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Abstract Low-cost, efficient catalyst high-throughput screening is crucial for future renewable energy technology. Interpretable machine learning is a powerful method for accelerating catalyst design by extracting physical meaning but faces huge challenges. This paper describes an interpretable descriptor model to unify activity and selectivity prediction for multiple electrocatalytic reactions (i.e., O2/CO2/N2 reduction and O2 evolution reactions), utilizing only easily accessible intrinsic properties. This descriptor, named ARSC, successfully decouples the atomic property (A), reactant (R), synergistic (S), and coordination effects (C) on the d-band shape of dual-atom sites, which is built upon our developed physically meaningful feature engineering and feature selection/sparsification (PFESS) method. Driven by this descriptor, we can rapidly locate optimal catalysts for various products instead of over 50,000 density functional theory calculations. The model’s universality has been validated by abundant reported works and subsequent experiments, where Co-Co/Ir-Qv3 are identified as optimal bifunctional oxygen reduction and evolution electrocatalysts. This work opens the avenue for intelligent catalyst design in high-dimensional systems linked with physical insights.

IntroductionValeriana amurensis, a tall herbaceous plant, has been traditionally utilized as a herbal remedy both in China and Russia.MethodsThis study was set to explore how to cultivate high quality seedlings, considering factors such as seedling time, seeding density, shading, and plastic film mulching. In addition, we investigated the impact of topping and fertilizer on the growth and quality of V. amurensis.ResultsAccording to the percentage of seed germination, the seeds of V. amurensis were sowed with 0.88 g m-2 density using plastic film mulching from late April to mid-May (germination percentage was more than 30%). The optimal Transplanting time was identified as late September, ensuring a high survival rate of 98%. Generally, topping showed the most improved growth indices in late fruit period (21.87 for number of radical leaves) and withering period (6.50 for number of buds and 234.81 for number of roots). Topping increased the yields of valtrate (10.91 mg per plant), valepotriates (809.51 mg per plant) and essential oil (395.64 mg per plant) in withering period. Nitrogen fertilizer promoted maximum root growth and increased the biomass of V. amurensis. Meanwhile, N fertilizer significantly increased the yields of valtrate to 10.46 mg per plant and valepotriates to 772.32 mg per plant among three types of fertilizers. Seedlings are obtained according to rational sowing factors and transplanting time. Topping and nitrogen fertilization emerge as superior strategies to enhance the growth and medicinal quality of this valuable plant.DiscussionThis study provides actionable insights for the cultivation V. amurensis.

A gallium nitride (GaN) semiconductor is one of the most promising materials integrated into biomedical devices to play the roles of connecting, monitoring, and manipulating the activity of biological components, due to its excellent photoelectric properties, chemical stability, and biocompatibility. In this work, it was found that the photogenerated free charge carriers of the GaN substrate, as an exogenous stimulus, served to promote neural stem cells (NSCs) to differentiate into neurons. This was observed through the systematic investigation of the effect of the persistent photoconductivity (PPC) of GaN on the differentiation of primary NSCs from the embryonic rat cerebral cortex. NSCs were directly cultured on the GaN surface with and without ultraviolet (UV) irradiation, with a control sample consisting of tissue culture polystyrene (TCPS) in the presence of fetal bovine serum (FBS) medium. Through optical microscopy, the morphology showed a greater number of neurons with the branching structures of axons and dendrites on GaN with UV irradiation. The immunocytochemical results demonstrated that GaN with UV irradiation could promote the NSCs to differentiate into neurons. Western blot analysis showed that GaN with UV irradiation significantly upregulated the expression of two neuron-related markers, βIII-tubulin (Tuj-1) and microtubule-associated protein 2 (MAP-2), suggesting that neurite formation and the proliferation of NSCs during differentiation were enhanced by GaN with UV irradiation. Finally, the results of the Kelvin probe force microscope (KPFM) experiments showed that the NSCs cultured on GaN with UV irradiation displayed about 50 mV higher potential than those cultured on GaN without irradiation. The increase in cell membrane potential may have been due to the larger number of photogenerated free charges on the GaN surface with UV irradiation. These results could benefit topical research and the application of GaN as a biomedical material integrated into neural interface systems or other bioelectronic devices.

The experiment for measuring the solar spectrum at different latitudes and altitudes was conducted to obtain a suitable Air Mass Zero (AM0) standard solar cell calibration strategy with high altitude balloon flight calibration method. This is the world’s first acquisition of solar spectrum data at an altitude of 35 km using high-altitude balloon platform. The solar spectrum at the upper boundary of the atmosphere was measured and the spectral distribution was obtained from 20 to 35 km during the ascent. The results show that spectral distribution at 35 km is almost equivalent to that of AM0, the peak irradiance at 35 km is close to that of AM0, and the highest peak of this spectrum is at 450.2 nm. Comparing the results taken at different altitude, the effect of ozone, oxygen and water vapor is clearly seen. The measurement methods and results discussed in this paper can assist in verifying the accuracy of space solar cell calibration using high-altitude balloons. It could also provide a reference for the design of photovoltaic energy systems for near space aircrafts. Finally, the results taken from the launch site may be of use for the air quality monitoring and the design of photovoltaic system used in ground-based solar power generation in the Qinghai-Tibet Plateau.

Lithium-ion (Li-ion) batteries are widely used in such devices as today’s electrical vehicles, consumer electronics, and unmanned aerial vehicles, and will play a key role in the future. Unexpected Li-ion battery abnormities may result in serious inconvenience and enormous replacement costs. Thus, the diagnostic and prognostic methods play important roles in battery replacement scheduling, maintenance strategy development, and battery failure precaution, However, many published methods are unsuitable for both battery capacity and end-of-discharge. In this paper, a hybrid ensemble approach, integrating k-fold cross validation (k-CV) and genetic algorithm with back-propagation neural network (GA-BPNN), is proposed for capacity and end-of-discharge of Li-ion battery prognostics combined with geometrical features. Geometrical features extracted from charge-discharge cycles of Li-ion batteries are set as the inputs of the neural network. K-fold cross validation is introduced to determine the number of BPNN hidden layer neurons, genetic algorithm is used to initialize and optimize the connection weights and thresholds of BPNN. By the critical geometrical feature extraction and the ensemble BPNN model with k-fold cross validation and genetic algorithm, accurate battery capacity and end-of discharge are accomplished, making the proposed model can potentially be used for real-time estimate for the conditions given in this article. The performance of the proposed approach is demonstrated by using actual Li-ion battery data, which is supplied by the NASA Ames Research Center database.

In recent years, semiconductors have aroused great interest in connecting, observing and influencing the behavior of biological elements, and it is possible to use semiconductor-cell compound interfaces to discover new signal transduction in the biological field. Among them, III-V nitride semiconductors, represented by gallium nitride (GaN), are used as substrates to form semiconductor-biology interfaces with cells, providing a platform for studying the effects of semiconductors on cell behavior. The interfaces between GaN substrate and cells play an important role in detecting and manipulating cell behaviors and provide a new opportunity for studying cell behavior and developing diagnostic systems. Hence, it is necessary to understand how the properties of the GaN substrate directly influence the behavior of biological tissues, and to create editable biological interfaces according to the needs. This paper reviews the synergism between GaN semiconductors and biological cells. The electrical properties, persistent photoconductivity (PPC), nanostructures, and chemical functionalization of GaN on the promotion of cell behaviors, such as growth, adhesion, differentiation, and signal transduction, are emphatically introduced. The purpose of this study is to provide guidance to explore the detection and regulation methods of cell behavior based on semiconductors and promote the application of them in the field of bioelectronics, such as biochips, biosensors, and implantable systems.

Bupleurum scorzonerifolium Willd. is a medicinal herb. Its root has a high content of volatile oil (BSVO), which shows a variety of biological activities. Currently, BSVO in the injectable form is used for treating fever in humans and livestock. The yield and quality of volatile oils depends on the developmental stages of plants. However, the changes in BSVO yield and quality during root development in Bupleurum scorzonerifolium and the underlying molecular regulatory mechanisms remain unclear. This knowledge gap is limiting the improvement in the quality of BSVO. In the present study, B. scorzonerifolium root was collected at germinative, vegetative, florescence, fruiting and defoliating stages. The yield of BSVO, metabolic profile of volatile components and transcriptome of root samples at various developmental stages were comprehensively determined and compared. BSVO continuously accumulated from the germinative to fruiting stages, and its level slightly decreased from the fruiting to defoliating stages. A total of 82 volatile components were detected from B. scorzonerifolium root, of which 22 volatiles were identified as differentially accumulated metabolites (DAMs) during the root development. Of these volatiles, fatty acids and their derivatives accounted for the largest proportion. The contents of most major volatiles were highest at the fruiting stage. A large number of differentially expressed genes (DEGs) were detected during B. scorzonerifolium root development, of which 65 DEGs encoded various enzymes and transcription factors regulating the biosynthesis of fatty acids and their derivatives. In further analysis, 42 DEGs were identified to be significantly correlated with DAMs, and these DEGs may be the key genes for the biosynthesis of volatiles. To the best of our knowledge, this is the first study to comprehensively report the changes in the composition and content of volatiles and underlying mechanism during B. scorzonerifolium root development. This study provided important reference for future studies to determine the harvest time of B. scorzonerifolium roots and improve the quality of BSVO.

People’s awareness about nutrition and health is increasing in the world. Plant-based foods, especially medicine-food homologous plants, have been received great attention in recent years, and the main active substances included saponins, flavonoids, polysaccharides and volatile oils. As a starter culture in the traditional and modern fermentation industry, lactic acid bacteria are inherently beneficial microorganisms in the human intestinal tract, and exhibit good biotransformation effects and health benefits. Therefore, lactic acid bacteria with high-safety are selected to ferment and transform medicine-food homologous plant to produce more active substances and improve functional efficacy, which becomes one of the research hotspots. In this paper, the biotransformation effect of lactic acid bacteria on the saponins, flavonoids and polysaccharides in medicine-food homologous plants are mainly discussed and reviewed from the aspects of biotransformation effect and mechanism. This review would provide ideas for the research and product development of medicine-food homologous plants biotransformed by lactic acid bacteria.

Paridis Rhizoma is a natural medicine with strong anti-tumor and anti-inflammatory activities. Our previous research have found that Fusarium sp. C39, an endophytic fungus isolated from Dioscorea nipponica which contains the similar chemical components, significantly increased the steroidal saponins content of Paridis Rhizoma by fermentation. In this study, the inhibitory effects of fermentated Paridis Rhizoma extract (PRE) on liver cancer cells (Hepal-6), cervical cancer cells (Hela), and lung cancer cells (A549) were determined to be stronger than that of the unfermented extract. For discovering the fermentation mechanism of PRE with Fusarium sp. C39, 36 components with obviously quantitative variations were screened out by UPLC-Q/TOF-MS and 53 key genes involved in the metabolic pathways of steroidal saponins were identified by transcriptome. On the basis of comprehensively analyzing information from the metabonomics and transcriptome, it can be speculated that the increase of spirostanol saponins and nuatigenin-type saponins enhanced the inhibitory effect of fermented PRE on cancer cell proliferation. Under the action of glycosidase, glycosyltransferase, oxidoreductases, and genes involved in sterol synthesis, strain C39 achieved the synthesis of diosgenin and the alteration of configurations, sugar chain and substituent of steroidal saponins. The research suggested a microbial transformation approach to increase the resource utilization and activity of Paris polyphylla.

The COVID-19 pandemic has brought more attention to the immune system, the body’s defense against infectious diseases. The immunomodulatory ability of traditional herbal medicine has been confirmed through clinical trial research, and has obvious advantages over prescription drugs due to its high number of potential targets and low toxicity. The active compounds of herbal drugs primarily include polysaccharides, saponins, flavonoids, and phenolics and can be modified to produce new active compounds after lactic acid bacteria (LAB) fermentation. LAB, primary source of probiotics, can produce additional immunomodulatory metabolites such as exopolysaccharides, short-chain fatty acids, and bacteriocins. Moreover, several compounds from herbal medicines can promote the growth and production of LAB-based immune active metabolites. Thus, LAB-mediated fermentation of herbal medicines has become a novel strategy for regulating human immune responses. The current review discusses the immunomodulatory properties and active compounds of LAB fermented herbal drugs, the interaction between LAB and herbal medicines, and changes in immunoregulatory components that occur during fermentation. This study also discusses the mechanisms by which LAB-fermented herbal medicines regulate the immune response, including activation of the innate or adaptive immune system and the maintenance of intestinal immune homeostasis.

Previous research mostly used simplistic measures and limited linguistic features (e.g., personal pronouns, absolutist words, and sentiment words) in a text to identify its author’s psychological states. In this study, we proposed using additional linguistic features, that is, sentiments polarities and emotions, to classify texts of various psychological states. A large dataset of forum posts including texts of anxiety, depression, suicide ideation, and normal states were experimented with machine-learning algorithms. The results showed that the proposed linguistic features with machine-learning algorithms, namely Support Vector Machine and Deep Learning achieved a high level of performance in the detection of psychological state. The study represents one of the first attempts that uses sentiment polarities and emotions to detect texts of psychological states, and the findings may contribute to our understanding of how accuracy may be enhanced in the detection of various psychological states. Significance and suggestions of the study are also offered.

This paper is concerned with the $H_{\infty }$ filtering for Lipschitz nonlinear systems under aperiodically sampled measurements. The developed filter is a hybrid system, whose states undergo a change or reset at sampling instants. The resulting filtering error system is then modelled as a kind of nonlinear impulsive systems. By introducing a time-varying Lyapunov functional candidate, a sufficient condition for the existence of desired filter is derived to ensure the filtering error system asymptotic stability and guarantee an $H_{\infty }$ performance. The optimal $H_{\infty }$ performance and corresponding filter gain matrix can be obtained by solving a convex problem with linear matrix inequalities (LMIs) constrains. Two examples are given to show the effectiveness of the theoretical results, and our results are less conservative than existing ones through comparisons.

This study investigated the relation between psychological states and linguistic features with the case of Virginia Woolf. We analyzed the data from The Diary of Virginia Woolf and Virginia Woolf: Biography by automatic text analysis and statistical analysis, including stepwise multiple regression and Deep Learning algorithm. The results suggested that the significant linguistic features can jointly predict the psychological states of Virginia Woolf, including the emotional value of anger, the absolutist word “everything,” and the total of first-person plural pronouns. In addition, we found that the total use of first-person plural pronouns and the emotional value of anger were negatively related to mental health of Virginia Woolf. While the use of the absolutist word “everything” was positively related to mental health of Virginia Woolf. Meanwhile, we developed a model that can predict the psychological states of Virginia Woolf, with 86.9% accuracy. We discussed the findings and enumerated the limitations of this study at the end of the paper. The results not only complemented previous studies in the understanding of the relation between language and psychological health, but also facilitated timely identification, intervention, and prevention of mental disorders.

This study conducted the solid fermentation process of Dioscorea nipponica using endophytic fungi C39 to determine the changes in the diosgenin concentration. The results revealed that endophytic fungi C39 could effectively biotransform the saponin components in D. nipponica. Moreover, the maximum increase in the diosgenin concentration reached 62.67% in 15 days of solid fermentation. MTT assay results demonstrated that the inhibitory effects of the fermentation drugs on four types of cancer cells (liver cancer cells (HepG2), stomach cancer cells (BGC823), cervical cancer cells (HeLa), and lung cancer cells (A549)) were better than those of the crude drugs obtained from D. nipponica. The chemical composition of the samples obtained before and after the biotransformation of D. nipponica was analyzed by UPLC-Q-TOF-MS. A total of 32 compounds were identified, 21 of which have been reported in Dioscorea saponins and the ChemSpider database and 11 compounds were identified for the first time in D. nipponica. The biotransformation process was inferred based on the variation trend of saponins, which included transformation pathways pertaining to glycolytic metabolism, ring closure reaction, dehydrogenation, and carbonylation. The cumulative findings provide the basis for the rapid qualitative analysis of the saponin components of D. nipponica before and after biotransformation. The 11 metabolites obtained from biotransformation are potential active ingredients obtained from D. nipponica, which can be used to further identify pharmacodynamically active substances.

Background: Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and heterogeneity. Genetic mutations caused by driver genes are important contributors to the formation of the tumor microenvironment. The purpose of this study is to discuss the expression of cancer driver genes in tumor tissues and their clinical value in predicting the prognosis of HCC.Methods: All data were sourced from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) public databases. Differentially expressed and prognostic genes were screened by the expression distribution of the cancer driver genes and their relationship with survival. Candidate genes were subjected to functional enrichment and transcription factor regulatory network. We further constructed a prognostic signature and analyzed the survival outcomes and immune status between different risk groups.Results: Most cancer driver genes are specifically expressed in cancer tissues. Driver genes may influence HCC progression through processes such as transcription, cell cycle, and T-cell receptor-related pathways. Patients in different risk groups had significant survival differences (p < 0.05), and risk scores showed high predictive efficacy (AUC>0.69). Besides, risk subgroups were also associated with multiple immune functions and immune cell content.Conclusion: We confirmed the critical role of cancer driver genes in mediating HCC progression and the immune microenvironment. Risk subgroups contribute to the assessment of prognostic value in different patients and explain the heterogeneity of HCC.

Participation in and opportunities for physical activity (PA) and sports (PA inclusively hereafter) are known to vary across individuals with different social positions. Intersectionality theory may help us to better understand the complex processes of multiple interlocking systems of oppression and privilege shaped by intersections of individuals’ social categories. The objectives of this systematic scoping review were (1) to summarize the findings of articles examining PA claimed operationalization of intersectionality and (2) to identify the scope and gaps pertaining to the operationalization of intersectionality in PA research. A search was conducted in September 2019 in seven electronic databases (e.g., SPORTDiscus, Scopus, Web of Science) for relevant research articles written in English. Key search terms included “intersectionality” AND “physical activity” OR “sport”. Database searches, data screening and extraction, and narrative synthesis were conducted between September 2019 and May 2020. Of 16564 articles identified, 45 articles were included in this review. The majority of included articles used qualitative methods (n = 41), with two quantitative and two mixed-methods articles. The most frequently observed intersectional social position was sex/gender + race/ethnicity (n = 11), followed by sex/gender + race/ethnicity + sexuality (n = 6) and sex/gender + race/ethnicity + religion (n = 6). Most qualitative studies (n = 38) explicitly claimed operationalization of intersectionality as a key theoretical framework, and over half of these studies (n = 27) implicitly used intra-categorical intersectionality. Two quantitative studies were identified which examined a number of intersections simultaneously using inter-categorical intersectionality. Complex processes of individual and social-structural level factors that drive inequalities in PA opportunities and participation could be better elucidated with the operationalization of intersectionality theory. Intersectionality theory may serve as a useful framework in both qualitative and quantitative investigations. Advancement in quantitative intersectionality is critical in order to produce knowledge that could inform more inclusive PA promotion efforts.

ABSTRACT High-throughput amplicon sequencing is a critical tool for studying microbiota; however, it results only in relative abundance data. Thus, changes in absolute abundance of microbiota cannot be determined, which hinders further microbiology research. We have therefore established a gradient internal standard absolute quantification (GIS-AQ) method to overcome this issue, which can simultaneously obtain the absolute abundances of bacteria and fungi. Deviations from the quantitative equations of microbes and internal standards were eliminated through calibration. Compared with traditional quantitative real-time PCR and microscopy quantifications, this method is reliable (R2average = 0.998; P 0.05). The GIS-AQ method can be adapted to any amplicon primer choice (e.g., 336F/806R and ITS3/ITS4), rendering it applicable to ecosystem studies including food, soil, and water samples. Crucially, when using solid-state fermentation samples from various temporal dimensions, the results obtained from the relative and absolute abundance are different. The absolute abundance can be used to study the difference in communities between different samples, and the GIS-AQ method allows this to be done rapidly. Therefore, combining the absolute abundance with relative abundance can accurately reflect the microbiota composition. IMPORTANCE To solve the problem of amplicon sequencing cannot discern the microbiota absolute abundance, we proposed a gradient internal standard absolute quantification method. We used Chinese liquor fermentation as a model system to demonstrate the reliability and accuracy of the method. By comparing the relative and absolute abundances of microbiota in various temporal dimensions, we found dynamic changes in the absolute abundance of communities under various temporal dimensions from the relative abundance. Based on its design principle, this method can be widely applied to different ecosystems. Therefore, we believe that the GIS-AQ method can play an immeasurably useful role in microbiological research.

The 5th member of the Upper Triassic Xujiahe Formation (T3x5) is one of the important targets for terrigenous natural gas exploration in the Xinchang Gas Field in the Western Sichuan Depression, however, the quality of the T3x5 source rocks is poorly studied and the understanding of it is controversial. Studies have been conducted on the development and organic geochemical characteristics of the T3x5 mudstone in the Xinchang Gas Field, and the results indicate that, the T3x5 mudstone in the Xinchang Gas Field display an average thickness of 285.3 m, and the thickness of each submember increases from north to south. The average TOC content, hydrocarbon potential (S1+S2) and chloroform bitumen “A” content of T3x5 mudstone are 2.17%, 2.26 mg/g and 0.264‰, respectively, with the organic abundance mainly reaching the standard of medium source rocks. The kerogen type index (TI) is lower than 0 with the mean δ13C value of −25.0‰, indicating mainly humic and sapropelic-humic types of organic matters. The average vitrinite reflectance (RO) value is 1.17%, indicating the stage after the peak of oil generation. The gas generation intensity of T3x5 mudstone is generally in the range of (3–16) × 108 m3/km2, which suggests the resource basis for the generation of medium-small gas fields. The total amount of natural gas generated by T3x5 mudstone in the Xinchang Gas Field is relatively low, and the generated gas cannot completely displace the water in the formation, therefore, the fullness of gas in the reservoirs is generally low, which causes the simultaneous production of gas and water and the low gas production in the process of production test.

Knowledge gaps exist in how we implement aerobic exercise programs during the early phases post-stroke. Therefore, the objective of this review was to provide evidence-based guidelines for pre-participation screening, mobilization, and aerobic exercise training in the hyper-acute and acute phases post-stroke. In reviewing the literature to determine safe timelines of when to initiate exercise and mobilization we considered the following factors: arterial blood pressure dysregulation, cardiac complications, blood-brain barrier disruption, hemorrhagic stroke transformation, and ischemic penumbra viability. These stroke-related impairments could intensify with inappropriate mobilization/aerobic exercise, hence we deemed the integrity of cerebral autoregulation to be an essential physiological consideration to protect the brain when progressing exercise intensity. Pre-participation screening criteria are proposed and countermeasures to protect the brain from potentially adverse circulatory effects before, during, and following mobilization/exercise sessions are introduced. For example, prolonged periods of standing and static postures before and after mobilization/aerobic exercise may elicit blood pooling and/or trigger coagulation cascades and/or cerebral hypoperfusion. Countermeasures such as avoiding prolonged standing or incorporating periodic lower limb movement to activate the venous muscle pump could counteract blood pooling after an exercise session, minimize activation of the coagulation cascade, and mitigate potential cerebral hypoperfusion. We discuss patient safety in light of the complex nature of stroke presentations (i.e., type, severity, and etiology), medical history, comorbidities such as diabetes, cardiac manifestations, medications, and complications such as anemia and dehydration. The guidelines are easily incorporated into the care model, are low-risk, and use minimal resources. These and other strategies represent opportunities for improving the safety of the activity regimen offered to those in the early phases post-stroke. The timeline for initiating and progressing exercise/mobilization parameters are contingent on recovery stages both from neurobiological and cardiovascular perspectives, which to this point have not been specifically considered in practice. This review includes tailored exercise and mobilization prescription strategies and precautions that are not resource intensive and prioritize safety in stroke recovery.

Intangible cultural heritage is an important part of Chinese excellent traditional culture, and college dance teaching is paid more attention by researchers of physical education and computer technology. In order to help the inheritance and development of non-legacy culture in college dance teaching, this paper analyzes the influencing factors of wireless communication network in college dance teaching, constructs an interactive platform for non-legacy digital dance teaching based on wireless communication network technology, and applies it in the dance teaching process of a university in Henan province to highlight the role of wireless communication technology in dance teaching. The results show that the interactive platform can effectively reduce teachers' physical energy consumption and has certain reliability and practicality. Through artificial intelligence algorithm, the traditional dance teaching method has been changed, and a new exploration of non-legacy dance teaching has been realized.

Background/Aims: The present study aims to explore the protective role and mechanism of ginsenoside Rg1 combined with bone marrow mesenchymal stem cell (BMSC) transplantation for cerebral ischemia reperfusion injury (CIRI) in rat brain. Methods: One hundred twenty male SD rats were randomly divided into a sham group, an Ischemia Reperfusion (IR) group, an IR group treated with BMSC transplantation (IR+BMSCs), an IR group treated with Rg1 (IR+Rg1), and an IR group treated with BMSC transplantation and Rg1 (IR+Rg1+BMSCs). To establish a CIRI model, right middle cerebral artery embolization was used. The neurological score, 2,3,5-triphenyltet-razolium chloride monohydrate (TTC) staining and brain water content were detected to assess the treatment efficiency. HE staining and TUNEL were used to explore the pathologic changes and apoptosis. To explore the protein levels of neuron-specific enolase (NSE) and glial fibrillary acidic protein (GFAP), immunofluoresence was utilized. Western blotting was used to explore apoptosis-related proteins such as Bcl-2 and Bax. Results: Compared with the sham group, the IR group demonstrated obvious ischemic changes, such as significant neurologic defects and enhanced brain water content. The Rg1 treatment resulted in an obvious decrease in cell apoptosis and improved ischemic conditions. By BMSC transplantation, the transplanted cells could be differentiated into neurons and glial cells, which also improved cerebral ischemia. More importantly, the IR+Rg1+BMSCs group showed the best treatment efficiency with reduced cell apoptosis and better cerebral recovery. Conclusions: The Rg1 treatment resulted in an obvious decrease in cell apoptosis, while the transplanted cells could be differentiated into neurons and glial cells, which also improved cerebral ischemia.

We demonstrated a fast switchable dual-model grating based on a polymer-stabilized sphere phase liquid crystal. To form binary periodicity layers, the polymer-stabilized sphere phase liquid crystal precursor was sequence ultraviolet cured at an isotropic and sphere phase. This grating jointly modulated both the phase and the amplitude, had six times the diffraction efficiency of that fabricated with polymer-stabilized blue phase liquid crystal. Moreover, the dual-model tunable grating shown polarization-independent and submillisecond response time, which may hold a great potential application in diffractive optics.