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The objective of this study was to evaluate and compare the effectiveness of three different types of bariatric surgeries, namely, sleeve gastrectomy (SG), one-anastomotic gastric bypass (OAGB), and single anastomosis sleeve ileal (SASI) bypass, in the treatment of metabolic syndrome (MS). The optimal approach for managing MS remains uncertain, and thus this study aimed to provide a recent analysis of the efficacy of these surgical procedures. This retrospective study evaluated data of individuals who underwent SG, OAGB, and SASI bypass. The primary outcome measures included weight, body mass index (BMI), glucolipid metabolic index, and the occurrence of treatment-related complications within 6 to 12 months post-surgery. A total of 324 patients were included in this study. Of these, 264 patients underwent SG, 30 underwent OAGB, and 30 underwent SASI bypass. A significant decrease in weight was observed at the 6-month and 12-month marks following all three surgical procedures. Of these, patients who underwent SASI bypass exhibited the greatest reduction in weight and BMI post-surgery. Furthermore, the SASI bypass was associated with a significantly higher percentage of total weight loss (%TWL) and excess body mass index loss (%EBMIL) compared to SG and OAGB. Patients who underwent OAGB and SASI bypass demonstrated notable improvements in type 2 diabetes mellitus (T2DM). Patients who underwent SASI bypass and OAGB experienced greater postoperative comfort and reported fewer complaints of discomfort compared to the other procedure. Based on the retrospective analysis of the data, SASI bypass was associated with greater reductions in weight and BMI, higher percentages of %TWL and %EBMIL, and better improvement in T2DM compared to SG and OAGB. Therefore, both SASI bypass and OAGB were found to be more effective than SG in the treatment of MS. [ABSTRACT FROM AUTHOR]

A Gram-positive, aerobic, non-motile, non-spore-forming, short rod-shaped strain, NEAU-LLCT, was isolated from cow dung in Shangzhi City, Heilongjiang Province, Northeast China and identified by a polyphasic taxonomic study. Colonies was light yellow, round, with entire margin. Strain NEAU-LLCT was grown at 15–45 ℃ and pH 6.0–10.0. NaCl concentration ranged from 0 to 5% (W/V). The 16S rRNA gene sequence of NEAU-LLCT showed the high similarities with Microbacterium kyungheense JCM 18735T (98.5%), Microbacterium trichothecenolyticum JCM 1358T (98.3%) and Microbacterium jejuense JCM 18734T (98.2%). The whole-cell sugars were glucose, rhamnose and ribose. The menaquinones contained MK-12 and MK-13. Ornithine, glutamic acid, lysine and a small amount of alanine and glycine were the amino acids in the hydrolyzed products of the cell wall. The major fatty acids were iso-C16:0, iso-C18:0, anteiso-C15:0 and anteiso-C17:0. The main polar lipids were diphosphatidylglycerol, phosphatidylglycerol and an unidentified glycolipid. The genome of NEAU-LLCT was 4,369,375 bp and G + C content is 70.28 mol%. A combination of DNA–DNA hybridization result and some phenotypic characteristics demonstrated that strain NEAU-LLCT could be distinguished from its closely related strains. Therefore, the strain NEAU-LLCT was considered to represent a novel species, which was named Microbacterium helvum sp. (Type strain NEAU-LLCT = CCTCC AA 2018026T = JCM 32661T). [ABSTRACT FROM AUTHOR]

Three Gram-stain positive, aerobic actinomycete strains, designated NEAU-A15T, NEAU-A13 and NEAU-C4, were isolated from rhizosphere soil of wheat (Triticum aestivum L.) collected from Langfang, Hebei Province, China. Based on their morphological characteristics, biochemical features and molecular phylogenetic studies, these strains were concluded to belong to a new member of the genus Glycomyces. 16S rRNA gene sequence analysis showed that strain NEAU-A15T shares 99.91% and 99.80% 16S rRNA gene sequence similarity with NEAU-A13 and NEAU-C4, respectively, and these three strains showed high sequence similarities to Glycomyces algeriensis DSM 44727T (99.24, 99.45, 99.38%), Glycomyces lechevalierae DSM 44724T (98.97, 99.17, 99.11%) and Glycomyces rutgersensis DSM 43812T (98.83, 99.04, 98.97%). Phylogenetic analysis indicated that these three strains clustered together and formed a cluster with Glycomyces tritici NEAU-C2T (97.30, 97.73, 99.48%), G. algeriensis DSM 44727T, G. lechevalierae DSM 44724T and G. rutgersensis DSM 43812T. These three strains were observed to contain MK-10(H2), MK-10(H6) and MK-11 as menaquinones. The whole cell sugar profiles were found to contain galactose, ribose and xylose. The polar lipids were found to consist of diphosphatidylglycerol, phosphatidylinositol, phosphatidylglycerol, phosphoglycolipid, phosphatidylinositol mannoside and an unidentified glycolipid. The major fatty acids were identified as anteiso-C15:0, iso-C16:0, anteiso-C17:0 and iso-C15:0. The DNA–DNA hybridization values between strain NEAU-A15T and NEAU-A13/NEAU-C4 were 86.2 ± 2.3% and 83.4 ± 3.5%, respectively. The values between these three strains and their close phylogenetic relatives were 48–52%, supporting the conclusion that they belong to a distinct genomic species. An array of phenotypic characteristics also differentiated these isolates from their closely related species. On the basis of the genetic and phenotypic properties, strains NEAU-A15T, NEAU-A13 and NEAU-C4 can be classified as representatives of a novel species of the genus Glycomyces, for which the name Glycomyces luteolus sp. nov., is proposed. The type strain is NEAU-A15T (= DSM 104643T = CGMCC 4.7394T). [ABSTRACT FROM AUTHOR]

From bacteria following simple chemical gradients to the brain distinguishing complex odour information, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemented using DNA-based neural networks, but has been limited to the recognition of a set of no more than four patterns, each composed of four distinct DNA molecules. Winner-take-all computation has been suggested as a potential strategy for enhancing the capability of DNA-based neural networks. Compared to the linear-threshold circuits and Hopfield networks used previously, winner-take-all circuits are computationally more powerful, allow simpler molecular implementation and are not constrained by the number of patterns and their complexity, so both a large number of simple patterns and a small number of complex patterns can be recognized. Here we report a systematic implementation of winner-take-all neural networks based on DNA-strand-displacement reactions. We use a previously developed seesaw DNA gate motif, extended to include a simple and robust component that facilitates the cooperative hybridization that is involved in the process of selecting a ‘winner’. We show that with this extended seesaw motif DNA-based neural networks can classify patterns into up to nine categories. Each of these patterns consists of 20 distinct DNA molecules chosen from the set of 100 that represents the 100 bits in 10 × 10 patterns, with the 20 DNA molecules selected tracing one of the handwritten digits ‘1’ to ‘9’. The network successfully classified test patterns with up to 30 of the 100 bits flipped relative to the digit patterns ‘remembered’ during training, suggesting that molecular circuits can robustly accomplish the sophisticated task of classifying highly complex and noisy information on the basis of similarity to a memory. DNA-strand-displacement reactions are used to implement a neural network that can distinguish complex and noisy molecular patterns from a set of nine possibilities—an improvement on previous demonstrations that distinguished only four simple patterns. [ABSTRACT FROM AUTHOR]

Self-assembled DNA nanostructures enable nanometre-precise patterning that can be used to create programmable molecular machines and arrays of functional materials. DNA origami is particularly versatile in this context because each DNA strand in the origami nanostructure occupies a unique position and can serve as a uniquely addressable pixel. However, the scale of such structures has been limited to about 0.05 square micrometres, hindering applications that demand a larger layout and integration with more conventional patterning methods. Hierarchical multistage assembly of simple sets of tiles can in principle overcome this limitation, but so far has not been sufficiently robust to enable successful implementation of larger structures using DNA origami tiles. Here we show that by using simple local assembly rules that are modified and applied recursively throughout a hierarchical, multistage assembly process, a small and constant set of unique DNA strands can be used to create DNA origami arrays of increasing size and with arbitrary patterns. We illustrate this method, which we term 'fractal assembly', by producing DNA origami arrays with sizes of up to 0.5 square micrometres and with up to 8,704 pixels, allowing us to render images such as the Mona Lisa and a rooster. We find that self-assembly of the tiles into arrays is unaffected by changes in surface patterns on the tiles, and that the yield of the fractal assembly process corresponds to about 0.95m − 1 for arrays containing m tiles. When used in conjunction with a software tool that we developed that converts an arbitrary pattern into DNA sequences and experimental protocols, our assembly method is readily accessible and will facilitate the construction of sophisticated materials and devices with sizes similar to that of a bacterium using DNA nanostructures. [ABSTRACT FROM AUTHOR]

The impressive capabilities of the mammalian brain-ranging from perception, pattern recognition and memory formation to decision making and motor activity control-have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control. Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the 'intelligent' behaviour required for survival. However, the study of how molecules can 'think' has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically, experimental work has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment. [ABSTRACT FROM AUTHOR]

This paper presents a DNA algorithm which adds two nonnegative binary integers using self-assembly in constant steps. The approach has the benefit of greater experimental simplicity when compared with previous DNA addition algorithms. For the addition of two binary n-bit integers, O(n) is different from DNA strands and only O(1) biochemical experimental procedures are required. [ABSTRACT FROM AUTHOR]

In this research, a nanoscale DNA structure of analogic China map is created. The nanostructure of roughly 150 nm in diameter with a spatial resolution of 6 nm is purely constructed by folding DNA. The picture observed by atomic force microscopy (AFM) is almost identical with the designed shape. The DNA origami technology invented by Rothemund in 2006 is employed in the construction of this shape, which has proved the capability of constructing almost any complicated shape enabled by DNA origami, and provides new bottom-up method for constructing nanostructures. [ABSTRACT FROM AUTHOR]

The original version of this Article omitted a reference to previous work in 'Stojanovic, M. N. & Stefanovic, D. A deoxyribozyme-based molecular automaton. Nat. Biotechnol. 21, 1069-1074 (2003)'. This has been added as reference 42. The following has been added after the third sentence of the fifth paragraph of the Discussion: 'Integration could also allow more sophisticated information processing, for example as shown by the classic deoxyribozyme-based automaton that plays tic-tac-toe42, to direct structural reconfiguration (Supplementary Discussion)'. This has been corrected in the PDF and HTML versions of the Article. [ABSTRACT FROM AUTHOR]

The dynamic interactions between complex molecular structures underlie a wide range of sophisticated behaviors in biological systems. In building artificial molecular machines out of DNA, an outstanding challenge is to develop mechanisms that can control the kinetics of interacting DNA nanostructures and that can compose the interactions together to carry out system-level functions. Here we show a mechanism of DNA tile displacement that follows the principles of toehold binding and branch migration similar to DNA strand displacement, but occurs at a larger scale between interacting DNA origami structures. Utilizing this mechanism, we show controlled reaction kinetics over five orders of magnitude and programmed cascades of reactions in multi-structure systems. Furthermore, we demonstrate the generality of tile displacement for occurring at any location in an array in any order, illustrated as a tic-tac-toe game. Our results suggest that tile displacement is a simple-yet-powerful mechanism that opens up the possibility for complex structural components in artificial molecular machines to undergo information-based reconfiguration in response to their environments. Strand displacement is commonly used in DNA nanotechnology to program dynamic interactions between individual DNA strands. Here, the authors describe a tile displacement principle that is similar in concept but occurs on a larger structural level: the displacement reactions take place between DNA origami tiles, allowing reconfiguration of entire systems of interacting DNA structures. [ABSTRACT FROM AUTHOR]