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Nervonic acid (NA) is an important long-chain monounsaturated fatty acid found in mammalian nervous tissue. It has recently garnered research attention due to its therapeutic potential in treating psychiatric and neurodegenerative disorders. In this study, we investigated the efficacy of NA in treating ischemia/reperfusion and poststroke events in a rat model. Specifically, there was significant reduction in the infarct area, cell death, and neuronal swelling after NA treatment, and the improvement in cerebral blood flow was also observed on day five after middle cerebral artery occlusion. Moreover, NA treatment led to the upregulation of brain-derived neurotrophic factors and myelin basic protein genes. NA displayed improved effects on depressive-like behavior of rats by three validated assays—the sucrose preference test, open-field test, and forced swim test. Regarding the mechanism of action, direct supplementation of NA in the brain was observed. We also observed the indirect effects of NA on the gut microbiota. Notably, the NA group gradually restored the bacterial diversity and the EGb group exhibited no impact based on observed-out analysis. We found an increase in the abundance of Blautia and Sutterella, which participated in phenylalanine metabolism. The metabolomics of plasma and brain samples revealed a decrease in the levels of phenylalanine-based amino acids, which alleviated the inhibitory effects on glutamine metabolism and promoted the recovery and signaling transmission of neurons after stroke. Altogether, our findings suggest that NA can be a viable treatment option for alleviating stroke and its associated poststroke depressive-like behaviors.

In response to the compliant tracking of surgical intent and adherence to safety range constraints in semi-active knee arthroplasty robots, a model predictive impedance control (MPIC) algorithm is proposed. First, to enhance this algorithm’s operational efficiency, the Stirling interpolation method is employed to linearize the dynamics model of the robotic arm as the predictive model. This method offers computational simplicity and high-precision solving accuracy. Second, based on the impedance model, the force-compliant control mechanism is used to identify the surgeon’s force intention, thereby generating the desired motion trajectory for the robotic arm. To facilitate programming implementation, the impedance model is discretized. Third, leveraging the rolling optimization and feedback correction properties of model predictive control, a virtual state enhancement is designed to improve the explicit constraint handling capability of the MPIC algorithm. This enhancement addresses the infeasibility issues encountered by traditional model predictive control near state constraint boundaries in practical applications. Transforming the model predictive problem into a quadratic programming problem reduces the difficulty of solving the model predictive problem and increases problem-solving speed. Finally, MPIC is integrated as the lower-level position-tracking controller for the robotic arm, with the impedance model serving as the upper-level task planning controller, thus forming the MPIC controller. Comparative experiments with three-loop PID (Proportional integral derivative) control are conducted on the ROKAE seven-axis collaborative robot experimental platform, confirming that the MPIC algorithm achieves better trajectory tracking accuracy and response speed, effectively realizing the desired impedance dynamics and yielding superior compliance. Additionally, further validation is conducted by installing a six-axis force sensor between the end-effector and the wrist of the robotic arm to measure human–robot interaction forces, confirming that the MPIC algorithm exhibits better compliance than traditional position-tracking control methods. Drag experiments are designed to verify the active constraint effect of MPIC on mechanically coupled robotic arms with complex system parameter structures, demonstrating that the control algorithm can actively constrain the motion of the robotic arm when it is manually manipulated to exceed the set state constraint range. Overall, the MPIC algorithm achieves better compliance and meets the safety requirements for knee arthroplasty surgery compared to traditional three-loop PID control methods. This advancement holds promise for further development and adoption of semi-active surgical robots, reducing the complexity of using surgical robots as surgeons and accelerating the widespread adoption of domestically produced surgical robots in hospitals. This paper should promote the practical application of semi-active surgical robots.

Abstract Background Using event-related potentials (ERPs), we aimed to investigate audiovisual integration neural mechanisms during a letter identification task in the left and right sides. Unimodal (A,V) and bimodal (AV) stimuli were presented on either side, with ERPs from unimodal (A,V) stimuli on the same side being compared to those from simultaneous bimodal stimuli (AV). Non-zero results of the AV-(A + V) difference waveforms indicated audiovisual integration on the left/right side. Results When spatially coherent AV stimuli were presented on the right side, two significant ERP components in the integrated differential wave were noted. The N134 and N262, present in the first 300 ms of the AV-(A + V) integration difference wave, indicated significant audiovisual integration effects. However, when these stimuli were presented on the left side, there were no significant integration components. This audiovisual integration difference may stem from left/right asymmetry of cerebral hemisphere language processing. Conclusions Audiovisual letter information presented on the right side was easier to integrate, process, and represent. Additionally, only one significant integrative component peaked at 140 ms in the parietal cortex for spatially non-coherent AV stimuli and provided audiovisual multisensory integration, which could be attributed to some integrative neural processes that depend on the spatial congruity of the auditory and visual stimuli.

Abstract Parkinson’s disease (PD) is the second largest group of neurodegenerative diseases, and its existing drug treatments are not satisfactory. Natural cell membrane drugs are used for homologous targeting to enhance efficacy. In this study, microfluidic electroporation chip prepared mesenchymal stem cell-derived neuron-like cell membrane-coated curcumin PLGA nanoparticles (MM-Cur-NPs) was synthesized and explored therapeutic effect and mechanism in PD. MM-Cur-NPs can protect neuron from damage, restore mitochondrial membrane potential and reduce oxidative stress in vitro. In PD mice, it also can improve movement disorders and restore damaged TH neurons. MM-Cur-NPs was found to be distributed in the brain and metabolized with a delay within 24 h. After 1 h administration, MM-Cur-NPs were distributed in brain with a variety of neurotransmitters were significantly upregulated, such as dopamine. Differentially expressed genes of RNA-seq were enriched in the inflammation regulation, and it was found the up-expression of anti-inflammatory factors and inhibited pro-inflammatory factors in PD. Mechanically, MM-Cur-NPs can not only reduce neuronal apoptosis, inhibit the microglial marker IBA-1 and inflammation, but also upregulate expression of neuronal mitochondrial protein VDAC1 and restore mitochondrial membrane potential. This study proposes a therapeutic strategy provide neuroprotective effects through MM-Cur-NPs therapy for PD.

Abstract Tissue engineered heart valves (TEHVs) demonstrates the potential for tissue growth and remodel, offering particular benefit for pediatric patients. A significant challenge in designing functional TEHV lies in replicating the anisotropic mechanical properties of native valve leaflets. To establish a biomimetic TEHV model, we employed melt-electrowriting (MEW) technology to fabricate an anisotropic PCL scaffold. By integrating the anisotropic MEW-PCL scaffold with bioactive hydrogels (GelMA/ChsMA), we successfully crafted an elastic scaffold with tunable mechanical properties closely mirroring the structure and mechanical characteristics of natural heart valves. This scaffold not only supports the growth of valvular interstitial cells (VICs) within a 3D culture but also fosters the remodeling of extracellular matrix of VICs. The in vitro experiments demonstrated that the introduction of ChsMA improved the hemocompatibility and endothelialization of TEHV scaffold. The in vivo experiments revealed that, compared to their non-hydrogel counterparts, the PCL-GelMA/ChsMA scaffold, when implanted into SD rats, significantly suppressed immune reactions and calcification. In comparison with the PCL scaffold, the PCL-GelMA/ChsMA scaffold exhibited higher bioactivity and superior biocompatibility. The amalgamation of MEW technology and biomimetic design approaches provides a new paradigm for manufacturing scaffolds with highly controllable microstructures, biocompatibility, and anisotropic mechanical properties required for the fabrication of TEHVs.

Abstract The world's population is growing, leading to an increasing demand for freshwater resources for drinking, sanitation, agriculture, and industry. Interfacial solar steam generation (ISSG) can solve many problems, such as mitigating the power crisis, minimizing water pollution, and improving the purification and desalination of seawater, rivers/lakes, and wastewater. Cellulosic materials are a viable and ecologically sound technique for capturing solar energy that is adaptable to a range of applications. This review paper aims to provide an overview of current advancements in the field of cellulose‐based materials ISSG devices, specifically focusing on their applications in water purification and desalination. This paper examines the cellulose‐based materials ISSG system and evaluates the effectiveness of various cellulosic materials, such as cellulose nanofibers derived from different sources, carbonized wood materials, and two‐dimensional (2D) and 3D cellulosic‐based materials from various sources, as well as advanced cellulosic materials, including bacterial cellulose and cellulose membranes obtained from agricultural and industrial cellulose wastes. The focus is on exploring the potential applications of these materials in ISSG devices for water desalination, purification, and treatment. The function, advantages, and disadvantages of cellulosic materials in the performance of ISSG devices were also deliberated throughout our discussion. In addition, the potential and suggested methods for enhancing the utilization of cellulose‐based materials in the field of ISSG systems for water desalination, purification, and treatment were also emphasized.

The natural aging process is accompanied by changes in exosomes, gut microbiota, and metabolites. This study aimed to reveal the anti-aging effect and mechanisms of fecal microbiota transplantation (FMT) from young donors on the natural aging process in mice by analyzing exosomes, gut microbiota, and metabolomics. Aging-relevant telomeric length, oxidative stress indexes in brain tissue, and serum cytokine levels were measured. Flow analysis of T-regulatory (Treg), CD4+, and CD8+ cells was performed, and the expression levels of aging-related proteins were quantified. High-throughput sequencing technology was used to identify differentially expressed serum exosomal miRNAs. Fecal microbiota was tested by 16 S rDNA sequencing. Changes in fecal metabolites were analyzed by UPLC-Q-TOF/MS. The results indicated that the expression of mmu-miR-7010–5p, mmu-miR-376b-5p, mmu-miR-135a-5p, and mmu-miR-3100–5p by serum exosomes was down-regulated and the abundance of opportunistic bacteria (Turicibacter, Allobaculum, Morganella.) was decreased, whereas the levels of protective bacteria (Akkermansia, Muribaculaceae, Helicobacter.) were increased after FMT. Metabolic analysis identified 25 potential biomarkers. Correlation analysis between the gut microbiota and metabolites suggested that the relative abundance of protective bacteria was positively correlated with the levels of spermidine and S-adenosylmethionine. The study indicated that FMT corrected brain injury due to aging via lipid metabolism, the metabolism of cofactors and vitamins, and amino acid metabolism.

Abstract Isochlorate dehydrogenase 1 (IDH1) is an important metabolic enzyme for the production of α-ketoglutarate (α-KG), which has antitumor effects and is considered to have potential antitumor effects. The activation of IDH1 as a pathway for the development of anticancer drugs has not been attempted. We demonstrated that IDH1 can limit glycolysis in hepatocellular carcinoma (HCC) cells to activate the tumor immune microenvironment. In addition, through proteomic microarray analysis, we identified a natural small molecule, scutellarin (Scu), which activates IDH1 and inhibits the growth of HCC cells. By selectively modifying Cys297, Scu promotes IDH1 active dimer formation and increases α-KG production, leading to ubiquitination and degradation of HIF1a. The loss of HIF1a further leads to the inhibition of glycolysis in HCC cells. The activation of IDH1 by Scu can significantly increase the level of α-KG in tumor tissue, downregulate the HIF1a signaling pathway, and activate the tumor immune microenvironment in vivo. This study demonstrated the inhibitory effect of IDH1–α-KG–HIF1a on the growth of HCC cells and evaluated the inhibitory effect of Scu, the first IDH1 small molecule agonist, which provides a reference for cancer immunotherapy involving activated IDH1.

Abstract Myocardial infarction (MI) induces neuroinflammation indirectly, chronic neuroinflammation may cause neurodegenerative diseases. Changes in the proteomics of heart and brain tissue after MI may shed new light on the mechanisms involved in neuroinflammation. This study explored brain and heart protein changes after MI with a data-independent acquisition (DIA) mode proteomics approach. Permanent ligation of the left anterior descending coronary artery (LAD) was performed in the heart of rats, and the immunofluorescence of microglia in the brain cortex was performed at 1d, 3d, 5d, and 7d after MI to detect the neuroinflammation. Then proteomics was accomplished to obtain the vital proteins in the heart and brain post-MI. The results show that the number of microglia was significantly increased in the Model-1d group, the Model-3d group, the Model-5d group, and the Model-7d group compared to the Sham group. Various proteins were obtained through DIA proteomics. Linking to key targets of brain disease, 14 proteins were obtained in the brain cortex. Among them, elongation of very long chain fatty acids protein 5 (ELOVL5) and ATP-binding cassette subfamily G member 4 (ABCG4) were verified through western blotting (WB). The results of WB were consistent with the proteomics results. Therefore, these proteins may be related to the pathogenesis of neuroinflammation after MI.

Lepidium meyenii (Maca) is a food and traditional herbal medicine derived from the roots of perennial plants cultivated at high altitudes in the Andes Mountains. Although many studies have shown the potential clinical value of maca, its integration into the existing clinical medical system remains a challenge. Therefore, this study used a combination of metabolomics and bioinformatics to accurately explore the characteristic metabolites of maca, which were verified in alcoholic fatty acid disease (AFLD) and nonalcoholic fatty acid disease (NAFLD) rat models, revealing the potential clinical efficacy of maca. Through subsequent quantitative analysis, we identified a new marker that may provide new ideas for subsequent clinical diagnosis of fatty liver.

Introduction: Aged-related brain damage and gut microbiome disruption are common. Research affirms that modulating the microbiota-gut-brain axis can help reduce age-related brain damage.Methods: Ginseng, esteemed in traditional Chinese medicine, is recognized for its anti-aging capabilities. However, previous Ginseng anti-aging studies have largely focused on diseased animal models. To this end, efforts were hereby made to explore the potential neuroprotective effects of fecal microbiota transplantation (FMT) from Ginseng-supplemented aged mice to those pre-treated with antibiotics.Results: As a result, FMT with specific modifications in natural aging mice improved animal weight gain, extended the telomere length, anti-oxidative stress in brain tissue, regulated the serum levels of cytokine, and balanced the proportion of Treg cells. Besides, FMT increased the abundance of beneficial bacteria of Lachnospiraceae, Dubosiella, Bacteroides, etc. and decreased the levels of potential pathogenic bacteria of Helicobacter and Lachnoclostridium in the fecal samples of natural aged mice. This revealed that FMT remarkably reshaped gut microbiome. Additionally, FMT-treated aged mice showed increased levels of metabolites of Ursolic acid, β-carotene, S-Adenosylmethionine, Spermidine, Guanosine, Celecoxib, Linoleic acid, etc., which were significantly positively correlated with critical beneficial bacteria above. Additionally, these identified critical microbiota and metabolites were mainly enriched in the pathways of Amino acid metabolism, Lipid metabolism, Nucleotide metabolism, etc. Furthermore, FMT downregulated p53/p21/Rb signaling and upregulated p16/p14, ATM/synapsin I/synaptophysin/PSD95, CREB/ERK/AKT signaling in brain damage following natural aging.Discussion: Overall, the study demonstrates that reprogramming of gut microbiota by FMT impedes brain damage in the natural aging process, possibly through the regulation of microbiota-gut-brain axis.

Abstract Chromium (Cr(VI)) pollution has attracted wide attention due to its high toxicity and carcinogenicity. Modified biochar has been widely used in the removal of Cr(VI) in water as an efficient and green adsorbent. However, the existing biochar prepared by chemical modification is usually complicated in process, high in cost, and has secondary pollution, which limits its application. It is urgent to explore modified biochar with simple process, low cost and environmental friendliness. Therefore, ball milling wheat straw biochar (BM-WB) was prepared by ball milling technology in this paper. The adsorption characteristics and mechanism of Cr(VI) removal by BM-WB were analyzed by functional group characterization, adsorption model and response surface method. The results showed that ball milling effectively reduced the particle size of biochar, increased the specific surface area, and more importantly, enhanced the content of oxygen-containing functional groups on the surface of biochar. After ball milling, the adsorption capacity of Cr(VI) increased by 3.5–9.1 times, and the adsorption capacity reached 52.21 mg/g. The adsorption behavior of Cr(VI) follows the pseudo-second-order kinetics and Langmuir isotherm adsorption model rate. Moreover, the Cr(VI) adsorption process of BM-WB is endothermic and spontaneous. Under the optimized conditions of pH 2, temperature 45 °C, and adsorbent dosage 0.1 g, the removal rate of Cr(VI) in the solution can reach 100%. The mechanism of Cr(VI) adsorption by BM-WB is mainly based on electrostatic attraction, redox and complexation. Therefore, ball milled biochar is a cheap, simple and efficient Cr(VI) removal material, which has a good application prospect in the field of remediation of Cr(VI) pollution in water.

Alzheimer’s Disease (AD) accounts for the majority of dementia, and Mild Cognitive Impairment (MCI) is the early stage of AD. Early and accurate diagnosis of dementia plays a vital role in more targeted treatments and effectively halting disease progression. However, the clinical diagnosis of dementia requires various examinations, which are expensive and require a high level of expertise from the doctor. In this paper, we proposed a classification method based on multi-modal data including Electroencephalogram (EEG), eye tracking and behavioral data for early diagnosis of AD and MCI. Paradigms with various task difficulties were used to identify different severity of dementia: eye movement task and resting-state EEG tasks were used to detect AD, while eye movement task and delayed match-to-sample task were used to detect MCI. Besides, the effects of different features were compared and suitable EEG channels were selected for the detection. Furthermore, we proposed a data augmentation method to enlarge the dataset, designed an extra ERPNet feature extract layer to extract multi-modal features and used domain-adversarial neural network to improve the performance of MCI diagnosis. We achieved an average accuracy of 88.81% for MCI diagnosis and 100% for AD diagnosis. The results of this paper suggest that our classification method can provide a feasible and affordable way to diagnose dementia.

Abstract In this study, modified biochar (BRB) was prepared from rice straw by ball milling technique and used for the adsorption of methylene blue (MB) in wastewater. The BRB was characterized by SEM, FTIR and XPS, and the adsorption model and Box–Behnken design were used to optimize the five influencing factors. The results showed that the ball milling technique could increase the content of functional groups (–OH, C=C and C–O, etc.) and aromatic structures on the surface of biochar, thus facilitating the removal of MB. The isotherm model was consistent with the Langmuir adsorption model (R2 = 0.947) and the maximum adsorption capacity was 50.27 mg/g. The adsorption kinetics was consistent with the pseudo-second-order kinetic model (R2 = 1) and the adsorption rate was mainly controlled by chemisorption. The thermodynamic model confirmed that the adsorption process was a spontaneous heat absorption reaction. The maximum adsorption efficiency was 99.78% under the optimal conditions (40℃, pH 8, reaction time = 90 min, dosing amount = 0.1 mg), and the adsorption efficiency could be improved by increasing the pH and BRB dosing amount. The surface functional groups and crystal structure properties of BRB were the main determinants of adsorption, and it was clarified that physical adsorption, electrostatic attraction and π-π interaction were the main mechanisms for the adsorption of MB by BRB. The main mechanisms were clarified. Therefore, BRB is an economic, efficient and green adsorption material with good potential for the removal of dye pollutants in the aqueous environment.

Peeling wheat yields higher-quality flour. During processing in a flaking machine, wheat kernels undergo continuous compression within the machine’s chamber. As this compression persists, damage to the kernels intensifies and accumulates, eventually leading to kernel breakage. To study the damage characteristics of wheat kernels during peeling, this study established a continuous damage model based on Hertzian contact theory and continuous damage theory. The model’s accuracy was validated through experiments, culminating in the calculation of critical parameters for wheat peeling. This study focused on different wheat varieties (Ningmai 22 and Jichun 1) and kernel sizes (the thicknesses of the small, medium, and large kernels were standardized as follows: Ningmai 22—2.67 ± 0.07 mm, 2.81 ± 0.07 mm, and 2.95 ± 0.07 mm; Jichun 1—2.98 ± 0.11 mm, 3.20 ± 0.11 mm, and 3.42 ± 0.11 mm). Continuous compression tests were conducted using a mass spectrometer, and critical damage parameters were analyzed and calculated by integrating the theoretical model with experimental data. The test results showed that the average maximum crushing force (Fc) for small, medium, and large-sized kernels of Ningmai 22 was 96.71 ± 2.27 N, 110.17 ± 2.68 N, and 128.41 ± 2.85 N, respectively. The average maximum crushing deformation (αc) was 0.65 ± 0.08 mm, 0.68 ± 0.13 mm, and 0.77 ± 0.17 mm, respectively. The average elastic–plastic critical pressure (Fs) was 50.21 N, 60.13 N, and 59.08 N, respectively, and the average critical values of elastic–plastic deformation (αs) were 0.37 mm, 0.38 mm, and 0.39 mm, respectively. For Jichun 1, the average maximum crushing force (Fc) for small-, medium-, and large-sized kernels was 113.34 ± 3.15 N, 125.28 ± 3.64 N, and 136.15 ± 3.29 N, respectively. The average maximum crushing deformation (αc) was 0.75 ± 0.11 mm, 0.83 ± 0.15 mm, and 0.88 ± 0.18 mm, respectively. The average elastic–plastic critical pressure (Fs) was 58.11 N, 64.17 N, and 85.05 N, respectively, and the average critical values of elastic–plastic deformation (αs) were 0.45 mm, 0.47 mm, and 0.52 mm, respectively. The test results indicated that during mechanical compression, if the deformation is less than αs, the continued application of the compression load will not result in kernel crushing. However, if the deformation exceeds αs, continued compression will lead to kernel crushing, with the required number of compressions decreasing as the deformation increases. If the deformation surpasses αc, a single compression load is sufficient to cause kernel crushing. Since smaller wheat kernels are more susceptible to breakage during processing, the peeling pressure (F) within the chamber should be controlled to remain below the average elastic–plastic critical pressure (Fs) of small-sized wheat kernels. Additionally, the kernel deformation (α) induced by the flow rate and loading in the chamber should be kept below the average elastic–plastic critical deformation (αs) of small-sized wheat kernels. This paper provides a theoretical foundation for the structural design and optimization of processing parameters for wheat peeling machines.

Background: Amino acids (AAs) metabolism profiles in brain play a pivotal role in cerebral ischemia (CI), which is a complex, spatial and temporal event. NaoXinTong Capsules (NXT) are widely prescribed in Chinese medicine for the treatment of cerebrovascular and cardiovascular diseases. Methods: In this study, a novel analytical method for the quantification of twenty-three AAs in cortex and hippocampus was developed by UPLC-QQQ-MS. Based on middle cerebral artery occlusion (MCAO) rat model, the cerebral infarction and the neurological behavior scores are firstly dynamically evaluated at 3, 12, and 24 h after CI. Then the dynamic levels of the AAs in cortex and hippocampus were analyzed respectively after CI. Results: After CI, MCAO rats showed neurological deficits especially at 24 h. Based on PCA scores plot at different time after CI, the time of the AAs metabolism showing an obvious disturbance in the cortex (12 and 24 h after ischemia) is earlier than that in the hippocampus (24 h after ischemia). Based on the fold-changes of MCAO vs. sham group and receiver operating curve (ROC) analysis, a total of nine AAs biomarkers, with continuous and consistent changes at different time points after CI, were finally obtained including eight AAs of Ala, GABA, Pro, Val, Ile, His, Cit and Leu in the cortex, and three AAs of Ile, Asp, and Cit in the hippocampus. After NXT treatment, the efficacy was confirmed by reducing cerebral infarction and improving the neurological behavior scores. Furthermore, GABA, Pro, His, Leu, Asp, Ile and Cit were found to exhibited an obvious tendency for returning to baseline values in the corresponding regions at 24 h after CI (P

Understanding the factors that shape the diversity, distribution, and function of denitrifying microbes is vital for managing nitrogen cycling in these ecosystems. This study explores the diversity, biogeographic distribution, assembly processes, interaction, and denitrification potential of the nirS-encoding microbial community (nirS denitrifier) in the Pearl River Estuary based on high-throughput and metagenomics sequencing dataset. The results of this study show that salinity is a crucial regulatory environmental factor that determines the spatial distribution, phylogenetic turnover, and co-occurrence patterns of nirS denitrifiers. Additionally, the dissolved organic carbon (DOC), suspended sediment concentration (SSC), and dissolved oxygen (DO) in water also significantly impact the biodiversity and abundance of nirS denitrifiers. Furthermore, our findings demonstrate that, in comparison to environmental factors, the ecological and evolutionary characteristics of nirS denitrifiers play a more prominent role in regulating their denitrification potential, suggesting that alterations in the microbial community within dynamic changes in estuarine water can profoundly affect its denitrification function. Our results indicate the significant roles of denitrification microbial structure and phylogenetic characteristics in maintaining their ecological functions. Future studies should continue to explore the interactions between microbial communities and environmental factors to further elucidate the denitrification process in estuaries and its implications for ecosystem health and water quality.

Abstract During the continuous charge and discharge process in lithium-sulfur batteries, one of the next-generation batteries, polysulfides are generated in the battery’s electrolyte, and impact its performance in terms of power and capacity by involving the process. The amount of polysulfides in the electrolyte could be estimated by the change of the Gibbs free energy of the electrolyte, $$\Delta _{mix}\textrm{G}$$ Δ mix G in the presence of polysulfide. However, obtaining $$\Delta _{mix}\textrm{G}$$ Δ mix G of the diverse mixtures of components in the electrolyte is a complex and expensive task that shows itself as a bottleneck in optimization of electrolytes. In this work, we present a machine-learning approach for predicting $$\Delta _{mix}\textrm{G}$$ Δ mix G of electrolytes. The proposed architecture utilizes (1) an attention-based model (Attentive FP), a contrastive learning model (MolCLR) or morgan fingerprints to represent chemical components, and (2) transformers to account for the interactions between chemicals in the electrolyte. This architecture was not only capable of predicting electrolyte properties, including those of chemicals not used during training, but also providing insights into chemical interactions within electrolytes. It revealed that interactions with other chemicals relate to the logP and molecular weight of the chemicals.

Abstract Background Powdery mildew is a common leaf disease of crops worldwide. A large quantity of chemical fungicides is used to control this disease in horticulture and agriculture, producing serious safety and environmental problems. To suppress this disease in safe and environment-friendly ways, the biocontrol of a self-isolated new strain of Lysobacter enzymogenes (CQ18) was studied against flue-cured tobacco powdery mildews. Results L. enzymogenes CQ18 produced chitinase, protease, β-1,3-glucanase, phosphatase, and siderophore, which may enable this biocontrol bacterium to degrade pathogen cell membranes and walls and deprive pathogens of iron. HPLC/MS analysis identified 14 antifungal metabolites present in L. enzymogenes CQ18 fermentation liquid (LEFL), which were grouped into organic acids, azoles, and pyrimidines. The variable targets in or on pathogen cells and combinative effects of these multiple metabolites may potently suppress the powdery mildew and be less likely to make Erysiphe cichoracearum develop resistance. LEFL was rich in L-pyroglutamate. Both LEFL and L-pyroglutamate inhibited the germination of E. cichoracearum conidia in vitro and reduced the powdery mildew index in the greenhouse and field. L-Pyroglutamate at a concentration of 0.50% achieved the same control efficacy as the chemical fungicide triadimefon (91–94%). Conclusions L. enzymogenes CQ18 and the metabolite L-pyroglutamate effectively controlled flue-cured tobacco powdery mildew. L. enzymogenes CQ18 grows rapidly and is resilient to adversity. L-Pyroglutamate has no toxicity to humans and is easy to synthesize at a low cost. Both show potential use in controlling plant powdery mildews. Graphical Abstract

Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.

Environmental protection talents training (EPTT) is recognized as a key prerequisite for maintaining environmental sustainability, and in order to study the influence of each player on EPTT. This paper innovatively constructs a tripartite evolutionary game model of government, university and enterprise. The equilibrium points and evolutionary stabilization strategies of each participant are solved by replicating the dynamic equations, and the behaviors of each subject in EPTT are analyzed so as to clarify the behavioral characteristics and optimal strategies of the government's participation in EPTT. The results show that enterprises occupy a more important position in influencing government decisions. The government should reduce the financial incentives for enterprises and replace them with greater policy support. Meanwhile, the government should actively promote the cultivation mechanism that integrates universities and enterprises. The results of the study can provide a decision-making basis for the government to promote the sustainable development of EPTT.

Abstract Heart failure (HF) is an advanced stage of most heart diseases. Some studies reported that Dengzhanshengmai (DZSM) capsule may improve HF, but its mechanisms are unclear. This study attempts to determine the function of DZSM in treating HF and investigates its potential mechanism. We demonstrated that DZSM can considerably reduce systemic inflammation, improve intestinal barrier functions and enhance cardiac functions in HF rats. Further investigations displayed that the beneficial effects of DZSM were related to the reduction of gut microbiota metabolite phenylacetylglutamine (PAGln) levels in serum and heart tissue. In addition, we demonstrated that PAGln can exacerbate the severity of HF in rats, and the serum PAGln levels in HF patients were higher than in healthy subjects. Moreover, by using microbial sequencing, we found that DZSM could alter the composition and function of the intestinal microbiota in HF rats, including decreased relative abundance of Turicibacter and Turicibacter_sp.TS3, and regulated the gene expression of PAGln synthesis‐related enzymes. Therefore, our findings have contributed novel perspectives on the involvement of DZSM in treating HF, specifically in its regulation of intestinal flora and associated detrimental metabolites. Furthermore, our results have offered empirical evidence supporting the utilization of DZSM as a therapeutic approach for HF.

Chemotherapy is one of the most commonly treatments of advanced colorectal cancer (CRC). However, the drug resistant following chemotherapeutic treatment is a significant challenge in the clinical management of CRC. Therefore, understanding the resistance mechanisms and developing new strategies for enhancing the sensitivity are urgently needed to improve CRC outcome. Connexins contribute to the formation of gap junctions among neighboring cells and then advance gap junctional intercellular communication (GJIC) for transportation of ions and small molecules. Although the drug resistance resulted from GJIC dysfunctional by aberrant expression of connexins is relatively well understood, the underlying mechanisms of mechanical stiffness mediated by connexin responsible for chemoresistance are largely unknown in CRC. Here, we demonstrated that connexin 43 (CX43) expression was downregulated in CRC and that loss of CX43 expression was positively correlated with metastasis and poor prognosis of CRC patients. The CX43 overexpressing suppressed CRC progression and increased the sensitivity to 5-fluorouracil (5-FU) via enhanced GJIC in vitro and in vivo. Moreover, we also highlight that the downregulation of CX43 in CRC increases the stemness of cells via reducing the cell stiffness, thus promoting the drug resistance. Our results further suggest that both effects, that is changes in the mechanical stiffness of the cell and GJIC mediated by CX43 deregulated, are closely related to drug resistance in CRC, which indicating CX43 as a target against cancer growth and chemoresistance in CRC.

During the rice milling process, single and continuous compression occurs between brown rice and the processing parts. When the external load exceeds the yield limit of brown rice, brown rice kernels are damaged; with an increase in compression deformation or the extent of compression, the amount of damage to the kernels expands and accumulates, ultimately leading to the fracture and breakage of kernels. In order to investigate the mechanical compression damage characteristics of brown rice kernels under real-world working conditions, this study constructs an elastic–plastic compression model and a continuous damage model of brown rice kernels based on Hertz theory and continuous damage theory; the accuracy of this model is verified through experiments, and the relevant processing critical parameters are calculated. In this study, three varieties of brown rice kernels are taken as the research object, and mechanical compression tests are carried out using a texture apparatus; finally, the test data are analysed and calculated by combining them with the theoretical model to obtain the relevant critical parameters of damage. The results of the single compression crushing test of brown rice kernels showed that the maximum destructive forces Fc in the single compression of Hunan Early indica 45, Hunan Glutinous 28, and Southern Japonica 518 kernels were 134.77 ± 11.20 N, 115.64 ± 4.35 N, and 115.84 ± 5.89 N, respectively; the maximum crushing deformations αc in the single compression crushing test were 0.51 ± 0.04 mm, 0.43 ± 0.01 mm, and 0.48 ± 0.17 mm, respectively; and the critical average deformations αs of elasticity–plasticity deformation were 0.224 mm, 0.267 mm, and 0.280 mm, respectively. The results of the continuous compression crushing test of brown rice kernels showed that the critical deformations αd of successive compression damage formation were 0.224 mm, 0.267 mm, and 0.280 mm, and the deformation ratios δ of compression damage were 12.24%, 14.35%, and 12.84%. From the test results, it can be seen that the continuous application of compression load does not result in the crushing of kernels if the compression deformation is less than αd during mechanical compression. The continuous application of compressive loads can lead to fragmentation of the kernels if the compressive deformation exceeds αd; the larger the compression variant, the less compression is required for crushing. If the compression deformation exceeds αc, then a single compressive load can directly fragment the kernels. Therefore, the load employed during rice milling should be based on the variety of brown rice used in order to prevent brown rice deformation, which should be less than αd, and the maximum load should not exceed Fc. The results of this study provide a theoretical reference for the structure and parameter optimisation of a rice milling machine.

The global increase in population, the phenomenon of climate change, the issue of water pollution and contamination, and the inadequate management of water resources all exert heightened strain on freshwater reserves. The potential utilization of the interfacial solar steam generation (ISSG) system, which utilizes photothermal conversion to generate heat on material surfaces for wastewater purification and desalination purposes, has been successfully demonstrated. Textile-material-based ISSG devices, including (woven, nonwoven, and knitted) fabrics and electrospinning membranes, exhibit distinct properties such as a rough surface texture, high porosity, significant surface area, exceptional flexibility, and robust mechanical strength. These characteristics, combined with their affordability, accessibility, and economic viability for widespread implementation, make them extremely attractive for applications in SSG. In this review, a comprehensive analysis of the emerging concepts, advancements, and applications of textile materials, such as woven, nonwoven, and knitted fabrics and electrospun membranes, in ISSG for wastewater purification and desalination is presented. We also emphasize significant obstacles and potential prospects in both theoretical investigations and real-world implementations, aiming to contribute to future advancements in the domain of textile-material-based interfacial evaporation in wastewater purification and desalination. Furthermore, the drawbacks and the challenges of ISSG systems are also highlighted.

Background: A cytokine storm (CS) is a rapidly occurring, complex, and highly lethal systemic acute inflammatory response induced by pathogens and other factors. Currently, no clinical therapeutic drugs are available with a significant effect and minimal side effects. Given the pathogenesis of CS, natural products have become important resources for bioactive agents in the discovery of anti-CS drugs. Purpose: This study aimed to provide guidance for preventing and treating CS-related diseases by reviewing the natural products identified to inhibit CS in recent years. Methods: A comprehensive literature review was conducted on CS and natural products, utilizing databases such as PubMed and Web of Science. The quality of the studies was evaluated and summarized for further analysis. Results: This study summarized more than 30 types of natural products, including 9 classes of flavonoids, phenols, and terpenoids, among others. In vivo and in vitro experiments demonstrated that these natural products could effectively inhibit CS via nuclear factor kappa-B, mitogen-activated protein kinase, and Mammalian target of rapamycin (mTOR) signaling pathways. Moreover, the enzyme inhibition assays revealed that more than 20 chemical components had the potential to inhibit ACE2, 3CL-protease, and papain-like protease activity. The experimental results were obtained using advanced technologies such as biochips and omics. Conclusions: Various natural compounds in traditional Chinese medicine (TCM) extracts could directly or indirectly inhibit CS occurrence, potentially serving as effective drugs for treating CS-related diseases. This study may guide further exploration of the therapeutic effects and biochemical mechanisms of natural products on CS.

Heart failure (HF) is a complex clinical syndrome with impaired ventricular ability due to structural or functional cardiac disorders. A traditional Chinese formula named Xinshubao tablet (XSB) is reported to protect cardiomyocytes and decrease the risk of HF clinically; however, the underlying mechanism of XSB on decreasing HF risk is not elucidated yet. Therefore, our study aimed to investigate the therapeutic efficacy and underlying mechanism of XSB by using HF model rats and H9c2 cells with oxygen glucose deprivation. Echocardiographic and pathological features of animal experiment showed that XSB treatment effectively improved cardiac function and ameliorated myocardial injury after 4 weeks of treatment. Cellular experiments indicated that XSB pretreatment significantly inhibited apoptosis and increased mitochondrial energy metabolism. Furthermore, in vivo and in vitro experiments both demonstrated that XSB suppressed oxidative stress and inflammatory response. Our results further revealed that the potential protective mechanism of XSB was closely associated with the DCN/PPARα/PGC-1α/P300 signaling pathway. Our findings provide novel mechanistic insights for HF treatment and a pharmacological basis for the therapeutic application of XSB against cardiovascular disorders.

Acute lung injury (ALI) is a serious pulmonary complication that often arises from pneumonia, respiratory tract infections caused by bacteria or viruses, and other factors. It is characterized by acute onset and high mortality. Angong Niuhuang Wan (AGNHW) is a renowned emergency medicine in traditional Chinese medicine, known as the ''cool open (febrile disease) three treasures'' and regarded as the first of the ''three treasures''. Previously studies have confirmed that AGNHW has anti-inflammatory effects, improves cerebral circulation, reduces brain edema, and protects vascular endothelium. However, the active components and pharmacological mechanisms of AGNHW in treating ALI remain unclear. In this study, we confirmed that AGNHW can inhibit cytokine storm activity and reduce inflammation induced by LPS in ALI mice. We then analyzed differential proteins using proteomic technology and identified 741 differential proteins. By combining network pharmacological analysis, we deeply discussed the key active components and mechanism of AGNHW in treating ALI. By constructing the interaction network between disease and drug, we identified 21 key active components (such as Quercetin, Kaempferol, and Crocetin) and 25 potential core targets (such as PIK3CG, p65, and MMP9). These candidate targets play an important role in anti-inflammation and immune regulation. Through enrichment analysis of core targets, we found several pathways related to ALI, such as the NF-κB signaling pathway, TNF signaling pathway, and Toll-like receptor signaling pathway. This indicates that AGNHW plays a therapeutic role in ALI through multi-components, multi-targets, and multi-pathways.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic hepatic disease characterized by excessive fat accumulation, and is the major risk for cardiovascular and metabolic disorders. We explored the therapeutic effect of gypenosides (Gyps) in combination with capsaicinoids (Caps) against high-fat-diet (HFD)-induced rat hyperlipidemia and oxidized low-density lipoprotein (ox-LDL)-treated Raw264.7 cells. Network pharmacology analysis predicted that the potential molecular mechanism of Gyps/Caps combination against hyperlipidemia was mainly associated with steroid metabolism, lipid synthesis and inflammatory response. Animal experiment demonstrated that Gyps/Caps combination lowered the liver weight, liver index, serum lipid profile and hepatic cholesterol content, improved liver function by reducing the serum markers of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), thereby relieving the hepatic injury. Moreover, Gyps/Caps combination inhibited oxidative stress by decreasing the lactic dehydrogenase (LDH) activity and increasing the superoxide dismutase (SOD) activity. Western blotting result suggested that Gyps/Caps combination could upregulate the expressions of peroxisome proliferator-activated receptors γ (PPARγ), liver X receptor α (LXRα), ATP-binding cassette transporter A1 (ABCA1) and ATP-binding cassette transporter G1 (ABCG1) in the liver tissue. Cellular experiment revealed that the combination treatment protected RAW264.7 cells from ox-LDL induction through inhibiting apoptosis, lipid-decreasing and anti-inflammation, and caused the dramatic enhancement on PPARγ expression. Notably, the combined use of Gyps and Caps did not influence the pharmacological outcomes of each other, but significantly enhanced the overall therapeutic effect in ameliorating HFD-induced hyperlipidemia. Our research provided an experimental basis for advanced research and clinical application of Gyps/Caps combination. Importantly, our cumulative data indicated that combination use of Gyps and Caps may be an effective therapeutic strategy for alleviating hyperlipidemia-induced NAFLD.

Traditional Chinese medicine offer unique advantages in mitigating and preventing early or intermediate stage for treating heart failure (HF). The purpose of this study was to assess the in vivo therapeutic efficacy of Xin-shu-bao (XSB) at different stages of HF following induction of a myocardial infarction (MI) in mice and use mass spectrometry-based proteomics to identify potential therapeutic targets for different stages of HF based on the molecular changes following XSB treatment. XSB had high cardioprotective efficacy in the pre-HF with reduced ejection fraction (HFrEF) stages, but had a weak or no effect in the post-HFrEF stages. This was supported by echocardiographic measurements showing that XSB decreased ejection fraction and fractional shortening in HF. XSB administration improved cardiac function in the pre- and post-HFrEF mouse model, ameliorated deleterious changes to the morphology and subcellular structure of cardiomyocytes, and reduced cardiac fibrosis. Proteomics analysis showed that XSB intervention exclusively targeted thrombomodulin (THBD) and stromal interaction molecule 1 (STIM1) proteins when administered to the mice for both 8 and 6 weeks. Furthermore, XSB intervention for 8, 6, and 4 weeks after MI induction increased the expression of fibroblast growth factor 1 (FGF1) and decreased arrestin β1 (ARRB1), which are classic biomarkers of cardiac fibroblast transformation and collagen synthesis, respectively. Overall, the study suggests that early intervention with XSB could be an effective strategy for preventing HFrEF and highlights potential therapeutic targets for further investigation into HFrEF remediation strategies.

Recent advances in deep learning have led to increased adoption of convolutional neural networks (CNN) for structural magnetic resonance imaging (sMRI)-based Alzheimer’s disease (AD) detection. AD results in widespread damage to neurons in different brain regions and destroys their connections. However, current CNN-based methods struggle to relate spatially distant information effectively. To solve this problem, we propose a graph reasoning module (GRM), which can be directly incorporated into CNN-based AD detection models to simulate the underlying relationship between different brain regions and boost AD diagnosis performance. Specifically, in GRM, an adaptive graph Transformer (AGT) block is designed to adaptively construct a graph representation based on the feature map given by CNN, a graph convolutional network (GCN) block is adopted to update the graph representation, and a feature map reconstruction (FMR) block is built to convert the learned graph representation to a feature map. Experimental results demonstrate that the insertion of the GRM in the existing AD classification model can increase its balanced accuracy by more than 4.3%. The GRM-embedded model achieves state-of-the-art performance compared with current deep learning-based AD diagnosis methods, with a balanced accuracy of 86.2%.

The diagnosis of mild cognitive impairment (MCI), a prodromal stage of Alzheimer’s disease (AD), is essential for initiating timely treatment to delay the onset of AD. Previous studies have shown the potential of functional near-infrared spectroscopy (fNIRS) for diagnosing MCI. However, preprocessing fNIRS measurements requires extensive experience to identify poor-quality segments. Moreover, few studies have explored how proper multi-dimensional fNIRS features influence the classification results of the disease. Thus, this study outlined a streamlined fNIRS preprocessing method to process fNIRS measurements and compared multi-dimensional fNIRS features with neural networks in order to explore how temporal and spatial factors affect the classification of MCI and cognitive normality. More specifically, this study proposed using Bayesian optimization-based auto hyperparameter tuning neural networks to evaluate 1D channel-wise, 2D spatial, and 3D spatiotemporal features of fNIRS measurements for detecting MCI patients. The highest test accuracies of 70.83%, 76.92%, and 80.77% were achieved for 1D, 2D, and 3D features, respectively. Through extensive comparisons, the 3D time-point oxyhemoglobin feature was proven to be a more promising fNIRS feature for detecting MCI by using an fNIRS dataset of 127 participants. Furthermore, this study presented a potential approach for fNIRS data processing, and the designed models required no manual hyperparameter tuning, which promoted the general utilization of fNIRS modality with neural network-based classification to detect MCI.

Abstract Cell therapy is the frontier technology of biotechnology innovation and the most promising method for the treatment of refractory diseases such as tumours. However, cell therapy has disadvantages, such as toxicity and poor therapeutic effects. Plant extracts are natural, widely available, and contain active small molecule ingredients that are widely used in the treatment of various diseases. By studying the effect of plant extracts on cell therapy, active plant extracts that have positive significance in cell therapy can be discovered, and certain contributions to solving the current problems of attenuation and adjuvant therapy in cell therapy can be made. Therefore, this article reviews the currently reported effects of plant extracts in stem cell therapy and immune cell therapy, especially the effects of plant extracts on the proliferation and differentiation of mesenchymal stem cells and nerve stem cells and the potential role of plant extracts in chimeric antigen receptor T-cell immunotherapy (CAR-T) and T-cell receptor modified T-cell immunotherapy (TCR-T), in the hope of encouraging further research and clinical application of plant extracts in cell therapy.

The ports of a three-phase voltage source converter have multiple frequency electrical parameters, which makes HVDC systems with these converters present multiple input multiple output (MIMO) characteristics. The generalized Nyquist criterion of the MIMO model is often used to analyze the system stability. However, this model is more difficult to obtain than the single-input single-output (SISO) model, and the stability margin and the oscillation frequency band are difficult to capture. To solve these problems, this paper took the two-terminal HVDC transmission system as the research object to derive a SISO model that can be measured by a port. Moreover, this study also proposed a method for analyzing the system stability through envelope SISO open-loop gains. Finally, the key port and parameters affecting the system stability were analyzed according to the stability margin, which provided theoretical support for the design of the system parameters. The established model and the proposed analysis method were verified in a MATLAB/Simulink simulation model.

In addition to the pharmacological effects of Periplaneta americana extracts (PAEs), including their antitumor, hepatic protection, antioxidant, antibacterial, anti-inflammatory, and tissue regeneration characteristics, their mucosal restorative effects have also attracted significant attention. The mucosa serves as a “gateway” into the body and its functions include the surveillance and clearance of bacteria and pathogens; it also has the immunological function of acquiring beneficial antigens from the external environment and removing non-beneficial ones, a mechanism controlled by the mucosal immune system. In the present study, the relevant modern research literature on the mucosal restorative effect of PAEs was reviewed via a summarization of its restorative effects on respiratory, digestive, dermal, and genitourinary mucosa. The aim of doing so was to present a comprehensive understanding of the mucosal restorative effect of PAEs and their related mechanisms and to provide a reference for their further development and clinical application.

The heart valve is crucial for the human body, which directly affects the efficiency of blood transport and the normal functioning of all organs. Generally, decellularization is one method of tissue-engineered heart valve (TEHV), which can deteriorate the mechanical properties and eliminate allograft immunogenicity. In this study, removable polyvinyl alcohol (PVA) is used to encapsulate decellularized porcine heart valves (DHVs) as a dynamic template to improve the processability of DHVs, such as suturing. Mechanical tests show that the strength and elastic modulus of DHVs treated with different concentrations of PVA significantly improve. Without the PVA layer, the valve would shift during suture puncture and not achieve the desired suture result. The in vitro results indicate that decellularized valves treated with PVA can sustain the adhesion and growth of human umbilical vein endothelial cells (HUVECs). All results above show that the DHVs treated with water-soluble PVA have good mechanical properties and cytocompatibility to ensure post-treatment. On this basis, the improved processability of DHV treated with PVA enables a new paradigm for the manufacturing of scaffolds, making it easy to apply.

(1) Background: Arteriovenous fistulas (AVFs) are the preferred site for hemodialysis. Unfortunately, approximately 60% of patients suffer from AVF failure within one year. Oxidative stress plays an important role in the occurrence and development of AVF. However, the underlying mechanisms remain unclear. Therefore, specific oxidative stress-related biomarkers are urgently needed for the diagnosis and treatment of AVF failure. (2) Methods: Bioinformatics analysis was carried out on dataset GSE119296 to screen for PTGS2 as a candidate gene related to oxidative stress and to verify the expression level and diagnostic efficacy of PTGS2 in clinical patients. The effects of NS398, a PTGS2 inhibitor, on hemodynamics, smooth muscle cell proliferation, migration, and oxidative stress were evaluated in a mouse AVF model. (3) Results: Based on 83 oxidative stress-related differentially expressed genes, we identified the important pathways related to oxidative stress. PTGS2 may have diagnostic and therapeutic efficacy for AVF failure. We further confirmed this finding using clinical specimens and validation datasets. The animal experiments illustrated that NS398 administration could reduce neointimal area (average decrease: 49%) and improve peak velocity (average increase: 53%). (4) Conclusions: Our study identified PTGS2 as an important oxidative stress-related biomarker for AVF failure. Targeting PTGS2 reduced oxidative stress and improved hemodynamics in an AVF mouse model.

Plant-endophytic microbes affect plant growth, development, nutrition, and resistance to pathogens. However, how endophytic microbial communities change in different strawberry plant compartments after Fusarium pathogen infection has remained elusive. In this study, 16S and internal transcribed spacer rRNA amplicon sequencing were used to systematically investigate changes in the bacterial and fungal diversity and composition in the endophytic compartments (roots, stems, and leaves) of healthy strawberries and strawberries with Fusarium wilt, respectively. The analysis of the diversity, structure, and composition of the bacterial and fungal communities revealed a strong effect of pathogen invasion on the endophytic communities. The bacterial and fungal community diversity was lower in the Fusarium-infected endophytic compartments than in the healthy samples. The relative abundance of certain bacterial and fungal genera also changed after Fusarium wilt infection. The relative abundance of the beneficial bacterial genera Bacillus, Bradyrhizobium, Methylophilus, Sphingobium, Lactobacillus, and Streptomyces, as well as fungal genera Acremonium, Penicillium, Talaromyces, and Trichoderma, were higher in the healthy samples than in the Fusarium wilt samples. The relative abundance of Fusarium in the infected samples was significantly higher than that in the healthy samples, consistent with the field observations and culture isolation results for strawberry wilt. Our findings provide a theoretical basis for the isolation, identification, and control of strawberry wilt disease.

Traditional protein chips are based on solid chips and cannot enable drug and target screening in a label-free manner. Herein, a protein thermal shift chip (PTSC) based on fluorescence signals is proposed, which enables low-cost, high-throughput, label-free screening. We developed a PTSC for COVID-19, containing 12 SARS-CoV-2 and host target proteins. A series of quality-control tests were performed for small-molecule drugs, macromolecular antibodies, and herbal-medicine extracts. This chip enabled high-throughput screening of COVID-19 drugs and thus may serve as a tool for screening drug targets clinically effective drugs.

Quantitative assessment of hand function can assist therapists in providing appropriate rehabilitation strategies, which plays an essential role in post-stroke rehabilitation. Conventionally, the assessment process relies heavily on clinical experience and lacks quantitative analysis. To quantitatively assess the hand motor function of patients with post-stroke hemiplegia, this study proposes a novel multi-modality fusion assessment framework. This framework includes three components: the kinematic feature extraction based on a graph convolutional network (HAGCN), the surface electromyography (sEMG) signal processing based on a multi-layer long short term memory (LSTM) network, and the quantitative assessment based on the multi-modality fusion. To the best of the authors’ knowledge, this is the first study of applying a graph convolution network to assess the hand motor function. We also collect the kinematic data and sEMG data from 70 subjects who completed 28 types of hand movements. Therapists first graded patients using traditional motor assessment scales (Brunnstrom Scale and Fugl-Meyer Assessment Scale) and further refined the patient’s motor assessment result by their experience. Then, we trained the HAGCN and LSTM networks and quantitatively assessed each patient based on the proposed assessment framework. Finally, the Spearman correlation coefficient (SC) between the assessment result of this study and the traditional scale are 0.908 and 0.967, demonstrating a significant correlation between the proposed assessment and the traditional scale scores. In addition, the SC value between the score of this study and the refined hand motor function is 0.997, indicating the “ceiling effect” of some traditional scales can be avoided.

Abstract Background and aims Cancer will soon become the leading cause of death in every country in the twenty-first century. This study aimed to analyze the mortality and morbidity of 29 types of cancer in 204 countries or regions from 1990 to 2019 to guide global cancer prevention and control. Methods Detailed information for 29 cancer groups was collected from the Global Burden of Disease Study in 2019. The age-standardized incidence rate (ASIR) and age-standardized death rate (ASDR) of the 29 cancer groups were calculated based on sex, age, region, and country. In addition, separate analyses were performed for major cancer types. Results In 2019, more than 10 million people died from cancer, which was approximately twice the number in 1990. Tracheal, bronchus, and lung (TBL) cancers collectively showed the highest death rate, and the ASDR of pancreatic cancer increased by 24%, which was cancer with the highest case fatality rate (CFR). The global cancer ASIR showed an increasing trend, with testicular cancer, thyroid cancer, and malignant skin melanoma showing a significant increase. The ASDR and ASIR of cancer in males were about 1.5 times higher than that in females. Individuals over 50 years had the highest risk of developing cancer, with incidences and deaths in this age group accounting for more than 85% of cancers in all age groups. Asia has the heaviest cancer burden due to its high population density, with esophageal cancer in this region accounting for 53% of the total fatalities related to this type of cancer in the world. In addition, the mortality and morbidity of most cancers increased with the increase in the development or socio-demographic index (SDI) in the SDI regions based on the World Bank's Human Development Index (HDI), with cancer characteristics varying in the different countries globally. Conclusions The global cancer burden continues to increase, with substantial mortality and morbidity differences among the different regions, ages, countries, gender, and cancer types. Effective and locally tailored cancer prevention and control measures are essential in reducing the global cancer burden in the future.

Abstract Natural products from traditional medicine inherit bioactivity from their source herbs. However, the pharmacological mechanism of natural products is often unclear and studied insufficiently. Pathway fingerprint similarity based on “drug-target-pathway” heterogeneous network provides new insight into Mechanism of Action (MoA) for natural products compared with reference drugs, which are selected approved drugs with similar bioactivity. Natural products with similar pathway fingerprints may have similar MoA to approved drugs. In our study, XYPI, an andrographolide derivative, had similar anti-inflammatory activity to Glucocorticoids (GCs) and non-steroidal anti-inflammatory drugs (NSAIDs), and GCs and NSAIDs have completely different MoA. Based on similarity evaluation, XYPI has similar pathway fingerprints as NSAIDs, but has similar target profile with GCs. The expression pattern of genes in LPS-activated macrophages after XYPI treatment is similar to that after NSAID but not GC treatment, and this experimental result is consistent with the computational prediction based on pathway fingerprints. These results imply that the pathway fingerprints of drugs have potential for drug similarity evaluation. This study used XYPI as an example to propose a new approach for investigating the pharmacological mechanism of natural products using pathway fingerprint similarity based on a “drug-target-pathway” heterogeneous network.

Root-associated fungal microbiota, which inhabit the rhizosphere, rhizoplane and endosphere, have a profound impact on plant growth and development. Sorghum bicolor (L.) Moench, also called broomcorn or sweet sorghum, is a multipurpose crop. The comparison between annual and perennial sweet sorghum cultivars in terms of plant growth, as well as their interactions with belowground fungal microbiota, is still poorly understood, although there has been growing interest in the mutualism between annual sweet sorghum and soil bacteria or bacterial endophytes. In this study, the perennial sweet sorghum cultivar N778 (N778 simply) and its control lines TP213 and TP60 were designed to grow under natural field conditions. Bulk soil, rhizosphere soil and sorghum roots were collected at the blooming and maturity stages, and then the fungal microbiota of those samples were characterized by high-throughput sequencing of the fungal ITS1 amplicon. Our results revealed that the alpha diversity of the fungal microbiota in rhizosphere soil and root samples was significantly different between N778 and the two control lines TP213 and TP60 at the blooming or maturity stage. Moreover, beta diversity in rhizosphere soil of N778 was distinct from those of TP213 and TP60, while beta diversity in root samples of N778 was distinct from those of TP213 but not TP60 by PCoA based on Bray–Curtis and WUF distance metrics. Furthermore, linear discriminant analysis (LDA) and multiple group comparisons revealed that OTU4372, a completely unclassified taxon but with symbiotroph mode, was enriched in sorghum roots, especially in N778 aerial roots at the blooming stage. Our results indicate that Cladosporium and Alternaria, two fungal genera in the rhizosphere soil, may also be dominant indicators of sorghum yield and protein content in addition to Fusarium at the maturity stage and imply that the perennial sweet sorghum N778 can primarily recruit dominant psychrotolerant bacterial taxa but not dominant cold-tolerant fungal taxa into its rhizosphere to support its survival below the freezing point.

The commercialization of sodium-ion batteries has been hampered by the anode’s performance. Carbon-based anodes have always had great application prospects, but traditional graphite anodes have great application limitations due to the inability of reversible insertion/de-insertion of sodium ions in them, while hard carbon materials have the high theoretical capacity, low reaction potential has received extensive attention in recent years. Nevertheless, the low first cycle Coulomb efficiency and rapid capacity decline of hard carbon materials limited its application. SEI has always played a crucial role in the electrochemical process. By controlling the formation of SEI, researchers have increased the efficiency of sodium-ion battery anodes, although the composition of SEI and how it evolved are still unknown. This paper briefly summarizes the research progress of hard carbon anode surface SEI in sodium-ion batteries in recent years. From the perspectives of characterization methods, structural composition, and regulation strategies is reviewed, and the future development directions of these three directions are suggested. The reference opinions are provided for the reference researchers.

Over the past decade, traditional Chinese medicine (TCM) has widely embraced systems biology and its various data integration approaches to promote its modernization. Thus, integrative pharmacology-based traditional Chinese medicine (TCMIP) was proposed as a paradigm shift in TCM. This review focuses on the presentation of this novel concept and the main research contents, methodologies and applications of TCMIP. First, TCMIP is an interdisciplinary science that can establish qualitative and quantitative pharmacokinetics–pharmacodynamics (PK–PD) correlations through the integration of knowledge from multiple disciplines and techniques and from different PK–PD processes in vivo. Then, the main research contents of TCMIP are introduced as follows: chemical and ADME/PK profiles of TCM formulas; confirming the three forms of active substances and the three action modes; establishing the qualitative PK–PD correlation; and building the quantitative PK–PD correlations, etc. After that, we summarize the existing data resources, computational models and experimental methods of TCMIP and highlight the urgent establishment of mathematical modeling and experimental methods. Finally, we further discuss the applications of TCMIP for the improvement of TCM quality control, clarification of the molecular mechanisms underlying the actions of TCMs and discovery of potential new drugs, especially TCM-related combination drug discovery.

Coastal wetlands are considered as important “blue carbon” sink, and mowing management induced by anthropogenic activities is anticipated to profoundly affect soil carbon stocks in coastal wetlands. However, the impacts of mowing management on soil organic carbon (SOC) and enzyme activities and the mechanisms responsible for associated changes in Phragmites australis wetland remain uncertain. We conducted a field mowing manipulation experiment [control (CK), mowing and returning straw in December (12MS), mowing and removing straw in December (12MR), mowing and returning straw in March (3MS), and mowing and removing straw in March (3MR)] in P. australis wetland of the Yellow River Delta and quantified their impacts on soil quality, SOC, SOC fractions, and enzyme activities. Results showed that mowing treatments led to overall increases in soil nutrients [total carbon (TC), total nitrogen (TN), total phosphorus (TP), NH4+, and NO3−] and decreases in soil C/N ratio. The effects of mowing treatments on soil nutrient content were pronounced on topsoil than deep soil, and the maximum value of TC, TN, and TP reached in the 12MR treatment. Compared with CK, the 12MS, 12MR, 3MS, and 3MR treatments at 0–10 cm depth significantly enhanced SOC content by 8.78%, 32.9%, 16.5%, and 30.1%, respectively, but only the 3MS treatment enhanced SOC by 16.5% at 10–20 cm depth. Mowing treatments increased dissolved organic carbon (DOC), microbial biomass carbon (MBC), particulate organic carbon (POC), and labile organic carbon (LOC) and the contents of DOC, MBC, POC, and LOC decreased with soil depth. Mowing treatments stimulated the activities of sucrase and urease in topsoil, but only the 3MR treatment improved alkaline phosphatase activity in topsoil. Path analysis indicated that mowing management dominantly modulates SOC by changing sucrase activity, alkaline phosphatase activity, TN, TP, NH4+, NO3−, DOC, and LOC in 0–10 cm depth. However, SOC was significantly controlled by sucrase activity, urease activity, TC, TN, TP, LOC, and POC in 10–20 cm depth. Collectively, our results indicate that the continuous mowing management is beneficial to enhance soil quality and carbon storage capacity of P. australis wetlands, which will contribute to enhance carbon sequestration and sink capacity of coastal wetlands.

Background: Chronic obstructive pulmonary disease (COPD) is the most common respiratory disease with high morbidity and mortality. Shema oral liquid (Shema) is a traditional Chinese medicine (TCM) approved for the treatment of respiratory diseases. Clinical applications have shown that Shema has antitussive, expectorant, and anti-asthmatic effects, but its definite efficacy to COPD is still unclear. This study aimed to explore the therapeutic capacity and potential mechanism of Shema in treatment of COPD.Methods: Network pharmacology was used to investigated the possible pharmacological mechanism of Shema against COPD. A rat model of lipopolysaccharide (LPS)-induced COPD was established to determine pulmonary ventilatory function, serum inflammatory cytokines, and pulmonary pathological change. Subsequently, tandem mass tag (TMT)-based quantitative proteomics was used to further reveal the therapeutic targets related with Shema against COPD. Western blot was finally performed to validate the expression of targeted proteins screened by proteomics research.Results: Network pharmacology analysis indicated that Shema against COPD mainly inhibited the inflammation and affected the immune system. The animal experiment demonstrated that Shema treatment protected the lung tissue from LPS induced injury, inhibited the levels of serum inflammatory cytokines such as interleukin (IL)-1β, IL-6, IL-8, and tumor necrosis factor (TNF)-α, and improved the respiratory ventilatory function by upregulating forced expiratory volume in 0.1 s (FEV0.1), FEV0.3, forced vital capacity (FVC), and the ratios of FEV0.1 (0.3)/FVC. Proteomic analysis and western blot both proved that Shema inhibited the expression of DNA methyltransferase 1 (DNMT1) in the lung tissue.Conclusion: The therapeutic mechanism of Shema in treatment of COPD may involve inhibiting inflammatory response, improving pulmonary ventilatory function, and alleviating LPS-induced lung injury through regulating the expression of DNMT1. This study also shed light on the development of therapeutic strategies in treating COPD by intervening DNMT-related pathways.