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Objective This study aimed to identify and characterize a novel endo-β-glucanase, IDSGLUC9-4, from the rumen metatranscriptome of Hu sheep. Methods A novel endo-β-glucanase, IDSGLUC9-4, was heterologously expressed in Escherichia coli and biochemically characterized. The optimal temperature and pH of recombinant IDSGLUC9-4 were determined. Subsequently, substrate specificity of the enzyme was assessed using mixed-linked glucans including barley β-glucan and Icelandic moss lichenan. Thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC), matrix assisted laser desorption ionization time of flight mass spectrometry analyses were conducted to determine the products released from polysaccharides and cello-oligosaccharides substrates. Results The recombinant IDSGLUC9-4 exhibited temperature and pH optima of 40°C and pH 6.0, respectively. It exclusively hydrolyzed mixed-linked glucans, with significant activity observed for barley β-glucan (109.59±3.61 μmol/mg min) and Icelandic moss lichenan (35.35±1.55 μmol/mg min). TLC and HPLC analyses revealed that IDSGLUC9-4 primarily released cellobiose, cellotriose, and cellotetraose from polysaccharide substrates. Furthermore, after 48 h of reaction, IDSGLUC9-4 removed most of the glucose, indicating transglycosylation activity alongside its endo-glucanase activity. Conclusion The recombinant IDSGLUC9-4 was a relatively acid-resistant, mesophilic endo-glucanase (EC 3.2.1.4) that hydrolyzed glucan-like substrates, generating predominantly G3 and G4 oligosaccharides, and which appeared to have glycosylation activity. These findings provided insights into the substrate specificity and product profiles of rumen-derived GH9 glucanases and contributed to the expanding knowledge of cellulolytic enzymes and novel herbivore rumen enzymes in general.

Abstract Background Health lifestyles exert a substantial influence on the quality of everyday life, primarily affecting health maintenance and enhancement. While health-related practices during the COVID-19 pandemic may have positively altered the health lifestyles of Canadians to a certain degree, government reports indicate that issues related to health behaviors, such as cigarette smoking, physical inactivity, and alcohol consumption, continue to pose challenges to the health of Canadians. Social determinants of these health behaviors thus hold significant academic value in the formulation of policy guidelines. Objective The aim of this study is to scrutinize the social determinants of health with respect to social factors that have may have impacts on the health-related behaviors of Canadians. We tested health behaviors including cigarette use, alcohol consumption, and participation in physical exercise, which are integral to the promotion and improvement of individual health. Methods To examine the social determinants of Canadians’ health lifestyles, we utilized nationally representative data from the 2017–2018 Canadian Community Health Survey annual component. Our data analysis involved the bootstrapping method with two-level mixed-effect logistic regressions, ordered logistic regressions, and negative binomial regressions. Additionally, we conducted several robustness checks to confirm the validity of our findings. Results The findings show that demographic background, socioeconomic status, social connections, and physical and mental health conditions all play a role in Canadians’ smoking, physical activity, and drinking behaviors. Noticeably, the association patterns linking to these social determinants vary across specific health lifestyles, shedding light on the complex nature of the social determinants that may influence young and middle-aged Canadians’ health lifestyles. Moreover, in the context of Canada, the health-region level demographic, socioeconomic, and working conditions are significantly linked to residents’ health lifestyles. Conclusions Investigating the social determinants of health lifestyles is pivotal for policymakers, providing them with the necessary insights to create effective interventions that promote healthy behaviors among specific demographic groups. It is recommended that health education and interventions at the community level targeting smoking, physical inactivity, and alcohol consumption be introduced. These interventions should be tailored to specific subgroups, considering their demographic and socioeconomic characteristics, social networks, and health status. For instance, it is imperative to focus our attention on individuals with lower educational attainment and socioeconomic status, particularly in relation to their smoking habits and physical inactivity. Conversely, interventions aimed at addressing alcohol consumption should be targeted towards individuals of a higher socioeconomic status. This nuanced approach allows for a more effective and tailored intervention strategy.

In this study, aiming at fulfilling the requirement of polarization acquisition and utilization, a method for active deception jamming recognition based on the time-varying polarization-conversion metasurface is investigated. First, an anisotropic phase-modulated metasurface supporting 3-bit phase quantization in the 9.6～10.1 GHz frequency band is designed. By optimizing the periodical phase coding, the polarization state can be converted on demand. And then, loading the polarization-conversion metasurface on a single polarization radar antenna so that the polarization states of the antenna can change along a specific trajectory. By extracting the difference in the polarization domain between target and active deception jamming, the active deception jamming could be distinguished from the radar echo. The simulation results show that under the constraints of three different polarization trajectories, the active deception jamming and targets exhibit a significant clustering effect, and the identification effect is stable. Compared with jamming identification methods that rely on dual-polarization or full-polarization radar systems, the proposed method has both low cost and high efficiency, which has great application potential in radar anti-jamming.

Abstract Background In plants, the leaf functions as a solar panel, where photosynthesis converts carbon dioxide and water into carbohydrates and oxygen. In soybean, leaf type traits, including leaf shape, leaf area, leaf width, and leaf width so on, are considered to be associated with yield. In this study, we performed morphological characterization, transcriptome analysis, and endogenous hormone analysis of a rolled and narrow leaf mutant line (rl) in soybean. Results Compared with wild type HX3, mutant line rl showed rolled and narrower leaflet, and smaller leaf, meanwhile rl also performed narrower pod and narrower seed. Anatomical analysis of leaflet demonstrated that cell area of upper epidermis was bigger than the cell area of lower epidermis in rl, which may lead rolled and narrow leaf. Transcriptome analysis revealed that several cytokinin oxidase/dehydrogenase (CKX) genes (Glyma.06G028900, Glyma.09G225400, Glyma.13G104700, Glyma.14G099000, and Glyma.17G054500) were up-regulation dramatically, which may cause lower cytokinin level in rl. Endogenous hormone analysis verified that cytokinin content of rl was lower. Hormone treatment results indicated that 6-BA rescued rolled leaf enough, rescued partly narrow leaf. And after 6-BA treatment, the cell area was similar between upper epidermis and lower epidermis in rl. Although IAA content and ABA content were reduced in rl, but exogenous IAA and ABA didn’t affect leaf type of HX3 and rl. Conclusions Our results suggest abnormal cytokinin metabolism caused rolled and narrow leaf in rl, and provide valuable clues for further understanding the mechanisms underlying leaf development in soybean.

Abstract Oxytetracycline (OTC) and ciprofloxacin (CIP) contamination have caused serious risks to human health, and modified biochar is considered as a potential adsorbent for their removal. The typical agricultural waste of cotton husk was used as the feedstock, then was combined with γ-Fe2O3 and ball milling to innovatively synthesize nano zero-valent iron (nZVI) supporting magnetic cotton hush-derived biochar (Fe2O3@BMBC) by reductive calcination. Fe2O3@BMBC performed excellent adsorption performance with a maximum adsorption capacity for OTC (266.7 mg·g−1) and CIP (83.36 mg·g−1), and its adsorption capacity was 1.6 and 2.3 times that of cotton husk biochar (BC). Characterization analysis showed that Fe2O3@BMBC contained abundant oxygenated functional groups (e.g., -OH, C = O and Fe–O) and its surface was covered by diverse iron oxides. The high magnetization sensitivity of Fe2O3@BMBC guaranteed that it was easily to be separated by a magnet. Oxygenated functional groups (e.g., -OH, C = O and Fe–O) participated in the adsorption process, and solution pH significantly affected the adsorption behaviour, and pseudo-second-order model and Freundlich model better fitting the kinetics and isotherms data. These results confirmed that π-π conjugation, H-bonding, Fe–O complexation and electrostatic interactions contributed to the greater adsorption capacity of Fe2O3@BMBC. Ethanol + ultrasound could efficiently regenerate the used Fe2O3@BMBC and maintain its sustainable adsorption performance for OTC and CIP. Additionally, Fe2O3@BMBC performed a good environmental security in a wide pH range (from 3 to 11) in view of the low leaching risk of Fe. Graphical Abstract

Infrastructure and economic networks can be used to describe different dimensions of urban systems, and a close relationship exists between them. Therefore, it is important to study the dynamic coupling relationship between them to promote the formation and development of urban networks. Relevant studies have compared and analyzed the evolution characteristics of urban network structures from different dimensions; however, relatively few studies have focused on the dynamic coupling relationship between high-speed rail and remote investment networks. The formation and development of high-speed rail networks has become a key factor affecting remote investment networks, and the layout of a remote investment network also affects the development of a high-speed rail network. To this end, we used high-speed railway operation service data and related transaction data of listed companies from 2008 to 2023 to construct high-speed railway and remote investment networks reflecting intercity high-speed railway and enterprise remote investment connections, respectively. QAP correlation analysis was used to explore the overall correlation between the two networks. Using the quadrantal diagram method and the coupling coordination degree model, we discuss the spatiotemporal coupling coordination of the two networks, identify the types of cities and urban connections, and propose operational planning suggestions for cities and high-speed railways. The results indicate the following: 1) Both the scale and density of the high-speed rail network and the off-site investment network show a rapid growth trend, and the expansion of the high-speed rail network is significantly faster than that of the off-site investment network. There is a significant positive correlation between high-speed rail and the remote investment network as a whole, and the degree of correlation first increases and then decreases. 2) In terms of space, cities with the simultaneous development of high-speed rail and remote investment networks are primarily concentrated in the administrative and economic centers of the eastern region. However, cities with lagging high-speed rail networks are mainly located in non-transportation hub cities in the economically developed areas of the Pearl River Delta, Dalian, and Urumqi. Moreover, cities with advanced high-speed rail networks are mainly centered in the central and eastern regions around the main high-speed rail lines. 3) Cities with synchronous development of high-speed rail and remote investment networks are mainly located in developed cities within the five major urban agglomerations. The pairs of cities with lagging high-speed rail networks are mainly located between the core cities of different urban agglomerations. Pairs of cities with advanced high-speed rail networks are typically positioned between cities that are closer together and contain at least one city with a less developed economy. The relevant research results can provide policy support for China's high-speed rail operation planning and urban system construction.

Abstract The cold tolerance of Litopenaeus vannamei is important for breeding in specific areas. To explore the cold tolerance mechanism of L. vannamei, this study analyzed biochemical indicators, cell apoptosis, and metabolomic responses in cold-tolerant (Lv-T) and common (Lv-C) L. vannamei under low-temperature stress (18 °C and 10 °C). TUNEL analysis showed a significant increase in apoptosis of hepatopancreatic duct cells in L. vannamei under low-temperature stress. Biochemical analysis showed that Lv-T had significantly increased levels of superoxide dismutase (SOD) and triglycerides (TG), while alanine aminotransferase (ALT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH-L), and uric acid (UA) levels were significantly decreased compared to Lv-C (p

Abstract Purpose To investigate the associations between the most popular social media platform WeChat usage and cognitive performance among the middle-aged and older Chinese population using data from a nationally representative survey. Methods In total, 17,472 participants (≥ 45 years old) from the China Health and Retirement Longitudinal Study (CHARLS, Wave 4, 2018) were analyzed. Cognitive performance including episodic memory and executive function was assessed using Mini-Mental Status Examination (MMSE). Other confounding variables included socio-economic characteristics, medical status, and lifestyle-related information. Multiple linear regression models were used to test the association between cognitive performance and WeChat usage by introducing covariates hierarchically. Subgroup analyses of age and gender were conducted to estimate the robustness of the primary findings. Results After adjusting for multiple confounders across all linear models, WeChat usage is significantly associated with executive function, episodic memory, and global cognitive performance (all p values

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic effects. The primary challenge is to integrate diverse pharmacophores within a single-molecule framework. To address this, we introduced DeepSA, a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine, a well-known local anesthetic. DeepSA integrates deep neural networks into metaheuristics, effectively constraining molecular space during compound generation. This framework employs a sophisticated objective function that accounts for scaffold preservation, anti-inflammatory properties, and covalent constraints. Through a sequence of local editing to navigate the molecular space, DeepSA successfully identified AT-17, a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal models. Mechanistic insights into AT-17 revealed its dual mode of action: selective inhibition of NaV1.7 and 1.8 channels, contributing to its prolonged local anesthetic effects, and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome pathway. These findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery, particularly within stringent chemical constraints.