Oxymatrine Modulation of TLR3 Signaling Pathway: A Dual-Action Mechanism against H9N2 Avian Influenza Virus and Immune Regulation

Oxymatrine Modulation of TLR3 Signaling Pathway: A Dual-Action Mechanism against H9N2 Avian Influenza Virus and Immune Regulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Oxymatrine Modulation of TLR3 Signaling Pathway: A Dual-Action Mechanism against H9N2 Avian Influenza Virus and Immune Regulation Yan Zhi, Zhenyi Liu, Guo Shen, Xiang Wang, Ying Liu, TAO Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3846667/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background H9N2 Avian Influenza Virus (AIV) poses a growing public health threat due to its rapid mutation rate and limited vaccine efficacy. Pulmonary Microvascular Endothelial Cells (PMVECs) play a critical role as a gateway for infection, highlighting the need for alternative therapeutic strategies. This study examines the antiviral potential of Oxymatrine (OMT), a traditional Chinese medicine derivative, against H9N2 AIV in PMVECs. Purpose The aim of this study is to explore the efficacy of OMT in modulating antiviral responses and to elucidate its impact on the TLR3 signaling pathway in PMVECs infected with H9N2 AIV. Study Design and Methods: Using an array of in vitro assays such as TCID50, CCK-8, RT-qPCR, ELISA, and Western blot, this study evaluated the viral infectivity, cell viability, gene and protein expression levels, and key cytokine levels in PMVECs. Additionally, RNAi technology was employed to silence TLR3 genes to further understand the mechanisms involved. Results OMT displayed a dose-dependent inhibitory effect on vital antiviral proteins PKR and Mx1 and modulated the expression of Type I interferons and cytokines including IFN-α, IFN-β, IL-6, and TNF-α. It significantly impacted the TLR3 signaling pathways, affecting downstream components such as NF-κB and IRF-3. TLR3 silencing studies indicated that OMT's antiviral efficacy was not solely dependent on the TLR3 pathway. Conclusion Our findings reveal that OMT exhibits a dual-action mechanism by inhibiting H9N2 AIV and modulating immune responses in PMVECs, primarily through the TLR3 signaling pathway. These results lay a promising foundation for the development of OMT as an alternative antiviral therapeutic against H9N2 AIV. H9N2 Avian Influenza Virus (AIV) Pulmonary Microvascular Endothelial Cells (PMVECs) Oxymatrine (OMT) Antiviral Mechanisms TLR3 Signaling Pathways Cytokine Modulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Influenza viruses are categorized into three types: A, B, and C, based on variations in their nucleoproteins and M proteins (Starick et al., 2000 ). Among these, Type A's H9N2 avian influenza has garnered attention due to its prevalence in poultry, driven by its robust mutagenic and gene recombination capabilities (Liu et al., 2016 , Wei and Li, 2018 ). Although deemed low in pathogenicity, H9N2's rampant transmission in poultry inflicts significant economic losses and poses a direct threat to human health (Wang et al., 2021 , Zhang et al., 2022 ). Primarily infecting the respiratory tracts of avian species (Yao et al., 2014 ), H9N2 triggers severe inflammatory responses and immune imbalances, potentially leading to fatal outcomes. While vaccination remains the primary preventive strategy, antigenic variation of the virus and vaccine immune escape pose increasing challenges (Zhang et al., 2023b , de Vries et al., 2018 ). The inflammatory response to avian influenza virus infection arises from a dynamic interplay between the virus and the host's immune system, with Toll-like receptor 3 (TLR3) as a pivotal player (Huo et al., 2018 ). Past research indicates that avian influenza infection elevates the expression of TLR3 and IFN- β in the lungs and brains of chicks, underscoring the significance of TLR3 in immune responses against avian influenza (Nang et al., 2011 ). The H9N2 virus can infect Pulmonary Microvascular Endothelial Cells (PMVECs), crucial for forming the vascular barrier and modulating immune responses (Teijaro et al., 2011 ). Upon viral entry into PMVECs, an array of receptors is activated through specific recognition of pathogen-associated molecular patterns (PAMPs) (Sun et al., 2022 ), with TLR3 emerging as the primary pattern recognition receptor for dsRNA detection. This activation propels a cascade of signaling events, inducing Type I interferons and inflammatory cytokines, thereby kick-starting the innate immune response (Edelmann et al., 2004 , Nasirudeen et al., 2011 ). Traditional Chinese Medicine (TCMs) holds promise in antiviral strategy development due to its mild nature and low likelihood of inducing drug resistance. Oxymatrine (OMT), an active monomer extracted from various TCMs including Sophora flavescens Ait and Radix Sophorae Tonkinensis (Bi et al., 2012 , Liang et al., 2023 ), has demonstrated efficacy in managing chronic hepatitis B (Lu et al., 2004 ). Besides its hepatoprotective role, OMT exhibits potential against tumorigenesis, inflammation, and bacterial infections (Li et al., 2022 , Cao et al., 2023 , Zhang et al., 2023a). Notably, in Hepatitis B virus (HBV) transgenic mice liver (Chen et al., 2001 ), OMT reduces levels of HBsAg and HBcAg, and as a potent immunosuppressant, it curtails replication and inflammation of type A influenza virus via the TLR4, p38 MAPK, and NF-κB pathways (Dai et al., 2018 ). Despite these diverse bioactivities, the role of OMT against avian influenza and its interaction with the TLR3 signaling pathway largely remain unknown. Given this background, this study endeavors to examine whether OMT mediates its antiviral effect against the H9N2 subtype of avian influenza virus via the TLR3 signaling pathway. We employed primary PMVECs from rats as the experimental model. Utilizing RNAi technology for validation, this investigation aims to shed light on OMT's role in countering H9N2 AIV, thereby offering novel strategies and a theoretical foundation for avian influenza treatment. Simultaneously, this study seeks to underline the untapped potential of TCMs in antiviral therapeutics. 2. Materials and Methods 2.1. Cell Lines and Viruses The primary cell lines utilized in this study were Madin Darby Canine Kidney cells (MDCKs) and Pulmonary Microvascular Endothelial Cells (PMVECs). MDCK Cells : MDCKs, preserved in our laboratory, were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM; BioWhittaker, Walkersville, MD, USA) supplemented with 10% fetal bovine serum (FBS; Gibco-BRL, New York, USA) and 2% penicillin/streptomycin antibiotic/antimycotic mixture (GIBCO-BRL, New York, USA). PMVEC Cells : PMVECs, isolated from 7–9 day-old rats using the tissue block explant method (Ocaña-Macchi et al., 2009 ), were supplemented with 15 µg/ml Endothelial Cell Growth Supplement (ECGS; Millipore, Billerica, USA) in DMEM during the isolation process. Like MDCKs, PMVECs were also cultured in DMEM supplemented with 10% FBS and 2% penicillin/streptomycin. Both cell lines were maintained at 37℃ in a humidified atmosphere containing 5% CO 2 . Viruses : The low pathogenicity avian influenza virus (LPAIV) H9N2 subtype, with GenBank accession numbers FJ499463-FJ499470, was obtained from the laboratory of the China Agricultural University. These viruses were propagated in either MDCKs, PMVECs, or 11-day-old specific pathogen-free (SPF) embryonated chicken eggs, as previously described (Mostafa et al., 2020 , Wang et al., 2020 ). 2.2. siRNA-mediated TLR3 Silencing in PMVECs TLR3 silencing in PMVECs was performed using siRNA sequences synthesized by Beijing Qinkai Biotechnology Co. Ltd. Specific siRNA sequences targeting the TLR3 gene were derived from the NCBI database. Their specificity was confirmed by BLAST analysis in NCBI, ensuring a match solely with the rat TLR3 gene and ensuring no off-target effects on other genes (Table S1). Safety concentration screenings for both siRNA and transfection reagent were conducted prior to transfection (Fig. S1). Optimal siRNA candidates were selected based on time-course, concentration evaluations, and sequence efficacy (Fig. S2). Transfection into PMVECs was carried out using the identified optimal conditions, aiming for a target interference effect of 60%-70% (Kleinman et al., 2008 ). 2.3. OMT Characterization and Cytotoxicity Assessment OMT, an established bioactive monomer (Bi et al., 2012 , Liang et al., 2023 ), was sourced from Shanghai Yuan-ye Biotechnology Co., Ltd., with its chemical structure illustrated in (Fig. 1 A). Cell Seeding : PMVECs were seeded in a 96-well polypropylene plate at a density of 1×10 4 cells/ml with 100 µL/well and incubated at 37°C in a 5% CO 2 atmosphere. OMT Treatment : At 80% confluence, cells were treated with OMT concentrations (2.5, 5, 10 µg/ml) in phenol-red free DMEM with DMSO as a solvent, ensuring a consistent and non-toxic DMSO concentration. Each concentration was replicated in six wells, and control wells received only DMSO in DMEM. To minimize the impact of edge evaporation on the experiment, the perimeter wells of the plate were filled with PBS. Viability Assessment : Post-OMT treatment over 12, 24, 36, and 48 h intervals, cells were washed with 200 µL PBS. Then, 10 µL of CCK-8 reagent (Beijing Solar-bio Science & Technology Co., Ltd.) was added to each well, followed by a 2–4 h incubation to allow for formazan crystal formation. Absorbance was measured at 450 nm, with a reference wavelength of 600–650 nm. Cell viability was calculated as: $$Cell Viability\left(\%\right)=\frac{Absorbance \text{o}\text{f} control sample}{Absorbance of \text{t}\text{e}\text{s}\text{t} sample}\times 100\%$$ 2.4. Determination of H9N2 TCID 50 The viral titers infecting 50% of MDCKs were quantified using the Reed and Muench method (Ramakrishnan, 2016 ). MDCKs were adjusted to a density of 1×10 4 cells/ml, plated in a 96-well format, and cultivated at 37°C under 5% CO 2 until approximately 80% confluence, followed by a brief PBS wash. H9N2 AIV was serially diluted ten-fold, spanning concentrations from 10 − 1 to 10 − 10 , and introduced to the monolayers of MDCKs. After a 1h adsorption at 37°C in 5% CO 2 , the inoculum was replaced with 2% DMEM maintenance medium. Over a 72 h period, wells displaying more than 70% Cytopathic Effect (CPE) were denoted as positive. Separately, PMVECs grown to over 90% confluence in 6-well plates were infected with doses of 1x TCID 50 , 50x TCID 50 , and 100x TCID 50 . The optimal infectious dose was ascertained through CPE analysis. 2.5. Experimental Grouping and Treatment Methods Investigation of OMT's Effect on Cytokine Expression Aim : To assess the influence of OMT on the expression levels of cytokines and key signaling pathways (TLR3, NF-κB, and IRF-3) in PMVECs following H9N2 AIV infection. Experimental Groups :Control group (uninfected), H9N2 AIV-infected group, H9N2 AIV-infected groups with OMT at low, medium, and high concentrations (2.5, 5, and 10 µg/ml, respectively). Sampling Time Points : Samples were collected at four distinct intervals: 12, 24, 36, and 48 h post-infection. Each time point consisted of triplicate samples. Assessment of OMT's Role in TLR3-Silenced PMVECs Aim : To evaluate how OMT affects PMVECs infected with H9N2 AIV when TLR3 protein is silenced. Experimental Groups : H9N2 AIV-infected control group, TLR3 RNAi + H9N2 AIV-infected group, H9N2 AIV-infected group with medium-dose OMT (5 µg/ml), two different types of TLR3 RNAi + H9N2 AIV-infected group with medium-dose OMT. Sampling Time Points : Similar to the previous setup, samples were collected at 12, 24, 36, and 48 h intervals, each with triplicate samples. 2.6. ELISA Determination of Cytokine Levels Samples acquired from the previous steps were analyzed via ELISA to quantify the levels of cytokines IFN- β , IFN- α , IL-6, and TNF- α . Commercial ELISA kits from ABclonal (Wuhan, China) were utilized, following the manufacturer’s instructions strictly. The homogenized samples were centrifuged at 1000 rpm for 10 min at 4℃. The supernatant was then carefully collected, and the optical density (OD) was determined at a wavelength of 450 nm using a TECAN F50 spectrophotometer (Mannedorf, Switzerland). 2.7. RNA Extraction and Real-Time Quantitative PCR RNA was isolated from PMVECs using the TransZol Up kit (Takara, Dalian, China). The extracted RNA was immediately reverse transcribed to cDNA and stored at -80°C. For RT-qPCR, we employed the 2 × Hieff UNICON® Universal Blue qPCR Master Mix (Yeasen, Shanghai, China). The amplification protocol included UDG activation at 50°C for 2 min, initial denaturation at 95°C for 2 min, followed by 40 cycles of 95°C for 15 s and 60°C for 30 s. A subsequent melting curve analysis was conducted. Each sample was analyzed in triplicate. The β-actin rRNA served as the endogenous control as previously described (Meng et al., 2022 ). Gene expression fold changes were calculated using the 2 −ΔΔCT method. Detailed genes and primer sequences for qRT-PCR are listed in Table S2. Data were analyzed utilizing GraphPad Prism 8. 2.8. Western Blot Analysis for Protein Expression in PMVECs For Western blot analysis, PMVECs were seeded in 6-well plates at a density of 1×10 5 cells/ml and cultured until 80–90% confluence. Cells were then exposed to H9N2 AIV for 1 h at 37°C, with control groups receiving 2% maintenance medium. Following infection, cells were treated with OMT concentrations of 2.5, 5, or 10 µg/ml. Proteins were harvested at 12, 24, 36, and 48 h post-infection by washing the cells with pre-cooled PBS and lysing them in cold RIPA:PMSF buffer (100:1) for 20–30 min. Lysates were centrifuged at 12,000 rpm for 20 mins at 4°C, and the supernatants were stored for further analysis. Protein concentrations were quantified employing the BCA assay (Beyotime, Shanghai, China). Samples were then resolved on 15% SDS-PAGE and transferred to membranes at 100 V for 2 h. For immunoblotting, membranes were blocked and then incubated overnight at 4°C with primary antibodies from Jiangsu Qinke Biotechnology Research Center, China, including TLR3 (Catalog No. DF6415), NF-κB p65 (Catalog No. AF5006), and IRF3 (Catalog No. DF6895). Additionally, β-actin (Catalog No. 20536-1-AP) and GAPDH (Catalog No. 10494-1-AP) antibodies were used, both sourced from Wuhan Sanying Biotechnology, China. This was followed by a 90 min incubation with appropriate secondary antibodies. Protein bands were visualized using the Odyssey infrared imaging system (LI-COR Biosciences, Lincoln, NE, USA) and quantified relative to β-actin or GAPDH using ImageJ software (version 1.51j8, National Institutes of Health, Bethesda, MD, USA). 2.9. Statistical Analysis Data were analyzed using GraphPad Prism (Version 8.0, San Diego, USA) and are shown as means ± SD. An unpaired Student’s t-test assessed differences between two groups, while a one-way ANOVA was employed for multiple group comparisons. For RT-qPCR, relative quantification (2 −ΔΔCT ) was applied. Western blot band intensities were quantified using ImageJ. P < 0.05 was considered statistically significant. 3. Results 3.1. Observation and Immunofluorescent Identification of PMVECs Cellular Observation Morphological changes in the primary isolated PMVECs were monitored over time. Migration from the tissue block periphery commenced around 6 h post-culture initiation (Fig. S3A), escalating with time (Fig. S3B-D). By 60 h, significant cell density was achieved, facilitating tissue block removal (Fig. 1 B). Predominantly, cells exhibited a cobblestone morphology with an interlocked arrangement, albeit some hematopoietic cells were also discerned. Post-media change, cells continued to proliferate, transitioning to a spindled morphology with increasing passage number (Fig. 1 C and D). Immunofluorescence Analysis Immunofluorescence staining revealed pronounced CD31 expression, a hallmark endothelial marker. Nuclei were stained blue with DAPI, while CD31 exhibited red fluorescence (Fig. S4). Merged images corroborated that the majority of cells were PMVECs (Fig. 1 E and F), validating their aptness for ensuing experiments. 3.2. H9N2 AIV Infectivity in PMVECs via TCID 50 Assay To determine H9N2 AIV infectivity in PMVECs, the virus was initially propagated in MDCKs through gradient dilutions. Daily observations disclosed pathological alterations in PMVECs attributable to viral infection. The calculated TCID 50 of H9N2 AIV was 10 − 4.8 /0.1ml based on the Reed-Muench method. A starting dilution of 10 − 2 yielded a virus titer of 10 − 3 /ml in PMVECs (Table 1 ). Table 1 TCID 50 determination results of H9N2 AIV Virus Dilution Observed CPE Cumulative CPE Infection Rate (%) Well Count CPE Positive Wells CPE Negative Wells Cumulative CPE Positive Wells Cumulative CPE Negative Wells Proportion of CPE Positive Wells CPE Positive Rate (%) 10 − 1 8 8 0 33 0 33/33 100 10 − 2 8 8 0 25 0 25/25 100 10 − 3 8 8 0 17 0 17/17 100 10 − 4 8 6 2 11 2 11/13 84.61 10 − 5 8 3 5 5 7 5/12 41.67 10 − 6 8 2 6 2 13 2/15 13.33 10 − 7 8 0 8 0 21 0/21 0 Note: CPE = Cytopathic Effect 3.3. Cytotoxic Effects of OMT on PMVECs Assessed by CCK-8 Assay The impact of varying OMT concentrations on PMVECs was explored across distinct time intervals: 12 h, 24 h, 36 h, and 48 h. Cell viability post-OMT exposure was assessed using the CCK-8 assay (Fig. 2 , Table 2 ). OMT concentrations exceeding 12.5 µg/ml significantly decreased cell viability ( P < 0.0001). Additionally, a narrow concentration gradient was screened for drug dosing (Fig. S5, Table S3). Subsequent studies utilized OMT at 2.5 µg/ml, 5 µg/ml, and 10 µg/ml. Table 2 Impact of various OMT concentrations on PMVECs survival rate OMT Concentration (µg/ml) Survival Rate (%) Time (h) 0 3.125 6.25 12.5 25 50 100 200 12 100.00 95.96 95.03 92.72 92.52 88.77 68.06 70.39 24 100.00 95.36 96.23 90.67 79.12 72.94 57.66 36.79 36 100.00 95.39 93.52 84.81 74.71 62.07 47.47 29.69 48 100.00 95.98 95.06 84.34 73.61 63.61 27.38 27.04 3.4. OMT's Influence on Antiviral Protein Expression in H9N2 AIV-Infected PMVECs The antiviral capacity of OMT in PMVECs infected with H9N2 AIV was investigated by assessing the modulation of antiviral proteins PKR and Mx1 at mRNA expression levels via RT-qPCR. Following H9N2 AIV infection, a surge in PKR and Mx1 mRNA expressions was noted in PMVECs. OMT treatment exhibited dose-dependent dynamics: low-dose OMT enhanced PKR mRNA levels ( P < 0.05), while medium-dose and high-dose progressively diminished them ( P < 0.01) (Fig. 3 A). Mx1 mRNA levels increased with low and medium OMT doses ( P < 0.05), yet high-dose led to suppression. By 48 h, all OMT concentrations resulted in reduced Mx1 mRNA levels ( P < 0.01), denoting both time and dose dependencies (Fig. 3 B). 3.5 Regulatory Effects of OMT on the Expression Levels of IFN- α , IFN- β , IL-6, and TNF- α in PMVECs Infected with H9N2 AIV Following H9N2 AIV infection and subsequent OMT treatment at varying doses, significant alterations in key cytokine levels within PMVECs were observed. As depicted in Fig. 4 A, within 12 and 24 h post-treatment, both the virus and high-dose OMT groups demonstrated significant elevations in IFN- α levels compared to the control group ( P < 0.05). Conversely, the low-dose OMT group exhibited a substantial reduction in IFN- α levels relative to the virus group ( P = 0.005). For IFN- β (Fig. 4 B), the 24 and 36 h post-treatment were particularly illuminating: both medium-dose and high-dose OMT groups not only surpassed the control group but also outperformed the virus group in terms of elevated IFN- β levels ( P < 0.01). Across all examined time points, IL-6 levels in all OMT treatment groups were significantly lower than those in the virus group (Fig. 4 C), a trend most pronounced at the 12 h mark ( P < 0.0001). Regarding TNF- α (Fig. 4 D), 36 h post-infection witnessed all OMT dosages yielding substantially reduced levels when compared to the virus group ( P < 0.05).These effects exhibited both time- and dose-dependent characteristics. 3.6 Effects of OMT on mRNA and Protein Expression Levels of NF-κB, IRF-3, and TLR3 in H9N2 AIV-Infected PMVECs Post H9N2 AIV infection and subsequent OMT treatment, significant alterations in the mRNA and protein expression levels of NF-κB, IRF-3, and TLR3 were noted, as evaluated through RT-qPCR and Western blot analyses. mRNA Expression Changes Compared to the control group, both the virus and OMT treatment groups demonstrated elevated mRNA levels of NF-κB, IRF-3, and TLR3 across various time points (Fig. 5 A-C). Specifically, NF-κB and IRF-3 mRNA levels were significantly upregulated at 12 and 24 h post-infection in the virus group and low-dose OMT groups ( P < 0.01). However, medium-dose and high-dose OMT groups exhibited a pronounced reduction in NF-κB and IRF-3 mRNA levels across all time points ( P < 0.01). For TLR3, the elevation was most prominent at 48 h in the virus and low-dose OMT groups, while medium-dose and high-dose OMT led to a consistent reduction ( P < 0.01). Protein Expression Changes Western blot analyses, quantified via ImageJ, unveiled distinct patterns in NF-κB, IRF-3, and TLR3 protein levels. (Fig. 5 D-I) Elevated TLR3 and NF-κB levels were consistently observed at all time points in both the virus group and OMT-treated groups ( P < 0.05). High-dose OMT treatment led to a significant reduction in TLR3 protein levels at 12 and 36 h ( P < 0.01). NF-κB protein levels remained consistently elevated in the virus and all OMT-treated groups but were mitigated across all OMT doses ( P < 0.0001). IRF-3 levels showcased a marked decrease in the high-dose OMT group at all times compared to the virus group ( P = 0.0001). 3.7 Effects of OMT on mRNA and Protein Expression Levels of NF-κB and IRF-3 Post-TLR3 Silencing and H9N2 AIV Infection mRNA Expression Changes Following TLR3 silencing, NF-κB mRNA levels significantly declined at all time points (12, 24, 36, and 48 h) post H9N2 AIV infection (Fig. 6 A; P < 0.005). Conversely, medium-dose OMT (5 µg/ml) significantly increased NF-κB mRNA levels across all time points ( P < 0.0005). Notably, different types of si-RNA for TLR3 silencing yielded varying effects on NF-κB mRNA levels at 36 and 48 h ( P < 0.0005). Similarly, TLR3 silencing resulted in a significant decrease in IRF-3 mRNA levels at all time points post H9N2 AIV infection (Fig. 6 B; P < 0.005). Medium-dose OMT treatment post-TLR3 silencing significantly augmented IRF-3 mRNA levels at all time points ( P < 0.0001). Distinct effects were observed at 12–48 h depending on the type of si-RNA utilized for TLR3 silencing ( P < 0.05). Protein Expression Changes Western blot analysis disclosed reduced NF-κB protein levels in the TLR3 RNAi + H9N2 AIV infection group across all time points (Fig. 6 C and 6 E; P < 0.01). Medium-dose OMT treatment post-TLR3 silencing led to a significant increase in NF-κB levels, although this effect was not sustained ( P < 0.01). For IRF-3 protein, levels significantly declined at all time points post TLR3 silencing (P < 0.01). However, medium-dose OMT treatment reversed this effect, dependent on the si-RNA type employed for TLR3 silencing (Fig. 6 D and 6 F; P < 0.01). 4. Discussion H9N2 AIV mainly targets the respiratory tracts of animals and humans through PMVECs, which form a vascular barrier and play a pivotal role in immune modulation 11 . Despite the virus's low pathogenicity, its rapid mutation rate and efficient transmission, exacerbated by insufficient preventative measures, have rendered conventional vaccine strategies increasingly less effective (Dong et al., 2022 ). Given this challenge, alternative therapeutic approaches are crucial. This prompted our study to comprehensively investigate the potential of OMT, a traditional Chinese medicine component, as a promising antiviral agent against H9N2 AIV. Our findings highlight OMT's dual-action mechanism modulating cellular responses and signaling, serving both antiviral and immune-regulatory functions. One of our pivotal findings is the inhibitory effect of OMT on the expression levels of PKR and Mx1 mRNA, both of which are significantly induced upon H9N2 AIV infection, as demonstrated by RT-qPCR analyses. These molecules, PKR and Mx1, are well-documented as crucial players in the antiviral response (Zuo et al., 2022 , Pillai et al., 2016 ). The inhibition observed suggests that OMT could be modulating host-virus interactions at the cellular level, possibly through its modulation of the TLR3 signaling pathways, although the exact mechanism remains to be elucidated (Sang et al., 2017 ). Additionally, our study demonstrated that OMT upregulates the expression of Type I interferons (IFN- α and IFN- β ), which are key mediators of innate immunity (Chen and Yu, 2016 ). This modulation of interferon levels by OMT resonates with previous studies on other traditional Chinese medicine components (Lee et al., 2020 , Zhang et al., 2021 ), which further strengthens the evidence for the antiviral efficacy of natural compounds (van de Sand et al., 2021 ). OMT's influence on the TLR3 pathway emphasizes its role in immune regulation and its dual-action against H9N2 AIV. However, the precise mechanism by which OMT influences interferon levels remains elusive and warrants further investigation, potentially through more detailed molecular and biochemical analyses. TLR3 signaling pathways further clarify OMT's effects. Our observations reveal that OMT modulates the expression of NF-κB and IRF-3, which are key downstream components of the TLR3 pathway (Audry et al., 2011 ). This modulation indicates that OMT may exert its antiviral effects, at least in part, by altering the TLR3-mediated activation of these transcription factors, thereby potentially dampening excessive inflammatory reactions while bolstering antiviral defenses against H9N2 AIV. These findings align with the pivotal role of TLR3 in viral infections as highlighted in previous research, and suggest that the elucidated involvement of TLR3 signaling in H9N2 AIV infection provides a promising avenue for devising targeted therapeutic strategies (de Carvalho et al., 2019 ). It's important to note that signaling pathways are not linear but form intricate networks, with multiple pathways and proteins potentially playing a role in the observed antiviral response. For instance, other pathways such as TLR4, TLR7, and MAPK, along with proteins like TNF- α , RIG-I, and MITA, could also be implicated in this complex antiviral response (Xu et al., 2015 , Liu et al., 2023 ). These pathways and proteins are not mutually exclusive and may interact either synergistically or antagonistically (Govorkova et al., 2004 ), thereby affecting the overall antiviral activity of OMT. This underscores the necessity for further investigation to unravel the complex signaling networks modulated by OMT and to understand how these modulations contribute to its antiviral efficacy. Our study shows that silencing TLR3 reduces NF-κB and IRF-3 expression, highlighting TLR3's role in the immune response to H9N2 AIV. Despite the silencing of TLR3, the antiviral activity of OMT persisted, indicating its diverse mechanistic pathways and suggesting its ability to mount a multi-faceted defense against H9N2 AIV. This observation has significant implications. Firstly, it posits that the antiviral efficacy of OMT is not solely dependent on TLR3 signaling, thereby potentially broadening its applicability as an antiviral agent. This could prove particularly valuable in situations where TLR3 signaling is compromised, either due to genetic mutations or other factors. Secondly, it introduces the likelihood that OMT may act through multiple signaling pathways, either in parallel or synergistically, to exert its antiviral effects. This aspect of polypharmacology could potentially offer a more robust and adaptable defense against rapidly mutating viruses like H9N2 AIV. A key limitation of our study is its primary reliance on in vitro models. Translating these findings to in vivo settings is crucial for OMT's antiviral validation. Our preliminary plan encompasses evaluating the antiviral efficacy and safety of OMT against H9N2 AIV in animal models, selecting appropriate models to ensure the clinical relevance of our experimental design. If initial in vivo studies show promise, our collaboration with clinical teams aims for preliminary clinical trials. Given these considerations, it's also imperative to understand the deeper mechanisms at play. The complex signaling networks suggest a systems biology approach, using computational modeling and experimental validation, to understand the interactions between OMT, TLR3 signaling, and its antiviral activity. Furthermore, delving into the pharmacological properties and pharmacokinetics of OMT will ascertain its optimal dosing and application regimen in humans, addressing challenges such as drug bioavailability, dosage determination, potential side effects, and drug interactions. In line with advancing OMT to the clinical evaluation stage, we acknowledge the significance of liaising with relevant regulatory authorities and seeking external funding support to ensure adherence to stipulations and standards for clinical trials. Our aim is to capitalize on the antiviral and immune-regulatory effects of OMT, providing a potential therapeutic avenue to tackle the challenges posed by H9N2 AIV. Through concerted efforts and close collaboration with clinical research teams, we aspire to lay a solid foundation for the clinical application of OMT. The time-consuming nature of this process is acknowledged, yet we are committed to navigating the intricacies involved, propelled by the potential of OMT as a versatile therapeutic agent against H9N2 AIV. 5. Conclusion Our study elucidates the dual-action mechanism of OMT against H9N2 AIV, showcasing its potential as both an antiviral agent and an immune modulator. This distinction highlights OMT's potential as a versatile therapeutic agent in addressing the challenges posed by H9N2 AIV. Our findings lay a groundwork for further investigations into the clinical potential of OMT. Future endeavors exploring OMT's efficacy in in vivo models and clinical trials are pivotal steps towards harnessing its therapeutic promise against H9N2 AIV and possibly other viral infections. Abbreviations AIV, Avian Influenza Virus; CCK-8, Cell Counting Kit-8; ELISA, Enzyme-Linked Immunosorbent Assay; IFN-α, Interferon Alpha; IFN-β, Interferon Beta; IL-6, Interleukin 6; IRF-3, Interferon Regulatory Factor 3; Mx1, Myxovirus Resistance 1; NF-κB, Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells; OMT, Oxymatrine; PKR, Protein Kinase R; PMVECs, Pulmonary Microvascular Endothelial Cells; RNAi, RNA Interference; RT-qPCR, Reverse Transcription Quantitative Polymerase Chain Reaction; TCID50, Tissue Culture Infectious Dose 50; TLR3, Toll-Like Receptor 3; TNF-α, Tumor Necrosis Factor Alpha; Declarations CRediT Authorship Contribution Statement Yan Zhi: Investigation, Writing – original draft, Visualization. Zhenyi Liu: Investigation, Data curation, Writing – original draft, Visualization. Guoyu Shen: Investigation, Data curation, Formal analysis. Ying Liu: Data curation, Formal analysis, Visualization. Tao Zhang: Supervision, Project administration. Yan Wu: Supervision, Project administration. Ge Hu: Conceptualization, Supervision, Project administration, Funding acquisition. Xiangdong Wang: Conceptualization, Supervision, Project administration, Funding acquisition. Conflict of interest The authors declare that they have no competing interests. Acknowledgments This study was supported by the Beijing Nova Program (No. 20220484226, China), the National Natural Science Foundation of China (No. 32273050, China) References Audry M, Ciancanelli M, Yang K, Cobat A, Chang HH, Sancho-Shimizu V et al. 2011. NEMO is a key component of NF-κB- and IRF-3-dependent TLR3-mediated immunity to herpes simplex virus. J Allergy Clin Immunol. 128, 610-7.e1-4. Bi W, Tian M, Row KH. Selective extraction and separation of oxymatrine from Sophora flavescens Ait. extract by silica-confined ionic liquid. J Chromatogr B Analyt Technol Biomed Life Sci. 2012;880:108–13. Cao G, Mao Z, Niu T, Wang P, Yue X, Wang X, et al. 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Inhibitory effect of oxymatrine on serum hepatitis B virus DNA in HBV transgenic mice. World J Gastroenterol. 2004;10:1176–9. Meng S, Xia F, Xu J, Zhang X, Xue M, Gu M, et al. Hepatocyte growth factor protects pulmonary endothelial barrier against oxidative stress and mitochondria-dependent apoptosis. Chin Med J (Engl). 2022;135:837–48. Mostafa A, Mahmoud SH, Shehata M, Müller C, Kandeil A, El-Shesheny R et al. 2020. PA from a Recent H9N2 (G1-Like) Avian Influenza a Virus (AIV) Strain Carrying Lysine 367 Confers Altered Replication Efficiency and Pathogenicity to Contemporaneous H5N1 in Mammalian Systems. Viruses. 12. Nang NT, Lee JS, Song BM, Kang YM, Kim HS, Seo SH. Induction of inflammatory cytokines and Toll-like receptors in chickens infected with avian H9N2 influenza virus. Vet Res. 2011;42:64. Nasirudeen AM, Wong HH, Thien P, Xu S, Lam KP, Liu DX. RIG-I, MDA5 and TLR3 synergistically play an important role in restriction of dengue virus infection. PLoS Negl Trop Dis. 2011;5:e926. Ocaña-Macchi M, Bel M, Guzylack-Piriou L, Ruggli N, Liniger M, Mccullough KC, et al. Hemagglutinin-dependent tropism of H5N1 avian influenza virus for human endothelial cells. J Virol. 2009;83:12947–55. Pillai PS, Molony RD, Martinod K, Dong H, Pang IK, Tal MC, et al. Mx1 reveals innate pathways to antiviral resistance and lethal influenza disease. Science. 2016;352:463–6. Ramakrishnan MA. Determination of 50% endpoint titer using a simple formula. World J Virol. 2016;5:85–6. Sang X, Wang R, Han Y, Zhang C, Shen H, Yang Z, et al. T cell–associated immunoregulation and antiviral effect of oxymatrine in hydrodynamic injection HBV mouse model. Acta Pharm Sin B. 2017;7:311–8. Starick E, Römer-Oberdörfer A, Werner O. Type- and subtype-specific RT-PCR assays for avian influenza A viruses (AIV). J Vet Med B Infect Dis Vet Public Health. 2000;47:295–301. Sun W, Wu W, Jiang N, Ge X, Zhang Y, Han J et al. 2022. Highly Pathogenic PRRSV-Infected Alveolar Macrophages Impair the Function of Pulmonary Microvascular Endothelial Cells. Viruses. 14. Teijaro JR, Walsh KB, Cahalan S, Fremgen DM, Roberts E, Scott F, et al. Endothelial cells are central orchestrators of cytokine amplification during influenza virus infection. Cell. 2011;146:980–91. Van De Sand L, Bormann M, Schmitz Y, Heilingloh CS, Witzke O, Krawczyk A. 2021. Antiviral Active Compounds Derived from Natural Sources against Herpes Simplex Viruses. Viruses 13. Wang D, Zhu W, Yang L, Shu Y. 2021. The Epidemiology, Virology, and Pathogenicity of Human Infections with Avian Influenza Viruses. Cold Spring Harb Perspect Med. 11. Wang S, Liang T, Luo Q, Li P, Zhang R, Xu M, et al. H9N2 swine influenza virus infection-induced damage is mediated by TRPM2 channels in mouse pulmonary microvascular endothelial cells. Microb Pathog. 2020;148:104408. Wei K, Li Y. Global genetic variation and transmission dynamics of H9N2 avian influenza virus. Transbound Emerg Dis. 2018;65:504–17. Xu RH, Wong EB, Rubio D, Roscoe F, Ma X, Nair S, et al. Sequential Activation of Two Pathogen-Sensing Pathways Required for Type I Interferon Expression and Resistance to an Acute DNA Virus Infection. Immunity. 2015;43:1148–59. Yao M, Lv J, Huang R, Yang Y, Chai T. Determination of infective dose of H9N2 Avian Influenza virus in different routes: aerosol, intranasal, and gastrointestinal. Intervirology. 2014;57:369–74. Zhang FL, Yang L, He WH, Xie LJ, Yang F, Wang YH et al. 2023a. In vivo antibacterial activity of medicinal plant Sophora flavescens against Streptococcus agalactiae infection. J Fish Dis 46, 977–86. Zhang J, Ye H, Liu Y, Liao M, Qi W. Resurgence of H5N6 avian influenza virus in 2021 poses new threat to public health. Lancet Microbe. 2022;3:e558. Zhang N, Quan K, Chen Z, Hu Q, Nie M, Xu N, et al. The emergence of new antigen branches of H9N2 avian influenza virus in China due to antigenic drift on hemagglutinin through antibody escape at immunodominant sites. Emerg Microbes Infect. 2023b;12:2246582. Zhang Y, Wang R, Shi W, Zheng Z, Wang X, Li C, et al. Antiviral effect of fufang yinhua jiedu (FFYH) granules against influenza A virus through regulating the inflammatory responses by TLR7/MyD88 signaling pathway. J Ethnopharmacol. 2021;275:114063. Zuo W, Wakimoto M, Kozaiwa N, Shirasaka Y, Oh SW, Fujiwara S, et al. PKR and TLR3 trigger distinct signals that coordinate the induction of antiviral apoptosis. Cell Death Dis. 2022;13:707. Supplementary Files Supplementary.docx floatimage1.jpeg Oxymatrine (OMT), a traditional Chinese medicine derivative, exhibits promising antiviral effects against H9N2 Avian Influenza by modulating key cellular pathways and cytokine expressions in PMVECs. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3846667","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267555941,"identity":"ef6589f6-774a-4ea8-8441-679a28161e3e","order_by":0,"name":"Yan Zhi","email":"","orcid":"","institution":"Beijing University of Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zhi","suffix":""},{"id":267555942,"identity":"639f4479-8ce8-4d66-8258-5cf1378a46ef","order_by":1,"name":"Zhenyi Liu","email":"","orcid":"","institution":"Beijing University of Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Zhenyi","middleName":"","lastName":"Liu","suffix":""},{"id":267555943,"identity":"20b7b4ad-42d9-45c9-87fc-3cad06238005","order_by":2,"name":"Guo Shen","email":"","orcid":"","institution":"Beijing University of Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Guo","middleName":"","lastName":"Shen","suffix":""},{"id":267555944,"identity":"c72577bb-2dba-4e77-9398-2aa00f7f51c0","order_by":3,"name":"Xiang Wang","email":"","orcid":"","institution":"Beijing Tongren Hospital Otolaryngology and Head and Neck Surgery Center: Beijing Tongren Hospital CMU","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Wang","suffix":""},{"id":267555945,"identity":"be3a5b80-49d4-4941-b337-8c659bc9b32a","order_by":4,"name":"Ying Liu","email":"","orcid":"","institution":"Beijing Academy of Agriculture and Forestry Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Liu","suffix":""},{"id":267555946,"identity":"d9c9f0d0-7593-4070-827b-b26cef02cff7","order_by":5,"name":"TAO Zhang","email":"","orcid":"","institution":"Beijing University of Agriculture","correspondingAuthor":false,"prefix":"","firstName":"TAO","middleName":"","lastName":"Zhang","suffix":""},{"id":267555947,"identity":"eb4ce84f-f6f5-4ceb-acb8-2af42d36e462","order_by":6,"name":"Ge Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYBACAwYeEGXDw8/eQJqWNBnJngOkaTlsY3DDgUgt5tK9xyS/VJznYbjBwPjhYw4RWiznnEuTljlzm4dxdgOz5MxtxDjsRo6ZtGTbbR5mmQNszLzEa/l3jodNIoEELZIfGw7w8BCtxXJGjrE1w7FkHgmeg83E+cVcIsfw5o8aO3v7480HP3wkRgsIMIOjhoGxgUj1ILU/iFc7CkbBKBgFIxEAAGLKMnxpspuGAAAAAElFTkSuQmCC","orcid":"","institution":"Beijing University of Agriculture","correspondingAuthor":true,"prefix":"","firstName":"Ge","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2024-01-09 00:01:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3846667/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3846667/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49833910,"identity":"5aef048a-f072-43c9-ab4f-96c222119078","added_by":"auto","created_at":"2024-01-18 17:53:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":177891,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChemical structure of Oxymatrine (OMT) and Morphological Observation of PMVECs Pre and Post-Purification with CD31 Immunofluorescence Identification.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Chemical structure of Oxymatrine (OMT).\u003c/p\u003e\n\u003cp\u003e(B) Growth state of primary isolated PMVECs at 60 hours prior to purification, observed under phase-contrast microscopy. Scale bar = 100 μm\u003c/p\u003e\n\u003cp\u003e(C-D) Morphological observation of PMVECs post-purification under phase-contrast microscopy at 200x (C) and 400x (D) magnification, showcasing the growth state and cell morphology. Scale bar = 25 μm and 50 μm.\u003c/p\u003e\n\u003cp\u003e(E-F) Immunofluorescence identification of CD31 antigen in PMVECs. Merged images at 200x (E) and 400x (F) magnification depict CD31 expression with red staining alongside nuclei with blue staining by DAPI. The prominent CD31 expression alongside the cellular morphology confirms the endothelial characteristic of PMVECs, validating their suitability for subsequent experiments. Scale bar =50 μm and 25 μm.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/7d8adcc71c8c605692038912.jpg"},{"id":49833913,"identity":"d8b3a769-2c40-4a33-bf96-3a9a0014172d","added_by":"auto","created_at":"2024-01-18 17:53:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114160,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCell Viability in PMVECs Following OMT Exposure Over Various Time Intervals.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-D) This bar graph illustrates the impact of varying concentrations of OMT on the viability of PMVECs across four distinct time intervals: 12h (A), 24h (B), 36h (C), and 48h (D). The cell viability post-OMT exposure was quantitatively evaluated using the CCK-8 assay.\u003c/p\u003e\n\u003cp\u003eExperiments were performed in triplicate, and the mean ± S.D. (n = 3) is shown. \u003cem\u003eP\u003c/em\u003e values were determined by non-parametric one-way ANOVA.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/fea976723a72b02bb8a67e96.jpg"},{"id":49834242,"identity":"d1e17bcb-3566-482c-be64-5e30ac74277c","added_by":"auto","created_at":"2024-01-18 18:01:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":78225,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlteration of Antiviral Protein mRNA Levels in PMVECs Following H9N2 AIV Infection and OMT Treatment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) The mRNA expression levels of antiviral proteins PKR (A) and Mx1 (B) in PMVECs post H9N2 AIV infection and subsequent OMT treatment at various dosages.\u003c/p\u003e\n\u003cp\u003eExperiments were performed in triplicate, and the mean ± S.D. (n = 3) is shown. \u003cem\u003eP \u003c/em\u003evalues were determined by non-parametric one-way ANOVA.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/cceaded570941a51adcb8dd1.jpg"},{"id":49833912,"identity":"108cb89b-eeeb-4078-bf4b-b172c597365e","added_by":"auto","created_at":"2024-01-18 17:53:57","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":397781,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCytokine Level Changes in PMVECs Following H9N2 AIV Infection and OMT Treatment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-D) Variations in levels of IFN-\u003cem\u003eα\u003c/em\u003e (A), IFN-\u003cem\u003eβ\u003c/em\u003e (B), IL-6 (C), and TNF-\u003cem\u003eα\u003c/em\u003e (D) across different treatment groups over time.\u003c/p\u003e\n\u003cp\u003eExperiments were performed in triplicate, and the mean ± S.D. (n = 3) is shown. \u003cem\u003eP\u003c/em\u003e values were determined by non-parametric one-way ANOVA.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/323578009cbf7745891fd5a1.jpg"},{"id":49833915,"identity":"8a8b8b91-3206-4923-aaa5-d3ed0121a7f1","added_by":"auto","created_at":"2024-01-18 17:53:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":350422,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOMT Modulates NF-κB, IRF-3, and TLR3 Expression in H9N2 AIV-Infected PMVECs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-C) Relative mRNA expression levels of NF-κB (A), IRF-3 (B), and TLR3 (C) across different treatment groups over time.\u003c/p\u003e\n\u003cp\u003e(D-F) Relative protein expression levels of NF-κB (D), IRF-3 (E), and TLR3 (F) across different treatment groups over time.\u003c/p\u003e\n\u003cp\u003e(H-J) Corresponding Western Blot bands for NF-κB (G), IRF-3 (H), and TLR3 (I) proteins.\u003c/p\u003e\n\u003cp\u003eExperiments were performed in triplicate, and the mean ± S.D. (n = 3) is shown. \u003cem\u003eP\u003c/em\u003e values were determined by non-parametric one-way ANOVA.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/7dfbaa0da94f997e24692424.jpg"},{"id":49834243,"identity":"c5a8d9e1-bec1-457f-b624-86c889cfc454","added_by":"auto","created_at":"2024-01-18 18:01:57","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":246814,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOMT's Impact on NF-κB and IRF-3 Expression Following TLR3 Silencing and H9N2 AIV Infection.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) Relative mRNA expression levels of NF-κB (A) and IRF-3 (B) across different treatment groups over time.\u003c/p\u003e\n\u003cp\u003e(C-D) Relative protein expression levels of NF-κB (C) and IRF-3 (D) across different treatment groups over time.\u003c/p\u003e\n\u003cp\u003e(E-F) Corresponding Western Blot bands for NF-κB (E) and IRF-3 (F) proteins.\u003c/p\u003e\n\u003cp\u003eExperiments were performed in triplicate, and the mean ± S.D. (n = 3) is shown. \u003cem\u003eP\u003c/em\u003e values were determined by non-parametric one-way ANOVA.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/5065025bdf8dbf25eb9d2d6a.jpg"},{"id":50624069,"identity":"a6017720-72ce-4a7e-8917-cd8de606d3e7","added_by":"auto","created_at":"2024-02-04 14:12:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1343269,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/ddcd4f89-20ec-4264-8628-06ac97b7dee4.pdf"},{"id":49833916,"identity":"27dbf33e-df3b-4a11-aac1-c69f056a66b1","added_by":"auto","created_at":"2024-01-18 17:53:57","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":575114,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/110d840a16fb3b81498da19f.docx"},{"id":49833917,"identity":"c1311bc4-cc79-4f15-a554-b423911610d5","added_by":"auto","created_at":"2024-01-18 17:53:57","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":78123,"visible":true,"origin":"","legend":"\u003cp\u003eOxymatrine (OMT), a traditional Chinese medicine derivative, exhibits promising antiviral effects against H9N2 Avian Influenza by modulating key cellular pathways and cytokine expressions in PMVECs.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3846667/v1/0aa6bc40bf361974d03d0d05.jpeg"}],"financialInterests":"","formattedTitle":"Oxymatrine Modulation of TLR3 Signaling Pathway: A Dual-Action Mechanism against H9N2 Avian Influenza Virus and Immune Regulation","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eInfluenza viruses are categorized into three types: A, B, and C, based on variations in their nucleoproteins and M proteins (Starick et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Among these, Type A's H9N2 avian influenza has garnered attention due to its prevalence in poultry, driven by its robust mutagenic and gene recombination capabilities (Liu et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Wei and Li, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although deemed low in pathogenicity, H9N2's rampant transmission in poultry inflicts significant economic losses and poses a direct threat to human health (Wang et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Zhang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Primarily infecting the respiratory tracts of avian species (Yao et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), H9N2 triggers severe inflammatory responses and immune imbalances, potentially leading to fatal outcomes. While vaccination remains the primary preventive strategy, antigenic variation of the virus and vaccine immune escape pose increasing challenges (Zhang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e, de Vries et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe inflammatory response to avian influenza virus infection arises from a dynamic interplay between the virus and the host's immune system, with Toll-like receptor 3 (TLR3) as a pivotal player (Huo et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Past research indicates that avian influenza infection elevates the expression of TLR3 and IFN-\u003cem\u003eβ\u003c/em\u003e in the lungs and brains of chicks, underscoring the significance of TLR3 in immune responses against avian influenza (Nang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe H9N2 virus can infect Pulmonary Microvascular Endothelial Cells (PMVECs), crucial for forming the vascular barrier and modulating immune responses (Teijaro et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Upon viral entry into PMVECs, an array of receptors is activated through specific recognition of pathogen-associated molecular patterns (PAMPs) (Sun et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), with TLR3 emerging as the primary pattern recognition receptor for dsRNA detection. This activation propels a cascade of signaling events, inducing Type I interferons and inflammatory cytokines, thereby kick-starting the innate immune response (Edelmann et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, Nasirudeen et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTraditional Chinese Medicine (TCMs) holds promise in antiviral strategy development due to its mild nature and low likelihood of inducing drug resistance. Oxymatrine (OMT), an active monomer extracted from various TCMs including Sophora flavescens Ait and Radix Sophorae Tonkinensis (Bi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Liang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), has demonstrated efficacy in managing chronic hepatitis B (Lu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Besides its hepatoprotective role, OMT exhibits potential against tumorigenesis, inflammation, and bacterial infections (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Cao et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Zhang et al., 2023a). Notably, in Hepatitis B virus (HBV) transgenic mice liver (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), OMT reduces levels of HBsAg and HBcAg, and as a potent immunosuppressant, it curtails replication and inflammation of type A influenza virus via the TLR4, p38 MAPK, and NF-κB pathways (Dai et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Despite these diverse bioactivities, the role of OMT against avian influenza and its interaction with the TLR3 signaling pathway largely remain unknown.\u003c/p\u003e \u003cp\u003eGiven this background, this study endeavors to examine whether OMT mediates its antiviral effect against the H9N2 subtype of avian influenza virus via the TLR3 signaling pathway. We employed primary PMVECs from rats as the experimental model. Utilizing RNAi technology for validation, this investigation aims to shed light on OMT's role in countering H9N2 AIV, thereby offering novel strategies and a theoretical foundation for avian influenza treatment. Simultaneously, this study seeks to underline the untapped potential of TCMs in antiviral therapeutics.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Cell Lines and Viruses\u003c/h2\u003e \u003cp\u003eThe primary cell lines utilized in this study were Madin Darby Canine Kidney cells (MDCKs) and Pulmonary Microvascular Endothelial Cells (PMVECs).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMDCK Cells\u003c/b\u003e: MDCKs, preserved in our laboratory, were cultured in Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium (DMEM; BioWhittaker, Walkersville, MD, USA) supplemented with 10% fetal bovine serum (FBS; Gibco-BRL, New York, USA) and 2% penicillin/streptomycin antibiotic/antimycotic mixture (GIBCO-BRL, New York, USA).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePMVEC Cells\u003c/b\u003e: PMVECs, isolated from 7\u0026ndash;9 day-old rats using the tissue block explant method (Oca\u0026ntilde;a-Macchi et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), were supplemented with 15 \u0026micro;g/ml Endothelial Cell Growth Supplement (ECGS; Millipore, Billerica, USA) in DMEM during the isolation process. Like MDCKs, PMVECs were also cultured in DMEM supplemented with 10% FBS and 2% penicillin/streptomycin.\u003c/p\u003e \u003cp\u003eBoth cell lines were maintained at 37℃ in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eViruses\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eThe low pathogenicity avian influenza virus (LPAIV) H9N2 subtype, with GenBank accession numbers FJ499463-FJ499470, was obtained from the laboratory of the China Agricultural University. These viruses were propagated in either MDCKs, PMVECs, or 11-day-old specific pathogen-free (SPF) embryonated chicken eggs, as previously described (Mostafa et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Wang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. siRNA-mediated TLR3 Silencing in PMVECs\u003c/h2\u003e \u003cp\u003eTLR3 silencing in PMVECs was performed using siRNA sequences synthesized by Beijing Qinkai Biotechnology Co. Ltd. Specific siRNA sequences targeting the TLR3 gene were derived from the NCBI database. Their specificity was confirmed by BLAST analysis in NCBI, ensuring a match solely with the rat TLR3 gene and ensuring no off-target effects on other genes (Table S1). Safety concentration screenings for both siRNA and transfection reagent were conducted prior to transfection (Fig. S1). Optimal siRNA candidates were selected based on time-course, concentration evaluations, and sequence efficacy (Fig. S2). Transfection into PMVECs was carried out using the identified optimal conditions, aiming for a target interference effect of 60%-70% (Kleinman et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. OMT Characterization and Cytotoxicity Assessment\u003c/h2\u003e \u003cp\u003eOMT, an established bioactive monomer (Bi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Liang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), was sourced from Shanghai Yuan-ye Biotechnology Co., Ltd., with its chemical structure illustrated in (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCell Seeding\u003c/b\u003e: PMVECs were seeded in a 96-well polypropylene plate at a density of 1\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells/ml with 100 \u0026micro;L/well and incubated at 37\u0026deg;C in a 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere.\u003c/p\u003e \u003cp\u003e \u003cb\u003eOMT Treatment\u003c/b\u003e: At 80% confluence, cells were treated with OMT concentrations (2.5, 5, 10 \u0026micro;g/ml) in phenol-red free DMEM with DMSO as a solvent, ensuring a consistent and non-toxic DMSO concentration. Each concentration was replicated in six wells, and control wells received only DMSO in DMEM. To minimize the impact of edge evaporation on the experiment, the perimeter wells of the plate were filled with PBS.\u003c/p\u003e \u003cp\u003e \u003cb\u003eViability Assessment\u003c/b\u003e: Post-OMT treatment over 12, 24, 36, and 48 h intervals, cells were washed with 200 \u0026micro;L PBS. Then, 10 \u0026micro;L of CCK-8 reagent (Beijing Solar-bio Science \u0026amp; Technology Co., Ltd.) was added to each well, followed by a 2\u0026ndash;4 h incubation to allow for formazan crystal formation. Absorbance was measured at 450 nm, with a reference wavelength of 600\u0026ndash;650 nm.\u003c/p\u003e \u003cp\u003eCell viability was calculated as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$Cell Viability\\left(\\%\\right)=\\frac{Absorbance \\text{o}\\text{f} control sample}{Absorbance of \\text{t}\\text{e}\\text{s}\\text{t} sample}\\times 100\\%$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Determination of H9N2 TCID\u003csub\u003e50\u003c/sub\u003e\u003c/h2\u003e \u003cp\u003eThe viral titers infecting 50% of MDCKs were quantified using the Reed and Muench method (Ramakrishnan, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). MDCKs were adjusted to a density of 1\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells/ml, plated in a 96-well format, and cultivated at 37\u0026deg;C under 5% CO\u003csub\u003e2\u003c/sub\u003e until approximately 80% confluence, followed by a brief PBS wash.\u003c/p\u003e \u003cp\u003eH9N2 AIV was serially diluted ten-fold, spanning concentrations from 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;10\u003c/sup\u003e, and introduced to the monolayers of MDCKs. After a 1h adsorption at 37\u0026deg;C in 5% CO\u003csub\u003e2\u003c/sub\u003e, the inoculum was replaced with 2% DMEM maintenance medium. Over a 72 h period, wells displaying more than 70% Cytopathic Effect (CPE) were denoted as positive.\u003c/p\u003e \u003cp\u003eSeparately, PMVECs grown to over 90% confluence in 6-well plates were infected with doses of 1x TCID\u003csub\u003e50\u003c/sub\u003e, 50x TCID\u003csub\u003e50\u003c/sub\u003e, and 100x TCID\u003csub\u003e50\u003c/sub\u003e. The optimal infectious dose was ascertained through CPE analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Experimental Grouping and Treatment Methods\u003c/h2\u003e \u003cp\u003e \u003cb\u003eInvestigation of OMT's Effect on Cytokine Expression\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAim\u003c/b\u003e: To assess the influence of OMT on the expression levels of cytokines and key signaling pathways (TLR3, NF-κB, and IRF-3) in PMVECs following H9N2 AIV infection.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExperimental Groups\u003c/b\u003e:Control group (uninfected), H9N2 AIV-infected group, H9N2 AIV-infected groups with OMT at low, medium, and high concentrations (2.5, 5, and 10 \u0026micro;g/ml, respectively).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling Time Points\u003c/b\u003e: Samples were collected at four distinct intervals: 12, 24, 36, and 48 h post-infection. Each time point consisted of triplicate samples.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssessment of OMT's Role in TLR3-Silenced PMVECs\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAim\u003c/b\u003e: To evaluate how OMT affects PMVECs infected with H9N2 AIV when TLR3 protein is silenced.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExperimental Groups\u003c/b\u003e: H9N2 AIV-infected control group, TLR3 RNAi\u0026thinsp;+\u0026thinsp;H9N2 AIV-infected group, H9N2 AIV-infected group with medium-dose OMT (5 \u0026micro;g/ml), two different types of TLR3 RNAi\u0026thinsp;+\u0026thinsp;H9N2 AIV-infected group with medium-dose OMT.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling Time Points\u003c/b\u003e: Similar to the previous setup, samples were collected at 12, 24, 36, and 48 h intervals, each with triplicate samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. ELISA Determination of Cytokine Levels\u003c/h2\u003e \u003cp\u003eSamples acquired from the previous steps were analyzed via ELISA to quantify the levels of cytokines IFN-\u003cem\u003eβ\u003c/em\u003e, IFN-\u003cem\u003eα\u003c/em\u003e, IL-6, and TNF-\u003cem\u003eα\u003c/em\u003e. Commercial ELISA kits from ABclonal (Wuhan, China) were utilized, following the manufacturer\u0026rsquo;s instructions strictly. The homogenized samples were centrifuged at 1000 rpm for 10 min at 4℃. The supernatant was then carefully collected, and the optical density (OD) was determined at a wavelength of 450 nm using a TECAN F50 spectrophotometer (Mannedorf, Switzerland).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. RNA Extraction and Real-Time Quantitative PCR\u003c/h2\u003e \u003cp\u003eRNA was isolated from PMVECs using the TransZol Up kit (Takara, Dalian, China). The extracted RNA was immediately reverse transcribed to cDNA and stored at -80\u0026deg;C.\u003c/p\u003e \u003cp\u003eFor RT-qPCR, we employed the 2 \u0026times; Hieff UNICON\u0026reg; Universal Blue qPCR Master Mix (Yeasen, Shanghai, China). The amplification protocol included UDG activation at 50\u0026deg;C for 2 min, initial denaturation at 95\u0026deg;C for 2 min, followed by 40 cycles of 95\u0026deg;C for 15 s and 60\u0026deg;C for 30 s. A subsequent melting curve analysis was conducted. Each sample was analyzed in triplicate. The β-actin rRNA served as the endogenous control as previously described (Meng et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Gene expression fold changes were calculated using the 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method. Detailed genes and primer sequences for qRT-PCR are listed in Table S2. Data were analyzed utilizing GraphPad Prism 8.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Western Blot Analysis for Protein Expression in PMVECs\u003c/h2\u003e \u003cp\u003eFor Western blot analysis, PMVECs were seeded in 6-well plates at a density of 1\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/ml and cultured until 80\u0026ndash;90% confluence. Cells were then exposed to H9N2 AIV for 1 h at 37\u0026deg;C, with control groups receiving 2% maintenance medium. Following infection, cells were treated with OMT concentrations of 2.5, 5, or 10 \u0026micro;g/ml. Proteins were harvested at 12, 24, 36, and 48 h post-infection by washing the cells with pre-cooled PBS and lysing them in cold RIPA:PMSF buffer (100:1) for 20\u0026ndash;30 min. Lysates were centrifuged at 12,000 rpm for 20 mins at 4\u0026deg;C, and the supernatants were stored for further analysis.\u003c/p\u003e \u003cp\u003eProtein concentrations were quantified employing the BCA assay (Beyotime, Shanghai, China). Samples were then resolved on 15% SDS-PAGE and transferred to membranes at 100 V for 2 h. For immunoblotting, membranes were blocked and then incubated overnight at 4\u0026deg;C with primary antibodies from Jiangsu Qinke Biotechnology Research Center, China, including TLR3 (Catalog No. DF6415), NF-κB p65 (Catalog No. AF5006), and IRF3 (Catalog No. DF6895). Additionally, β-actin (Catalog No. 20536-1-AP) and GAPDH (Catalog No. 10494-1-AP) antibodies were used, both sourced from Wuhan Sanying Biotechnology, China. This was followed by a 90 min incubation with appropriate secondary antibodies. Protein bands were visualized using the Odyssey infrared imaging system (LI-COR Biosciences, Lincoln, NE, USA) and quantified relative to β-actin or GAPDH using ImageJ software (version 1.51j8, National Institutes of Health, Bethesda, MD, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Statistical Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using GraphPad Prism (Version 8.0, San Diego, USA) and are shown as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. An unpaired Student\u0026rsquo;s t-test assessed differences between two groups, while a one-way ANOVA was employed for multiple group comparisons. For RT-qPCR, relative quantification (2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e) was applied. Western blot band intensities were quantified using ImageJ.\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Observation and Immunofluorescent Identification of PMVECs\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eCellular Observation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMorphological changes in the primary isolated PMVECs were monitored over time. Migration from the tissue block periphery commenced around 6 h post-culture initiation (Fig. S3A), escalating with time (Fig. S3B-D). By 60 h, significant cell density was achieved, facilitating tissue block removal (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). Predominantly, cells exhibited a cobblestone morphology with an interlocked arrangement, albeit some hematopoietic cells were also discerned. Post-media change, cells continued to proliferate, transitioning to a spindled morphology with increasing passage number (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC and D).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eImmunofluorescence Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eImmunofluorescence staining revealed pronounced CD31 expression, a hallmark endothelial marker. Nuclei were stained blue with DAPI, while CD31 exhibited red fluorescence (Fig. S4). Merged images corroborated that the majority of cells were PMVECs (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE and F), validating their aptness for ensuing experiments.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. H9N2 AIV Infectivity in PMVECs via TCID\u003csub\u003e50\u003c/sub\u003e Assay\u003c/h2\u003e\n \u003cp\u003eTo determine H9N2 AIV infectivity in PMVECs, the virus was initially propagated in MDCKs through gradient dilutions. Daily observations disclosed pathological alterations in PMVECs attributable to viral infection. The calculated TCID\u003csub\u003e50\u003c/sub\u003e of H9N2 AIV was 10\u003csup\u003e\u0026minus;\u0026thinsp;4.8\u003c/sup\u003e/0.1ml based on the Reed-Muench method. A starting dilution of 10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e yielded a virus titer of 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e/ml in PMVECs (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTCID\u003csub\u003e50\u003c/sub\u003e determination results of H9N2 AIV\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVirus Dilution\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eObserved CPE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCumulative CPE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInfection Rate (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWell Count\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCPE Positive Wells\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCPE Negative Wells\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCumulative CPE Positive Wells\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCumulative CPE Negative Wells\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProportion of CPE Positive Wells\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCPE Positive Rate (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33/33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25/25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17/17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11/13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eNote: CPE\u0026thinsp;=\u0026thinsp;Cytopathic Effect\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Cytotoxic Effects of OMT on PMVECs Assessed by CCK-8 Assay\u003c/h2\u003e\n \u003cp\u003eThe impact of varying OMT concentrations on PMVECs was explored across distinct time intervals: 12 h, 24 h, 36 h, and 48 h. Cell viability post-OMT exposure was assessed using the CCK-8 assay (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). OMT concentrations exceeding 12.5 \u0026micro;g/ml significantly decreased cell viability (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Additionally, a narrow concentration gradient was screened for drug dosing (Fig. S5, Table S3). Subsequent studies utilized OMT at 2.5 \u0026micro;g/ml, 5 \u0026micro;g/ml, and 10 \u0026micro;g/ml.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eImpact of various OMT concentrations on PMVECs survival rate\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOMT Concentration\u003c/p\u003e\n \u003cp\u003e(\u0026micro;g/ml)\u003c/p\u003e\n \u003cp\u003eSurvival\u003c/p\u003e\n \u003cp\u003eRate (%)\u003c/p\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3.125\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6.25\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. OMT\u0026apos;s Influence on Antiviral Protein Expression in H9N2 AIV-Infected PMVECs\u003c/h2\u003e\n \u003cp\u003eThe antiviral capacity of OMT in PMVECs infected with H9N2 AIV was investigated by assessing the modulation of antiviral proteins PKR and Mx1 at mRNA expression levels via RT-qPCR. Following H9N2 AIV infection, a surge in PKR and Mx1 mRNA expressions was noted in PMVECs. OMT treatment exhibited dose-dependent dynamics: low-dose OMT enhanced PKR mRNA levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while medium-dose and high-dose progressively diminished them (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA). Mx1 mRNA levels increased with low and medium OMT doses (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), yet high-dose led to suppression. By 48 h, all OMT concentrations resulted in reduced Mx1 mRNA levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), denoting both time and dose dependencies (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.5 Regulatory Effects of OMT on the Expression Levels of IFN-\u003c/strong\u003e \u003cstrong\u003e\u0026alpha;\u003c/strong\u003e, \u003cstrong\u003eIFN-\u003c/strong\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e, \u003cstrong\u003eIL-6, and TNF-\u003c/strong\u003e\u003cstrong\u003e\u0026alpha;\u003c/strong\u003e \u003cstrong\u003ein PMVECs Infected with H9N2 AIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eFollowing H9N2 AIV infection and subsequent OMT treatment at varying doses, significant alterations in key cytokine levels within PMVECs were observed. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA, within 12 and 24 h post-treatment, both the virus and high-dose OMT groups demonstrated significant elevations in IFN-\u003cem\u003e\u0026alpha;\u003c/em\u003e levels compared to the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, the low-dose OMT group exhibited a substantial reduction in IFN-\u003cem\u003e\u0026alpha;\u003c/em\u003e levels relative to the virus group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005). For IFN-\u003cem\u003e\u0026beta;\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB), the 24 and 36 h post-treatment were particularly illuminating: both medium-dose and high-dose OMT groups not only surpassed the control group but also outperformed the virus group in terms of elevated IFN-\u003cem\u003e\u0026beta;\u003c/em\u003e levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Across all examined time points, IL-6 levels in all OMT treatment groups were significantly lower than those in the virus group (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC), a trend most pronounced at the 12 h mark (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Regarding TNF-\u003cem\u003e\u0026alpha;\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD), 36 h post-infection witnessed all OMT dosages yielding substantially reduced levels when compared to the virus group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).These effects exhibited both time- and dose-dependent characteristics.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6 Effects of OMT on mRNA and Protein Expression Levels of NF-\u0026kappa;B, IRF-3, and TLR3 in H9N2 AIV-Infected PMVECs\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003ePost H9N2 AIV infection and subsequent OMT treatment, significant alterations in the mRNA and protein expression levels of NF-\u0026kappa;B, IRF-3, and TLR3 were noted, as evaluated through RT-qPCR and Western blot analyses.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003emRNA Expression Changes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eCompared to the control group, both the virus and OMT treatment groups demonstrated elevated mRNA levels of NF-\u0026kappa;B, IRF-3, and TLR3 across various time points (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA-C). Specifically, NF-\u0026kappa;B and IRF-3 mRNA levels were significantly upregulated at 12 and 24 h post-infection in the virus group and low-dose OMT groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). However, medium-dose and high-dose OMT groups exhibited a pronounced reduction in NF-\u0026kappa;B and IRF-3 mRNA levels across all time points (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). For TLR3, the elevation was most prominent at 48 h in the virus and low-dose OMT groups, while medium-dose and high-dose OMT led to a consistent reduction (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProtein Expression Changes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eWestern blot analyses, quantified via ImageJ, unveiled distinct patterns in NF-\u0026kappa;B, IRF-3, and TLR3 protein levels. (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eD-I) Elevated TLR3 and NF-\u0026kappa;B levels were consistently observed at all time points in both the virus group and OMT-treated groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). High-dose OMT treatment led to a significant reduction in TLR3 protein levels at 12 and 36 h (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). NF-\u0026kappa;B protein levels remained consistently elevated in the virus and all OMT-treated groups but were mitigated across all OMT doses (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). IRF-3 levels showcased a marked decrease in the high-dose OMT group at all times compared to the virus group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7 Effects of OMT on mRNA and Protein Expression Levels of NF-\u0026kappa;B and IRF-3 Post-TLR3 Silencing and H9N2 AIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003e\u003cstrong\u003eInfection mRNA Expression Changes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFollowing TLR3 silencing, NF-\u0026kappa;B mRNA levels significantly declined at all time points (12, 24, 36, and 48 h) post H9N2 AIV infection (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). Conversely, medium-dose OMT (5 \u0026micro;g/ml) significantly increased NF-\u0026kappa;B mRNA levels across all time points (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0005). Notably, different types of si-RNA for TLR3 silencing yielded varying effects on NF-\u0026kappa;B mRNA levels at 36 and 48 h (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0005).\u003c/p\u003e\n \u003cp\u003eSimilarly, TLR3 silencing resulted in a significant decrease in IRF-3 mRNA levels at all time points post H9N2 AIV infection (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). Medium-dose OMT treatment post-TLR3 silencing significantly augmented IRF-3 mRNA levels at all time points (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Distinct effects were observed at 12\u0026ndash;48 h depending on the type of si-RNA utilized for TLR3 silencing (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProtein Expression Changes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eWestern blot analysis disclosed reduced NF-\u0026kappa;B protein levels in the TLR3 RNAi\u0026thinsp;+\u0026thinsp;H9N2 AIV infection group across all time points (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eC and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eE; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Medium-dose OMT treatment post-TLR3 silencing led to a significant increase in NF-\u0026kappa;B levels, although this effect was not sustained (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n \u003cp\u003eFor IRF-3 protein, levels significantly declined at all time points post TLR3 silencing (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). However, medium-dose OMT treatment reversed this effect, dependent on the si-RNA type employed for TLR3 silencing (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eD and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eF; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eH9N2 AIV mainly targets the respiratory tracts of animals and humans through PMVECs, which form a vascular barrier and play a pivotal role in immune modulation\u003csup\u003e11\u003c/sup\u003e. Despite the virus's low pathogenicity, its rapid mutation rate and efficient transmission, exacerbated by insufficient preventative measures, have rendered conventional vaccine strategies increasingly less effective (Dong et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Given this challenge, alternative therapeutic approaches are crucial. This prompted our study to comprehensively investigate the potential of OMT, a traditional Chinese medicine component, as a promising antiviral agent against H9N2 AIV. Our findings highlight OMT's dual-action mechanism modulating cellular responses and signaling, serving both antiviral and immune-regulatory functions.\u003c/p\u003e \u003cp\u003eOne of our pivotal findings is the inhibitory effect of OMT on the expression levels of PKR and Mx1 mRNA, both of which are significantly induced upon H9N2 AIV infection, as demonstrated by RT-qPCR analyses. These molecules, PKR and Mx1, are well-documented as crucial players in the antiviral response (Zuo et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Pillai et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The inhibition observed suggests that OMT could be modulating host-virus interactions at the cellular level, possibly through its modulation of the TLR3 signaling pathways, although the exact mechanism remains to be elucidated (Sang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, our study demonstrated that OMT upregulates the expression of Type I interferons (IFN-\u003cem\u003eα\u003c/em\u003e and IFN-\u003cem\u003eβ\u003c/em\u003e), which are key mediators of innate immunity (Chen and Yu, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This modulation of interferon levels by OMT resonates with previous studies on other traditional Chinese medicine components (Lee et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which further strengthens the evidence for the antiviral efficacy of natural compounds (van de Sand et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). OMT's influence on the TLR3 pathway emphasizes its role in immune regulation and its dual-action against H9N2 AIV. However, the precise mechanism by which OMT influences interferon levels remains elusive and warrants further investigation, potentially through more detailed molecular and biochemical analyses.\u003c/p\u003e \u003cp\u003eTLR3 signaling pathways further clarify OMT's effects. Our observations reveal that OMT modulates the expression of NF-κB and IRF-3, which are key downstream components of the TLR3 pathway (Audry et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This modulation indicates that OMT may exert its antiviral effects, at least in part, by altering the TLR3-mediated activation of these transcription factors, thereby potentially dampening excessive inflammatory reactions while bolstering antiviral defenses against H9N2 AIV. These findings align with the pivotal role of TLR3 in viral infections as highlighted in previous research, and suggest that the elucidated involvement of TLR3 signaling in H9N2 AIV infection provides a promising avenue for devising targeted therapeutic strategies (de Carvalho et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It's important to note that signaling pathways are not linear but form intricate networks, with multiple pathways and proteins potentially playing a role in the observed antiviral response. For instance, other pathways such as TLR4, TLR7, and MAPK, along with proteins like TNF-\u003cem\u003eα\u003c/em\u003e, RIG-I, and MITA, could also be implicated in this complex antiviral response (Xu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Liu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These pathways and proteins are not mutually exclusive and may interact either synergistically or antagonistically (Govorkova et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), thereby affecting the overall antiviral activity of OMT. This underscores the necessity for further investigation to unravel the complex signaling networks modulated by OMT and to understand how these modulations contribute to its antiviral efficacy.\u003c/p\u003e \u003cp\u003eOur study shows that silencing TLR3 reduces NF-κB and IRF-3 expression, highlighting TLR3's role in the immune response to H9N2 AIV. Despite the silencing of TLR3, the antiviral activity of OMT persisted, indicating its diverse mechanistic pathways and suggesting its ability to mount a multi-faceted defense against H9N2 AIV. This observation has significant implications. Firstly, it posits that the antiviral efficacy of OMT is not solely dependent on TLR3 signaling, thereby potentially broadening its applicability as an antiviral agent. This could prove particularly valuable in situations where TLR3 signaling is compromised, either due to genetic mutations or other factors. Secondly, it introduces the likelihood that OMT may act through multiple signaling pathways, either in parallel or synergistically, to exert its antiviral effects. This aspect of polypharmacology could potentially offer a more robust and adaptable defense against rapidly mutating viruses like H9N2 AIV.\u003c/p\u003e \u003cp\u003eA key limitation of our study is its primary reliance on \u003cem\u003ein vitro\u003c/em\u003e models. Translating these findings to \u003cem\u003ein vivo\u003c/em\u003e settings is crucial for OMT's antiviral validation. Our preliminary plan encompasses evaluating the antiviral efficacy and safety of OMT against H9N2 AIV in animal models, selecting appropriate models to ensure the clinical relevance of our experimental design. If initial \u003cem\u003ein vivo\u003c/em\u003e studies show promise, our collaboration with clinical teams aims for preliminary clinical trials. Given these considerations, it's also imperative to understand the deeper mechanisms at play. The complex signaling networks suggest a systems biology approach, using computational modeling and experimental validation, to understand the interactions between OMT, TLR3 signaling, and its antiviral activity. Furthermore, delving into the pharmacological properties and pharmacokinetics of OMT will ascertain its optimal dosing and application regimen in humans, addressing challenges such as drug bioavailability, dosage determination, potential side effects, and drug interactions.\u003c/p\u003e \u003cp\u003eIn line with advancing OMT to the clinical evaluation stage, we acknowledge the significance of liaising with relevant regulatory authorities and seeking external funding support to ensure adherence to stipulations and standards for clinical trials. Our aim is to capitalize on the antiviral and immune-regulatory effects of OMT, providing a potential therapeutic avenue to tackle the challenges posed by H9N2 AIV. Through concerted efforts and close collaboration with clinical research teams, we aspire to lay a solid foundation for the clinical application of OMT. The time-consuming nature of this process is acknowledged, yet we are committed to navigating the intricacies involved, propelled by the potential of OMT as a versatile therapeutic agent against H9N2 AIV.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur study elucidates the dual-action mechanism of OMT against H9N2 AIV, showcasing its potential as both an antiviral agent and an immune modulator. This distinction highlights OMT's potential as a versatile therapeutic agent in addressing the challenges posed by H9N2 AIV. Our findings lay a groundwork for further investigations into the clinical potential of OMT. Future endeavors exploring OMT's efficacy in in \u003cem\u003evivo\u003c/em\u003e models and clinical trials are pivotal steps towards harnessing its therapeutic promise against H9N2 AIV and possibly other viral infections.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIV, Avian Influenza Virus; CCK-8, Cell Counting Kit-8; ELISA, Enzyme-Linked Immunosorbent Assay; IFN-\u0026alpha;, Interferon Alpha; IFN-\u0026beta;, Interferon Beta; IL-6, Interleukin 6; IRF-3, Interferon Regulatory Factor 3; Mx1, Myxovirus Resistance 1; NF-\u0026kappa;B, Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOMT, Oxymatrine; PKR, Protein Kinase R; PMVECs, Pulmonary Microvascular Endothelial Cells; RNAi, RNA Interference; RT-qPCR, Reverse Transcription Quantitative Polymerase Chain Reaction; TCID50, Tissue Culture Infectious Dose 50; TLR3, Toll-Like Receptor 3; TNF-\u0026alpha;, Tumor Necrosis Factor Alpha;\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCRediT Authorship Contribution Statement\u003c/h2\u003e \u003cp\u003eYan Zhi: Investigation, Writing \u0026ndash; original draft, Visualization.\u003c/p\u003e \u003cp\u003eZhenyi Liu: Investigation, Data curation, Writing \u0026ndash; original draft, Visualization.\u003c/p\u003e \u003cp\u003eGuoyu Shen: Investigation, Data curation, Formal analysis.\u003c/p\u003e \u003cp\u003eYing Liu: Data curation, Formal analysis, Visualization.\u003c/p\u003e \u003cp\u003eTao Zhang: Supervision, Project administration.\u003c/p\u003e \u003cp\u003eYan Wu: Supervision, Project administration.\u003c/p\u003e \u003cp\u003eGe Hu: Conceptualization, Supervision, Project administration, Funding acquisition.\u003c/p\u003e \u003cp\u003eXiangdong Wang: Conceptualization, Supervision, Project administration, Funding acquisition.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis study was supported by the Beijing Nova Program (No. 20220484226, China), the National Natural Science Foundation of China (No. 32273050, China)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAudry M, Ciancanelli M, Yang K, Cobat A, Chang HH, Sancho-Shimizu V et al. 2011. 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Cell Death Dis. 2022;13:707.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"H9N2 Avian Influenza Virus (AIV), Pulmonary Microvascular Endothelial Cells (PMVECs), Oxymatrine (OMT), Antiviral Mechanisms, TLR3 Signaling Pathways, Cytokine Modulation","lastPublishedDoi":"10.21203/rs.3.rs-3846667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3846667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH9N2 Avian Influenza Virus (AIV) poses a growing public health threat due to its rapid mutation rate and limited vaccine efficacy. Pulmonary Microvascular Endothelial Cells (PMVECs) play a critical role as a gateway for infection, highlighting the need for alternative therapeutic strategies. This study examines the antiviral potential of Oxymatrine (OMT), a traditional Chinese medicine derivative, against H9N2 AIV in PMVECs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aim of this study is to explore the efficacy of OMT in modulating antiviral responses and to elucidate its impact on the TLR3 signaling pathway in PMVECs infected with H9N2 AIV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design and Methods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing an array of in vitro assays such as TCID50, CCK-8, RT-qPCR, ELISA, and Western blot, this study evaluated the viral infectivity, cell viability, gene and protein expression levels, and key cytokine levels in PMVECs. Additionally, RNAi technology was employed to silence TLR3 genes to further understand the mechanisms involved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOMT displayed a dose-dependent inhibitory effect on vital antiviral proteins PKR and Mx1 and modulated the expression of Type I interferons and cytokines including IFN-α, IFN-β, IL-6, and TNF-α. It significantly impacted the TLR3 signaling pathways, affecting downstream components such as NF-κB and IRF-3. TLR3 silencing studies indicated that OMT's antiviral efficacy was not solely dependent on the TLR3 pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings reveal that OMT exhibits a dual-action mechanism by inhibiting H9N2 AIV and modulating immune responses in PMVECs, primarily through the TLR3 signaling pathway. These results lay a promising foundation for the development of OMT as an alternative antiviral therapeutic against H9N2 AIV.\u003c/p\u003e","manuscriptTitle":"Oxymatrine Modulation of TLR3 Signaling Pathway: A Dual-Action Mechanism against H9N2 Avian Influenza Virus and Immune Regulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-18 17:53:52","doi":"10.21203/rs.3.rs-3846667/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c0a61ca0-1c6e-4d8d-b098-23b279c0afce","owner":[],"postedDate":"January 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-04T14:04:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-18 17:53:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3846667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3846667","identity":"rs-3846667","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}