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Nonalcoholic fatty liver disease (NAFLD) is considered a risk factor for cardiovascular and cerebrovascular disease owing to its close association with coagulant disturbances. However, the precise biological functions and mechanisms that connect coagulation factors to NAFLD pathology remain inadequately understood. Herein, with unbiased bioinformatics analyses followed by functional testing, we demonstrate that hepatic expression of coagulation factor VII (FVII) decreases in patients and mice with NAFLD/nonalcoholic steatohepatitis (NASH). By using adenovirus-mediated F7 -knockdown and hepatocyte-specific F7 -knockout mouse models, our mechanistic investigations unveil a noncoagulant function of hepatic FVII in mitigating lipid accumulation and lipotoxicity. This protective effect is achieved through the suppression of fatty acid uptake, orchestrated via the AKT-CD36 pathway. Interestingly, intracellular FVII directly interacts with AKT and PP2A, thereby promoting their association and triggering the dephosphorylation of AKT. Therapeutic intervention through adenovirus-mediated liver-specific overexpression of F7 results in noteworthy improvements in liver steatosis, inflammation, injury, and fibrosis in severely afflicted NAFLD mice. In conclusion, our findings highlight coagulation factor FVII as a critical regulator of hepatic steatosis and a potential target for the treatment of NAFLD and NASH. Article Highlights: Coagulation factor VII (FVII) abundance is significantly decreased during nonalcoholic fatty liver disease and negatively correlated with nonalcoholic fatty liver disease progression. Hepatic F7 deficiency exacerbates high-fat diet–induced liver steatosis. Deficiency of F7 accelerates fatty acid uptake via AKT-mediated CD36 upregulation in hepatocytes. FVII directly interacts with PP2A and AKT, triggering the dephosphorylation of AKT by PP2A. Hepatocyte-specific overexpression of F7 ameliorates liver steatosis. [ABSTRACT FROM AUTHOR]

Antioxidant molecules play a crucial role in maintaining redox homeostasis, eliminating oxidative damage, and regulating pathogenesis in phytopathogenic fungi. These antioxidants function through a complex regulatory network involving enzymatic scavengers such as the superoxide dismutases (SODs), catalases, thioredoxins, and glutathiones, as well as non-enzymatic molecules. Specifically, the thioredoxin and glutathione systems (AaTrr1, AaTsa1, AaGpx3, and AaGlr1) mediated by NADPH oxidase represent vital thiol antioxidant systems utilized to regulate the detoxification of reactive oxygen species (ROS) in Alternaria alternata. This present study investigated the regulatory roles of AaBemA, a component of the fungal NADPH oxidase (Nox) complex, in the tangerine pathotype of A. alternata. Loss-of-function genetic analysis demonstrated that AaBemA is essential for the accumulation of cellular hydrogen peroxide (H2O2). Mutant strains with defective AaBemA displayed higher sensitivity to H2O2 and the ROS-generating oxidant tert-butyl-hydroperoxide. These phenotypes closely resembled those previously observed in AaNoxB, AaTrr1, AaTsa1, AaGlr1, and AaYap1 mutants, suggesting a potential interconnection among them. Notably, the defective phenotype of ΔAaBemA could be restored through genetic complementation with wildtype AaBemA gene. Subcellular localization of a functional AaBemA fused with green fluorescent protein (GFP) gene under confocal microscope revealed a widespread distribution of green fluorescence in the cytoplasm and cell membrane, indicating high expression of AaBemA during fungal growth in A. alternata. Intriguingly, inactivation of AaBemA did not affect the morphological phenotype and pathogenicity, indicating that the AaBemA is dispensable for the aforementioned phenotypes. To explore the molecular mechanisms underlying the regulation of ROS stress response, we sequenced the whole transcriptomes of A. alternata wildtype and ROS-sensitive mutants (ΔAaBemA, ΔAaNoxB, ΔAaGlr1, ΔAaTrr1, ΔAaTsa1, ΔAaYap1) which displayed considerable sensitivity to oxidants. Comparative transcriptome analysis revealed significant influence on the gene-expression pattern of numerous genes related to glutathione metabolism, cellular oxidant detoxification, cellular response to abiotic stimulus, and cellular response to osmotic stress. The gene-expression data and pathways related to various essential metabolic processes and ROS tolerance enabled us to propose a NADPH oxidase-mediated regulatory network involving NADPH oxidase (AaNoxB, AaBemA), AaYap1, glutaredoxin (AaGPx3, AaGlr1), and thioredoxin systems (AaTrr1, AaTsa1) in responding to ROS stress in A. alternata. [ABSTRACT FROM AUTHOR]

Objective: Betaine–homocysteine methyltransferase (Bhmt) belongs to the family of methyltransferases and is involved in the one‐carbon metabolic cycle, which is associated with the risk of diabetes and adiposity. This study aimed to explore whether Bhmt participated in the development of obesity or its associated diabetes, as well as the mechanism involved. Methods: The expression levels of Bhmt were examined in stromal vascular fraction cells and mature adipocytes in obesity and nonobesity. Knockdown and overexpression of Bhmt in C3H10T1/2 cells were used to investigate Bhmt's function in adipogenesis. Bhmt's role in vivo was analyzed using an adenovirus‐expressing system and a high‐fat diet–induced obesity mouse model. Results: Bhmt was highly expressed in stromal vascular fraction cells rather than mature adipocytes of adipose tissue and was upregulated in adipose tissue in obesity and C3H10T1/2‐commited preadipocytes. Overexpression of Bhmt promoted adipocyte commitment and differentiation in vitro and exacerbated adipose tissue expansion in vivo, with a concomitant increase in insulin resistance, whereas Bhmt silencing exhibited opposite effects. Mechanistically, Bhmt‐induced adipose expansion was mediated by stimulating the p38 MAPK/Smad pathway. Conclusions: The findings of this study highlight the obesogenic and diabetogenic role of adipocytic Bhmt and propose Bhmt as a promising therapeutic target for obesity and obesity‐related diabetes. [ABSTRACT FROM AUTHOR]

The present study provides a comprehensive overview of the Bacillus velezensis strain Htq6, and its potential applications in plant disease control. Htq6 is an endophytic bacterium derived from walnut, which was found to possess a strong inhibitory effect on a wide range of plant pathogenic microorganisms and was identified as a good plant disease control agent. The entire genome of the Bacillus velezensis Htq6 was sequenced, and a comparative genomic analysis was conducted with various Bacillus species in order to better understand the mechanism of the strain's biological control. At the same time, a new classification result was presented. Additionally, transcriptome analysis was performed to explore the response mechanism of tomato gray mold fungus after treatment with the fermentation liquid of Bacillus velezensis Htq6. The study analyzed the distribution of various secondary metabolite gene clusters in the Bacillus model strains and employed RNA-Seq technology to obtain transcriptome expression profiles. Furthermore, the cell wall, cell membrane, and antioxidant-related genes of Botrytis cinerea were analyzed, providing insight into the antibacterial mechanism of biocontrol bacteria and the stress response mechanism of Botrytis cinerea. The results of the research are promising, and could potentially lead to the development of an effective biocontrol agent for the prevention and control of various plant diseases. [ABSTRACT FROM AUTHOR]

Host-pathogen interactions are the result of the continuously evolving dynamics of the genomic interphases between pathogens and the host plants. Alternaria brown spot (ABS) caused by the pathogen Alternaria alternata is a serious threat to tangerine production. Although recent studies have made significant advances in the characterization of A. alternata virulence factors, a gap exists in the regulation of virulent genes throughout the course of A. alternata infection on host plants. To gain a better understanding of the dynamic defense transcriptome in Alternaria alternata during Infection, we performed a comparative transcriptome approach. After inoculation on citrus, we found that 2142, 1964, 2359 genes were up-regulated, and 1948, 1434, 1996 genes were down-regulated at 12 hours-post-inoculation (hpi), 24 hpi and 48 hpi, respectively. Among these genes, 1333 genes were up-regulated at three time points, and 1054 genes were down-regulated, indicating that most of the differentially expressed genes at the early stage of infection tended to remain differentially expressed at the later stage of infection. In addition to the genes that are known to be part of the infection network in plant-pathogen interactions, many novel genes related to plant-pathogen interaction were identified. Interestingly, our results indicate that A. alternata is able to rapidly alter its gene expression pattern during infection process, which is vital for the successful colonization of the pathogen. Moreover, this rapid alteration of gene expression is likely to be an adaptive mechanism, enabling the pathogen to quickly respond to any changes in the environment and adapt to the host's defense system. This ability to modify gene expression quickly in the face of environmental changes could play a critical role in the successful establishment of infection. RT-qPCR analysis confirmed that the expression pattern of nine randomly selected genes from the peroxisome pathway were consistent with the RNA-seq data. Our study provided a comprehensive study of the expression of genes during A. alternata infection of citrus, which may facilitate the understanding of host-plant interactions in A. alternata. [ABSTRACT FROM AUTHOR]

To analyze the genetic structure and genetic diversity of Colletotrichum gloeosporioides as the dominant Colletotrichum species on Citrus, the Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) genetic diversity, including 63 strains isolated and selected from 8 different sites and 5 different citrus species, was studied. A total of 19 GAPDH haplotypes were identified by genetic analysis, and the main haplotype (haplotype 5) was distributed in 28 isolates, mainly from Citrus unchiu Hort. ex Tanaka (WG) and Citrus reticulata Blanco cv. Succosa (BDZ) in Huangyan (HY), Linhai (LH), and Jiande (JD) of Zhejiang province, and Mashui tangerine (MSJ) in Mengshan of Guangxi province (GX). Using the genetic differentiation index, Fst revealed significant genetic differentiation in C. gloeosporioides populations between Jiangxi province (JXGZ) and GX, HY, LH, JD, and Chun'an (CA) of Zhejiang province, and also revealed slightly less genetic differentiation for C. gloeosporioides populations between HY, LH, JD, GX, Shaanxi province (SX), and Quzhou (QZ) of Zhejiang province. In addition, Fst revealed great genetic differentiation between the C. gloeosporioides populations obtained from MSJ and Citrus paradise Macf (PTY), and also revealed weak genetic differentiation between the C. gloeosporioides populations obtained from Citrus sinensis Osbeck (QC), WG, and BDZ. The AMOVA test showed that the levels of genetic differentiation for C. gloeosporioides were 19% and 81% among and within geographic populations, respectively. It also showed that C. gloeosporioides had levels of genetic differentiation among and within host populations of 12% and 88%, respectively. The Mantel test showed that the genetic distance was not linearly correlated with geographical distance and the haplotype phylogenetic analysis showed that C. gloeosporioides from different regions and hosts were scattered in the phylogenetic tree, implying that the genetic differentiation was independent of host variety and geographical origin. We speculated that genetic differentiation may be mainly due to gene mutation, gene recombination, or gene migration within native populations and has nothing to do with natural selection triggered by geography or host variety. [ABSTRACT FROM AUTHOR]

Pinus massoniana Lamb. is found in 17 Chinese provinces and is an important timber tree species in southern China. The current seasonal drought climate is becoming increasingly severe, threatening P. massoniana growth and limiting the development of the P. massoniana industry. Plant growth, development, and stress were all regulated by AP2/ERF. We identified 124 AP2/ERF transcription factor family members in this study and discovered that all the genes had their own conserved structural domains and that PmAP2/ERFs were divided into 12 subfamilies with high conservation and similarity in gene structure and evolutionary level. Nine PmAP2/ERF genes were constitutively expressed under drought treatment, and it was hypothesized that the PmAP2/ERF96 gene negatively regulated drought stress, PmAP2/ERF46 and PmAP2/ERF49 genes showed a positive or negative response to drought in different tissues, while the remaining six genes were positively regulated. The PmAP2/ERF genes responded to drought stress following treatment with the exogenous hormones SA, ABA, and MeJA, but the expression patterns differed, with each gene responding to at least one exogenous hormone to induce up-regulation of expression under drought stress, with PmAP2/ERF11, PmAP2/ERF44, PmAP2/ERF77, and PmAP2/ERF80 genes significantly induced by three hormones. The genes mentioned above may be involved in hormone signaling pathways in response to drought stress. The results indicate that the PmAP2/ERF genes may positively or negatively regulate the corresponding signaling pathways in P. massoniana to improve drought resistance. [ABSTRACT FROM AUTHOR]

Maritime moving targets continuation observation has important implications to maintain the safety of the navigation barrier. Existing methods either rely on satellite observations, or only rely on UAV observations. Even though the two cooperative observations, it confined to a simple task allocation. They did not solve the problem of maritime moving targets continuation observation. On the basis of difference between satellites observation and UAV observation, we constructed the aerospace collaborative continuation observation model for maritime moving target, and put forward aerospace collaborative continuation observation strategy (ACCOS) to reduce the complexity of solving the model. According to the spatial and temporal characteristics of the task, ACCOS extracted five sub problems to solve the model: Satellite planning, UAV flight plan, UAV observation sequence, target potential area and distribution probability density prediction, UAV path planning. In order to realize the optimization goal of the model, the five sub problems are modelled and solved in turn. Finally, the simulation results show that the proposed method can greatly reduce the average observation period of the target, and effectively solve the problem of the continuous observation of maritime moving target.

Reinforcement learning, as an effective method to solve complex sequential decision-making problems, plays an important role in areas such as intelligent decision-making and behavioral cognition. It is well known that the sample experience replay mechanism contributes to the development of current deep reinforcement learning by reusing past samples to improve the efficiency of samples. However, the existing priority experience replay mechanism changes the sample distribution in the sample set due to the higher sampling frequency assigned to a specific transition, and it cannot be applied to actor-critic and other on-policy reinforcement learning algorithm. To address this, we propose an adaptive factor based on TD-error, which further increases sample utilization by giving more attention weight to samples of larger TD-error, and embeds it flexibly into the original Deep Q Network and Advantage Actor-Critic algorithm to improve their performance. Then we carried out the performance evaluation for the proposed architecture in the context of CartPole-V1 and 6 environments of Atari game experiments, respectively, and the obtained results either on the conditions of fixed temperature or annealing temperature, when compared to those produced by the vanilla DQN and original A2C, highlight the advantages in cumulative rewards and climb speed of the improved algorithms. [ABSTRACT FROM AUTHOR]

Link prediction in social networks has become a growing concern among researchers. In this paper, the clustering method was used to exploit the grouping tendency of nodes, and a clustering index (CI) was proposed to predict potential links with characteristics of scientific cooperation network taken into consideration. Results showed that CI performed better than the traditional indices for scientific coauthorship networks by compensating for their disadvantages. Compared with traditional algorithms, this method for a specific type of network can better reflect the features of the network and achieve more accurate predictions. [ABSTRACT FROM AUTHOR]

Clarireedia spp. is a destructive phytopathogenic fungus that causes turf dollar spot of bent-grass, leading to widespread lawn death. In this study, we explored the antifungal capability of 6-pentyl-2 H -pyran-2-one (6PP), a natural metabolite volatilized by microorganisms, which plays an important role in the biological control of turfgrass dollar spot. However, the mechanisms by which 6PP inhibits Clarireedia jacksonii remain unknown. In the present study, C. jacksonii mycelial growth was inhibited by the 6PP treatment and the 6PP treatment damaged cell membrane integrity, causing an increase in relative conduc-tivity. Furthermore, physiological and biochemistry assay showed that 6PP treatment can enhance reactive oxygen species (ROS) levels, malondialdehyde (MDA) content obviously increased with 6PP exposure, increased alchohol dehydrogenase (ADH) and depleted acetalde-hyde dehydrogenase (ALDH), and activated the activities of many antioxidant enzymes in C. jacksonii. Gen Ontology and Kyoto Encyclopedia of Genes and Genomes analysis revealed that some genes in C. jacksonii after 6PP treatment related to integrity of the cell wall and membrane, and oxidative stress were significantly downregulated. It is worth mentioning that the fatty acid degradation pathway is significantly upregulated, with an increase in ATP content and ATP synthase activity, which may promote fungal cell apoptosis. Moreover, we found that the expression of ABC transporters, and glutathione metabolism encoding genes were increased to respond to external stimuli. Taken together, these findings revealed the potential antifungal mechanism of 6PP against Clarireedia spp., which also provides a theoretical basis for the commercial utilization of 6PP as a green pesticide in the future. [Display omitted] • 6PP has inhibitory effect on Clarireedia jacksonii. • 6PP causes morphological changes and oxidative damage to C. jacksonii. • 6PP can disturbs energy metabolism and promotes cell apoptosis of C. jacksonii. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea syndrome (OSAS), characterized by chronic intermittent hypoxia (CIH), is an independent risk factor for aggravating non-alcoholic steatohepatitis (NASH). The prevailing mouse model employed in CIH research is inadequate for the comprehensive exploration of the impact of CIH on NASH development due to reduced food intake observed in CIH-exposed mice, which deviates from human responses. To address this issue, a pair-feeding investigation with CIH-exposed and normoxia-exposed mice is conducted. It is revealed that CIH exposure aggravates DNA damage, leading to hepatic fibrosis and inflammation. The analysis of genome-wide association study (GWAS) data also discloses the association between Eepd1, a DNA repair enzyme, and OSAS. Furthermore, it is revealed that CIH triggered selective autophagy, leading to the autophagic degradation of Eepd1, thereby exacerbating DNA damage in hepatocytes. Notably, Eepd1 liver-specific knockout mice exhibit aggravated hepatic DNA damage and further progression of NASH. To identify a therapeutic approach for CIH-induced NASH, a drug screening is conducted and it is found that Retigabine dihydrochloride suppresses CIH-mediated Eepd1 degradation, leading to alleviated DNA damage in hepatocytes. These findings imply that targeting CIH-mediated Eepd1 degradation can be an adjunctive approach in the treatment of NASH exacerbated by OSAS., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Deep reinforcement learning (DRL) integrates the feature representation ability of deep learning with the decision-making ability of reinforcement learning so that it can achieve powerful end-to-end learning control capabilities. In the past decade, DRL has made substantial advances in many tasks that require perceiving high-dimensional input and making optimal or near-optimal decisions. However, there are still many challenging problems in the theory and applications of DRL, especially in learning control tasks with limited samples, sparse rewards, and multiple agents. Researchers have proposed various solutions and new theories to solve these problems and promote the development of DRL. In addition, deep learning has stimulated the further development of many subfields of reinforcement learning, such as hierarchical reinforcement learning (HRL), multiagent reinforcement learning, and imitation learning. This article gives a comprehensive overview of the fundamental theories, key algorithms, and primary research domains of DRL. In addition to value-based and policy-based DRL algorithms, the advances in maximum entropy-based DRL are summarized. The future research topics of DRL are also analyzed and discussed.

The incomplete and imperfect essence of the battlefield situation results in a challenge to the efficiency, stability, and reliability of traditional intention recognition methods. For this problem, we propose a deep learning architecture that consists of a contrastive predictive coding (CPC) model, a variable-length long short-term memory network (LSTM) model, and an attention weight allocator for online intention recognition with incomplete information in wargame (W-CPCLSTM). First, based on the typical characteristics of intelligence data, a CPC model is designed to capture more global structures from limited battlefield information. Then, a variable-length LSTM model is employed to classify the learned representations into predefined intention categories. Next, a weighted approach to the training attention of CPC and LSTM is introduced to allow for the stability of the model. Finally, performance evaluation and application analysis of the proposed model for the online intention recognition task were carried out based on four different degrees of detection information and a perfect situation of ideal conditions in a wargame. Besides, we explored the effect of different lengths of intelligence data on recognition performance and gave application examples of the proposed model to a wargame platform. The simulation results demonstrate that our method not only contributes to the growth of recognition stability, but it also improves recognition accuracy by 7%-11%, 3%-7%, 3%-13%, and 3%-7%, the recognition speed by 6- 32× , 4- 18× , 13-* × , and 1- 6× compared with the traditional LSTM, classical FCN, OctConv, and OctFCN models, respectively, which characterizes it as a promising reference tool for command decision-making.

Background: The ruminant gastrointestinal contains numerous microbiomes that serve a crucial role in sustaining the host's productivity and health. In recent times, numerous studies have revealed that variations in influencing factors, including the environment, diet, and host, contribute to the shaping of gastrointestinal microbial adaptation to specific states. Therefore, understanding how host and environmental factors affect gastrointestinal microbes will help to improve the sustainability of ruminant production systems., Results: Based on a graphical analysis perspective, this study elucidates the microbial topology and robustness of the gastrointestinal of different ruminant species, showing that the microbial network is more resistant to random attacks. The risk of transmission of high-risk metagenome-assembled genome (MAG) was also demonstrated based on a large-scale survey of the distribution of antibiotic resistance genes (ARG) in the microbiota of most types of ecosystems. In addition, an interpretable machine learning framework was developed to study the complex, high-dimensional data of the gastrointestinal microbial genome. The evolution of gastrointestinal microbial adaptations to the environment in ruminants were analyzed and the adaptability changes of microorganisms to different altitudes were identified, including microbial transcriptional repair., Conclusion: Our findings indicate that the environment has an impact on the functional features of microbiomes in ruminant. The findings provide a new insight for the future development of microbial resources for the sustainable development in agriculture., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yan, Shi, Bao, Gai, Liang, Jiang and Li.)