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Abstract Pest detection is important for crop cultivation. Crop leaf is the main place of pest invasion. Current technologies to detect crop pests have constraints, such as low efficiency, storage demands and limited precision. Image segmentation is a fast and efficient computer-aided detection technology. High resolution image capture solidly supports the crucial processes in discerning pests from images. Study of analytical methods help parse information in the images. In this paper, a regional convolutional neural network (R-CNN) architecture is designed in combination with the radial bisymmetric divergence (RBD) method for enhancing the efficiency of image segmentation. As a special application of RBD, the hierarchical mask (HM) is produced to endorse detection and classification of the leaf-dwelling pests, offering enhanced efficiency and reduced storage requirements. Moreover, to deal with some mislabeled data, a threshold variable is introduced to adjust a fault-tolerant mechanism into HM, to generate a novel threshold-based hierarchical mask (TbHM). Consequently, the hierarchical mask R-CNN (HM-R-CNN) model and the threshold-based hierarchical mask R-CNN (TbHM-R-CNN) model are established to detect various types of healthy and pest-invasive crop leaves to select the regional image features that are rich in pest information. Then simple linear iterative clustering (SLIC) method is incorporation to finish the image segmentation for the classification of pest invasion. The models are tuned and optimized, then validated. The most optimized modeling results are from the TbHM-R-CNN model, with the classification accuracy of 96.2%, the recall of 97.5% and the F1 score of 0.982. Additionally, the HM-R-CNN model observed appreciable results second only to the best model. These results indicate that the proposed methodologies are well-suited for training and testing a dataset of plant diseases, offering heightened accuracy in pest classification. This study revealed that the proposed methods significantly outperform the existing techniques, marking a substantial improvement over current methods.

The phase equilibria of the Cu–Cr–Ag–Y and Cu–Cr–Ag–Zr systems at 600 and 700 °C with a fixed Y and Zr contents of 5.0 at.% were extrapolated by CALPHAD (CALculation of PHAse Diagrams) method based on the thermodynamic parameters for the constitutive binary and ternary systems. Twelve Cu–Cr–Ag–Y and six Cu–Cr–Ag–Zr alloys were designed in different phase regions of extrapolated isothermal sections. The phases, phase compositions and microstructures of alloys were experimentally investigated by means of X-ray diffraction (XRD) and scanning electron microscopy (SEM). No quaternary phase was found. The solubilities of the solid solution phases and intermediate compounds were measured. The solidified sequences and microstructures of the Cu–Cr–Ag–X (X = Y, Zr) as-cast alloys were experimentally investigated as well as simulated by Scheil model. The calculated results are in agreement with the experimental data, which indicates the accuracy of thermodynamic databases of the Cu–Cr–Ag–X (X = Y, Zr) systems. The present work lays an important foundation for establishing the thermodynamic database of multicomponent Cu alloys.

Abstract Advanced Persistent Threats (APTs) achieves internal networks penetration through multiple methods, making it difficult to detect attack clues solely through boundary defense measures. To address this challenge, some research has proposed threat detection methods based on provenance graphs, which leverage entity relationships such as processes, files, and sockets found in host audit logs. However, these methods are generally inefficient, especially when faced with massive audit logs and the computational resource-intensive nature of graph algorithms. Effectively and economically extracting APT attack clues from massive system audit logs remains a significant challenge. To tackle this problem, this paper introduces the ProcSAGE method, which detects threats based on abnormal behavior patterns, offering high accuracy, low cost, and independence from expert knowledge. ProcSAGE focuses on processes or threads in host audit logs during the graph construction phase to effectively control the scale of provenance graphs and reduce performance overhead. Additionally, in the feature extraction phase, ProcSAGE considers information about the processes or threads themselves and their neighboring nodes to accurately characterize them and enhance model accuracy. In order to verify the effectiveness of the ProcSAGE method, this study conducted a comprehensive evaluation on the StreamSpot dataset. The experimental results show that the ProcSAGE method can significantly reduce the time and memory consumption in the threat detection process while improving the accuracy, and the optimization effect becomes more significant as the data size expands.

Ulcerative colitis (UC) is a chronic intestinal disorder characterized by severe intestinal inflammation and superficial mucosal ulcers. Ramulus mori alkaloids (SZ-A) were approved by the National Medical Products Administration of China in 2020 for the treatment of type 2 diabetes mellitus. Later studies confirmed that SZ-A act on multiple inflammatory pathways to exert anti-inflammatory effects, suggesting that SZ-A has the potential to alleviate UC. A temperature-sensitive hydrogel embedded with sodium alginate (SA)-chitosan (CS) microspheres was constructed for colon-targeted delivery of SZ-A. The results showed that the microspheres prepared by exogenous emulsification had rounded and smooth surfaces with high drug-loading capacity. The optimum preparation conditions were as follows: 600 rpm stirring speed; a 1:4 ratio of water-to-oil phase; and a 5% Span80 emulsifier. The temperature-sensitive hydrogels embedded with SA-CS microspheres (TMH) had a moderate gelling temperature of 31.8 ± 0.74°C. The rheologic results showed that the internal structure of TMH was stable with viscoelasticity, and the in vitro release results indicated that the TMH exhibited slow-release performance. The findings suggest that TMH has suitable gelling temperature and viscoelasticity, and may be a promising targeted delivery vector for UC treatment.

Abstract Despite the growing attention on blockchain, phishing activities have surged, particularly on newly established chains. Acknowledging the challenge of limited intelligence in the early stages of new chains, we propose ADA-Spear-an automatic phishing detection model utilizing adversarial domain adaptive learning which symbolizes the method’s ability to penetrate various heterogeneous blockchains for phishing detection. The model effectively identifies phishing behavior in new chains with limited reliable labels, addressing challenges such as significant distribution drift, low attribute overlap, and limited inter-chain connections. Our approach includes a subgraph construction strategy to align heterogeneous chains, a layered deep learning encoder capturing both temporal and spatial information, and integrated adversarial domain adaptive learning in end-to-end model training. Validation in Ethereum, Bitcoin, and EOSIO environments demonstrates ADA-Spear’s effectiveness, achieving an average F1 score of 77.41 on new chains after knowledge transfer, surpassing existing detection methods.

Abstract Background Epidermal patterning factor / -like (EPF/EPFL) gene family encodes a class of cysteine-rich secretory peptides, which are widelyfound in terrestrial plants.Multiple studies has indicated that EPF/EPFLs might play significant roles in coordinating plant development and growth, especially as the morphogenesis processes of stoma, awn, stamen, and fruit skin. However, few research on EPF/EPFL gene family was reported in Gossypium. Results We separately identified 20 G. raimondii, 24 G. arboreum, 44 G. hirsutum, and 44 G. barbadense EPF/EPFL genes in the 4 representative cotton species, which were divided into four clades together with 11 Arabidopsis thaliana, 13 Oryza sativa, and 17 Selaginella moellendorffii ones based on their evolutionary relationships. The similar gene structure and common motifs indicated the high conservation among the EPF/EPFL members, while the uneven distribution in chromosomes implied the variability during the long-term evolutionary process. Hundreds of collinearity relationships were identified from the pairwise comparisons of intraspecifc and interspecific genomes, which illustrated gene duplication might contribute to the expansion of cotton EPF/EPFL gene family. A total of 15 kinds of cis-regulatory elements were predicted in the promoter regions, and divided into three major categories relevant to the biological processes of development and growth, plant hormone response, and abiotic stress response. Having performing the expression pattern analyses with the basic of the published RNA-seq data, we found most of GhEPF/EPFL and GbEPF/EPFL genes presented the relatively low expression levels among the 9 tissues or organs, while showed more dramatically different responses to high/low temperature and salt or drought stresses. Combined with transcriptome data of developing ovules and fibers and quantitative Real-time PCR results (qRT-PCR) of 15 highly expressed GhEPF/EPFL genes, it could be deduced that the cotton EPF/EPFL genes were closely related with fiber development. Additionally, the networks of protein–protein interacting among EPF/EPFLs concentrated on the cores of GhEPF1 and GhEPF7, and thosefunctional enrichment analyses indicated that most of EPF/EPFLs participate in the GO (Gene Ontology) terms of stomatal development and plant epidermis development, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways of DNA or base excision repair. Conclusion Totally, 132 EPF/EPFL genes were identified for the first time in cotton, whose bioinformatic analyses of cis-regulatory elements and expression patterns combined with qRT-PCR experiments to prove the potential functions in the biological processes of plant growth and responding to abiotic stresses, specifically in the fiber development. These results not only provide comprehensive and valuable information for cotton EPF/EPFL gene family, but also lay solid foundation for screening candidate EPF/EPFL genes in further cotton breeding.

Background This study aimed to examine whether baseline atherosclerosis was associated with subsequent short‐term domain‐specific cognitive decline. Methods and Results This research was based on the BRAVE (Beijing Research on Aging and Vessel) study, a population‐based prospective cohort study of adults aged 40 to 80 years, free of dementia. At baseline (wave 1, 2019), cognitive assessments and atherosclerosis measures, including carotid intima‐media thickness, carotid plaques, coronary artery calcification, and brachial–ankle pulse wave velocity were conducted. Cognitive function was reassessed in wave 2 (2022–2023) using linear mixed models for analysis. A total of 932 participants (63.7% women; mean age, 60.0±6.9 years) were included. Compared with the lowest tertile of carotid intima‐media thickness, carotid plaques, and brachial–ankle pulse wave velocity, or a coronary artery calcification score=0, the highest tertile of carotid intima‐media thickness (β=−0.065 SD/y [95% CI, −0.112 to −0.017]; P=0.008), carotid plaques (β=−0.070 SD/y [95% CI, −0.130 to −0.011]; P=0.021), and brachial–ankle pulse wave velocity (β=−0.057 SD/y [95% CI, −0.105 to −0.010]; P=0.018), and a coronary artery calcification score≥400 (β=−0.081 SD/y [95% CI, −0.153 to −0.008]; P=0.029) were significantly associated with a faster decline in semantic fluency after multivariable adjustment. Moreover, greater carotid intima‐media thickness, coronary artery calcification, and brachial–ankle pulse wave velocity were significantly associated with a faster decline in global cognition. Conclusions More significant atherosclerosis was associated with faster semantic fluency and global cognition declines.

Calcium-Dependent Protein Kinases (CDPKs) are a class of serine/threonine protein kinases encoded by several gene families that play key roles in biotic and abiotic stresses response and plant growth and development. However, snow lotus (Saussurea involucrata kar L.) CDPKs has rarely been reported. In this study, 20 CDPK genes in snow lotus were identified based on transcriptome data and classified into four groups (I-IV) based on their structural features and phylogenetic analyses. Among them, the transcript levels of SikCDPK1 were significantly induced by low temperature and multiple hormone treatments, and SikCDPK1 gene was found to have different expression in snow lotus seeds, leaves, stems and roots. The full-length promoter activity of SikCDPK1 gene was higher than that of the 5’ end deletion fragment, and the promoter fragment containing the low temperature inducing element had increased activation after low temperature treatment. The promoter activity of SikCDPK1 gene was mainly expressed in roots and rosette leaves. In addition, overexpressing plants of SikCDPK1 were more tolerant compared to the wild type after being subjected to low temperature stress. Physiological analyses indicated that SikCDPK1 improved plant tolerance to low temperature stress by maintaining cell membrane stability and reducing the accumulation of reactive oxygen species (ROS). These findings provided insights into CDPK gene families in snow lotus and broaden our understanding of the biological role of SikCDPK1 and the mechanism of low temperature stress tolerance in snow lotus.

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.

The Cu–Cr alloys with magnesium and yttrium exhibit appealing high-strength and high-conductivity (HSHC) characteristics. Anticipated contributions to the design of HSHC copper alloys include new insights from understanding the phase equilibria, solidified microstructure, and thermodynamics of the Cu–Cr–X (X = Mg, Y) systems. Five Cu–Cr–Y alloys and three Cu–Cr–Mg alloys were melted through arc melting and powder metallurgy, respectively. An analysis was conducted on the primary phases and solidification path of the as-cast Cu–Cr–Y alloys. Five three-phase regions in the Cu–Cr–Y system and three in the Cu–Cr–Mg system at the isothermal sections of 673 K were identified using XRD and EPMA. No ternary compound was discovered among either of these systems. The agreement between the experimental data and the calculated isothermal sections and liquidus projection derived from the thermodynamic description of the binary systems is quite good. The investigation on phase equilibria in Cu–Cr–X (X = Mg, Y) systems in this study helps in developing the thermodynamic database for multi-component copper alloys.

Abstract Due to global warming and the disturbance of the interannual variability of precipitation, the frequency of extreme drought events has increased. The impact of global climate change on water resources is becoming increasingly apparent, then it is particularly necessary to explore the carrying capacity of water ecological environment under extreme drought conditions, which can guarantee the ecological water security in river basins. This study takes the Guanzhong area of the Wei River Basin as an example, calculating the water environment carrying capacity of 40 areas in the Weihe Guanzhong area in different levels of years under extreme drought conditions by comprehensive evaluation model of carrying capacity and using geographic information system GIS to display the spatial distribution of water environment carrying capacity in 40 regions. According to the results of the spatial distribution of water environmental bearing capacity, four different schemes are designed to improve the bearing capacity. The first plan reduces the industrial water consumption and irrigation quota by 5%, the second plan increases the industrial water and sewage treatment rate on this basis. the third plan further improves the development and utilization rate of surface and groundwater, and the fourth plan, on the basis of the first three plans, supplies 600 million cubic meters of industrial and agricultural water to Guanzhong region. Through comparative analysis, without taking any measures, under the extreme drought conditions, the water environment carrying capacity of the 40 areas in Guanzhong is all in an unbearable state. Overall, plan 4 has the most significant improvement in the water environment-carrying capacity, especially the Dong zhuang Reservoir of the Jing River which has played a very important role in enhancing the water ecological environment carrying capacity of the downstream water of the Wei River.

In recent years, extensive research on dynamic precipitation has led to a growing interest in exploring how deformation affects microstructure and mechanical properties. In this study, the response of microstructure and performance to cold pre-strain and the early aging stage in the Al–Zn–Mg–Cu alloy was investigated using a combination of modelling and experimental approaches. A Kampmann-Wagner based numerical framework was developed and applied to the Al–Zn–Mg–Cu alloy. The deformation or quenching induced dislocations and vacancies, their dynamics and acceleration on the diffusivities of solute atoms, and the competition between homogeneous and heterogeneous nucleation were considered in the framework. The effect of the different pre-strain levels (0%–10%) on the evolution of vacancies, dislocations, precipitation kinetics and hardening are given in detail. The results suggest that the acceleration of precipitation kinetics and hardening during the aging process following pre-strain is primarily attributed to the overall increase in diffusivity resulting from deformation-induced dislocations, rather than vacancies. The simulation framework developed in the current work effectively captures the evolution of microstructure and mechanical properties, which has significant practical implications for materials manufacturing.

Abstract As a progressive security strategy, the zero trust model has attracted notable attention and importance within the realm of network security, especially in the context of the Internet of Things (IoT). This paper aims to evaluate the current research regarding zero trust and to highlight its practical applications in the IoT sphere through extensive bibliometric analysis. We also delve into the vulnerabilities of IoT and explore the potential role of zero trust security in mitigating these risks via a thorough review of relevant security schemes. Nevertheless, the challenges associated with implementing zero trust security are acknowledged. We provide a summary of these issues and suggest possible pathways for future research aimed at overcoming these challenges. Ultimately, this study aims to serve as a strategic analysis of the zero trust model, intending to empower scholars in the field to pursue deeper and more focused research in the future.

Unhealthy aging causes the development of various diseases, which makes intervening in key targets an important breakthrough in the development of new drugs to delay aging and prevent age-related diseases. Regulating gut microbiota has become a potential intervention pathway for anti-aging. Modern studies have shown that polysaccharides, the main active ingredients of traditional Chinese medicine (TCM), have multi-target advantages in the mechanisms of action of anti-aging. Non-starch polysaccharides are degraded by the gut microbiota in vivo to produce short-chain fatty acids to enable the local and systemic physiological functions have also been confirmed, but the researches on how TCM polysaccharides can exert anti-aging by the regulation of the gut microbiota and its metabolites lack systematic review. This review describes changes in the gut microbiota with age, and how it causes the pathogenesis of age-related diseases. It summarizes the effects of TCM polysaccharides in interfering with aging, the process of regulating gut microbiota to exert anti-ageing activity through the mediation of AMPK, Nrf2, and NF-κB signaling pathways and other potential intervention pathways. Finally, this review summarizes laws that changes in molecular weight and monosaccharide composition affect the role of polysaccharides in the intestinal microenvironment thereby altering the function of gut microbiota.

IntroductionKaempferol, a flavonoid found in numerous foods and medicinal plants, offers a range of health benefits such as anti-inflammatory, antioxidant, antiviral, anticancer, cardioprotective, and neuroprotective effects.MethodsHerein, a bibliometric and visual analysis of global publications on kaempferol was performed to map the evolution of frontiers and hotspots in the field. Using the search string TS = kaempferol, bibliometric data for this analysis was extracted from the Web of Science Core Collection database and analyzed using the VOSviewer, CiteSpace, and Scimago Graphica software.ResultsAs a result, by February 26, 2024, 11,214 publications were identified, comprising articles (n = 10,746, 96%) and review articles (n = 468, 4%). Globally, the annual number of kaempferol publications surpassed 100 per year since 2000, exceeded 500 per year since 2018, and further crossed the threshold of 1,000 per year starting in 2022. The major contributing countries were China, the United States of America, and India, while the top three institutes of the citations of kaempferol were the Chinese Academy of Sciences, Consejo Superio de Investigaciones Cientficas, and Uniersidade do Porto. These publications were mainly published in agricultural and food chemistry journals, food chemistry, and phytochemistry.DiscussionThe keywords frequently mentioned include phenolic compounds, antioxidant activity, flavonoids, NF-kappa B, inflammation, bioactive compounds, etc. Anti-inflammation, anti-oxidation, and anti-cancer have consistently been the focus of kaempferol research, while cardiovascular protection, neuroprotection, antiviral, and anti-bacterial effects have emerged as recent highlights. The field of kaempferol research is thriving.

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.

Phenanthroindolizidine alkaloids (PAs) are a series of compounds that have been isolated from traditional herbal medicines and have significant therapeutic potential, such as anti-arthritic, anti-viral, anti-inflammatory, and anti-glioma effects in vitro and in vivo . This study aimed to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics of 44 compounds in silico and to verify the ADMET characteristics. The 2-dimensional structures of these compounds were generated using ChemDraw and the characteristics were predicted using ADMET Predictor™ software. Key characteristics, such as p K a , log P /log D , solubility, permeability, absolute bioavailability in rats, and preliminary toxicity, were measured on some typical compounds to verify the accuracy of the prediction results. The results showed that ADMET predicts physicochemical and biological properties quickly and accurately for PAs. PAs are biopharmaceutics classification system (BCS) class IV compounds with low bioavailability. Moreover, these compounds have higher lipophilicity and are easily distributed into the brain after oral administration to treat brain diseases. However, some of these compounds exhibited colonic toxicity. To improve the drug-like availability of these compounds, more in-depth research should be conducted on drug delivery systems.

Calcium-based biomaterials have been intensively studied in the field of drug delivery owing to their excellent biocompatibility and biodegradability. Calcium-based materials can also deliver contrast agents, which can enhance real-time imaging and exert a Ca2+-interfering therapeutic effect. Based on these characteristics, amorphous calcium carbonate (ACC), as a brunch of calcium-based biomaterials, has the potential to become a widely used biomaterial. Highly functional ACC can be either discovered in natural organisms or obtained by chemical synthesis However, the standalone presence of ACC is unstable in vivo. Additives are required to be used as stabilizers or core–shell structures formed by permeable layers or lipids with modified molecules constructed to maintain the stability of ACC until the ACC carrier reaches its destination. ACC has high chemical instability and can produce biocompatible products when exposed to an acidic condition in vivo, such as Ca2+ with an immune-regulating ability and CO2 with an imaging-enhancing ability. Owing to these characteristics, ACC has been studied for self-sacrificing templates of carrier construction, targeted delivery of oncology drugs, immunomodulation, tumor imaging, tissue engineering, and calcium supplementation. Emphasis in this paper has been placed on the origin, structural features, and multiple applications of ACC. Meanwhile, ACC faces many challenges in clinical translation, and long-term basic research is required to overcome these challenges. We hope that this study will contribute to future innovative research on ACC.

Obesity and related metabolic syndromes have been recognized as important disease risks, in which the role of adipokines cannot be ignored. Adiponectin (ADP) is one of the key adipokines with various beneficial effects, including improving glucose and lipid metabolism, enhancing insulin sensitivity, reducing oxidative stress and inflammation, promoting ceramides degradation, and stimulating adipose tissue vascularity. Based on those, it can serve as a positive regulator in many metabolic syndromes, such as type 2 diabetes (T2D), cardiovascular diseases, non-alcoholic fatty liver disease (NAFLD), sarcopenia, neurodegenerative diseases, and certain cancers. Therefore, a promising therapeutic approach for treating various metabolic diseases may involve elevating ADP levels or activating ADP receptors. The modulation of ADP genes, multimerization, and secretion covers the main processes of ADP generation, providing a comprehensive orientation for the development of more appropriate therapeutic strategies. In order to have a deeper understanding of ADP, this paper will provide an all-encompassing review of ADP.

BackgroundRosacea, a chronic inflammatory skin condition affecting millions worldwide, is influenced by complex interactions between genetic and environmental factors. Although gut microbiota’s role in skin health is well-acknowledged, definitive causal links between gut microbiota and rosacea remain under-explored.MethodsUsing a two-sample Mendelian randomization (MR) design, this study examined potential causal relationships between gut microbiota and rosacea. Data was sourced from the largest Genome-Wide Association Study (GWAS) for gut microbiota and the FinnGen biobank for rosacea. A total of 2078 single nucleotide polymorphisms (SNPs) associated with gut microbiota were identified and analyzed using a suite of MR techniques to discern causal effects.ResultsThe study identified a protective role against rosacea for two bacterial genera: phylum Actinobacteria and genus Butyrivibrio. Furthermore, 14 gut microbiota taxa were discovered to exert significant causal effects on variant categories of rosacea. While none of these results met the strict False Discovery Rate correction threshold, they retained nominal significance. MR outcomes showed no pleiotropy, with homogeneity observed across selected SNPs. Directionality tests pointed toward a robust causative path from gut microbiota to rosacea.ConclusionThis study provides compelling evidence of the gut microbiota’s nominal causal influence on rosacea, shedding light on the gut-skin axis’s intricacies and offering potential avenues for therapeutic interventions in rosacea management. Further research is warranted to validate these findings and explore their clinical implications.

Although numerous photothermal nanoparticles have been designed to improve the enhanced and permeability and retention (EPR) effect, the delivery of nanoparticles to the tumor site remains a major obstacle in cancer treatment. The interstital structure and its internal fluid that play an important role in material transmission, intercellular signal transduction, tissue morphology, immunity, tumor development, and disease diagnosis and treatment may be considered as a new route for drug delivery. Here, we prepared a nanoplatform composed of polydopamine (PDA), indocyanine green (ICG) as a photothermal agent, and paclitaxel (PTX) as a chemotherapeutic drug. The designed PDA-ICG nanoparticles displayed excellent photothermal conversion ability, with the synergistic effect of PTX, the growth of MDA-MB-231 cells was significantly suppressed with the cell viability of 6.19% in vitro. Taking advantage of bioimaging ability of ICG, tumor-targeting of the nanoparticles injected into the interstitial space was study, Compared with intravenous injection, nanoparticles better targeted the tumor based on the interstitial fluid flow in MBA-MD-231 bearing mice. Furthermore, the antitumor efficacy was studied in vivo. With the improved accumulation of PDA-ICG-PTX nanoparticles injected into the interstitial space and the synergistic effect of photothermal therapy and chemotherapy, tumor growth was inhibited without obvious side effects. These results demonstrated that interstitial space injection may be a superior administration route for tumor-targeting nanoparticles. The PDA-ICG-PTX nanoparticles delivered via the interstitial space exhibit great potential in the photothermal chemotherapy of cancers.

Fluidized bed granulation (FBG) is a widely used granulation technology in the pharmaceutical industry. However, defluidization caused by the formation of large aggregates poses a challenge to FBG, particularly in traditional Chinese medicine (TCM) due to its complex physicochemical properties of aqueous extracts. Therefore, this study aims to identify the complex relationships between physicochemical characteristics and defluidization using data mining methods. Initially, 50 types of TCM were decocted and assessed for their potential influence on defluidization using a set of 11 physical properties and 10 chemical components, utilizing the loss rate as an evaluation index. Subsequently, the random forest (RF) and Apriori algorithms were utilized to uncover intricate association rules among physicochemical characteristics and defluidization. The RF algorithm analysis revealed the top 8 critical factors associated with defluidization. These factors include physical properties like glass transition temperature (Tg) and dynamic surface tension (DST) of DST100ms, DST1000ms, DST10ms and conductivity, in addition to chemical components such as fructose, glucose and protein contents. The results from Apriori algorithm demonstrated that lower Tg and conductivity were associated with an increased risk of defluidization, resulting in a higher loss rate. Moreover, DST100ms, DST1000ms and DST10ms exhibited a contrasting trend in the physical properties Specifically, defluidization probability increases when Tg and conductivity dip below 29.04℃ and 6.21 ms/m respectively, coupled with DST10ms, DST100ms and DST1000ms values exceeding 70.40 mN/m, 66.66 mN/m and 61.58 mN/m, respectively. Moreover, an elevated content of low molecular weight saccharides was associated with a higher occurrence of defluidization, accompanied by an increased loss rate. In contrast, protein content displayed an opposite trend regarding chemical properties. Precisely, the defluidization likelihood amplifies when fructose and glucose contents surpass 20.35 mg/g and 34.05 mg/g respectively, and protein concentration is less than 1.63 mg/g. Finally, evaluation criteria for defluidization were proposed based on these results, which could be used to avoid this situation during the granulation process. This study demonstrated that the RF and Apriori algorithms are effective data mining methods capable of uncovering key factors affecting defluidization.

Abstract Ethereum’s high attention, rich business, certain anonymity, and untraceability have attracted a group of attackers. Cybercrime on it has become increasingly rampant, among which scam behavior is convenient, cryptic, antagonistic and resulting in large economic losses. So we consider the scam behavior on Ethereum and investigate it at the node interaction level. Based on the life cycle and risk identification points we found, we propose an automatic detection model named Aparecium. First, a graph generation method which focus on the scam life cycle is adopted to mitigate the sparsity of the scam behaviors. Second, the life cycle patterns are delicate modeled because of the crypticity and antagonism of Ethereum scam behaviors. Conducting experiments in the wild Ethereum datasets, we prove Aparecium is effective which the precision, recall and F1-score achieve at 0.977, 0.957 and 0.967 respectively.

Abstract The illegal use of compromised email accounts by adversaries can have severe consequences for enterprises and society. Detecting compromised email accounts is more challenging than in the social network field, where email accounts have only a few interaction events (sending and receiving). To address the issue of insufficient features, we propose a novel approach to detecting compromised accounts by combining time zone differences and alternate logins to identify abnormal behavior. Based on this approach, we propose a compromised email account detection framework that relies on widely available and less sensitive login logs and does not require labels. Our framework characterizes login behaviors to identify logins that do not belong to the account owner and outputs a list of account-subnet pairs ranked by their likelihood of having abnormal login relationships. This approach reduces the number of account-subnet pairs that need to be investigated and provides a reference for investigation priority. Our evaluation demonstrates that our method can detect most email accounts that have been accessed by disclosed malicious IP addresses and outperforms similar research. Additionally, our framework has the capability to uncover undisclosed malicious IP addresses.

As a new type of high-performance material, gradient structural steel is widely used in engineering fields due to its unique microstructure and excellent mechanical properties. For the prevalent fatigue failure problem, the rate of change in the local grain size gradients along the structure (referred to as the gradient rate) is a key parameter in the design of gradient structures, which significantly affects the fatigue performance of gradient structural steel. In this study, a new method of ‘Voronoi primary + secondary modeling’ is adopted to successfully establish three typical high-strength steel models corresponding to the convex-, linear-, and concave-type gradient rates for gradient structures, focusing on the stress–strain response and crack propagation in structural steel with different gradient rates under cyclic loading. It was found that the concave gradient rate structural model is dominated by finer grains with larger volume fraction, which is conducive to hindering fatigue crack propagation and has the longest fatigue life, which is 16.16% longer than that of the linear gradient rate structure and 23.66% longer than that of the convex gradient rate structure. The simulation results in this study are consistent with the relevant experimental phenomena. Therefore, when regulating the gradient rate, priority should be given to increasing the volume fraction of fine grains and designing a gradient rate structure dominated by fine grains to improve the fatigue life of the material. This study presents a new strategy for designing engineering materials with better service performance.

Nebulized inhalation offers a noninvasive method for delivering drugs to treat both local respiratory and systemic diseases. In this study, insulin was used as a model drug to design a series of deformable nanovesicles (DNVs) with key quality attributes, including particle size, deformability, and drug load capacity. We investigated the effects of these properties on aerosol generation, macrophage phagocytosis, and bloodstream penetration. The results showed that deformability improved nebulization performance and reduced macrophage phagocytosis, benefiting local and systemic delivery. However, the advantage of DNVs for transmembrane penetration was not evident in the alveolar epithelium. Within the size range of 80–490 nm, the smaller the particle size of IPC-DNVs, the easier it is to evade clearance by macrophages and the more effective the in vivo hypoglycemic efficacy will be. In the drug load range of 3–5 mg/mL, a lower drug load resulted in better hypoglycemic efficacy. The area above the blood glucose decline curve with time (AAC) of nebulized DNVs was 2.32 times higher than that of the insulin solution, demonstrating the feasibility and advantages of DNVs in the pulmonary delivery of biomacromolecule drugs. This study provides insights into the construction and formulation optimization of pulmonary delivery carriers.

Abstract Background The development of cotton fiber is regulated by the orchestrated binding of regulatory proteins to cis-regulatory elements associated with developmental genes. The cis–trans regulatory dynamics occurred throughout the course of cotton fiber development are elusive. Here we generated genome-wide high-resolution DNase I hypersensitive sites (DHSs) maps to understand the regulatory mechanisms of cotton ovule and fiber development. Results We generated DNase I hypersensitive site (DHS) profiles from cotton ovules at 0 and 3 days post anthesis (DPA) and fibers at 8, 12, 15, and 18 DPA. We obtained a total of 1185 million reads and identified a total of 199,351 DHSs through ~ 30% unique mapping reads. It should be noted that more than half of DNase-seq reads mapped multiple genome locations and were not analyzed in order to achieve a high specificity of peak profile and to avoid bias from repetitive genomic regions. Distinct chromatin accessibilities were observed in the ovules (0 and 3 DPA) compared to the fiber elongation stages (8, 12, 15, and 18 DPA). Besides, the chromatin accessibility during ovules was particularly elevated in genomic regions enriched with transposable elements (TEs) and genes in TE-enriched regions were involved in ovule cell division. We analyzed cis-regulatory modules and revealed the influence of hormones on fiber development from the regulatory divergence of transcription factor (TF) motifs. Finally, we constructed a reliable regulatory network of TFs related to ovule and fiber development based on chromatin accessibility and gene co-expression network. From this network, we discovered a novel TF, WRKY46, which may shape fiber development by regulating the lignin content. Conclusions Our results not only reveal the contribution of TEs in fiber development, but also predict and validate the TFs related to fiber development, which will benefit the research of cotton fiber molecular breeding.

PurposeTo investigate the relationship between optic disc morphology, axial length, and regional distribution of retinal vessels in healthy eyes of young adults.MethodsNine hundred and two healthy eyes were enrolled in this university-based, cross-sectional study. Spectral-domain optical coherence tomography angiography was used to measure the parapapillary retinal vessel density. We automated the process of calculating optic disc tilt and rotation by using a program written in Python. Relationships between optic disc rotation, optic disc tilt, parapapillary vessel density, and other ocular parameters were analyzed using regression models.ResultsAs axial length increased, optic disc morphology became more tilted and rotated inferiorly. The superficial vessel density (SVD) and radial peripapillary capillary density (RPCD) gradually decreased in all regions except for the temporal quadrant. Increased temporal SVD (OR [95% CI] = 1.081 [1.039, 1.124], p

Highlights Periplaneta americana L. derived exosome-like nanoparticles (PA-ELNs) as a novel wound healing accelerator was isolated and proved. Protein and small RNA components in PA-ELNs were characterized by omics technology. PA-ELNs remarkably accelerated diabetic wound healing, and were involved in anti-inflammatory, re-epithelialization and autophagy regulation in this process.

The accurate diffusivity and kinetic database of fcc quinary Cu–Co–Mn–Ni–Si system is essential for designing high-performance Cu alloys, which is still not investigated yet. In the present work, on the basis of the critically reviewed experimental diffusivities available in the literature, the atomic mobilities of fcc Mn–Ni and Cu–Mn–Ni alloys were re-assessed through CALTPP (CALculation of ThermoPhysical Properties) program, aiming to establish a self-consistent kinetic database for fcc Cu–Co–Mn–Ni–Si system. Comparing the model-calculated diffusion coefficients, composition profiles and diffusion paths with the measured ones for fcc Mn–Ni and fcc Cu–Mn–Ni alloys, it is found that the experimental data are reasonably reproduced by the re-assessed atomic mobilities, indicating their good reliability. Therefore, integrating the presently obtained atomic mobilities for the fcc Mn–Ni and fcc Cu–Mn–Ni systems with those for other sub-systems, a complete kinetic database for fcc Cu–Co–Mn–Ni–Si system was established for the first time. The reliability of the constructed kinetic database was confirmed by the reasonable agreements between the model-predicted composition profiles of sub-quaternary and quinary diffusion couples and the measured ones. Furthermore, this obtained kinetic database was applied to simulate the microstructure evolution of second-phase precipitates in Cu–Mn–Ni, Cu–Ni–Si and Cu–Ni–Co–Si alloys during the aging process, and the simulated results demonstrate good agreements with the experimental ones. The present work indicates the reliability and significance of the presently obtained kinetic database of fcc quinary Cu–Co–Mn–Ni–Si system for predicting the microstructure evolution during the heat treatment process, which can greatly contribute to the design of Cu alloys with high performance.

Aiming at the problems that “over optimizing” the quality of steganographic text and lack of constraints on the semantic expression of the generated steganographic text in existing generative text steganography methods, a generative text steganography method was proposed based on emotional expression in semantic space.In order to make use of the scene fusion provided by the new media platform to obtain many camouflage scenes, the focus was how to use the unsupervised extraction model to extract the emotional expression combination candidate set from the original data set, then sort the candidate set of emotional expression combinations based on the improved bipartite graph sorting algorithm to obtain the emotional expression combination set, map them to the semantic space, and then implement embedding secret information while generating the user’s opinions based on the emotion expression combinations.Experimental results show that, compared with the existing generative text steganography methods in semantic space, the product reviews generated by the proposed method have a minimum perplexity of 10.536, and have a strong correlation with the chosen product, which can further guarantee the cognitive concealment of steganographic texts.At the same time, the proposed method can also be effectively used in the field of secure and confidential communication, and can avoid the senders being traced and analyzed.

Atherosclerosis is the main pathological basis of cardiovascular diseases (CVDs). Fufang Danshen Tablet (FDT) is a traditional Chinese medicine that has been clinically used to treat CVDs for more than 40 years. Nevertheless, owing to the complexity of the ingredients, the pharmacological mechanism of FDT in the treatment of CVDs has not been fully elucidated. In this study, an integrated strategy of UFLC-Q-TOF-MS/MS, network pharmacology, molecular biology, and transcriptomics was used to elucidate the mechanisms of action of FDT in the treatment of atherosclerosis. In total, 22 absorbed constituents were identified in rat serum after oral administration of FDT. In silico, network pharmacology studies have shown that FDT regulates four key biological functional modules for the treatment of atherosclerosis: oxidative stress, cell apoptosis, energy metabolism, and immune/inflammation. In animal experiments, FDT exerted protective effects against atherosclerosis by reducing the plaque area and lipid levels in ApoE−/− mice. Furthermore, we found that FDT inhibited inflammatory macrophage accumulation by regulating the expression of Selp and Ccl2, which are both involved in monocyte adhesion and migration. The inhibition of monocyte recruitment by FDT is a new perspective to elucidate the anti-atherosclerotic mechanism of FDT, which has not been adopted in previous studies on FDT. Our results may help to elucidate the therapeutic mechanism of FDT against CVDs and provide potential therapeutic targets.

The discovery of a simple and efficient detection method for biothiols would be scientifically significant due to the crucial role of them in various physiological processes. Recently, a simple fluorescent probe, DEMCA-NBSC, based on coumarin fragments, was developed by Ding et al., and provided an efficient way for real-time sensing of biothiols both in vivo and vitro. Theoretical insights to the fluorescence sensing mechanism of the probe were provided in this work. Details of the electron transfer process in the probe under optical excitation and the fluorescent character of the probe were analyzed using a quantum mechanical method. All these theoretical results could inspire the development of a highly convenient and efficient fluorescent probe to sense biothiols both in vivo and vitro.

Thermal conductivity, one of critical properties for composite materials, constitutes an indispensable part of high-efficient materials design. However, a quantitative model to describe the thermal conductivity of two-phase composites has yet to be developed. In this work, we proposed an effective evaluation framework of a microstructure-based thermal conductivity model with key inputs from CALPHAD-type approach. Two-phase WC-Ni composites with Ni–W solid-solution matrix were used as the target system to validate this framework combined with key thermal conductivity measurements. Calculated thermal conductivities agree well with experimental results within the experimental error of 10%. Applying this well-established framework, thermal conductivities depending on wide ranges of temperature, WC grain size (dWC), and phase constitution are predicted, suggesting some unique features. The thermal conductivity becomes less dependent on dWC when dWC is >3 μm. Additionally, the thermal conductivity of nano-sized WC-Ni shows a quite different temperature-dependent variation tendency in contrast to that of micron-sized WC-Ni. These correlations are found and quantitatively described in the present work. Furthermore, the thermal conductivity for WC-Ni carbide rolls is predicted by the established framework, demonstrating a high accuracy. The present work is expected to guide the design of composite materials with desirable thermal properties efficiently.

Lipid nanoemulsions are promising nanodrug delivery carriers that can improve the efficacy and safety of paclitaxel (PTX). However, no intravenous lipid emulsion of PTX has been approved for clinical treatment, and systemic safety profiles have not yet been reported. Here we outline the development of a PTX-loaded tumor-targeting intravenous lipid emulsion (PTX Emul) and describe its characteristics, colloidal stability, and systemic safety profiles in terms of acute toxicity, long-term toxicity, and toxicokinetics. We also compare PTX Emul with conventional PTX injection. Results showed that PTX Emul exhibited an ideal average particle size (approximately 160 nm) with narrow size distribution and robust colloidal stability under different conditions. Hypersensitivity reaction and hemolysis tests revealed that PTX Emul did not induce hypersensitivity reactions and had no hemolytic potential. In addition, where the alleviated systemic toxicity of PTX Emul may be attributed to the altered toxicokinetic characteristics in beagle dogs, including the decreased AUC and increased plasma clearance and volume of distribution, PTX Emul alleviated acute and long-term toxicity as evidenced by the enhanced the median lethal dose and approximate lethal dose, moderate body weight change, decreased bone marrow suppression and organ toxicity compared with those under PTX injection at the same dose. A fundamental understanding of the systemic safety profiles, high tumor-targeting efficiency, and superior antitumor activity in vivo of PTX Emul can provide powerful evidence of its therapeutic potential as a future treatment for breast cancer.

The subtransient reactance Xd′′and transient reactance Xd′of large-capacity alternators are crucial parameters to determine the fault current magnitude and design the protection system for the machine. The traditional calculation method of Xd′′and Xd′will bring errors in the graphical decomposition process which depends on the subjective judgement of different individuals, and the analytical method is also inherently imprecise. In this paper, the superconductor simulation method (SSM) incorporated with field-circuit coupled finite element model is presented. The SSM has high accuracy and is capable of considering the saturation effect, skin effect and arbitrary structure of the machine. The unsaturated and saturated values of Xd′′and Xd′of a pumped storage machine are calculated with the proposed SSM. The method of establishing the field-circuit coupled model, governing equations and the superconductor simulation method are introduced in detail. The short-circuit test is conducted on the real machine and the calculated results of both Xd′′and Xd′are verified by the measured values.

Tumor-associated macrophages (TAMs) are key contributors to tumor development, accelerated tumor invasion and metastasis, and induction of immunosuppression. Targeted delivery of immunomodulatory agents to promote polarization of TAMs may alleviate the immunosuppressive tumor microenvironment. Calcium carbonate nanoparticles (CCN), which exhibit excellent biocompatibility, pH sensitivity, and easy surface modification, have attracted substantial attention in targeted nano delivery. In this study, CCN were used as a matrix material to develop UNO-peptide-modified lipid CCN for targeted immunomodulation of TAMs by using the mannose receptor overexpressed on the surfaces of TAMs as targets. The preparation of CCN was optimized through single-factor testing with the gas diffusion method with the particle size as the index. The surface modification of CCN with UNO-peptide-modified phospholipids was performed, and its targeting effect on TAMs was investigated. The average particle size of the CCN and UNO-peptide-modified CCN was 144.5 ± 3.8 nm and 167.0 ± 1.3 nm, respectively. UNO-peptide-modified CCN entered TAMs via actively targeted uptake mediated by mannose receptors. Our results demonstrated that the developed UNO-peptide-modified CCN with controlled nano-size and excellent TAMs-targeting properties is a highly promising nanocarrier for targeted delivery of TAM immunomodulatory agents.

Abstract Background Tiger bone, which had been one of the most famous traditional Chinese medicine for 2000 years, was originate from the skeleton of Panthera tigris L., and had the actions of anti-inflammatory, analgesic, immune-regulatory and promoting healing of bone fracture, and was used for the treatment of osteoporosis and rheumatoid arthritis. Jin-Tian-Ge (JTG), the artificial tiger bone powder, were prepared from skeletons of several farmed animals to substitute the natural tiger bone, and has been used for the treatment of osteoporosis in clinical practice. However, the characteristic and mechanism of action of JTG for the therapy of osteoporosis need to be further evidenced by using modern pharmacological methods. The aim of this work is to investigate the bone-protective effects of JTG, and explore the possible underlying mechanism. Methods Ovariectomy (OVX) rats were orally administrated JTG or estradiol valerate (EV) for 12 weeks. We investigated the pharmacodynamic effects of JTG on anti-bone loss in OVX rats, and also investigated the role of JTG in promoting osteogenesis and inhibiting osteoclast differentiation. Results JTG increased the bone mineral density (BMD), improved the bone microarchitecture and biomechanical properties in ovariectomized rast, whereas reversed the bone high turnover in OVX rats as evidenced by serum biochemical markers in OVX rats. JTG increased osteogenic differentiation of BMSCs in vitro, and up-regulated the expression of the key proteins of BMP and Wnt/β-catenin pathways. JTG also inhibited the osteoclastogenesis of BMM as evidenced by the alteration of the TRAP activity, F-actin construction and the expression of nuclear factor of activated T-cells cytoplasmic 1 (NFATc1), c-Fos, Cathepsin K (Ctsk) and matrix metallopeptidase 9 (MMP9) of OCs induced with RANKL and LPS, reduced the expression and phosphorylation of NF-κB in OCs. Conclusions JTG prevented bone loss in OVX rats and increased osteogenic differentiation of BMSCs through regulation of the BMP and Wnt/β-catenin pathway, inhibited osteoclastogenesis by suppressing the NF-κB pathway, suggesting that JTG had the potentials for prevention and treatment of osteoporosis by modulating formation and differentiation of osteoblast and osteoclast.

Objective: To compare the efficacy and safety of ethanol ablation (EA) and m icrowave ablation (MWA) in the treatment of cystic or predominantly cyst ic thyroid nodules. Methods: Patients with cystic or predominantly cystic thyroid nodules i ntervened with EA or MWA were retrospectively enrolled and divided into EA group (n = 30) and MWA group (n = 31). The volume and volume reduction rate (VRR) of thyroid nodules before ablation, and at 3 and 12 months after ablation were compared between the two groups. The effective rate (ER) and incidence of adverse events in both grou ps were recorded. Results: The median VRR and ER at 3 months after ablation were significa ntly higher in EA group than in MWA group (81.30% vs 75.76%, P = 0.011; 76.67% (23/30) vs 51.61% (16/31), P = 0.040), while no significant difference was detected at 12 months (93.39% vs 88.78%, P = 0.141; 86.67% (26/30) vs 87.10% (27/31), P = 0.960). The median VRR of small nodules in EA group was significantly higher than that in MWA group (81.30% vs 71.18%, P = 0.006; 93.40% vs 83.14%, P = 0.032). There was no significant difference of median VRR in medium nodules at final follow-up between MWA and EA group (93.01% vs 89.68%, P = 0.482). Serious adverse events were not reported in both groups. Conclusion: EA and MWA are both effective and safe in the treatment of cyst ic or predominantly cystic thyroid nodules. EA is more cost-effective and effective than MWA for small nodules, but it requires more cycles of treatment and may pose a higher risk of postoperative pain compared with MWA.

Abstract Domain name system (DNS), as one of the most critical internet infrastructure, has been abused by various cyber attacks. Current malicious domain detection capabilities are limited by insufficient credible label information, severe class imbalance, and incompact distribution of domain samples in different malicious activities. This paper proposes a malicious domain detection framework named PUMD, which innovatively introduces Positive and Unlabeled (PU) learning solution to solve the problem of insufficient label information, adopts customized sample weight to improve the impact of class imbalance, and effectively constructs evidence features based on resource overlapping to reduce the intra-class distance of malicious samples. Besides, a feature selection strategy based on permutation importance and binning is proposed to screen the most informative detection features. Finally, we conduct experiments on the open source real DNS traffic dataset provided by QI-ANXIN Technology Group to evaluate the PUMD framework’s ability to capture potential command and control (C&C) domains for malicious activities. The experimental results prove that PUMD can achieve the best detection performance under different label frequencies and class imbalance ratios.

As China continues to play an increasingly dynamic role in international society, attention to its cultural relevance is also on the rise. This is indicated in the global popularity of recent Chinese animated films adapted from Chinese folktale, such as Xiyouji zhi dasheng guilai (Monkey King: Hero is Back) (2015), Nezha zhi motong jiangshi (Ne Zha) (2019) and Baishe: Yuanqi (White Snake) (2019) in the global market. But while these films offer international society a new window to access Chinese culture, they also pose challenges presented by their innate Chinese elements which significantly differ from the West’s conventional presentation of Chinese culture. Since most Chinese animations are adapted from Chinese folktale which contains rich cultural elements that are context-dependant and exclusive to Chinese communities, intercultural interaction that happened within an animated film can include adaptation of the story from the original source to the script; intersemiotics translation from script to the audiovisual production; and interlingual translation which occurs in bilingual subtitles. Looking to the performance of Chinese animated films both at home and abroad, this paper aims to evaluate the above translation-related activities and the success of a Chinese animated film. Special attention will be paid to the extent to which cultural translation plays a role in the making of these animated films.

Presently, the essential oils are obtained by hydro-distillation, which demand long extracting time and great energy. Consequently, efficiently obtaining essential oils needs to be considered. In this work, microwave-assisted ionic liquids treatment followed by hydro-distillation (MILT-HD) is used to extract essential oils. The purpose is to use the multivariate analysis model to investigate the effects of process parameters on extraction efficiency and explore the mechanism for enhancing extraction yields. Through multi-objective optimization, optimum parameters are ionic liquid ratio of 70.00%, irradiation time of 6.00 min and irradiation power of 30.00%. Under these conditions, MILT-HD can significantly increase the extraction efficiency. And it can reduce energy demands. Furthermore, the mechanism for efficient extraction is innovatively explored by electrostatic potential analysis and temperature profile. The ionic liquid has a strong interaction with cellulose, and can better absorb microwave energy and quickly convert it into heat. Under the synergistic interactions of ionic liquids-cell wall and ionic liquids-microwave, the MILT-HD can strongly destroy the cell wall structure. It makes the essential oil efficiently diffuse. Based on this work, it provided a way to obtain Forsythiae fructus essential oils efficiently. And It is helpful to improve the comprehensive understanding of the extraction process of MITL-HD.

Purpose: To explore the application of intelligent nursing (IN) based on the Internet of Things (IoT) in children with pneumonia and sepsis treated with human gamma globulin (HGG). Methods: A total of 200 children with pneumonia combined with sepsis who attended the First People’s Hospital of Shangqiu from January 1, 2020 to February 13, 2022 were consecutively collected. Children were randomly divided into IN group and routine nursing (RN) group, with 100 children in each group. All children received standard anti-infection treatment along with intravenous HGG. In IN group, IN measures based on the IoT cloud computing platform monitored the treatment process of children with HGG throughout the whole process, while children in the RN group only received RN measures. Information on both groups was collected from the medical records, such as gender, age, duration of hospitalization, fever, antibiotic use, serological indicators, pulmonary function indicators, immune function indicators and adverse effects of HGG. Multi-factorial logistic regression was performed to access the correlation between IN and the duration of hospitalization and a range of other factors studied above. Results: After adjusting for numerous confounding factors, multifactorial logistic regression revealed that the application of IN was associated with a shorter duration of hospitalization ( p = .030) and lower white blood cell (WBC) and creatinine (Cr) levels in post-treatment children ( p = .003, p = .010). It was also associated with higher levels of forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and peak expiratory flow (PEV) after treatment ( p = .014, p = .001, p = .002) and higher levels of immune CD4 + /CD8 + ratio after treatment ( p = .001) and reduced symptoms of vomiting among the adverse effects ( p = .047). Conclusion: The IoT cloud-based IN model significantly improved the efficacy of HGG in the treatment of pneumonia sepsis in children and reduce occurrence of some adverse reactions.

BackgroundMorus alba L. (Sangzhi) alkaloid (SZ-A) is a new antidiabetic drug approved by the China National Medical Products Administration in 2020. Diabetic nephropathy (DN) is a common diabetic complication and an important cause of morbidity and mortality in patients with diabetes. The effects of SZ-A on DN remain unknown.PurposeThis study evaluated the effects of SZ-A on DN in Zucker diabetic fatty (ZDF) rats and explored the underlying mechanisms based on nitrosative stress, inflammation, and fibrosis.MethodsDiabetic ZDF rats were orally administered 100 and 200 mg/kg of SZ-A once daily for 9 weeks. The glucose metabolism and kidney function were assayed. The pathological injury and fibrosis of the kidneys were separately evaluated using hematoxylin and eosin staining and Masson’s staining. The oxidative and nitrosative stress and inflammation were assayed by determining the levels of related indices in the blood and kidneys and quantifying the related gene and protein expression. The expression of transforming growth factor β1 (TGFβ1) gene and protein were assayed by quantitative real-time PCR and immunohistochemistry, respectively. The renal transcriptomics was analyzed using RNA sequencing.ResultsRepeated treatment with SZ-A significantly improved glucose metabolism, dose-dependently decreased the levels of blood urea nitrogen, urinary albumin, and β2-microglobulin, and evidently relieved the renal injury in diabetic ZDF rats. As for the mechanisms, SZ-A remarkably ameliorated systemic nitrosative stress through lowering the levels of blood inducible nitric oxide synthase and nitric oxide, and significantly relieved systemic and renal inflammation by reducing the levels of blood interleukin-1β and monocyte chemoattractant protein-1 (MCP-1) and decreasing the levels of renal C-reactive protein content and expression of tumor necrosis factor-α in the kidneys. SZ-A also improved renal fibrosis by lowering the expression of TGFβ1 in the kidneys. Additionally, SZ-A significantly lowered the expression of stimulator of chondrogenesis 1 in the kidneys.ConclusionRepeated treatments with SZ-A significantly ameliorates DN by regulating systemic nitrosative stress, renal inflammation, and renal fibrosis partially through inhibition of the cytokine-NO and TGF-β1 signaling in ZDF rats, providing evidence for the additional application of SZ-A in clinical use for the treatment of DN.

Near-surface temperatures, such as air, land surface, and soil temperatures, play significant roles in surface radiation and energy balance. This study assessed nine gridded near-surface temperature products and analyzed the spatial heterogeneity and clear-sky bias of these temperature variables, using extensive measurements collected at Heihe River Basin. The MXD21 (MOD21 and MYD21) product had the lowest root mean square error (RMSE) (3.35 K) among all skin temperature products but a high percentage of missing values (48.4 %). All-weather skin temperature products had comparable accuracy for the interpolated cloudy-sky cases (RMSE 4.92 K) and observed clear-sky pixels (RMSE 3.42 K). For air temperature, AMSR2 had the lowest RMSE (2.48 K), but a high percentage of invalid data (32.5 %); and ERA5 had a worse accuracy (RMSE 3.87 K) but a high spatial resolution and gap-free data coverage. Comparing products from the same data source, air and soil temperatures had higher accuracies than skin temperature. Among the different variables of temperature, the 0 cm soil temperature and skin temperature had higher spatiotemporal heterogeneity than the air temperature and the soil temperatures at greater depths. The skin temperature, 0 cm soil temperature, and air temperature had higher clear-sky biases compared to soil temperatures.

Summary: Here, we present a protocol to identify the pro-embolic sub-population of human adipose-derived multipotent stromal cells (ADSCs) and predict fatal embolism risks from ADSC infusion. We describe steps for the collection, processing, and classification of ADSC single-cell RNA-seq data. We then detail the development of a mathematical model for predicting ADSC embolic risk. This protocol allows for the development of prediction models to enhance the assessment of cell quality and advance the clinical applications of stem cells.For complete details on the use and execution of this protocol, please refer to Yan et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

The array interferometric synthetic aperture radar (Array InSAR) system resolves shadow issues by employing two scans in opposite directions, facilitating the acquisition of a comprehensive three-dimensional representation of the observed scene. The point clouds obtained from the two scans need to be transformed into the same coordinate system using registration techniques to create a more comprehensive visual representation. However, the two-point clouds lack corresponding points and exhibit distinct geometric distortions, thereby preventing direct registration. This paper analyzes the error characteristics of array InSAR point clouds and proposes a robust registration method for array InSAR point clouds in urban scenes. It represents the 3D information of the point clouds using images, with pixel positions corresponding to the azimuth and ground range directions. Pixel intensity denotes the average height of points within the pixel. The KAZE algorithm and enhanced matching approach are used to obtain the homonymous points of two images, subsequently determining the transformation relationship between them. Experimental results with actual data demonstrate that, for architectural elements within urban scenes, the relative angular differences of registered facades are below 0.5°. As for ground elements, the Root Mean Square Error (RMSE) after registration is less than 1.5 m, thus validating the superiority of the proposed method.

Monitoring the level of biothiols in organisms would be beneficial for health inspections. Recently, 3-(2′-nitro vinyl)-4-phenylselenyl coumarin as a fluorescent probe for distinguishing the detection of the small-molecule biothiols cysteine/homocysteine (Cys/Hcy) and glutathione (GSH) was developed. By introducing 4-phenyselenium as the active site, the probe CouSeNO2/CouSNO2 was capable of detecting Cys/Hcy and GSH in dual fluorescence channels. Theoretical insights into the fluorescence sensing mechanism of the probe were provided in this work. The details of the electron excitation process in the probe and sensing products under optical excitation and the fluorescent character were analyzed using the quantum mechanical method. All these theoretical results would provide insight and pave the way for the molecular design of fluorescent probes for the detection of biothiols.

Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.