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Industrial Prospects of Bacterial Microcompartment Technologies
Published in Deepak Kumar Verma, Ami R. Patel, Sudhanshu Billoria, Geetanjali Kaushik, Maninder Kaur, Microbial Biotechnology in Food Processing and Health, 2023
Shagun Rastogi, Chiranjit Chowdhury
Bacterial MCPs are complex protein containers that are widely distributed across bacterial phyla. These protein containers encase serially acting metabolic enzymes and optimize metabolic pathways (Figure 10.1) (Bobik, 2006; Kerfeld et al., 2010; Rae et al., 2013; Chowdhury et al., 2014). The outer shells of the MCP polyhedra are comprised of hexagonal BMC domain proteins that form facets and BMV pentamers that create the vertices (Kerfeld et al., 2010; Rae et al., 2013; Chowdhury et al., 2014; Lehman et al., 2017). MCPs show morphological resemblance to viral capsids; although, their size and shape vary among bacterial species. Typical MCPs are 80–200 nm across the diameter and are visible under electron microscope (Bobik et al., 1999; Chowdhury et al., 2014) (Figure 10.2). Recently, new methods of visualization of polyhedral shell through the crystal structure, atomic force microscopy and fluorescent labeling have provided new insights into subcellular localization, assembly, and structure of MCPs (Savage et al., 2010; Sutter et al., 2016, 2017; Kerfeld et al., 2018). MCPs polyhedral bodies are nearly icosahedral in shape with 20 flat triangular facets and 12 pentagonal vertices (Schmid et al., 2006; Iancu et al., 2007; Yeates et al., 2013). Although, carboxysomal MCPs appears to be regular icosahedron, the other type of MCPs is less regular, often conform structural polymorphisms (Figure 10.2).
Applications Of Micellear Phase Of Pluronics And Tetronics As Nanoreactors In The Synthesis Of Nobel Metal Nanoparticles
Published in Alexander V. Vakhrushev, Suresh C. Ameta, Heru Susanto, A. K. Haghi, Advances in Nanotechnology and the Environmental Sciences, 2019
Rajpreet Kaur, Navdeep Kaur, Divya Mandial, Lavanya Tandon, Poonam Khullar
F88, P85, P104, P105 pluronics has also been used to prepare icosahedral Au NPs. But a regular icosahedron shapes are formed only when a high molecular weight copolymer i.e. P85 is used. It is due to the fact that larger molecular weight copolymer is more flexible and it can adsorb on the surface of gold cluster more efficiently which is required for the formation of regular icosahedral Au NPs. Also the size of these NPs can be controlled in the range of 100 nm to 1 micrometer by simply varying the experimental conditions such as temperature, concentration, etc.
Aided- and self-assembly of liquid crystalline nanoparticles in bulk and in solution: computer simulation studies
Published in Liquid Crystals, 2023
A. Slyusarchuk, D. Yaremchuk, J. Lintuvuori, M. R. Wilson, M. Grenzer, S. Sokołowski, J. Ilnytskyi
The ROD pattern has patching symmetry with two patches located at the polar regions of the core unit, each formed of ligands (left most panel in Figure 13). The evidence for the experimental realisation of such a pattern can be found in Refs [62,69]. The TRI pattern has been reported in [69]. Another possibility for the experimental realisation of both TRI and QTR patterns, is provided by the discotic core of conjugated aromatic rings, as shown in Refs [64,66]. Both TRI and QTR models have patching symmetry, and their natural continuation is the EQU model with twelve single ligand patches arranged equidistantly on the equator of the core unit. This patching pattern is a part of the decorated nanoparticles reported in Ref [62] and may possibly be realised using discotic core units shown in Figure 3 of Ref [66]. Finally, the models AXI and HDG have patching symmetry. In the former, six patches of ligands each are arranged along each of three axes and the interpatch angles are introduced similarly to the case of the QTR model. In the HDG model, there are 12 single ligand patches arranged uniformly on the surface of the core unit, namely, on the vertices of a regular icosahedron resulting in a hedgehog-like appearance. The closest experimental realisations are, possibly, those based on tetrahedral decorations of the fullerene pseudo-spherical polyhedra [70,71].
Optimized deployment of anchors based on GDOP minimization for ultra-wideband positioning
Published in Journal of Spatial Science, 2022
Chuanyang Wang, Yipeng Ning, Jian Wang, Longping Zhang, Jun Wan, Qimin He
Different from the dynamic configuration optimization in outdoor satellite positioning, the anchors need to be pre-installed in advance in the indoor positioning. For the design of indoor positioning systems, the positions of fixed anchors can only be determined during installation based on the architecture of the building (Sharp et al. 2012). To achieve the lowest average GDOP, the base stations for absolute range and pseudorange need to be deployed differently (Li et al. 2011). A closed-form expression for the position dilution of precision (PDOP) in absolute-range-based two-dimensional (2-D) wireless location systems is derived, and the lowest PDOP has been proven (Quan 2014). The regular polygon is the configuration with the lowest possible GDOP attainable from pseudo-range measurements in two-dimensional scenarios (Levanon 2000). Similarly, the configuration which is composed of a regular polyhedron as the control point and the centre as unknown point has the lowest GDOP. The five kinds of regular polyhedrons including regular tetrahedron, cube, regular octahedron, regular icosahedron and regular dodecahedron are all optimal configurations in three-dimensional space (Shim and Yang 2010). However, these regular polyhedrons are not suitable for indoor positioning system design due to the signal propagation. Considering the complex indoor environment and the system cost, cone configuration can be introduced to apply for the design of an indoor positioning system. Meanwhile, the optimized deployment of anchors is an important way to improve the positioning precision.
Optimal orientations of discrete global grids and the Poles of Inaccessibility
Published in International Journal of Digital Earth, 2020
The methods described below will exhaustively generate all the possible orientations for each of several polyhedra. This is done at a coarse resolution using elliptical calculations. Duplicate orientations will be searched for and removed. Each remaining member of this sparsely-sampled orientation space will then used as a starting point for a hillclimbing algorithm which finds optimal orientations given some criteria of interest. Several polyhedra are considered here (Figure 1): the cuboctahedron, the regular dodecahedron, the regular icosahedron, the regular octahedron, and the regular tetrahedron. Since textual descriptions may be insufficient to recreate the algorithm, I provide source code on Github at https://github.com/r-barnes/Barnes2017-DggBestOrientations. Various software packages were used in the analysis (Barnes 2017; Becker et al. 2018; McIlroy et al. 2018; Wickham 2016; Wickham et al. 2018).