of the LRU stack is relatively high.

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