Rhodococcus sp. AD45, and an alternative model organism has yet to be characterised. Here, we report the characterisation of a novel Gram-negative isoprene-degrading bacterium, Variovorax sp. WS11. Isoprene metabolism in this bacterium involves a plasmid-encoded iso metabolic gene cluster which differs from that found in Rhodococcus sp. AD45 in terms of organisation and regulation. Expression of iso metabolic genes is significantly upregulated by both isoprene and epoxyisoprene. The enzyme responsible for the initial oxidation of isoprene, isoprene monooxygenase, oxidises a wide range of alkene substrates in a manner which is strongly influenced by the presence of alkyl side-chains and differs from other well-characterised soluble diiron monooxygenases according to its response to alkyne inhibitors. This study presents Variovorax sp. WS11 as both a comparative and contrasting model organism for the study of isoprene metabolism in bacteria, aiding our understanding of the conservation of this biochemical pathway across diverse ecological niches.Plant-produced isoprene  represents a significant portion of global volatile organic compound production, equaled only by methane. A metabolic pathway for the degradation of isoprene was first described for the Gram-positive bacterium  WS11 by marker exchange mutagenesis according to Schäfer et al. [isoA were synthesised by Q5 high-fidelity polymerase  using primers isoA_up_F (5′-ATCAGGATCCCATGGGCCCGGACATCCCATTCG-3′)/isoA_up_R (5′-TGACTCTAGACGGCAGAAGCGGCTCTGCATCG-3′) and isoA_down_F (5′-ATCATCTAGAACATGGCGCAGACCTACC-3′)/isoA_down_R (5′-CTTAAAGCTTGATCGGCACCGTACACTC-3′) using Variovorax sp. WS11 genomic DNA as the template. Each region was cloned into pK18mobsacB and a gentamicin resistance cassette was excised from p34S-Gm [XbaI site between the isoA flanking regions. Variovorax sp. WS11 was prepared for electroporation according to Pehl et al. [Variovorax sp. WS11 was grown in 50 mL culture using 10 mM glucose as the sole source of carbon and energy to an OD540 of 0.6, chilled at 4 °C for 48 h, then washed twice in chilled distilled water and finally resuspended in 1 mL of 10% (v/v) glycerol. Then, 100 μL aliquots were transformed by electroporation with 100 ng of the above construct, with pBBR1MCS-2 acting as a control for transformation efficiency. Exponential decay electroporation was used at 2.5 kV, 2.5 μF, 200 Ω in a 2 mm gap cuvette. Cells were allowed to recover for 3 h in 1 mL Ewers medium containing 10 mM glucose, pre-warmed to 30 °C for recovery, cultures were maintained at 30 °C and shaken at 160 rpm. Transformed cells were then plated onto Ewers agar containing 10 mM succinate and 50 μg/mL kanamycin, incubated at 30 °C for 1 week to select for single-crossover of the suicide construct into the genome. The pK18mobsacB backbone was removed from the genome by a second recombination event, selected for by spreading cells on Ewers agar containing 10 mM succinate, 10 μg/mL gentamicin and 5% sucrose (w/v), incubated at 30 °C for 5 days. Deletion of isoA was confirmed by loss of kanamycin resistance with concomitant maintenance of gentamicin resistance, as well as verification by PCR using primers aacC1_F (5′-TCGTGAGTTCGGAGACGTAG-3′)/isoB_R (5′-ACGTCGAAGCACTCCATCTC-3′).r et al. . Regions p34S-Gm  and ligal et al.  with miniso metabolic cluster was restored by complementing the mutant with pBBR:isoAp:isoA-F plasmid. The sequence including isoA-F with 256 bp of its native flanking region was generated by PCR using isoAprom_fwd(5′-ATCAGGTACCTTCCGACATCGATCGCGCAACC-3′) and isoFprom_rev(5′-TGATGGATCCCGATGGCGATCAGCTCGTAGTG-3′) under the assumption that the promoter would be located within the flanking region. The resulting product was digested with KpnI and BamHI. pBBR1MCS-2 [KpnI and BamHI and dephosphorylated using FastAP thermosensitive alkaline phosphatase . Both vector and digested PCR product were cleaned using a HighPure PCR product purification kit  and ligated together with T4 DNA ligase (Thermo Scientific). The resulting mixture was used to transform E. coli Top10. Prepared plasmid DNA was sequenced and used to transform Variovorax sp. WS11 ∆isoA as described earlier. Colonies were grown in Ewers medium containing 10 mM succinate and then sub-cultured into Ewers medium containing 1% (v/v) isoprene.Function of the BR1MCS-2  was digeVariovorax sp. WS11 ∆isoA was grown to an OD540 of 0.6 in 50 mL Ewers medium containing 10 mM succinate. Cells were centrifuged at 7000× g for 10 min and washed in an equal volume of 50 mM HEPES, pH 6.0. Three replicate cultures were resuspended in 50 mL Ewers medium without a carbon source and starved for 2 h at 30 °C with shaking at 160 rpm. Three biological replicates were spiked with 10 mM succinate, 1% isoprene, or 0.1% (v/v) epoxyisoprene and incubated for a further 2 h before extracting RNA using a hot phenol extraction method [isoG was amplified by qisoG_F (5′-AAGACCATGAGCAACCAGGA-3′) and qisoG_R (5′-GCCGTTGTTCTCGACTTCAA-3′), and rpoB as a reference gene was amplified by qrpoB_F (5′-TGCAGGCCATTTACACCAAC-3′), qrpoB_R (5′-TTGAACTTCATGCGACCGAC-3′). Changes in iso gene expression were calculated relative to the rpoB reference gene according to the comparative CT method, and further analysed by comparison of normalised CT values between each carbon source [n method . SamplesVariovorax sp. WS11 was grown in triplicate in 20 mL Ewers medium containing 1% (v/v) isoprene, 10 mM glucose or 10 mM glucose + 1% isoprene. Cells were harvested by centrifugation at 7000× g for 10 min and resuspended to an OD540 of 10.0 in 1 mL HEPES, pH 6.0. Cell suspensions were sealed in 30 mL vials with butyl rubber stoppers and pre-heated to 30 °C in a water bath, shaken at 160 rpm for 3 min before adding 300 ppmv isoprene. After incubation for 1 min, 50 μL of headspace gas was sampled using a gas-tight syringe  and isoprene was measured using a Fast Isoprene Sensor  at 3 min intervals for 1 h. Depletion of isoprene was used to calculate the rate of isoprene uptake by cells grown under each condition.Variovorax sp. WS11 was prepared for RNA extraction by growing in 50 mL Ewers medium in 120 mL vials using the same substrate combinations described above. Cells were harvested at an OD540 of 0.6 by centrifugation at 7000× g for 10 min, then total RNA was extracted as described above. isoA was amplified using qisoA_F (5′-GATGTCTCGTTCTGGCGTTC-3′), qisoA_R (5′-ACCCGTAGTCCTTCATCGTG-3′). Expression of isoA under each growth condition was calculated relative to expression of rpoB.Variovorax sp. WS11 was grown in 2 litre flasks in 400 mL Ewers medium containing either 10 mM glucose or 10 mM succinate as the sole source of carbon and energy. Cells were grown to an OD540 of 0.6, harvested by centrifugation at 7000× g for 10 min and resuspended in 4 mL of 50 mM HEPES, pH 6.0. Cells were drop frozen in liquid nitrogen and stored at −80 °C until required. Variovorax sp. WS11 was grown in 4 litres of Ewers medium using isoprene as the sole source of carbon and energy in a 4 litre working volume fermentor  with constant maintenance of optimal growth conditions  and air flow (2.4 L/min). Isoprene was supplied by bubbling air (1 mL min−1) through a small volume of liquid isoprene contained in a 30 mL vial, held at 0 °C on ice  of acetylene (4.1 × 10−4 mol/m3 Pa), propyne (9.3 × 10−4 mol/m3 Pa), and butyne (5.4 × 10−4 mol/m3 Pa) [v/v) in dimethyl sulfoxide (DMSO). Variovorax sp. WS11 was used for isoprene uptake assays at an OD540 of 1.0 in 1 mL HEPES . Isoprene-grown cells were placed in 30 mL serum vials sealed with butyl rubber stoppers and pre-warmed for 3 min at 30 °C, with shaking at 160 rpm. The 300 ppm isoprene was added and Variovorax sp. WS11 was incubated for a further 1 min before sampling 50 μL headspace as previously described. Samples were taken at 5 min intervals for 45 min. Alkynes were added (to an aqueous concentration of 50 μM) as gases to the headspace or as concentrated stock in DMSO immediately after sampling timepoint 3. The inhibited rate (timepoints 5–10) was calculated relative to the initial rate of isoprene oxidation (timepoints 1–3). Samples without alkyne and with DMSO alone were used as controls. Each assay was performed using three biological replicates. With the exception of C6–C8 alkynes, results are reported as the mean of these three replicates ± standard deviation. C6–C8 alkynes were presented as the mean inhibition by DMSO (1.4 ± 7.2%) subtracted from the mean inhibition by alkyne ± standard deviation about the means.C2–C4 alkynes were added from gaseous stocks. Gas–liquid partitioning was calculated according to the Henry’s Law constants (l/m3 Pa)  to enablMethylococcus capsulatus (Bath) was grown in a 2 litre fermentor  using methane as the sole source of carbon and energy as previously described [escribed , with thescribed . Cells wescribed . Alkyne isoA-F was amplified by Q5 high-fidelity polymerase using primers isoA_fwd (5′-ATGAACATGTCCTTGCTGAGCCGAGACGACTG-3′) and isoF_rev (5′-ATCAGGATCCCGATGGCGATCAGCTCGTAG-3′). The purified PCR product was digested with BamHI and PciI and ligated with pTipQC1 [BamHI and NcoI. The resulting vector (pTipQC1:iso11) was used to transform Rhodococcus sp. AD45-id [Rhodococcus sp. AD45-id containing either pTipQC1 or pTipQC1:iso11 was grown in 120 mL serum vials sealed with butyl rubber stoppers, in 20 mL Ewers medium containing 10 mM succinate to an OD540 of 0.6 and induced with 1 µg/mL thiostrepton (prepared as 20 mg/mL stock in DMSO). Induced cells were incubated for 16 h at 30 °C with shaking at 160 rpm and then centrifuged at 7000× g for 10 min. Pellets were resuspended to an OD540 of 10.0 in 50 mM phosphate buffer (pH 7.0). Cells were tested for isoprene consumption using the Fast Isoprene Sensor as described earlier. Three biological replicates were used for each assay. pTipQC1  that had AD45-id  by elect AD45-id . IsoMO e AD45-id . In brieVariovorax sp. WS11 have been deposited at DDBJ/ENA/Genbank under the accession JAAGOW000000000. The version described in this paper is version JAAGOW010000000. The genomic nucleotide sequence of Ramlibacter sp. WS9 is available under accession number NZ_RKMB00000000.The chromosomal and megaplasmid sequences of Variovorax sp. WS11 was previously isolated from willow soil samples by continuously enriching in the presence of 25 ppmv isoprene, as a comparatively low concentration [Variovorax sp. WS11 was one of two Gram-negative isoprene-degrading bacteria isolated from this environment, together with Ramlibacter sp. WS9 [Variovorax. Phylogenetic analysis of the 16S rRNA gene of Variovorax sp. WS11 indicates that it is most related to Variovorax sp. RA8  [The genome of Platform . Two megPlatform . The GC ectively . Of 593005/2019) ,66. RASTVariovorax sp. WS11. One such gene cluster was predicted to encode a methanesulfonate monooxygenase (msmABCD), located on the chromosome, which resembled the well-characterised msm cluster of Methylosulfonomonas methylovora [26-CXXH) within msmA [msmB, predicted to encode the hydroxylase β-subunit, was located immediately downstream of msmA  (nagAa) and a ferredoxin (nagAb) (nagAcAd) to salicylate comprising the upper part of the pathway [nahAa-nahAD) [Variovorax sp. WS11 made it unlikely for growth on salicylate or naphthalene to occur, and neither 5 mM naphthalene or 5 mM sodium salicylate supported growth of Variovorax sp. WS11  . Each pu (nagAb) . Salicyl pathway . The laca-nahAD)  in the gsp. WS11 .iso metabolic genes of Rhodococcus sp. AD45 as tBLASTn query sequences, putative iso metabolic genes were located on a single gene cluster on megaplasmid 1 in Variovorax sp. WS11  [Gordonia rubripertincta CWB2 also involves glutathione [Variovorax spp. produce glutathione as a core metabolic process, and all predicted glutathione biosynthesis genes are located on the chromosome. It was predicted that Rhodococcus sp. AD45 gained the genes required for glutathione biosynthesis (gshAB), located in the iso metabolic gene cluster  compared to only 26.1% amino acid identity with aldH2 (69% coverage), predicted to encode a 4-hydroxymuconic semialdehyde dehydrogenase [aldH1 and aldH2 in isoprene metabolism are currently unconfirmed, although the tadD gene of Rhodococcus sp. PD630, which shares 81% amino acid identity with aldH1 of Rhodococcus sp. AD45 [Rhodococcus sp. AD45 contains two putative regulatory genes annotated as marR, with only the divergently transcribed marR2 being upregulated in response to isoprene [marR homolog in Variovorax sp. WS11 also resides on megaplasmid 1 but is 200 kbp in distance from the iso gene cluster. Instead, two putative LysR-type transcriptional regulators, annotated as dmlR, are divergently transcribed from the iso cluster in Variovorax sp. WS11  ,23,24. Ttathione . In comm cluster , by hori sp. WS9 , while Rrogenase ,75. The sp. AD45 . Rhodocosp. WS11 , suggest.004 h−1 . Secondloxus EPS , we set isoA-F in Rhodococcus sp. AD45-id, a strain cured of the megaplasmid containing the isoprene gene cluster, which is therefore unable to metabolise isoprene [isoA-F) from Variovorax sp. WS11 were cloned into the Rhodococcus expression vector pTipQC1 [Rhodococcus sp. AD45-id containing pTipQC1:iso11 were capable of oxidising isoprene at 38% of the wild-type rate when induced, in contrast to cells transformed with pTipQC1 without an isoA-F insert (data not shown), confirming that the iso metabolic gene cluster identified in Variovorax sp. WS11 was active. Functional confirmation of putative isoprene monooxygenase-encoding genes has previously been achieved by expression of isoprene . The Iso pTipQC1 , under tVariovorax sp. WS11, targeted mutagenesis was used. Deletion of isoA abolished all growth on isoprene  and epoxyisoprene (146-fold) after 2 h of exposure to the inducing substrate  are oxidised. The same is observed for cyclohexene and methyl-cyclohexene, with activity only being observed in the branched derivative. SDIMOs are typically capable of oxidising a wide range of organic substrates. The substrate specificity of IsoMO was investigated by comparing the substrate oxidation profile of  alkenes . The subropylene . A consiMethylococcus capsulatus (Bath) was completely inhibited by relatively low concentrations of acetylene [M. capsulatus (Bath) decreased with increasing carbon chain length [Alkynes have been known to act as inhibitors of SDIMO activity for many years. Methane oxidation by the soluble methane monooxygenase (sMMO) of cetylene ,79, and n length . TherefoVariovorax sp. WS11. The rate of isoprene oxidation was decreased by 6.5% by 50 μM acetylene, demonstrating that acetylene is a significantly less potent inhibitor of IsoMO than of sMMO (Alkynes (C2–C8) were tested for their ability to inhibit isoprene oxidation by IsoMO in  of sMMO . Inhibit of sMMO . DMSO haMethylococcus capsulatus (Bath) was selected as a comparative SDIMO for inhibition by alkynes due to the pre-existing knowledge of the potency of acetylene as an inhibitor of this sMMO [Methylocella silvestris BL2 has previously been reported to co-oxidise isoprene [M. capsulatus (Bath) was tested and confirmed to co-oxidise isoprene with an initial rate of 1.38 ± 0.15 nmoL/min/mg dry weight. A total of 50 μM acetylene and 50 μM octyne were the least potent and most potent inhibitors (respectively) of isoprene oxidation by the IsoMO of Variovorax sp. WS11 under the conditions tested (The sMMO from his sMMO ,79, and isoprene , althougs tested  and weres tested . These dVariovorax sp. WS11. The genetic tractability of this model organism was demonstrated, and the use of a Gram-negative isolate may aid in the functional characterisation of the downstream steps of the isoprene metabolic pathway, such as the function of isoG, isoJ, and aldH. The iso metabolic gene cluster in Variovorax sp. WS11 was located on a megaplasmid, suggesting that this second well-characterised iso gene cluster was acquired through horizontal gene transfer. The iso metabolic gene cluster displayed significant variation from the original model of Rhodococcus sp. AD45, such as the lack of duplications of isoGHIJ and aldH, and the lack of glutathione biosynthesis genes. Functionality of isoA-F was confirmed by expression in Rhodococcus sp. AD45-id, and the dependency of Variovorax sp. WS11 on iso genes was confirmed by knockout of isoA. Two putative LysR-type transcriptional regulators may play a role in regulating isoprene metabolism and remain the subjects of further study. IsoMO oxidised a wide range of alkenes, with a tendency to display increased activity with branched hydrocarbon chains when compared to their unbranched counterparts. Inhibition of isoprene oxidation by 50 μM acetylene and 50 μM octyne differed significantly between IsoMO and sMMO. An estimated 2.4 million tons of isoprene are degraded each year by soils [This study describes the genetic and biochemical characterisation of a new model bacterium for isoprene degradation, the Gram-negative bacterium by soils ,19. The


Background: Structure-activity relationships describe the relationship between chemical structure and biologic activity and are capable of informing deliberate structural modifications to a molecule in order enhance drug properties. Methods: Here, we present a subtle, yet unique twist on structure-activity relationships in which a collective biologic activity was measured among five cinnamon constituents with a shared phenylpropanoid template . This template-based approach utilized publicly available transcriptomic data through the Gene Expression Omnibus (GEO) to identify a fundamental biologic effect; in essence, a phenylpropanoid template effect. Results: The recurrent identification of cytokine-cytokine receptor interaction and neuroactive ligand receptor pathways in each individual treatment condition strongly supports the fact that changes in gene expression within these pathways is a hallmark of the phenylpropanoid template. With a template effect identified, future structural modifications can be performed in order to overcome pharmacokinetic barriers to clinical use . Moreover, these modifications can be implemented with a high degree of confidence knowing that a consistent and robust template effect is likely to persist. Conclusion: We believe this template-based approach offers researchers an attractive and cost-effective means for evaluating multicomponent natural products during drug development. In recent years, there has been a renewed interest in the utilization and evidence-based use of natural products in conventional medicine practices . Major cHowever, despite the array of diverse molecular structures, cinnamon constituents are purported to possess remarkably similar and broad therapeutic benefits. For example, cinnamic acid derivatives have been shown to possess anti-inflammatory, antioxidant, anti-microbial, and neuroprotective activities ,4,5. In Rather than evaluating individual agents for activity, this work sought to identify a robust template effect first, which could then be modified to improve pharmacokinetic parameters. Based on the fact that the phenylpropanoid template exists within all five of these cinnamic acid-like derivatives, we sought to examine to what extent the phenylpropanoid template guides pharmacologic effects. In other words, by deconstructing five molecules to their phenylpropanoid template, we might reveal important characteristics based on their foundational structural design. If common characteristics could be identified, reverse engineering could then be utilized to improve the potency and pharmacokinetic profile of the template, thus allowing researchers to simplify the complexities associated with the specific characteristics of each individual compound. Ultimately, this study hopes to present a potential approach to overcome the barriers that have prevented natural product derivatives from reaching clinical utility using cinnamon’s phenylpropanoid template as a case study.In order to accomplish this objective, a direct comparison between cinnamon constituents was performed using a microarray dataset containing 102 traditional Chinese medicines, which was obtained from Gene Expression Omnibus (GEO) . GEO is n = 3), whereas caffeic acid was significantly associated with the greatest number (n = 6). Interestingly, cytokine–cytokine receptor interaction and a neuroactive ligand receptor were found to be consistently downregulated across all five exposures. Within these two pathways, eight transcripts were universally identified: CCL13, CCL24, CNR1, CXCL5, GRIA1, GRM1, HGF, and THRA.The 1500 most downregulated transcripts following treatment with either chlorogenic acid, cinnamaldehyde, cinnamic acid, ferulic acid or caffeic acid were significantly associated with three, four, four, four, or six KEGG pathways, respectively . Chlorogn = 16). As in the downregulated gene set, the neuroactive ligand receptor interaction pathway was consistently identified across all five treatment conditions. The fact that this pathway was identified in both the up and downregulated datasets suggests major alterations to transcript expression within this pathway are occurring in response to cinnamon-based phenylpropanoid exposure. Seven transcripts were universally identified to be upregulated in the neuroactive ligand receptor interactions pathway: CRHR2, CSH1, F2RL2, GH1, GNRHR, GRIK1, and GRIN2B. Other pathways that were common to more than one treatment condition included hematopoietic cell linage, linoleic acid metabolism, arachidonic acid metabolism, and long-term depression, which were all significantly associated with four treatment conditions . In addition, the natural killer cell-mediated cytotoxicity pathway was significantly associated with chlorogenic acid, cinnamic acid and ferulic acid, while the vascular smooth muscle contraction pathway was significantly associated with both cinnamaldehyde and cinnamic acid . In GEO alone, there are over three million samples available to the public at no cost. Independent researchers have the ability to repurpose or collate existing sample datasets to ask novel questions that drive new discoveries, which in turn generate new hypotheses that can be tested in a laboratory or clinical setting . Our stuGene expression profiles of Michigan Cancer Foundation-7 (MCF7) cells exposed to 102 different molecules used in traditional Chinese medicines were obtained through GEO DataSeries GSE85871 . Gene exGene expression changes for each of the five cinnamon constituents were analyzed individually. The 1500 genes with the largest changes in expression magnitude (up or down) were uploaded into the Data for Annotation Visualization and Integrated Discovery  ,25. The p-value using a Benjamini correction (p < 0.05) to minimize the false discovery rate.Significance thresholds for KEGG pathway analysis through DAVID were set at an adjusted


Calculus Bovis is a valuable Chinese medicine, which is widely used in the clinical treatment of ischemic stroke. The present study is aimed at investigating its target and the mechanism involved in ischemic stroke treatment by network pharmacology. Calculus Bovis were collected using methods of network pharmacology and using the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Potential compound targets were searched in the TCMSP and SwissTargetPrediction databases. Ischemic stroke-related disease targets were searched in the Drugbank, DisGeNet, OMIM, and TTD databases. These two types of targets were uploaded to the STRING database, and a network of their interaction (PPI) was built with its characteristics calculated, aiming to reveal a number of key targets. Hub genes were selected using a plug-in of the Cytoscape software, and Gene Ontology (GO) biological processes and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted using the clusterProfiler package of R language.  Effective compounds of Calculus Bovis compound targets and 590 ischemic stroke targets were found with 92 overlapping targets, including hub genes such as TP53, AKT, PIK2CA, MAPK3, MMP9, and MMP2. Biological functions of Calculus Bovis are associated with protein hydrolyzation, phosphorylation of serine/threonine residues of protein substrates, peptide bond hydrolyzation of peptides and proteins, hydrolyzation of intracellular second messengers, antioxidation and reduction, RNA transcription, and other biological processes.  Among 12 compounds, deoxycorticosterone, methyl cholate, and biliverdin were potentially effective components. A total of 344 Calculus Bovis may play a role in ischemic stroke by activating PI3K-AKT and MAPK signaling pathways, which are involved in regulating inflammatory response, cell apoptosis, and proliferation. Stroke is an acute cerebrovascular disease with typical clinical manifestations of sudden weakness in one side of the face, arms, or legs; sudden faintness; and unconsciousness. Ischemic stroke, the most common form of stroke, accounts for 70-80% of the total number of cases among stroke patients . In ChinCalculus Bovis, one of the most commonly used Chinese herbs for stroke, has been used for over 2,000 years in China. It was first described in “Shen Nong Ben Cao Jing” as a medication with a bitter taste and cooling nature [Calculus Bovis protects the brain through its anti-inflammatory, antiapoptosis [Calculus Bovis and its formulas are widely used to treat ischemic stroke, but the mechanisms underlying its therapeutic effect have not been studied intensively.g nature . And it poptosis , antilippoptosis , and antpoptosis . It is wpoptosis , 15. CurCalculus Bovis in managing ischemic stroke by network pharmacology methods, which will lay the foundation for future pharmacological and clinical studies on ischemic stroke. The protocol of our experimental procedures is shown in Network pharmacology for Chinese herbs is developed to decipher interactions between herbs and diseases at a system level by analysing the network between herbs, compounds, targets, diseases, and genes –19. In tCalculus Bovis were collected from the herbal platform TCMSP and BATMAN-TCM. The TCMSP (https://tcmspw.com/tcmsp.php) is a systems pharmacology platform for herbs providing information about compounds and their targets [http://bionet.ncpsb.org/batman-tcm/) is an online bioinformatics analysis tool comprised of functions like target prediction for herbs and target analysis [Calculus Bovis)” was typed in the “Cluster name,” “Score cutoff” value was set at 20, and “Adjusted p value” was set at 0.05, compounds of Calculus Bovis and their targets would be displayed. In addition, potential targets could be searched in the TCMSP and SwissTargetPrediction (http://www.swisstargetprediction.ch/) databases [Calculus Bovis. Names of target proteins were translated into gene names in the UniProt (http://www.uniprot.org/) database. If there was overlap in their target genes, the duplicates were deleted. Similarly, when the gene names of the protein targets were not found in the Uniprot database, they were deleted. SMILES IDs of compounds contained in Calculus Bovis were searched in the PubChem (https://pubchem.ncbi.nlm.nih.gov/) database, and their targets were predicted using SwissTargetPrediction after setting “Homo sapiens.” After collecting targets from the TCMSP, BATMAN-TCM, and SwissTargetPrediction databases, the duplicates were deleted.Compounds of  targets . The BATanalysis . When “Natabases  to furthCalculus Bovis. Based on the content of known compounds, OB and DL were set at ≥15% and ≥0.1, respectively. It has been reported that ergosterol  is an indispensable compound of Calculus Bovis [In pharmacological studies, absorption, distribution, metabolism, and excretion (ADME) are key indices for identifying specific drugs . Herein,us Bovis , 25 and Homo sapiens” was selected for species. They were searched in the Drugbank [Key words such as “ischemic stroke,” “cerebral ischemic stroke,” and “brain ischemia” were used, and “Drugbank , DisGeNeDrugbank , OMIM [2Drugbank , and TTDDrugbank , and duphttps://bioinfogp.cnb.csic.es/tools/venny/); overlapping genes were the potential targets of bioactive compounds, and they interact with the body in ischemic stroke.Both compound targets and disease targets were uploaded to the website of Venny 2.1.0 (https://string-db.org) database has collected a large number of well-known or predicted protein-protein interaction results [Homo sapiens” was selected for species, high confidence (0.700) was set for the minimum required interaction score, and irrelevant targets were concealed. As a result, a network map showing interactions between individual targets was rendered.The STRING ( results . Overlaphttps://cytoscape.org/) [Calculus Bovis compounds and compound targets and (2) a PPI network of Calculus Bovis compound targets and a PPI network of Calculus Bovis treating ischemic stroke targets after connecting Calculus Bovis compound targets and disease targets. Topographical analysis for networks was completed using the NetworkAnalyzer tool in Cytoscape. Overlapping genes, also named Hub genes, were selected from the PPI networks using the cytoHubba plug-in in Cytoscape and 3 algorithms were used in the calculations. The latter included degree of freedom, Maximum Neighborhood Component (MNC), and Maximal Clique Centrality (MCC).Network analysis facilitates interpretation of relationships between herbs, compounds, diseases, and genes. In the present study, two networks were constructed using Cytoscape 3.7.0 (pe.org/) : (1) a np values were ranked. The top 20 results from the GO enrichment and KEGG pathway enrichment analyses were presented. Visualization of these pathways with a p value < 0.05 was completed using the R software package.Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted using the clusterProfiler package of R (R 4.0.2 for Windows) to identify biological processes and pathways with systemic involvement. Biological processes and pathways with a significant difference were selected, and their numbers of enrichment as well their as A total of 12 bioactive compounds were found after ADME screening, and all of them have been verified in other studies.Calculus Bovis. Details of these ingredients are listed in Calculus Bovis, and triangles represent the targets; their colors are darkened as their degrees of freedom increased. There were 362 nodes and 706 edges with a network density of 0.011 and a network diameter of 5. Details of these parameters are listed in A total of 344 targets were found by 12 bioactive compounds of Using key words listed in After entering compound targets and disease targets to Venny 2.1.0 in the form of gene names, 92 overlapping genes were found see . These gCalculus Bovis targets, 12 compounds were connected with 344 targets in the TCMSP and the SwissTargetPrediction databases, and they were imported into the STRING database ), and the PPI network was visualized after reconstructing it with Cytoscape (version 3.7.0). As shown in PPI networks have been widely used in studying protein-protein interactions in different diseases. To construct the PPI network of Calculus Bovis in managing ischemic stroke, 92 shared targets by Calculus Bovis compounds and ischemic stroke were connected and imported into the STRING database as shown in Calculus Bovis-ischemic stroke targets were constructed by visualizing the results using Cytoscape , channel activity (GO:0015267), passive transmembrane transporter activity (GO:0022803), gated channel activity (GO:0022836), cation channel activity (GO:0005261), metal ion transmembrane transporter activity (GO:0046873), neurotransmitter receptor activity (GO:0030594), ligand-gated ion channel activity (GO:0015276), ligand-gated channel activity (GO:0022834), postsynaptic neurotransmitter receptor activity (GO:0098960), extracellular ligand-gated ion channel activity (GO:0005230), neurotransmitter receptor activity involved in regulation of postsynaptic membrane potential (GO:0099529), transmitter-gated ion channel activity (GO:0022824), transmitter-gated channel activity (GO:0022835), and steroid dehydrogenase activity (GO:0016229). Details are listed in Twenty results were selected based on their (1) Bubble Plot. In the bubble plot, letters on the left are GO names, numbers on the bottom are the proportions of genes, sizes of circles indicate the numbers of enriched genes, and colors reflect p values. The redder the colors are, the more enriched the genes are, and the smaller the p values are (lues are .(2) Column Chart. In the column chart, letters on the left are GO names, numbers on the bottom are the numbers of genes enriched on GO, and p reflects significance of enrichment. The redder the colors are, the more enriched the genes are, and the smaller the p values are ; protein serine/threonine kinase activity (GO:0004674); metallopeptidase activity (GO:0008237); phosphoric diester hydrolase activity (GO:0008081); heme binding (GO:0020037); tetrapyrrole binding (GO:0046906); oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen (GO:0016705); serine-type peptidase activity (GO:0008236); serine hydrolase activity (GO:0017171); carboxylic acid binding (GO:0031406); organic acid binding (GO:0043177); metalloendopeptidase activity (GO:0004222); RNA polymerase II transcription factor binding (GO:0001085); monocarboxylic acid binding (GO:0033293); and fatty acid binding (GO:0005504)  see . Results504) see  and a co504) see  using thCalculus Bovis targets and 92 shared targets.KEGG pathway enrichment analysis was performed for 344 p values and their numbers of enrichment. They were mainly involved in neuroactive ligand-receptor interaction (hsa04080), Alzheimer disease (hsa05010), calcium signaling pathway (hsa04020), nicotine addiction (hsa05033), steroid hormone biosynthesis (hsa00140), GABAergic synapse (hsa04727), morphine addiction (hsa05032), cholinergic synapse (hsa04725), retrograde endocannabinoid signaling (hsa04723), and cellular senescence (hsa04218) (see Eighteen results were selected based on their 218) see .(1) Bubble Plot. In the bubble plot, letters on the left are KEGG names, numbers on the bottom are the proportions of genes, sizes of circles indicate the numbers of enriched genes, and colors reflect p values. The redder the colors are, the more enriched the genes are, and the smaller the p values are (lues are .(2) Column Chart. In the column chart, letters on the left are KEGG names, numbers on the bottom are the numbers of genes enriched on KEGG, columns represent genes enriched on KEGG, and p reflects significance of enrichment. The redder the colors are, the more enriched the genes are, and the smaller the p values are , human papillomavirus infection (hsa05165), Kaposi sarcoma-associated herpesvirus infection (hsa05167), human cytomegalovirus infection (hsa05163), microRNAs in cancer (hsa05206), fluid shear stress and atherosclerosis (hsa05418), proteoglycans in cancer (hsa05205), AGE-RAGE signaling pathway in diabetic complications (hsa04933), cAMP signaling pathway (hsa04024), prostate cancer (hsa05215), TNF signaling pathway (hsa04668), platelet activation (hsa04611), EGFR tyrosine kinase inhibitor resistance (hsa01521), small cell lung cancer (hsa05222), and endocrine resistance (hsa01522)  . Resultssa01522)  and a cosa01522)  using thCalculus Bovis itself and its potential mechanism for the treatment of ischemic stroke through compound target network construction, PPI network analysis, GO enrichment analysis, and KEGG pathway analysis.Network pharmacology was used in this study to investigate Calculus Bovis.Network analysis of compound targets showed that deoxycorticosterone (MOL008846), methyl cholate (MOL008838), and biliverdin (MOL008834) had the most connections with these targets, suggesting that these 3 compounds might be the key compounds of Deoxycorticosterone is a type of steroid hormone possessing activities of the mineralocorticoid and serves as the precursor of aldosterone. It is involved in water and salt metabolism, playing an important role in electrolyte balance and in the volume of body fluid . It has Calculus Bovis compounds and their targets but also the potential pharmacological effects of Calculus Bovis, which reflects the multicompound and multitarget theory of modern drugs.Similarly, other targets like 11-beta-hydroxysteroid dehydrogenase 1 (HSD11B1), dual-specificity phosphatase Cdc25A (CDC25A), cytochrome P450 19A1 (CYP19A1), progesterone receptor (PGR), and androgen receptor (AR) were also regulated by two or more compounds. The present study revealed not only relationships between Calculus Bovis influences ischemic stroke through its impact on a complex biological network, including TP53, AKT1, MAPK1, VEGFA, TNF, PIK3CA, MAPK3, MMP9, PTGS2, and IL1B. Hub gene screening revealed that TP53, AKT1, PIK3CA, MAPK3, MMP9, and MMP2 were essential in this process. The above potential targets for the action of Calculus Bovis in the treatment of ischemic stroke are our first discoveries.Furthermore, the PPI network demonstrated information not only about protein homology and coexpression but also about protein-protein interactions. Our PPI analysis showed that TP53, cellular tumor antigen p53, is a tumor suppressing gene. It promotes cell apoptosis, increases gene stability, and suppresses tumorigenesis . It has AKT/PKB was involved in brain ischemia, and its activity was related to the extent of ischemic injury. Activation of AKT was the key factor in determining survival of neurons after ischemic injury . PIK3CA 2O2 induced PC12 cell injury model, activation of the AKT and ERK1/2 pathways leads to an antioxidation effect [MAPK (mitogen-activated protein kinase) is involved in reaction to physiological and pathological stimuli, such as cytokines, neurotransmitters, hypoxia, and hypoglycemia . MAPK3  were related to endopeptidase activities of the matrix metalloproteinase (MMPs) family  and the cysteine-containing aspartate-specific peptidase family . MMPs are a type of highly conserved proteinase in nature, belonging to the family of zinc-dependent endopeptidases. They are capable of degrading extracellular matrix, growth factors, cytokines, and cell adhesion molecules. They are indispensable in ECM and tissue remodeling, angiogenesis, immune reactions, inflammation, cell migration, proliferation, cell apoptosis, and other physiological and pathological processes [GO enrichment and KEGG pathway analyses against the shared 92 targets showed that rocesses . Their mrocesses . Decreasrocesses . Targeterocesses , but thirocesses . Neuroinrocesses . Both inrocesses .Calculus Bovis might protect the brain from ischemic stroke through its anti-inflammatory and antiapoptosis effects which are accomplished by interacting with the abovementioned key genes and pathways.Another 12 genes (13.0%) are related to activities of protein serine/threonine kinases, consistent with the findings of the PI3K-AKT signaling pathway  in the KEGG pathway analysis. AKT is also named serine/threonine kinase, whose activation is key for neuronal survival . It is kHowever, there are some limitations in this study. Access to databases of Chinese herbal medicines and disease targets is relatively limited, and there may be some data selection bias. Meanwhile, due to the fact that this study was based on data analysis, the conclusion needs to be confirmed by further research.Calculus Bovis were examined using network pharmacology methods. KEGG pathway analysis showed that the PI3K/AKT and the MAPK signaling pathways were the key targets for ischemic stroke treatment. The effect of Calculus Bovis was achieved through directly or indirectly regulating the above targets and pathways. Our results confirmed that Calculus Bovis was a multicompound and multitarget drug with a multisystem character in the treatment of ischemic stroke, which laid the theoretical foundation for the development of drugs and therapeutic methods based on the results of Calculus Bovis in the future.Bioactive compounds, potential targets, and underlying mechanisms of


Precision treatment of cancer requires knowledge on active tumor driving signal transduction pathways to select the optimal effective targeted treatment. Currently only a subset of patients derive clinical benefit from mutation based targeted treatment, due to intrinsic and acquired drug resistance mechanisms. Phenotypic assays to identify the tumor driving pathway based on protein analysis are difficult to multiplex on routine pathology samples. In contrast, the transcriptome contains information on signaling pathway activity and can complement genomic analyses. Here we present the validation and clinical application of a new knowledge-based mRNA-based diagnostic assay platform  for measuring activity of relevant signaling pathways simultaneously and quantitatively with high resolution in tissue samples and circulating tumor cells, specifically with very small specimen quantities. The approach uses mRNA levels of a pathway’s direct target genes, selected based on literature for multiple proof points, and used as evidence that a pathway is functionally activated. Using these validated target genes, a Bayesian network model has been built and calibrated on mRNA measurements of samples with known pathway status, which is used next to calculate a pathway activity score on individual test samples. Translation to RT-qPCR assays enables broad clinical diagnostic applications, including small analytes. A large number of cancer samples have been analyzed across a variety of cancer histologies and benchmarked across normal controls. Assays have been used to characterize cell types in the cancer cell microenvironment, including immune cells in which activated and immunotolerant states can be distinguished. Results support the expectation that the assays provide information on cancer driving signaling pathways which is difficult to derive from next generation DNA sequencing analysis. Current clinical oncology applications have been complementary to genomic mutation analysis to improve precision medicine: (1) prediction of response and resistance to various therapies, especially targeted therapy and immunotherapy; (2) assessment and monitoring of therapy efficacy; (3) prediction of invasive cancer cell behavior and prognosis; (4) measurement of circulating tumor cells. Preclinical oncology applications lie in a better understanding of cancer behavior across cancer types, and in development of a pathophysiology-based cancer classification for development of novel therapies and precision medicine. Cellular mechanisms of cancer can be described in terms of abnormal activity of a discrete number of signal transduction pathways that control crucial cellular functions and play important roles in both physiology  and pathophysiology. They can be categorized as hormone driven pathways , growth factor pathways , the inflammatory pathway (NFκB), and developmental pathways .Signal transduction pathways drive tumor growth and metastasis, either as a single active pathway  or through cooperation or crosstalk between signaling pathways  . AbnormaTraditionally, the selection of targeted drugs has been based in immunohistochemistry  and can be applied to formalin fixed paraffin embedded (FFPE) tissue samples. IHC staining is currently semi-quantitative, however, and multiplexing staining remains a major challenge. Correct normalization of staining signals can be inconsistent, and sample preparation and staining protocols can vary substantially among pathology departments. Expression levels of signaling proteins do not provide information on their functional activity and activity of the associated signaling pathway . The prePIK3CA mutation, based on the results of the SOLAR-1 trial  techniques has enabled identifying tumor-driving gene mutations in many histologies of cancer. This has resulted in a number of therapeutic successes, as evident from FDA approved companion diagnostic assays based on identification of a specific gene mutation to predict therapy response . FDA app-1 trial . Other m therapy . For man therapy . An impo therapy . This maRNA-based methods to measure signaling pathway activity have advanced during the past decade to provide information on signaling pathway activity based on mRNA expression data of a tumor sample. However, using mRNA expression levels as a proxy for the presence of corresponding activated signaling molecules or transcription factors can be inaccurate. First, mRNA expression levels are unreliable indicators of corresponding protein levels because their production and turnover rates are frequently not matched. Second, signaling protein levels are in general not related to the functional activity state of the protein, which is determined by post-translational modifications, such as specific phosphorylations. Nevertheless, mRNA expression levels can provide information on activity of the transcription factors that produce them, and indirectly on activity of signaling pathways that lead to activation of such transcription factors.1, and WikiPathways2. The term “pathways” there usually refers to a variety of intracellular molecular mechanisms, not specifically to activity of signal transduction pathways , Gene Set Enrichment Analysis (GSEA)  and DAVIpathways . These tEven if above pathway analysis approaches yield relevant “pathways” that are differentially expressed, then a step is to be made to translate them into a gene expression profile or a classifier that can be applied on an individual test sample. This requires a training step on samples with known ground truth pathway status. Since many of these “pathway” gene sets have been derived in a data-driven manner, one should be cautious when applying them on test samples of a different nature than the original discovery set. Data-driven discovery approaches are difficult to properly assess functional activity of tumor-driving pathways. Here we will present a novel approach that focuses on specific pathway activations that are distinct from traditional gene enrichment set analysis.Starting from the opportunities provided by the transcriptome, we have developed an assay  to quantitatively measure activity of signal transduction pathways across cell and tissue types. At the core of the approach is a mathematical Bayesian model which quantitatively infers activity of signal transduction pathways from mRNA measurements of a small number of selected direct target genes of the respective signaling pathway-associated transcription factor . By seleWe have employed a Bayesian network model that describes the causal relation between transcription factor activation of a certain pathway and the mRNA expression levels of the corresponding direct target genes , as showGiven the network structure, we subsequently define parameters describing (a) the relation between the transcription factor complex and the direct target genes, and (b) the relation between each target gene and its corresponding measurements. The parameters of the first layer (a) are based on literature insights, whereas those of the second layer (b) are calibrated based on measurements on samples with a known ground truth status for activity of the respective signal transduction pathway, from which typical measurement levels are deduced in an inactive or an active state. These ground truth samples may come from patient studies, such as for the Wnt pathway, which is known to be activated in colon adenomas and inactive in normal colon samples, or from controlled cell line experiments in which a default inactive pathway is activated by adding ligands, or a constitutively activated pathway is blocked by means of blocking compounds.After building and calibrating Bayesian pathway models as described above, the models can be applied on subsequent individual test samples by taking such a sample’s measurements and feeding them into the model after which Bayesian inference is used to re-engineer the odds that the transcription factor must have been activated compared to those that are not activated. These odds are represented on a log2 scale, with a positive value indicating that there is more evidence for an active pathway, and a negative value indicating more evidence of an inactive pathway. For ease of comparison, these log2 values are further normalized to a 0–100 scale.We have developed Bayesian network models to assess the phenotypic activity of the PI3K, MAPK-AP1, JAK-STAT1/2 and JAK-STAT3, NFκB, ER, AR, Notch, TGFβ, Wnt and HH signaling pathways using Affymetrix expression microarray data (HG-U133Plus2.0 arrays), and we tested each of them extensively on data sets from publicly available sources such as the Gene Expression Omnibus to show that they give a correct read-out of activity in samples with known ground truth pathway status . Some vaThe signal transduction pathway (STP) assays have been biologically validated on a variety of cell types and are in principle applicable to all healthy and diseased cell and tissue types. The major reason for this broad applicability is the focus on transcription factor target genes. This maximally eliminates influences of cell type-specific proteins on the target gene levels. Another feature of the Bayesian computational network model is that it can deal well with variability in input data, including conflicting data such as target genes that are not expressed in a specific sample despite the transcription factor being active, or target genes that are expressed despite an inactive transcription factor. Third, target genes were not selected based on relevance for a specific disease or tissue type, but solely as reliable readout for transcription factor activity. When expression levels of individual pathway target genes vary between samples and between different cell types, the Bayesian reasoning principle allows robust interpretation of these mRNA levels. This explains why the STP assays can deliver reliable pathway activity measurements across patient samples in spite of the variation that is inherent to such samples. The same signal transduction pathways that play a role in cancer, also determine activity or immunosuppression of the many cell types that together generate the innate and adaptive immune response, and as a consequence STP tests are being studied to measure activity of the immune system .Our STP assays were first built and tested on Affymetrix expression microarray data, having the advantage of access to publicly available datasets from the GEO database, enabling model validation on multiple independent preclinical and clinical datasets . To faciTo build these RT-qPCR pathway assays, we first reduced the number of target genes used per pathway to around 12. This still enables robust behavior of the assays, while maintaining specificity, and all validation results were confirmed with these reduced gene lists. Next, we used the very same calibration samples to determine the model parameters with the only difference that we measured them again with RT-qPCR. In this way, we ensure compatibility between the microarray-based and RT-qPCR based STP assays.When performing an STP analysis on an individual patient sample to help guide the decision on targeted therapy, it will be necessary to know whether and to which extent a specific signaling pathway activity is considered abnormal, and if increased, whether it is likely to be tumor driving and targetable. This requires the definition of a normal pathway activity range including a pathway activity threshold. To obtain this, STP activity analysis was performed on healthy tissue samples, and the 95th percentile of normal was defined as threshold above which the signaling pathway activity in tumor tissue is considered to be abnormal . When thCTNNB1 gene) protein function are known to result in increased Wnt pathway activity. Wnt pathway activity scores were normal in the reference (WT), increased in loss-of-function APC-mutated ovary cancer and in gain-of-function CTNNB1 Asp32Tyr mutated breast cancer, and normal in non-functionally mutated CTNNB1 Asp665Glu breast cancer  pathway is a tumor driving signaling pathway in breast cancer, and can also be active in ovarian and endometrium cancer although its role in those malignancies is less clear. Adjuvant tamoxifen treatment of ER positive breast cancer patients was associated with significantly lower recurrence rate in patients with an ER pathway active primary tumor, compared to patients with an ER-inactive tumor . PathwayThe AR pathway is another important hormonal pathway and positive IHC staining has been described for different cancer types . While, The PI3K pathway is a major growth factor pathway, sometimes called a “survival” pathway, and the frequent pathway activity can be caused by for example mutations in the PIK3CA gene or amplification of the HER2 gene . In lineActivity of developmental signaling pathways, such as the TGFβ, Hedgehog, Notch and Wnt pathways, is a typical characteristic of stem cells and was found in a variety of tumors including medulloblastomas and gliomas . Some ofThe Wnt pathway is well known for its tumor initiating role in colon adenoma and cancer, and Wnt pathway activity was confirmed in these tumors . The rolNotch pathway activity was associated with improved prognosis in T cell-acute lymphoblastic lymphoma . ActivitFor many diseases, including cancer, the immune response is a major determinant of progression, response to therapy, and clinical outcome. Immunotherapy has emerged as a high potential curative treatment for many cancer types, and checkpoint inhibitor therapy is becoming standard of care for cancer types for a variety of tumors including melanoma, lung cancer, head and neck cancers . Variousin vitro study results suggest that this may be mediated by soluble factors from cancer tissue  that reduce effector immune pathway activity  and increase activity of the immune suppressive TGFβ pathway  can be measured simultaneously and quantitatively on individual patient cancer tissue samples from different cancer types. As illustrated above, this pathway analysis approach reveals commonalities with respect to pathway activities across different cancer types, potentially enabling an alternative cancer classification system based on signaling pathway activity profiles, complementary to the conventional classification based on the organ location. Developing a molecular fingerprint of tumors with respect to signaling pathway activities is expected to provide new insights into the pathophysiology of the many cancer types, including discovery of novel mechanisms for tumorigenesis and metastasis. STP analysis may also contribute to identification of novel drug targets and development of therapies that are more generalizable across cancer types including rare cancers.Clinical diagnostic applications of STP analysis for prediction of prognosis and response to therapy, including identification of resistance pathways, are currently being further developed in clinical studies. Prospective clinical validation studies in various cancer types and basket studies are being initiated with clinical partners, predominantly making use of RT-qPCR-based STP analysis on FFPE tissue samples with considerations toward low quantity specimens including circulating tumor cells.In the future, an important focus will lie on measuring the host immune response to cancer, both in blood as well as in cancer tissue samples. Taken together, measurement of STP activity in cancer, complementary to DNA mutation analysis, is expected to enable development of novel therapies, improve prediction of therapy response and resistance, and improve clinical outcome for a variety of tumor types and treatments, including targeted drugs and immunotherapy.The raw data supporting the conclusions of this article will be made available by the authors upon request, without undue reservation.As far as data did not come from public data repositories, the studies involving human participants were reviewed and approved by local IRBs, and the patients/participants provided their written informed consent to participate.HH and AS: conception and design, writing, review and comments. J-YB, CM, PP, MP, HP, DDR, NS, SS, and KW-G: review and comments. WV: modeling, writing, review and comments. All authors contributed to the article and approved the submitted version.WV is an employee of Philips Research. J-YB, CM, PP, MP, HP, DDR, NS, SS, KW-G, and HH are on the advisory board of Philips MPDx.


Rhizoma Curcumae in nasopharyngeal carcinoma by using network pharmacological techniques and to explore the associated molecular mechanism.  To analyse the target of Rhizoma Curcumae were obtained from the TCMSP and SymMap databases. The data were imported into the STRING database and Cytoscape 3.7.1 to construct a network of “Chinese medicine component-target-disease” interactions; then, the intersection was screened as the core Rhizoma Curcumae antinasopharyngeal cancer targets. Through GO target function and KEGG pathway enrichment analyses of the core targets, we predicted the biological processes and key signalling pathways involved in the Rhizoma Curcumae treatment of nasopharyngeal carcinoma.  The targets of nasopharyngeal carcinoma were retrieved from the GeneCards database. At the same time, the drug therapeutic targets of Rhizoma Curcumae in nasopharyngeal carcinoma were mined: TP53, BCL2 ICAM1 RXRA, TLR3 and TLR9, TNF, PTGS2, IL-6, CTSD, MMP2, MMP9, MMP14, TIMP2, ABCC1, ABCB1, ABCG2, and so on. The results of visual analysis showed that the Rhizoma Curcumae treatment of nasopharyngeal carcinoma mainly involves leukocyte adhesion to vascular endothelial cells, positive regulation of NF-κB import into the nucleus, regulation of the reactive oxygen species biosynthetic and metabolic process, regulation of the chemokine biosynthetic and metabolic process, various cancer-related signalling pathways, and a variety of cytokine signal transduction pathways, such as the NF-κB, TLR, IL-17, and TNF signalling pathways.  Twenty-five core targets of Rhizoma Curcumae treatment in NPC may be related to immune regulatory pathways, the inhibition of cancer cell proliferation, metastasis, and angiogenesis, as well as the regulation of tumour microenvironment. Combined with the prediction of its associated mechanism of action, the core targets can provide targeted reference value for subsequent drug development related to Curcuma. The core targets predicted by our research can be used as molecular markers for the treatment and prediction of nasopharyngeal carcinoma. The mechanism of  Nasopharyngeal carcinoma (NPC) is a common epithelial tumour in southern China and Southeast Asia. It is one of the most common malignant tumours in China. The incidence of NPC is closely related to heredity, EB virus infection, and environmental factors. Lymph node metastasis can occur early, with most patients first diagnosed at the late stage; NPC has a high recurrence rate and easy distant metastasis , resultiRhizoma Curcumae, known as Ezhu in China, is a plant of Curcuma L of Zingiberaceae, from dried roots of Curcuma phaeocaulis, Curcuma kwangsiensis, and Curcuma wenyujin. It is a traditional Chinese medicine, widely distributed throughout China, and contains a variety of biologically active ingredients, such as curcumol [Rhizoma Curcumae has been used in the clinical treatment of cervical cancer and has been proven to have antitumor effects in various human cancers such as liver cancer, ovarian cancer, and breast cancer [Rhizoma Curcumae is a common medicine in the traditional Chinese medicine treatment of NPC. Studies have shown that curcumol may inhibit the further development of NPC by attenuating epithelial-mesenchymal transition in nasopharyngeal carcinoma cells [Rhizoma Curcumae has significant antitumor effects, but its target in NPC cells remains unclear. Revealing and understanding the mechanism of the action of Rhizoma Curcumae is essential for the prevention and treatment of nasopharyngeal carcinoma.Traditional Chinese medicine (TCM) with antitumor effects has become an important part of clinical prescriptions of TCM and the source of new antitumor drug development . Rhizomacurcumol . It has curcumol . Rhizomat cancer , 7. Rhizma cells . Curcumoma cells . These sRhizoma Curcumae treatment in NPC. For further exploration and integration, our study used network pharmacology to construct a network of “component-target-disease-pathway” interactions to predict the targets of Rhizoma Curcumae treatment and its possible mechanism of action in NPC, providing a reference for subsequent experiments and even a new direction for molecular targeted therapy of NPC.Network pharmacology is a new drug design method and strategy based on the rapid development of systems biology and multidirectional pharmacology. It is based on the “disease-gene-target-drug” interaction network. Network pharmacology provides a new approach for studying the mechanism of Chinese medicine ingredients through identifying connections with targets and diseases; through the analysis of information from existing databases, such as gene network, protein network, disease network, and drug network libraries, combined with spectral data obtained from our experiments, we used professional network analysis software and algorithms to apply this approach. At present, there are few studies on the target and molecular mechanism of Rhizoma Curcumae, with oral availability  ≥30% and drug-like properties  ≥0.18 as a standard screen for chemical components acting as active ingredients in Rhizoma Curcumae. We used the GeneCards database to find targets related to NPC, screening genes with a correlation score of ≥5 as candidate target genes. We used the UniProt database to remove non-human target gene names, and finally, we eliminated duplicates.The TCMSP database and the SymMap database were used to obtain the active ingredients and the corresponding drug targets of Rhizoma Curcumae-target-nasopharyngeal cancer PPI network.Disease and target PPI data were obtained from the STRING database, PPI data with a score of ≥0.9 were screened, and the results were imported into Cytoscape 3.7.1 to construct a Rhizoma Curcumae and the targets of nasopharyngeal carcinoma were mapped to each other to obtain the targets of Rhizoma Curcumae treatment for NPC. The antinasopharyngeal cancer targets of Rhizoma Curcumae obtained after mapping were imported into the STRING database to determine the role between the target proteins and their functions. PPI data with a score of ≥0.9 were screened and visualized by Cytoscape 3.7.1. Finally, we determined the core target of Rhizoma Curcumae treatment in NPC.The targets of Rhizoma Curcumae against NPC was performed. The target-pathway network and component-target network as well as Rhizoma Curcumae-target-NPC were imported into Cytoscape 3.7.1 for network consolidation. The integration result of the “component-target-disease-path” was obtained.Pathway enrichment analysis of the core target genes of The Cytoscape 3.7.1 plug-in ClueGO was used to perform GO and KEGG analyses on the core targets of Rhizoma Curcumae against nasopharyngeal carcinom and to visualize the possible biological processes, molecular function, cellular component, and signalling pathways that were involved.Rhizoma Curcumae with the DB ≥ 30 and DL ≤ 0.18 standards and found 33 corresponding active ingredients. 40 active ingredient targets were obtained by using the SymMap database. Subsequently, the UniProt database was used for target standardization and removal of nonhuman targets and duplicates. Ultimately, we obtained 66 Rhizoma Curcumae-related targets.We collected 681 genes as the study targets by using the GeneCards database. Through TCMSP, we screened the active ingredients of Rhizoma Curcumae were obtained through the STRING database, and the PPI data with confidence scores ≥0.9 were selected and imported into Cytoscape to construct the target network interaction map. The merge function was used to merge the target network map with the disease target network map to obtain a target-disease network map consisting of 100 nodes and 359 edges , MMP2, MMP9, and MMP14, can promote the invasion and metastasis of NPC cells , 27. MMPκB , and MMPκB . Tissue κB , and theκB . ABCB1, κB . ABCB1 gκB , 34; tumκB .Rhizoma Curcumae can be used as an antinasopharyngeal cancer agent by positively regulating the metabolic process of reactive oxygen species biosynthesis. TP53, one of the core targets screened out, can also enhance the damage of reactive oxygen species (ROS). So, Rhizoma Curcumae maybe reduce reactive oxygen species damage by regulating TP53 to play role against nasopharyngeal carcinoma, the mechanism of which needs further research. Besides, Rhizoma Curcumae is likely to inhibit tumour microenvironment formation by regulating the biochemical metabolic processes of chemokines.In addition, we performed GO annotation analysis and KEGG pathway analysis by target proteins. GO analysis showed that the biological processes of core targets are mainly focused on leukocyte adhesion to vascular endothelial cells. Cell-cell adhesion is the basis of tissue integrity . DecreasRhizoma Curcumae may regulate the proliferation of nasopharyngeal carcinoma cells by regulating the MAPK signalling pathway. NF-κB, as the key node, and its upstream TP53 gene as well as downstream BLC2 and ICAM1 were found closely related to NPC. EBV infection can activate TLR3 and TLR9/NF-κB signalling pathways to upregulate TNF. And the abnormally regulated toll-like receptor signalling pathway, TNF signalling pathway, and NF-κB signalling pathway as well as positive regulation of NF-κB import into the nucleus are closely related to the occurrence and development of NPC. These signal pathways and targets will guide future research.The KEGG analyses showed that most of the enriched biological information was associated with the thyroid cancer pathway, small-cell lung cancer pathway, prostate cancer pathway, bladder cancer pathway, and other cancer pathways. According to an analysis of the literature, we found that multiple target proteins contained in these pathways can activate the MAPK signalling pathway –41. TherκB signalling pathway, which subsequently upregulates the expression of MMP2 and MMP9 and enhances epithelial-mesenchymal transition [Moreover, the results of KEGG analysis were also enriched in the IL-17 signalling pathway, hepatitis B pathway, AGE-RAGE signalling in the diabetic complication pathway, and malaria pathway. IL-17 is a proinflammatory cytokine mainly produced by T-helper 17 cells. It is reported that IL-17A promotes the migration and invasion of NPC cells through the p38 mitogen-activated protein kinase/NF-ansition . Hepatitansition . Anti-HBansition . Type 2 ansition . High-tiRhizoma Curcumae exerts potent anticancer effects by regulating the expression of the predicted targets in nasopharyngeal carcinoma cells. These predicted targets can also be used as potential molecular markers against nasopharyngeal carcinoma. The pharmacological mechanism of Rhizoma Curcumae in NPC may be closely related to the regulation of tumor proliferation and metastasis as well as tumour environment, cancer pathways, and transduction of some cytokine signalling pathway, indicating that the pharmacological and molecular mechanisms generated via the network pharmacology approach are predictive. The accuracy and practicality of this approach lay a good foundation for further exploration of the pharmacological targets and molecular mechanisms of Rhizoma Curcumae in nasopharyngeal carcinoma.In summary, we can speculate that


From 734 total respondents, 62.0% declared VD supplementation. The main personal rationale for VD supplementation were recommendation of medical specialist 172 (37.8%) and self-education 135 (29.7%). The main reasons for non-supplementation of VD were lack of knowledge about VD 159 (57.0%) and lack of motivation 77 (27.6%). VD supplementation was independently associated with a family doctor (odds ratio (OR), 95% confidence interval (CI): 4.67, 2.32–9.40) or medical specialist recommendation , and self-education . Most Polish individuals with T1DM use VD supplements, and the decision is related to physicians’ recommendations and self-education.Half of the individuals with type 1 diabetes (T1DM) may present Vitamin D (VD) deficiency. There is little known about factors determining a decision on VD supplementation. The study aimed to determine the factors affecting vitamin D supplementation in people with T1DM. A cross-sectional survey study using the authors’ questionnaire paper and its digital version was performed. The questions involved data on the basic characteristics of the respondent, medical history, VD supplementation status, influence of the social environment, self-education, and the most important personal motivator for VD supplement use. Multivariate logistic regression analysis was performed. We collected a total of  Vitamin D (VD) is a prohormone produced by the skin in response to sunlight stimulation and ingested with food  . The actThe aim of the study was to determine the factors affecting vitamin D supplementation in people with T1DM.A survey in the T1DM population using a simple, anonymous, authors’ questionnaire was performed. The questionnaire contained mostly closed-ended questions that were inspired by previous survey studies on VD supplementation ,24,25. T2 and below 30 kg/m2, and obesity as BMI ≥ 30 kg/m2.For the study, patients in the Department of Diabetology and the outpatient clinic were requested to fill in a paper version of the questionnaire. The data from paper surveys were prescribed to the REDCap database . FurtherAdditionally, a short, anonymous authors’ questionnaire dedicated to diabetologists or residents of diabetology was prepared. The questions were inspired by previous survey studies ,28. The p-value < 0.05. Statistical analysis was performed with STATISTICA 12.0 . The number of positive responses (“YES”) for each respondent was calculated,  or numbers (percentages). To compare the groups who declared or denied VD supplementation and the individuals who filled in the paper vs. the digital version of the survey, the Mann–Whitney U test for numerical data and Pearson chi-square test for categorical variables were used. Each category of the variables with more than two categories was compared separately using the chi-square test. For instance, living in a village vs. living outside of a village. The significance level was set at a p-value < 0.1 in the univariate regression analysis were chosen. Plots were generated using the “forestplot” package of R 3.5.1  [To assess factors that could be associated with VD supplement use univariate and multivariate logistic regression analyses were performed. The dependent variable was declared VD supplementation (count as one) or denied VD supplementation (coded as null). In univariate logistic regression model, the independent factors were: version of the survey , sex , age, diabetes duration, overweight or obese , living place , at least one diabetic complication (coded as one), presence of diabetic complications, , concomitant disease , recommendation and influence of the social environment (answer “Yes” coded as one). The version of the survey was analyzed using a logistic regression model to take into account potential differences between both groups (respondents from the department vs. Facebook users) in clinical characteristics and VD supplementation. Therefore, the version of the survey reflects the data source. For the multivariate logistic regression model, variables with a Austria) .In total, 1181  responses were collected, but 734 surveys were completed including 184/734 (25.1%) paper and 550/734 (74.9%) digital surveys. The median age of the study population was 31 (24–39) years . The VD supplementation was declared by 455 (62.0%) of all individuals .In the comparison of the group who declared the VD supplementation with the participants who denied VD supplement use, a significant difference in the ratio of paper survey respondents, prevalence of individuals living in village; living in a city of above 50,000 citizens; presence of retinopathy; presence of hypothyroidism; supplementation recommendation made by family doctor, medical specialist, pharmacist, relative; knowledge about VD supplementation acquired from Internet/media/books; ratio of respondents who admitted that their relative supplements VD; friend supplements VD; and number of positive responses on social environment influence were found . Additionally, the groups who filled in the paper or the digital version of the survey were compared . Both grIn the group who declared VD supplementation, the subjective reasons for VD supplement use were: recommendation of medical specialist 172 (37.8%), knowledge on VD acquired from Internet/media/books 135 (29.7%), relative recommendation 43 (9.5%), family doctor recommendation 38 (8.3%), friend recommendation 27/455 (5.9%), pharmacist recommendation 6 (1.3%), and others 34 (7.5%). Among the other rationales, the most frequent were results of lab findings 20 (4.4%), disease 11 (2.4%). In the group who denied VD supplementation, the most important personal reason for non-supplementation of VD were: lack of knowledge about VD 159 (57.0%), lack of motivation 77 (27.6%), believe that VD has low importance for health 14 (5.0%), consider VD supplementation as a waste of money 11 (3.9%) and others 18 (6.5%). n = 64 (14.1%)) did not disclose the VD supplementation dose. Two hundred and fifty-eight  respondents supplement VD in accordance with the current guidelines: adequate for age and BMI. Proper VD supplement use was identified in 27 obese individuals  and in 2 respondents aged >65 years . In the group who declared VD supplementation, 129 (28.4%) supplemented VD from October to April, 108 (23.7%) irregularly, and 218 (47.9%) throughout the year. There were identified a total of 8 (1.8%) individuals who supplemented VD less than 800 UI/daily (UI/d), 72 (15.8%) from 800 to 1000 UI/d, 180 (39.6%) from 1200 to 2000 UI/d, 96 (21.1%) from 2200 to 4000 UI/d, 23 (5.1%) from 4500 to 8000 UI/d, 5 (1.1%) from 10,000 to 12,000 UI/d, 7 (1.5%) from 13,000 to 80,000 UI/d. Substantial number of the responders  physicians mostly female were obtained. VD supplementation was declared by n = 30 (79%) of the respondents. The main motivation for VD supplementation was the knowledge obtained from media/books/Internet (n = 26), the counsel of specialist (n = 3), and own VD serum concentration (n = 1). Most of the respondents declared VD supplementation from October to April (n = 19) next to all year (n = 7) and irregular (n = 4). The diabetologists who did not declare VD supplementation attributed their decision to a lack of motivation (n = 4), absentmindedness (n = 1), lack of the need (n = 1), “lack of the Polish studies and guidelines” (n = 1), doubts about the current supplementation guidelines (n = 1). Both groups who declared or denied VD supplementation were compared (The digital survey was sent to compared . In the In this cross-sectional survey study, we analyzed the prevalence of VD supplementation among individuals with T1DM, personal reasons, and factors affecting the decision on supplement use. Moreover, we analyzed the association between personal beliefs of diabetologists on VD supplementation and its recommendation to patients.Previously, it was reported that Danish individuals with both T1DM and type 2 diabetes more frequently supplemented VD than non-diabetic subjects . In the Interestingly, there was no significant difference between men and women with T1DM who declared VD supplementation. VD especially is recommended for individuals at risk of osteopenia and osteoporosis, which is mostly elder women. However, the majority of the study group were young or middle-aged women. Therefore, it may be assumed that the distribution of sex and age in the population does not promote women to be more frequently advised for VD supplementation. Approximately, 14% of the responders who declared VD supplementation did not provide the exact dose of supplemented VD. Moreover, a substantial number of entities supplemented VD in very low or very high doses that are not recommended by national guidelines . TherefoIn our study, most of the patients who denied VD supplementation admitted a lack of knowledge and a lack of personal motivation to initialize VD supplementation. These justify the continuation of efforts to increase public awareness on VD benefits ,34. MoreThis study provides a unique insight into the determinants of VD supplementation in T1DM population. The physicians’ recommendation was the significant factor of VD supplementation. However, any significant association between pharmacist, relative, or friend recommendation and VD supplementation was not observed. These results may mirror a personal hierarchy of authorities in health issues of the respondents: medical specialists are the most trusted, second are family doctors, while recommendations of pharmacists, relatives, and friends are not considered as reliable. Interestingly, VD supplementation in relatives or friends did not affect the decision on VD supplementation of the respondents. This suggests that encouraging patients for the initialization of VD supplementation might require a more personal approach. Respondents who get to know about VD from Internet/media/books were more eager to supplement VD. Goodman et al. showed that online materials and mobile apps may increase awareness of VD importance . MoreoveInterestingly, living in a village was negatively associated with VD supplementation. However, Zadka et al. reported that parents living in the countryside had higher knowledge of VD and tended to more commonly take VD than respondents living in the city . We hypoIn most cases, VD supplementation did not have an association with medical history. This may be surprising because it may be suspected that patients with more comorbidities will be more frequently encouraged to take VD for health reasons.The individuals from Facebook groups were more likely to supplement VD. This may be caused by survey bias. The author spread the links to the digital version of the survey on Facebook groups and encourage the users, while the paper version was mainly handing to the patient. Though, it is possible that active Internet users who are associates of Facebook groups for individuals with diabetes are more aware of the beneficial properties of VD. Our survey dedicated to diabetologists revealed that more than three of four declared VD supplementation. The personal decision about VD supplementation was associated with recommending patient VD supplementation. Up to 40% of physicians who supplement VD declared that they recommend VD of most of their patients. Moreover, diabetologists who declared VD supplementation mostly agreed that every medical professional should discuss VD supplementation with the patient. However, 37% of physicians admitted that lack of time limits the possibility to counsel the supplementation. This may mirror the main obstacle for the education of the patient in circumstances of a medical office.This is, to our best knowledge, the first study investigating the most important personal motivations and factors determining VD supplementation in T1DM population. Furthermore, there were investigated the personal attitude of diabetologists on VD supplementation. We hope that our findings may be an inspiration for a detailed investigation of factors limiting proper VD supplementation in the different local populations.The authors acknowledge several limitations of the study. Firstly, the data was collected using two different versions of the survey. Secondly, an anonymous survey is associated with the bias of the respondents. The answers came mostly from females with T1DM. Studies suggest that women are more eager to supplement VD than men ,37. TakeMost of the Polish individuals with T1DM use VD supplements and the decision is related to physicians’ recommendations and self-education.