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Abstract Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. This study was aimed to identify a lipid metabolism-related signature associated with the HCC microenvironment to improve the prognostic prediction of HCC patients. Clinical information and expression profile data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, including the GEO dataset GSE76427. The gene expression profile of lipid metabolism was downloaded from Molecular Signatures Database (MSigDB) database. The infiltrating immune cells were estimated by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE), MCP-counter, and TIMER algorithms. Functional analysis, including Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) were performed to elucidate the underlying mechanisms. The prognostic risk model was performed by Least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis. Two distinct subgroups of survival were identified. Better prognosis was associated with high immune score, high abundance of immune infiltrating cells, and high immune status. GO and KEGG analysis showed that differentially expressed genes (DEGs) between the two subgroups were mainly enriched in immune related pathways. GSEA analysis suggested that the expression of lipid metabolism related genes (LMRGs) was related to dysregulation of immune in the high-risk group. Risk models and clinical features based on LMRGs predicted HCC prognosis. This study indicated that the lipid metabolism-related signature was important for the prognosis of HCC. The expression of LMRGs was related to the immune microenvironment of HCC patients and could be used to predict the prognosis of HCC.

In the context of chronic hepatitis B virus (HBV) infection, the continuous replication of HBV within host hepatocytes is a characteristic feature. Rather than directly causing hepatocyte destruction, this replication leads to immune dysfunction and establishes a state of T-B immune tolerance. Successful clearance of the HBV virus is dependent on the close collaboration between humoral and cellular immunity. Humoral immunity, mediated by B-cell subpopulations, and cellular immunity, dominated by T-cell subpopulations show varying degrees of dysfunction during chronic hepatitis B (CHB). Notably, not all T- and B-cells produce positive immune responses. This review examine the most recent developments in the mutual regulation of T-B cells during chronic HBV infection. Our focus is on the prevailing immunotherapeutic strategies, such as T cell engineering, HBV-related vaccines, PD-1 inhibitors, and Toll-like receptor agonists. While nucleos(t)ide analogues (NUCs) and interferons have notable limitations, including inadequate viral suppression, drug resistance, and adverse reactions, several HBV entry inhibitors have shown promising clinical efficacy. To overcome the challenges posed by NUCs or monotherapy, the combination of immunotherapy and novel antiviral agents presents a promising avenue for future CHB treatment and potential cure.

BackgroundLiver disease is among the top ten causes of death globally. With studies suggesting a link between gut microbiota (GM) and liver disease.MethodWe selected summary statistics data from the largest available whole-genome association study (n = 13,266) of GM by the MiBioGen consortium as the exposure, and obtained liver disease-related data from IEU Open GWAS and The NHGRI-EBI GWAS Catalog. A two-sample Mendelian Randomization (MR) analysis employing various methods, to establish the causal relationship between GM and five liver diseases. Meanwhile, single-cell RNA sequencing data were used to examine Prevotella-related genes expression under healthy and disease liver.ResultsThe IVW analysis indicate a causal relationship between GM and liver diseases, with Prevotella exhibiting a protective effect in all five liver diseases: Alcoholic liver disease (OR:0.81,95% confidence interval:0.66-1.00,PIVW = 0.0494); Cirrhosis (OR: 0.85,95% confidence interval: 0.73-0.99,PIVW = 0.0397); Hepatic failure, not elsewhere classified (OR:0.60,95% confidence interval:0.37-0.95,PIVW = 0.0305); Benign neoplasm:Liver (OR:0.39,95% confidence interval:0.2-0.75,PIVW = 0.0046); Malignant neoplasm of liver, primary (OR:0.41, 95% confidence interval:0.18-0.93,PIVW = 0.0334). The single-cell results suggest differential expression of Prevotella-related genes between liver disease patients and healthy individuals.ConclusionOur MR results show a causal relationship between the GM and liver disease. Prevotella displays a notable protective effect. This finding may enhance the precision of GM-based therapies and offer new insights for clinical research.

BackgroundIn the 21st century, childhood overweight and obesity have become major public health issues worldwide. Previous studies have shown that breastfeeding helps prevent overweight or obesity in children. Despite the significant advantages of breastfeeding, the global exclusive breastfeeding rate for infants under 6 months old is only 40%, while in the United States, the rate is only 25%. The aim of this study is to explore the relationship between breastfeeding duration and BMI in children aged 2 to 6 in the United States, and to raise awareness of breastfeeding.MethodsA cross-sectional study included 2,769 participants between the ages of 2 and 6 from a sample that represented the entire NHANES 2009–2018. Data was analyzed using EmpowerStats, (www.empowerstats.com) linear regression as well as Chi-square test, t-tests, multivariate regression analysis and smooth cure fitting were done.ResultsBreastfeeding duration long-term group exhibited a statistically significant negative association with BMI, with a regression coefficient of −0.21 (P < 0.05). The continuous analysis of breastfeeding duration by tertile also demonstrate a statistically significant negative association with BMI. Subgroup analysis revealed that the potential benefits of breastfeeding on BMI were more obvious in low-income environments and maternal age 18 to 35 years, with a regression coefficient of −0.57 and −0.24, respectively (all P < 0.05).ConclusionThe findings emphasize the importance of breastfeeding in reducing childhood overweight/obesity and preventing associated diseases, both in clinical and public health settings.

The incidence of liver disease continues to rise, encompassing a spectrum from simple steatosis or non-alcoholic fatty liver disease (NAFLD) to non-alcoholic steatohepatitis (NASH), cirrhosis and liver cancer. Dietary habits in individuals with liver disease may significantly impact the treatment and prevention of these conditions. This article examines the role of chili peppers, a common dietary component, in this context, focusing on capsaicin, the active ingredient in chili peppers. Capsaicin is an agonist of the transient receptor potential vanilloid subfamily 1 (TRPV1) and has been shown to exert protective effects on liver diseases, including liver injury, NAFLD, liver fibrosis and liver cancer. These protective effects are attributed to capsaicin’s anti-oxidant, anti-inflammatory, anti-steatosis and anti-fibrosis effects. This article reviewed the different molecular mechanisms of the protective effect of capsaicin on liver diseases.

Lithium argyrodite solid electrolytes have attracted ever‐increasing attention for all‐solid‐state batteries due to their high ionic conductivity and low cost. However, the relation between structure and ionic transport for the halogen‐rich lithium argyrodites under different synthesis routes is still elusive. Herein, the influence of synthesis procedures, such as annealing conditions and balling milling, on the structure, ionic conductivity, and activation energy of the lithium argyrodite (e.g., Li5.5PS4.5Cl1.5, Li5.3PS4.3Cl1.7), is systematically investigated. Compared with high‐energy ball milling followed by annealing, using fast dry mixing followed by annealing can obtain comparable ionic conductivity of the chlorine‐rich lithium argyrodites. Single‐crystal LiNi0.83Co0.11Mn0.06O2‐based solid‐state battery with these electrolytes shows stable cycling performance, demonstrating that chlorine‐rich lithium argyrodite is a promising candidate for all‐solid‐state batteries.

Hepatocellular carcinoma (HCC) is one of the most common cancers and the third leading cause of death worldwide. surgery, transarterial chemoembolization (TACE), systemic therapy, local ablation therapy, radiotherapy, and targeted drug therapy with agents such as sorafenib. However, the tumor microenvironment of liver cancer has a strong immunosuppressive effect. Therefore, new treatments for liver cancer are still necessary. Immune checkpoint molecules, such as programmed death-1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T lymphocyte antigen-4 (CTLA-4), along with high levels of immunosuppressive cytokines, induce T cell inhibition and are key mechanisms of immune escape in HCC. Recently, immunotherapy based on immune checkpoint inhibitors (ICIs) as monotherapy or in combination with tyrosine kinase inhibitors, anti-angiogenesis drugs, chemotherapy agents, and topical therapies has offered great promise in the treatment of liver cancer. In this review, we discuss the latest advances in ICIs combined with targeted drugs (targeted-immune combination) and other targeted-immune combination regimens for the treatment of patients with advanced HCC (aHCC) or unresectable HCC (uHCC), and provide an outlook on future prospects. The literature reviewed spans the last five years and includes studies identified using keywords such as “hepatocellular carcinoma,” “immune checkpoint inhibitors,” “targeted therapy,” “combination therapy,” and “immunotherapy”.

NRF2 is an important transcription factor that regulates redox homeostasis in vivo and exerts its anti-oxidative stress and anti-inflammatory response by binding to the ARE to activate and regulate the transcription of downstream protective protein genes, reducing the release of reactive oxygen species. Ferroptosis is a novel iron-dependent, lipid peroxidation-driven cell death mode, and recent studies have shown that ferroptosis is closely associated with acute lung injury/acute respiratory distress syndrome (ALI/ARDS). NRF2 is able to regulate ferroptosis through the regulation of the transcription of its target genes to ameliorate ALI/ARDS. Therefore, This article focuses on how NRF2 plays a role in ALI/ARDS by regulating ferroptosis. We further reviewed the literature and deeply analyzed the signaling pathways related to ferroptosis which were regulated by NRF2. Additionally, we sorted out the chemical molecules targeting NRF2 that are effective for ALI/ARDS. This review provides a relevant theoretical basis for further research on this theory and the prevention and treatment of ALI/ARDS. The intended audience is clinicians and researchers in the field of respiratory disease.

Abstract All-solid-state batteries with non-flammable solid electrolytes offer enhanced safety features, and show the potential for achieving higher energy density by using lithium metal as the anode. Among various solid electrolytes, sulfides are favored for their high room-temperature ionic conductivity and low-temperature processing. However, making large-scale thin electrolyte films via pressing sulfide powder is still challenging. A polymer has recently been introduced as a binder or framework to obtain a flexible thin sulfide-based composite electrolyte film with high ionic conductivity. In this Review, we initially discuss the ionic transport mechanism of sulfide/polymer composite electrolyte films. Then, the preparation methods and the properties of sulfide-based composite electrolytes are introduced in detail, and the advantages and disadvantages of each method are also analyzed. We later discuss the application of composite electrolyte films in all-solid-state batteries. Finally, we provide a perspective on the future development direction of sulfide-based composite electrolyte films.

Abstract Background Chronic hepatitis B virus (HBV) infection is the major etiology of hepatocellular carcinoma (HCC). However, the mechanism of hepatitis B-related hepatocellular carcinoma (HBV-related HCC) is still unclear. Therefore, understanding the pathogenesis and searching for drugs to treat HBV-related HCC was an effective strategy to treat this disease. Purpose Bioinformatics was used to predict the potential targets of HBV-related HCC. The reverse network pharmacology of key targets was used to analyze the clinical drugs, traditional Chinese medicine (TCM) and small molecules of TCM in the treatment of HBV-related HCC. Methods In this study, three microarray datasets totally containing 330 tumoral samples and 297 normal samples were selected from the GEO database. These microarray datasets were used to screen DEGs. And the expression profile and survival of 6 key genes were analyzed. In addition, Comparative Toxicogenomics Database and Coremine Medical database were used to enrich clinical drugs and TCM of HBV-related HCC by the 6 key targets. Then the obtained TCM were classified based on the Chinese Pharmacopoeia. Among these top 6 key genes, CDK1 and CCNB1 had the most connection nodes and the highest degree and were the most significantly expressed. In general, CDK1 and CCNB1 tend to form a complex, which is conducive to cell mitosis. Hence, this study mainly studied CDK1 and CCNB1. HERB database was used to predict small molecules TCM. The inhibition effect of quercetin, celastrol and cantharidin on HepG2.2.15 cells and Hep3B cells was verified by CCK8 experiment. The effects of quercetin, celastrol and cantharidin on CDK1 and CCNB1 of HepG2.2.15 cells and Hep3B cells were determined by Western Blot. Results In short, 272 DEGs (53 upregulated and 219 downregulated) were identified. Among these DEGs, 6 key genes with high degree were identified, which were AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS. Kaplan–Meier plotter analysis showed that higher expression levels of AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS were associated with poor OS. According to the first 6 key targets, a variety of drugs and TCM were identified. These results showed that clinical drugs included targeted drugs, such as sorafenib, palbociclib and Dasatinib. and chemotherapy drugs, such as cisplatin and doxorubicin. TCM, such as the TCM flavor was mainly warm and bitter, and the main meridians were liver and lung. Small molecules of TCM included flavonoids, terpenoids, alkaloids and glycosides, such as quercetin, celastrol, cantharidin, hesperidin, silymarin, casticin, berberine and ursolic acid, which have great potential in anti-HBV-related HCC. For molecular docking of chemical components, the molecules with higher scores were flavonoids, alkaloids, etc. Three representative types of TCM small molecules were verified respectively, and it was found that quercetin, celastrol and cantharidin inhibited the proliferation of HepG2.2.15 cells and Hep3B cells along concentration gradient. Quercetin, celastrol and cantharidin decreased CDK1 expression in HepG2.2.15 and Hep3B cells, but for CCNB1, only cantharidin decreased CCNB1 expression in the two strains of cells. Conclusion In conclusion, AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS could be potential targets for the diagnosis and prognosis of HBV-related HCC. Clinical drugs include chemotherapeutic and targeted drug, traditional Chinese medicine is mainly bitter and warm TCM. Small molecular of TCM including flavonoids, terpenoids and glycosides and alkaloids, which have great potential in anti-HBV-related HCC. This study provides potential therapeutic targets and novel strategies for the treatment of HBV-related HCC.

As a kind of inexhaustible renewable energy, solar energy is popular, and photovoltaic power generation has been paid attention to by all circles. However, determining the global maximum power point (GMPP) is difficult under external ambient temperature and light intensity change, and MPPT control technology becomes the key to research. Fast, accurate, and stable GMPP capture has become a hot research problem in PV power generation systems. The GWO algorithm incorporating the Levy flight function and the INC using the vertex as the dividing point with different step sizes on the left and right sides are combined and applied to the MPPT control strategy of PV systems. The global search is completed by IGWO first, and then the exact search is completed by the improved INC when it is close to the global optimum. The final tracking accuracy is above 99%, and compared with the GWO, INC, and ICS-IP&O algorithms, respectively, in the case of abrupt changes, the tracking time is accelerated by 0.021 s on average. The oscillation amplitude is smaller, and the voltage is more stable.

Abstract In chronic infections and cancers, T lymphocytes (T cells) are exposed to persistent antigen or inflammatory signals. The condition is often associated with a decline in T-cell function: a state called “exhaustion”. T cell exhaustion is a state of T cell dysfunction characterized by increased expression of a series of inhibitory receptors (IRs), decreased effector function, and decreased cytokine secretion, accompanied by transcriptional and epigenetic changes and metabolic defects. The rise of immunotherapy, particularly the use of immune checkpoint inhibitors (ICIs), has dramatically changed the clinical treatment paradigm for patients. However, its low response rate, single target and high immunotoxicity limit its clinical application. The multiple immunomodulatory potential of traditional Chinese medicine (TCM) provides a new direction for improving the treatment of T cell exhaustion. Here, we review recent advances that have provided a clearer molecular understanding of T cell exhaustion, revealing the characteristics and causes of T cell exhaustion in persistent infections and cancers. In addition, this paper summarizes recent advances in improving T cell exhaustion in infectious diseases and cancer with the aim of providing a comprehensive and valuable source of information on TCM as an experimental study and their role in collaboration with ICIs therapy.

The application of immunotherapy in tumor, especially immune checkpoint inhibitors (ICIs), has played an important role in the treatment of advanced unresectable liver cancer. However, the efficacy of ICIs varies greatly among different patients, which has aroused people’s attention to the regulatory mechanism of programmed death ligand-1 (PD-L1) in the immune escape of liver cancer. PD-L1 is regulated by multiple levels and signaling pathways in hepatocellular carcinoma (HCC), including gene variation, epigenetic inheritance, transcriptional regulation, post-transcriptional regulation, and post-translational modification. More studies have also found that the high expression of PD-L1 may be the main factor affecting the immunotherapy of liver cancer. However, what is the difference of PD-L1 expressed by different types of cells in the microenvironment of HCC, and which type of cells expressed PD-L1 determines the effect of tumor immunotherapy remains unclear. Therefore, clarifying the regulatory mechanism of PD-L1 in liver cancer can provide more basis for liver cancer immunotherapy and combined immune treatment strategy. In addition to its well-known role in immune regulation, PD-L1 also plays a role in regulating cancer cell proliferation and promoting drug resistance of tumor cells, which will be reviewed in this paper. In addition, we also summarized the natural products and drugs that regulated the expression of PD-L1 in HCC.

Single-cell sequencing (scRNA-seq) technology provides higher resolution of cellular differences than bulk RNA sequencing and reveals the heterogeneity in biological research. The analysis of scRNA-seq datasets is premised on the subpopulation assignment. When an appropriate reference is not available, such as specific marker genes and single-cell reference atlas, unsupervised clustering approaches become the predominant option. However, the inherent sparsity and high-dimensionality of scRNA-seq datasets pose specific analytical challenges to traditional clustering methods. Therefore, a various deep learning-based methods have been proposed to address these challenges. As each method improves partially, a comprehensive method needs to be proposed. In this article, we propose a novel scRNA-seq data clustering method named AttentionAE-sc (Attention fusion AutoEncoder for single-cell). Two different scRNA-seq clustering strategies are combined through an attention mechanism, that include zero-inflated negative binomial (ZINB)-based methods dealing with the impact of dropout events and graph autoencoder (GAE)-based methods relying on information from neighbors to guide the dimension reduction. Based on an iterative fusion between denoising and topological embeddings, AttentionAE-sc can easily acquire clustering-friendly cell representations that similar cells are closer in the hidden embedding. Compared with several state-of-art baseline methods, AttentionAE-sc demonstrated excellent clustering performance on 16 real scRNA-seq datasets without the need to specify the number of groups. Additionally, AttentionAE-sc learned improved cell representations and exhibited enhanced stability and robustness. Furthermore, AttentionAE-sc achieved remarkable identification in a breast cancer single-cell atlas dataset and provided valuable insights into the heterogeneity among different cell subtypes.

ABSTRACT Objective: To determine the absolute number of serum T lymphocytes and cytokine levels and the characteristics of patients with active pulmonary tuberculosis and to assess their effect on the immune status of these patients and their diagnostic and predictive value for tuberculosis. Methods: We included 1,069 patients with active tuberculosis, 51 patients with latent tuberculosis infection, and 600 health individuals. Absolute serum T-lymphocyte counts and cytokine levels were quantified. Results: T lymphocytes were significantly reduced in patients with active tuberculosis when compared with healthy individuals. The immune function of patients gradually decreased with age and was stronger in female patients than in males. Th1 cells expressed higher levels of cytokines than did Th2 cells. Logistic regression analysis showed that reduced CD3+ T, CD8+ T, and NK cell counts, as well as reduced IL-4 and IFN-g expression, were independent influencing factors for active tuberculosis. ROC analysis showed that the sensitivity and specificity of absolute CD3+ T and CD8+ T lymphocyte counts and combined factors were significantly higher than were those of IL-4 and IFN-g for diagnosing active tuberculosis. Conclusions: Serum T-lymphocyte counts and cytokine levels can assess the immune status of tuberculosis patients; they are also useful biomarkers for predicting and diagnosing tuberculosis.

The fabrication of silicon nitride (Si3N4) fiber-reinforced boron nitride (BN) and Si3N4 matrix (Si3N4f/BN/Si3N4) composites with BN interphase through precursor infiltration and pyrolysis (PIP) process is reported. The effects of heating rate during PIP process on mechanical and dielectric properties of composites are analyzed. When the heating rate is 5 °C/min, the overall performance of Si3N4f/BN/Si3N4 composites is optimal, and the flexural strength and fracture toughness attain 138 MPa and 5.7 MPa m1/2, and the dielectric constant and dielectric loss are 3.90 and 0.008, respectively. The composites achieve a synergy combining structural with functional properties. The influence mechanism of the heating rate during PIP process on the Si3N4f/BN/Si3N4 composites disclose the following. First, the heating rate makes an effect on the carbon content in the Si3N4 matrix, and consequently the dielectric properties of the composites are changed. Second, at 8 °C/min, the modulus of Si3N4 matrix is the lowest due to the existence of nanopores. At 2 °C/min, the strong axial tensile stress results in severe cracking of the Si3N4 matrix, so the matrix modulus decrease. Third, the heating rate strongly affects the radial stress state at the interphase, which affects the interfacial shear strength of the composites. The matrix modulus and interfacial shear strength can be optimized at 5 °C/min to improve the mechanical properties of the composites.

Mitochondrial dysfunction plays an important role in the occurrence and development of different liver diseases. Oxidative phosphorylation (OXPHOS) dysfunction and production of reactive oxygen species are closely related to mitochondrial dysfunction, forcing glycolysis to become the main source of energy metabolism of liver cells. Moreover, glycolysis is also enhanced to varying degrees in different liver diseases, especially in liver cancer. Therefore, targeting the glycolytic signaling pathway provides a new strategy for the treatment of non-alcoholic fatty liver disease (NAFLD) and liver fibrosis associated with liver cancer. Natural products regulate many steps of glycolysis, and targeting glycolysis with natural products is a promising cancer treatment. In this review, we have mainly illustrated the relationship between glycolysis and liver disease, natural products can work by targeting key enzymes in glycolysis and their associated proteins, so understanding how natural products regulate glycolysis can help clarify the therapeutic mechanisms these drugs use to inhibit liver disease.

It is a challenging task to accurately track the global maximum power point (GMPP) in a changing environment in widely used photovoltaic (PV) systems. So far, a variety of maximum power point (MPP) tracking algorithms have been used in solar PV power systems. The classical algorithm is simple and fast to track the speed effectively in a constant environment, but it can get stuck at an extreme point in a variable environment. In this paper, the variable-step incremental conductance (VINC) method is combined with the gray wolf optimization (GWO) algorithm. Firstly, GWO conducts a global search. When the search reaches the area near GMPP, the next step of the search process is carried out based on the iteration number conditions of GWO. Enter the search process of VINC and determine whether the current search process is on the left or right side of the vertex based on the current search value. And adjust the duty cycle during the VINC search process using different variable step size methods based on the left and right sides, and finally accurately locate the GMPP value. To verify the robustness of the proposed algorithm, simulation, and experimental comparisons were conducted between the proposed method in the article and GWO and VINC. The tracking efficiency of static shadows, simulated dynamic shadows, and experimental static and dynamic shadows is 99.80%, 98.82%, 99.43%, and 98.51%, respectively. The tracking time of simulation and experiment is 46.49% and 89.34% faster than GWO and VINC technologies, respectively. The results show that compared with the GWO and VINC methods, the proposed method has improved tracking speed and efficiency. Moreover, compared with the method that combines the two intelligent algorithms, this method has fewer algorithm parameters, a simple calculation process, lower complexity, lower hardware requirements, and better actual implementation performance.

Natural perception relies inherently on inferring causal structure in the environment. However, the neural mechanisms and functional circuits essential for representing and updating the hidden causal structure and corresponding sensory representations during multisensory processing are unknown. To address this, monkeys were trained to infer the probability of a potential common source from visual and proprioceptive signals based on their spatial disparity in a virtual reality system. The proprioceptive drift reported by monkeys demonstrated that they combined previous experience and current multisensory signals to estimate the hidden common source and subsequently updated the causal structure and sensory representation. Single-unit recordings in premotor and parietal cortices revealed that neural activity in the premotor cortex represents the core computation of causal inference, characterizing the estimation and update of the likelihood of integrating multiple sensory inputs at a trial-by-trial level. In response to signals from the premotor cortex, neural activity in the parietal cortex also represents the causal structure and further dynamically updates the sensory representation to maintain consistency with the causal inference structure. Thus, our results indicate how the premotor cortex integrates previous experience and sensory inputs to infer hidden variables and selectively updates sensory representations in the parietal cortex to support behavior. This dynamic loop of frontal-parietal interactions in the causal inference framework may provide the neural mechanism to answer long-standing questions regarding how neural circuits represent hidden structures for body awareness and agency.

Abstract Background Interferon-inducible 16 (IFI16)/caspase-1 inflammasome activates and secretes IL-1β. However, it is still unclear whether the IFI16 inflammasome is involved in human laryngeal squamous cell carcinoma. Autophagy directly removed inflammasome components and limited early IL-1β production. RalB is required for the crosstalk between inflammasome and autophagy in macrophages. Dihydroartemisinin (DHA), the main derived ingredient of artemisinin, has a variety of biological activities. The mechanism of DHA in regulating the crosstalk between IFI16 inflammasome and autophagy by inhibiting RalB expression was analyzed in order to provide clues for new therapeutic methods in laryngeal cancer. Methods The expression of IFI16 was analyzed by Oncomine and GEPIA databases and detected by Western blot and immunohistochemistry. The relationship between IFI16 inflammasome and autophagy was investigated by transmission electron microscopy, immunofluorescence assay, etc. in Hep-2, Cal-27 and HeLa cells treated with DHA. The xenograft tumor of hep-2 cell in nude mice were used to assess the effect of DHA on laryngeal cancer. Results It was reported for the first time in this study that IFI16 was overexpressed and positively correlated with caspase-1 in laryngeal carcinoma tissues. DHA significantly inhibited the activation of inflammasome and reduced IL-1β production in the microenvironment of Hep-2 cell xenograft tumor in nude mice. Mechanistically, we found that DHA degraded RalB, inhibited USP33 expression, and triggered autophagy. Meanwhile, enhanced autophagy can reduce the expression of RalB and USP33. Furthermore, DHA promotes autophagy, which suppresses the activation of IFI16/caspase-1 inflammasome and IL-1β production. Conclusions Therefore, our findings demonstrate that DHA may act as a RalB inhibitor to regulate the crosstalk between autophagy and IFI16/caspase-1 inflammasome, which inhibits IL-1β production in tumor microenvironment.

Seamounts have important effects on sound propagation in deep water. A sound propagation experiment was conducted in the South China Sea in 2016. The three-dimensional (3D) effects of a seamount on sound propagation are observed in different propagation tracks. Ray methods (BELLHOP N×2D and 3D models) are used to analyze and explain the phenomena. The results show that 3D effects have obvious impacts on a sound field within a horizontal refraction zone behind the seamount because some sound beams cannot reach the receiver for the horizontal refraction effects, which impacts the sound field within a certain angle range behind the seamount. The arrival structure results show that the eigenrays after horizontal reflection will arrive at the receiver earlier than those obtained from the two-dimensional (2D) model within the horizontal refraction zone behind the seamount. This means that the horizontal reflection effect of a seamount will cause the shortening of sound propagation paths. Finally, in the reflection zone in front of the seamount, the 2D and 3D TL results show that the shape of the reflection zone is similar to an “arch” type, and the horizontal refraction of sound waves has little effect on the TLs in the reflection zone of a seamount.

Carbohydrates are nutrients and important signal molecules in higher plants. Sugar transporters (ST) play important role not only in long-distance transport of sugar, but also in sugar accumulations in sink cells. Longan (Dimocarpus longan L.) is one of the most important commercial tropical/subtropical evergreen fruit species in Southeast Asia. In this study, a total of 52 longan sugar transporter (DlST) genes were identified and they were divided into eight clades according to phylogenetic analysis. Out of these 52 DlST genes, many plant hormones (e.g., MeJA and gibberellin), abiotic (e.g., cold and drought), and biotic stress responsive element exist in their promoter region. Gene structure analysis exhibited that each of the clades have closely associated gene architectural features based on similar number or length of exons. The numbers of DlSTs, which exhibited alternative splicing (AS) events, in flower bud is more than that in other tissues. Expression profile analysis revealed that ten DlST members may regulate longan flowerbud differentiation. In silico expression profiles in nine longan organs indicated that some DlST genes were tissue specificity and further qRT-PCR analysis suggested that the transcript level of seven DlSTs (DlINT3, DlpGlcT1, DlpGlcT2, DlPLT4, DlSTP1, DlVGT1 and DlVGT2) was consistent with sugar accumulation in fruit, indicating that they might be involved in sugar accumulations during longan fruit development. Our findings will contribute to a better understanding of sugar transporters in woody plant.

An a priori map is often unavailable for a mobile robot in a new environment. In a large-scale environment, relying on manual guidance to construct an environment map will result in a huge workload. Hence, an autonomous exploration algorithm is necessary for the mobile robot to complete the exploration actively. This study proposes an autonomous exploration and mapping method based on an incremental caching topology−grid hybrid map (TGHM). Such an algorithm can accomplish the exploration task with high efficiency and high coverage of the established map. The TGHM is a fusion of a topology map, containing the information gain and motion cost for exploration, and a grid map, representing the established map for navigation and localization. At the beginning of one exploration round, the method of candidate target point generation based on geometry rules are applied to extract the candidates quickly. Then, a TGHM is established, and the information gain is evaluated for each candidate topology node on it. Finally, the node with the best evaluation value is selected as the next target point and the topology map is updated after each motion towards it as the end of this round. Simulations and experiments were performed to benchmark the proposed algorithm in robot autonomous exploration and map construction.

Eupatorin is the major bioactive component of Java tea (Orthosiphon stamineus), exhibiting strong anticancer and anti-inflammatory activities. However, no research on the metabolism of eupatorin has been reported to date. In the present study, ultra-high-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) combined with an efficient online data acquisition and a multiple data processing method were developed for metabolite identification in vivo (rat plasma, bile, urine and feces) and in vitro (rat liver microsomes and intestinal flora). A total of 51 metabolites in vivo, 60 metabolites in vitro were structurally characterized. The loss of CH2, CH2O, O, CO, oxidation, methylation, glucuronidation, sulfate conjugation, N-acetylation, hydrogenation, ketone formation, glycine conjugation, glutamine conjugation and glucose conjugation were the main metabolic pathways of eupatorin. This was the first identification of metabolites of eupatorin in vivo and in vitro and it will provide reference and valuable evidence for further development of new pharmaceuticals and pharmacological mechanisms.

Background: Antibodies, which target programmed cell death protein-1 (PD-1) or its ligand programmed death ligand-1 (PD-L1), can rescue T cells from an exhausted state and resume their immune response to cancer cells. Clinically, the purpose of blocking the PD-1/PD-L1 signaling pathway is to induce immune cells to play an anti-tumor role. However, the effect of intertumor PD-1/PD-L1 signal blocking on tumor cells remains unclear. Methods: HepG2 cells were treated with DHA, IFN-γ, BSA, DDP, PD-1-Fc (1 μg/ml), IgG-Fc, nivolumab, or human IgG for 24 h, respectively. GEPIA, cBioPortal, and TIMER databases were used to analyze the correlation between YAP1, PD-1, and PD-L1 and ERK, ERK-5, JNK, and p38. Western blot was used to detect the expression of YAP1 and p-ERK. Results: GEPIA, cBioPortal, and TIMER databases analysis showed that YAP1 was positively correlated with ERK. After HepG2 cells were treated with PD98059 (ERK inhibitor), the expression of YAP1 was decreased. In this study, we investigated the inhibitory effect of PD98059 on PD-1/PD-L1 signaling. Our study found that PD-1-Fc (PD-1 fusion protein) promoted the expression of p-ERK/ERK and YAP1 in HepG2 cells. In contrast, nivolumab (PD-1 blocking antibody) reduced the expression of p-ERK/ERK and YAP1 in IFN-γ-pretreated HepG2 cells. In addition, the application of DHA also inhibited the expression of p-ERK/ERK to inhibit YAP1. Furthermore, treatment of HepG2 cells with DHA alone or DHA combined with cisplatin (DDP) both inhibited the expression of p-ERK/ERK and YAP1. Conclusions: These results suggested that PD-1/ PD-L1 interactions between tumor cells could promote the expression of ERK or YAP1 within tumors. Moreover, the conduction of PD-1/PD-L1 could be reversed using ERK inhibitors. [ABSTRACT FROM AUTHOR]

Abstract Background Hydrogen peroxide (H2O2), a novel water treatment agent, can be used for disinfection, water quality adjustment, and disease prevention, while excessive H2O2 can injure farm animals, even leading to death. Hydrogen peroxide is a recommended disinfectant and bactericide for treating gill diseases and vibriosis in the greenfin horse-faced filefish Thamnaconus septentrionalis. However, its cumulative effect, toxic molecular mechanism and relevant signal transduction/metabolic networks in marine fishes are largely unknown. Results We employed a multi-omics approach to investigate the detrimental effects of 50 mg/L H2O2 exposure (2 h/d) on filefish for 2 d, 4 d, and 6 d. Transcriptome sequencing showed that differentially expressed genes (DEGs) were mainly classified into functions such as signal transduction, nervous system, liver and bile acid metabolism, energy metabolism, cell adhesion and communication, inflammation and immune response. Metabolomic analysis found that the significantly changed metabolites (SCMs) were involved in phenylalanine metabolism, inflammatory mediator regulation, linoleic acid metabolism, and necroptosis. The main SCMs were cholic acid, carnitine C12:1, dimethylmalonic acid, glutamic acid, L-lactic acid, shikimic acid, 2-methylsuccinic acid, and others. Moreover, H2O2-induced oxidative stress also disturbs the balance of the gut microbiota, altering the microbial composition and affecting digestive processes. Conclusions Integrated multiomics analysis revealed that H2O2-induced detrimental impacts include mucosal damage, inflammatory and immune responses, altered energy metabolism, and gut microbiota disorders. These findings offer novel insights into the harmful effects and signal transduction/metabolic pathways triggered by H2O2 exposure in marine fishes.

Abstract Climate change is exerting unprecedented impacts on marine habitats, and many sessile invertebrate species, such as the endangered giant clam Tridacna maxima, are particularly sensitive to climate driven changes in their environment. Understanding its spatial distribution and conservation requirements is of crucial significance in formulating effective protection strategies. However, the species has been extensively harvested and depleted in many regions, leading to its listing as endangered species by the International Union for Conservation of Nature (IUCN). While marine protected areas (MPAs) are considered effective conservation tools, it remains uncertain whether existing MPAs adequately protect these vulnerable giant clams. To enhance the management and conservation of this species, we employed a Species Distribution Models (SDMs) approach, integrating occurrence records of T. maxima with environmental variables, to predict its potential distribution based on habitat suitability and capture spatiotemporal changes. Based on geographical and genetic variations, the T. maxima in the Indo‐Pacific core region is primarily divided into two populations: the East Indian Ocean‐South China Sea population (EIOS) and the West Pacific‐Indonesia population (WPI). We first quantified realized niche to reveal significant differences in ecological niche space among different populations. Subsequently, SDMs were constructed at both species and population levels, demonstrating that population‐level SDMs provide more reliable predictions of population distributions due to differential responses to climatic predictor variables. Finally, we conducted an assessment to identify conservation gaps for T. maxima beyond the existing MPAs and proposed recommendations for future establishment of MPAs within the current framework. Based on these findings, appropriate conservation policies have been proposed to effectively protect the habitat of different geographical populations of T. maxima. Additionally, spatiotemporal predictions of habitat suitability provide crucial information for developing adaptive management strategies for T. maxima in response to climate change, including designing new protected areas and adjusting the location and extent of existing protected areas based on their geographical distribution.

Abstract The deep sea harbours microorganisms with unique life characteristics and activities due to adaptation to particular environmental conditions, but the limited sample collection and pure culture techniques available constrain the study of deep-sea microorganisms. In this study, strain Ant34-E75 was isolated from Antarctic deep-sea sediment samples and showed the highest 16 S rRNA gene sequence similarity (97.18%) with the strain Aequorivita viscosa 8-1bT. Strain Ant34-E75 is psychrotrophic and can effectively increase the cold tolerance of Chlamydomonas reinhardtii (a model organism). Subsequent transcriptome analysis revealed multiple mechanisms involved in the Ant34-E75 response to temperature stress, and weighted gene co-expression network analysis (WGCNA) showed that the peptidoglycan synthesis pathway was the key component. Overall, this study provides insights into the characteristics of a deep-sea microorganism and elucidates mechanisms of temperature adaptation at the molecular level.

Abstract Lithium–sulfur (Li–S) batteries have been regarded as promising next‐generation energy‐storage devices owing to their inherently high theoretical energy density. Unfortunately, the poor capacity and cycling life caused by severe polysulfide shuttle effect and sluggish redox kinetics in sulfur cathodes greatly impede the practical application of Li–S batteries. Herein, a new class of nanonetwork‐structured carbon decorated with oxygen‐vacancy‐containing cerium oxide nanoparticles (NSC–CeO2−x), in which carbon skeleton is composed of highly conductive carbon nanotube core welded by hybrid carbon shell, has been developed via one‐step heating treatment of hybrid molecular brush and further employed as functional interlayer to modify separator of Li–S battery. Owing to the synergistic effect of the highly active CeO2−x nanoparticles and the three‐dimensional carbon nanonetwork in enhancing the preservation of the soluble polysulfides and boosting the redox kinetics of sulfur species, the NSC–CeO2−x significantly promotes the electrochemical performance of sulfur cathode. As a result, the as‐constructed Li–S batteries exhibit an ultrahigh initial sulfur utilization of 92.9% and an extremely large capacity of 751 mA h g−1 at a high rate of 5 C. Remarkably, a stable capacity of 728 mA h g−1 over 300 cycles at 1 C is also achieved.

This article studies internal control of the sixth order Boussinesq equation utt uxx+ βuxxxx uxxxxxx +(u²)xx = f posed on a periodic domain T with the internal control input f(·, t) acting on an arbitrarily small open subset of the domain T. It is shown that the system is locally exactly controllable and exponentially stabilizable in the classic Sobolev space Hs+3(T)Ã--Hs(T) for any s ≥ 0. [ABSTRACT FROM AUTHOR]

Abstract Background Bacteria are an essential component of the earth`s biota and affect circulation of matters through their metabolic activity. They also play an important role in the carbon and nitrogen cycle in the deep-sea environment. In this paper, two strains from deep-sea sediments were investigated in order to understand nitrogen cycling involved in the deep-sea environment. Results In this paper, the basic genomic information of two strains was obtained by whole genome sequencing. The Cobetia amphilecti N-80 and Halomonas profundus 13 genome sizes are 4,160,095 bp with a GC content of 62.5% and 5,251,450 bp with a GC content of 54.84%. Through a comparison of functional analyses, we predicted the possible C and N metabolic pathways of the two strains and determined that Halomonas profundus 13 could use more carbon sources than Cobetia amphilecti N-80. The main genes associated with N metabolism in Halomonas profundus 13 are narG, narY, narI, nirS, norB, norC, nosZ, and nirD. On the contrast, nirD, using NH4 + for energy, plays a main role in Cobetia amphilecti N-80. Both of them have the same genes for fixing inorganic carbon: icd, ppc, fdhA, accC, accB, accD, and accA. Conclusion In this study, the whole genomes of two strains were sequenced to clarify the basic characteristics of their genomes, laying the foundation for further studying nitrogen-metabolizing bacteria. Halomonas profundus 13 can utilize more carbon sources than Cobetia amphilecti N-80, as indicated by API as well as COG and KEGG prediction results. Finally, through the analysis of the nitrification and denitrification abilities as well as the inorganic carbon fixation ability of the two strains, the related genes were identified, and the possible metabolic pathways were predicted. Together, these results provide molecular markers and theoretical support for the mechanisms of inorganic carbon fixation by deep-sea microorganisms.

Lithium–sulfur batteries (LSBs) are considered a promising candidate for next-generation energy storage devices due to the advantages of high theoretical specific capacity, abundant resources and being environmentally friendly. However, the severe shuttle effect of polysulfides causes the low utilization of active substances and rapid capacity fading, thus seriously limiting their practical application. The introduction of conductive polymer-based interlayers between cathodes and separators is considered to be an effective method to solve this problem because they can largely confine, anchor and convert the soluble polysulfides. In this review, the recent progress of conductive polymer-based interlayers used in LSBs is summarized, including free-standing conductive polymer-based interlayers, conductive polymer-based interlayer modified separators and conductive polymer-based interlayer modified sulfur electrodes. Furthermore, some suggestions on rational design and preparation of conductive polymer-based interlayers are put forward to highlight the future development of LSBs.

The Bohai Sea is a semi-enclosed shallow water that is influenced by both natural and anthropogenic stressors. However, the microeukaryotic communities and environmental factors that affect them in different regions remain largely unclear. We investigated microeukaryotic communities in surface sediments from five geographic regions using high-throughput sequencing of the 18S rDNA gene. The Miaodao Archipelago, Yellow River Estuary, and Central Bohai Sea had the highest Shannon and Simpson indices of the eukaryotic communities, while the Yellow River Estuary exhibited the highest Chao1 index. The microeukaryotic communities in surface sediments were mainly composed of Dinoflagellata, Bacillariophyta, Ciliophora, Cercozoa, and Protalveolata. Thalassiosira has a relatively high abundance at the Liaodong Bay and Central Bohai Sea, possessing the proportion of 41.70% and 38.10%, respectively, while Gonyaulax was the most abundant taxa in the Bohai Bay, occupying a proportion of 57.77%. Moreover, a negative correlation between diatoms and dinoflagellates was observed. Phosphorus, nitrogen, salinity, temperature, and silicate were major environmental determinants of microeukaryotic composition. Microeukaryotic communities in the surface sediments, especially for the composition and ratio of diatoms to dinoflagellates, reflected the environmental quality of marine ecosystems. Overall, these microeukaryotic community compositions provide a reliable indicator for monitoring the level of marine eutrophication in the Bohai Sea.

Cadmium (Cd) pollution has become a global issue due to industrial and agricultural developments. However, the molecular mechanism of Cd-induced detrimental effects and relevant signal transduction/metabolic networks are largely unknown in marine fishes. Here, greenfin horse-faced filefish (Thamnaconus septentrionalis) were exposed to 5.0 mg/L Cd up to 7 days. We applied both biochemical methods and multi-omics techniques to investigate how the gills respond to Cd exposure. Our findings revealed that Cd exposure caused the formation of reactive oxygen species (ROS), which in turn activated the MAPK and apoptotic pathways to alleviate oxidative stress and cell damage. Glycolysis, protein degradation, as well as fatty acid metabolism might assist to meet the requirements of nutrition and energy under Cd stress. We also found that long-term (7 days, “long-term” means compared to 12 and 48 h) Cd exposure caused the accumulation of succinate, which would in turn trigger an inflammatory response and start an immunological process. Moreover, ferroptosis might induce inflammation. Overall, Cd exposure caused oxidative stress, energy metabolism disturbance, and immune response in greenfin horse-faced filefish. Our conclusions can be used as references for safety risk assessment of Cd to marine economic fishes.

The sense of one's own body is a pillar of self-consciousness and could be investigated by inducing human illusions of artificial objects as part of the self. Here, we present a nonhuman primate version of a rubber-hand illusion that allowed us to determine its computational and neuronal mechanisms. We implemented a video-based system in a reaching task in monkeys and combined a casual inference model to establish an objective and quantitative signature for the monkey's body representation. Similar to humans, monkeys were more likely to perceive an external object as part of the self when the dynamics (spatial disparity) and the features (shape and structure) of visual (V) input was closer to proprioceptive (P) signals. Neural signals in the monkey's premotor cortex reflected the strength of illusion and the likelihood of misattributing the illusory hand to oneself, thus, revealing a cortical representation of body ownership. [ABSTRACT FROM AUTHOR]

Cepola schlegelii (Bleeker 1854) belongs to the genus Cepola in the family Cepolidae and order Priacanthiformes. The complete mitochondrial genome of C. schlegelii was sequenced and analyzed by a high-throughput sequencing approach. The full length of the genome is 17,020 bp, including 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs), and a non-coding control region (D-loop). Phylogenetic analysis based on complete mitochondrial genomes revealed that C. schlegelii was most closely related to Acanthocepola krusensternii. The complete mitochondrial sequence of C. schlegelii will enrich the mitochondrial genome database and provide useful resources for population genetics and evolution analyses.

Local adaptation has been increasingly involved in the designation of species conservation strategies to response to climate change. Marine mammals, as apex predators, are climatechange sensitive, and their spatial distribution and conservation requirements are critically significant for designing protection strategies. In this study, we focused on an ice-breeding marine mammal, the spotted seal (Phoca largha), which exhibits distinct morphological and genetic variations across its range. Our objectives were to quantify the ecological niches of three spotted seal populations, construct the species-level model and population-level models that represent different regions in the Bering population (BDPS), Okhotsk population (ODPS) and southern population (SDPS), and conduct a conservation gap analysis. Our findings unequivocally demonstrated a clear niche divergence among the three populations. We predicted habitat contraction for the BDPS and ODPS driven by climate change; in particular, the spotted seals inhabiting Liaodong Bay may face breeding habitat loss. However, most spotted seal habitats are not represented in existing marine protected areas. Drawing upon these outcomes, we propose appropriate conservation policies to effectively protect the habitat of the different geographical populations of spotted seals. Our research addresses the importance of incorporating local adaptation into species distribution modeling to inform conservation and management strategies.

The integration of Global Navigation Satellite System (GNSS) Real-Time Kinematics (RTK) can provide high-precision, real-time, and global coverage of location information in open areas. But in arboretum environment, the ability to achieve continuous high-precision positioning using global positioning technology is limited due to various sources of interference, such as multi-path effects, signal obstruction, and environmental noise. In order to achieve precise navigation in challenging GNSS signal environments, visual SLAM systems are widely used due to their ability to adapt to different environmental features. Therefore, this paper proposes an optimized solution that integrates the measurements from GNSS-RTK and stereo cameras. The presented approach aligns the coordinates between the two sensors, and then employs an adaptive sliding window approach, which dynamically adjusts the window size and optimizes the pose within the sliding window. At the same time, to address the variations and uncertainties of GNSS signals in non-ideal environments, this paper proposes a solution that utilizes a Gaussian Mixture Model (GMM) to model the potential noise in GNSS signals. Furthermore, it employs a Variational Bayesian Inference-based (VBI) method to estimate the parameters of the GMM model online. The integration of this model with an optimization-based approach enhances the positioning accuracy and robustness even further. The evaluation results of real vehicle tests show that in challenging GNSS arboretum environments, GMM applied to GNSS/VO integration has higher accuracy and better robustness.

Antarctica is the coldest, driest, and most windy continent on earth. The major terrestrial vegetation consists of cryptogams (mosses and lichens) and two vascular plant species. However, the molecular mechanism of cold tolerance and relevant regulatory networks were largely unknown in these Antarctic plants. Here, we investigated the global alterations in metabolites and regulatory pathways of an Antarctic moss (Pohlia nutans) under cold stress using an integrated multi-omics approach. We found that proline content and several antioxidant enzyme activities were significantly increased in P. nutans under cold stress, but the contents of chlorophyll and total flavonoids were markedly decreased. A total of 559 metabolites were detected using ultra high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). We observed 39 and 71 differentially changed metabolites (DCMs) after 24 h and 60 h cold stress, indicating that several major pathways were differentially activated for producing fatty acids, alkaloids, flavonoids, terpenoids, and phenolic acids. In addition, the quantitative transcriptome sequencing was conducted to uncover the global transcriptional profiles of P. nutans under cold stress. The representative differentially expressed genes (DEGs) were identified and summarized to the function including Ca2+ signaling, ABA signaling, jasmonate signaling, fatty acids biosynthesis, flavonoid biosynthesis, and other biological processes. The integrated dataset analyses of metabolome and transcriptome revealed that jasmonate signaling, auxin signaling, very-long-chain fatty acids and flavonoid biosynthesis pathways might contribute to P. nutans acclimating to cold stress. Overall, these observations provide insight into Antarctic moss adaptations to polar habitats and the impact of global climate change on Antarctic plants.

Most regions of the Antarctic continent are experiencing increased dryness due to global climate change. Mosses and lichens are the dominant vegetation of the ice-free areas of Antarctica. However, the molecular mechanisms of these Antarctic plants adapting to drought stress are less documented. Here, transcriptome and metabolome analyses were employed to reveal the responses of an Antarctic moss (Pohlia nutans subsp. LIU) to drought stress. We found that drought stress made the gametophytes turn yellow and curled, and enhanced the contents of malondialdehyde and proline, and the activities of antioxidant enzymes. Totally, 2,451 differentially expressed genes (DEGs) were uncovered under drought treatment. The representative DEGs are mainly involved in ROS-scavenging and detoxification, flavonoid metabolism pathway, plant hormone signaling pathway, lipids metabolism pathway, transcription factors and signal-related genes. Meanwhile, a total of 354 differentially changed metabolites (DCMs) were detected in the metabolome analysis. Flavonoids and lipids were the most abundant metabolites and they accounted for 41.53% of the significantly changed metabolites. In addition, integrated transcriptome and metabolome analyses revealed co-expression patterns of flavonoid and long-chain fatty acid biosynthesis genes and their metabolites. Finally, qPCR analysis demonstrated that the expression levels of stress-related genes were significantly increased. These genes included those involved in ABA signaling pathway (NCED3, PP2C, PYL, and SnAK2), jasmonate signaling pathway (AOC, AOS, JAZ, and OPR), flavonoid pathway (CHS, F3’,5’H, F3H, FLS, FNS, and UFGT), antioxidant and detoxifying functions (POD, GSH-Px, Prx and DTX), and transcription factors (ERF and DREB). In summary, we speculated that P. nutans were highly dependent on ABA and jasmonate signaling pathways, ROS scavenging, flavonoids and fatty acid metabolism in response to drought stress. These findings present an important knowledge for assessing the impact of coastal climate change on Antarctic basal plants.

Flavonoids, the largest group of polyphenolic secondary metabolites present in all land plants, play essential roles in many biological processes and defense against abiotic stresses. In the flavonoid biosynthesis pathway, flavones synthase I (FNSI), flavanone 3-hydroxylase (F3H), flavonol synthase (FLS), and anthocyanidin synthase (ANS) all belong to 2-oxoglutarate/Fe(II)-dependent dioxygenases (2-ODDs) family, which catalyzes the critical oxidative reactions to form different flavonoid subgroups. Here, a novel 2-ODD gene was cloned from Antarctic moss Pohlia nutans (Pn2-ODD1) and its functions were investigated both in two model plants, Physcomitrella patens and Arabidopsis thaliana. Heterologous expression of Pn2-ODD1 increased the accumulation of anthocyanins and flavonol in Arabidopsis. Meanwhile, the transgenic P. patens and Arabidopsis with expressing Pn2-ODD1 exhibited enhanced tolerance to salinity and drought stresses, with larger gametophyte sizes, better seed germination, and longer root growth. Heterologous expression of Pn2-ODD1 in Arabidopsis also conferred the tolerance to UV-B radiation and oxidative stress by increasing antioxidant capacity. Therefore, we showed that Pn2-ODD1 participated in the accumulation of anthocyanins and flavonol in transgenic plants, and regulated the tolerance to abiotic stresses in plants, contributing to the adaptation of P. nutans to the polar environment.

This paper presents a focused investigation into real-time segmentation in unstructured environments, a crucial aspect for enabling autonomous navigation in off-road robots. To address this challenge, an improved variant of the DDRNet23-slim model is proposed, which includes a lightweight network architecture and reclassifies ten different categories, including drivable roads, trees, high vegetation, obstacles, and buildings, based on the RUGD dataset. The model’s design includes the integration of the semantic-aware normalization and semantic-aware whitening (SAN–SAW) module into the main network to improve generalization ability beyond the visible domain. The model’s segmentation accuracy is improved through the fusion of channel attention and spatial attention mechanisms in the low-resolution branch to enhance its ability to capture fine details in complex scenes. Additionally, to tackle the issue of category imbalance in unstructured scene datasets, a rare class sampling strategy (RCS) is employed to mitigate the negative impact of low segmentation accuracy for rare classes on the overall performance of the model. Experimental results demonstrate that the improved model achieves a significant 14% increase mIoU in the invisible domain, indicating its strong generalization ability. With a parameter count of only 5.79M, the model achieves mAcc of 85.21% and mIoU of 77.75%. The model has been successfully deployed on a a Jetson Xavier NX ROS robot and tested in both real and simulated orchard environments. Speed optimization using TensorRT increased the segmentation speed to 30.17 FPS. The proposed model strikes a desirable balance between inference speed and accuracy and has good domain migration ability, making it applicable in various domains such as forestry rescue and intelligent agricultural orchard harvesting.

This paper presents a method for dynamically maintaining a regional elevation datum using CORS stations as core nodes. By utilizing CORS station data and surface mass loading data (including land water storage, sea level, and atmospheric pressure), the normal height changes of each station can be determined and dynamically maintained. The validity of this method is verified using multiple leveling survey results from five CORS stations in Beijing’s subsidence area between January 2012 and June 2021. Results show that it is necessary to derive and correct the height anomaly variation of CORS stations caused by surface mass loading using the remove-calculate-restore method and the Green’s function integration method, with the influence of surface mass changes reaching a subcentimeter level. CORS stations exhibiting great observation quality achieve a mean accuracy of 2.7 mm in determining normal height changes. Such accuracy surpasses the requirements of second-class leveling surveys covering route lengths exceeding 1.35 km, as well as conforming/closed loop routes with distances greater than 0.46 km. By strategically selecting CORS stations with long-term continuous observations and high-quality data as core nodes within the elevation control network, dynamic maintenance of the regional elevation datum can be achieved based on CORS station data.

The Antarctic continent has extreme natural environment and fragile ecosystem. Mosses are one of the dominant floras in the Antarctic continent. However, their genomic features and adaptation processes to extreme environments remain poorly understood. Here, we assembled the high-quality genome sequence of the Antarctic moss (Pohlia nutans) with 698.20 Mb and 22 chromosomes. We found that the high proportion of repeat sequences and a recent whole-genome duplication (WGD) contribute to the large size genome of P. nutans when compared to other bryophytes. The genome of P. nutans harbors the signatures of massive segmental gene duplications and large expansions of gene families, likely facilitating neofunctionalization. Genomic characteristics that may support the Antarctic lifestyle of this moss comprise expanded gene families involved in phenylpropanoid biosynthesis, unsaturated fatty acid biosynthesis, and plant hormone signal transduction. Additional contributions include the significant expansion and upregulation of several genes encoding DNA photolyase, antioxidant enzymes, flavonoid biosynthesis enzymes, possibly reflecting diverse adaptive strategies. Notably, integrated multi-omic analyses elucidate flavonoid biosynthesis may function as the reactive oxygen species detoxification under UV-B radiation. Our studies provide insight into the unique features of the Antarctic moss genome and their molecular responses to extreme terrestrial environments.