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Abstract This study investigates the mechanical, thermal, and water absorption properties of high-density polyethylene (HDPE) composites filled with barley straw and varying amounts of waste rubber. The research aims to develop sustainable materials that repurpose agricultural and industrial waste while addressing resource scarcity and waste management challenges. Composites were prepared using a twin-rotor mixer and hydraulic press, with waste rubber content varying from 0 to 20 wt%. Mechanical properties were evaluated through tensile testing, thermal behavior was analyzed using TGA, DTG, and DSC, and long-term water absorption was measured. Results show that increasing waste rubber content from 0 to 20% led to a decrease in tensile strength (11.3 to 8.9 MPa) and tensile modulus (1760 to 790 MPa), while relative extension increased (2.4–5.9%). Thermal analysis revealed a slight reduction in onset degradation temperature (270 °C to 240 °C) and increased char residue (8–18%) with higher rubber content. Water absorption decreased significantly, from 12 to 13% to 6–7% after 600 h of immersion, as waste rubber content increased. These findings demonstrate that incorporating waste rubber into HDPE/barley straw composites results in materials with enhanced flexibility and water resistance at the cost of some strength and stiffness. In conclusion, the results of this study offer a clear pathway for the development of sustainable polymer composites that have broad potential applications across industries like construction, marine infrastructure, automotive, and packaging. By replacing traditional, resource-intensive materials with eco-friendly alternatives, these composites not only provide functional benefits but also support global efforts toward sustainable development and environmental conservation.

Abstract This study presents an experimental and numerical comparison between the mechanical performance of a lightweight corrugated sandwich panel based on the tea oil camellia shell (TOCS). Hence, TOCS was mixed in two groups with Poplar particles and fibers. After that, in the experimental part, the conventional mechanical tests, including the 3-point bending test, flatwise compression, dowel bearing, and screw resistance, and in the numerical part, finite element analysis (FEA), including the normal, maximum principal, and equivalent (von Mises) stress by Ansys Mechanical software carried out. The specimens for experimental and numerical tests were prepared in transverse and longitudinal directions. Before that, the engineering data (shear modulus, Young's modulus, and Poisson's ratio) for improving the FEA simulation were obtained from TOCS-based flat panels fabricated with a mixture of Poplar particles and fibers. The results of FEA are used to compare the mechanical behavior and failure mechanism with the results of experimental tests. According to the mean values of bending stiffness and maximum bending moment, sandwich panels made with 100% particles demonstrated an advantage in both directions. Nevertheless, the compression strength and screw resistance showed the same trend, but the dowel bearing showed higher values for panels made with fibers. The observed results of equivalent (von Mises) stress indicated a coloration with the results of failure mechanisms.

Abstract Pressure engineering in semiconductors leads to a variety of novel physical phenomena and has recently received considerable attention. Here, we report on pressure-induced superconductivity in III–V gallium phosphide (GaP), a commercially important semiconductor that exhibits excellent optical performance. We show that the emergence of superconductivity is accompanied by the concurrence of piezochromic transition and metallization and can be correlated to a structural transition from the cubic to orthorhombic phase. In line with the structural origin of superconductivity, the critical temperature T c monotonically decreases with increasing pressure up to ~50 GPa. Moreover, the superconductivity could be preserved toward ambient pressure because of the irreversibility of the structural transition. Nevertheless, the superconducting transition displays evident broadening associated with the presence of amorphization in the depressurized sample. The synchronous evolution of the structural and electronic properties not only shows a vivid structure-property relationship but also could facilitate the exploration of novel functionalities by means of pressure treatment.

Financial time series data are characterized by non-linearity, non-stationarity, and stochastic complexity, so predicting such data presents a significant challenge. This paper proposes a novel hybrid model for financial forecasting based on CEEMDAN-SE and ARIMA- CNN-LSTM. With the help of the CEEMDAN-SE method, the original data are decomposed into several IMFs and reconstructed via sample entropy into a lower-complexity stationary high-frequency component and a low-frequency component. The high-frequency component is predicted by the ARIMA statistical forecasting model, while the low-frequency component is predicted by a neural network model combining CNN and LSTM. Compared to some classical prediction models, our algorithm exhibits superior performance in terms of three evaluation indexes, namely, RMSE, MAE, and MAPE, effectively enhancing model accuracy while reducing computational overhead.

Abstract Infrared and visible image fusion aims to generate synthetic images including salient targets and abundant texture details. However, traditional techniques and recent deep learning-based approaches have faced challenges in preserving prominent structures and fine-grained features. In this study, we propose a lightweight infrared and visible image fusion network utilizing multi-scale attention modules and hybrid dilated convolutional blocks to preserve significant structural features and fine-grained textural details. First, we design a hybrid dilated convolutional block with different dilation rates that enable the extraction of prominent structure features by enlarging the receptive field in the fusion network. Compared with other deep learning methods, our method can obtain more high-level semantic information without piling up a large number of convolutional blocks, effectively improving the ability of feature representation. Second, distinct attention modules are designed to integrate into different layers of the network to fully exploit contextual information of the source images, and we leverage the total loss to guide the fusion process to focus on vital regions and compensate for missing information. Extensive qualitative and quantitative experiments demonstrate the superiority of our proposed method over state-of-the-art methods in both visual effects and evaluation metrics. The experimental results on public datasets show that our method can improve the entropy (EN) by 4.80%, standard deviation (SD) by 3.97%, correlation coefficient (CC) by 1.86%, correlations of differences (SCD) by 9.98%, and multi-scale structural similarity (MS_SSIM) by 5.64%, respectively. In addition, experiments with the VIFB dataset further indicate that our approach outperforms other comparable models.

This paper studies an extended continuous-time insider trading model of Calentey and Stacchetti (2010, Econometrica), which allows market makers to observe some partial information about a dynamic risky asset. For each of the two cases with trading until either a fixed time or a random time, we establish the existence and uniqueness of linear Bayesian equilibrium, consisting of insider trading intensity, price pressure on market orders and price pressure on asset observations. It shows that at each of the two equilibria, all information on the risky asset is incorporated in the market price and when the volatility of observation noise keeps constant, the more information observed by market makers, the smaller price pressure on market orders but the greater price pressure on asset observations such that the insider earns less profit and vice versa. It suggests that the partial observation of market makers weakens the information advantage of the insider, which prevents the insider from monopolizing the market to make excessive profit, then reduces the losses of noise traders, thus improving the fairness and effectiveness in the insider trading market.

In order to standardize the characterization and application of food inspection, promote the processing and exchange of food inspection information, accelerate the fusion and sharing of food inspection data, improve the comprehensive efficiency of food inspection, the structural reconstruction and integration of the core elements of food inspection information was carried out. The method of hybrid classifying combining line classifying and surface classifying was adopted to create the classifying systems of food inspection items and food inspection methods. The methods of sequence coding, concatenation coding and combination coding were adopted to prepare the coding schemes of food inspection items and food inspection methods, and the coding structure of 6 code segments and 16 code bits was designed, Thus, the general system of food inspection classifying and coding with stable logical structure features and open data expansion functions was build. The general system showed a high degree of professional integration and a wide range of industry universality. It can assign a unique decimal Arabic numeral code to specific food inspection event, and achieve efficient query of food inspection. The prospect of using computer programming technology to develop the general information system of food inspection classifying and coding based on internet cloud, a public technical service product, was also put forward.

This paper summarized the sampling results of food safety supervision issued by Henan Provincial Administration for Market Regulation in 2021, and analyzed them from multiple dimensions such as food category, unqualified items, sampling areas, packaging type, time, etc, so as to find out food safety risks and provide a reference for the regulatory authorities. It was found that among a total of 73918 batches of inspected food samples, 1417 batches were unqualified, with an overall qualified rate of 98.08%. The inspected samples covered 32 food categories in total. The qualified rates of 10 categories, including roasted seeds and nuts, frozen drinks, catering food, edible agricultural products, convenience food and so on, were lower than the overall qualified rate of 98.08%. The main risk indicators were excessive residues of pesticides and veterinary drugs, microbial contamination, unqualified quality index and excessive use of food additives, accounting for 88.08% of the total number of unqualified items. The unqualified rate in the fourth quarter was significantly higher than that in the first three quarters. The unqualified rate of bulk foods was higher than that of prepackaged foods. In 2021, the overall situation of food safety in Henan Province was good, but there were still varying degrees of risks in some categories and indicators. It was suggested to strengthen the supervision of high-risk categories, indicators, as well as enterprises with frequent problems, and enhance source management.

A stochastic discrete fractional Cournot duopoly game model with a unique interior Nash equilibrium is developed in this study. Some sufficient criteria of the Lyapunov stability in probability for the proposed model at the interior Nash equilibrium are derived using the Lyapunov theory. The proposed model’s finite time stability in probability is then investigated using a nonlinear feedback control approach at the interior Nash equilibrium. The stochastic Bellman theory is also used to explore the locally optimum control problem. Furthermore, bifurcation diagrams, time series, and the 0-1 test are used to investigate the chaotic dynamics of this model. Finally, numerical examples are given to illustrate the obtained results.

There has been growing interest in the high-entropy ceramic (HEC) recently owing to its tailorable compositions and microstructures, versatile properties, together with promising structural and functional applications. However, inferior fracture toughness (KIC) and damage tolerance restricted many practical applications of the HEC. Herein, we addressed this challenge by incorporating a three-dimensional graphene–carbon nanotube (3D G–CNT) as toughening agent in (Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)C. The resulting enhanced 3D G–CNT/(Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)C featured an outstanding toughness of 8.23 MPa·m1/2, while remaining superior strength (763 MPa) and hardness (24.7 GPa). An ultralow friction coefficient (0.15) coupled with an ultralow wear rate (w, 2.6×10−7 mm3/(N·m)) in the 3D G–CNT/(Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)C was obtained primarily as a function of lubricating scrolls, in which two-dimensional (2D) graphene acted as a tribolayer, and one-dimensional (1D) carbon nanotubes acted as nano ball bearings embedded inside. Strikingly, the 3D G–CNT/(Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)C exhibited rather low thermal conductivity (κ) yet excellent electrical conductivity (σ, 1.3×106 S/m) in comparison with the pure (Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)C. This study provided great potential for maximizing the physical and functional properties of the HEC for various applications.

With the development of multimedia editing technologies, the copyright protection has attacked more attentions. Reversible data hiding (RDH), in which the cover can be recovered losslessly, is an effect method to eliminate embedding distortions. As a typical RDH method, histogram shifting (HS) is used widely. Most existing RDH schemes based on HS usually build sharp histograms by predicting and sorting techniques. To make use of spatial correlations of multimedia, several RDH schemes based on multiple HS (MHS) are proposed to protect copyright, in which some rigid rules are used to build multiple histograms. Against images, videos have more spatial and temple correlations and it is easier to acquire sharper histograms. In this paper, a video MHS scheme based on compression sensing (CS) is proposed. As a linear sensing algorithm, CS can measure macroblock residuals by reducing corrections among pixels to acquire distinguishable macroblock features, while keeping their statistical characteristics immutable. By employing CS, macroblocks with similar characteristics cluster together to formulate multiple histograms. For each of these histograms, data embedding is implemented to reduce shifting distortions by expanding the outermost bins while other bins are unchanged. Experimental results show that the quality of most test videos in our scheme are higher than that in the state-of-art schemes.

Abstract Data hiding aims to embed a secret message into a digital object such as image by slightly modifying the object content without arousing noticeable artefacts. The resultant object containing hidden information will be sent to a desired receiver via some insecure channels, e.g. images transmitted through noisy channel, social networks are vulnerable to unknown pollution or compression by a third party, which may lead the transmitted objects to be attacked such that the reconstructed message has a significant error rate. It therefore requires us to use robust embedding strategies for data hiding to realise reliable message retrieval. To this end, in this paper, a metric model to estimate the robustness of data hiding for noisy transmission based on the statistical characteristics of cover and embedding operation is presented, the former is mainly reflected by spatial frequency and texture feature, and the latter embedding operation is mainly reflected by embedding modification. The goal is to ensure that both statistical characteristics and embedding operation can be used to maximise the embedding robustness. To the best knowledge, it is the first time to estimate robustness before data hiding by a special metric model. Experimental results show that, by combining the proposed metric model in three classical data hiding methods, i.e. BPS, DE and QIM, the robustness can be significantly improved, which demonstrates its superiority and applicability.

In this paper, the insider trading model of Xiao and Zhou (Acta Mathematicae Applicatae, 2021) is further studied, in which market makers receive partial information about a static risky asset and an insider stops trading at a random time. With the help of dynamic programming principle, we obtain a unique linear Bayesian equilibrium consisting of insider's trading intensity and market liquidity parameter, instead of none Bayesian equilibrium as before. It shows that (i) as time goes by, both trading intensity and market depth increase exponentially, while residual information decreases exponentially; (ii) with average trading time increasing, trading intensity decrease, but both residual information and insider's expected profit increase, while market depth is a unimodal function with a unique minimum with respect to average trading time; (iii) the less information observed by market makers, the weaker trading intensity and market depth are, but the more both expect profit and residual information are, which is in accord with our economic intuition.

We report an optimized chemical vapor transport method to grow single crystals of (Mn1−xNix)2P2S6 where x = 0, 0.3, 0.5, 0.7, and 1. Single crystals up to 4 mm × 3 mm × 200 μm were obtained by this method. As-grown crystals are characterized by means of scanning electron microscopy and powder X-ray diffraction measurements. The structural characterization shows that all crystals crystallize in monoclinic symmetry with the space group C2/m (No. 12). We have further investigated the magnetic properties of this series of single crystals. The magnetic measurements of the all as-grown single crystals show long-range antiferromagnetic order along all principal crystallographic axes. Overall, the Néel temperature TN is non-monotonous; with increasing Ni2+ doping, the temperature of the antiferromagnetic phase transition first decreases from 80 K for pristine Mn2P2S6 (x = 0) up to x = 0.5 and then increases again to 155 K for pure Ni2P2S6 (x = 1). The magnetic anisotropy switches from out-of-plane to in-plane as a function of composition in (Mn1−xNix)2P2S6 series. Transport studies under hydrostatic pressure on the parent compound Mn2P2S6 evidence an insulator-metal transition at an applied critical pressure of ~22 GPa.

In recent years, reversible data hiding technology has been widely used in JPEG images for special purposes such as file management and image authentication. Histogram shifting is one of the most popular techniques for achieving reversible data hiding technology. However, invalid shifting in histogram shifting limits the performance of existing reversible data hiding schemes. Therefore, we propose a two-dimensional histogram shifting-based reversible data hiding scheme in this article to improve the performance of marked JPEG images in terms of visual quality and file size. In the proposed histogram shifting method, only the coefficient pairs containing two non-zero quantized discrete cosine transform coefficients are changed for embedding data. Specifically, the coefficient pairs with at least one quantized discrete cosine transform coefficient valued −1 or +1 are shifted and the rests leave room for embedding data. With our proposed reversible data hiding scheme, the number of invalid shifting pixels is reduced so that it improves the performance of marked JPEG images. The experimental results show that the proposed method achieves a higher peak signal-to-noise ratio and has a lower increase in file size than state-of-art methods.

Streptococcus suis (S. suis) can decrease its virulence or modify local conditions through biofilm formation, which promotes infection persistence in vivo. Biofilm formation is an important cause of chronic drug-resistant S. suis infection. The aim of this study was to evaluate whether tylosin effectively inhibits S. suis biofilm formation by interacting with O-acetylserine (thiol)-lyase B (CysM), a key enzymatic regulator of cysteine synthesis. Biofilm formation of the mutant (ΔcysM) strain was significantly lower compared to the wild-type ATCC 700794 strain. Tylosin inhibited cysM gene expression, decreased extracellular matrix contents, and reduced cysteine, homocysteine, and S-adenosylmethionine levels, indicating its potential value as an effective inhibitor of S. suis biofilm formation. Furthermore, using biolayer interferometry technology and fourier-transform infrared spectroscopy, we found that tylosin and CysM could be combined directly. Overall, these results provide evidence that tylosin inhibits S. suis biofilm formation by interacting with CysM.

Abstract Background As a kind of opportunist pathogen, Staphylococcus xylosus (S. xylosus) can cause mastitis. Antibiotics are widely used for treating infected animals and tylosin is a member of such group. Thus, the continuous use of antibiotics in dairy livestock enterprise will go a long way in increasing tylosin resistance. However, the mechanism of tylosin-resistant S. xylosus is not clear. Here, isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics methods was used to find resistance-related proteins. Results We compared the differential expression of S. xylosus in response to tylosin stress by iTRAQ. A total of 155 proteins (59 up-regulated, 96 down-regulated) with the fold-change of >1.2 or

A model of insider trading in continuous time in which a risk-neutral insider possesses long-lived imperfect information on a risk asset is studied. By conditional expectation theory and filtering theory, we turn it into a model with insider knowing complete information about the asset with a revised risky value and deduce its linear Bayesian equilibrium consisting of optimal insider trading strategy and semistrong pricing rule. It shows that, in the equilibrium, as the degree of insider observing the signal of the risky asset value is more and more accurate, market depth, trading intensity, and residual information are all decreasing and the total expectation profit of the insider is increasing and that the information about the asset value incorporated into the equilibrium price, which has nothing to do with the volatility of noise trades, is increasing as time goes by, but not all information of asset value is incorporated into the price in the final disclosed time due to the incompleteness of insider’s observation, though the market depth is still a time-independent constant. Some simulations are illustrated to show these features. However, it is an open question of how to make maximal profit if the insider is risk-averse.

In this paper, we consider the two-dimensional compressible magnetohydrodynamic system with Coulomb force. We apply the method of relative entropy to establish the weak-strong uniqueness property of this system.

In this paper, we study a model of continuous-time insider trading in which noise traders have some memories and the trading stops at a random deadline. By a filtering theory on fractional Brownian motion and the stochastic maximum principle, we obtain a necessary condition of the insider’s optimal strategy, an equation satisfied. It shows that when the volatility of noise traders is constant and the noise traders’ memories become weaker and weaker, the optimal trading intensity and the corresponding residual information tend to those, respectively, when noise traders have no any memory. And, numerical simulation illustrates that if both the trading intensity of the insider and the volatility of noise trades are independent of trading time, the insider’s expected profit is always lower than that when the asset value is disclosed at a finite fixed time; this is because the trading time ahead is a random deadline which yields the loss of the insider’s information.

Staphylococcus xylosus (S. xylosus) is one of the emerging pathogens causing bovine mastitis with high rate of isolation in most of the reported clinical and field cases. To verify the role of glutamine synthetase (GS) in the pathogenesis of S. xylosus, we evaluated the virulence level of the wild-type strain and its glnA mutant strain in biofilm assays in vitro and murine infection model in vivo. From the results, it was observed that the glnA mutant strain was attenuated and could reduce tissue damage. 1-Hydroxyanthraquinone (1-HAQ) is a kind of anthraquinones, it exhibited a significant inhibitory effect on the growth of S. xylosus and biofilm formation in vitro and provided anti-inflammatory effects in vivo. In addition, the rate at which it inhibits the biofilm, inflammatory factors, and CFU of wild-type strains were significantly higher than that of the mutant strains, indicating that 1-hAQ might have pharmacological effects against S. xylosus through the regulation of GS protein. The effect of 1-hAQ on GS was further confirmed by the down-regulation of glnA expression, reduced GS activity, Gln content and the results of molecular docking. Taken together, these findings suggest that 1-hAQ facilitated a significant attenuation of S. xylosus pathogenicity by regulating the GS protein: a vital virulence factor. Therefore, it can be inferred that 1-hAQ may serve as a potential source of organic compound for the development of novel alternative drugs in mitigating the menace of bovine mastitis.

Abstract Transition-metal chalcogenides host various phases of matter, such as charge-density wave (CDW), superconductors, and topological insulators or semimetals. Superconductivity and its competition with CDW in low-dimensional compounds have attracted much interest and stimulated considerable research. Here we report pressure induced superconductivity in a strong spin-orbit (SO) coupled quasi-one-dimensional (1D) transition-metal chalcogenide NbTe4, which is a CDW material under ambient pressure. With increasing pressure, the CDW transition temperature is gradually suppressed, and superconducting transition, which is fingerprinted by a steep resistivity drop, emerges at pressures above 12.4 GPa. Under pressure p = 69 GPa, zero resistance is detected with a transition temperature T c = 2.2 K and an upper critical field μ 0 H c2 = 2 T. We also find large magnetoresistance (MR) up to 102% at low temperatures, which is a distinct feature differentiating NbTe4 from other conventional CDW materials.

Non-alcoholic fatty liver disease (NAFLD), characterized by hepatic steatosis, is one of the most common liver diseases worldwide. So far, no definitive medical treatment has been established to treat NAFLD except for lifestyle medication. Nitzschia laevis extract (NLE), a microalgal extract rich in fucoxanthin, has been previously demonstrated to reduce bodyweight in high-fat-diet (HFD) C57BL/6J mice, indicating potential for prevention of NAFLD. In the present study, we investigated the lipid-lowering effects of NLE in HFD-induced steatosis murine model and palmitate-treated HepG2 cells. The results showed that NLE significantly lowered inguinal fat and attenuated hepatic steatosis in C57BL/6J mice. Especially, NLE significantly prevented lipid accumulation in HepG2 cells. This was probably due to its capability to enhance hepatic mitochondrial function as evidenced by the increased oxygen consumption rate (OCR) and mitochondrial membrane potential (MMP), and repress fatty acid synthesis through phosphorylation of acetyl-CoA carboxylase (ACC). Moreover, fucoxanthin was identified to be responsible for the lipid-lowering effect of NLE. Taken together, NLE or other microalgal fucoxanthin-rich products are promising natural products that may help prevent against NAFLD.

High-pressure physics: transitions and superconductivity of compressed ReS2 ReS2 is a unique transition metal dichalcogenide (TMD) in terms of its distorted low-symmetry structure at ambient conditions. A subject that remains elusive so far is how its structure and electronic properties respond to pressure. Now a collaborative team led by Prof. Jian Sun from Nanjing University looks at the phase transitions in ReS2 under pressure utilizing ab initio crystal structure searching combining with high-pressure electrical resistance measurements. Upon small compression, the ambient phase transforms to a triclinic distorted 1T structure before changing to a tetragonal polymorph at higher pressure. The former transition is due to the layer sliding with a Peierls mechanism governing the energy stabilization and this semiconducting phase would be metallized with increasing pressure. The latter predicted structure is superconducting at a critical temperature of around 2 K at 100 GPa. This work suggests the role of pressure in tailoring the electronic structures of TMDs.

Staphylococcus xylosus (S. xylosus) is a type of coagulase-negative Staphylococcus, which was previously considered as non-pathogenic. However, recent studies have linked it with cases of mastitis in cows. Isoliquiritigenin (ISL) is a bioactive compound with pharmacological functions including antibacterial activity. In this study, we evaluated the effect of ISL on S. xylosus in vitro and in vivo. The MIC of ISL against S. xylosus was 80 μg/mL. It was observed that sub-MICs of ISL (1/2MIC, 1/4MIC, 1/8MIC) significantly inhibited the formation of S. xylosus biofilm in vitro. Previous studies have observed that inhibiting imidazole glycerol phosphate dehydratase (IGPD) concomitantly inhibited biofilm formation in S. xylosus. So, we designed experiments to target the formation of IGPD or inhibits its activities in S. xylosus ATCC 700404. The results indicated that the activity of IGPD and its histidine content decreased significantly under 1/2 MIC (40 μg/mL) ISL, and the expression of IGPD gene (hisB) and IGPD protein was significantly down-regulated. Furthermore, Bio-layer interferometry experiments showed that ISL directly interacted with IGPD protein (with strong affinity; KD = 234 μM). In addition, molecular docking was used to predict the binding mode of ISL and IGPD. In vivo tests revealed that, ISL significantly reduced TNF-α and IL-6 levels, mitigated the destruction of the mammary glands and reversed the production of inflammatory cells in mice. The results of the study suggest that, ISL may inhibit S. xylosus growth by acting on IGPD, which can be used as a target protein to treat infections caused by S. xylosus.

Staphylococcus xylosus, a coagulase-negative, non-pathogenic bacterium, responsible for opportunistic infections in humans and bovine mastitis, has the ability to form biofilms, which are responsible for persistent infections and antibiotic resistance. In our study, azithromycin significantly inhibited biofilm formation by altering protein expression. Of the 1764 proteins measured by the isobaric Tag for Relative and Absolute Quantification (iTRAQ) technique, only 148 proteins showed significantly different expression between the azithromycin-treated and untreated cells. Most ribosomal proteins were markedly up-regulated, and the expression of the proteins involved in histidine biosynthesis, which, in turn, influence biofilm formation, was down-regulated, particularly imidazole glycerophosphate dehydratase (IGPD). Previously, we had observed that IGPD plays an important role in biofilm formation by S. xylosus. Therefore, hisB expression was studied by real-time PCR, and the interactions between azithromycin and IGPD were predicted by molecular docking analysis. hisB was found to be significantly down-regulated, and six bond interactions were observed between azithromycin and IGPD. Many active atoms of azithromycin did not interact with the biologically active site of IGPD. Surface plasmon resonance analysis used to further study the relationship between IGPD and azithromycin showed minimum interaction between them. Histidine content in the azithromycin-treated and untreated groups was determined. We noted a slight difference, which was not consistent with the expression of the proteins involved in histidine biosynthesis. Therefore, histidine degradation into glutamate was also studied, and we found that all proteins were down-regulated. This could be the reason why histidine content showed little change between the treated and untreated groups. In summary, we found that azithromycin is a potential inhibitor of S. xylosus biofilm formation, and the underlying mechanism was preliminarily elucidated in this study.

Streptococcus suis (S. suis) form biofilms and causes severe diseases in humans and pigs. Biofilms are communities of microbes embedded in a matrix of extracellular polymeric substances. Eradicating biofilms with the use of antibiotics or biocides is often ineffective and needs replacement with other potential agents. Compared to conventional agents, promising and potential alternatives are biofilm-inhibiting compounds without impairing growth. Here, we screened a S. suis adhesion inhibitor, rutin, derived from Syringa. Rutin, a kind of flavonoids, shows efficient biofilm inhibition of S. suis without impairing its growth. Capsular polysaccharides(CPS) are reported to be involved in its adherence to influence bacterial biofilm formation. We investigated the effect of rutin on S. suis CPS content and structure. The results showed that rutin was beneficial to improve the CPS content of S. suis without changing its structure. We further provided evidence that rutin specifically affected S. suis biofilm susceptibility by affecting CPS biosynthesis in vitro. The study explores the antibiofilm potential of rutin against S. suis which can be used as an adhesion inhibitor for the prevention of S. suis biofilm-related infections. Nevertheless, rutin could be used as a novel natural inhibitor of biolfilm and its molecular mechanism provide basis for its pharmacological and clinical applications.

S. suis (Streptococcus suis) caused serious disease symptoms in humans and pigs. S. suis is able to form thick biofilms and this increases the difficulty of treatment. After growth with 1/2 MIC of azithromycin, 1/4 MIC of azithromycin, or 1/8 MIC of azithromycin, biofilm formation of S. suis dose-dependently decreased in the present study. Furthermore, scanning electron microscopy analysis revealed the obvious effect of azithromycin against biofilm formation of S. suis. Especially, at two different conditions (1/2 MIC of azithromycin nontreated cells and treated cells), we carried out comparative proteomic analyses of cells by using iTRAQ technology. Finally, the results revealed the existence of 19 proteins of varying amounts. Interestingly, several cell surface proteins (such as ABC superfamily ATP binding cassette transporter (G7SD52), CpsR (K0FG35), Cps1/2H (G8DTL7), CPS16F (E9NQ13), Putative uncharacterized protein (G7SER0), NADP-dependent glyceraldehyde-3-phosphate dehydrogenase (G5L259), Putative uncharacterized protein (G7S2D6), Amino acid permease (B0M0G6) and NsuB (G5L351)) were found to be implicated in biofilm formation. More importantly, we also found that azithromycin affected expression of the genes cps1/2H, cpsR and cps16F. Especially, after growth with 1/2 MIC of azithromycin and 1/4 MIC of azithromycin, the capsular polysaccharide (CP) content of S. suis was significantly higher.

In this study, ITS sequences of the nuclear ribosomal DNA were conducted for six putative species of Orinus (O. alticulmus, O. anomala, O. kokonorica, O. longiglumis, O. thoroldii and O. tibeticus) with 572 individuals from 73 populations. The results found that the six species formed two monophyletic groups: the one (O. anomala Keng ex Keng f. and L. Liou) with O. alticulmus, O. anomala and O. kokonorica, and another (O. thoroldii (Stapfex Hemsl.) Bor) with O. longiglumis, O. thoroldii and O. tibeticus. The taxonomic data from ITS sequences were not congruent with those from morphological characteristics, likely resulting from rapid speciation trigged by the uplifts of the Qinghai-Tibetan Plateau and its adjacent regions and the extensive selection pressure under the alpine environments. The ITS data suggest that the classification of the six species within the genus Orinus should be reduced to two species. We include a complete taxonomic revision of the genus and a key to distinguish the two species. Therefore, it is very necessary to make the comprehensive revision and arrangement of these taxa, strictly regulate the taxa confusion of genus and species order, and do new reports on belonging to the genus taxa.

The public goods game is one of the most famous models for studying the evolution of cooperation in sizable groups. The multiplication factor in this game can characterize the investment return from the public good, which may be variable depending on the interactive environment in realistic situations. Instead of using the same universal value, here we consider that the multiplication factor in each group is updated based on the differences between the local and global interactive environments in the spatial public goods game, but meanwhile limited to within a certain range. We find that the adaptive and bounded investment returns can significantly promote cooperation. In particular, full cooperation can be achieved for high feedback strength when appropriate limitation is set for the investment return. Also, we show that the fraction of cooperators in the whole population can become larger if the lower and upper limits of the multiplication factor are increased. Furthermore, in comparison to the traditionally spatial public goods game where the multiplication factor in each group is identical and fixed, we find that cooperation can be better promoted if the multiplication factor is constrained to adjust between one and the group size in our model. Our results highlight the importance of the locally adaptive and bounded investment returns for the emergence and dominance of cooperative behavior in structured populations.