scholarly journals Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

2020 ◽  
Author(s):  
Wang Xiaoqi ◽  
Bin Xin ◽  
Zhijian Xu ◽  
Kenli LI ◽  
Fei Li ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Inflammatory Responses ◽  
Representation Learning ◽  
Mechanisms Of Action ◽  
Network Representation ◽  
Drug Mechanism ◽  
Tnf Α ◽  
Therapeutic Development ◽  
Anti Inflammatory ◽  
Immune Imbalance

<div>Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git</div>

scholarly journals Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

2020 ◽  
Author(s):  
Wang Xiaoqi ◽  
Bin Xin ◽  
Zhijian Xu ◽  
Kenli LI ◽  
Fei Li ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Inflammatory Responses ◽  
Representation Learning ◽  
Mechanisms Of Action ◽  
Network Representation ◽  
Drug Mechanism ◽  
Tnf Α ◽  
Therapeutic Development ◽  
Anti Inflammatory ◽  
Immune Imbalance

<div>Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git</div>

scholarly journals Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

2020 ◽  
Author(s):  
Wang Xiaoqi ◽  
Bin Xin ◽  
Zhijian Xu ◽  
Kenli LI ◽  
Fei Li ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Inflammatory Responses ◽  
Representation Learning ◽  
Mechanisms Of Action ◽  
Network Representation ◽  
Drug Mechanism ◽  
Tnf Α ◽  
Therapeutic Development ◽  
Anti Inflammatory ◽  
Immune Imbalance

<div>Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git</div>

scholarly journals Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

2021 ◽  
Author(s):  
Wang Xiaoqi ◽  
Bin Xin ◽  
Zhijian Xu ◽  
Kenli LI ◽  
Fei Li ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Inflammatory Responses ◽  
Representation Learning ◽  
Binding Modes ◽  
Network Representation ◽  
Drug Mechanism ◽  
Docking Program ◽  
Therapeutic Development ◽  
Anti Inflammatory ◽  
Low Dimensional

<p>Recent studies have been demonstrated that the excessive inflammatory response is an important factor of death in COVID-19 patients. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID-19. This work explores the multi-hub characteristic of a heterogeneous drug network integrating 8 unique networks. Inspired by the multi-hub characteristic, we design three billion special meta paths to train a deep representation model for learning low-dimensional vectors that integrate long-range structure dependency and complex semantic relation among network nodes. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 22 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. Finally, we analyze mechanisms of action based on PubMed publications and ongoing clinical trials, and explore the possible binding modes between the new predicted drugs and targets via docking program. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git.</p>

Comparing the effect of intestinal bacteria from rabbit, pig, and chicken on inflammatory response in cultured rabbit crypt and villus

2019 ◽  
Vol 65 (1) ◽  
pp. 59-67 ◽  
Author(s):  
Hong Xiao Cui ◽  
Xiu Rong Xu
Keyword(s):  
Inflammatory Response ◽  
Inflammatory Responses ◽  
Intestinal Bacteria ◽  
Inflammatory Factors ◽  
Rabbit Ileum ◽  
Necrosis Factor Alpha ◽  
Heat Treated ◽  
Tnf Α ◽  
Factor Alpha ◽  
Anti Inflammatory

Rabbit is susceptible to intestinal infection, which often results in severe inflammatory response. To investigate whether the special community structure of rabbit intestinal bacteria contributes to this susceptibility, we compared the inflammatory responses of isolated rabbit crypt and villus to heat-treated total bacteria in pig, chicken, and rabbit ileal contents. The dominant phylum in pig and chicken ileum was Firmicutes, while Bacteroidetes was dominant in rabbit ileum. The intestinal bacteria from rabbit induced higher expression of toll-like receptor 4 (TLR4) in rabbit crypt and villus (P < 0.05). TLR2 and TLR3 expression was obviously stimulated by chicken and pig intestinal bacteria (P < 0.05) but not by those of rabbit. The ileal bacteria from those three animals all increased the expression of tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) in crypts and villus (P < 0.05). Chicken and pig ileal bacteria also stimulated the expression of anti-inflammatory factors interferon beta (IFN-β) and IL-10 (P < 0.05), while those of rabbit did not (P > 0.05). In conclusion, a higher abundance of Gram-negative bacteria in rabbit ileum did not lead to more expressive pro-inflammatory cytokines in isolated rabbit crypt and villus, but a higher percentage of Lactobacillus in chicken ileum might result in more expressive anti-inflammatory factors.

scholarly journals In Vitro Evaluation of the Anti-Inflammatory Effect of KMUP-1 and in Vivo Analysis of Its Therapeutic Potential in Osteoarthritis

Biomedicines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 615
Author(s):  
Shang-En Huang ◽  
Erna Sulistyowati ◽  
Yu-Ying Chao ◽  
Bin-Nan Wu ◽  
Zen-Kong Dai ◽  
...  
Keyword(s):  
Articular Cartilage ◽  
Inflammatory Responses ◽  
Therapeutic Potential ◽  
Antioxidant Properties ◽  
Serum Levels ◽  
Gene Expressions ◽  
Tnf Α ◽  
Anti Inflammatory

Osteoarthritis is a degenerative arthropathy that is mainly characterized by dysregulation of inflammatory responses. KMUP-1, a derived chemical synthetic of xanthine, has been shown to have anti-inflammatory and antioxidant properties. Here, we aimed to investigate the in vitro anti-inflammatory and in vivo anti-osteoarthritis effects of KMUP-1. Protein and gene expressions of inflammation markers were determined by ELISA, Western blotting and microarray, respectively. RAW264.7 mouse macrophages were cultured and pretreated with KMUP-1 (1, 5, 10 μM). The productions of TNF-α, IL-6, MMP-2 and MMP- 9 were reduced by KMUP-1 pretreatment in LPS-induced inflammation of RAW264.7 cells. The expressions of iNOS, TNF-α, COX-2, MMP-2 and MMP-9 were also inhibited by KMUP-1 pretreatment. The gene expression levels of TNF and COX families were also downregulated. In addition, KMUP-1 suppressed the activations of ERK, JNK and p38 as well as phosphorylation of IκBα/NF-κB signaling pathways. Furthermore, SIRT1 inhibitor attenuated the inhibitory effect of KMUP-1 in LPS-induced NF-κB activation. In vivo study showed that KMUP-1 reduced mechanical hyperalgesia in monoiodoacetic acid (MIA)-induced rats OA. Additionally, KMUP-1 pretreatment reduced the serum levels of TNF-α and IL-6 in MIA-injected rats. Moreover, macroscopic and histological observation showed that KMUP-1 reduced articular cartilage erosion in rats. Our results demonstrated that KMUP-1 inhibited the inflammatory responses and restored SIRT1 in vitro, alleviated joint-related pain and cartilage destruction in vivo. Taken together, KMUP-1 has the potential to improve MIA-induced articular cartilage degradation by inhibiting the levels and expression of inflammatory mediators suggesting that KMUP-1 might be a potential therapeutic agent for OA.

scholarly journals p38/AP-1 Pathway in Lipopolysaccharide-Induced Inflammatory Responses Is Negatively Modulated by Electrical Stimulation

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Deok Jeong ◽  
Jaehwi Lee ◽  
Young-Su Yi ◽  
Yanyan Yang ◽  
Kyoung Won Kim ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Inflammatory Response ◽  
Inflammatory Responses ◽  
Inflammatory Diseases ◽  
Physiological Role ◽  
Peritoneal Macrophages ◽  
Cellular Level ◽  
Transcriptional Level ◽  
Weak Current ◽  
Anti Inflammatory

Electrical stimulation with a weak current has been demonstrated to modulate various cellular and physiological responses, including the differentiation of mesenchymal stem cells and acute or chronic physical pain. Thus, a variety of investigations regarding the physiological role of nano- or microlevel currents at the cellular level are actively proceeding in the field of alternative medicine. In this study, we focused on the anti-inflammatory activity of aluminum-copper patches (ACPs) under macrophage-mediated inflammatory conditions. ACPs generated nanolevel currents ranging from 30 to 55 nA in solution conditions. Interestingly, the nanocurrent-generating aluminum-copper patches (NGACPs) were able to suppress both lipopolysaccharide-(LPS-) and pam3CSK-induced inflammatory responses such as NO and PGE2production in both RAW264.7 cells and peritoneal macrophages at the transcriptional level. Through immunoblotting and immunoprecipitation analyses, we found that p38/AP-1 could be the major inhibitory pathway in the NGACP-mediated anti-inflammatory response. Indeed, inhibition of p38 by SB203580 showed similar inhibitory activity of the production of TNF-αand PGE2and the expression of TNF-αand COX-2 mRNA. These results suggest that ACP-induced nanocurrents alter signal transduction pathways that are involved in the inflammatory response and could therefore be utilized in the treatment of various inflammatory diseases such as arthritis and colitis.

scholarly journals Proinflammatory responses in SARS-CoV-2 infected and soluble spike glycoprotein S1 subunit activated human macrophages

2021 ◽  
Author(s):  
Kim Chiok ◽  
Kevin Hutchison ◽  
Lindsay Grace Miller ◽  
Santanu Bose ◽  
Tanya A Miura
Keyword(s):  
Virus Infection ◽  
Inflammatory Response ◽  
Virus Replication ◽  
Inflammatory Mediators ◽  
Inflammatory Responses ◽  
Activated Macrophages ◽  
Human Macrophages ◽  
Tnf Α ◽  
Proinflammatory Responses

Critically ill COVID-19 patients infected with SARS-CoV-2 display signs of generalized hyperinflammation. Macrophages trigger inflammation to eliminate pathogens and repair tissue, but this process can also lead to hyperinflammation and resulting exaggerated disease. The role of macrophages in dysregulated inflammation during SARS-CoV-2 infection is poorly understood. We used SARS-CoV-2 infected and glycosylated soluble SARS-CoV-2 Spike S1 subunit (S1) treated THP-1 human-derived macrophage-like cell line to clarify the role of macrophages in pro-inflammatory responses. Soluble S1 upregulated TNF-α and CXCL10 mRNAs, and induced secretion of TNF-α from THP-1 macrophages. While THP-1 macrophages did not support productive SARS-CoV-2 replication, virus infection resulted in upregulation of both TNF-α and CXCL10 genes. Our study shows that S1 is a key viral component inducing inflammatory response in macrophages, independently of virus replication. Thus, virus-infected or soluble S1-activated macrophages may become sources of pro-inflammatory mediators contributing to hyperinflammation in COVID-19 patients.

Abstract 553: Siglec-1 (CD169) on Monocytes/Macrophages: A New Receptor For Extracellular Self-RNA in Triggering Inflammatory Responses via the Sheddase TACE/ADAM17

2015 ◽  
Vol 35 (suppl_1) ◽  
Author(s):  
Hector A Cabrera-Fuentes ◽  
Klaus T Preissner ◽  
William A Boisvert
Keyword(s):  
Inflammatory Cytokines ◽  
Inflammatory Responses ◽  
Transmembrane Protein ◽  
Macrophage Polarization ◽  
Extracellular Rna ◽  
Tnf Α ◽  
M1 Phenotype ◽  
Phenotype Markers ◽  
Anti Inflammatory

As an important component of atherosclerosis, monocytes/macrophages respond to external stimuli with rapid changes in their expression of many inflammation-related genes to undergo polarization towards the M1 (pro-inflammatory) or M2 (anti-inflammatory) phenotype. Although sialoadhesin (Sn), also known as SIGLEC-1 or CD169, is a transmembrane protein receptor expressed on monocytes and macrophages whether it has a role in macrophage polarization and ultimately, macrophage-driven atherogenesis, has not been investigated. We have previously shown that, independently of Toll-like receptor signaling, extracellular RNA (eRNA) could exert pro-thrombotic and pro-inflammatory properties in the cardiovascular system by inducing cytokine mobilization. In the current study, recombinant mouse macrophage CSF[[Unable to Display Character: &#8211;]]driven bone marrow-derived macrophage (BMDM) differentiation was found to be skewed towards the M1 phenotype by exposure of cells to eRNA. This resulted in up-regulation of inflammatory markers, whereas anti-inflammatory genes were significantly down-regulated by eRNA. Interestingly, eRNA was released from BMDM under hypoxia and induced TNF-α liberation by activating TNF-α converting enzyme (TACE) to provoke inflammation. Conversely, TNF-α promoted eRNA release, especially under hypoxia, feeding a vicious cycle of cell damage. Administration of RNase1 or TAPI (a TACE-inhibitor) prevented the production of inflammatory mediators. Murine BMDM isolated from mice deficient in sialoadhesin had the opposite reaction to eRNA treatment with a prominent down-regulation of pro-inflammatory cytokines/M1 phenotype markers, while anti-inflammatory cytokines/M2 phenotype markers were significantly raised. In keeping with the proposed role of eRNA as a pro-inflammatory “alarm signal”, these data further shed light on the role of eRNA in macrophage function in the context of chronic inflammatory diseases such as atherosclerosis. The identification of sialoadhesin as putative eRNA recognition site on macrophages may allow further investigation of the underlying mechanisms of eRNA-macrophage interaction and related signal transduction pathways. Siglec-1 thereby may provides a new target to treat eRNA-mediated vascular diseases.

Abstract 620: Angiotensin AT2 Receptor Exerts an Anti-inflammatory Response in Lipopolysaccharide-activated THP-1 Macrophages

Hypertension ◽  
2013 ◽  
Vol 62 (suppl_1) ◽  
Author(s):  
Isha S Dhande ◽  
Tahir Hussain
Keyword(s):  
Inflammatory Response ◽  
Interleukin 10 ◽  
Receptor Expression ◽  
Human Macrophage ◽  
No Production ◽  
At2 Receptor ◽  
Tnf Α ◽  
Anti Inflammatory ◽  
Pre Treatment ◽  
Lps Activation

Macrophages have been shown to be an important contributor to the pathogenesis of hypertension and stroke. The angiotensin AT2 receptor (AT2R), which is expressed in macrophages, is known to promote vasodialation, natriuresis and lower inflammation. The goal of the present study was to explore the anti-inflammatory role of AT2R stimulation in human macrophage-like THP-1 cells activated by lipopolysaccharide (LPS). Phorbol 12-myristate 13-acetate (PMA) differentiated macrophage-like THP-1 cells were treated with AT2R agonist C21 (1 μmol/L) for 30 minutes prior to activation with LPS (1 μg/ml). Media and cells were collected after 24 hours and were analyzed for levels of pro- and anti-inflammatory cytokines and proteins. Pre-treatment with C21 resulted in a 4-fold increase (104.8±6.1 vs 406.7±52.3) in anti-inflammatory interleukin-10 (IL-10) production and a 5-fold decrease (3560±237 vs 588.8±15.94) in pro-inflammatory tumor necrosis factor-α (TNF-α) levels in the media in response to LPS. Predictably, LPS resulted in a 6-fold up-regulation of iNOS expression which was prevented with C21 pre-treatment. A modest decrease in the anti-inflammatory macrophage mannose receptor C type 2 (MRC2) expression was detected with LPS treatment. AT2R agonist pre-treatment, however, increased this receptor expression by ~70% after LPS activation. C21 alone also resulted in a 20% increase in MRC2 expression compared to untreated controls. The anti-inflammatory effect of AT2R activation was abolished in the presence of neutralizing IL-10 antibody (1 μg/ml), indicating a central role for IL-10 in mediating the beneficial response to C21 in LPS activated macrophages. Further, inhibition of nitric oxide (NO) by L-NAME prior to C21 pre-treatment also prevented the decrease in TNF-α and increase in IL-10 in response to AT2R agonist, which suggests that the anti-inflammatory response to C21 may be mediated via increase in NO production prior to LPS activation of macrophages. In conclusion, AT2R stimulation may potentially suppress the inflammatory response of macrophages to LPS by shifting the balance from pro- to anti-inflammatory cytokine production and may prove to be beneficial in the control of the inflammatory component of stroke and hypertension.

scholarly journals Obesity Affects β2 Adrenergic Regulation of the Inflammatory Profile and Phenotype of Circulating Monocytes from Exercised Animals

Nutrients ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2630 ◽  
Author(s):  
Isabel Gálvez ◽  
Leticia Martín-Cordero ◽  
María Dolores Hinchado ◽  
Alberto Álvarez-Barrientos ◽  
Eduardo Ortega
Keyword(s):  
Inflammatory Response ◽  
Adrenergic Receptor ◽  
Acute Exercise ◽  
Inflammatory Responses ◽  
Adrenergic Regulation ◽  
Immune Stress ◽  
Β2 Adrenergic Receptor ◽  
Anti Inflammatory ◽  
Inflammatory Profile ◽  
Inflammatory Effect

Anomalous immune/inflammatory responses in obesity take place along with alterations in the neuroendocrine responses and dysregulation in the immune/stress feedback mechanisms. Exercise is a potential anti-inflammatory strategy in this context, but the influence of exercise on the β2 adrenergic regulation of the monocyte-mediated inflammatory response in obesity remains completely unknown. The first objective of this study was to analyze the effect of exercise on the inflammatory profile and phenotype of monocytes from obese and lean animals, and the second aim was to determine whether obesity could affect monocytes’ inflammatory response to β2 adrenergic activation in exercised animals. C57BL/6J mice were allocated to different lean or obese groups: sedentary, with acute exercise, or with regular exercise. The inflammatory profile and phenotype of their circulating monocytes were evaluated by flow cytometry in the presence or absence of the selective β2 adrenergic receptor agonist terbutaline. Exercise caused an anti-inflammatory effect in obese individuals and a pro-inflammatory effect in lean individuals. β2 adrenergic receptor stimulation exerted a global pro-inflammatory effect in monocytes from exercised obese animals and an anti-inflammatory effect in monocytes from exercised lean animals. Thus, β2 adrenergic regulation of inflammation in monocytes from exercised animals seems to depend on the inflammatory basal set-point.

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