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Abstract This study aimed to understand the health status of low-income individuals living alone and to identify influencing factors. Using systematic random sampling methods, low-income individuals living alone were randomly selected. Via telephone interviews, we gathered information about their general health status. A logistic regression model was used to analyze relevant factors about the physical health of this population. The study included 1583 low-income individuals living alone. The prevalence rate of all kinds of diseases in low-income living alone in this survey was 88.63%. The multifactorial logistic regression analysis revealed that the risk factors for illness in this population were age ≥ 60 (OR 1.842, 95% CI 1.135–2.926, P = 0.006), self-rated poor mental health (OR 2.538, 95% CI 1.128–3.828, P = 0.005), and self-rated poor hearing status (OR 2.781, 95% CI 1.586–3.647, P = 0.001). Being female (OR 0.469, 95% CI 0.178–0.821, P = 0.033) was identified as a protective factor. Low-income individuals living alone are a unique group who lack familial care and economic and social support, and are thus in a disadvantaged social position. Therefore, this population requires increased attention, especially regarding their physical health. Implementing targeted assistance policies to improve their health status and enhance their quality of life is essential.

Galvanized steel plates with Zn–Al–Mg coatings are extensively utilized due to their exceptional corrosion resistance. This study, focusing on the cracking behavior of coatings with varying Mg/Al ratios, was conducted using in-situ tensile tests on different samples. The influence of the Mg/Al ratio on the crack resistance of the sample coatings was systematically summarized. To elucidate this point, five types of Zn–Al–Mg coatings with varying Mg/Al ratios were prepared using the same galvanizing process and tensile testing performed using a scanning electron microscope equipped with in-situ tensile capabilities. Macroscopic digital image statistical techniques were employed to quantify the extent of coating cracking, demonstrating the impact of the Mg/Al ratio on the coatings' crack resistance. The findings suggest that an increase in the Mg/Al ratio deteriorates the crack resistance of the coating, while enhancing its hardness. Moreover, this research offers a novel perspective in evaluating the crack resistance of coatings by comparing the effects of different Mg/Al ratios.

ABSTRACT: Cinnamomi Cortex was a material as medicinal and edible resources and it has been demonstrated that Cinnamomi Cortex aqueous extract (CCAE) possess hypoglycemic effect, but there were no active compounds identified as quality standard of CCAE to be used in the investigate of hypoglycemic activity. Hence, in this study, the quality standard and the hypoglycemic effect of CCAE were investigated. Cinnamaldehyde and coumarin as the quality control in CCAE were analyzed by high performance liquid chromatography (HPLC) method. The results showed that the average yield of extraction was 10.06%. The concentration of coumarin was linear with peak area ranging from 0.02–1.00 μg/mL (r = 0.999 6, n = 6) and that of cinnamaldehyde also demonstrated a good linear relationship with peak area in the range of 1.05–52.50 μg/mL (r = 0.999 7, n = 6). The average recovery rate of coumarin and cinnamaldehyde was 99.42% and 100.11%, respectively. The investigation of hypoglycemic effect revealed that CCAE could improve weight loss, lower liver and pancreas indices, improve organ damage caused by diabetes, and lower fasting blood glucose, glycosylated serum protein (GSP) and total cholesterol (TC) levels. The results showed that CCAE can reduce fasting blood glucose and blood lipid levels in diabetic mice.

ObjectiveTo understand the physical health condition and its influencing factors among the low-income population.MethodLow-income residents who visited or consulted at our Hospital during 2022 were selected for this study. Through telephone or face-to-face interviews, a self-made basic information questionnaire was used for data collection. The physical health level of the low-income population was analyzed, and a logistic regression model was applied to study its influencing factors.ResultsA total of 2,307 people were included in this study, of which 2,069 had various types of diseases, indicating a disease rate of 89.68%. Multivariate logistic regression analysis showed that age ≥ 60 years old (OR = 1.567, 95%CI: 1.122–2.188), poor mental health status (OR = 2.450, 95%CI: 1.203–3.678), smoking (OR = 1.752, 95%CI: 1.269–2.206), pulse pressure difference ≥ 60 (OR = 1.485, 95%CI: 1.164–1.787), and poor hearing (OR = 1.268, 95%CI: 1.026–1.324) were risk factors for disease, whereas being female (OR = 0.729, 95%CI: 0.540–0.984) was a protective factor for physical health.ConclusionAs a developing country with a large population, we should particularly focus on the physical health issues of the low-income population, take targeted measures for disease situations, and improve the quality of life of the low-income population.

Rhododendron is famous for its high ornamental value. However, the genus is taxonomically difficult and the relationships within Rhododendron remain unresolved. In addition, the origin of key morphological characters with high horticulture value need to be explored. Both problems largely hinder utilization of germplasm resources. Most studies attempted to disentangle the phylogeny of Rhododendron, but only used a few genomic markers and lacked large-scale sampling, resulting in low clade support and contradictory phylogenetic signals. Here, we used restriction-site associated DNA sequencing (RAD-seq) data and morphological traits for 144 species of Rhododendron, representing all subgenera and most sections and subsections of this species-rich genus, to decipher its intricate evolutionary history and reconstruct ancestral state. Our results revealed high resolutions at subgenera and section levels of Rhododendron based on RAD-seq data. Both optimal phylogenetic tree and split tree recovered five lineages among Rhododendron. Subg. Therorhodion (clade I) formed the basal lineage. Subg. Tsutsusi and Azaleastrum formed clade II and had sister relationships. Clade III included all scaly rhododendron species. Subg. Pentanthera (clade IV) formed a sister group to Subg. Hymenanthes (clade V). The results of ancestral state reconstruction showed that Rhododendron ancestor was a deciduous woody plant with terminal inflorescence, ten stamens, leaf blade without scales and broadly funnelform corolla with pink or purple color. This study shows significant distinguishability to resolve the evolutionary history of Rhododendron based on high clade support of phylogenetic tree constructed by RAD-seq data. It also provides an example to resolve discordant signals in phylogenetic trees and demonstrates the application feasibility of RAD-seq with large amounts of missing data in deciphering intricate evolutionary relationships. Additionally, the reconstructed ancestral state of six important characters provides insights into the innovation of key characters in Rhododendron.

Spinal cord injury (SCI) causes neuroinflammation, neuronal death, and severe axonal connections. Alleviating neuroinflammation, protecting residual cells and promoting neuronal regeneration via endogenous neural stem cells (eNSCs) represent potential strategies for SCI treatment. Extracellular vesicles (EVs) released by mesenchymal stem cells have emerged as pathological mediators and alternatives to cell-based therapies following SCI. In the present study, EVs isolated from untreated (control, C-EVs) and TGF-β1-treated (T-EVs) mesenchymal stem cells were injected into SCI mice to compare the therapeutic effects and explore the underlying mechanisms. Our study demonstrated for the first time that the application of T-EVs markedly enhanced the proliferation and antiapoptotic ability of NSCs in vitro. The infusion of T-EVs into SCI mice increased the shift from the M1 to M2 polarization of reactive microglia, alleviated neuroinflammation, and enhanced the neuroprotection of residual cells during the acute phase. Moreover, T-EVs increased the number of eNSCs around the epicenter. Consequently, T-EVs further promoted neurite outgrowth, increased axonal regrowth and remyelination, and facilitated locomotor recovery in the chronic stage. Furthermore, the use of T-EVs in Rictor−/− SCI mice (conditional knockout of Rictor in NSCs) showed that T-EVs failed to increase the activation of eNSCs and improve neurogenesis sufficiently, which suggested that T-EVs might induce the activation of eNSCs by targeting the mTORC2/Rictor pathway. Taken together, our findings indicate the prominent role of T-EVs in the treatment of SCI, and the therapeutic efficacy of T-EVs for SCI treatment might be optimized by enhancing the activation of eNSCs via the mTORC2/Rictor signaling pathway.

AN2 was thought to be the key gene inducing the fruit color differentiation of Lycium barbarum and Lycium ruthenicum, but there was no direct evidence. In this study, AN2 from L. ruhtenicum was overexpressed in L. barbarum to conform its function in regulating anthocyanin biosynthesis. The results showed that the stems, leaves, and fruits of transgenic plants were purple and contained significantly higher anthocyanin levels compared to the wild-type plants. Transcriptome analysis of leaf and fruit identified 5,832 differentially expressed genes (DEGs) in leaves and 2,029 DEGs in fruits, with 910 genes common to both tissues. GO and KEGG pathway enrichment analyses indicated a significant impact of LrAN2 on flavonoid biosynthesis and anthocyanin biosynthesis. The structural genes involved in the anthocyanin pathway, such as 4CL, CHS, F3H, F3’5’H, DFR, ANS, and UFGT, were up-regulated in transgenic lines, while the expression of transcription factors bHLH and WD40 were remained unchanged. These findings confirm the role of LrAN2 in the color differentiation of L. barbarum and L. ruthenicum and highlight its potential for the genetic enhancement of anthocyanin content in L. barbarum and other Solanaceae species.

To improve the quality of industrial internet network security assessment, this paper proposes an improved industrial internet network security situation assessment model. First,we analyze the factors that affect the network security of the industrial internet and determine the evaluation indicators; Second, the ER iterative algorithm and mutation method are used to fuse the evaluation indicators; Then, according to the fusion results, the industrial Internet network security situation assessment model is established; Finally, the selection covariance matrix adaptive evolution strategy (S-CMA-ES) is used to optimize the model parameters. This method establishes one-way selection of better strategies among different subclass groups, achieving better evaluation results. This method effectively solves the problem of reduced modeling accuracy caused by insufficient data. This paper conducts evaluation experiments on an industrial data set, and verifies the feasibility and effectiveness of the industrial Internet network security situation assessment model and S-CMA-ES optimization algorithm proposed in this paper.

In order to support the implementation of “multidimensional orthogonal configured communication protection between communication modules as well as parameters and interference” in cognitive communication countermeasures scenarios, jamming effectiveness requires module level responsiveness.A penetrating jamming effectiveness evaluation method was proposed.Firstly, the core parameters of each signal processing module were selected as evaluation parameters.Secondly, analytic hierarchy process (AHP) and entropy weight method (EWM) were used to determine the weight of indicators.The coordination problem in AHP was solved through expert weight allocation, and the weight allocation problem in EWM was solved through non-uniform mapping.Finally, the subjective and objective weights were weighed through game theory, and the jamming effectiveness was judged by the technique for order preference by similarity to ideal solution (TOPSIS).By conducting evaluation experiments on the jamming performance of the Link16 data link, taking into account multiple aspects such as jamming types, number of jamming frequencies, jamming duration, and system types.Experiment results demonstrate that the penetration-based jamming performance evaluation method not only provides a more intuitive representation of the relationship between evaluation results and metric parameters, but also possesses excellent jamming discrimination capability.

Abstract Angelica sinensis roots (Angelica roots) are rich in many bioactive compounds, including phthalides, coumarins, lignans, and terpenoids. However, the molecular bases for their biosynthesis are still poorly understood. Here, an improved chromosome-scale genome for A. sinensis var. Qinggui1 is reported, with a size of 2.16 Gb, contig N50 of 4.96 Mb and scaffold N50 of 198.27 Mb, covering 99.8% of the estimated genome. Additionally, by integrating genome sequencing, metabolomic profiling, and transcriptome analysis of normally growing and early-flowering Angelica roots that exhibit dramatically different metabolite profiles, the pathways and critical metabolic genes for the biosynthesis of these major bioactive components in Angelica roots have been deciphered. Multiomic analyses have also revealed the evolution and regulation of key metabolic genes for the biosynthesis of pharmaceutically bioactive components; in particular, TPSs for terpenoid volatiles, ACCs for malonyl CoA, PKSs for phthalide, and PTs for coumarin biosynthesis were expanded in the A. sinensis genome. These findings provide new insights into the biosynthesis of pharmaceutically important compounds in Angelica roots for exploration of synthetic biology and genetic improvement of herbal quality.

Diabetes has become one of the most prevalent global epidemics, significantly impacting both the economy and the health of individuals. Diabetes is associated with numerous complications, such as obesity; hyperglycemia; hypercholesterolemia; dyslipidemia; metabolic endotoxemia; intestinal barrier damage; insulin-secretion defects; increased oxidative stress; and low-grade, systemic, and chronic inflammation. Diabetes cannot be completely cured; therefore, current research has focused on developing various methods to control diabetes. A promising strategy is the use of probiotics for diabetes intervention. Probiotics are a class of live, non-toxic microorganisms that can colonize the human intestine and help improve the balance of intestinal microbiota. In this review, we summarize the current clinical studies on using probiotics to control diabetes in humans, along with mechanistic studies conducted in animal models. The primary mechanism by which probiotics regulate diabetes is improved intestinal barrier integrity, alleviated oxidative stress, enhanced immune response, increased short-chain fatty acid production, etc. Therefore, probiotic supplementation holds great potential for the prevention and management of diabetes.

This paper predicts the network security posture of an ICS, focusing on the reliability of Industrial Control Systems (ICSs). Evidence reasoning (ER) and belief rule base (BRB) techniques are employed to establish an ICS network security posture prediction model, ensuring the secure operation and prediction of the ICS. This model first integrates various information from the ICS to determine its network security posture value. Subsequently, through ER iteration, information fusion occurs and serves as an input for the BRB prediction model, which necessitates initial parameter setting by relevant experts. External factors may influence the experts’ predictions; therefore, this paper proposes the Projection Equalization Optimization (P-EO) algorithm. This optimization algorithm updates the initial parameters to enhance the prediction of the ICS network security posture through the model. Finally, industrial datasets are used as experimental data to improve the credibility of the prediction experiments and validate the model’s predictive performance in the ICS. Compared with other methods, this paper’s prediction model demonstrates a superior prediction accuracy. By further comparing with other algorithms, this paper has a certain advantage when using less historical data to make predictions.

Djulis (Chenopodium formosanum), a traditional Taiwanese crop enriched with phenolic compounds and betalain pigments, is associated with various health benefits, including antioxidant and hepatoprotective effects. This study analysed the phytochemical content and antioxidant capacity of extracts from both the hull and kernel of Djulis. The hull extract, which contained higher levels of flavonoids and exhibited superior antioxidant activity compared to the kernel extract, was selected for further in vivo studies. These experiments showed that oral administration of the Djulis hull crude extract significantly mitigated lipopolysaccharide (LPS)-induced acute liver injury (ALI) in mice by increasing the activity of the antioxidant enzyme glutathione peroxidase (GPx), reducing plasma levels of pro-inflammatory cytokine interferon gamma (IFN-γ), and enhancing liver levels of the anti-inflammatory cytokine interleukin-4 (IL-4). Additionally, the extract demonstrated potential in inhibiting the TLR4/NF-κB pathway, a critical signalling pathway in inflammation and apoptosis, offering insights into its protective mechanisms. These findings underscore Djulis hull’s potential as a functional food ingredient for ALI prevention and propose a valuable application for agricultural by-products.

Abstract Background Long non-coding RNA (lncRNA) H19 is one of the most highly expressed and conserved transcripts in mammalian development, and its functions have been fully discussed in many contexts including tumorigenesis and skeletal muscle development. However, its exact role in muscle atrophy remains largely unknown. This study investigated the effect of lncRNA H19 on muscle atrophy and the potential underlying mechanism. Methods Hindlimb suspension (HS) of C57BL/6 mice and starvation of C2C12 cells with PBS were conducted to induce atrophy. Real-time PCR and Western blotting were used to measure the expression of RNAs and proteins. LncRNA H19 and its encoded miR-675 were overexpressed or inhibited in different models of muscle atrophy. Immunofluorescence was carried out to examine the cross-sectional area (CSA) and minimal Feret’s diameter (MFD) of myofibers and myotube diameter. Results The expression levels of lncRNA H19 and miR-675 were significantly reduced in both the soleus and gastrocnemius muscles in response to HS. Overexpression of lncRNA H19 led to an increase in Atrogin-1 mRNA expression, and this effect was reversed by inhibiting miR-675. The overexpression of miR-675 aggravated both HS- and starving-induced muscle atrophy by inhibiting the IGF1R/Akt signaling pathway and promoting FoxO/Atrogin-1 expression. Conversely, miR-675 inhibition had the opposite effects. Conclusion The lncRNA H19/miR-675 axis can induce muscle atrophy, and its downregulation in mice with HS-induced muscle atrophy may act as a protective mechanism against this condition.

ABSTRACT Gut microbiota dysbiosis is causally related to inflammatory bowel disease (IBD), and increased levels of the gut metabolite ammonia have been proposed to contribute to IBD development. In this study, we aimed to clarify the anti-colitis mechanism of gallic acid (GA) based on its ability to trap the deleterious metabolite ammonia and improve gut microbiota. Aminated product was detected in the fecal samples of mice after oral gavage of gallic acid (GA) and identified as 4-amino-substituted gallic acid (4-NH2-GA), thus confirming the ability of GA to trap ammonia in vivo. Then, we compared the beneficial effects of GA and 4-NH2-GA on dextran sulfate sodium (DSS)-induced colitis mouse and found that both compounds managed to alleviate colitis phenotypes, indicating ammonia trapping had no adverse effect on the original anti-colitis activity of GA. In addition, both GA and 4-NH2-GA improved the gut microbiota dysbiosis induced by DSS, and fecal microbiota transplantation was subsequently performed, which further revealed that the gut microbiota mediated the anti-colitis activity of both GA and 4-NH2-GA. In summary, this study clarified that GA alleviated colitis by targeting both the symptoms and root causes: it directly reduced the deleterious metabolite ammonia by forming aminated metabolites without compromising the original anti-colitis activity, and it also improved gut microbiota dysbiosis, which in turn contributed to the alleviation of colitis. Since the GA structure is presented in various polyphenols as a common building block, the novel anti-colitis mechanism obtained from GA may also apply to other complex polyphenols.IMPORTANCEThe dysbiosis of the gut microbiota and its metabolism directly cause the emergence of IBD. In this study, we aimed to clarify the anti-colitis mechanism of GA in sight of gut microbiota and its metabolite ammonia. We discovered that GA directly captured and reduced the harmful metabolite ammonia in vivo to produce the aminated metabolite 4-NH2-GA, while the amination of GA had no adverse effect on its initial anti-colitis activity. In addition, both GA and its aminated metabolite improved the gut microbiota in colitis mice, and the modified gut microbiota, in turn, helped to relieve colitis. Since the GA structure is presented in diverse polyphenols as a common building block, the novel anti-colitis mechanism targeting the symptoms and root causes might also apply to other complex polyphenols.

BackgroundN-lactoylphenylalanine (Lac-Phe) is a new form of “exerkines” closely related to lactate (La), which may be able to inhibit appetite. Blood flow restriction (BFR) can lead to local tissue hypoxia and increase lactate accumulation. Therefore, this study investigated the effects of combining Moderate-intensity Continuous Exercise (MICE) with BFR on Lac-Phe and appetite regulation in obese adults.MethodsThis study employed the cross-design study and recruited 14 obese adults aged 18-24 years. The participants were randomly divided into three groups and performed several tests with specific experimental conditions: (1) M group (MICE without BFR, 60%VO2max, 200 kJ); (2) B group (MICE with BFR, 60%VO2max, 200 kJ); and (3) C group (control session without exercise). Participants were given a standardized meal 60 min before exercise and a ad libitum 60 min after exercise. In addition, blood and Visual Analogue Scale (VAS) were collected before, immediately after, and 1 hour after performing the exercise.ResultsNo significant difference in each index was detected before exercise. After exercise, the primary differential metabolites detected in the M and B groups were xanthine, La, succinate, Lac-Phe, citrate, urocanic acid, and myristic acid. Apart from that, the major enrichment pathways include the citrate cycle, alanine, aspartate, and glutamate metabolism. The enhanced Lac-Phe and La level in the B group was higher than M and C groups. Hunger of the B group immediately after exercise substantially differed from M group. The total ghrelin, glucagon-like peptide-1 and hunger in the B group 1 hour after exercise differed substantially from M group. The results of calorie intake showed no significant difference among the indexes in each group.ConclusionsIn conclusion, this cross-design study demonstrated that the combined MICE and BFR exercise reduced the appetite of obese adults by promoting the secretion of Lac-Phe and ghrelin. However, the exercise did not considerably affect the subsequent ad libitum intake.

Abstract Seasonal drought is common in Yunnan province, and water is the dominant factor limiting the growth of Pinus. yunnanensis and Pinus. armandii. The water use efficiency (WUE) of the two species is poorly understood. Needles were collected in a plantation (P. yunnanensis and P. armandii mixed forest) in four seasons, and the needle δ13C values were measured. The selected species had larger δ13C values and exhibited higher WUE than typical subtropical species. P. armandii needles showed a more conservative water use strategy (high WUE) than P. yunnanensis. There were significant differences in the δ13C values of P. armandii between the two ages, whereas no difference was observed in the δ13C values of P. yunnanensis. The lowest δ13C value in the young P. armandii forest was observed in spring, whereas the δ13C value of middle-aged forests did not differ between the seasons. The δ13C value of young P. yunnanensis forests showed no difference in the four seasons, and the maximum value was observed in summer in middle-aged forests. In general, the δ13C value of P. armandii was lowest in spring, whereas that of P. yunnanensis was higher in spring and winter. The needle δ13C values were lower in spring and winter, indicating that the season had different effects on the δ13C values of different tree species. Correlation analysis between the needle δ13C values and meteorological data indicated that temperature and precipitation were the dominant factors affecting WUE in P. yunnanensis and P. armandii. The effect of temperature on WUE was greater in P. yunnanensis middle-aged forests. The identification and selection of subtropical tree species with high WUE are critical to maintaining high levels of forest benefits under limited water conditions.

Soybeans rank among the top five globally produced crops. Black soybeans contain anthocyanins in their seed coat, offering strong antioxidant and anti-inflammatory benefits. This study explores the protective effects of black soybean seed coat (BSSC) against acute liver injury (ALI) in mice. Mice pretreated with BSSC crude extract showed reduced liver damage, inflammation, and apoptosis. High doses (300 mg/kg) of the extract decreased levels of proinflammatory cytokines (IL-6, IFN-γ) and increased levels of anti-inflammatory ones (IL-4, IL-10), alongside mitigating liver pathological damage. Additionally, it influenced the Nrf2/HO-1 pathway and reduced levels of apoptosis-related proteins. In vitro, the compounds delphinidin-3-O-glucoside (D3G) and cyanidin-3-O-glucoside (C3G) in BSSC were found to modulate cytokine levels, suggesting their role in ALI protection. The study concludes that BSSC extract, particularly due to D3G and C3G, effectively protects against LPS-induced ALI in mice by inhibiting inflammation, oxidative stress, and apoptosis.

To solve the problem of industrial control network (ICN) security situation prediction, this paper proposes a security situation prediction model for ICN based on evidential reasoning (ER) and belief rule base (BRB). First, this paper analyzes multiple factors influencing the security situation of the ICN, establishes a framework for security situation assessment, employs the ER algorithm for attribute fusion, and derives the security situation value of the ICN. Second, using historical data combined with expert knowledge, a security situation prediction model for ICN based on the BRB is constructed. Additionally, an extended projection covariance matrix adaptive evolution strategy (EP-CMA-ES) optimization algorithm is proposed, which is employed to optimize the parameters of the prediction model. The model not only comprehensively uses qualitative knowledge and quantitative data, but also integrates more uncertain information, and the reasoning process is interpretable. It also solves the subjectivity problem of expert knowledge, overcomes the problem of small amount of data caused by the difficulty of collecting industrial control safety data, and improves the accuracy of model prediction. Finally, prediction experiments were conducted on industrial datasets, confirming the feasibility and effectiveness of the security situation prediction model for ICN and the EP-CMA-ES optimization algorithm proposed in this paper.

The traditional support vector machine (SVM) requires manual feature extraction to improve classification performance and relies on the expressive power of manually extracted features. However, this characteristic poses limitations in complex Industrial Internet of Things (IIoT) environments. Traditional manual feature extraction may fail to capture all relevant information, thereby restricting the application effectiveness of SVM in IIoT settings. CNN-RNN, as a deep learning network capable of simultaneously extracting spatial and temporal features, can alleviate researchers’ burden. In this paper, we propose a novel intrusion detection system (IDS) framework based on anomalies, called CRSF. The framework’s pre-training part employs a dimension transformation function to process input data into two-dimensional images. Two-dimensional convolutional kernels are then employed to extract spatial features, and the feature sequences are passed to an RNN to capture richer temporal features. After sufficient pre-training, SVM is used as a classifier to map the pre-training data from the feature space to a high-dimensional space and learn nonlinear decision boundaries, enabling the framework to accurately differentiate feature representations of different classes. Simulation experiments on the TON_IoT-Datasets demonstrate the effectiveness of the CRSF framework in intrusion detection. When using the “linear” kernel function in SVM, the framework achieves an accuracy, F1-score, and AUC of 0.9959, 0.9959, and 0.9977, respectively, indicating its capability and superiority in intrusion detection.

The network security status assessment (NSSA) method can evaluate the network security status of cloud manufacturing systems (CMSs), which is of great significance to reduce the network security risk and loss of CMSs. At present, the NSSA of CMSs suitable for semiquantitative and uncertain information conditions is commonly used, which has certain limitations and low accuracy. This paper proposes an NSSA method for CMSs based on semiquantitative information. First, through the detailed analysis of the influencing factors of the network security status of the CMSs, the security evaluation indicators are selected, and the evaluation framework containing multilevel indicators is established by combining semiquantitative information. Second, the evaluation level is established according to the data distribution and the properties of the indicators. Third, a process of data fusion reasoning based on an evidential reasoning algorithm is designed, and a strong reference fusion case is given. Finally, the effectiveness of the proposed security state assessment algorithm in the NSSA of CMSs is verified and analyzed by simulation experiments. The experimental results show that the proposed method can make full use of semiquantitative information and uncertain information to evaluate the network security status of CMSs, and the evaluation results can reflect the actual security status of CMSs.

Airborne laser scanning (ALS) point cloud classification is a necessary step for understanding 3-D scenes and their applications in various industries. However, the classification accuracy and efficiency are low: 1) point cloud classification methods lack effective filtering of the large number of traditional features, 2) significant category imbalance and coordinate scale problems in ALS point cloud classification. To address these problems, this article proposes an airborne LiDAR point cloud classification method based on deep learning network with optimal feature fusion-based spectral information. This method involves the following steps: First, multiscale point cloud features are extracted, and random forest method is used to filter the features, while spectral information is fused to obtain a point cloud feature dataset with less but better data. Second, to adapt to the characteristics of the airborne point cloud, the improved RandLA-Net can simultaneously retain the advantages of random sampling and learn deeper semantic information by fusing the constructed point cloud features with the local feature aggregation module in the network. Third, four fusion models are constructed to verify the effectiveness of the optimal feature fusion-based spectral information network (OFFS-Net) model for airborne point cloud classification. Last, these models are trained and tested on Vaihingen 3-D dataset. The OFFS-Net achieves overall accuracy score of 84.9% and F1-score of 72.3%, which are better than the mainstream methods. This also validates that the proposed OFFS-Net point cloud classification method, based on the advantages of geometric feature and spectral information is excellent.

ABSTRACT: In 2021, there are approximately 537 million adults ageing 2079 years affected by diabetes worldwide and the number is rising rapidly, hence it is important to manage and control diabetes mellitus and its associated complications. Food is one of the key factors in preventing and combating diseases such as diabetes. Both as a food and an herbal medicine, Polygonum multiflorum (PM) has been used as an anti-aging tonic, for hair darkening in traditional Chinese medicine for several centuries. The recent research effort of PM has been focused on antioxidant, anti-ageing and anti-tumor properties. In the present study, we utilized the traditional processing of harvested raw PM, and identified several stilbene components and then evaluated the potential anti-diabetic effects of the processed PM extract (PME). PME (0.075 %) was given to diabetic mice (KK CgAy/J) in drinking water and after 7 weeks, PME-treated mice had significantly lower glucose levels than mice in the diabetic control group (P < 0.01). The mechanism was explored with ELISA and Western blotting and results suggested that the effect was through maintaining β-cell function.

A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of a deep learning network model (DLNM). To explore the influence of label image accuracy on the performance of a concrete crack segmentation network model in a semantic segmentation dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening labelling and topological structure widening labelling, respectively, to generate crack label images and construct three sets of crack semantic segmentation datasets with different accuracy. Four semantic segmentation network models (SSNMs), U-Net, High-Resolution Net (HRNet)V2, Pyramid Scene Parsing Network (PSPNet) and DeepLabV3+, were used for learning and training. The results show that the datasets constructed from the crack label images with pix-el-level fine labelling are more conducive to improving the accuracy of the network model for crack image segmentation. The U-Net had the best performance among the four SSNMs. The Mean Intersection over Union (MIoU), Mean Pixel Accuracy (MPA) and Accuracy reached 85.47%, 90.86% and 98.66%, respectively. The average difference between the quantized width of the crack image segmentation obtained by U-Net and the real crack width was 0.734 pixels, the maximum difference was 1.997 pixels, and the minimum difference was 0.141 pixels. Therefore, to improve the segmentation accuracy of crack images, the pixel-level fine labelling strategy and U-Net are the best choices.

Tea (Camellia sinensis) is widely considered to promote feelings of calming and soothing. This effect is attributed to L-theanine (L-γ-glutamylethylamide) in tea, a non-protein amino acid mainly derived from tea leaves. As a naturally occurring structural analogue of glutamate, L-theanine competes for the receptors with glutamate and is able to pass the blood-brain barrier to exert its relaxation effect. This review focuses on the relaxation effect of L-theanine, including animal models and the latest human trials as well as the potential molecular mechanisms regarding neuron stem cells. The biological efficacy of dietary L-theanine in the food matrix has been further discussed in this review in relation to the physiological changes in the gastrointestinal tract and bindings of L-theanine with other food components.

Tea as the most consumed beverage in the world has received enormous attention for its promoting health benefits. The deleterious effect of α-dicarbonyls and AGEs formed in Maillard reaction is also a long-term challenge. The connection between the two topics was the main aim of this review, to address and update the antiglycation effect and mechanism of tea and tea polyphenols. By analyzing recent publications, we have covered across chemistry models, cell lines and animal studies. Tea polyphenols, particularly catechins, showed outstanding antiglycation effect by trapping α-dicarbonyl compounds and impeding AGEs formation. Reduction of carbonyl stress brought alleviation to aging, diabetes, and collagen related diseases or complications through regulation of RAGE expression and subsequent MAPK and TGF-β pathway. Therefore, tea polyphenols can serve as promising natural candidates in the treatment and/or prevention of nephropathy, retinopathy, hepatopathy, hyperglycemia and obesity among others, by their potent antiglycation effect. Further studies need to address on aspects like exact mechanisms, solution of detection obstacles, balance of practical usage and harmful effects such as potential flavor damage and toxicity in food, to gain a comprehensive understanding of antiglycation activities of tea polyphenols and its actual application.

ABSTRACT: Oolong tea, partially fermented from Camellia sinensis leaves, exhibits significant antioxidative, anti-inflammatory, and anti-cancer activities as indicated in several in vitro and in vivo studies. However, studies on health promoting effects of oolong tea and its characteristic compounds are limited. The potential efficacy of bioactives derived from oolong tea and their roles as promising anticancer agents, their cardio-protective benefits during hypoxic conditions, effects in treating allergic disorders, potential prebiotic activities, improvement of blood lipid status in human beings, effectivity as oral hypoglycemic agent in the treatment of type 2 diabetes, and their potentials to reduce the risk of obesity have been discussed in this review. These promising studies mainly gained from animal studies might broaden the consumption and usage of the phenolic-enriched oolong tea and its products in food and pharmaceutical industries. However, potential health beneficial effects of oolong tea in humans should be further complemented by large-sized, randomized double-blind and placebo-controlled trials to consolidate potential therapeutic applications.

Tea polysaccharides (TPSs), one of the major bioactive ingredients in tea, have been widely studied due to their variety of biological activities, including antioxidant, cancer prevention, hypoglycemia, anti-fatigue, anti-coagulant, anti-obesity and immunomodulatory effect. The biological effectiveness of TPSs has direct relation with their structures such as monosaccharide composition, molecular weight, glycosidic linkages, conformation and others, which can be influenced by tea materials, processing methods, extraction and purification procedures among others. Comparing to the study of tea polyphenols, the exploration of TPSs in structural elucidation and biofunctionality is very preliminary. Yet several factors affecting the structural change of TPSs have been studied and identified. Consequently, the variation of some TPS biological activity brought by the change of TPS structures has been evaluated and preliminary correlation of structure activity relationship of TPSs has been performed. Therefore, this review aims to serve as a summary research report regarding the influencing factors on TPSs structures and consequential effects on the biological activities of TPSs. We hope to provide updated information and systematic references for future study and functional food development of TPSs.

ABSTRACT: Myriad evidence attests to the health-promoting benefits of tea drinking. While there are multiple factors of tea influencing the effective biological properties, tea polyphenols are the most significant and valuable components. The chemical characterization and physical characteristics of tea polyphenols have been comprehensively studied over the previous years. Still the emergence of new chemistry in tea, particularly the property of scavenging reactive carbonyl species (RCS) and the newly discovered flavoalkaloid compounds, has drawn increasing attention. In this review, we summarize recent findings of a new class of compounds in tea - flavonoid alkaloids (flavoalkaloids), which exist in fresh tea leaves and can be generated during the process of post-harvesting, and also postulate the formation mechanism of flavoalkaloids between catechins and theanine-derived Strecker aldehyde. Additionally, we detail the up-to-date research results of tea polyphenols regarding their ability to trap RCS and their in vivo aminated metabolites to suppress advanced glycation ends products (AGEs). We further raise questions to be addressed in the near future, including the synthetic pathways for the generation of flavoalkaloids and AGEs in fresh tea leaves before processing and the concentrations of tea polyphenols that affect their RCS scavenging capability due to their pro-oxidant nature. More intensive research is warranted to elucidate the mechanisms of action underlying the biological activity of flavoalkaloids and the pharmacological application of tea polyphenols in scavenging RCS and impeding detrimental AGEs.

Abstract Background Nitraria sibirica Pall. is an economic plant with two kinds of fruit color, widely spreads in the Qinghai Tibet Plateau. The chemical analysis and pharmacological evaluation had been carried out for several tens of years, the mechanism behind the fruit color differentiation is still unclear. Results In this manuscript, the chemical analysis of the extractions showed that the chemical composition of fruit color was anthocyanin, and two kind of Nitraria sibirica Pall. were caused by the content differentiation with the same anthocyanin kinds. Cyanidin-3-[2”-(6′”-coumaroyl)-glucosyl]-glucoside (C3G) was the major anthocyanin. Transcriptome analysis and the qRT-PCR revealed that the structural genes relative to anthocyanin biosynthesis except CHS, F3’5’H and ANS were up-regulated in the peels of BF (Black fruit) compared with the peels of RF (Red fruit), which indicated that transcript factor should be the reason for the expression difference of the structure genes. In the unigenes of the transcript factor MYB and bHLH, relative to anthocyanin, only NsMYB1 (Cluster 8422.10600), was high-expression and up-expression in the peels of BF. NsMYB1 encoded the same length protein with four amino acid differences in the RF and BF, and both contained the intact DNA, HTH-MYB and SANT domains. NsMYB1 was close to the AtMYB114, AtMYB113 and AtPAP1, regulating anthocyanin biosynthesis, in phylogenetic relationship. Both NsMYB1r and NsMYB1b could promote the transcript of the structural genes, and induced the anthocyanin accumulation in all tissues of transgenic tobacco. The insertion of ‘TATA’ in the promoter of NsMYB1r gave one more promoter region, and was the reason for higher transcripts in black fruit possibly. Conclusions Cyanidin-3-[2′’-(6′”-coumaroyl)-glucosyl]-glucoside was the major anthocyanin in black fruit of Nitraria sibirica Pall.. NsMYB1 was a functional R2R3-MYB transcription factor, regulated the anthocyanin biosynthesis, and led to the fruit color differentiation in Nitraria sibirica Pall.

There are numerous evaluations of natural products, of which majority are food bioactives, performed up to date for their various health beneficial activities via targeting specific proteins. However, the direct identification of a targeted protein remains unexplored for natural occurring compounds. Proteolysis targeting chimera (PROTAC) is a type of bifunctional chimeric molecules that can directly degrade the binding proteins targeted by bioactive molecules in an ubiquitin-proteasome pathway. As the agents in protein degradation dependent on ubiquitin ligase, the bifunctional molecule connects the target protein ligand and E3 ligase ligand together via an appropriate linker. It is highly selective and efficient to induce the ubiquitin-mediated degradation of targeted binding proteins. Therefore, it has been demonstrated that the PROTAC technology has broad application in the modulation of the target protein level. In this review, we outlined the advances in PROTAC combined molecule compounds, summarized its quantitative structure-activity relationship, and finally reviewed the methods applied in identifying the target proteins of natural products. We hope it will provide an insightful application of PROTAC techniques in the target protein identification of natural products including food bioactive molecules.

Badminton, a dynamic racquet sport demanding agility and power, features the overhead forehand smash as a pivotal offensive shot. Utilizing 3D motion analysis, this research delves into the intricate biomechanical facets underpinning this pivotal shot, with a dual focus on both novice and proficient players. Through a comparative analysis of these two player cohorts, the investigation aims to elucidate the fundamental factors influencing the quality of the forehand smash. Our findings reveal that skilled players exhibit significant improvements in smash quality, including a 60.2% increase in shuttlecock speed, reduced clearance height, and flight angle at release. These enhancements are associated with specific determinants, such as consistent positioning, racket angle at impact, and range of motion (ROM) in various joints. More crucially, full-body tension-arc formation and a four-segment whip-like smash contribute to these improvements. Unique to the whip-like smash is the rapid trunk and shoulder rotations in early whip-like control inducing passive elbow flexion and wrist over-extension, enhancing the stretch-shortening cycle (SSC) effect of muscles for a more powerful smash. Emphasizing this uniqueness and the determinants simplify smash learning, potentially boosting training effectiveness. This research contributes to a deeper understanding of badminton’s biomechanics and offers practical implications for coaches and players to enhance their forehand smashes, especially among beginners.

The traditional Transformer model primarily employs a self-attention mechanism to capture global feature relationships, potentially overlooking local relationships within sequences and thus affecting the modeling capability of local features. For Support Vector Machine (SVM), it often requires the joint use of feature selection algorithms or model optimization methods to achieve maximum classification accuracy. Addressing the issues in both models, this paper introduces a novel network framework, CTSF, specifically designed for Industrial Internet intrusion detection. CTSF effectively addresses the limitations of traditional Transformers in extracting local features while compensating for the weaknesses of SVM. The framework comprises a pre-training component and a decision-making component. The pre-training section consists of both CNN and an enhanced Transformer, designed to capture both local and global features from input data while reducing data feature dimensions. The improved Transformer simultaneously decreases certain training parameters within CTSF, making it more suitable for the Industrial Internet environment. The classification section is composed of SVM, which receives initial classification data from the pre-training phase and determines the optimal decision boundary. The proposed framework is evaluated on an imbalanced subset of the X-IIOTID dataset, which represent Industrial Internet data. Experimental results demonstrate that with SVM using both “linear” and “rbf” kernel functions, CTSF achieves an overall accuracy of 0.98875 and effectively discriminates minor classes, showcasing the superiority of this framework.

Assessing the spatiotemporal changes in forest aboveground biomass (AGB) provides crucial insights for effective forest carbon stock management, an accurate estimation of forest carbon uptake and release balance, and a deeper understanding of forest dynamics and climate responses. However, existing research in this field often lacks a comprehensive methodology for capturing tree-level AGB dynamics using multitemporal remote sensing techniques. In this study, we quantitatively characterized spatiotemporal variations of tree-level AGB in boreal natural secondary forests in the Greater Khingan Mountains region using multitemporal light detection and ranging (LiDAR) data acquired in 2012, 2016, and 2022. Our methodology emphasized improving the accuracy of individual tree segmentation algorithms by taking advantage of canopy structure heterogeneity. We introduced a novel three-dimensional metric, similar to crown width, integrated with tree height to calculate tree-level AGB. Moreover, we address the challenge of underestimating tree-level metrics resulting from low pulse density, ensuring accurate monitoring of AGB changes for every two acquisitions. The results showed that the LiDAR-based ΔAGB explained 62% to 70% of the variance of field-measured ΔAGB at the tree level. Furthermore, when aggregating the tree-level AGB estimates to the plot level, the results also exhibited robust and reasonable accuracy. We identified the average annual change in tree-level AGB and tree height across the study region, quantifying them at 2.23 kg and 0.25 m, respectively. Furthermore, we highlighted the importance of the Gini coefficient, which represents canopy structure heterogeneity, as a key environmental factor that explains relative AGB change rates at the plot level. Our contribution lies in proposing a comprehensive framework for analyzing tree-level AGB dynamics using multitemporal LiDAR data, paving the way for a nuanced understanding of fine-scale forest dynamics. We argue that LiDAR technology is becoming increasingly valuable in monitoring tree dynamics, enabling the application of high-resolution ecosystem dynamics products to elucidate ecological issues and address environmental challenges.

Abstract Background Non-alcoholic fatty liver disease (NAFLD), which is growing more common in the Western world, has become the main cause of chronic liver disease and is strongly associated with metabolism syndromes. NAFLD can indicate a wide spectrum of hepatic pathologies, ranging from simple hepatic steatosis and inflammatory non-alcoholic steatohepatitis to more severe stages of fibrosis and cirrhosis. Moreover, evidence has demonstrated that physical inactivity and westernized dietary habits may facilitate the development of NAFLD. Lipid modulation and metabolism could be important factors in the development of steatosis. Lipid species, characterized using a lipidomic approach with untargeted analysis, could provide potential biomarkers for the pathogenesis of NAFLD or therapeutic applications. Thus, in this study, the effects of exercise on the improvement of NAFLD were further investigated from a lipidomic perspective through the aspects of lipid regulation and metabolism. Methods Wild type (WT) C57BL/6 J and C57BL/6-ApoE em1Narl /Narl mice were assigned to one of four groups: WT mice fed a normal chow diet (CD), apolipoprotein E (ApoE) knockout mice fed a normal CD, ApoE knockout mice fed a high-fat diet (HFD), and ApoE knockout mice fed a HFD and provided with swimming exercise. The treatments (e.g., normal diet, HFD, and exercise) were provided for 12 consecutive weeks before the growth curves, biochemistry, fat composition, pathological syndromes, and lipid profiles were determined. Results Exercise significantly reduced the HFD-induced obesity (weight and fat composition), adipocyte hypertrophy, liver lipid accumulation, and pathological steatosis. In addition, exercise ameliorated HFD-induced steatosis in the process of NAFLD. The lipidomic analysis revealed that the changes in plasma triglyceride (14:0/16:0/22:2), phosphatidic acid (18:0/17:2), and phosphatidylglycerol (16:0/20:2) induced by the administration of the HFD could be reversed significantly by exercise. Conclusions The 12-week regular exercise intervention significantly alleviated HFD-induced NAFLD through modulation of specific lipid species in plasma. This finding could elucidate the lipids effects behind the hepatic pathogenesis with exercise.

Abstract Osteogenic differentiation is a vital process for growth, repair, and remodeling of bones. Accumulating evidence have suggested that microRNAs (miRNAs or miRs) play a crucial role in osteogenic differentiation of mesenchymal stem cells (MSCs). Hence, the current study set out to elucidate the role of miR-149 in osteogenic differentiation of MSCs and the underlying mechanism. First, rat models of bone differentiation were established using the Masquelet-induced membrane technique, and MSCs were isolated. The expression of miR-149 and AKT1 in the rats and cells was detected with RT-qPCR and western blot analysis. The relationships among miR-149, AKT1, and Twist1 were further predicted by online bioinformatics prediction and verified using dual luciferase reporter gene assay. Alteration of miR-149, AKT1, or Twist1 was performed to further explore their effect on osteogenic differentiation of MSCs. miR-149 was poorly expressed in the process of osteogenic differentiation of MSCs, while AKT1 was highly expressed. miR-149 negatively regulated the expression of AKT1, which in turn diminished the protein levels of Twist1 and promoted the phosphorylation levels of Twist1. Lastly, miR-149 acted as an inhibitor of osteogenic differentiation of MSCs, which could be reversed by AKT1. To sum up, miR-149 silencing promoted osteogenic differentiation of MSCs by enhancing Twist1 degradation through AKT1 upregulation, representing a new method for bone repair treatment.

ObjectiveA systematic review and meta-analysis was performed to evaluate the prevalence of suicide ideation among HIV/AIDS patients in China.MethodsSystematic search of CNKI, Wanfang, China biology medicine database, Weipu, EMBASE, Web of science and PubMed for studies related to the suicide ideation of HIV/AIDS patients. The incidence of suicide ideation of HIV / AIDS patients in China was investigated by meta-analysis.ResultsA total of 16 studies were included (n = 6,174). The incidence of suicidal ideation in HIV/AIDS patients was 30.6% (95%CI: 21.4–39.9%). The results of subgroup analysis showed that the incidence of suicidal ideation in male was 36.1%, which was higher than that in female (32.8%), homosexual patients (39.7%) higher than heterosexual patients (27.1%), 2013–2021 survey (35.2%) higher than 2003–2012 survey (26.5%), the unmarried patients (39.6%) were higher than the married patients (34.5%), the patients diagnosed >1 year (28.4%) were higher than the patients diagnosed 400 cells/ul group (19.8%).ConclusionThe incidence of suicide ideation in HIV/AIDS patients in China is relatively high.

The complexity of the Industrial Internet of Things (IIoT) presents higher requirements for intrusion detection systems (IDSs). An adversarial attack is a threat to the security of machine learning-based IDSs. For such a complex situation, this paper analyses adversarial attackers’ ability to deceive IDSs used in the IIoT and proposes the evaluation of an IDS with function-discarding adversarial attacks in the IIoT (EIFDAA), a framework that can evaluate the defence performance of machine learning-based IDSs against various adversarial attack algorithms. This framework is composed of two main processes: adversarial evaluation and adversarial training. Adversarial evaluation can diagnose IDS that is unfitting in adversarial environments. Then, adversarial training is used to treat the weak IDS. In this framework, five well-known adversarial attacks, the fast-gradient sign method (FGSM), basic iterative method (BIM), projected gradient descent (PGD), DeepFool and Wasserstein generative adversarial network with gradient penalty (WGAN-GP) are used to convert attack samples into adversarial samples to simulate the adversarial environment. This study evaluates the capability of mainstream machine learning techniques as intrusion detection models to defend against adversarial attacks, and retrains these detectors to improve the robustness of IDSs through adversarial training. In addition, the framework includes an adversarial attack model that discards the attack function of the attack samples in the IIoT. Through the experimental results on the X-IIoTID dataset, the dropped adversarial detection rate of these detectors to nearly zero demonstrates that an adversarial attack has black-box attack capabilities for these IDSs. Additionally, the improved IDSs retrained with adversarial samples can effectively defend against adversarial attackers while maintaining the original detection rate for the attack samples. EIFDAA is expected to be a solution that can be applied to IDS for improving the robustness in the IIoT.

Assessing the changes in forest carbon stocks over time is critical for monitoring carbon dynamics, estimating the balance between carbon uptake and release from forests, and providing key insights into climate change mitigation. In this study, we quantitatively characterized spatiotemporal variations in aboveground carbon density (ACD) in boreal natural forests in the Greater Khingan Mountains (GKM) region using bi-temporal discrete aerial laser scanning (ALS) data acquired in 2012 and 2016. Moreover, we evaluated the transferability of the proposed design model using forest field plot data and produced a wall-to-wall map of ACD changes for the entire study area from 2012 to 2016 ​at a grid size of 30 ​m. In addition, we investigated the relationships between carbon dynamics and the dominant tree species, age groups, and topography of undisturbed forested areas to better understand ACD variations by employing heterogeneous forest canopy structural characteristics. The results showed that the performance of the temporally transferable model (R2 ​= ​0.87, rRMSE ​= ​18.25%), which included stable variables, was statistically equivalent to that obtained from the model fitted directly by the 2016 field plots (R2 ​= ​0.87, rRMSE ​= ​17.47%). The average rate of change in carbon sequestration across the entire study region was 1.35 ​Mg·ha−1·year−1 based on the changes in ALS-based ACD values over the course of four years. The relative change rates of ACD decreased as the elevation increased, with the highest and lowest ACD growth rates occurring in the middle-aged and mature forest stands, respectively. The Gini coefficient, which represents forest canopy surface structure heterogeneity, is sensitive to carbon dynamics and is a reliable predictor of the relative change rate of ACD. This study demonstrated the applicability of bi-temporal ALS for predicting forest carbon dynamics and fine-scale spatial change patterns. Our research contributed to a better understanding of the influence of remote sensing-derived environmental variables on forest carbon dynamic patterns and the development of context-specific management approaches to increase forest carbon stocks.

ABSTRACT: Increasing interest in attaining an optimal health have longstanding and are imperative for consumers, medical and health researchers and functional food scientists and producers among others. Functional food is defined as foods that have a biological function with a very broad range of coverage including natural and conventional foods with reported bioactivities, dietary supplements and medical foods. Its concept is inclusively broad and ambiguous. Medical food is a specific class of functional foods with clear definition and limited coverage to guarantee its integrity. This review introduced the definition of medical food by the US Food and Drug Administration, intended to clarify the differences among medical food, dietary supplements and conventional foods, and listed some examples of medical food products developed in the US.

Ferroptosis is a newly discovered way of programmed cell death, mainly caused by the accumulation of iron-dependent lipid peroxides in cells, which is morphologically, biochemically and genetically different from the previously reported apoptosis, necrosis and autophagy. Studies have found that ferroptosis plays a key role in the occurrence and development of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease and vascular dementia, which suggest that ferroptosis may be involved in regulating the progression of neurodegenerative diseases. At present, on the underlying mechanism of ferroptosis in neurodegenerative diseases is still unclear, and relevant research is urgently needed to clarify the regulatory mechanism and provide the possibility for the development of agents targeting ferroptosis. This review focused on the regulatory mechanism of ferroptosis and its various effects in neurodegenerative diseases, in order to provide reference for the research on ferroptosis in neurodegenerative diseases.

The emergency response is crucial in preventing and mitigating urban floods. Both remote sensing and social media data offer distinct advantages in large-scale flood monitoring and near-real-time flood monitoring. However, current research lacks a thorough exploration of the application of social media data and remote sensing imagery in the urban flood emergency response. To address this issue, this paper, while extracting disaster information based on social media data, deeply mines the spatiotemporal distribution characteristics and dynamic spatial accessibility of rescue points. Furthermore, SAR imagery and social media data for monitoring urban flooding are compared. This study took the Zhengzhou 7.20 urban flood as a case study and created a methodological framework to quickly extract flood disaster information (flood, landslide, and rescue points) using these two types of data; spatiotemporal analysis and random forest classification were also conducted to mine valuable information. Temporally, the study revealed that disaster information did not increase proportionally with the amount of rainfall during the rainfall process. Spatially, specific regions with higher susceptibility to flooding, landslides, and rescue points were identified, such as the central region characterized by low drainage standards and high-density urban areas, as well as the eastern region with low-lying terrain. Moreover, this study examined the spatial accessibility of rescue resources in real flood scenarios and found that their service coverage varied throughout the day during and after the disaster. In addition, social media excelled in high-density urban areas’ flood point extraction, while SAR performed better in monitoring floods at the edges of low-density urban areas and large water bodies, allowing them to complement each other, to a certain extent. The findings of this study provide scientific reference value for the optimal selection of rescue paths and the allocation of resources in the emergency response to urban floods caused by extreme rainstorms.

Background: Activation of the unfolded protein response (UPR) is closely related to the pathogenesis of many metabolic disorders. Accumulating evidence also shows that UPR and metabolic signaling pathways are interdependent. The AMP-activated protein kinase (AMPK) signal pathway controls the energy balance of eukaryotes. The aim of this study was therefore to investigate the possible interaction between AMPK signaling and UPR in muscle cells exposed to saturated fatty acids, as well as the potential mechanism. Methods: The saturated fatty acid palmitate was used to induce UPR in C2C12 myotubes. Compound C or knockdown of AMPKα with short hairpin RNA (shRNA) were used to inhibit the AMPK signaling pathway in palmitate-treated muscle cells. AMPK signaling in myotubes was activated using 5-amino-1-β-D-ribofuranosylimidazole-4-carboxamide (AICAR) or ex229. C2C12 myotubes were pre-treated with taurourdodeoxycholic acid (TUDCA) to inhibit UPR before adding palmitate. Real-time PCR and Western blotting were performed to evaluate the expression of UPR markers and activation of AMPK. Results: Palmitate treatment induced UPR in C2C12 myotubes while activating AMPK signaling. Inhibition of the AMPK pathway with compound C or AMPK shRNA reduced palmitate-induced activation of UPR, while inhibition of UPR with TUDCA reduced palmitate-induced AMPK activation. This indicates a positive feedback loop between UPR and AMPK. Furthermore, activation of the AMPK pathway with AICAR or ex229 caused a dose-dependent upregulation of UPR markers, including activating transcription factor 4 (ATF4), binding immunoglobulin protein (BIP), and growth arrest and DNA damage-inducible 34 (GADD34) protein. Conclusions: These results provide the first evidence that AMPK signaling is involved in the early activation of UPR caused by saturated fatty acids in skeletal muscle. Furthermore, they indicate that physiological or pharmacological activation of the AMPK pathway (e.g., by exercise or phenformin, respectively) can promote muscle health and function, thereby improving the quality of life in individuals with metabolic disorders due to a high-fat diet or obesity.

Due to expansive soils and high slopes, the deep excavated channel section of the China South–North Water-Diversion Middle-Route Project has a certain risk of landslide disaster. Therefore, examining the deformation law and mechanism of the channel slope in the middle-route section of the project is an extreme necessity for safe operation. However, the outdated monitoring method limits research on the surface deformation law and mechanism of the entire deep excavation channel section. For these reasons, we introduced a novel approach that combines SBAS-InSAR and GNSS, enabling the surface domain monitoring of the study area at a regional scale as well as real-time monitoring of specific target regions. By using SBAS-InSAR technology and leveraging 11-view high-resolution TerraSAR-X data, we revealed the spatiotemporal evolution law of surface deformations in the channel slopes within the study area. The results demonstrate that the predominant deformation in the study area was uplifted, with limited evidence of subsidence deformation. Moreover, there is a distinct region of significant uplift deformation, with the highest annual uplift rate reaching 19 mm/y. Incorporating GNSS and soil-moisture-monitoring timeseries data, we conducted a study on the correlation between soil moisture and the three-dimensional deformation of the ground surface, revealing a positive correlation between the soil moisture content and vertical displacement of the channel slope. Furthermore, combining field investigations on surface uplift deformation characteristics, we identified that the main cause of surface deformation in the study area was attributed to the expansion of the soil due to water absorption in expansive soils. The research results not only revealed the spatiotemporal evolution law and mechanism of the channel slope deformation in the studied section of the deep excavation channel but also provide successful guidance for the prevention and control of channel slope-deformation disasters in the study area. Furthermore, they offer effective technical means for the safe monitoring of the entire South–North Water-Diversion Middle-Route Project and similar long-distance water-conveyance canal projects.

Background: Muscle atrophy resulting wholly or partially from disuse represents a serious medical complication that decreases quality of life and increases morbidity and mortality. The accumulation of misfolded/unfolded proteins disrupts endoplasmic reticulum (ER) homeostasis and thus causes ER stress. Growing evidence indicates that ER stress plays an essential role in skeletal muscle remodeling under various physiological or pathophysiological conditions. However, whether ER stress is involved in disuse-induced muscle atrophy remains unclear. Methods: To induce muscle atrophy, 8-week-old C57BL/6JNifdc male mice were subjected to 3, 7, or 14 days of hindlimb unloading (HU), and rhesus macaques (Macaca mulatta) were subjected to 10∘ head-down tilted bed rest (HDBR) for 6 weeks. Tauroursodeoxycholic acid (TUDCA) (500 mg/kg/d) was orally administered to mice during HU to inhibit ER stress. Quantitative PCR, Western blotting, and immunohistochemistry were conducted to evaluate gene, protein, and structural changes, respectively. Results: ER stress marker genes were rapidly induced by HU in a similar trend to that observed with atrophy-related genes such as Atrogin-1, muscle RING finger 1 (MuRF1), and muscle ubiquitin ligase of SCF complex in atrophy-1 (MUSA1). Inhibition of ER stress with TUDCA, a pan-ER stress inhibitor, attenuated HU-induced muscle atrophy and the upregulation of ubiquitin ligases via the AKT/forkhead box O3a pathway. In addition, the oxidative-to-glycolytic myofiber type transition caused by HU was also inhibited by TUDCA treatment. ER stress activation was also confirmed in HDBR-induced rhesus soleus muscle atrophy. Conclusions: The strong positive correlation between ER stress activation and both HU- and HDBR-induced muscle atrophy indicates that ER stress activation is ubiquitously involved in disuse-induced muscle atrophy, regardless of species. Thus, inhibiting ER stress may be an effective therapeutic strategy to prevent muscle atrophy during disuse.

Norisoboldine (NOR), the major isoquinoline alkaloid constituent of a Chinese traditional medicine Radix Linderae, has been demonstrated to inhibit osteoclast differentiation and improve arthritis. The aim of this study is to examine the effect of NOR on bone fracture healing and the underlying mechanisms correlated with bone marrow stromal cells (BMSCs) differentiation to chondrocytes. Our results showed that NOR inhibits the tibia fracture healing process by suppressing cartilage formation, which leads to less endochondral ossification, indicated by less osterix and collage I signaling at the fracture site. Moreover, NOR significantly reduced the differentiation of primary BMSCs to chondrocytes in vitro by reducing the bone morphogenetic protein 2 (BMP2) signaling. These findings imply that NOR negatively regulates the healing of the tibial midshaft fracture, which might delay the union of the fractures and should be noticed when used in other treatments.

Abstract Background Foxtail millet (Setaria italica) is one of the oldest domesticated crops and has been considered as an ideal model plant for C4 grasses. It has abundant type of anther and hull colors which is not only a most intuitive morphological marker for color selection in seed production, but also has very important biological significance for the study of molecular mechanism of regulating the synthesis and metabolism of flavonoids and lignin. However, only a few genetic studies have been reported for anther color and hull color in foxtail millet. Results Quantitative trait loci (QTL) analysis for anther color and hull color was conducted using 400 F6 and F7 recombinant inbreed lines (RILs) derived from a cross between parents Yugu18 and Jigu19. Using restriction-site associated DNA sequencing, 43,001 single-nucleotide polymorphisms (SNPs) and 3,022 indels were identified between both the parents and the RILs. A total of 1,304 bin markers developed from the SNPs and indels were used to construct a genetic map that spanned 2196 cM of the foxtail millet genome with an average of 1.68 cM/bin. Combined with this genetic map and the phenotypic data observed in two locations for two years, two QTL located on chromosome 6 (Chr6) in a 1.215-Mb interval (33,627,819–34,877,940 bp) for anther color (yellow - white) and three QTL located on Chr1 in a 6.23-Mb interval (1–6,229,734 bp) for hull color (gold-reddish brown) were detected. To narrow the QTL regions identified from the genetic map and QTL analysis, we developed a new method named “inconsistent rate analysis” and efficiently narrowed the QTL regions of anther color into a 60-kb interval (34.13–34.19 Mb) in Chr6, and narrowed the QTL regions of hull color into 70-kb (5.43–5.50 Mb) and 30-kb (5.69–5.72 Mb) intervals in Chr1. Two genes (Seita.6G228600.v2.2 and Seita.6G228700.v2.2) and a cinnamyl alcohol dehydrogenase (CAD) gene (Seita.1G057300.v2.2) with amino acid changes between the parents detected by whole-genome resequencing were identified as candidate genes for anther and hull color, respectively. Conclusions This work presents the related QTL and candidate genes of anther and hull color in foxtail millet and developed a new method named inconsistent rate analysis to detect the chromosome fragments linked with the quality trait in RILs. This is the first study of the QTL related to hull color in foxtail millet and clarifying that the CAD gene (Seita.1G057300.v2.2) is the key gene responsible for this trait. It lays the foundation for further cloning of the functional genes and provides a powerful tool to detect the chromosome fragments linked with quality traits in RILs.

Abstract Background Setaria italica is the second-most widely planted species of millets in the world and an important model grain crop for the research of C4 photosynthesis and abiotic stress tolerance. Through three genomes assembly and annotation efforts, all genomes were based on next generation sequencing technology, which limited the genome continuity. Results Here we report a high-quality whole-genome of new cultivar Huagu11, using single-molecule real-time sequencing and High-throughput chromosome conformation capture (Hi-C) mapping technologies. The total assembly size of the Huagu11 genome was 408.37 Mb with a scaffold N50 size of 45.89 Mb. Compared with the other three reported millet genomes based on the next generation sequencing technology, the Huagu11 genome had the highest genomic continuity. Intraspecies comparison showed about 94.97 and 94.66% of the Yugu1 and Huagu11 genomes, respectively, were able to be aligned as one-to-one blocks with four chromosome inversion. The Huagu11 genome contained approximately 19.43 Mb Presence/absence Variation (PAV) with 627 protein-coding transcripts, while Yugu1 genomes had 20.53 Mb PAV sequences encoding 737 proteins. Overall, 969,596 Single-nucleotide polymorphism (SNPs) and 156,282 insertion-deletion (InDels) were identified between these two genomes. The genome comparison between Huagu11 and Yugu1 should reflect the genetic identity and variation between the cultivars of foxtail millet to a certain extent. The Ser-626-Aln substitution in acetohydroxy acid synthase (AHAS) was found to be relative to the imazethapyr tolerance in Huagu11. Conclusions A new improved high-quality reference genome sequence of Setaria italica was assembled, and intraspecies genome comparison determined the genetic identity and variation between the cultivars of foxtail millet. Based on the genome sequence, it was inferred that the Ser-626-Aln substitution in AHAS was responsible for the imazethapyr tolerance in Huagu11. The new improved reference genome of Setaria italica will promote the genic and genomic studies of this species and be beneficial for cultivar improvement.

IntroductionThe current field of research on the impact of COVID-19 on mental health was mostly limited to the evaluation of the first round of the epidemic, few reports focused on the impact of the re-emergence of COVID-19. This study aimed to investigate the mental health literacy and status of residents during the re-outbreak of COVID-19 in China.MethodsThe basic information sheet, health literacy survey scale, physical health questionnaire-9 (PHQ-9), generalized anxiety disorder-7 (GAD-7), insomnia severity index (ISI), and Alzheimer dementia 8 (AD8) were applied to evaluate the mental health literacy, mental health status and elderly cognitive function, and χ2 test was applied for analysis of the difference between different groups.ResultsA total of 2,306 participants were involved in this study, of which 734 people completed the mental health literacy survey. The qualified rate of mental health literacy was 6.4%. The difference is statistically significant. A total of 1,015 people completed the survey of mental health status, the prevalence of depressive symptoms was 8.87%, the monthly income of different families (χ2 = 13.96, P = 0.01), the self-assessed health status (χ2 = 128.56, P < 0.05), the presence or absence of chronic diseases (χ2 = 4.78, P = 0.03), among all which the difference was statistically significant; the prevalence of anxiety symptoms was 3.84%, different regions (χ2 = 12.26, P < 0.05), occupations (χ2 = 11.65, P < 0.05), household monthly income (χ2 = 12.65, P = 0.01), self-rated health status (χ2 = 151.11, P < 0.05), and chronic diseases (χ2 = 7.77, P = 0.01), among all which the differences were statistically significant. The prevalence of insomnia symptoms was 7.98%, different age (χ2 = 18.45, P < 0.05), region (χ2 = 5.11, P = 0.02), monthly household income (χ2 = 12.68 P = 0.01), and self-assessed health status (χ2 = 91.71, P < 0.05), in which there was a statistically significant difference between those with or without chronic diseases (χ2 = 3 3.25, P < 0.05). A total of 557 elderly people over 65 years old completed the cognitive dysfunction screening, in which the prevalence of cognitive dysfunction was 17.41%, and the difference was statistically significant at the different self-assessed health status (χ2 = 96.24, P < 0.05) and with or without chronic diseases (χ2 = 107.09, P < 0.05).ConclusionThe mental health literacy and status of residents have not improved significantly during the second outbreak of the epidemic, indicating that under the normalization of epidemic prevention and control, more attention should be paid to the mental health of residents, and targeted health education and psychological intervention should be carried out to avoid relative adverse events.