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The widespread use of mobile internet and social media has driven the creation and development of the micro-marketing model. Micro-influencers utilize marketing techniques that have a small and highly targeted reach, which in turn affects the psychology and perception of the target population. In the process of micromarketing, a very important influencing factor is interpersonal relationships. Therefore, this paper takes interpersonal relationships as an entry point, analyzes several aspects of interpersonal relationships participation in micro-marketing, the current situation of interpersonal relationships among micro-influencers, and the influence of interpersonal relationships on marketing strategy, which is of great significance in exploring the influence of interpersonal relationships on micro-marketing from the perspective of social influence. The author analyzes some micro-marketing strategies on the Chinese social platform Red Booklet. The empirical study shows that the more interaction between micro-influencers and the target population, the stronger the influence on the target population; compared with unilateral promotion by celebrities, micro-influencers have a stronger influence on the target population.

Glutathione reductase (GR) plays a pivotal role in managing oxidative stress, a process crucial for microbial virulence and adaptation, yet it has not been extensively explored in bacteria such as Avibacterium paragallinarum ( Av. paragallinarum ). This study examined the specific roles of GR in Av. paragallinarum , focusing on how GR modulates the bacterium’s response to oxidative stress and impacts its pathogenic behavior. Using gene knockouts together with transcriptomic and metabolomic profiling, we identified an important shift in redox balance due to GR deficiency, which disrupted energy metabolism and weakened the oxidative stress defense, culminating in a notable decline in virulence. In addition, decreased growth rates, reduced biofilm production, and weakened macrophage interactions were observed in GR-deficient strains. Notably, our findings reveal a sophisticated adaptation mechanism wherein the bacterium recalibrated its metabolic pathways in response to GR deficiency without fully restoring virulence. Our in vivo studies further highlight the pivotal role of GR in pathogen fitness. Together, our findings connect GR-mediated redox control to bacterial virulence, thereby furthering the understanding of microbial adaptation and positioning GR as a potential antimicrobial target. Our insights into the GR-centric regulatory network pave the way for leveraging bacterial redox mechanisms in the development of novel antimicrobial therapies, highlighting the importance of oxidative stress management in bacterial pathogenicity.

Region proposal network (RPN) based object detection, such as Faster Regions with CNN (Faster R-CNN), has gained considerable attention due to its high accuracy and fast speed. However, it has room for improvements when used in special application situations, such as the on-board vehicle detection. Original RPN locates multiscale anchors uniformly on each pixel of the last feature map and classifies whether an anchor is part of the foreground or background with one pixel in the last feature map. The receptive field of each pixel in the last feature map is fixed in the original faster R-CNN and does not coincide with the anchor size. Hence, only a certain part can be seen for large vehicles and too much useless information is contained in the feature for small vehicles. This reduces detection accuracy. Furthermore, the perspective projection results in the vehicle bounding box size becoming related to the bounding box position, thereby reducing the effectiveness and accuracy of the uniform anchor generation method. This reduces both detection accuracy and computing speed. After the region proposal stage, many regions of interest (ROI) are generated. The ROI pooling layer projects an ROI to the last feature map and forms a new feature map with a fixed size for final classification and box regression. The number of feature map pixels in the projected region can also influence the detection performance but this is not accurately controlled in former works. In this paper, the original faster R-CNN is optimized, especially for the on-board vehicle detection. This paper tries to solve these above-mentioned problems. The proposed method is tested on the KITTI dataset and the result shows a significant improvement without too many tricky parameter adjustments and training skills. The proposed method can also be used on other objects with obvious foreshortening effects, such as on-board pedestrian detection. The basic idea of the proposed method does not rely on concrete implementation and thus, most deep learning based object detectors with multiscale feature maps can be optimized with it.

The H9N2 avian influenza virus, although not highly pathogenic, still poses ongoing risks to poultry health and food security due to its ability to resist vaccines and its potential to spread to humans. This study investigated the effects of baicalin, a flavonoid derived from , on respiratory mucosal immunity during H9N2 infection. In vitro experiments were conducted using MLE-12 alveolar epithelial cells, and in vivo evaluations were performed in a mouse model of H9N2 infection. Baicalin treatment enhanced the expression of antiviral proteins Mx1 and PKR in a dose- and time-dependent manner, helping to counteract the virus's suppression of these defense proteins. In addition to strengthening this epithelial barrier, baicalin has both antiviral and immune-regulating effects: it directly blocks viral replication and helps restore the CD4+/CD8+ T cell ratio in H9N2-infected mice. Most importantly, baicalin reduces lung damage and spleen shrinkage while keeping the immune system balanced. These results show that baicalin enhances mucosal antiviral defenses by simultaneously regulating innate antiviral pathways (Mx1 and PKR) and restoring adaptive immune balance (CD4+/CD8+ T-cell ratio). These dual protective effects highlight baicalin's potential as a natural therapeutic strategy for improving mucosal immunity against vaccine-resistant influenza viruses such as H9N2, contributing valuable insights into plant-derived immunomodulatory approaches against emerging zoonotic viral threats.

Due to the complexity of terrain and climate in the mountain–plain transition zone, it is difficult to simulate and forecast the flow discharge of river basins accurately. The poor regularity of the river thus leads to uncertain flood control scheduling. Meanwhile, reservoirs and flood detention areas are constructed to store and divert water when severe floods threaten the safety of the basin. In order to improve the accuracy of flood forecasts and the effectiveness of flood control, a hydrological and 1D/2D hydrodynamic coupling model was developed to enable the joint computation of multiple objects, including mountainous streams, plains river networks, hydraulic control structures, and flood detention areas. For the hydrological component, the Xin’anjiang model with the Muskingum module is employed to simulate mountainous flow discharge. For the hydrodynamic component, the Saint–Venant equations and shallow water equations are applied to estimate flood processes in rivers and on land surfaces, respectively. The Dongtiaoxi River Basin in Zhejiang Province, China, serves as the case study, where river flow is influenced by both upstream mountainous floods and downstream backwater effects. Using the integrated model, flood routing and scheduling are simulated and visualized. Both the Xin’anjiang model and the 1D hydrodynamic model demonstrate over 80% acceptability in calibration and validation, confirming their robustness and reliability. Meanwhile, inundation in flood detention areas can be effectively estimated by coupling the 1D and 2D hydrodynamic models with a flood diversion scheduling model. The coupled model proves capable of simulating flood routing in complex river basins that include mountains, plains, and hydraulic control structures, accounting for the interactions between hydrological elements. These findings provide a new perspective on flood simulation in other similarly complex river basins.

In our research, we explored a natural substance called Oxymatrine, found in a traditional Chinese medicinal plant, to fight against a common bird flu virus known as H9N2. This virus not only affects birds but can also pose a threat to human health. We focused on how this natural compound can help in stopping the virus from spreading in cells that line the lungs of birds and potentially humans. Our findings show that Oxymatrine can both directly block the virus and boost the body’s immune response against it. This dual-action mechanism is particularly interesting because it indicates that Oxymatrine might be a useful tool in developing new ways to prevent and treat this type of bird flu. Understanding how Oxymatrine works against the H9N2 virus could lead to safer and more natural ways to combat viral infections in animals and humans, contributing to the health and well-being of society. The H9N2 Avian Influenza Virus (AIV) is a persistent health threat because of its rapid mutation rate and the limited efficacy of vaccines, underscoring the urgent need for innovative therapies. This study investigated the H9N2 AIV antiviral properties of Oxymatrine (OMT), a compound derived from traditional Chinese medicine, particularly focusing on its interaction with pulmonary microvascular endothelial cells (PMVECs). Employing an array of in vitro assays, including 50% tissue culture infectious dose, Cell Counting Kit-8, reverse transcription-quantitative polymerase chain reaction, enzyme-linked immunosorbent assay, and Western blot, we systematically elucidated the multifaceted effects of OMT. OMT dose-dependently inhibited critical antiviral proteins (PKR and Mx1) and modulated the expression of type I interferons and key cytokines (IFN-α, IFN-β, IL-6, and TNF-α), thereby affecting TLR3 signaling and its downstream elements (NF-κB and IRF-3). OMT’s antiviral efficacy extended beyond TLR3-mediated responses, suggesting its potential as a versatile antiviral agent. This study not only contributes to the growing body of research on the use of natural compounds as antiviral agents but also underscores the importance of further investigating the broader application of OMT for combating viral infections.

Acquisition of the arterial and haemogenic endothelium fates concurrently occur in the aorta–gonad–mesonephros (AGM) region prior to haematopoietic stem cell (HSC) generation. The arterial programme depends on Dll4 and the haemogenic endothelium/HSC on Jag1-mediated Notch1 signalling. How Notch1 distinguishes and executes these different programmes in response to particular ligands is poorly understood. By using two Notch1 activation trap mouse models with different sensitivity, here we show that arterial endothelial cells and HSCs originate from distinct precursors, characterized by different Notch1 signal strengths. Microarray analysis on AGM subpopulations demonstrates that the Jag1 ligand stimulates low Notch strength, inhibits the endothelial programme and is permissive for HSC specification. In the absence of Jag1, endothelial cells experience high Dll4-induced Notch activity and select the endothelial programme, thus precluding HSC formation. Interference with the Dll4 signal by ligand-specific blocking antibodies is sufficient to inhibit the endothelial programme and favour specification of the haematopoietic lineage. It is unclear how Notch1 signals regulate both the maintenance of the endothelial fate and the endothelial-to-hematopoietic transition in the embryonic aorta. Here the authors show that those cells in which Notch1 ligand Jag1 is out-competed by Dll4 remain endothelial, while higher Jag1 activity leads to generation of hematopoietic stem cells.

Cannabidiol (CBD), as an important therapeutic property of the cannabis plants, is mainly produced in the flower organs. Auxin response factors (ARFs) are play a crucial role in flower development and secondary metabolite production. However, the specific roles of ARF gene family in cannabis remain unknown. In this study, various bioinformatics analysis of genes were conducted using online website and bioinformatics, quantitative real time PCR technology was used to investigate the expression patterns of the gene family in different tissues of different cannabis varieties, and subcellular localization analysis was performed in tobacco leaf. In this study, 22 genes were identified and found to be unevenly distributed across 9 chromosomes of the cannabis genome. Phylogenetic analysis revealed that the ARF proteins were divided into 4 subgroups. Duplication analysis identified one pair of segmental/whole-genome duplicated , and three pairs of tandemly duplicated . Collinearity analysis revealed that two genes, and , were orthologous in both rice and soybean. Furthermore, subcellular localization analysis showed that was localized in the nucleus. Tissue-specific expression analysis revealed that six genes were highly expressed in cannabis male flowers, and among these genes, 3 genes were further found to be highly expressed at different developmental stages of male flowers. Meanwhile, correlation analysis between the expression level of genes and CBD content in two cultivars 'H8' and 'Y7' showed that the expression level of was negatively correlated with CBD content, while the expression levels of six genes were positively correlated with CBD content. In addition, most of genes were responsive to IAA treatment. Our study laid a foundation for the further studies of CsARFs function in cannabis, and provides candidate genes for breeding varieties with high CBD yield in cannabis production.

Background/Objectives: Periostracum Cicadae (PC) is commonly used to treat chronic atrophic gastritis (CAG), but its underlying mechanisms are unclear. We investigated the therapeutic effects, active ingredients and molecular mechanisms of PC on CAG. Methods: We analyzed the components in the serum extract of PC by UHPLC-Q-Orbitrap-MS/MS. Then, we used rat and cell models to assess the impact of PC on CAG and employed network pharmacology and bioinformatics to predict key targets and active ingredients. Finally, we confirmed hub targets through experiments and molecular docking. Results: A total of 22 components were identified in the PC extract-containing serum using UHPLC-Q-Orbitrap MS/MS. Network pharmacology combined with molecular docking revealed that the protective effect was primarily mediated by three compounds: (Z)-akuammidine, chicoric acid, and columbianadin. And we revealed that c-Fos/c-Jun signaling pathways were crucial in therapy. PC extract-containing serum inhibited the vitality, migration, invasion, and multiplication of MC cells (model cells for CAG), induced apoptosis, and caused G0/G1 phase cell cycle arrest. The expression level of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β) and gastrin 17 (G17) in the serum of CAG rats increased, while the expression level of pepsinogen I (PG I) and pepsinogen II (PG II) decreased. After 12 weeks of PC administration, these conditions were significantly improved. PC not only reduced the levels of antigen KI-67 (Ki67) and tumor protein p53 (P53) but also enhanced SRY-box Transcription Factor (SOX2). Simultaneously, PC down-regulated the expression of N-cadherin and Vimentin while up-regulating that of E-cadherin. Conclusions: PC inhibited epithelial–mesenchymal transition (EMT) via the c-Fos/c-Jun signaling pathway, thereby providing therapeutic benefits for CAG. Our study elucidates the mechanisms and material basis of PC in treating CAG, providing experimental evidence to support its clinical application.