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Photo-induced self-healing materials, which can be controlled remotely, instantly and precisely, are attracting increasing attention in various fields. However, it still remains challenging to modulate the self-healing materials with integrated functionalities possessing multiple-wavelength photo-responsiveness. Herein, we report a strategy of building a photo-responsive self-healing system capable of performing ultraviolet (UV) and near-infrared (NIR) two-wavelength induced double-repair. The strategy is based on azobenzene-functionalized multiwalled carbon nanotubes (MWCNTs) via a two-step method. Oxidized MWCNTs were first reacted subsequently with thionyl chloride, glycol, and 2-bromoisobutyryl bromide to yield MWCNT-Br macroinitiators. Then atom transfer radical polymerization (ATRP) of azobenzene monomer, 6-(4-butyl-4′-oxyazobenzene) hexyl methacrylate (Azo), was directly initiated by MWCNT-Br, affording MWCNT-PAzo nanocomposites. The MWCNT-PAzo system can undergo photothermal- and photochemical-induced solid-liquid phase transition to manipulate the self-healing behavior while MWCNTs act as photo-absorbers/heat sources and azobenzene moieties serve on glass transition temperatures (Tg) switchers, in response to NIR and UV light stimuli, respectively. To our best of knowledge, this is the first-time that MWCNT-PAzo nanocomposites possess two-wavelength photo-responsiveness and exhibit excellent self-healing performance through the irradiation of two-wavelength bands (365 and 808 nm) of UV/NIR light.

Purpose/Aim: Pulmonary fibrosis (PF) is characterized by the progressive and ultimately fatal accumulation of fibroblasts and extracellular matrix in the lung that distorts its architecture and compromises its function.Objective: The present study investigated the potential protective effects of schisandrin B (Sch B) on the Wingless/Integrase-1 (Wnt) signaling pathway in attenuating inflammation and oxidative stress in ICR mice.Methods: Sixty healthy ICR mice were randomly divided into the following groups: control group, bleomycin (BLM) group, Sch B low dose (Sch B-L) group, Sch B medium dose (Sch B-M) group, Sch B high dose (Sch B-H) group, and dexamethasone (DXM) group. The expression of transforming growth factor (TGF)-β1 was examined by ELISA. In addition, the levels of superoxide dismutase (SOD), hydroxyproline (HYP), and the total antioxidant capacity (T-AOC) were determined. The protein and mRNA levels of matrix metalloproteinase 7 (MMP7) and β-catenin in mice were analyzed by western blot and quantitative real -quantitative time PCR (qRT-PCR), respectively.Results: Lung tissues from the BLM group exhibited significantly more inflammatory changes and a significantly greater number of collagen fibers than lung tissues from the control group. In addition, the lung tissues from these BLM-treated mice exhibited slightly increased MMP7 and β-catenin protein expression. Lung tissues from the Sch B-H group exhibited fewer inflammatory changes and fewer collagen fibers than lung tissues from the BLM group. Furthermore, the lung tissues from the Sch B-H mice exhibited decreased HYP and TGF-β1 levels, but increased SOD and T-AOC levels.Conclusions: The present study provided evidence that Sch B may be a potential therapeutic agent for the treatment of PF.

Cervical cancer is one of the most common cancers among women in the world, over 570,000 patients are affected annually. Pathological examination for patients using Pap Smear becomes the mainstream of cervical cancer diagnoses. Accurate diagnoses and analyses largely rely on 3 factors: cell segmentation, feature extraction and selection as well as classification. Firstly, a 2-layer segmentation algorithm based on block Maximum Between-Class Variance (Otsu) and Gradient Vector Flow (GVF) Snake model is applied to obtain regions of interest (ROI). Then the features of chroma, shape and texture are extracted and selected for a better classification performance. The random forest algorithm based on Artificial Fish Swarms Algorithm (AFSA) is used to recognize and classify cervical epithelial cells. The proposed methods were tested on 200 cervical Pap Smear images. Experimental results show that cervical cells can be segmented with an effective segmentation result. The proposed feature selection method achieved an accuracy of 81.31% with the minimum feature number. The improved random forest algorithm with 2 and 7 classification under fivefold cross-validation reaches the highest classification accuracy (96.86%). Experimental results showed that the proposed method has obvious recognition advantages, and thus provides a practical classification frame for the diagnoses of cervical cancer.

Allosteric effects are common in biology, but have not been fully explored in the control of supramolecular polymerization. Herein, ditopic UPy derivatives with acyclic crown ether-like spacers were designed and synthesized, which can undergo supramolecular polymerization through quadruple hydrogen bonding. Upon the addition of K+, drastic molecular conformational change to the U-shape is induced by metal-coordination, reconfiguring remote UPy sites towards the formation of discrete cyclic dimers. Interestingly, the supramolecular polymerization can be restored by simply removing K+ by water-extraction.

Carbon dioxide is an ideal raw material for the synthesis of complex organic compounds because of its rich, non-toxic, and good physical properties. It is of great significance to transform CO2 into valuable fine chemicals and develop a green sustainable cycle of carbon surplus. Based on hydrosilane as a reducing agent, this work summarizes the recent applications of reductive amidation of CO2 using different catalysts such as organocatalysts, ionic liquids (ILs), salts, transition metal complexes, and solvents. The main factors affecting the reductive amidation of CO2 and the possible reaction mechanism are discussed. Moreover, the future orientation and catalytic systems of the formylation of amines with CO2 and hydrosilane are prospected.

Local binary pattern (LBP) has already been proved to be a powerful measure of image texture with fixed sampling scheme: all P neighbor pixels in a single-scale are usually sampled by using a fixed radius R. It can effectively address grayscale and rotation variations. However, the LBP method is sensitive to image noise and fails to achieve desirable performance for texture classification with significant scale changes. With the aim to deal with these disadvantages of LBP, a new method named scale-adaptive local binary pattern (SALBP) is proposed in this paper. The essence of our proposed SALBP method is to adaptively find a single but optimal scale from multiple scales for each radial direction in accordance with the characteristics of a local area. First, we select candidates of neighbors by the majority vote strategy for signs. Second, we determine final neighbor pixels by the maximal difference magnitude selection strategy for magnitudes of candidates. This procedure lets each neighbor pixel to adaptively obtain its own optimal scale from multiple scales, which refers to the adaptive optimal sampling radius. Therefore, scale invariance can be significantly improved. Extensive experiments on four public texture databases (i.e., Outex, CUReT, UIUC and Brodatz) demonstrate that the proposed SALBP method achieves significantly better results than representative LBP variants for texture classification tasks with a smaller feature dimension.

In recent years, magnon and spin texture are attracting great interest in condensed matter physics and magnetism. Magnonics is aiming to use magnon as information carriers to realize functions for storage, transmission, and processing. Magnetic skyrmion is representative spin texture due to its topologically nontrivial properties. Since skyrmions are topologically protected, their transformation to other spin configurations requires overcoming additional topological energy barriers. Therefore, skyrmions are more stable than other trivial spin textures. In addition, the characters of nanoscale size, quasiparticle properties, and various excitation modes make them a potential candidate for spintronic application. Magnon and skyrmion, as two fundamental excitations, can coexist in magnetic systems and interplay with each other through direct exchange interactions. In this review, we provide an overview of recent theoretical and experimental studies on magnon–skyrmion interactions. We mainly focus on three kinds of magnon–skyrmion interactions: (i) magnon scattering by skyrmion, (ii) skyrmion motion driven by magnon, and (iii) coupling between magnon and skyrmion modes. The first two kinds of interactions could be clearly explained by the wave-particle interaction model on the classical level. Alternatively, the last kind of interaction could be understood by the coupled harmonic oscillator model on the quantum level, which indicates fast energy exchange and hybrid magnon states. The exploration focused on quantum phenomena of magnon has led to the emerging field of quantum magnonics and promoted applications of magnon in quantum information storage and processing. In the end, we give a perspective on the exploration of magnon–skyrmion interaction in quantum magnonics.

The phenotypic traits of

The development of new sustainable catalytic conversion methods of carbon dioxide (CO

A simple strategy to afford trifluoromethyl-containing bendamustine hydrochloride in 34% overall via nine simple steps including substitution, selective reduction, N-acylation, cyclization, esterification, nitro-reduction, N-dihydroxyethylation, chlorination, and acid-catalyzed hydrolysis from commercially available 2,4-dinitrochlorobenzene is described. The structures of the intermediates and target product are established on the basis of infrared, nuclear magnetic resonance, and high resolution mass spectrometer. Moreover, the structure of target product is also confirmed by X-ray crystal analysis, and further studies indicate that the existence of intermolecular O–H···Cl and N–H···Cl hydrogen bonds are effective in stabilization of the crystal structure.

In this study, the authors propose a parallel concatenated decoding (PCD) scheme for short non-binary low-density-parity-check (NB-LDPC) codes. It consists of a reduced trellis extended min-sum (R-TEMS) algorithm which efficiently reduces the check node updating complexity over high-order Galois fields and a low complexity ordered statistic decoding aided by partial cyclic redundancy check bits. The R-TEMS algorithm has a negligible performance loss and noticeable reduction in decoding complexity with respect to the trellis-based EMS (TEMS) algorithm. Besides, the PCD shows a close error-correction performance when compared with other concatenated decoding schemes for NB-LDPC codes. It achieves a coding gain about 0.5 dB with reasonable complexity contrasted with the Q-ary sum-product algorithm for high-rate short NB-LDPC codes over GF(256).

In this paper, we study inventory management for the one warehouse multi-retailer (OWMR) system with considering carbon emissions, in which we determine the reorder intervals for the warehouse and the retailers while minimizing the inventory ordering and holding cost and the carbon emission cost. We consider the carbon emissions from the holding and replenishing inventory activities in the OWMR system, and calculate the carbon emissions based on the frequency of the inventory replenishment at the warehouse and the retailers. We focus on stationary and integer-ratio policies, and formulate the problem as an optimization model with a convex objective function and a set of integer-ratio constraints. We relax the integer-ratio constraints, and introduce an algorithm to solve the corresponding relaxed problem to optimality in O ( n log n ) times, where n represents the number of retailers. Based on the optimal solution of the relaxed problem, we build an integer-ratio policy, i.e., power-of-two (POT) policy, with 94% optimality for the primal problem. The computational results show that with considering the carbon emission cost, the reorder intervals of the warehouse and the retailers both increase, and that the integrated model proposed in this paper has more superiorities in terms of reducing the system-wide cost and the carbon emissions.

Local binary pattern (LBP) has been successfully used in computer vision and pattern recognition applications, such as biomedical image analysis, remote sensing and image retrieval. However, the current LBP-based features, which assign a fixed sampling radius for all pixels in a single scale, completely ignore the fact that different central pixels actually have different local gray-value distributions and the proper sampling radius should be different for pixels. In this paper, we propose a novel and effective central pixel selection (CPS) strategy by using gradient information to classify central pixels of a texture image into different classes based on their local gray-value distributions. Then, we introduce this CPS strategy into the LBP framework and assign an adaptive sampling radius for each central pixel according to the class it belongs to. As a preprocessing step of LBP framework, this CPS strategy can also be integrated into any other LBP variants so as to extract more effective local texture features. Extensive experiments on five representative texture databases of Outex, UIUC, CUReT, UMD and ALOT validate the efficiency of the proposed central pixel selection (CPS) strategy, which can achieve almost 16% improvement over the original LBP and 1%–10% improvement compared with the best classification accuracy among other benchmarked state-of-the-art LBP variants.

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease of the central nervous system (CNS). Evidence about experimental autoimmune encephalomyelitis (EAE), a mouse model of MS, has been shown to modulate disease parameters within exercise intervention. However, these initial studies weren't carried out intensity of exercise in mice. This study explored the impacts of different-intensity swimming training on EAE mice. Female mice were given access to swimming with predetermined weight (moderated-intensity (ME) group is 0% body weight; high-intensity (HE) group is 4% body weight) for 6 weeks, were immunized to induce EAE and then continued swimming until sacrificed. Compared to non-exercise mice, ME training didn't affect EAE clinical symptoms and neuropathology. However, HE swimming attenuated EAE clinical scores, reduced infiltrating cells and demyelination of spinal cords. Analysis of CD4+ T cell subsets from CNS of EAE showed the reduction of Th1 and Th17 populations and an increase of Treg in HE, not ME mice. Accordingly, HE training lead to a decrease of IFN-γ and IL-17 and an increase of IL-10 and TGF-β. Of note, HE, not ME, swimming induced an increase of brain derived neurotrophic factor in the CNS of EAE. Moreover, HE training upregulated Treg and downregualted antigen-specific T cell proliferation and Th1 and Th17 populations from draining lymph node cells. These results suggest that HE swimming training might have benefits on attenuating the progression and pathological hallmarks of EAE, thus representing an important non-pharmacological intervention for improvement of chronic inflammation or T-cell mediated autoimmunity.

Here we report our research on biomimetic folding architectures self-assembled hierarchically from well-designed UPy-based monomers with low molecular weight (MW < 400 Da). These monomers are first dimerized via quadruple hydrogen bonding and then form folded dimers with the assistance of π–π interactions. More interestingly, the folded dimer further formed one-dimensional supramolecular stacks through additional weak π–π interactions in the solid state. Similar to DNA, these well-defined structures are stabilized by the concerted hydrogen bonding and π–π interaction in a synergistic manner, which would provide inspiration for constructing biomimetic self-folding materials.

The control of supramolecular polymerization is of high fundamental significance for understanding self-assembly processes at the nanoscale. It also remarkably affects the design and improves the efficiency of dynamic polymer materials. To this end, we have developed an effective strategy which employs a type of non-covalent interaction to orthogonally regulate the supramolecular polymerization driven by another non-covalent interaction. Specifically, we herein report the quadruple hydrogen bond-driven supramolecular polymerization controlled by the assistance of the π–π interaction. A series of aromatic group bridged ditopic ureidopyrimidinone (UPy) derivatives (M1, M2, and M3) were designed and successfully synthesized. These molecules could self-assemble into cyclic monomers or linear supramolecular polymers under different conditions via quadruple hydrogen bonding. By additionally introducing a π–π interaction into the cyclic monomers, which exists between the aromatic group and the dimerized UPy motifs, a ring-opening supramolecular polymerization process based on ring-chain equilibrium can be preliminarily controlled due to the adjustable strength of the π–π interaction. These findings could offer new perspectives into orthogonal self-assembly and provide model systems for the studies of fundamental supramolecular polymer physics.

The relationship between molecular structure and macroscopic characteristics is a fundamental issue for materials design. Some minor changes in molecular structure may have a great impact on the molecular self-assembly process. Therefore, it is of interest to design new isomeric building blocks for supramolecular self-assembly, offering inspiration for the development of smart materials by supramolecular engineering. In this study, two dioxynaphthalene (DNP) group bridged bifunctional ureidopyrimidinone (UPy) monomers (DNP1 and DNP2) were synthesized. The chemical structures of the two isomers are very similar and the only difference is that DNP1 is 2,6-substituted and DNP2 is 1,5-substituted on the DNP motif. Interestingly, these two isomers exhibit completely different supramolecular self-assembly behaviors. Highly viscous supramolecular polymers were obtained in a concentrated solution of DNP1, while crystals based on highly stable cyclic monomers were precipitated from a concentrated solution of DNP2. Since DNP is an electron rich group, the host–guest behaviors of DNP1 and DNP2 with a blue-box were further studied, which also showed different ring-threading capabilities.

Background Opioid use disorder presents a public health issue afflicting millions across the globe. There is a pressing need to understand the opioid supply chain to gain new insights into the mitigation of opioid use and effectively combat the opioid crisis. The role of anonymous online marketplaces and forums that resemble eBay or Amazon, where anyone can post, browse, and purchase opioid commodities, has become increasingly important in opioid trading. Therefore, a greater understanding of anonymous markets and forums may enable public health officials and other stakeholders to comprehend the scope of the crisis. However, to the best of our knowledge, no large-scale study, which may cross multiple anonymous marketplaces and is cross-sectional, has been conducted to profile the opioid supply chain and unveil characteristics of opioid suppliers, commodities, and transactions. Objective We aimed to profile the opioid supply chain in anonymous markets and forums via a large-scale, longitudinal measurement study on anonymous market listings and posts. Toward this, we propose a series of techniques to collect data; identify opioid jargon terms used in the anonymous marketplaces and forums; and profile the opioid commodities, suppliers, and transactions. Methods We first conducted a whole-site crawl of anonymous online marketplaces and forums to solicit data. We then developed a suite of opioid domain–specific text mining techniques (eg, opioid jargon detection and opioid trading information retrieval) to recognize information relevant to opioid trading activities (eg, commodities, price, shipping information, and suppliers). Subsequently, we conducted a comprehensive, large-scale, longitudinal study to demystify opioid trading activities in anonymous markets and forums. Results A total of 248,359 listings from 10 anonymous online marketplaces and 1,138,961 traces (ie, threads of posts) from 6 underground forums were collected. Among them, we identified 28,106 opioid product listings and 13,508 opioid-related promotional and review forum traces from 5147 unique opioid suppliers’ IDs and 2778 unique opioid buyers’ IDs. Our study characterized opioid suppliers (eg, activeness and cross-market activities), commodities (eg, popular items and their evolution), and transactions (eg, origins and shipping destination) in anonymous marketplaces and forums, which enabled a greater understanding of the underground trading activities involved in international opioid supply and demand. Conclusions The results provide insight into opioid trading in the anonymous markets and forums and may prove an effective mitigation data point for illuminating the opioid supply chain.

Nonnutritive sweeteners (NNSs) are sugar substitutes widely used to reduce the negative health effects of excessive sugar consumption. Dental caries, one of the most prevalent chronic diseases globally, results from a pathogenic biofilm with microecological imbalance and frequent exposure to sugars. Some research has shown that certain NNSs possess less cariogenic potential than sucrose, indicating their putative effect on oral microbiome. To uncover the alterations of acidogenic pathogens and alkali-generating commensals, as well as the biofilm cariogenic potential under the influence of NNSs, we selected four common NNSs (acesulfame-K, aspartame, saccharin, and sucralose) and established single-, dual-, and multispecies in vitro culture model to assess their effects on Streptococcus mutans (S. mutans) and/or Streptococcus sanguinis (S. sanguinis) compared to sucrose with the same sweetness. The results showed that NNSs significantly suppressed the planktonic growth, acid production, and biofilm formation of S. mutans or S. sanguinis compared with sucrose in single-species cultures. Additionally, decreased S. mutans/S. sanguinis ratio, less EPS generation, and higher pH value were observed in dual-species and saliva-derived multispecies biofilms with supplementary NNSs. Collectively, this study demonstrates that NNSs inhibit the cariogenic potential of biofilms by maintaining microbial equilibrium, thus having a promising prospect as anticaries agents.

With the ongoing deployment of 5G cellular networks, the research and development of 6G technologies have recently triggered. The current studies begin to explore the higher frequency bands, such as Terahertz (THz) and Petahertz (PHz). In order to meet the requirements PHz communications, we focus on the novel coding schemes with short block-length and high code rate. Last year, Arikan proposed new concatenated codes called polarization-adjusted convolutional (PAC) codes. Under the Fano decoding, the performance of PAC codes with short block-length can approach Polyanskiy-Poor-Verdu (PPV) bound. In order to reduce complexity, list decoding of PAC codes is proposed. However, there is no general construction method for PAC codes with different block-lengths and code rates. In order to obtain an effective solution of PAC codes construction with higher code rates and longer lengths, we propose a genetic algorithm (GenAlg) based optimization scheme of PAC codes evaluated by list decoding. The simulation results show that a (512, 256) PAC code optimized by the proposed GenAlg scheme can achieve a noticeable performance gain of 0.25 dB at block error rate (BLER) of 10−3, when compared to the PAC code constructed by Gaussian approximation (GA). A (256,192) PAC code constructed by our scheme can lend to a coding gain of 0.3 dB at BLER of 10−2 when compared to the PAC code constructed by Gaussian approximation (GA).

We investigated whether identification of different finger tasks only relying on the agonist or antagonist extensor digitorum communis (EDC) can be improved by using high-density sEMG (HDsEMG) pre-processed with principal component analysis (PCA). Monopolar HDsEMG was respectively recorded from EDC when the EDC muscle respectively acted as agonist or antagonist muscles. PCA-based approach was evaluated using k-nearest neighbour (KNN) classifier and compared with the classical spatial filters. Using PCA-based configuration can achieve better classification performance in identification of tasks and effort levels and dramatically outperformed spatial filtering configurations in all cases (p

BACKGROUND Opioid use disorder presents a public health issue afflicting millions across the globe. There is a pressing need to understand the opioid supply chain to gain new insights into the mitigation of opioid use and effectively combat the opioid crisis. The role of anonymous online marketplaces and forums that resemble eBay or Amazon, where anyone can post, browse, and purchase opioid commodities, has become increasingly important in opioid trading. Therefore, a greater understanding of anonymous markets and forums may enable public health officials and other stakeholders to comprehend the scope of the crisis. However, to the best of our knowledge, no large-scale study, which may cross multiple anonymous marketplaces and is cross-sectional, has been conducted to profile the opioid supply chain and unveil characteristics of opioid suppliers, commodities, and transactions. OBJECTIVE We aimed to profile the opioid supply chain in anonymous markets and forums via a large-scale, longitudinal measurement study on anonymous market listings and posts. Toward this, we propose a series of techniques to collect data; identify opioid jargon terms used in the anonymous marketplaces and forums; and profile the opioid commodities, suppliers, and transactions. METHODS We first conducted a whole-site crawl of anonymous online marketplaces and forums to solicit data. We then developed a suite of opioid domain–specific text mining techniques (eg, opioid jargon detection and opioid trading information retrieval) to recognize information relevant to opioid trading activities (eg, commodities, price, shipping information, and suppliers). Subsequently, we conducted a comprehensive, large-scale, longitudinal study to demystify opioid trading activities in anonymous markets and forums. RESULTS A total of 248,359 listings from 10 anonymous online marketplaces and 1,138,961 traces (ie, threads of posts) from 6 underground forums were collected. Among them, we identified 28,106 opioid product listings and 13,508 opioid-related promotional and review forum traces from 5147 unique opioid suppliers’ IDs and 2778 unique opioid buyers’ IDs. Our study characterized opioid suppliers (eg, activeness and cross-market activities), commodities (eg, popular items and their evolution), and transactions (eg, origins and shipping destination) in anonymous marketplaces and forums, which enabled a greater understanding of the underground trading activities involved in international opioid supply and demand. CONCLUSIONS The results provide insight into opioid trading in the anonymous markets and forums and may prove an effective mitigation data point for illuminating the opioid supply chain.

With the aid of CTAB amphiphile, water-phase artificial light-harvesting systems were fabricated as nanoparticles by the self-assembly of two low-molecular-weight organic molecules: a UPy-functionalized TPE derivative 1 with both supramolecular polymerization and AIE capabilities as a donor and a fluorescent chromophore NiR as an acceptor. Owing to the flexibility of supramolecular self-assembly, tunable emissions including white-light emission could be easily realized with high energy transfer efficiency and the antenna effect.

This paper applies machine learning core algorithms to business district operation planning to explore the attributes of retail performance and operational efficiency of Business District. This paper mainly uses K-Nearest Neighbor Algorithms to sort shops by their consumption records. Besides that it also uses K-means Clustering Algorithm and Association Rules Algorithm to cluster shop consumption types and uses association rules to find consumption association routes. Based on the above operation results, it can provide more accurate and effective data for business operators to make business district operation plans.

Carbon dioxide is an ideal raw material for the synthesis of complex organic compounds because of its rich, non-toxic, and good physical properties. It is of great significance to transform CO

S-glutathionylation is an important post-translational modification (PTM) process that targets protein cysteine thiols by the addition of glutathione (GSH). This modification can prevent proteolysis caused by the excessive oxidation of protein cysteine residues under oxidative or nitrosative stress conditions. Recent studies have suggested that protein S-glutathionylation plays an essential role in the control of cell-signaling pathways by affecting the protein function in bacteria and even humans. In this study, we investigated the effects of S-glutathionylation on physiological regulation within Streptococcus mutans, the primary etiological agent of human dental caries. To determine the S-glutathionylated proteins in bacteria, the Cys reactive isobaric reagent iodoacetyl Tandem Mass Tag (iodoTMT) was used to label the S-glutathionylated Cys site, and an anti-TMT antibody-conjugated resin was used to enrich the modified peptides. Proteome profiling identified a total of 357 glutathionylated cysteine residues on 239 proteins. Functional enrichment analysis indicated that these S-glutathionylated proteins were involved in diverse important biological processes, such as pyruvate metabolism and glycolysis. Furthermore, we studied a thioredoxin-like protein (Tlp) to explore the effect of S-glutathionylation on interspecies competition between oral streptococcal biofilms. Through site mutagenesis, it was proved that glutathionylation on Cys41 residue of Tlp is crucial to protect S. mutans from oxidative stress and compete with S. sanguinis and S. gordonii. An addition rat caries model showed that the loss of S-glutathionylation attenuated the cariogenicity of S. mutans. Taken together, our study provides an insight into the S-glutathionylation of bacterial proteins and the regulation of oxidative stress resistance and interspecies competition., Author summary S-glutathionylation is involved in many physiological processes such as antioxidation, detoxification and cell proliferation. However, the proteomics research on S-glutathionylation has never been performed in gram-positive bacteria. The identification of and functional studies on glutathione reductase, glutathione synthesis dual-functional enzyme and glutathione-S-transferase in Streptococcus mutans, the main causative agent of dental caries, inspired the existence of complete S-glutathionylation system in this type of bacteria. It may impact various crucial physiological processes by regulating the function of modified proteins. Here, we explored the entire S-glutathionylation proteome through high-specific labeling and high-sensitivity mass spectrometry technologies. The results showed that about 11.7% of the total S. mutans proteins were S-glutathionylated, which indicated that S-glutathionylation plays a fundamental role in the regulation of cellular processes. Through functional analysis and domain prediction, we next uncovered a potential thioredoxin that contains two modified cysteines on its key active motif; S-glutathionylation of the sites affected the oxidative resistance, competition and cariogenecity of S. mutans. We anticipate that S-glutathionylation proteome studies could be performed on more refractory infectious diseases, revealing more mechanisms of pathogen infection and providing new methods to treat infectious diseases.

More than 700 different species of bacteria, viruses, fungi, mycoplasma, and chlamydia live in the human oral cavity, collectively known as the oral microbiome. The ecological imbalance of oral microbiome can induce oral infectious diseases, such as dental caries and periodontal disease. Oral microorganisms are also closely related to tumors, diabetes, rheumatoid arthritis, cardiovascular diseases, premature delivery, and other systemic diseases, which have a significant impact on human health. So far, more than 65% of oral microbiota can be cultured in vitro. In order to better study the relationship between oral microbes and human health, several human oral microbiome collection and oral microbiome database have been established. In this chapter, the biological and pathogenic characteristics of several newly isolated oral microbes from dental plaque were introduced. Gram staining, plate culture, colony, and scanning electron microscope (SEM) images of each microorganism were also provided.

Gait analysis is the systematic study of human locomotion from the perspective of biology and kinematic. This work investigates the relationship between motion of feet and plantar pressure during human walking on five different types of terrains typical of daily living. Temporal parameters and symmetry index of gaits are calculated by method based on angular velocity of coronal axis. The results show gait features on different terrain and subject have commonness and differences.

A number of upper rim-functionalized calix[4]thiourea cyclohexanediamine derivatives have been designed, synthesized and used as catalysts for enantioselective Michael addition reactions between nitroolefins and acetylacetone. The optimal catalyst 2 with a mono-thiourea group exhibited good performance in the presence of water/toluene (v/v = 1:2). Under the optimal reaction conditions, high yields of up to 99% and moderate to good enantioselectivities up to 94% ee were achieved. Detailed experiments clearly showed that the upper rim-functionalized hydrophobic calixarene scaffold played an important role in cooperation with the catalytic center to the good reactivities and enantioselectivities.

Coal gasification wastewater (CGW) possess a high phenolics content, how to remove phenols is the crux of the environmental problems. In this work, we report the design and synthesis of a several highly graphitized ordered mesoporous carbons (OMCs) by carbonization of precursors from phenol and formalin. The obtained porous OMCs have uniform structures with the pore size, order degree, and surface areas being controllable by varying the synthesis conditions. In depth study of the prepared materials reveals that the OMCs carbonized at 923.15 K exhibit ordered 2D hexagonal mesoporous structures with high degree of graphitization, high surface area (590.6 m2·g−1), appropriate pore size (mean diameter about 10 nm) and large mesoporous pore volume (0.512 cm3·g−1). The prepared OMCs are applied as adsorbent for treatment of the CGW collected directly from the biochemical effluent of coal chemical enterprise in Inner Mongolia Autonomous region, China. The OMCs show excellent adsorption properties for phenol effluent with the removal efficiency of phenols being up to 92.3%. The adsorption experiment data demonstrates that the adsorption is a multi-molecular layer adsorption process, during which the physical adsorption takes place. In addition, the study of adsorption thermodynamics indicates that the adsorption process is spontaneous and endothermic. The adsorption of samples on phenol from CGW has reached an ideal level.

As a simple and efficient local feature descriptor, local binary pattern (LBP) is mainly made up of two steps: extraction step and encoding step. In the extraction step, a local region is denoted by a difference vector between the center pixel and its neighbors. In the encoding step, the corresponding binary bit-string of the difference vector is encoded for the following texture classification. Though encoding step plays a vital role in the whole process of LBP, two current widely used encoding schemes of LBPriu2 and LBC still have some limitations. Different from these two current encoding schemes, in this paper, we propose a new LBP encoding scheme based on the maximum run length of state “1” (LBPmr1) in a binary bit-string. The maximum run length of state “1” reflects the most important part of the binary bit-string structure and it is used as the LBP code of a binary bit-string for the first time. Experimental results on four representative texture databases of Outex, UIUC, CUReT and UMD show that the proposed LBPmr1 achieves better classification accuracy compared with other related LBP encoding schemes.

A novel oxo-spirocyclic structure bridged ditopic Schiff base fluorescent probe L has been successfully synthesized and characterized. Interestingly, probe L exhibits a specific turn-on response to zinc(II) ion in fluorescence with a high selectivity and sensitivity. Further study show that probe L could be applied in imaging of live cells for sensing zinc(II) ion. By contrast, those compounds (L1, L2, and L3) with very similar structure to L lack this properties. The fluorescence intensity of L increases with Zn2+, which is less affected by other metal ions. The binding property of L with Zn2+ was studied by a combination of technologies, such as Job's plot, 1H NMR, ESI-MS, and DFT calculations. Moreover, we have successfully applied the probe L to detect Zn2+ in cancer cell. We are anticipating that this new oxo-spirocyclic structure bridged ditopic Schiff base may provide a new idea for the design of fluorescent probe.

The two-well-vertical (TWV) cavern-constructing with gas blanket technology is an important alternative to the single-well (SW) with oil blanket technology. This technology has the advantages of achieving larger cavern volume, clean brine, great water flow rate, and high economic benefits. Promoting and developing its theory and technology will help the future development of salt mining and cavern construction for energy storage in China, as it is in the initial stage. In this paper, a visualized physical simulation platform of water dissolving of the TWV caverns with gas blanket was established, and large size salt rock blocks were used to simulate the constructing process of salt caverns. The similarity ratios of size, flow rate, and time between prototype and model were calculated by using the similarity theory and dimensional analysis. A series of physical simulation tests of water-dissolving caverns were carried out, that the research factors including the two-well-spacing, flow rate, and gas/oil blanket. The results show that: (1) The water flow rate can be increased to 200–400 m3/h by increasing the two-well-spacing when using the TWV technology, which is 2–4 times that of the single-well. (2) It is found that 30–40 m is the optimal size for the two-well-spacing, and the two-well-space is much larger than 40 m may exist risks of roof instability. (3) During the initial stage of cavern construction, it will obtain a smaller lateral solution angle and an ideal cavern bottom groove shape with gas blanket. After the cavern construction is finished, it also will obtain better cavern shape, larger cavern volume and clean brine by comparing with oil blanket. So, the technology of the TWV cavern construction with gas blanket is promising for brine leaching and energy storage cavern construction and it is also worth further study.