Objective:Acanthopanax senticosus (Rupr. et Maxim.) Harms (ASH) is a traditional herbal medicine widely known for its antifatigue and antistress effects, as well as tonifying qi, invigorating spleen and kidney, and tranquilizing the mind. Recent evidence suggests that ASH has a therapeutic effect on major depressive disorder (MDD), but its mechanism is still unclear. The current study aimed to investigate the effect of ASH on MDD and potential therapeutic mechanisms.Materials and Methods: The chemical compound potential target network was predicted based on network pharmacology. Simultaneously, chronic unpredictable mild stress (CUMS) model mice were orally administrated ASH with three dosages  for 6 weeks, and hepatic metabolomics based on gas chromatography–mass spectrometry (GC–MS) was carried out to identify differential metabolites and related metabolic pathways. Next, the integrated analysis of metabolomics and network pharmacology was applied to find the key target. Finally, molecular docking technology was employed to define the combination of the key target and the corresponding compounds.Results: A total of 13 metabolites and four related metabolic pathways were found in metabolomics analysis. From the combined analysis of network pharmacology and metabolomics, six targets  are the overlapping targets and two metabolic pathways  are the most related pathways. Finally, DAO, MAOA, MAOB, GAA, HK1, and PYGM were verified bounding well to their corresponding compounds including isofraxidin, eleutheroside B1, eleutheroside C, quercetin, kaempferol, and acacetin.Conclusion: Based on these results, it was implied that the potential mechanism of ASH on MDD was related to the regulation of metabolism of several excitatory amino acids and carbohydrates, as well as the expression of DAO, MAOA, MAOB, GAA, HK1, and PYGM. Major depressive disorder (MDD) is a complicated and severe psychological disorder, characterized by low mood, reduced activity, and cognitive dysfunction. More than 350 million people worldwide suffer from depression . AccordiEven though the monoamine transmitter hypothesis is widely accepted, the pathological mechanism of depression is still uncertain. In addition, the neuroendocrine hypothesis, abnormal feedback regulation of the hypothalamus–pituitary–adrenal (HPA) axis, and social stress are also related to depression . Based oAcanthopanax senticosus (Rupr. et Maxim.) Harms (ASH), also known as “Siberian ginseng,” is a kind of hardy shrub that originates in China, Korea, Russia, and Japan, famous for its antifatigue and antistress effect. As a traditional Chinese herbal medicine, it is widely known for tonifying Qi. Qi is the vital energy of life, and Qi deficiency is mostly caused by over work, improper diet, aging, frailty, and chronic illness, and generally manifests as physical weakness, pale complexion, shortness of breath, limb weakness, dizziness, insomnia, sweating, and low voice. The manifestation of Qi deficiency is similar to physical weakness in modern medicine, accompanied by low-energy metabolic levels and pre-depression symptoms. The indication of ASH in traditional Chinese medicine is physical weaknesses, fatigue, loss of appetite, and insomnia. Now, ASH is commonly used in heart disease, hypertension, allergies, diabetes, rheumatoid arthritis, and neurodegenerative diseases  combined with network pharmacology was first applied to find biomarkers, related pathways, hub targets, and key compounds of ASH on MDD. Then, a molecular docking method was used to identify the binding affinity of each compound and target, preliminary exploring the mechanism of ASH on MDD. The flowchart of this study design is presented in http://www.swisstargetprediction.ch/) was used to obtain potential targets for each chemical compound. The UniProt database (https://www.UniProt.org/UniProt/) was employed to define each abbreviation of the proteins of ASH. The information on ADME including oral bioavailability (OB), drug-likeness (DL), gastrointestinal (GI) absorption, and blood–brain barrier (BBB), was obtained from the SwissADME database (http://www.swissadme.ch/) and TCMSP database (http://lsp.nwu.edu.cn/tcmsp.php).The major chemical constituents of ASH were determined by the literature on ASH chemical composition study. The SwissTargetPrediction database (https://www.OMIM.org/), GeneCard (https://www.genecards.org/), DrugBank (https://www.DrugBank.ca), PharmGkb (https://www.PharmGkb.org/), and Therapeutic Target database (http://bidd.nus.edu.sg/bidd-databases/TTD/TTD.asp). Combined the targets searched from each database and deleted duplicate ones, the rest were targets for MDD. The shared targets for both the active compounds in ASH and the disease were selected as the possible targets of ASH in treating MDD. The Venny 2.1 (http://bioinfogp.cnb.csic.es/tools/venny/index.html) was used to map the targets between ASH and MDD.“Major depressive disorder” was imported to the database of OMIM , chloroform , pyridine , heptadecanoic acid , O-methoxyamine-HCl . N, O-Bis (trimethylsilyl) trifluoro-acetamide (BSTFA with 1% TMCS) . Tabellae Acanthopanacis Senticosi was purchased from Shan Xi Yun Peng Pharmaceutical Co. Ltd., and fluoxetine hydrochloride dispersible tablets were purchased from Eli Lilly and Company. The quality control of ASH was carried out by high-performance liquid chromatography (HPLC), according to the method of GC–MS , automatic sample rapid grinder , vortex mixer , high-speed refrigerated centrifuge , nitrogen blowing apparatus , oscillating low-temperature incubator .Methanol–water–chloroform: prepared in a ratio of 5∶2∶2 (v/v/v); heptadecanoic acid methanol solution (1.0 mg/ml): 10 mg of heptadecanoic acid dissolved in 10 ml of methanol; methoxyamine pyridine hydrochloride solution (15 mg/ml): 150 mg of O-methoxyamine–HCl dissolved in 10 ml of pyridine.A total of 36 male ICR mice  were provided by the Laboratory Animal Center of Shanghai University of Traditional Chinese Medicine. All mice were free to food (AIN-93 purified standard diets) and water under the barrier system and bred adaptively for 7 days. Animal welfare is strictly implemented in accordance with the “The Guide for Care and Use of Laboratory Animals” and the ethics and regulations of Shanghai University of Traditional Chinese Medicine (IACUC Issue No: SZY201711003).i.g.) of ASH or fluoxetine from 9:30 to 10:30 (1 h before modeling) every day for 6 weeks. The administration started on the first day of modeling and continued throughout the modeling period.The mice were randomly divided into six groups: normal group , model group , ASH high-dose group , middle-dose group , low-dose group  , and posThe specific operations of the CUMS method included food deprivation (24 h), water deprivation (24 h), overnight lighting (24 h), wet wood chips (24 h), tail pinching (1 min), tilting cage (24 h), and swimming in cold water at 4°C (5 min). All stresses did not threaten the lives of mice, and mice were randomly given different stresses every day to avoid adaptation. Animal welfare was strictly followed in accordance with the “Guidelines for the Care and Use of Laboratory Animals” and the regulation of Shanghai University of Traditional Chinese Medicine (IACUC Issue No: SZY201711003).The liver tissues were collected and stored in the refrigerator at −80°C for further testing. A measure of 500°µL of the methanol–water–chloroform mixed solution was added to the centrifuge tube with a 50 mg liver sample. The samples were homogenized at 70 Hz for 80 s, vortexed for 1 min, sonicated for 5 min, and placed at −20°C for 20 min to precipitate the protein. Then the samples were centrifuged for 10 min  and 300 µL supernatant was collected. A measure of 20 µL of methanolic heptadecanoic acid solution (1.0 mg/ml) was added to the supernatant. The supernatant was blown dry with nitrogen at 30°C and reconstituted with 50 µL of O-methoxyamine–HCl pyridine solution (15 mg/ml). The samples were transferred into a shaker for methoxylation reaction for 90 min (30°C). After the reaction, 50 µL of BSTFA was added and the silylation reaction was carried out for 1 h (70°C). After being placed at room temperature for 1 h, the samples were analyzed on the GC–MS.The GC–MS column was Agilent J&W DB-5ms Ultra Inert (30 m × 0.25 mm × 0.25 μm). GC parameters: high-purity helium (purity: 99.9996%) was the carrier gas, the injection port temperature was 260°C with splitless injection and 1.0 µL injection volume, and the flow rate was 1.0 ml/min. The initial temperature was 80°C and lasted for 2 min. The temperature was raised to 180°C at a rate of 10°C/min, then to 240°C at 5°C/min, and finally to 290°C at 25°C/min and kept for 9 min. MS parameters: ion source temperature was 230°C, quadrupole temperature was 150°C, and mass spectrometer interface temperature was 280°C. Solvent delay was 5 min, ionization mode was EI, electron impact ionization voltage was 70 eV, and scan range (m/z) was 30–550. The parallel injection sequence method was used.p < 0.05 was defined as a significant difference, and fold change (FC) was calculated based on the average relative peak area of the difference variable between each group. Finally, values with VIP ≥1 and p-value ≤ 0.05 were determined as differential metabolites.The raw data were imported into R software (v2.13.2) for data preprocessing. Subsequently, the processed data were imported into SIMCA software  for multi-dimensional statistical analysis, including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA). The S-plot was obtained on the basis of OPLS-DA, and variable importance in the projection (VIP) value >1.0 as the standard to find candidate difference variables. Then the value was imported into SPSS software (v21.0) for an independent sample t-test. http://www.hmdb.ca/) to further confirm potential biomarkers, and MetaboAnalyst 4.0  platform and Kyoto Encyclopedia of Genes and Genomes  database were used for enrichment analysis of metabolic pathways. Key pathways were determined with p-value < 0.05, and targets related to the pathways were identified based on the KEGG database.Combined with the Human Metabolome Database  was used to obtain the structural information of the target. The docking software LigPlot (https://www.ebi.ac.uk/thornton-srv/software/LigPlus/) was used to make images of the interaction between protein molecules and ligand molecules.The protein structure database Protein Data Bank , monoamine oxidase A (MAOA), monoamine oxidase B (MAOB), alpha glucosidase (GAA), amylase alpha 1A (AMY1A), hexokinase 1 (HK1), and glycogen phosphorylase muscle associated (PYGM). The Cytoscape was applied to visualize the network of compounds in ASH, shared targets, pathways, and relevant metabolites  have two subtypes: MAOA and MAOB, which are thought to mediate the degradation of monoamine neurotransmitters (including DA) in the brain. Starch and sucrose metabolism is another major pathway in the results of our study, and it is a prominent pathway in patients with MDD . It beloα-glucosidase, is widely distributed in the systemic circulation and can cause glycogen accumulation in many tissues and the entire central nervous system and severe neuromuscular damage when deficient, which eventually leads to Pompe disease, a metabolic and neuromuscular disorder (GAA, acid disorder . Increasdisorder . In the disorder . In partdisorder . The studisorder .HK1, mainly distributed in the brain, is a kind of hexokinase that initiates the first step of glycolysis by the phosphorylation of glucose . HK1 attPYGM, a muscle glycogen phosphorylase or myophosphorylase, is mainly involved in glycogenolysis and provides sufficient energy for cell biological processes . PYGM isIn the results of molecular docking, eleutheroside B1 was bound well to GAA, HK1, and PYGM, while eleutheroside C had a good docking with PYGM. Therefore, we proposed that GAA and PYGM might affect the occurrence and development of depression by regulating glycogen metabolism in the brain, while HK1 affects the survival and growth of neurons by regulating glycolysis, and eventually affects the mood of depressed patients. Also, it was implied that eleutheroside B1 and eleutheroside C play an antidepressant effect by regulating energy metabolism.Our study provides clues for the mechanism and material basis of ASH treatment of depression, but the current research still has some limitations. First of all, this study is based on the hepatic metabolomics study. Although hepatic metabolites may also enter the blood circulation and interact with the target or drug-active components, they still need to be compared with components in blood circulation and brain. Second, only part of the active components of ASH can be directly absorbed and pass through the blood–brain barrier. Although they are closely related to many depression targets in the prediction of network pharmacological targets, their actual binding sites in the body are still unclear. Also, based on the current results, it is speculated that the liver may play an important role in the antidepressant effect of ASH, and the targets may not be limited to the central nervous system. Finally, the current findings are still preliminary, and further validation is under design, such as the effect of administration of a single ingredient of ASH on depression and changes in distribution and expression of the predicted targets, as well as targeted, quantitative experiments for validating the role of those targets in the regulation of MDD by ASH.In our study, first, ASH administration improved depression-like behaviors and simultaneously ameliorated hepatic metabolomic alterations in CUMS mice. Second, combined with network pharmacology and molecular docking techniques, the potential active components, targets, and related metabolic pathways of ASH in the treatment of depression were predicted, that is, isofraxidin, quercetin, kaempferol, and acacetin might target DAO, MAOA, and MAOB to regulate glycine, serine, and threonine metabolism, while eleutheroside B1 and eleutheroside C seemed to regulate starch and sucrose metabolism by targeting GAA, HK1, and PYGM. As the components in ASH and their targets are primarily derived from the literature and network pharmacology rather than direct experiments, these conclusions are predictive and require validation by both qualitative and quantitative experiments on compounds to single targets. In addition, there is a certain gap between the metabolic pathway results derived from the depression model mice and the clinical patients, so validation studies based on the quantitative analysis of metabolites in clinical samples are needed.


Clinical evidence proves that patients with cancer are more easily infected with severe acute respiratory disease coronavirus 2 (SARS-CoV-2) because of immunologic deficiency. Thus, there is an urgent need to develop candidate medications to treat patients with cancer plus COVID-19, including those with osteosarcoma (OS). Ferulic acid, a latent theriacal compound that has anti-tumor and antivirus activities, is discovered to have potential pharmacological use. Thus, in this study, we aimed to screen and determine the potential therapeutic targets of ferulic acid in treating patients with OS plus COVID-19 as well as the pharmacological mechanisms. We applied a well-established integrated methodology, including network pharmacology and molecular docking technique, to detail target prediction, network construction, gene ontology, and pathway enrichment in core targets. The network pharmacology results show that all candidate genes, by targeting autophagy, were the core targets of ferulic acid in treating OS and COVID-19. Through molecular docking analysis, the signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase 1 (MAPK1), and phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1) were identified as the pharmacological targets of ferulic acid in treating OS. These preclinical findings from bioinformatics analysis altogether effectively determined the pharmacological molecules and mechanisms  The pro pathway . Based ohttp://www.ncbi.nlm.nih.gov/geo/) database (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was applied for gene differential analysis. The screening conditions were set as the difference fold |log2FC| >0.5, and the false discovery rate (FDR) was <0.05 to obtain the significantly differentially expressed genes of human OS and to draw the volcano plot associated with differential genes. Using the Genecards database  and Human in the UniprotKB database . The OMIp-value cutoff was 0.05, and the q-value cutoff was 0.05 during enrichment, resulting in an output corresponding to a bubble chart and a circle chart. In addition, Cytoscape_v3.8.2 was used to create a drug-target–GO–CC–MF-pathway disease visualization graph from the results of the biological process and pathway enrichment of ferulic acid against OS and COVID-19 targets through autophagy (The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and visualization of core targets were performed using R-packages such as “ClusterProfiler”, “org.Hs.eg.Db”, and “ggplot2” in the R language. The gene annotation information was obtained from “org.Hs.eg.Db”, the adjusted utophagy .To reveal the interaction between the ferulic acid targets and OS/COVID-19 targets, a protein–protein interaction (PPI) network was established through the Search Tool for the Retrieval of Interacting Genes (STRING) database . All corhttps://pubchem.ncbi.nlm.nih.gov/) (https://www.uniprot.org/) and transferred in Protein Data Bank (https://www.pdbus.org/) format. In addition, the Autodock (version 1.5.6) software was used to increase polar hydrogen and set the grid box, and the autodock vina function was further used to conduct the molecular docking assay. The binding energy of ferulic acid with these identified proteins was established, and then the Pymol software was used to visualize the optimal docking conformations  . The cryrmations .We compared 19 normal group samples to four OS tumor group samples through the GEO database by retrieving the GSE28424 dataset. After screening, a total of 3,011 differential genes were obtained, including 1,500 upregulated genes and 1,511 downregulated genes, as shown in Using databases such as TCD to search for drug targets and correcting through the UniprotKB database, a total of 360 ferulic acid targets were obtained. The OMIM and other databases were used to obtain 870 autophagy-related targets. The obtained targets were mapped using a Venn diagram, and a total of five intersection targets were obtained, including MAPK1, TLR4, PIK3R1, STAT3, and PARP1 Figure 2To better indicate the biological characteristics of the identified intersection targets, the R language software was used to implement GO and KEGG enrichment assays. Using parametric analysis, the GO-based biological process (BP) terms Figure 3in silico imitation analysis.To further ascertain the core targets, topological parameters and target degrees of freedom were measured through Cytoscape_v3.8.2, wherein the filter condition range was set to three to four. As a result, all top three targets, including STAT3, MAPK1, and PIK3R1, were identified as the core genes before further To confirm the potential targets of ferulic acid, these STAT3, MAPK1, and PIK3R1 proteins were computationally docked with ferulic acid based on the binding energy scores, characterized by 6SM8, 3SA0, and 6OCO binding active sites. The amino acid residue GLY-1020 (3.4 Å) formed a functional hydrogen bond between ferulic acid and 6SM8 (STAT3), and the free docking energy was -6.3 kcal/mol  and Guangxi Natural Science Foundation of China (grant no. 2020JJA140172).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Multi-omic approaches are expected to deliver a broader molecular view of cancer. However, the promised mechanistic explanations have not quite settled yet. Here, we propose a theoretical and computational analysis framework to semi-automatically produce network models of the regulatory constraints influencing a biological function. This way, we identified functions significantly enriched on the analyzed omics and described associated features, for each of the four breast cancer molecular subtypes. For instance, we identified functions sustaining over-representation of invasion-related processes in the basal subtype and DNA modification processes in the normal tissue. We found limited overlap on the omics-associated functions between subtypes; however, a startling feature intersection within subtype functions also emerged. The examples presented highlight new, potentially regulatory features, with sound biological reasons to expect a connection with the functions. Multi-omic regulatory networks thus constitute reliable models of the way omics are connected, demonstrating a capability for systematic generation of mechanistic hypothesis. The establishment of high-throughput technologies has made possible a systems biology approach to cancer through multi-omics integration . The mulAlthough there is a plethora of statistical approximations , sparse Here, we applied the sparse generalized canonical correlation analysis (SGCCA) to data on DNA methylation and gene and miRNA expression from TCGA. The SGCCA is a statistical method that outputs correlated features among a large collection by the use of LASSO penalization . The SGChttp://csbig.inmegen.gob.mx/SGCCA/. Release 105 of biomaRt was used all along and plots were produced with ggplot2 , a design matrix, and a function to maximize the covariance. Sparsity parameters were chosen for each omic from the sequence , by cross-validation. With this purpose, a balanced dataset, composed of 10 samples per tumor subtype and 10 samples from normal tissue, was randomly taken from the original data, 10 times per each sparsity parameter value. Each time, a simple SGCCA was run, recovering only one component and taking note of the selected number of features and the average variance explained (AVE). Summing the different combinations, in total, every value was tested 11,340 times per omic. Sparsity parameters were chosen in order to obtain the largest AVE with the lowest number of features . To translate CpG probes to Entrez IDs, we recovered the genes affected by each probe from the microarray annotation file. This results in an amplification of CpG representation since one site can be associated with a whole cluster of genes and assumes a methylation effect on overlapping genes, which is not necessarily true. Both are cons of this mapping that need to be considered.clusterProfiler package , only with transcript data, to check for functions affected by differential expression. GSEA was also performed with the 1. We extracted a sub-matrix from the original dataset and run ARACNE.multiMiR package (TFtargets (github.com/slowkow) for the transcript coding for transcription factors. This latter package queries several resources, namely, TRED, ITFP, ENCODE, TRRUST, and the databases from 2. We retrieved regulatory interactions involving the selected features. Again, this was performed with the microarray annotation file for the CpGs, assuming position overlap is enough to affect gene expression. The  package  was usedinfotheo package  between every pair of nodes using ARACNE software  and thenigraph package  features behind the functional enrichment. To verify if this happens, we calculated the Jaccard index for every pair of functions enriched more than once. The Jaccard index divides the size of intersection between two sets by their union, measuring similarity with a normalized value between 0 (fully disjoint sets) and 1 (the same set). Distributions for the Jaccard index are shown in The obtained distributions are enough to state that, for most functions, the CpG–transcript–miRNA circuitry is not the same across datasets since the features involved are not the same. Only seven biological processes enriched in a given pair of SGCCA results share more than 50% of the involved features. Five of them are related to development, while the other two are related to cell adhesion. These are the functions that may share the interactions between CpG sites, transcripts, and miRNAs.If this index hints at the similarity between subtypes pertaining to CpG–transcript–miRNA co-variation, the distance with Her2-enriched subtype results are intriguing. This may be caused by a bias induced by the low number of samples. Or perhaps this is associated with the lower correlation with DNA methylation patterns . Not surTo answer if functions exclusively found in one dataset bring to light subtype-specific properties, we analyzed over-representation of GOslim categories and KEGG classes. The proportion of biological processes found for each dataset in every one of the categories is given in cellular component organization in the basal SGCCA components, establishment of localization in luminal A, and DNA metabolic process in the normal tissue. There are seven biological processes behind the cellular component organization over-representation, comprising five processes related to axon extension, which are clustered with regulation of the extent of cell growth. Collagen fibril organization is not in the cluster and is the seventh process, suggesting a potential bond between the basal subtype and invasiveness.None of the KEGG classes is biased toward a given subtype, but there is an enrichment for the categories: establishment of localization. These processes affect transport and secretion and conform to 32 different clusters. Regarding over-representation in the normal tissue, it is interesting that it is related to DNA alkylation and methylation processes, perhaps implying that these processes are somehow disarranged on the tumor subtypes.In the case of luminal A, there are 62 biological processes behind the over-representation of When checking the features responsible for the enrichment of a given function, we discovered that several functions are enriched in the exact same set of co-varying features, that is, the same set of SGCCA components. This suggests some level of crosstalk between functions that can be connected through correlated features. This observation has been made subtype-wise and implies that a single network of correlated features may actually span several functions.Going through each subtype separately, we clustered functions by the proportion of SGCCA components shared. Clustering exposes information that needs to be accounted when discussing one particular enrichment. Functions exclusively found in one subtype may reveal mechanistic explanations of subtype-specific alterations, but, if exclusive functions are clustered with others that are non-exclusive and better represented, relevance may be debatable. Similarly, clusters may help explain some odd enrichments, like the one found in the luminal A dataset for morphine addiction. Morphine addiction has been found enriched on methylation-driven genes  but depeIn order to select functions to explore further, we repeated the analysis described with Her2+ for each SGCCA result. While not all clustering are displayed here, full groups and enrichment results are supplied as In our path to answer if a function enriched twice involves identical features and interactions, we found that a given function is commonly enriched through distinct sets of features in two different datasets. At the same time, we observed several functions over-represented among the same sets of co-selected features and wondered how functions were connected. Functions involving the same features are already identifiable in the annotation databases, but by means of this multi-omic integration strategy, we have been able to find cross-linking paths across single layers and maybe even connect seemingly independent functions through multi-omics pattern co-variation. To check how this appears, we built mutual information (MI) networks. The networks went through a stringent threshold to keep just the interactions that are most likely regulatory. To this end, we obtained the MI values accompanying true regulatory interactions and took the median value as the minimum MI required to consider an edge as possibly regulatory. Within these reduced sets of interactions, the following figures show the network components that contain those features annotated as participating in the functions, though some of the obtained networks extend further.The intuition is that co-selected features, whose patterns are correlated with those of functional features, may also be participating in a given function. Beyond that, nodes for miRNAs, CpGs, and transcripts that ultimately code for transcription factors may be playing regulatory roles. The stringent threshold attempts to filter out the interactions owed to simple co-variation. Two broad possible scenarios are expected, 1) disconnected components per function, each with its own potential regulators, or 2) functions that crosstalk through common features, whose potential regulators could be of medical interest. The different scenarios are exemplified through the four subtypes and the normal tissue in the coming sections.Hypoxia-inducible factor 1 (HIF-1) signaling is one of the KEGG pathways enriched exclusively in the basal SGCCA results. HIF-1 is the master regulator of oxygen homeostasis since it induces transcription from at least 100 hypoxia-responsive elements . HIF-1 sThe network we identified for this function is given in Only two functional features, that is, annotated as participants of the function, pass the MI threshold, NOS3 and RPS6. It is important to clarify that the enrichment does not rest only on these two features, but we only find interactions over the threshold for them. There are also two nodes that have been linked with the signaling pathway without being participants as such. PEG3 gets upregulated after hypoxia in mouse lungs , while SOn the other hand, the complete network is formed by CpG–transcript interactions, more specifically, by edges linking a CpG with a transcript coding for a ribosomal protein. Since CpG sites are not in the same chromosome as the transcript, a direct regulatory influence can be discarded. To account for indirect relations, we estimated the mutual information between the corresponding transcripts, even when these were not originally in the SGCCA set of co-selected features. Obtained MI values are smaller than the global threshold and smaller than the edges between CpGs and ribosomal protein-coding transcripts. Hence, indirect effects going through the transcript linked with the CpG do not seem to fully explain the phenomenon.p-value: 0.7937). HIF-1 signaling in the basal subtype is transcriptionally comparable with that of the normal tissue. Nevertheless, the pathway is not found enriched in the normal tissue SGCCA output, suggesting a change in the correlation between omics.Most nodes are not significantly different from the normal tissue, either regarding expression or methylation values. This is consistent with the lack of significance of the pathway GSEA score  in this analysis.Ras signaling is one of the many pathways exclusively found enriched in the luminal A subtype. It is a well-documented pathway influencing cancer aspects like cell proliferation, survival, migration, and differentiation. Although the pathway is more frequently activated in the other subtypes, it has been reported as an indicator of poor prognosis in luminal tumors . Not surOnly one functional feature endures the MI threshold, GNB2. The subunit beta 2 of G protein links the signaling pathway with a set of CpGs associated with cell communication and brain function, through the calcium sensor SYT13. Genes affected by the CpGs include the brain active kinase, STK32C; MIDN, that is predicted to enable kinase binding; OBP2B, which is supposed to enable binding of small volatile molecules; a TF from early brain development, RFX4; and SYCN, which is predicted to be active in exocytosis.Among the remaining nodes, the connection with the CUX1 CpG site agrees with the cooperation observed between this transcription factor and Kras-G12V mutant in lung cancer . In a siAgain, the network shown in Wnt signaling normally controls organ development. In breast cancer, Wnt signaling is involved in tumor proliferation and metastasis, immune microenvironment regulation, stemness maintenance, and therapeutic resistance . The relnegative regulation of the Wnt signaling pathway is exclusively found enriched in this subtype, but related Wnt pathways were also found for luminal A. The cross-talking functions shown in In our results, negative regulation of Wnt signaling and regulation of Wnt share functional features. The transcription factor for skeletal development, Sox9, is represented by its CpG at the crossroad between Wnt signaling with the developmental processes, but there are also multiple indirect paths. Since the genes coding collagen subunit Col4a2 and cell adhesion molecule Ceacam6 are targeted by Sox9  and has been linked with hypomethylation  cannot be used in a straightforward manner. Thus, the setting of varying thresholds based on regulatory interactions is established. In this case, MI ability to recover non-linear relations may not be fully profited, being posterior to the lineal filter of SGCCA. MI is, however, used as a way to bring together all the results concerning a function and highlight some potentially interesting pairs of nodes.The DPI posed with ARACNE discards the lowest weighted edge from a triad, as a likely indirect interaction driven by the other pair of nodes. The difficulty of using it comes from the observation that mutual information distributions change with the different omics . While mIt is worth considering that MI has a dependency on the number of observations, which varies between subtypes and the normal tissue. Her2 enriched has a smaller number of samples than recommended, and so special care must be taken with it. Given that MI is rank-invariant, it is expected that, even with the stringent threshold, only a subset of the interactions in To end with the pros and cons’ discussion, here, we have overlooked interactions between CpG sites because those are beyond described regulatory mechanisms. Nevertheless, links between CpG sites are accompanied by large MI values that would surpass our threshold and may become of relevance in the cancer context . On the The networks produced in this way capture statistical dependencies that may guide further work. However, such a hypothetical future work depends on a user being able to find these kinds of networks and research the reasons behind a statistical dependency. Article databases can serve this purpose, as we have done here, but may become unspecific. Instead, network databases  may offe


These HDPE systems were HDPEBi-0 (pure HDPE), HDPEBi-10 (10 wt% Bi2O3), HDPEBi-20 (20 wt% Bi2O3−), HDPEBi-30 (30 wt% Bi2O3), HDPEBi-40 (40 wt% Bi2O3), and HDPEBi-50 (50 wt% Bi2O3). The values of the linear attenuation coefficients of the experimental results  were compared with the theoretical results (obtained using Phy-X software) at 0.060, 0.662, 1.173, and 1.333 MeV energies. To ensure the accurateness of the experimental results, this comparison was made. It was crystal clear that for energy values from 0.06 MeV to 1.333 MeV, all the experimental values were in line with Phy-X software data, which demonstrated the research setup’s reliability. Here, the linear attenuation coefficient (LAC), and mean free path (MFP) shielding parameters were assessed. At the energy of 1.333 MeV, sample HDPEBi-0 showed an HVL value 1.7 times greater than that of HDPEBi-50, yet it was 23 times greater at 0.0595 MeV. That means that for proper radiation protection, very-low-energy HDPE systems containing 10–50% Bi2O3 could be used; however, the thickness of the HDPE system must be increased according to the energy of incident radiation.For extensive radiation exposure, inventing a novel radiation shielding material is a burning issue at present for the purpose of life saving. Considering this thought, in this study, by adding sundry amounts of Bi Natural ionizing radiation enduringly eclipses earth . In our 2O3, and WO3 to the matrix material enhances the shielding ability of this material due to the large atomic number of Pb, Bi, and W elements [+3 ion has a large density and effective atomic number, it is not yet possible to synthesize glass using individual Bi+3 ions. However, glass with added Bi2O3 is considered one of the most important radiation protective materials [The addition of high-density oxides such as PbO, Bielements . Althougaterials . Onuoha aterials . In 2022aterials . Very reaterials .2O3-containing glass (as a replacement of PbO) are utilized for radiation shielding purposes [2O3 into it by taking into account the measuring values of the LAC, HVL, MFP, and Zeff shielding parameters in the energy range from 0.015 MeV to 15 MeV. Additionally, for validating the experimental setup, the values of the linear attenuation coefficients of the prepared high-density polyethylene measured using an HPGe detector were coordinated with the theoretical results obtained using Phy-X software. To the best of the authors’ knowledge, these compositional HDPE systems have not been previously assessed.Moreover, due to the low rates of crystallization, non-toxicity, high radioactive resistance, large optical basicity, high third-order nonlinear optical susceptibility, high polarizability, long infrared cut-off wavelengths, and moisture resistance, Bipurposes ,21,22,23A quantity of high-density polyethylene was obtained from Sidi Kerir Petrochemicals Company, weighed with a 0.0001 g sensitive scale, and placed in a thermal mill at an effective temperature of 140 °C, where the melting point of polyethylene is 130 °C. The mill was operated at a rotation speed of 40 revolutions per minute (rpm) for a period of one-third of an hour. Powdered bismuth oxide was purchased from Al-Gomhoria Chemicals Company in Egypt with a purity of 98.7% and was filtered using a sieve having a diameter of 50 µm. After making sure that high-density polyethylene was completely melted, powdered bismuth oxide was gradually added to the specific amounts presented in Scanning electron microscopy (SEM) was used to analyze the microstructure of bismuth-injected high-density polyethylene samples to obtain the characterization of the samples. A JSM-5300 JEOL microscope was used .2O3 samples  was determined using the following equation ,31:(1)LA2O3 samples were compared with the results obtained using Phy-X software [The experimental results of the LACs of the HDPE-Bisoftware . The MFPsoftware ,35,36,372O3 increased in the matrix with the increase in the proportion of particles, as shown in 2O3) was, the more uniformed the distribution of particles inside the polymer was; therefore, the rate of photon collision with the material was higher due to the gaps being filled by Bi2O3 particles, and consequently, the attenuation of the incident photons was higher. We could conclude that the addition of bismuth particles improved the shielding properties of HDPE.Scanning was performed to know the distribution of bismuth oxide particles within HDPE using the electron microscope, and it was clear that the particles uniformly distributed and that the amount of Bi2O3), HDPEBi-20 (20 wt% Bi2O3−), HDPEBi-30 (30 wt% Bi2O3), HDPEBi-40 (40 wt% Bi2O3), and HDPEBi-50 (50 wt% Bi2O3) HDPE systems were prepared by adding Bi2O3 to HDPEBi-0 (pure HDPE). To compare the experimental results (obtained using HPGe) with the theoretical results (obtained using Phy-X software), the linear attenuation coefficients were measured in the lab at four different energies; their graphical representation is presented in In this study, HDPEBi-10 (10 wt% Bi2O3) followed the following declining trend: HDPEBi-50 > HDPEBi-40 > HDPEBi-30 > HDPEBi-20 > HDPEBi-10. At all energy values E < 0.3 MeV, the HDPE systems supplemented with Bi2O3 showed higher LAC values. At the energy of 0.015 MeV, the values of the LACs of all studied HDPE systems were as follows: HDPEBi-0, 0.71 cm−1; HDPEBi-10, 11.7 cm−1; HDPEBi-20, 25 cm−1; HDPEBi-30, 41.6 cm−1; HDPEBi-40, 62.8 cm−1; and HDPEBi-40, 90.8 cm−1. HDPE system HDPEBi-50 (50 wt% Bi2O3) showed the highest LAC value compared with the other HDPE systems, which indicated that a higher amount of Bi2O3 in pure HDPE boosted the radiation shielding ability.We calculated the LACs in a wide energy range to examine the behavior of the LACs at higher energies see . For all2O3, and the discrepancies among the assessed Zeff values are presented as functions of the photon energy in eff lay in the ranges of 4–3, 42–3, 57–3, 65–4, 70–4, and 74–5, respectively. The maximum values of the effective atomic number (Zeff) originated at the low energy of 0.015 MeV and were 4, 40, 55, 63, 69, and 73 for the studied HDPE series . Yet, the Zeff values of all studied HDPE systems followed a similar trend after Bi2O3 contamination, and HDPEBi-50 showed the highest Zeff value, whereas HDPEBi-10 showed the lowest Zeff value. Here, HDPEBi-10, HDPEBi-20, HDPEBi-30, HDPEBi-40, and HDPEBi-50 showed values 9, 13, 15, 16, and 17 times greater than that of HDPEBi-0 at the energy of 0.015 MeV thanks to the addition of Bi2O3 at 10, 20, 30, 40 and 50 wt% to HDPE. For energy values in the range of 0.02–0.08 MeV, Zeff decreased and rapidly came down. It was clear that a higher amount of Bi2O3 increased the Zeff value of HDPE. An exponential decrease was found for the energy range of 0.1–0.6 MeV; however, in the 1–15 MeV energy range, the effective atomic number (Zeff) sharply increased. In the energy range of 2–15 MeV, HDPEBi-10, HDPEBi-20, HDPEBi-30, HDPEBi-40, and HDPEBi-50 showed values 1.2, 1.5, 1.9, 2.4, and 3.0 times greater than that of HDPEBi-0. Here, the minimum values were seen at an energy of 1.5 MeV, and the values were 2.7, 2.9, 3.2, 3.6, 4.1, and 4.8 for the studied HDPE series, respectively  and HDPE containing 10–50% Bi2O3 . The figure shows that the HVL of the studied samples increased with the increase in energy . From 2O3 could be used for protection from hazardous radiation, but with the increase in energy, the thickness of HDPE must be increased in order to obtain suitable protection from the high energy of radiation. It was revealed that at any fixed energy, the HVL decreased with the addition of Bi2O3 in HDPE. Pure HDPE showed a higher HVL than the other studied HDPE samples containing Bi2O3. Moreover, HDPEBi-50, with the highest content (50 wt%) of Bi2O3, showed the lowest HVL value. Thus, all studied HDPE samples containing Bi2O3 showed better radiation shielding competence than pure HDPE. Hence, it was clear that Bi2O3 addition was the cause of the reduction in the thickness of the HDPE samples that could attenuate the photon incidence.In 2O3) and of the HDPE (with 10–50% Bi2O3) systems, the mean free path (MFP) values were examined herein for identifying the radiation shielding ability and the gained MFP fallouts for the pure and contaminated HDPE systems against photon energy, as demonstrated in 2O3-containing HDPE systems  showed lower MFP values than pure HDPE at the low energy levels of 0.0595 MeV and 0.0810 MeV. This provided the suggestion that these HDPE systems with the apt addition of Bi2O3 showed proficiency as radiation shielding materials. It is eminent that lower MFP values designate a healthier radiation shielding ability in any absorbing material. The MFP values of the HDPE systems ranked as follows: HDPEBi-50 < HDPEBi-40 < HDPEBi-30 < HDPEBi-20 < HDPEBi-10 < HDPEBi-0. The MFP values of HDPE systems HDPEBi-0, HDPEBi-10, HDPEBi-20, HDPEBi-30, and HDPEBi-40 were found to be 1.7, 1.6, 1.4, 1.3, and 1.2 times higher than that of HDPEBi-50 against Co-60 gamma irradiation. HDPE system HDPEBi-50 (50 wt% Bi2O3) had the lowermost MFP value among the other HDPE systems; hence, we could conclude that the radiation shielding features of the HDPE systems improved with the addition of Bi2O3.To validate the efficacies of pure HDPE (without Bi2O3 in HDPE were studied to identify its radiation shielding capability. The values of the linear attenuation coefficients obtained using Phy-X software and an HPGe detector were compared to ensure the sample preparation was consistent. The Zeff maximum values originated at the low energy of 0.015 MeV and were 4, 40, 55, 63, 69, and 73 for the studied HDPE series, i.e., HDPEBi-0, HDPEBi-10, HDPEBi-20, HDPEBi-30, HDPEBi-40, and HDPEBi-50, respectively. HDPEBi-50 showed the highest Zeff value, whereas HDPEBi-10 showed the lowest Zeff value. Here, HDPEBi-10, HDPEBi-20, HDPEBi-30, HDPEBi-40, and HDPEBi-50 showed values 9, 13, 15, 16, and 17 times greater than that of HDPEBi-0 at the energy of 0.015 MeV. The MFP values of the HDPE systems ranked in the following order: HDPEBi-50 < HDPEBi-40 < HDPEBi-30 < HDPEBi-20 < HDPEBi-10 < HDPEBi-0. The MFP values of HDPE systems HDPEBi-0, HDPEBi-10, HDPEBi-20, HDPEBi-30, and HDPEBi-40 were found to be 1.7, 1.6, 1.4, 1.3, and 1.2-times higher than of HDPEBi-50 against Co-60 gamma irradiation. In the energy range of 0.015 MeV to 15 MeV, HDPE systems showed greater shielding ability according to their higher contents of Bi2O3.Very few data on HDPE exist in terms of radiation shielding purposes, even though HDPE is extensively used worldwide. Hence, various amounts of Bi


Salvia miltiorrhiza, Angelica sinensis, frankincense, and myrrh were obtained by using TCMSP, SwissADME, and Swisstarget databases. Similarly, relevant targets of KOA were collected through GeneCards, OMIM, TTD, PharmGKB, and DrugBank databases. Next, the potential targets of ZXP in the treatment of KOA were obtained by intersection of drug and disease targets. Finally, Cytoscape 3.7.1 software was used to construct a “disease-drug-component-target” network, and Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Gnomes (KEGG) signaling pathway enrichment analysis were performed on the core targets through Metascape website. A total of 99 active components and 203 corresponding potential therapeutic targets were obtained from the components of HXP. And KOA has 2543 potential therapeutic targets, of which 120 cross targets correspond to 120 active compounds in HXP. Then, topology analysis displayed that the six targets form the core PPI network. In addition, GO and KEGG enrichment analyses showed that these core targets were mainly enriched in inflammatory response, apoptosis, oxidation reaction, and other related pathways.Based on the deep fusion of intelligent meridian sensing technology and Huoluo Xiaoling Pill (HXP) in the treatment of knee osteoarthritis (KOA), firstly, the effective components and targets of  Knee osteoarthritis (KOA), belonging to the category of osteoarthritis (OA), is a common disease with continuous knee pain, morning stiffness, limited activity, and reduced function . The speKOA that belongs to the category of “bone arthralgia disease” and “knee arthralgia disease” in traditional Chinese medicine (TCM) can be divided into cold dampness arthralgia, damp heat arthralgia, qi stagnation and blood stasis, liver and kidney deficiency, and qi and blood weakness . AcupuncHuoluo Xiaoling Pill (HXP) is used for promoting blood circulation and removing blood stasis, dredging meridians and relieving pain, treating qi and blood stasis, confidant pain, leg and arm pain, etc. There were frequent additions and subtractions in orthopaedic therapy for closed fractures, compartment syndrome (OFCS), traumatic knee synovitis combined, and so in . AdditioIn this study, the treatment of KOA by HXP was analyzed by NP, which provided direction and enlightenment for exploring the drug action mechanism of HXP. This study is aimed at exploring the potential mechanism of HXP in the treatment of KOA through the method network pharmacology (NP), which may contribute to the screening of clinical drugs for KOA and improve the dosage form of HXP, providing reference for exploring the matrix of HXP in the treatment of KOA.The intelligent meridian therapy instrument is guided by the basic theory of traditional Chinese medicine. The dynamic interference frequency conversion pulse therapy used is based on the traditional acupuncture theory, which combines high voltage and low frequency conversion pulses with the meridian theory. The internal and external knee eye points) are electrically stimulated to achieve the day of clearing the meridians, promoting blood circulation and removing blood stasis, promoting qi, and relieving pain. Meridian physiotherapy instrument can play a role in adjuvant treatment and remission for some inflammatory diseases and can assist in the treatment of some nervous system diseases.Salvia miltiorrhiza (Dan Shen in Chinese), Angelica sinensis (Dang Gui in Chinese), frankincense (Ru Xiang in Chinese), and myrrh (Mo Yao in Chinese) in HXP were obtained by TCMSP database . Further, the effective components and target information, which were obtained in virtue of screening according to the restrictions of drug oral bioavailability (OB) ≥ 30% and drug like (DL) ≥ 0.18%, convert the obtained target information into the verified human gene identification code in UniProt database (https://www.uniprot.org/) for subsequent use.The chemical components of https://go.drugbank.com/), GeneCards, OMIM , TTD , and PharmGKB databases (https://www.pharmgkb.org/) to search for disease targets related to KOA, respectively. After all results were screened and deduplicated, target information of KOA was obtained.“Knee osteoarthritis,” “knee arthritis of knees,” and “knee arthritis in the knee” were entered into DrugBank (The common targets of drugs and diseases are obtained through the pug(a process of writing code by indenting) in the R Programming Language (R), and the Venn diagram (Venn) is drawn. Drug targets refer to the binding sites of drugs in the body, including biological macromolecules such as genetic loci, receptors, enzymes, ion channels, and nucleic acids.The active components of drugs obtained by “1.2.1,” common targets of drug diseases gained by “1.2.3,” and the network information between them are imported into Cytoscape 3.7.1 to construct the network diagram. Each node is the target, component, and drug name, respectively, between which each edge represents the interaction relationship.The common targets of drug diseases obtained in “1.2.3” are imported into STRING database, and the species is limited to human, to obtain PPI information, which is imported into the Cytoscape 3.7.1 to generate PPI network diagram, and then, the CytoNCA plug-in is used to conduct topological analysis on the network data. First of all, the degree centrality (DC) nodes which are greater than twice median are screened. After that, the index parameters of betweenness, closeness, local average connection-based method (LAC), and neighborhood connectivity were greater than the twofold median. Eventually, the core targets of HXP in the treatment of KOA were obtained, and the PPI core network was mapped. The interaction between proteins is the basis for the occurrence of life phenomena, and the study of their interactions can clarify the mechanism of biological reactions and reveal the essence of life phenomena.P < 0.01, and minimum enrichment of 1.5, the GO analysis of which also includes the data analysis of biological process (BP), molecular function (MF), and cellular component (CC). In the end, the top 10 items obtained from GO-BP, GO-MF, and GO-CC and the first 20 results from KEGG were selected, respectively, being drawn into bubble chart for visual processing via origin Lab 2018. The size of bubble represents the number of targets enriched in the specified path, while the color means the enriched q value. As shown in First, add 1.2.3, the obtained intersection targets were introduced into the Metascape, and human species were selected. Afterwards, the GO and KEGG enrichment analyses were carried out separately under the limiting conditions of minimum overlap of 3, Salvia miltiorrhiza, 2 Angelica sinensis, 6 frankincense, and 34 myrrh, where Angelica sinensis and myrrh also contain β-sitosterol and stigmasterol , viral and parasitic infections , cancer and transcriptional disorders in cancer, nonalcoholic fatty liver disease, rheumatoid arthritis, etc. According to the comparison between the core targets gained in 2.5 and the genes obtained by each KEGG pathway, 32 pathways related to KOA were selected through comparison with the existing literature, and the top 20 pathways with larger enrichment factors were chosen for display  and gateways.β-sitosterol, an antioxidant [This study explored the potential targets and mechanism of HXP in the treatment of KOA through NP. The 99 drug active ingredients and 120 intersection targets obtained were used to construct the “drug-component-target-disease” network model, and the analysis showed that most of the ingredients affected multiple targets. For example, quercetin, luteolin, beta-sitosterol, tanshinone IIA, and dihydrotanshinlactone have affected 90, 44, 32, 24, and 17 targets, respectively, so they may be the most concernful active components of HXP. Quercetin and, at the same time, multiple active components can act on the same target, which proves that these have synergistic effects on the target. Quercetin belongs to flavonol and is one of the six subclasses of flavonoids and has anticancer, anti-inflammatory, and antiviral activities, as well as the effects of reducing lipid peroxidation, platelet aggregation, and capillary permeability . AdditioκB inhibitor α, is an important inhibitor of NF-κB that binds to the NF-κB complex and further inactivates NF-κB by retaining its cytoplasmic localization, which has been proved to promote the development of OA by promoting inflammation, stress, and chondrocyte hypertrophy differentiation [κB signaling, is involved in cartilage formation and differentiation, cell survival, and the production of catabolic enzymes, which exerts antiapoptotic effects on chondrocytes during bone growth and articular cartilage homeostasis [Through the analysis of the core network, some information that may be helpful to explain the effect of HXP is also explained. NFKBIA, NF-ntiation . And RELeostasis . Besideseostasis . MoreoveGo and KEGG analyses further verified the above, especially KEGG analysis, which displayed that IL-17 and TNF were the pathways with high enrichment factors and genes. At present, the research on KOA has found that its pathological and physiological process mainly includes the catabolism mediated by inflammatory cytokines and other mediators, as well as the protective effect of anti-inflammatory cytokines on joint tissue . IL-17 iAngelica sinensis and Salvia miltiorrhiza in the prescription can quicken the blood and dispel stasis and free collaterals vessels and relieve pain; frankincense and myrrh are commonly used in traumatology to quicken the blood and free collaterals vessels and dispel stasis and relieve pain. For KOA, the whole prescription plays the functions of quickening the blood and removing stasis and freeing collaterals vessels and relieving pain. The above network pharmacological analysis of HXP also coincides with the traditional Chinese medicine theory of the action mechanism of HXP drugs. Although all drugs play different roles in the treatment of KOA, most of the components with high connectivity come from Salvia miltiorrhiza, and the traditional Chinese medicine theory will also take Salvia miltiorrhiza, which plays a strong role, as the king medicine of this prescription. The unification of these two theoretical verification results not only provides more favorable evidence for the action mechanism of HXP but also provides new ideas for the follow-up drug research and development.KOA belongs to “knee arthralgia disease” and “bone arthralgia disease” in the category of “arthralgia disease” in TCM. Arthralgia, mostly caused by the feeling excesses of wind, cold, and dampness in muscles, bones, and meridians, manifests the pain, heavy, numbness, and adverse events of limb joints and muscles, whose pathogenesis is stagnation of qi and blood, and the fact the muscles and veins are not be nourished. In traditional Chinese medicine, the obstruction of qi and blood stasis is regarded as “impassability,” and the loss of nourishment of muscles and veins is regarded as “dystrophy.” Both impassability and dystrophy can lead to pain, numbness, and other symptoms. HXP mainly applies the method of promoting blood circulation and removing blood stasis to the main pathogenesis of impassability. Although modern medicine has no final conclusion on the etiology of KOA, most studies have reported that the disease is related to congenital factors, trauma, overweight, postmenopausal changes, lifestyle, work, and so on .β-sitosterol, tanshinone IIA, dihydrotanshinolactone, and so on that achieve therapeutic effects by regulating relevant signals such as inflammatory response, apoptosis, and oxidation reaction, which provides direction and enlightenment for exploring the drug mechanism of HXP. At the same time, this study still has limitations. Firstly, as previously reported, signaling pathways can be cross-regulated with each other, and the pivotal signaling pathways of HXP in the treatment of KOA remain to be explored. Secondly, current research work mainly comes from bioinformatics analysis, thereby future research can be verified by in vitro and in vivo experiments. Finally, due to the limitations of current pharmacological techniques, it is impossible to determine the dose-response relationship between HXP and KOA.This study analyzes the treatment of KOA with HXP through NP, thus revealing that the specific mechanism of drug action may be mainly through effective components such as quercetin, luteolin,


Aquatic bird bornavirus 1 (ABBV-1) is a neurotropic virus that infects waterfowls, resulting in persistent infection. Experimental infection showed that both Muscovy ducks and chickens support persistent ABBV-1 infection in the central nervous system (CNS), up to 12 weeks post-infection (wpi), without the development of clinical disease. The aim of the present study was to describe the transcriptomic profiles in the brains of experimentally infected Muscovy ducks and chickens infected with ABBV-1 at 4 and 12 wpi. Transcribed RNA was sequenced by next-generation sequencing and analyzed by principal component analysis (PCA) and differential gene expression. The functional annotation of differentially expressed genes was evaluated by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The PCA showed that the infected ducks sampled at both 4 and 12 wpi clustered separately from the controls, while only the samples from the chickens at 12 wpi, but not at 4 wpi, formed a separate cluster. In the ducks, more genes were differentially expressed at 4 wpi than 12 wpi, and the majority of the highly differentially expressed genes (DEG) were upregulated. On the other hand, the infected chickens had fewer DEGs at 4 wpi than at 12 wpi, and the majority of those with high numbers of DEGs were downregulated at 4 wpi and upregulated at 12 wpi. The functional annotation showed that the most enriched GO terms were immune-associated in both species; however, the terms associated with the innate immune response were predominantly enriched in the ducks, whereas the chickens had enrichment of both the innate and adaptive immune response. Immune-associated pathways were also enriched according to the KEGG pathway analysis in both species. Overall, the transcriptomic analysis of the duck and chicken brains showed that the main biological responses to ABBV-1 infection were immune-associated and corresponded with the levels of inflammation in the CNS. Bornaviridae family, Orthobornavirus genus 16]. Ther16]. TherTLR1A (binds di- and triacylated lipopeptides), TLR3 (binds dsRNA), TLR4 , TLR7 (binds ssRNA), DHX58  LGP2 and binds to dsRNA), IFIH1 (encodes MDA5 and regulated by DHX58), and TMEM173 (aka STING1 and binds DNA) [TLR4 is commonly known to be activated by bacterial lipopolysaccharide [TLR4 and TMEM173 upregulation in the context of ABBV-1 is not without precedent.The KEGG analysis showed the enrichment of 12 pathways in ducks at 4 wpi, 9 in ducks at 12 wpi, and 10 in chickens at 12 wpi. Seven common KEGG pathways were enriched between all the groups. As with the GO analysis, the KEGG pathway analysis showed the enrichment of pathways mainly related to immune functions or viral infections, with the highest significance in the groups with the most inflammation (the ducks at 4 wpi and the chickens at 12 wpi). Multiple pattern-recognition receptor (PRR) pathways were enriched, including the ‘toll-like receptor-signaling pathway’, ‘NOD-like receptor-signaling pathway’, ‘cytosolic DNA-sensing pathway’, and ‘RIG-I-like receptor-signaling pathway’. The ‘toll-like receptor-signaling pathway’, ‘NOD-like receptor-signaling pathway’, and ‘cytosolic DNA-sensing pathway’ were also enriched in the brains of the rats after infection with BoDV-1 , corrobonds DNA) ,55,56,57ccharide , it can ccharide . TMEM173DDX60, TRIM25, and TRIM14 were differentially expressed in response to ABBV-1 infection and have important roles in either the activation or propagation of the signaling cascades [IRF-7, which then induces the expression of IFN-α/β [IRF-7, IFN-A, STAT1, and STAT2. Similarly, the BoDV-1 infection of rat brains led to the upregulation of IRF-7 and STAT1 transcripts [OASL, RSAD2 (aka viperin), and MX1, all of which possess antiviral activities [Mx1 transcripts, OASL2 transcripts, and Mx1 proteins were also previously found to be upregulated in mice embryos and rat brains infected with BoDV-1 [The activation of PRRs leads to signaling cascades of multiple pathways, involving several proteins. Facilitator genes, such cascades ,60,61,62 IFN-α/β . IFN-α/β IFN-α/β . In our nscripts  and KEGGnscripts . The IFNnscripts . The ISGtivities . Similarh BoDV-1 ,66.p-value adj. 6.503 × 10−22) and ducks at 4 wpi , corresponding with the time points of severe inflammation. However, the statistical significance level of this enrichment was much greater in the chickens at 12 wpi than in the ducks at 4 wpi, which correlates with the enriched GO terms in the chickens associated with B-cell development and humoral immunity. Therefore, IgA production against ABBV-1 proteins was probably stimulated in the chickens and ducks. The BoDV-1 infection of rats also led to the enrichment of the ‘intestinal immune network for IgA production’ KEGG pathway, along with the ‘antigen processing and presentation’ KEGG pathway [The ‘intestinal immune network for IgA production’ KEGG pathway was enriched in both chickens at 12 wpi ( pathway . This fuThe ‘necroptosis’ (or inflammatory cell death) KEGG pathway was enriched in the brains of infected ducks at 4 wpi, when the inflammation was severe. The enrichment of this pathway was further supported by the enrichment of both the ‘influenza A’ and ‘herpes simplex virus 1 infection’ KEGG pathways, as these were two viruses known to modulate necroptosis . NecroptThis study shows that the transcriptomic changes in the brains of both Muscovy ducks and chickens infected with ABBV-1 were driven by the development of non-heterophilic inflammation, as evidenced by histopathology. The majority of highly differentially expressed genes were associated with immune response and cytokine signaling. Additionally, numerous highly differentially expressed novel genes were determined to be lncRNAs. In the groups with high magnitudes of inflammation (the ducks at 4 wpi and the chickens at 12 wpi), the chickens had greater upregulation of the pathways associated with adaptive immune response and B-cell maturation than the ducks.When infection was established, but inflammation was not developed, as in the case of the infected chickens at 4 wpi, the transcriptomic changes were dominated by downregulated genes; however, no functional pathways were significantly enriched. This suggests that the transcriptomic changes caused by ABBV-1 infection alone are of low magnitude, supporting the notion that bornaviruses are not cytolytic and can establish chronic infection without severe cellular derangement.Separating infection from inflammation may be of no use in the context of animal studies. While in vivo studies are needed to model infection in the host, in vitro or ex vivo studies may be better suited to assessing changes in the global transcriptomic profiles caused by ABBV-1, without the confounding effect of superimposed inflammation.


Curcuma aromatica Salisb. rhizome (CASR) has multifunctional characteristics worldwide and a long history of use as a botanical drug with. Currently, it is often used clinically to treat coronary heart disease (CHD) caused by blood stasis syndrome. However, the therapeutic mechanism of CASR in the treatment of CHD remains poorly understood. In study, the main chemical constituents of CASR were analyzed using UPLC-Q-TOF-MS/MS. Then, its potential therapeutic mechanism against CHD was predicted. Subsequently, pharmacological evaluation was performed using CHD rat model. Finally, a lipidomics approach was applied to explore the different lipid metabolites to verify the regulation of CASR on lipid metabolism disorders in CHD. A total of 35 compounds was identified from CASR. Seventeen active components and 51 potential targets related to CHD were screened by network pharmacology, involving 13 key pathways. In vivo experiments showed that CASR could significantly improve myocardial infarction, blood stasis, and blood lipid levels and regulate the PI3K/AKT/mTOR signaling pathway in CHD rats. Lipidomics further showed that CASR could regulate abnormal sphingolipid, glycerophospholipid, and glycerolipid metabolism in CHD rats. The therapeutic mechanism of CASR against CHD was initially elucidated and included the regulation of lipid metabolism. Its effects may be attributed to active ingredients, such as curzerene, isoprocurcumenol, and (+)-curcumenol. This study reveals the characteristics of multi-component and multi-pathway of CASR in the treatment of CHD, which provides a basis for the follow-up development and utilization of CASR. Coronary heart disease (CHD) is caused by various inducements based on abnormal lipid metabolism . Liquid Curcuma aromatica Salisb. rhizome (CASR) is obtained from plants of the genus Curcuma of the Zingiberaceae family. These plants are mainly found in the tropics and subtropics of South and Southeast Asia and largely cultivated in Bengal, China, and Sri Lanka . Finally, a lipidomics approach was applied to reveal the regulation of CASR on lipid metabolism disorders in CHD. The flow chart of this study is shown in Curcuma aromatica Salisb. by Professor Jianwei Chen at the Nanjing University of Chinese Medicine. Vouchers for the sample are available at the Nanjing University of Chinese Medicine.The CASR was collected from Zhejiang, China. The samples were identified as rhizomes of More details could be found in The CASR slices and extracts were prepared as described in a study . FinallyThe treatment method for CASR extracts was based on a previously published article  with somβ-elemene, demethoxycurcumin, curzerene, germacrone, curcumenol, isocurcumenol, curdione, curcumin, and furanodienon) were weighed accurately and dissolved in methanol to form a mixed stock solution (approximately 5 μg/ml).Known amounts of 10 standards . The methods used for the identification and statistical analysis of compounds were similar to the methods used in a previous article .https://tcmspw.com/). The thresholds for OB, DL, and Caco-2 were set to 30%, 0.1, and −0.4, respectively  parameters, including oral bioavailability (OB), drug-likeness (DL), and human Caucasian colon adenocarcinoma (Caco-2) permeability, provided by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform  were used to search potential gene targets of the active compounds. The species was defined as homo sapiens. These target names were converted into official gene symbols using the UniProt database (http://www.uniprot.org/). Duplicates were removed after merging, and the target genes of the active ingredients in CASR were isolated.TCMSP and DrugBank (http://www.genecards.org) and the Online Mendelian Inheritance in Man database (OMIM) to identify targets derived from the literature and tested using experiments. This process did not set any conditions. After removing duplicates, the related targets of CHD were isolated.The keywords “coronary heart disease” were put into the GeneCards database (https://bioinfogp.cnb.csic.es/tools/venny/index.html), which were used as potential targets of CASR against CHD.The overlapping targets of the active ingredients in CASR with the related targets of CHD were determined using Venny 2.1 online software (http://metascape.org/). Official gene symbols were used and homo sapiens was selected. GO enrichment terms included biological processes (BP), molecular functions (MF), and cellular components (CC). A threshold of p < 0.01 was set, and the targets were sorted according to the gene number involved. OmicStudio (https://www.omicstudio.cn/tool) was used to screen and plot top-ranking biological processes and pathways.Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the potential targets of CASR against CHD were performed using the Metascape database  software for the interaction network construction. Additionally, the CytoNCA plug-in was used to calculate topological parameters including “Degree,” “Closeness Centrality,” and “Betweenness Centrality”.n = 8), model group (M) (n = 15), positive drug  control group (P) (n = 8), CASR high-dose treatment group (CASR-H) (n = 8), and CASR low-dose treatment group (CASR-L) (n = 8).Male specific pathogen-free Sprague-Dawley rats (180–200 g) were obtained from the Experimental Animal Center, Hangzhou Medical College, Zhejiang, China (license number: SCXK (ZHE) 2019-0002). The animals were kept in a temperature (25 ± 2°C), humidity (60% ± 5%), and daylight (periodic 12 h light/dark cycle)-controlled room but with free access to standard diet and water. Following 1 week of acclimatization, the rats were divided randomly into a normal control group (NC) . Additional vitamin D3  was administered orally at the 2nd, 4th, 6th, and 8th week, and the same volume of normal saline was administered to the rats in the NC group. For the last 2 days of the 17th week, 30 min after oral administration, M, P, and CASR group of rats were subcutaneously injected (on the back) with isoproterenol hydrochloride (85 mg/kg), once each day. The NC group received the same volume of normal saline. The experimental protocol was in accordance with the Regulations of Experimental Animal Administration issued by the State Committee of Science and Technology of the People’s Republic of China.The CHD model group of rats was fed an HFD combined with vitamin Dus study  with somFrom week 15 of modeling, the drug administration scheme was as follows: CASR-L group was orally administered with CASR extracts at a dose of 0.63 g/kg/d; CASR-H group was orally administered with CASR extracts at a dose of 0.95 g/kg/d; P group was orally administered with atorvastatin calcium tablets at a dose of 2.1 mg/kg/d; other groups were orally administered with the same amount of normal saline. The CASR dosage was converted equally according to the upper and lower limits stipulated in the Chinese Pharmacopoeia (2020 edition) and referred to previous article .During the experimental period, six rats died. Among the 41 rats that survived, 8, 13, 7, 7, and 6 rats belonged to the NC, M, P, CASR-L, and CASR-H groups, respectively. The modelling rate exceeded 84%.−1, 30 s−1, 5 s−1, 1 s−1) and erythrocyte aggregation index (EAI), were measured using the SA-9000 Automated Blood Rheology Analyzer . Serum TC, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were determined using Roche Cobas 8000 c702 . Interleukin-6 (IL-6), oxidized low-density lipoprotein (OxLDL), endothelin (ET), and cardiac troponin I (cTn-I) levels in the serum were determined using the ELISA kits. Plasma was stored at −80°C for lipidomic analysis. Simultaneously, the heart was soaked in 4% PFA and embedded in paraffin. Hematoxylin and eosin (H&E) and Masson’s trichrome (MT) were applied to each of sections (5 µm thick). The histopathological samples were then examined under a light microscope .The rats were euthanized 30 min after the final dose. Serum and plasma samples were immediately collected using the abdominal aortic method. Hemorheological parameters, such as whole blood viscosity (WBV)  was used for the multivariate analysis. Based on the logarithmic transformation (base 10) and Pareto scaling, statistical models were developed for the total ion chromatogram (TIC) normalized data (SERRF). Partial least-squares discriminant analysis (PLS-DA) was used to develop the classificatory/predictive models. Two factors were combined to select the significantly different lipids: (I) p value <0.05; (II) variable importance in projection (VIP) value >1.0.Lipid annotation and data processing methods were used, as described in previous studies . MetaboAp < 0.05.Statistical analysis was performed using the SPSS software . The results were expressed as mean ± standard deviation (SD). Differences between groups were analyzed using unpaired T tests. The significance level was set at A typical TIC of the compounds in CASR is shown in According to ADME screening, 19 candidate compounds were obtained. In addition, 10 compounds with pharmacological activities were combined. For example, curcumin  could reduce lipid levels in the blood and inhibit CHD progression , despiteOverall, 18 of the 29 candidate active compounds yielded 69 targets, according to TCMSP and DrugBank. Furthermore, 7,716 and 200 targets related to CHD were collected using GeneCards and OMIM, respectively. A total of 7,828 targets were collected after merging and removing the duplicates. The interaction of the targets of the active ingredients in CASR and CHD was considered the potential target of CASR against CHD. A total of 51 shared targets were identified.The 51 potential target genes of CASR against CHD were enriched and analyzed using the Metascape database. The results of GO and KEGG pathway analyses are shown in β-elemene. Certain target genes were found to be linked to various pathways. For example, CHRM1 participates in the neuroactive ligand-receptor interaction pathway, calcium signaling pathway, cholinergic synapse, and PI3K-Akt signaling pathway, whereas GABRA1 is involved in the neuroactive ligand-receptor interaction and retrograde endocannabinoid signaling pathway. These results suggest that CASR acts on CHD through a multitarget, multipathway, and integrative manner.Based on the results of the analysis, we predicted the specific mechanism of CASR against CHD. A global view of the active ingredient-target-pathway network, including 79 nodes  and 197 edges, was constructed . A complHistopathological characteristics of CHD rats are shown in p < 0.01) than in the NC group, indicating that the rats in the M group were in a serious state of blood stasis. However, the hemorheological parameters of the rats in each treatment group decreased significantly (p < 0.01). The results of the P group were close to that of the NC group and that of the CASR-H group was more significant.The hemorheological parameters of rats are shown in The results for serum lipids and cardiac marker enzymes are summarized in To further investigate the mechanism of CASR in the treatment of CHD, the combined results of the KEGG enrichment analysis in network pharmacology prediction and the expression analysis of PI3K/AKT/mTOR signaling pathway components was verified. The expression of the key genes PI3K, AKT, Bcl-2, TP53, NOS3, and mTOR in this pathway was detected using RT-qPCR. The mTOR pathway was related to lipid metabolism. As shown in The method was validated as described in a previous article . The relTICs of the samples from the positive and negative ion modes are shown in In the positive ion mode, 422 lipids were identified, mainly containing acylcarnitine (CAR), cholesteryl ester (CE), and diacylglycerol (DG). In the negative ion mode, 154 lipids were found, mainly containing bile acid (BA), ceramide (Cer), and cardiolipin (CL). To summarize, 576 lipids from plasma samples were identified.p < 0.05), validating the model  screened. Among them, 44 were regulated after CASR administration (28 in the positive ion mode and 16 in the negative ion mode). The 44 differentially expressed lipids are shown in A total of 265 differential lipids with the criteria of p < 0.05). SM 34:2; 2O was the most downregulated lipid in SM, LPC 20:1/0:0 was the most upregulated lipid in LPC, FA 20:5 was the most upregulated lipid in FA, and PC 32:0; 3O|PC 16:0_16:0; 3O was the most downregulated lipid in OxPC.In addition, enrichment analysis was beneficial for obtaining mechanistic insights into the lipids. As shown in Further analysis performed on the metabolic network  to underin vivo detection and analysis methods for compounds in CASR were based on our previous study -limonene were not detected.Among the eight core compounds listed in us study . The corIn the network pharmacology analysis, GO enrichment analysis revealed that CASR against CHD is involved in a number of biological processes, such as circulatory processes, response to steroids, and phospholipase C activating G protein-coupled receptor signaling pathway, which are directly related to the pathogenesis of CHD . The KEGβ-elemene, curzerene, demethoxycurcumin, curzerenone, isoprocurcumenol, furanodiene, (+)-curcumenol, and (+)-limonene, interacted on an average with 10 targets. They have been shown to exert protective effects against cardiovascular diseases. For example, furanodiene, demethoxycurcumin, and (+)-curcumenol exhibit anti-inflammatory activities (β-elemene could improve atherosclerosis by restoring nitric oxide (NO) levels and alleviating oxidative stress, which is associated with CHD -limonene, curzerene, furanodiene, germacrone, isoprocurcumenol, isocurcumenol, actility . Each siIn the pharmacological evaluation, the results of the model group were consistent with those of many clinical studies , indicatCASR was proved to improve dyslipidemia of CHD model. The present results showed that after treatment with CASR, the lipids recalled included SM, LPC, FA, and OxPC. Among these lipid compounds, the most significant callbacks were observed in SM 34:2; 2O, LPC 20:1/0:0, FA 20:5, and PC 32:0; 3O|PC 16:0_16:0; 3O, which are presumed to be biomarkers for the regulation of lipid metabolism in CHD by CASR. The metabolic network revealed that CASR plays a major role in CHD treatment through three metabolic pathways: sphingolipid metabolism, glycerophospholipid metabolism, and glycerolipid metabolism. Noteworthily, the sphingolipid signaling pathway is a shared pathway between network pharmacology and lipidomics results. Sphingolipids are key components of organelles and cell membranes, which regulate cell growth, differentiation, and senescence . They include ceramide, sphingomyelin, and sphingosine 1-phosphate. Ceramide is the core of sphingolipid metabolism, and sphingolipid metabolism revolves around its synthesis and decomposition . The levIn addition, through correlation analysis, it was found that curzerene, isoprocurcumenol and (+)-curcumenol reduced blood viscosity, improved blood lipid levels, and reduced vascular endothelial damage. Furanodiene was responsible only for regulating blood lipid levels and vascular endothelial function. Curzerenone was only responsible for reducing blood viscosity. The above results also show that the CASR has multicomponent and multieffect characteristics.In view of the unclear therapeutic mechanism of CASR against CHD, this study clarified that CHD regulates the PI3K/AKT/mTOR signaling pathway. This in turn regulates downstream sphingolipid metabolism and improves abnormal lipid levels and hemorheology. A reduction in vascular endothelial injury, inflammatory reactions, and lipid deposition was observed using UPLC-Q-TOF-MS/MS, network pharmacology, lipidomics, and RT-qPCR, in the treatment of CHD with CASR. In addition, curzerene, isoprocurcumenol, and (+)-curcumenol were identified as the main active compounds and are expected to be potential novel drugs for treating CHD. The results also showed the multicomponent and multipathway characteristics of CASR in the treatment of CHD.


Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen’s essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri. Shigella flexneri is a gram-negative bacterium that belongs to the family Enterobacteriaceae. The genus Shigella can be classified into 4 species: Shigella flexneri, Shigella boydii, Shigella sonnei and Shigella dysenteriae. The species can be further diversified into different serotypes dependent on biochemical contrasts and variety of O-antigen. S. flexneri is separated into 13 serotypes. Shigellosis is an increasing cause of concern in developing nations as it causes more than 170 million estimated deaths each year, with the primary victims being children below 5 years of age [S. flexneri is one of the most lethal organisms afflicting developing countries [Shigella species attack the epithelium of the colon and rectum in primates and people, causing the intense aggravation of the mucosa which is associated with shigellosis. Without compelling medications, shigellosis patients may develop auxiliary conditions, for example, septicaemia, pneumonia and haemolytic uremic disorder. The increased prevalence in developing countries is due to lack of food and water hygiene. The pathogenesis of S. flexneri is rapid in the system, as once it enters the colonial epithelium, it leads to very severe inflammation in the mucosal region. Traditional treatment of the disease condition begins with rehydration and antibiotics. However, there have been numerous reports in the last decade that the strain has become multi-drug resistant [3Shigella has acquired plasmid-encoded resistance to the traditional drugs provided to patients as the first line of treatment. Hence, newer approaches and research must be undertaken to combat the increasing drug resistance.ountries . The modsistant 3. Over thWith the advent of the post-genomic era, since the human genome project was completed successfully, there has been a revolution in the development of drug-designing approaches. The experimental approaches for drug designing are time consuming and costly. Host pathogen interactions can be studied by identifying the non-homologous proteins for host and pathogens. These proteins can be treated as targets in the drug discovery process. Pathway analysis using comparative methods has been the most sought-after approach in the last decade. A number of studies have been published in the past with reference to different pathogens on the basis of metabolic pathway analysis and protein-protein interaction studies -11. HoweA schematic representation of the methodology is given in Homo sapiens and the pathogen S. flexneri. Pathways were then manually compared to identify those that were unique only to the pathogen. The criterion for selecting the pathways was based on whether the pathway was not present in the host. human but was present in the pathogen and unique to S. flexneri. The identification numbers of all metabolic pathways from both organisms were extracted from the database. A manual comparison was then conducted by placing the name of each individual pathway of the pathogen against the pathways of the host, H. sapiens. According to the KEGG database annotations, pathways that were absent in humans but did appear in the pathogen were considered unique to S. flexneri. Further, the enzymes that were involved in these unique pathways were extracted from the KEGG database and sequence retrieval was done from the NCBI database in the FASTA format.The extraction of the metabolic pathways was done using the KEGG  pathway Protein sequences extracted in the FASTA format which were part of the unique pathways were submitted to the Geptop tool  to identFunctional interactions take place between genes/proteins and provide fundamental knowledge for cellular processing and systematic characterization, which play a vital role in molecular systems biology . The PPISubcellular localization of the essential non-human proteins selected from network analysis was predicted by PSORTb v3.0.2  and CELLShigella flexneri are ideal as drug candidates. Two-step methodology was performed. to analyze the drug targets identified through the work. As the first step, the DAVID Functional Annotation Tool was used for Gene Ontology analysis [Novel drug targets of analysis ,25. The analysis , threshoS. flexneri. Metabolic pathways that are available in both the host and the pathogen are distinguished as normal pathways and those which are available as having pathogenicity and not in the host are deemed as novel pathways. A total of 85 metabolic pathways were extracted from the pathogen and among these 26 metabolic pathways  purine-rich sequence. Part of the 30S ribosomal subunit such as some nascent polypeptide chains can cross-link to this protein. Also, 50S ribosomal protein L23 is the underlying gathering protein and ties with the 23S rRNA. This protein target frames the center docking site as a requisite to bind with ribosome. One of the early assembly proteins, it binds 23S rRNA. It is an important target since it is one of the proteins that surrounds the polypeptide exit tunnel on the outside of the ribosome and forms the main docking site for trigger factor binding to the ribosome. It is an important contact for protein L29, and trigger factor when it is bound to the ribosome. The main function of DNA-directed RNA polymerase subunit alpha is to catalyze translation of DNA into RNA utilizing four ribonucleoside triphosphates as substrates. DNA-dependent RNA polymerase catalyzes the transcription of DNA into RNA using the four ribonucleoside triphosphates as substrates and is a homodimer. The RNAP catalytic core consists of 2 alpha, 1 beta, 1 beta' and 1 omega subunit. When a sigma factor is associated with the core the holoenzyme is formed, which can initiate transcription. The N-terminal domain is essential for RNAP assembly and basal transcription, whereas the C-terminal domain is involved in interaction with transcriptional regulators and with upstream promoter elements. Elongation factor P is mainly engaged with the synthesis of peptide bonds and reduces ribosome, slowing down protein which requires change of Lys-34. Elongation factor Ts is linked with the EF-Tu. GDP complex prompts the trading of GDP to GTP. It stays bound to the aminoacyl-tRNA.EF-Tu.GTP complex up to the GTP hydrolysis stage on the ribosome. Elongation factors are proteins that perform significant roles during the elongation cycle of protein biosynthesis on the ribosome. They alleviate ribosome pausing at polyproline (PPX) motifs by enabling peptide bond formation. In the absence of these proteins, PPX peptide bond formation can limit translation rate, leading to pleotropic phenotypes with slowed growth, increased antibiotic sensitivity, and loss of virulence. Hence, these proteins are the key targets of several antibiotics. Cell division protein FtsQ is a fundamental cell division protein. It performs a key role in the assembly of the divisome, a large protein complex that regulates bacterial cell division. It formulates a stable trimeric complex with FtsB and FtsL, which is essential for successful cell division [The present study focused on subtractive genome analysis  that leddivision , 28. TheShigella flexneri is a gram-negative bacterium that is a member of the family Enterobacteriaceae. It is the most endemic species and the most lethal for developing countries. Traditional treatment of the disease condition begins with rehydration and antibiotics. However, there have been numerous reports in the last decade suggesting that the strain has become multi-drug resistant. Over the last decade, Shigella has acquired plasmid-encoded resistance to the traditional drugs that were provided to patients as the first line of treatment. Here, we employed comparative metabolic pathway analysis for the identification of essential enzymes for the survival of the bacteria and based on our prediction we are able to propose potential drug targets for the pathogen. In conclusion, we can suggest five essential enzymes, elongation factor P, DNA-directed RNA polymerase subunit alpha, 30S ribosomal protein S1, 50S ribosomal protein L23 and elongation factor Ts as the best putative drug targets against the pathogenesis of Shigella flexneri and cell division protein FtsQ as the vaccine drug targets against all strains of Shigella . To the best of our understanding, the research outcome from our work could highlight a novel approach and identify drug targets to overcome the infection caused by the pathogen. In the future, whole genome proteome sequence data can be retrieved for all the strains of Shigella and further core proteomic analysis can be performed for the dataset, leading to improved and more enhanced applications of this work.http://jmb.or.kr.Supplementary data for this paper are available on-line only at


Quininic acid is an important intermediate for synthesis of a variety of raw chemical materials and drugs. Gallic acid and catechol receive widespread attention as pharmaceutical intermediates. It is one of the hotspots to accumulate many kinds of target products by rationally modifying the shikimate pathway and its branches in recombinant strains by means of metabolic engineering. This review considers the effects of classical metabolic engineering methods, such as central carbon metabolism (CCM) pathway modification, key enzyme gene modification, blocking the downstream pathway on the shikimate pathway, as well as several expansion pathways and metabolic engineering strategies of the shikimate pathway, and expounds the synthetic biology in recent years in the application of the shikimate pathway and the future development direction.The shikimate pathway is a necessary pathway for the synthesis of aromatic compounds. The intermediate products of the shikimate pathway and its branching pathway have promising properties in many fields, especially in the pharmaceutical industry. Many important compounds, such as shikimic acid, quinic acid, chlorogenic acid, gallic acid, pyrogallol, catechol and so on, can be synthesized by the shikimate pathway. Among them, shikimic acid is the key raw material for the synthesis of GS4104 (Tamiflu Apicomplexa parasites  regulated by the same promoter (Ptac) in the RBS libraries applied in C. glutamicum RES167ΔaroK. The results showed that SA products by C. glutamicum RES167Δarok strain with a genetic module (4.3 g/L) were 54 times higher than that by the non-genetic module strain (80 mg/L), during fermentation in flasks (250 mL)  in P. aeruginosa PAO1 was heterogeneously expressed in the transformed pTrc-ant3 plasmid, and a new pathway for catechol production was reconstructed. Catechol titer in a bioreactor culture was 4.47 g/L with 16% yield [In one study, 6% yield .The process of production of catechol from glucose can be used to design and improve the process of biosynthesis of organic compounds derived from catechol. For example, catechol can be completely converted into muconic acid (389 mg/L) by expressing heterologous AntDO and catechol 1,2-dioxygenase .The SA pathway is a common pathway for aromatic amino acid synthesis and widely exists in plants and microorganisms. The important intermediary products in this pathway are of great value. Besides exhibiting extensive medicinal value, SA is the raw material for the synthesis of various alkaloids, aromatic amino acids, indole derivatives and chiral drugs; 3-dehydroshikimic acid exerts great antioxidant effects and is the raw material for the synthesis of catechol, GA, and other important chemical products; and QA derived from 3-dehydroquinic acid can be used as a food additive, a cosolvent, and an optical material. Moreover, pyrogallol and chlorogenic acid synthesized via an artificial pathway derived from the shikimate pathway are widely used in various fields. There is a growing demand for these intermediates and their derivatives.E. coli and sometimes in C. glutamicum and B. subtilis, because non-model microbes are expensive, and the development of new genetic tools is time-consuming. The main metabolic engineering methods include: (1) blocking the downstream pathway of the target product to increase product accumulation; (2) modification of the CCM pathway by modifying the PTS and or overexpressing or inactivating related genes to increase the supply of the starting substrates, PEP and E4P pathways; (3) reducing by-product formation to enhance product yield and titer; (4) overexpressing or inactivating key enzyme-encoding genes to relieve feedback inhibition; (5) introducing heterogenic genes to expand metabolic networks, and (6) performing modularization transformation. To date, classical metabolic engineering methods have achieved good results; for instance, the construction of the recombinant E. coli SP1.1 PTS/pSC6.090B strain by Chanderan et al. resulted in an SA titer of 87 g/L with a yield of 0.36 mol/mol [As shown in  mol/mol . The use mol/mol . It is aMetabolic engineering for the synthesis of complex compounds with high value, via catalysis of simple compounds has rapidly developed. In recent years, a strategy for modular metabolic network regulation, multivariate modular metabolic engineering (MMME), was developed by metabolic engineering researchers . This stC. glutamicum has been constructed. This biosensor can specifically respond to intracellular SA concentration and detect extracellular SA when co-expressed with the shiA gene, thus achieving high-throughput screening of C. glutamicum with high SA production [E. coli SA-GS-2-7, which can produce 24.64 g/L SA from sucrose in a yield of 1.42 mol/mol [Furthermore, a biosensor is a kind of instrument that converts the concentration of bioactive substances into electrical signals. It has the characteristics of signal amplification, high accuracy, high sensitivity, and strong specificity. It has been used for the dynamic regulation of metabolic pathways, real-time monitoring of metabolites, high-throughput screening of engineering bacteria, etc., which makes people more effectively realize the optimal combination of various genetic modules. Recently, a novel SA biosensor based on the LysR-type transcriptional regulator (ShiR) of oduction . This me mol/mol . This alIt is a great idea to produce as many products as possible through bioengineering, but according to the findings of this paper, the limitations of classical metabolic engineering have greatly hindered this process. However, metabolic engineering has been constantly evolving during the past twenty years. With the combination of synthetic biology and systems biology, the concept of systems metabolic engineering has also emerged spontaneously . Reshapi