Electroencephalography (EEG) measures the neuronal activities in different brain regions via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit the topology of EEG channels. In this paper, we propose a regularized graph neural network (RGNN) for EEG-based emotion recognition. RGNN considers the biological topology among different brain regions to capture both local and global relations among different EEG channels. Specifically, we model the inter-channel relations in EEG signals via an adjacency matrix in a graph neural network where the connection and sparseness of the adjacency matrix are inspired by neuroscience theories of human brain organization. In addition, we propose two regularizers, namely node-wise domain adversarial training (NodeDAT) and emotion-aware distribution learning (EmotionDL), to better handle cross-subject EEG variations and noisy labels, respectively. Extensive experiments on two public datasets, SEED and SEED-IV, demonstrate the superior performance of our model than state-of-the-art models in most experimental settings. Moreover, ablation studies show that the proposed adjacency matrix and two regularizers contribute consistent and significant gain to the performance of our RGNN model. Finally, investigations on the neuronal activities reveal important brain regions and inter-channel relations for EEG-based emotion recognition.

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Heparan sulfate is a sulfated glycan that exhibits essential physiological functions. Interrogation of the specificity of heparan sulfate-mediated activities demands a library of structurally defined oligosaccharides. Chemical synthesis of large heparan sulfate oligosaccharides remains challenging. We report the synthesis of oligosaccharides with different sulfation patterns and sizes from a disaccharide building block using glycosyltransferases, heparan sulfate C 5 -epimerase, and sulfotransferases. This method offers a generic approach to prepare heparan sulfate oligosaccharides possessing predictable structures. Heparan sulfate (HS)3 is a unique class of macromolecular natural product that is present in large quantities on the mammalian cell surface and in the extracellular matrix. HS participates in regulating blood coagulation, embryonic development, and the inflammatory response and assists viral/bacterial infections. It consists of a repeating disaccharide unit of glucuronic acid (GlcUA) or iduronic acid (IdoUA) and glucosamine, both capable of carrying sulfo groups (1). The sulfation pattern of HS dictates its biological activity (2, 3). Heparin, a widely used anticoagulant drug, is a specialized form of highly sulfated HS. The diverse biological functions present considerable opportunities for exploiting HS or HS-protein conjugates for developing new classes of anticancer (4), antiviral (5), and improved anticoagulant drugs (6). Furthermore, a recent worldwide outbreak of contaminated heparin underscores the needs for synthetic heparins to replace those isolated from animal tissues (7). Chemical synthesis is a powerful tool to obtain structurally defined heparin/HS oligosaccharides. The most successful example is the total synthesis of an antithrombin-binding pentasaccharide (8). This pentasaccharide is marketed under the trade name Arixtra for the treatment of venous thromboembolic disorders. However, the chemical synthesis of oligosaccharides larger than an octasaccharide is extremely difficult, especially when multiple target structures are required for biological evaluation (8). An enzyme-based method offers a promising alternative approach to synthesize HS.The HS biosynthetic pathway involves multiple enzymes, including HS polymerase, epimerase, and sulfotransferases ( Fig. 1). HS polymerase is responsible for building the polysaccharide backbone, containing the repeating unit of -GlcUA-GlcNAc-. The backbone is then modified by N-deacetylase/N-sulfotransferase (having two separate domains exhibiting the activity of N-deacetylase and N-sulfotransferase, respectively), C 5 -epimerase (C 5 -epi, converting GlcUA to IdoUA), 2-O-sulfotransferase (2-OST), 6-O-sulfotransferase (6-OST) and 3-O-sulfotransferase (3-OST) to produce the fully elaborated HS. With the exception of HS polymerase, all of these biosynthetic enzymes have been expressed at high levels in Escherichia coli (1), permitting easy access to an abundance of enzymes. Using HS sulfotransferases and C 5 -epi, we previously developed a method ...

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We report the first chemoenzymatic synthesis of the stable isotope-enriched heparin from a uniformly labeled [ 13 C, 15 N]N-acetylheparosan (-GlcA(1,4)GlcNAc-) prepared from E. coli K5. Glycosaminoglycan (GAG) precursors and heparin were formed from N-acetylheparosan by the following steps: chemical N-deacetylation and N-sulfonation leading to N-sulfoheparosan (-GlcA (1,4)GlcNS-); enzyme-catalyzed C 5 -epimerization and 2-O-sulfonation leading to undersulfated heparin (-IdoA2S(1,4)GlcNS-); enzymatic 6-O-sulfonation leading to the heparin backbone (-IdoA2S(1,4)GlcNS6S-); and selective enzymatic 3-O-sulfonation leading to the anticoagulant heparin, containing the GlcNS6S3S residue. Heteronuclear, multidimensional nuclear magnetic resonance spectroscopy was employed to analyze the chemical composition and solution structure of [ 13 C, 15 N]N-acetylheparosan, precursors, and heparin. Isotopic enrichment was found to provide well-resolved 13 C spectra with the high sensitivity required for conformational studies of these biomolecules. Stable isotope-labeled heparin was indistinguishable from heparin derived from animal tissues and is a novel reagent for studying the interaction of heparin with proteins.