Carbazole-based artificial light-harvesting system for photocatalytic cross-coupling dehydrogenation reaction.

A carbazole-based artificial light-harvesting system (LHS) was successfully fabricated based on the supramolecular assembly of AIE-enhanced donor (CTD), water-soluble phosphate-pillar[5]arene (WPP5), and eosin Y (ESY) acceptor. The formed WPP5-CTD possessed remarkable AIE emission, featuring an ideal energy donor for light harvesting. After encapsulation of ESY, the energy of WPP5-CTD was efficiently transferred to ESY in WPP5-CTD-ESY, and the antenna effect was 38.5, which was much higher than that of recently reported LHSs. Notably, WPP5-CTD-ESY was successfully utilized as a photocatalyst to realize the cross-coupling dehydrogenation reaction of diphenylphosphine oxide and benzothiazole derivatives, suggesting great potential for aqueous photocatalytic applications of this LHS.

Integrated Three-Dimensional Microdevice with a Modified Surface for Enhanced DNA Separation from Biological Samples.

Functional interfaces and devices for rapid adsorption and immobilization of nucleic acids (NAs) are significant for relevant bioengineering applications. Herein, a microdevice with poly(acrylic acid) (PAA) photosensitive resin was integrated by three-dimensional (3D) printing, named DPAA for short. Precise microscale structures and abundant surface carboxyl functional groups were fabricated for fast and high-throughput deoxyribonucleic acid (DNA) separation. Surface modification was then done using polydopamine (PDA) and poly(ethylene glycol) (PEG) to obtain modified poly(acrylic acid) (PAA)-based devices DPDA-PAA and DPEG-PAA rich in amino and hydroxyl groups, respectively. The fabricated device DPAA possessed superior printing accuracy (40-50 µm). Functionalization of amino and hydroxyl was successful, and the modified devices DPDA-PAA and DPEG-PAA maintained a high thermal stability like DPAA. Surface potential analysis and molecular dynamics simulation indicated that the affinity for DNA was in the order of DPDA-PAA > DPEG-PAA > DPAA. Further DNA separation experiments confirmed the high throughput and high selectivity of DNA separation performance, consistent with the predicted affinity results. DPDA-PAA showed relatively the highest DNA extraction yield, while DPEG-PAA was the worst. An acidic binding system is more favorable for DNA separation and recovery. DPDA-PAA showed significantly better DNA extraction performance than DPAA in a weakly acidic environment (pH 5.0-7.0), and the average DNA yield of the first elution was 2.16 times that of DPAA. This work validates the possibility of modification on integrated 3D microdevices to improve their DNA separation efficiency effectively. It also provides a new direction for the rational design and functionalization of bioengineering separators based on nonmagnetic methods. It may pave a new path for the highly efficient polymerase chain reaction diagnosis.

Feature hypergraph representation learning on spatial-temporal correlations for EEG emotion recognition.

Electroencephalogram(EEG) becomes popular in emotion recognition for its capability of selectively reflecting the real emotional states. Existing graph-based methods have made primary progress in representing pairwise spatial relationships, but leaving higher-order relationships among EEG channels and higher-order relationships inside EEG series. Constructing a hypergraph is a general way of representing higher-order relations. In this paper, we propose a spatial-temporal hypergraph convolutional network(STHGCN) to capture higher-order relationships that existed in EEG recordings. STHGCN is a two-block hypergraph convolutional network, in which feature hypergraphs are constructed over the spectrum, space, and time domains, to explore spatial and temporal correlations under specific emotional states, namely the correlations of EEG channels and the dynamic relationships of temporal stamps. What's more, a self-attention mechanism is combined with the hypergraph convolutional network to initialize and update the relationships of EEG series. The experimental results demonstrate that constructed feature hypergraphs can effectively capture the correlations among valuable EEG channels and the correlations inside valuable EEG series, leading to the best emotion recognition accuracy among the graph methods. In addition, compared with other competitive methods, the proposed method achieves state-of-art results on SEED and SEED-IV datasets.

Water-soluble phosphate-pillar[5]arene (WPP5)-based artificial light-harvesting system for photocatalytic cross-coupling dehydrogenation.

A novel water-soluble phosphate-pillar[5]arene (WPP5)-based artificial light-harvesting system (LHS) was successfully fabricated through the supramolecular assembly of phenyl-pyridyl-acrylonitrile derivative (PBT), WPP5, and organic pigment Eosin Y (ESY). Initially, after host-guest interaction, WPP5 could bind well with PBT and form WPP5 âŠƒ PBT complexes in water, which further assembled into WPP5 âŠƒ PBT nanoparticles. WPP5 âŠƒ PBT nanoparticles performed an outstanding aggregation-induced emission (AIE) capability because of the J-aggregates of PBT in WPP5 âŠƒ PBT nanoparticles, which were appropriate as fluorescence resonance energy transfer (FRET) donors for artificial light-harvesting. Moreover, due to the emission region of WPP5 âŠƒ PBT overlapped well with the UV-Vis absorption of ESY, the energy of WPP5 âŠƒ PBT (donor) could be significantly transferred to ESY (acceptor) via FRET process in WPP5 âŠƒ PBT-ESY nanoparticles. Notably, the antenna effect (AEWPP5⊃PBT-ESY) of WPP5 âŠƒ PBT-ESY LHS was determined to be 30.3, which was much higher than that of recent artificial LHSs for photocatalytic cross-coupling dehydrogenation (CCD) reactions, suggesting a potential application in photocatalytic reaction. Furthermore, through the energy transfer from PBT to ESY, the absolute fluorescence quantum yields performed a remarkable increase from 14.4% (for WPP5 âŠƒ PBT) to 35.7% (for WPP5 âŠƒ PBT-ESY), further confirming their FRET processes in WPP5 âŠƒ PBT-ESY LHS. Subsequently, in order to output the harvested energy for catalytic reactions, WPP5 âŠƒ PBT-ESY LHSs were used as photosensitizers to catalyze the CCD reaction of benzothiazole and diphenylphosphine oxide. Compared to free ESY group (21%), a significant cross-coupling yield of 75% in WPP5 âŠƒ PBT-ESY LHS was observed, because more UV region energy of PBT was transferred to ESY for CCD reaction, which suggested more potential in improving the catalytic activity of organic pigment photosensitizers in aqueous systems.

Fusion Graph Representation of EEG for Emotion Recognition.

Various relations existing in Electroencephalogram (EEG) data are significant for EEG feature representation. Thus, studies on the graph-based method focus on extracting relevancy between EEG channels. The shortcoming of existing graph studies is that they only consider a single relationship of EEG electrodes, which results an incomprehensive representation of EEG data and relatively low accuracy of emotion recognition. In this paper, we propose a fusion graph convolutional network (FGCN) to extract various relations existing in EEG data and fuse these extracted relations to represent EEG data more comprehensively for emotion recognition. First, the FGCN mines brain connection features on topology, causality, and function. Then, we propose a local fusion strategy to fuse these three graphs to fully utilize the valuable channels with strong topological, causal, and functional relations. Finally, the graph convolutional neural network is adopted to represent EEG data for emotion recognition better. Experiments on SEED and SEED-IV demonstrate that fusing different relation graphs are effective for improving the ability in emotion recognition. Furthermore, the emotion recognition accuracy of 3-class and 4-class is higher than that of other state-of-the-art methods.

Solid-phase extraction methods for nucleic acid separation. A review.

The separation and purification of biomacromolecules such as nucleic acid is a perpetual topic in separation processes and bioengineering (fine chemicals, biopharmaceutical engineering, diagnostics, and biological characterization). In principle, the solid-phase extraction for nucleic acid exhibits efficient phase separation, low pollution risk, and small sample demand, compared to the conventional liquid-phase extraction. Herein, solid-phase extraction methods are systematically reviewed to outline research progress and explore additional solid-phase sorbents and devices for novel, flexible, and high-efficiency nucleic acid separation processes. The functional materials capture nucleic acid, magnetic and magnetic-free solid-phase extraction methods, separation device design and optimization, and high-throughput automatable applications based on high-performance solid-phase extraction are summarized. Finally, the current challenges and promising topics are discussed.