Elucidating the structural and conformational preferences of bioactive chromone and its monohydrate through advanced rotational spectroscopy.

Chromones are a class of naturally occurring compounds, renowned for their diverse biological activities with significant relevance in medicine and biochemistry. This study marks the first analysis of rotational spectra of both the chromone monomer and its monohydrate through Fourier transform microwave spectroscopy. The observation of nine mono-substituted 13C isotopologues facilitated a semi-experimental determination of the equilibrium structure of the chromone monomer. In the case of chromone monohydrate, two distinct isomers were identified, each characterized by a combination of O-H⋯O and C-H⋯O hydrogen bonds involving the chromone's carbonyl group. This study further delved into intermolecular non-covalent interactions, employing different theoretical approaches. The relative population ratio of the two identified isomers was estimated to be about 2:1 within the supersonic jet.

A Closer Look at the Reflection Formulation in Single Image Reflection Removal.

How to model the effect of reflection is crucial for single image reflection removal (SIRR) task. Modern SIRR methods usually simplify the reflection formulation with the assumption of linear combination of a transmission layer and a reflection layer. However, the large variations in image content and the real-world picture-taking conditions often result in far more complex reflection. In this paper, we introduce a new screen-blur combination based on two important factors, namely the intensity and the blurriness of reflection, to better characterize the reflection formulation in SIRR. Specifically, we present Screen-blur Reflection Networks (SRNet), which executes the screen-blur formulation in its network design and adapts to the complex reflection on real scenes. Technically, SRNet consists of three components: a blended image generator, a reflection estimator and a reflection removal module. The image generator exploits the screen-blur combination to synthesize the training blended images. The reflection estimator learns the reflection layer and a blur degree that measures the level of blurriness for reflection. The reflection removal module further uses the blended image, blur degree and reflection layer to filter out the transmission layer in a cascaded manner. Superior results on three different SIRR methods are reported when generating the training data on the principle of the screen-blur combination. Moreover, extensive experiments on six datasets quantitatively and qualitatively demonstrate the efficacy of SRNet over the state-of-the-art methods.

Intranasal G5-BGG/pDNA Vaccine Elicits Protective Systemic and Mucosal Immunity against SARS-CoV-2 by Transfecting Mucosal Dendritic Cells.

Infectious disease pandemics, including the coronavirus disease 2019 pandemic, have heightened the demand for vaccines. Although parenteral vaccines induce robust systemic immunity, their effectiveness in respiratory mucosae is limited. Considering the crucial role of nasal-associated lymphoid tissue (NALT) in mucosal immune responses, in this study, the intranasal complex composed of G5-BGG and antigen-expressing plasmid DNA (pSP), named G5-BGG/pSP complex, is developed to activate NALT and to promote both systemic and mucosal immune defense. G5-BGG/pSP could traverse mucosal barriers and deliver DNA to the target cells because of its superior nasal retention and permeability characteristics. The intranasal G5-BGG/pSP complex elicits robust antigen-specific immune responses, such as the notable production of IgG antibody against several virus variants. More importantly, it induces elevated levels of antigen-specific IgA antibody and a significant expansion of the lung-resident T lymphocyte population. Notably, the intranasal G5-BGG/pSP complex results in antigen expression and maturation of dendritic cells in nasal mucosae. These findings exhibit the potential of G5-BGG, a novel cationic material, as an effective gene carrier for intranasal vaccines to obtain robust systemic and mucosal immunity.

Inorganic Skeleton Reinforcement-A Generic Approach to Improve the Mechanical Properties of Biochar.

Biochar is considered as a promising candidate for emerging sustainable energy systems and environmental technology applications. However, the improvement of mechanical properties remains challenges. Herein, we propose a generic strategy to enhance the mechanical properties of bio-based carbon materials through inorganic skeleton reinforcement. As a proof-of-concept, silane, geopolymer, and inorganic gel are selected as precursors. The composites' structures are characterized and an inorganic skeleton reinforcement mechanism is elucidated. Specifically, two types of reinforcement of the silicon-oxygen skeleton network formed in situ with biomass pyrolysis and the silica-oxy-al-oxy network are constructed to improve the mechanical properties. A significant improvement in mechanical strength was achieved for bio-based carbon materials. The compressive strength of well-balanced porous carbon materials modified by silane can reach up to 88.9 kPa, geopolymer-modified carbon material exhibits an enhanced compressive strength of 36.8 kPa, and that of inorganic-gel-polymer-modified carbon material is 124.6 kPa. Moreover, the prepared carbon materials with enhanced mechanical properties show excellent adsorption performance and high reusability for organic pollutant model compound methylene blue dye. This work demonstrates a promising and universal strategy for enhancing the mechanical properties of biomass-derived porous carbon materials.

Design and Synthesis of Functional Silane-Based Silicone Resin and Application in Low-Temperature Curing Silver Conductive Inks.

In the field of flexible electronics manufacturing, inkjet printing technology is a research hotspot, and it is key to developing low-temperature curing conductive inks that meet printing requirements and have suitable functions. Herein, methylphenylamino silicon oil (N75) and epoxy-modified silicon oil (SE35) were successfully synthesized through functional silicon monomers, and they were used to prepare silicone resin 1030H with nano SiO2. 1030H silicone resin was used as the resin binder for silver conductive ink. The silver conductive ink we prepared with 1030H has good dispersion performance with a particle size of 50-100 nm, as well as good storage stability and excellent adhesion. Additionally, the printing performance and conductivity of the silver conductive ink prepared with n,n-dimethylformamide (DMF): proprylene glycol monomethyl ether (PM) (1:1) as solvent are better than those of the silver conductive ink prepared by DMF and PM solvent. Cured at a low temperature of 160 °C, the resistivity of 1030H-Ag-82%-3 conductive ink is 6.87 × 10-6 Ω·m, and that of 1030H-Ag-92%-3 conductive ink is 0.564 × 10-6 Ω·m, so the low-temperature curing silver conductive ink has high conductivity. The low-temperature curing silver conductive ink we prepared meets the printing requirements and has potential for practical applications.

Shotgun knockdown of RNA by CRISPR-Cas13d in fission yeast.

The CRISPR-Cas13d system has a single small effector protein that targets RNA and does not require the presence of a protospacer flanking site in the targeted transcript. These features make CRISPR-Cas13d an attractive system for RNA manipulation. Here, we report the successful implementation of the CRISPR-Cas13d system in fission yeast for RNA knockdown. A high effectiveness of the CRISPR-Cas13d system was ensured by using an array of CRISPR RNAs (crRNAs) that are flanked by two self-cleaving ribozymes and are expressed from an RNA polymerase II promoter. Given the repressible nature of the promoter, RNA knockdown by the CRISPR-Cas13d system is reversible. Moreover, using the CRISPR-Cas13d system, we identified an effective crRNA array targeting the transcript of gfp and the effectiveness was demonstrated by successful knockdown of the transcripts of noc4-gfp, bub1-gfp and ade6-gfp. In principle, the effective GFP crRNA array allows knockdown of any transcript carrying the GFP sequences. This new CRISPR-Cas13d-based toolkit is expected to have a wide range of applications in many aspects of biology, including dissection of gene function and visualization of RNA.

Recent advances in the design of single-atom electrocatalysts by defect engineering.

Single-atom catalysts (SACs) with isolated metal atoms dispersed on supports have attracted increasing attention due to their maximum atomic utilization and excellent catalytic performance in various electrochemical reactions. However, SACs with a high surface-to-volume ratio are fundamentally less stable and easily agglomerate, which weakens their activity. In addition, another issue that restricts the application of SACs is the low metal loading. Defect engineering is the most effective strategy for the precise synthesis of nanomaterials to catch and immobilize single atoms through the modulation of the electronic structure and coordination environment. Herein, in this mini-review, the latest advances in designing SACs by defect engineering have been first highlighted. Then, the heteroatom doping or intrinsic defects of carbon-based support and anion vacancies or cation vacancies of metal-based supports are systematically evaluated. Subsequently, the structure-activity relationships between a single-atom coupled defect structure and electrocatalytic performance are illustrated by combining experimental results and theoretical calculations. Finally, a perspective to reveal the current challenges and opportunities for controllable preparation, in situ characterization, and commercial applications is further proposed.

Multi-view spectral clustering via common structure maximization of local and global representations.

The essential problem of multi-view spectral clustering is to learn a good common representation by effectively utilizing multi-view information. A popular strategy for improving the quality of the common representation is utilizing global and local information jointly. Most existing methods capture local manifold information by graph regularization. However, once local graphs are constructed, they do not change during the whole optimization process. This may lead to a degenerated common representation in the case of existing unreliable graphs. To address this problem, rather than directly using fixed local representations, we propose a dynamic strategy to construct a common local representation. Then, we impose a fusion term to maximize the common structure of the local and global representations so that they can boost each other in a mutually reinforcing manner. With this fusion term, we integrate local and global representation learning in a unified framework and design an alternative iteration based optimization procedure to solve it. Extensive experiments conducted on a number of benchmark datasets support the superiority of our algorithm over several state-of-the-art methods.

Brain-computer interface based on intermodulation frequency.

OBJECTIVE: Most recent steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems have used a single frequency for each target, so that a large number of targets require a large number of stimulus frequencies and therefore a wider frequency band. However, human beings show good SSVEP responses only in a limited range of frequencies. Furthermore, this issue is especially problematic if the SSVEP-based BCI takes a PC monitor as a stimulator, which is only capable of generating a limited range of frequencies. To mitigate this issue, this study presents an innovative coding method for SSVEP-based BCI by means of intermodulation frequencies. APPROACH: Simultaneous modulations of stimulus luminance and color at different frequencies were utilized to induce intermodulation frequencies. Luminance flickered at relatively large frequency (10, 12, 15 Hz), while color alternated at low frequency (0.5, 1 Hz). An attractive feature of the proposed method was that it would substantially increase the number of targets at a single flickering frequency by altering color modulated frequencies. Based on this method, the BCI system presented in this study realized eight targets merely using three flickering frequencies. MAIN RESULTS: The online results obtained from 15 subjects (14 healthy and 1 with stroke) revealed that an average classification accuracy of 93.83% and information transfer rate (ITR) of 33.80 bit min(-1) were achieved using our proposed SSVEP-based BCI system. Specifically, 5 out of the 15 subjects exhibited an ITR of 40.00 bit min(-1) with a classification accuracy of 100%. SIGNIFICANCE: These results suggested that intermodulation frequencies could be adopted as steady responses in BCI, for which our system could be used as a practical BCI system.