Palladium-Catalyzed Annulative π-Extension of Bay-Iodinated Triphenylenes to Access Polycyclic Aromatic Compounds.

A palladium-catalyzed annulative π-extension reaction of bay-iodinated triphenylenes with aryl iodides/o-chloroaromatic carboxylic acids was developed. This approach enabled the synthesis of diverse polycyclic aromatic compounds, including dibenzo[fg,op]tetracenes, azadibenzo[fg,op]tetracenes, and tribenzo[a,g,m]coronenes. Initial studies indicate that the resulting product, 2,3,8,9,14,15-hexakis(decyloxy)tribenzo[a,g,m]coronene, exhibits good liquid-crystalline properties.

OsACA9, an Autoinhibited Ca2+-ATPase, Synergically Regulates Disease Resistance and Leaf Senescence in Rice.

Calcium (Ca2+) is a versatile intracellular second messenger that regulates several signaling pathways involved in growth, development, stress tolerance, and immune response in plants. Autoinhibited Ca2+-ATPases (ACAs) play an important role in the regulation of cellular Ca2+ homeostasis. Here, we systematically analyzed the putative OsACA family members in rice, and according to the phylogenetic tree of OsACAs, OsACA9 was clustered into a separated branch in which its homologous gene in Arabidopsis thaliana was reported to be involved in defense response. When the OsACA9 gene was knocked out by CRISPR/Cas9, significant accumulation of reactive oxygen species (ROS) was detected in the mutant lines. Meanwhile, the OsACA9 knock out lines showed enhanced disease resistance to both rice bacterial blight (BB) and bacterial leaf streak (BLS). In addition, compared to the wild-type (WT), the mutant lines displayed an early leaf senescence phenotype, and the agronomy traits of their plant height, panicle length, and grain yield were significantly decreased. Transcriptome analysis by RNA-Seq showed that the differentially expressed genes (DEGs) between WT and the Osaca9 mutant were mainly enriched in basal immune pathways and antibacterial metabolite synthesis pathways. Among them, multiple genes related to rice disease resistance, receptor-like cytoplasmic kinases (RLCKs) and cell wall-associated kinases (WAKs) genes were upregulated. Our results suggest that the Ca2+-ATPase OsACA9 may trigger oxidative burst in response to various pathogens and synergically regulate disease resistance and leaf senescence in rice.

The Resistance of Soybean Variety Heinong 84 to Apple Latent Spherical Virus Is Controlled by Two Genetic Loci.

Apple latent spherical virus (ALSV) is widely used as a virus-induced gene silencing (VIGS) vector for function genome study. However, the application of ALSV to soybeans is limited by the resistance of many varieties. In this study, the genetic locus linked to the resistance of a resistant soybean variety Heinong 84 was mapped by high-throughput sequencing-based bulk segregation analysis (HTS-BSA) using a hybrid population crossed from Heinong 84 and a susceptible variety, Zhonghuang 13. The results showed that the resistance of Heinong 84 to ALSV is controlled by two genetic loci located on chromosomes 2 and 11, respectively. Cleaved amplified polymorphic sequence (CAPS) markers were developed for identification and genotyping. Inheritance and biochemical analyses suggest that the resistance locus on chromosome 2 plays a dominant dose-dependent role, while the other locus contributes a secondary role in resisting ALSV. The resistance locus on chromosome 2 might encode a protein that can directly inhibit viral proliferation, while the secondary resistance locus on chromosome 11 may encode a host factor required for viral proliferation. Together, these data reveal novel insights on the resistance mechanism of Heinong 84 to ALSV, which will benefit the application of ALSV as a VIGS vector.

Anticipating the transmissibility of the 2022 mpox outbreak.

An ongoing outbreak of monkeypox virus (MPXV) was first reported in the United Kingdom on 6 May 2022. As of 17 November, there had been a total of 80 221 confirmed MPXV cases in over 110 countries. Based on data reported between 6 May and 30 June 2022 in the United Kingdom, Spain, and Germany, we applied a deep learning approach using convolutional neural networks to evaluate the parameters of the 2022 MPXV outbreak. The basic reproduction number (R0 ) of MPXV was estimated to be 2.32 in the United Kingdom, which indicates the active diffusion of MPXV since the beginning of the outbreak. The data from Spain and Germany produced higher median R0 values of 2.42 and 2.88, respectively. Importantly, the estimated R0 of MPXV in the three countries tends to the previously calculated R0 of smallpox (3.50 to 6.00). Furthermore, the incubation (1/ε) and infectious (1/γ) period was predicted between 9 and 10 days and 4-5 days, respectively. The R0 value derived from MPXV is consistent with the significantly increasing number of cases, indicating the risk of a rapid spread of MPXV worldwide, which would provide important insights for the prevention and control of MPXV epidemic.

ldi-miR396-LdPMaT1 enhances reactive oxygen species scavenging capacity and promotes drought tolerance in Lilium distichum Nakai autotetraploids.

Drought is a key environmental stress that inhibits plant growth, development, yield and quality. Whole-genome replication is an effective method for breeding drought resistant cultivars. Here, we evaluated the tolerance of Lilium distichum Nakai diploids (2n = 2× = 24) and artificially induced autotetraploids (2n = 4× = 48) to drought simulated by polyethylene glycol (PEG) stress. Autotetraploids showed stronger drought tolerance than diploids, and high-throughput sequencing during PEG stress identified five differentially expressed miRNAs. Transcriptome analysis revealed significantly different reactive oxygen species (ROS)-scavenger expression levels between diploids and autotetraploids, which increased the drought tolerance of autotetraploids. Specifically, we identified ldi-miR396b and its only target gene (LdPMaT1) for further study based on its expression level and ROS-scavenging ability in response to drought stress (DS). Autotetraploids showed higher expression of LdPMaT1 and significantly downregulated expression of ldi-miR396b under DS compared with diploids. Through a short tandem target mimic (STTM) in transgenic lilies, functional studies revealed that miR396b silencing promotes LdPMaT1 expression and the DS response. Under PEG stress, STTM393 transgenic lines showed improved drought resistance mediated by lowered MDA content but exhibited high antioxidant enzyme activity, consistent with the autotetraploid results. Collectively, these findings suggest that ldi-miR396b-LdPMaT1 potentially enhances ROS-scavenging ability, which contributes to improved stress adaptation in autotetraploid lilies.

KCMF1-like suppresses white spot syndrome virus infection by promoting apoptosis in mud crab (Scylla paramamosain).

Potassium channel modulatory factor 1 (KCMF1), an E3 ubiquitin ligase, plays a vital role in renal tubulogenesis, preeclampsia, and tumor development in mammals. Nevertheless, the function of KCMF1 in invertebrates remains to be investigated. Here, we identified KCMF1-like from Scylla paramamosian, encoding 242 amino acids with two zinc finger domains at the N-terminal. Real-time quantitative PCR analysis revealed that KCMF1-like was expressed in all tested tissues, including hemocytes, brain, mid-intestine, subcuticular epidermis, gills, muscle, heart, and stomach, with higher levels in muscle and mid-intestine. KCMF1-like was up-regulated in the hemocytes of mud crabs challenged with white spot syndrome virus (WSSV). RNA interference (RNAi) was performed to investigate the impact of KCMF1-like on the proliferation of WSSV in mud crabs. Knock-down of KCMF1-like resulted in an increase of the WSSV copy number and an impairment of the hemocytes apoptosis rate in vivo. In addition, KCMF1-like could also affect the mitochondrial membrane potential. Collectively, these results revealed that KCMF1-like might play a crucial role in the defense against virus infection in mud crab. This study contributes a novel insight into the role of KCMF1-like in the antiviral immune defense mechanism in crustaceans.

An AQI decomposition ensemble model based on SSA-LSTM using improved AMSSA-VMD decomposition reconstruction technique.

Air quality index (AQI) is a key index for monitoring air pollution and can be used as guide for ensuring good public health. Accurate AQI prediction allows timely control and management of air pollution. In this study, a new integrated learning model was constructed to predict AQI. A smart reverse learning approach based on AMSSA was utilized to increase the diversity of populations, and an improved AMSSA (IAMSSA) was established. The optimum parameters with penalty factor α and mode number K of VMD were obtained using IAMSSA. The IAMSSA-VMD was used to decompose nonlinear and non-stationary AQI information series into several regular and smooth sub-sequences. The Sparrow Search Algorithm (SSA) was used to determine the optimum LSTM parameters. The results showed that: (1) IAMSSA exhibits faster convergence and higher accuracy and stability using simulation experiments compared with seven conventional optimization algorithms in 12 test functions. (2) IAMSSA-VMD was used to decompose the original air quality data results in multiple uncoupled intrinsic mode function (IMF) components and one residual (RES). An SSA-LSTM model was built for each IMF and one RES component, which effectively extracted the predicted values. (3) LSTM, SSA-LSTM, VMD-LSTM, VMD-SSA-LSTM, AMSSA-VMD-SSA-LSTM, and IAMSSA-VMD-SSA-LSTM models were used for prediction of AQI based on data from three cities (Chengdu, Guangzhou, and Shenyang). IAMSSA-VMD-SSA-LSTM exhibited the optimal prediction performance with MAE, RMSE, MAPE, and R2 of 3.692, 4.909, 6.241, and 0.981, respectively. (4) Generalization outcomes revealed that the IAMSSA-VMD-SSA-LSTM model had optimal generalization ability. In summary, the decomposition ensemble model proposed in this study has higher prediction accuracy, improved fitting effect and generalization ability compared with other models. These properties indicate the superiority of the decomposition ensemble model and provides a theoretical and technical basis for prediction of air pollution and ecosystem restoration.

ADAR1p110 promotes Enterovirus D68 replication through its deaminase domain and inhibition of PKR pathway.

BACKGROUND: Severe respiratory and neurological diseases caused by human enterovirus D68 (EV-D68) pose a serious threat to public health, and there are currently no effective drugs and vaccines. Adenosine deaminase acting on RNA1 (ADAR1) has diverse biological functions in various viral infections, but its role in EV-D68 infections remains undetermined. METHODS: Rhabdomyosarcoma (RD) and human embryonic kidney 293 T (293 T) cells, and HeLa cells were used to evaluate the expression level of ADAR1 upon EV-D68 (Fermon strain) and human parainfluenza virus type 3 (HPIV3; NIH47885) infection, respectively. Knockdown through silencing RNA (siRNA) and overexpression of either ADAR1p110 or ADAR1p150 in cells were used to determine the function of the two proteins after viral infection. ADAR1p110 double-stranded RNA binding domains (dsRBDs) deletion mutation was generated using a seamless clone kit. The expression of ADAR1, EV-D68 VP1, and HPIV3 hemagglutinin-neuraminidase (HN) proteins was identified using western blotting. The median tissue culture infectious dose (TCID50) was applied to detect viral titers. The transcription level of EV-D68 mRNA was analyzed using reverse transcription-quantitative PCR (RT-qPCR) and the viral 5'-untranslated region (5'-UTR)-mediated translation was analyzed using a dual luciferase reporter system. CONCLUSION: We found that the transcription and expression of ADAR1 was inhibited upon EV-D68 infection. RNA interference of endogenous ADAR1 decreased VP1 protein expression and viral titers, while overexpression of ADAR1p110, but not ADAR1p150, facilitated viral replication. Immunofluorescence assays showed that ADAR1p110 migrated from the nucleus to the cytoplasm after EV-D68 infection. Further, ADAR1p110 lost its pro-viral ability after mutations of the active sites in the deaminase domain, and 5'-UTR sequencing of the viral genome revealed that ADAR1p110 likely plays a role in EV-D68 RNA editing. In addition, after ADAR1 knockdown, the levels of both phosphorylated double-stranded RNA dependent protein kinase (p-PKR) and phosphorylated eukaryotic initiation factor 2α (p-eIF2α) increased. Attenuated translation activity of the viral genome 5'-UTR was also observed in the dual-luciferase reporter assay. Lastly, the deletion of ADAR1p110 dsRBDs increased the level of p-PKR, which correlated with a decreased VP1 expression, indicating that the promotion of EV-D68 replication by ADAR1p110 is also related to the inhibition of PKR activation by its dsRBDs. Our study illustrates that ADAR1p110 is a novel pro-viral factor of EV-D68 replication and provides a theoretical basis for EV-D68 antiviral research.

Palladium-catalyzed annulative π-extension of o-halobiphenyls with o-chloropyridinecarboxylic acids to access azatriphenylenes.

A palladium-catalyzed bay-region annulative π-extension reaction of o-halobiphenyls with o-chloropyridinecarboxylic acids was developed. The reaction was carried out with a 1 : 1 ratio of substrates. A variety of azatriphenylene derivatives could be synthesized by this approach. This transformation could be applied to the synthesis of ionic liquid-crystalline molecules.

DetectFormer: Category-Assisted Transformer for Traffic Scene Object Detection.

Object detection plays a vital role in autonomous driving systems, and the accurate detection of surrounding objects can ensure the safe driving of vehicles. This paper proposes a category-assisted transformer object detector called DetectFormer for autonomous driving. The proposed object detector can achieve better accuracy compared with the baseline. Specifically, ClassDecoder is assisted by proposal categories and global information from the Global Extract Encoder (GEE) to improve the category sensitivity and detection performance. This fits the distribution of object categories in specific scene backgrounds and the connection between objects and the image context. Data augmentation is used to improve robustness and attention mechanism added in backbone network to extract channel-wise spatial features and direction information. The results obtained by benchmark experiment reveal that the proposed method can achieve higher real-time detection performance in traffic scenes compared with RetinaNet and FCOS. The proposed method achieved a detection performance of 97.6% and 91.4% in AP50 and AP75 on the BCTSDB dataset, respectively.

Transcriptomics and targeted metabolomics reveal the regulatory network of Lilium davidii var. unicolor during bulb dormancy release.

MAIN CONCLUSION: Through combined analysis of the transcriptome and targeted metabolome of lily bulbs, the possible molecular mechanism of dormancy release was revealed. Regulation of bulb dormancy is critical for ensuring annual production and high-quality cultivation. The application of low temperatures is the most effective method for breaking bulb dormancy, but the molecular mechanism underlying this response is unclear. Herein, targeted metabolome and transcriptome analyses were performed on Lilium davidii var. unicolor bulbs stored for 0, 50, and 100 days at 4 °C. Dormancy release mainly depended on the accumulation of gibberellins GA4 and GA7, which are synthesized by the non-13-hydroxylation pathway, rather than GA3, and ABA was degraded in the process. The contents of nonbioactive GA9, GA15, and GA24, the precursors of GA4 synthesis, increased with bulb dormancy release. Altogether, 113,252 unique transcripts were de novo assembled through high-throughput transcriptome sequences, and 639 genes were continuously differentially expressed. Energy sources during carbohydrate metabolism mainly depend on glycolysis and the pentose phosphate pathway. Screening of transcription factor families involved in bulb dormancy release showed that MYB, WRKY, NAC, and TCP members were significantly correlated with the targeted metabolome. Coexpression analysis further confirmed that ABI5, PYL8, PYL4, and PP2C, which are vital ABA signaling elements, regulated GA3ox and GA20ox in the GA4 biosynthesis pathway, and XERICO may be involved in the regulation of ABA and GA4 signaling through the ubiquitination pathway. WRKY32, WRKY71, DAM14, NAC8, ICE1, bHLH93, and TCP15 also participated in the ABA/GA4 regulatory network, and ICE1 may be the key factor linking temperature signals and hormone metabolism. These results will help to reveal the bulb dormancy molecular mechanism and develop new strategies for high-quality bulb production.

Self-Erasing Network for Person Re-Identification.

Person re-identification (ReID) plays an important role in intelligent surveillance and receives widespread attention from academics and the industry. Due to extreme changes in viewing angles, some discriminative local regions are suppressed. In addition, the data with similar backgrounds collected by a fixed viewing angle camera will also affect the model's ability to distinguish a person. Therefore, we need to discover more fine-grained information to form the overall characteristics of each identity. The proposed self-erasing network structure composed of three branches benefits the extraction of global information, the suppression of background noise and the mining of local information. The two self-erasing strategies that we proposed encourage the network to focus on foreground information and strengthen the model's ability to encode weak features so as to form more effective and richer visual cues of a person. Extensive experiments show that the proposed method is competitive with the advanced methods and achieves state-of-the-art performance on DukeMTMC-ReID and CUHK-03(D) datasets. Furthermore, it can be seen from the activation map that the proposed method is beneficial to spread the attention to the whole body. Both metrics and the activation map validate the effectiveness of our proposed method.

Improved Point-Line Feature Based Visual SLAM Method for Complex Environments.

Traditional visual simultaneous localization and mapping (SLAM) systems rely on point features to estimate camera trajectories. However, feature-based systems are usually not robust in complex environments such as weak textures or obvious brightness changes. To solve this problem, we used more environmental structure information by introducing line segments features and designed a monocular visual SLAM system. This system combines points and line segments to effectively make up for the shortcomings of traditional positioning based only on point features. First, ORB algorithm based on local adaptive threshold was proposed. Subsequently, we not only optimized the extracted line features, but also added a screening step before the traditional descriptor matching to combine the point features matching results with the line features matching. Finally, the weighting idea was introduced. When constructing the optimized cost function, we allocated weights reasonably according to the richness and dispersion of features. Our evaluation on publicly available datasets demonstrated that the improved point-line feature method is competitive with the state-of-the-art methods. In addition, the trajectory graph significantly reduced drift and loss, which proves that our system increases the robustness of SLAM.

Ultrahighly Efficient and Stable Fluorescent Gold Nanoclusters Coated with Screened Peptides of Unique Sequences for Effective Protein and Serum Discrimination.

Gold nanoclusters (Au NCs) coated with various peptides have been widely used as fluorescent probes, and nowadays the most commonly used are cysteine (C) and tyrosine (Y) based ones. Herein, we report the preparation and clinical application of highly efficient and stable fluorescent Au NCs protected by screened peptides with a specific amino acid sequence Cys-Met-Met-Met-Met-Met (CMMMMM). Compared with traditional C, Y based peptide (CYYYYY) protected Au NCs, the fluorescence intensity of the CMMMMM-Au NCs increased by 230%, and the photobleaching resistance or stability of the CMMMMM-Au NCs increased by about 300% (after continuous ultraviolet irradiation for 60 min, the fluorescence of the CMMMMM-Au NCs remained more than 90% of their initial intensity, while the CYYYYY-Au NCs remained less than 30%). Assaying arrays based on CMMMMM protected Au NCs with different positive or negative charges as sensing receptors were developed through regulating different pH values, and multivariate analysis on the patterns obtained by these arrays allowed effective identification of not only ten proteins separately but also complex protein mixtures with subtly diverse compositions. The docking simulation and isothermal titration confirmed that target proteins interacted with CMMMMM-Au NCs mainly through electrostatic interactions and partly hydrophobic interactions, which affected the binding energy and fluorescence lifetime of CMMMMM-Au NCs, resulting in the unique fingerprint-like recognition patterns. Furthermore, serums from breast cancer, severe osteoarthritis, and rectal cancer patients can be effectively identified with healthy people using this CMMMMM-Au NCs based sensor array.

Aquaporin1 regulates development, secondary metabolism and stress responses in Fusarium graminearum.

The Ascomycete fungus Fusarium graminearum, the causal agent of Fusarium head blight of wheat and barley, has become a predominant model organism for the study of fungal phytopathogens. Aquaporins (AQPs) have been implicated in the transport of water, glycerol, and a variety of other small molecules in yeast, plants and animals. However, the role of these proteins in phytopathogenic fungi is not well understood. Here, we identified and attempted to elucidate the function of the five aquaporin genes in F. graminearum. The phylogenetic analysis revealed that FgAQPs are divided into two clades, with FgAQP1 in the first clade. The ∆AQP1 mutant formed whitish colonies with longer aerial hyphae and reduced conidiation and perithecium formation. The ∆AQP1 mutant conidia were morphologically abnormal and appeared to undergo abnormal germination. The ∆AQP1 mutant and the wild type strain were equally pathogenic, while the mutant produced significantly higher quantities of deoxynivalenol (DON). The ∆AQP1 mutant also exhibited increased resistance to osmotic and oxidative stress as well as cell-wall perturbing agents. Using FgAQP1-GFP and DAPI staining, we found that FgAQP1 is localized to the nuclear membrane in conidia. Importantly, deletion of FgAQP1 increased the severity of conidium autophagy. Taken together, these results suggest that FgAQP1 is involved in hyphal development, stress responses, secondary metabolism, and sexual and asexual reproduction in F. graminearum. Unlike the ∆AQP1 mutant, the ∆AQP2, ∆AQP3, ∆AQP4 and ∆AQP5 mutants had no variable phenotypes.

Differential roles of three FgPLD genes in regulating development and pathogenicity in Fusarium graminearum.

Phospholipase D (PLD) is an important phospholipid hydrolase that plays critical roles in various biological processes in eukaryotic cells. However, little is known about its functions in plant pathogenic fungi. In this study, we identified three FgPLD genes in Fusarium graminearum that are homologous to the Saccharomyces cerevisiae Spo14 gene. We constructed deletion mutants of all three FgPLD genes using homologous recombination. Deletion of FgPLD1 (Δpld1), but not FgPLD2 or FgPLD3, affected hyphal growth, conidiation, and perithecium formation. The Δpld1 mutant showed reduced deoxynivalenol (DON) production and virulence in flowering wheat heads and corn silks. Furthermore, three FgPLD proteins have the same subcellular localization and localize to the cytoplasm in F. graminearum. Taken together, these results indicate that FgPLD1, but not FgPLD2 or FgPLD3, is important for hyphal growth, sexual or asexual reproduction, and plant infection.

Exploring Agrobacterium-mediated genetic transformation methods and its applications in Lilium.

As a typical bulb flower, lily is widely cultivated worldwide because of its high ornamental, medicinal and edible value. Although breeding efforts evolved over the last 10000 years, there are still many problems in the face of increasing consumer demand. The approach of biotechnological methods would help to solve this problem and incorporate traits impossible by conventional breeding. Target traits are dormancy, development, color, floral fragrance and resistances against various biotic and abiotic stresses, so as to improve the quality of bulbs and cut flowers in planting, cultivation, postharvest, plant protection and marketing. Genetic transformation technology is an important method for varietal improvement and has become the foundation and core of plant functional genomics research, greatly assisting various plant improvement programs. However, achieving stable and efficient genetic transformation of lily has been difficult worldwide. Many gene function verification studies depend on the use of model plants, which greatly limits the pace of directed breeding and germplasm improvement in lily. Although significant progress has been made in the development and optimization of genetic transformation systems, shortcomings remain. Agrobacterium-mediated genetic transformation has been widely used in lily. However, severe genotypic dependence is the main bottleneck limiting the genetic transformation of lily. This review will summarizes the research progress in the genetic transformation of lily over the past 30 years to generate the material including a section how genome engineering using stable genetic transformation system, and give an overview about recent and future applications of lily transformation. The information provided in this paper includes ideas for optimizing and improving the efficiency of existing genetic transformation methods and for innovation, provides technical support for mining and identifying regulatory genes for key traits, and lays a foundation for genetic improvement and innovative germplasm development in lily.

Analysis of Virus-Induced Double-Stranded RNA in Living Plant Cells by the dRBFC Assay.

Double-stranded RNA (dsRNA) is the replicate intermediate of all RNA viruses, and is also recognized by their host cells as a virus-invading molecule signal. Analysis of the localization and dynamic of virus-induced dsRNA can reveal crucial information concerning the molecular mechanism of virus replication and host responses to viral infection. In this chapter, we provide an easy and efficient protocol called dsRNA binding-dependent fluorescence complementation (dRBFC) assay for labeling the dsRNAs in living plant cells using two different plant RNA viruses, namely potato virus X and turnip mosaic virus. Moreover, both YFP- and mRFP-based dRBFC plasmids are available for the flexibility of experiment design.

Analysis of research trends (2014-2023) on oxidative stress and male fertility based on bibliometrics and knowledge graphs.

Background: Oxidative stress (OS) is considered one of the major factors affecting male fertility, and research in this field has seen constant growth year by year. Currently, around 700 relevant papers are published each year, with a trend of further growth. Therefore, this study systematically summarizes the literature published in the last decade from a bibliometric perspective, revealing the dynamic development of the field, identifying research hotspots, analyzing future trends, and providing reference for further research. Methods: Relevant literature on oxidative stress and male fertility was retrieved from the Web of Science Core Collection (WoSCC) database, covering the timespan from 2014 to 2023 and including two types, articles and reviews. CiteSpace and VOSviewer were used for bibliometric analysis, including cluster analysis, co-occurrence analysis, co-citation analysis, and burst analysis of countries/regions, institutions, journals, authors, references, and keywords. Results: This paper studied a total of 5,301 papers involving 107 countries/regions, with China having the highest number of publications (898 papers) and the United States having the highest centrality (0.62). Burst analysis of journal citations revealed the emergence of many new journals (e.g., Antioxidants-Basel, Front Endocrinol) after 2021, indicating continuous expansion and development in this field. Cluster analysis of co-cited references and co-occurring keywords divided the research into areas such as oxidative stress and male infertility, oxidative stress level detection, and antioxidants. The keywords associated with research hotspots shifted from oxidative stress detection, sperm DNA damage, apoptosis, and redox potential to DNA methylation, embryonic development, infection, polyunsaturated fatty acids, and antioxidants. Conclusion: Bibliometric methods provide an intuitive reflection of the development process in the field of oxidative stress and male fertility, as well as the analysis of research hotspots in different periods. Research on oxidative stress and embryonic development, as well as antioxidant health management, may become hotspots in future research.

Research on landslide susceptibility prediction model based on LSTM-RF-MDBN.

The occurrence of landslide disasters causes huge economic losses and casualties. Although many achievements have been made in predicting the probability of landslide disasters, various factors such as the scale and spatial location of landslide geological disasters should still be fully considered. Further research on how to quantitatively characterize the susceptibility of landslide geological disasters is necessarily important. To this end, taking the Wenchuan earthquake as the research area and extracting eight influencing factors, including terrain information entropy (Ht), lithology, distance from rivers, distance from faults, vegetation coverage (NDVI), distance from roads, peak ground motion acceleration (PGA), and annual rainfall, a landslide susceptibility prediction model was hereby established based on LSTM-RF-MDBN, a landslide susceptibility prediction map was drawn, and the spatial distribution characteristics of landslide disasters were analyzed. The results showed that (1) LSTM had good prediction results for the eight influencing factors, with an average prediction accuracy of 85%; (2) compared with models such as DNN and LR for predicting landslide disaster points, the AUC value of RF for predicting landslide point positions reached 0.88, presenting a higher accuracy compared to other models; (3) the AUC value of the landslide susceptibility prediction model based on LSTM-RF-MDBN reached 0.965, which had a high accuracy in predicting landslide susceptibility. Overall, the research results can provide a scientific basis for selecting the best strategy for landslide disaster warning, prevention, and mitigation.