We discovered for the first time that light can twist metal to control the chirality of metal nanostructures (hereafter, chiral metal nanoneedles). The helicity of optical vortices is transferred to ...the constituent elements of the irradiated material (mostly melted material), resulting in the formation of chiral metal nanoneedles. The chirality of these nanoneedles could be controlled by just changing the sign of the helicity of the optical vortex. The tip curvature of these chiral nanoneedles was measured to be <40 nm, which is less than 1/25th of the laser wavelength (1064 nm). Such chiral metal nanoneedles will enable us to selectively distinguish the chirality and optical activity of molecules and chemical composites on a nanoscale and they will provide chiral selectivity for nanoscale imaging systems (e.g., atomic force microscopes), chemical reactions on plasmonic nanostructures, and planar metamaterials.
Abstract
Glycans serve important roles in signaling events and cell-cell communication, and they are recognized by lectins, viruses and bacteria, playing a variety of roles in many biological ...processes. However, there was no system to organize the plethora of glycan-related data in the literature. Thus GlyTouCan (https://glytoucan.org) was developed as the international glycan repository, allowing researchers to assign accession numbers to glycans. This also aided in the integration of glycan data across various databases. GlyTouCan assigns accession numbers to glycans which are defined as sets of monosaccharides, which may or may not be characterized with linkage information. GlyTouCan was developed to be able to recognize any level of ambiguity in glycans and uniquely assign accession numbers to each of them, regardless of the input text format. In this manuscript, we describe the latest update to GlyTouCan in version 3.0, its usage, and plans for future development.
Accurate representation of structural ambiguity is important for storing carbohydrate structures containing varying levels of ambiguity in the literature and databases. Although many representations ...for carbohydrates have been developed in the past, a generalized but discrete representation format did not exist. We had previously developed the Web3 Unique Representation of Carbohydrate Structures (WURCS) in an attempt to define a generalizable and unique linear representation for carbohydrate structures. However, it lacked sufficient rules to uniquely describe ambiguous structures. In this work, we updated WURCS to handle such ambiguous monosaccharide structures. In particular, to handle structural ambiguity around (potential) carbonyl groups incidental to the carbohydrate analysis, we defined a representation of backbone carbons containing atomic-level ambiguity. As a result, we show that WURCS 2.0 can represent a wider variety of carbohydrate structures containing ambiguous monosaccharides, such as those whose ring closure is undefined or whose anomeric information is only known. This new format provides a representation of carbohydrates that was not possible before, and it is currently being used by the International Glycan Structure Repository GlyTouCan.
GlyTouCan version 1.0 was released in 2015 as the international glycan structure repository, and a new sequence format called WURCS (Web3 Unique Representation of Carbohydrate Structures) was ...proposed during the early stages of the GlyTouCan project. GlyTouCan uses WURCS as its base representation for glycans because existing formats were insufficient in their flexibility to represent any and all glycans universally. Therefore, in order to obtain WURCS strings for existing or new glycan structures, conversion tools or glycan structure editors that can export WURCS became necessary. GlycanBuilder was an obvious choice to extend due to its wide usage by the community. However, GlycanBuilder was limited because it was originally developed to support mammalian glycans. It also did not support the newly proposed monosaccharide symbol standard called Symbol Nomenclature for Glycans (SNFG). Therefore in this work, we implemented a new version of GlycanBuilder to greatly increase its usability. The glycan rendering system was refactored so that cyclic glycans, nested repeating units, monosaccharide compositions and cross-linked glycan structures can be represented. Both import and export utilities for WURCS were also implemented and SNFG symbols were incorporated to allow glycans to be exported as graphics using the latest glycan symbol nomenclature.
This new version of GlycanBuilder called “GlycanBuilder2”, is able to support a wide variety of ambiguous glycans, including structures containing monosaccharides from bacteria and plants. These glycans can also be displayed using the new SNFG symbols. This tool can aid researchers in communicating about the complex, diverse, and ambiguous structures of glycans more rapidly. Moreover, the new GlycanBuilder can now easily output WURCS sequences from glycans drawn on the canvas. Most importantly, because GlyTouCan employs WURCS as the basic format for registration and searching of glycan information, a wider variety of glycans can now be readily registered and queried in GlyTouCan.
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•Implemented the new GlycanBuilder to support a wide variety of ambiguous glycans.•Ambiguous glycans such as cyclic and cross-linked structures can be drawn.•Updated to handle the newly proposed monosaccharide symbol called SNFG.•The new GlycanBuilder can visualize glycan images from WURCS strings.•The new GlycanBuilder can output WURCS sequences from glycans drawn on the canvas.
Rapid and continued growth in the generation of glycomic data has revealed the need for enhanced development of basic infrastructure for presenting and interpreting these datasets in a manner that ...engages the broader biomedical research community. Early in their growth, the genomic and proteomic fields implemented mechanisms for assigning unique gene and protein identifiers that were essential for organizing data presentation and for enhancing bioinformatic approaches to extracting knowledge. Similar unique identifiers are currently absent from glycomic data. In order to facilitate continued growth and expanded accessibility of glycomic data, the authors strongly encourage the glycomics community to coordinate the submission of their glycan structures to the GlyTouCan Repository and to make use of GlyTouCan identifiers in their communications and publications. The authors also deeply encourage journals to recommend a submission workflow in which submitted publications utilize GlyTouCan identifiers as a standard reference for explicitly describing glycan structures cited in manuscripts.
Lateral and vertical two-dimensional heterostructure devices, in particular graphene–MoS2, have attracted profound interest as they offer additional functionalities over normal two-dimensional ...devices. Here, we have carried out electrical and optical characterization of graphene–MoS2 heterostructure. The few-layer MoS2 devices with metal electrode at one end and monolayer graphene electrode at the other end show nonlinearity in drain current with drain voltage sweep due to asymmetrical Schottky barrier height at the contacts and can be modulated with an external gate field. The doping effect of MoS2 on graphene was observed as double Dirac points in the transfer characteristics of the graphene field-effect transistor (FET) with a few-layer MoS2 overlapping the middle part of the channel, whereas the underlapping of graphene have negligible effect on MoS2 FET characteristics, which showed typical n-type behavior. The heterostructure also exhibits a strongest optical response for 520 nm wavelength, which decreases with higher wavelengths. Another distinct feature observed in the heterostructure is the peak in the photocurrent around zero gate voltage. This peak is distinguished from conventional MoS2 FETs, which show a continuous increase in photocurrent with back-gate voltage. These results offer significant insight and further enhance the understanding of the graphene–MoS2 heterostructure.
Glycans are known as the third major class of biopolymers, next to DNA and proteins. They cover the surfaces of many cells, serving as the 'face' of cells, whereby other biomolecules and viruses ...interact. The structure of glycans, however, differs greatly from DNA and proteins in that they are branched, as opposed to linear sequences of amino acids or nucleotides. Therefore, the storage of glycan information in databases, let alone their curation, has been a difficult problem. This has caused many duplicated efforts when integration is attempted between different databases, making an international repository for glycan structures, where unique accession numbers are assigned to every identified glycan structure, necessary. As such, an international team of developers and glycobiologists have collaborated to develop this repository, called GlyTouCan and is available at http://glytoucan.org/, to provide a centralized resource for depositing glycan structures, compositions and topologies, and to retrieve accession numbers for each of these registered entries. This will thus enable researchers to reference glycan structures simply by accession number, as opposed to by chemical structure, which has been a burden to integrate glycomics databases in the past.
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