Metagenomic sequencing revealed the regulative effect of Danshen and Honghua herb pair on the gut microbiota in rats with myocardial ischemia injury.

In recent years, more and more evidence has shown that the disorder of gut microbiota (GM) is closely correlated with myocardial ischemia (MI). Even though the Danshen and Honghua herb pair (DHHP) is widely used in treating cardiovascular disease in China and exhibits obvious clinical efficacy on MI, the anti-MI mechanism of DHHP remains and needs to be explored in depth. Thus, in this study, we investigated whether the amelioration effect and molecular mechanism of DHHP on MI were related to regulating GM through pharmacodynamics evaluation and metagenomic sequencing. Histopathological testing results showed that DHHP treatment could alleviate the pathological changes of myocardial tissue in the acute MI (AMI) rats induced by isoproterenol (ISO), especially structural disorder, irregular distribution, and enlargement of the myocardial space. These pathological changes were all alleviated to some extent by DHHP treatment. Biochemical analysis results suggested that compared with the control group, the serum levels of AST, CTn-I, CK-MB, and TNF-α in model group rats were notably decreased, and the CAT and SOD levels in serum were markedly increased. These abnormal trends were significantly reversed by DHHP treatment. Furthermore, metagenomic sequencing analysis results indicated that DHHP could improve disorders in the composition and function of GM in AMI rats, mainly reflected in increasing diversity and richness, and obviously enhancing the abundance of Bacteroides fluxus, B. uniformis, B. stercoris, Roseburia hominis, Schaedlerella arabinosiphila, and R. intestinalis, and reducing the abundance of Enterococcus avium and E. canintestini, which were associated with purine metabolism, tyrosine metabolism, cyanoamino acid metabolism, and glutathione metabolism. In conclusion, DHHP may attenuate ISO-induced MI by regulating the structure, composition, and function of GM, thus contributing to further our understanding of the anti-MI mechanisms of DHHP and providing new therapeutic ideas and diagnostic targets for the clinical studies of MI.

Enhancing Spns2/S1P in macrophages alleviates hyperinflammation and prevents immunosuppression in sepsis.

Sepsis is a leading cause of in-hospital mortality resulting from a dysregulated response to infection. Novel immunomodulatory therapies targeting macrophage metabolism have emerged as an important focus for current sepsis research. However, understanding the mechanisms underlying macrophage metabolic reprogramming and how they impact immune response requires further investigation. Here, we identify macrophage-expressed Spinster homolog 2 (Spns2), a major transporter of sphingosine-1-phosphate (S1P), as a crucial metabolic mediator that regulates inflammation through the lactate-reactive oxygen species (ROS) axis. Spns2 deficiency in macrophages significantly enhances glycolysis, thereby increasing intracellular lactate production. As a key effector, intracellular lactate promotes pro-inflammatory response by increasing ROS generation. The overactivity of the lactate-ROS axis drives lethal hyperinflammation during the early phase of sepsis. Furthermore, diminished Spns2/S1P signaling impairs the ability of macrophages to sustain an antibacterial response, leading to significant innate immunosuppression in the late stage of infection. Notably, reinforcing Spns2/S1P signaling contributes to balancing the immune response during sepsis, preventing both early hyperinflammation and later immunosuppression, making it a promising therapeutic target for sepsis.

Low-Grade Waste Heat Enables Over 80 L m- 2 h-1 Interfacial Steam Generation Based on 3D Superhydrophilic Foam.

Clean water scarcity and energy shortage have become urgent global problems due to population growth and human industrial development. Low-grade waste heat (LGWH) is a widely available and ubiquitous byproduct of human activities worldwide, which can provide effective power to address the fresh water crisis without additional energy consumption and carbon emissions. In this regard, 3D superhydrophilic polyurethane/sodium alginate (PU/SA) foam and LGWH-driven interfacial water evaporation systems are developed, which can precipitate over 80 L m-2  h-1 steam generation from seawater and has favorable durability for purification of high salinity wastewater. The excellent water absorption ability, unobstructed water transport, and uniform thin water layer formed on 3D skeletons of PU/SA foam ensure the strong heat exchange between LGWH and fluidic water. As a result, the heat-localized PU/SA foam enables the efficient energy utilization and ultrafast water evaporation once LGWH is introduced into PU/SA foam as heat flow. In addition, the precipitated salt on PU/SA foam can be easily removed by mechanical compression, and almost no decrease in water evaporation rate after salt precipitation and removal for many times. Meanwhile, the collected clean water has high rejection of ions of 99.6%, which meets the World Health Organization (WHO) standard of drinking water. Above all, this LGWH-driven interfacial water evaporation system presents a promising and easily accessible solution for clean water production and water-salt separation without additional energy burden for the society.

The impact of COVID-19 on the employment status and psychological expectations of college graduates: Empirical evidence from the survey data of Chinese recruitment websites.

Based on the big data and survey data of online recruitment platform, this paper empirically tests the impact of COVID-19 on the employment status and psychological expectations of college graduates. The results show that: under the impact of COVID-19 epidemic, both supply and demand sides of college graduates' employment market are affected, such as the decline of recruitment demand, the rise of the employment supply, and the obvious decrease of employment market prosperity. The impacts of COVID-19 epidemic on college graduates' employment status and psychological expectation in different cities are heterogeneous. In the short term, the epidemic has a negative impact on the employment of graduates, but the employment situation is gradually improving with the support of national policies. Under the influence of COVID-19 epidemic, graduates will change their employment location and expected salary, and they tend to choose "temporary non-employment," and their proportions of getting offers and signing contracts are significantly reduced. This paper suggests: Firstly, we should continue to push forward the action plan of "expanding jobs in graduation season to promote employment," and strengthen the persistence and permanence of employment promotion policies for college graduates; Secondly, encourage college students to change their employment concept and rationally adjust their employment expectations; Thirdly, to promote the development of flexible employment of college graduates, it is necessary to strengthen the propaganda of flexible employment, so that students can understand relevant policies; Fourthly, strengthen employment guidance services for graduates from poor families to ensure the continuity and stability of employment assistance policies.

Transfer learning enhanced water-enabled electricity generation in highly oriented graphene oxide nanochannels.

Harvesting energy from spontaneous water flow within artificial nanochannels is a promising route to meet sustainable power requirements of the fast-growing human society. However, large-scale nanochannel integration and the multi-parameter coupling restrictive influence on electric generation are still big challenges for macroscale applications. In this regard, long-range (1 to 20 cm) ordered graphene oxide assembled framework with integrated 2D nanochannels have been fabricated by a rotational freeze-casting method. The structure can promote spontaneous absorption and directional transmission of water inside the channels to generate considerable electric energy. A transfer learning strategy is implemented to address the complicated multi-parameters coupling problem under limited experimental data, which provides highly accurate performance optimization and efficiently guides the design of 2D water flow enabled generators. A generator unit can produce ~2.9 V voltage or ~16.8 µA current in a controllable manner. High electric output of ~12 V or ~83 µA is realized by connecting several devices in series or parallel. Different water enabled electricity generation systems have been developed to directly power commercial electronics like LED arrays and display screens, demonstrating the material's potential for development of water enabled clean energy.

A Machine-Learning-Enhanced Simultaneous and Multimodal Sensor Based on Moist-Electric Powered Graphene Oxide.

Simultaneous multimodal monitoring can greatly perceive intricately multiple stimuli, which is important for the understanding and development of a future human-machine fusion world. However, the integrated multisensor networks with cumbersome structure, huge power consumption, and complex preparation process have heavily restricted practical applications. Herein, a graphene oxide single-component multimodal sensor (GO-MS) is developed, which enables simultaneous monitoring of multiple environmental stimuli by a single unit with unique moist-electric self-power supply. This GO-MS can generate a sustainable moist-electric potential by spontaneously adsorbing water molecules in air, which has a characteristic response behavior when exposed to different stimuli. As a result, the simultaneous monitoring and decoupling of the changes of temperature, humidity, pressure, and light intensity are achieved by this single GO-MS with machine-learning (ML) assistance. Of practical importance, a moist-electric-powered human-machine interaction wristband based on GO-MS is constructed to monitor pulse signals, body temperature, and sweating in a multidimensional manner, as well as gestures and sign language commanding communication. This ML-empowered moist-electric GO-MS provides a new platform for the development of self-powered single-component multimodal sensors, showing great potential for applications in the fields of health detection, artificial electronic skin, and the Internet-of-Things.

Sunlight-Coordinated High-Performance Moisture Power in Natural Conditions.

It is a challenge to spontaneously harvest multiple clean sources from the environment for upgraded energy-converting systems. The ubiquitous moisture and sunlight in nature are attractive for sustainable power generation especially. A high-performance light-coordinated "moist-electric generator" (LMEG) based on the rational combination of a polyelectrolyte and a phytochrome is herein developed. By spontaneous adsorption of gaseous water molecules and simultaneous exposure to sunlight, a piece of 1 cm2 composite film offers an open-circuit voltage of 0.92 V and a considerable short-circuit current density of up to 1.55 mA cm-2 . This record-high current density is about two orders of magnitude improvement over that of most conventional moisture-enabled systems, which is caused by moisture-induced charge separation accompanied with photoexcited carrier migration, as confirmed by a dynamic Monte Carlo device simulation. Flexible devices with customizable size are available for large-scale integration to effectively work under a wide range of relative humidity (about 20-100%), temperature (10-80 °C), and light intensity (30-200 mW cm-2 ). The wearable and portable LMEGs provide ample power supply in natural conditions for indoor and outdoor electricity-consuming systems. This work opens a novel avenue to develop sustainable power generation through collecting multiple types of natural energy by a single hybrid harvester.

Maximization of Spatial Charge Density: An Approach to Ultrahigh Energy Density of Capacitive Charge Storage.

Capacitive energy storage has advantages of high power density, long lifespan, and good safety, but is restricted by low energy density. Inspired by the charge storage mechanism of batteries, a spatial charge density (SCD) maximization strategy is developed to compensate this shortage by densely and neatly packing ionic charges in capacitive materials. A record high SCD (ca. 550 C cm-3 ) was achieved by balancing the valance and size of charge-carrier ions and matching the ion sizes with the pore structure of electrode materials, nearly five times higher than those of conventional ones (ca. 120 C cm-3 ). The maximization of SCD was confirmed by Monte Carlo calculations, molecular dynamics simulations, and in situ electrochemical Raman spectroscopy. A full-cell supercapacitor was further constructed; it delivers an ultrahigh energy density of 165 Wh L-1 at a power density of 150 WL-1 and retains 120 Wh L-1 even at 36 kW L-1 , opening a pathway towards high-energy-density capacitive energy storage.

sPortfolio: Stratified Visual Analysis of Stock Portfolios.

Quantitative Investment, built on the solid foundation of robust financial theories, is at the center stage in investment industry today. The essence of quantitative investment is the multi-factor model, which explains the relationship between the risk and return of equities. However, the multi-factor model generates enormous quantities of factor data, through which even experienced portfolio managers find it difficult to navigate. This has led to portfolio analysis and factor research being limited by a lack of intuitive visual analytics tools. Previous portfolio visualization systems have mainly focused on the relationship between the portfolio return and stock holdings, which is insufficient for making actionable insights or understanding market trends. In this paper, we present s Portfolio, which, to the best of our knowledge, is the first visualization that attempts to explore the factor investment area. In particular, sPortfolio provides a holistic overview of the factor data and aims to facilitate the analysis at three different levels: a Risk-Factor level, for a general market situation analysis; a Multiple-Portfolio level, for understanding the portfolio strategies; and a Single-Portfolio level, for investigating detailed operations. The system's effectiveness and usability are demonstrated through three case studies. The system has passed its pilot study and is soon to be deployed in industry.

Moist-electric generation.

The exploration of green and clean energy could solve the increasingly serious problems of environmental pollution and energy crisis on the Earth. Moist air is ubiquitous around the world, which particulalrly has huge chemical potential energy because of the gaseous state of the water molecules. Recently, our group demonstrated direct electricity generation by the interactions between moisture and various functional materials, which opened a window for the utilization of moisture power. This has led to an upsurge in studies on moist-electric generation (MEG). In this minireview, we provide a brief and systematic discussion on MEG from its working mechanism to practical applications and, the recent progress in advanced materials. The current challenges and the potential trends in MEG are also outlined to guide the design and synthesis of high-performance MEG devices in the future.

(111) Facets-Oriented Au-Decorated Carbon Nitride Nanoplatelets for Visible-Light-Driven Overall Water Splitting.

Development of a simple and stable photocatalyst for overall water splitting is a promising avenue for solar energy conversion. Here, carbon nitride (CN) nanosheet panels decorated with in situ-formed (111) facets-oriented Au nanoparticles (AuNPs) have been prepared by vapor-deposition polymerization followed by an easy immersion technique. Benefiting from the enhanced visible light absorption, the surface plasmon resonance effect of AuNPs, rapid transportation and separation of charge carriers, as well as better-aligned valence band levels, the as-obtained photocatalyst shows effective overall water splitting with stoichiometric H2 and O2 evolution even without any sacrificial agent, distinct from the half-reaction of Pt-decorated CN. This work opens up a brand-new route for facet self-selective growth of metal on two-dimensional conjugated carbon nitride materials, which has been demonstrated to be effective for artificial photosynthesis applications.

Wall-Mesoporous Graphitic Carbon Nitride Nanotubes for Efficient Photocatalytic Hydrogen Evolution.

Graphitic carbon nitride (g-CN) has attracted tremendous attention as visible-light photocatalyst. However, for further improving the catalytic activity, multilevel and hierarchical nanostructuring of g-CN is highly desirable to effectively expose active sites and facilitate separation and migration of photoexciteded charge carriers for largely enhanced photocatalytic behavior. Here, we prepare wall-mesoporous graphitic carbon nitride nanotubes (g-CNNTs) by in situ annealing of urea microrod arrays preformed in virtue of a vertical gradient freeze growth (VGFG) method. Benefiting from the distinctive structural features, the hierarchical g-CNNTs exhibit a high photocatalytic H2 production rate of 8789 µmol h-1 g-1 with an excellent apparent quantum yield of 6.3 % under visible-light irradiation and long-term cycling stability. This work provides a facile and eco-friendly strategy to prepare a new type of carbon nitride-based nanostructural material for photocatalysis and environmental remediation.