Lobelia chinensis is a traditional whole grass herbal. With the continuous deepening of pharmacological research on TCM, the active ingredients of L. chinensis are continuously revealed, which contained the alkaloids, flavonoids, flavonoid glycosides and amino acids that have the good effects of anti-inflammatory, anti-viral and anti-diabetic. In order to further explore the targets of active ingredients and its anti-diabetic mechanism, a feasible network pharmacology analysis model based on chemical, pharmacokinetic and pharmacological data was developed by network construction method to clarify the anti-diabetic mechanism of L. chinensis. The present study conducted by gas chromatography–mass spectrometer (GC/MS), which identified 208 metabolites of L. chinensis, of which 23 ingredients may have effective pharmacological effects after absorption, distribution, metabolism, and excretion (ADME) screening. Network pharmacological analysis on the active ingredients revealed that 5-hydroxymethylfurfural in L. chinensis affects the insulin resistance signaling pathway by acting on GSK3B, TNF, and MAPK1, acacetin affects the diabetic pathway by acting on INSR, DPP4, and GSK3B, that regulate type 2 diabetes, non-insulin-dependent DM, and inflammatory diseases. These results successfully indicated the potential anti-diabetic mechanism of the active ingredients of L. chinensis.Diabetes mellitus (DM) is a chronic inflammatory disease, and the rapidly increasing DM is becoming a major problem of global public health. Traditional Chinese medicine (TCM) has a long history of treating diabetes. It has been developed and utilized because of its good efficacy and no toxic side effects.  Diabetes mellitus (DM) is a chronic inflammatory disease that seriously threatens human health, and is affected by the interaction between genetic and environmental factors . DM is cLobelia chinensis (L. chinensis Lour.) is an annual dwarf herb, belonging to the family Campanulaceae, and is widely distributed in East Asian countries including China, Korea, and Japan  has been used for treating DM for more than 2000 years. Relevant studies have shown that TCM can significantly improve blood sugar and clinical indicators of diabetic patients, and effectively delay the progress of DM. . Lobeliand Japan . Modern ammatory . Accordiavonoids , terpenoavonoids , lignansavonoids , alkaloiavonoids , and somL. chinensis by metabolomics analysis. Based on the pharmacokinetic and pharmacological data of components, we constructed a network pharmacological model of active ingredients, and systematically analyzed the potential anti-diabetes mechanism of active ingredients in L. chinensis. The detailed procedures can be seen in In order to comprehensively evaluate the pharmacological effects of TCM, network pharmacology has been introduced to explore the molecular mechanism of TCM in recent years . The devL. chinensis is a plant, commonly called Chinese lobelia, creeping lobelia, or Banbianlian, is a low-growing, tiny-leaved, herbaceous perennial that typically forms an attractive ground cover rising to only 2–3″ tall but spreading rapidly by creeping decumbent stems to 36″ wide. Creeping stems are clad with narrow, lanceolate, green leaves (to 3/4″ long). Pale pink to white, usually solitary flowers (1 1/4″across) bloom from the leaf axils from July to October. Each lobelia-like flower features two lanceolate to oblanceolate lateral lobes and three more prominent central elliptic lobes in a flattened plane. L. chinensis is 1 of the 50 fundamental herbs used in TCM  were added to the tube, and then placed at −80°C for 2 min, ground at 60 Hz for 2 min, and sonicated for 30 min. After that, 200 μl of chloroform was added to the tube and the mixtures were mixed thoroughly at ambient temperature, then 400 μl of water was added. The samples were centrifuged at 12,000g for 10 min at 4°C. An aliquot of the 200 μl supernatant was transferred to a glass sampling vial for desiccation at room temperature. Eighty microliters of methoxyamine hydrochloride in pyridine (15 mg/ml) was subsequently added. The resultant mixture was vortexed vigorously for 2 min and incubated at 37°C for 90 min, then 80 μl of BSTFA (with 1% TMCS) and 20 μl n-hexane was added into the mixture, which was vortexed vigorously for 2 min and incubated at 70°C for 60 min. All the samples were placed at ambient temperature for 30 min before gas chromatography–mass spectrometry (GC-MS) analysis. And all the samples were tested in triplicate.The derivatized samples were analyzed on an Agilent 7890B gas chromatography system coupled to an Agilent 5977A MSD system . DB-5MS fused-silica capillary columns  with highly pure helium (purity not less than 99.999%) at a constant ﬂow rate of 1.0 ml/min were utilized to separate the derivatives. The injector temperature was maintained at 260°C. Injection volume was 1 μl, and the split ratio was 10:1. The initial temperature of the column oven was 60°C, ramped to 125°C at a rate of 8°C/min, to 210°C at a rate of 4°C/min, to 270°C at a rate of 5°Cmin, to 305°C at a rate of 10°C/min, and finally held at 305°C for 3 min. The temperature of MS quadrupole and ion source (electron impact) was set to 150°C and 230°C, respectively. The collision energy was 70 eV. Scan mode was Full Scan mode (SCAN) and mass scan range was m/z 50–500.L. chinensis were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform   and blood–brain barrier (BBB) permeability. OB is one of the most important pharmacokinetic parameters in the characteristics of absorption, distribution, metabolism, and excretion (ADME) characteristics of drugs, indicating the ratio of the oral drug to the oral dosage of the blood circulatory system (https://pubchem.ncbi.nlm.nih.gov/) and Drug Bank (https://www.drugbank.ca/drugs).All of the constituent data of msp.php) . The acty system . The ADMy system . MeanwhiL. chinensis, a method combined with information integration and data mining was implemented. First of all, the active ingredients and interact targets were submitted to Cytoscape 3.2.1 software to construct an ingredient–target network to explore the pharmacological mechanism of the active ingredients of L. chinensis. The input data with Excel format file can be seen in the andIn order to identify the corresponding targets of the active ingredients of L. chinensis were uploaded to STRING (http://string-db.org) online website to obtain the information of protein-protein interaction (PPI). The website generated a score for each protein mutual information. The higher the score, the higher the confidence in the interaction between target proteins. Therefore, we selected high confidence data >0.7 to ensure the reliability of this analysis. The obtained protein interaction data were imported into Cytoscape 3.2.1 software to construct a PPI protein interaction network.To explain the interaction between target proteins, the target proteins of related ingredients of L. chinensis in gene function and signaling pathway, the Database for Annotation, Visualization and Integrated Discovery  v6.8 was used to analyze the Gene Ontology (GO) function and KEGG pathway enrichment of proteins involved in PPI network. The target proteins involved in the cellular components (CC), molecular function (MF), biological process (BP), and the pathways were also described.To elucidate the role of target proteins that interact with the active ingredients of After getting the interaction information of the active ingredient compounds, target proteins, and the pathways, the “Ingredient–Target–Pathway” network was established by Cystoscope 3.2.1 software. In the network, nodes represent components, targets, and pathways, edges represent the interaction of each other. Then a hypothesized schematic diagram of the target proteins involved in the pathways was drawn. Based on the network model map, the pathway of active ingredients and targets in the disease is initially explored to provide a preliminary theoretical basis for the design of subsequent targeted drugs.L. chinensis powder was analyzed triple times by GC/MS. The results showed strong signals, high peak capacity, and well reproducibility. The typical total ion current (TIC) was shown in L. chinensis are shown in To demonstrate the ability of the GC/MS method to accurately separate and identify ingredients, the sample of L. chinensis ingredients with favorable pharmacokinetic properties. Therefore, all chemicals that meet the screening criteria: OB (> 30%) and BBB (>-0.3) are considered as candidate ingredients. Twenty-three differentiated ingredients with effective pharmacological activities were identified after screening ADME parameters  for PPI network construction, and high confidence of protein interaction data with a score >0.7 was selected . Meanwhile, they could also regulate inflammatory cytokines, promote endocrine and metabolism, and achieve the therapeutic effect in the treatment of diabetes.In this study, 208 metabolites of active ingredients in L. chinensis on DPP-4.GSK3B is a serine-threonine kinase in glycogen synthase subfamily, and it is also a negative regulator of glycometabolism balance that participates in energy metabolism, inflammatory response, endoplasmic reticulum stress, mitochondrial dysfunction, and apoptotic pathway . SelectiAccording to the results of pathway analysis, mitogen-activated protein kinases (MAPKs), including extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 MAPK, may also play a crucial role in regulating diabetes and inflammation through the MAPK signaling pathway. The MAPKs are extracellular signal-regulated protein kinases, increasing cellular proliferation and involving in the cell survival regulation . MAPK caet al. have shown that TNF-alpha is an inflammatory mediator, and its overexpression can lead to the rapid activation of p38MAPK under the external or internal stimulation, which promotes the production of IL-6 and induces the body’s inflammatory response  on the surface of liver cell membrane and then activates insulin receptor phosphorylates tyrosine site of IRS-1/2, regulating the PI3K/AKT signal pathway, of which IRS2 is the main target in the insulin metabolism effects in liver . The actL. chinensis can regulate target proteins involved in signal pathways and play a role in stabilizing signal pathway, revealing the multi-ingredient–multi-target–multi-pathway action mode of TCM. Deep analysis of anti-diabetic and anti-inflammatory pharmacological effects of L. chinensis, as well as the target and pathway acting with the active ingredients still need to be further validated.In summary, the pathogenesis of DM is more complex, and the signal pathways are cross-linked and mutually modulated, presenting a multi-pathway and multi-target pattern. The active ingredients of All datasets generated for this study are included in the article/QG is the major contributor to this manuscript. QG conducted the analytical part, wrote the first version of the manuscript, and finalized the manuscript. LC and YY downloaded the reference and processed the graph and the table in the manuscript. LL, FF, PL, and SM collected the data. KC (corresponding author) and QY (corresponding author) conceived and coordinated the study, and critically evaluated the data. All authors read and approved the final manuscript.This work was supported by the National Natural Science Foundation of China  and the Maternal and Child Health Research Project of Jiangsu Province (F201604).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.


Diabetic nephropathy (DN) is the leading cause of ESRD. Emerging evidence indicated that proteinuria may not be the determinant of renal survival in DN. The aim of the current study was to provide molecular signatures apart from proteinuria in DN by an integrative bioinformatics approach.  Affymetrix microarray datasets from microdissected glomerular and tubulointerstitial compartments of DN, healthy controls, and proteinuric disease controls including minimal change disease and membranous nephropathy were extracted from open-access database. Differentially expressed genes (DEGs) in DN versus both healthy and proteinuric controls were identified by limma package, and further defined by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Hub genes were checked by protein-protein interaction networks.  A total of 566 glomerular and 581 tubulointerstitial DEGs were identified in DN, which were commonly differentially expressed compared to normal controls and proteinuric disease controls. The upregulated DEGs in both compartments were significantly enriched in GO biological process associated with fibrosis, inflammation, and platelet dysfunction, and largely located in extracellular space, including matrix and extracellular vesicles. Pathway analysis highlighted immune system regulation. Hub genes of the upregulated DEGs negatively correlated with estimated glomerular filtration rate (eGFR). While the downregulated DEGs and their hub genes in tubulointerstitium were enriched in pathways associated with lipid metabolism and oxidation, which positively correlated with eGFR.  Our study identified pathways including fibrosis, inflammation, lipid metabolism, and oxidative stress contributing to the progression of DN independent of proteinuria. These genes may serve as biomarkers and therapeutic targets. Diabetic nephropathy (DN) is the leading cause of chronic kidney disease (CKD) and end stage renal disease (ESRD) , 2. AlthRenal biopsy captures pathological characteristics of the disease and the gene expression profiles of renal tissue provide unbiased comprehensive understanding of the molecular mechanisms. Several transcriptome analyses have been taken in DN and they observed molecules and pathways aberrantly regulated in DN such as matrix expansion, vascular damage, and inflammation –10. ResuIn the current study, to further rule out the confounding role of proteinuria, we included datasets from both DN and proteinuric controls including minimal change disease (MCD) and membranous nephropathy (MN) , 12. Andhttps://www.ncbi.nlm.nih.gov/geo/). “Diabetic nephropathy OR DN”, “Membranous nephropathy OR membranous glomerulonephritis OR MGN OR MN”, and “minimal change diseases OR MCD” were searched, respectively, and kidney biopsy samples were from the European Renal cDNA bank (ERCB) cohort, which was established to collect kidney biopsy tissue for gene expression analysis, were studied. After excluding duplicated submissions, GEL files from GSE47183 [Microdissection transcriptome data were obtained from the public genomics data repository GEO  [According to the published study which originally submitted the microdissected glomeruli microarray, the urinary protein level of DN, MN, and MCD cases were 3.1 ± 2.7 g/d, 4.6 ± 3.2 g/d, and 6.7 ± 5.8 g/d, respectively . The mic 1.73m2) .P < 0.05 and fold changes >1.5.Affymetrix CEL files were normalized using the robust multiarray average method, log2 transformed using R software (version 3.6.1). Expression data with shared probes by the Human Genome U133 Plus 2.0 Array and Human Genome U133A Array were combined and batch corrected by “removebatcheffects” function in Limma package . Probes https://david.ncifcrf.gov/) was used for GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. GO analysis enables the annotation of cellular component (CC), biological process (BP), and molecular function (MF). KEGG pathway illustrates the path of the gene cluster and associated functions. GO annotations relating to other diseases or organs were excluded. Gene count >2 and P < 0.05 were set as the threshold.An online bioinformatics tool DAVID version 6.8 (http://string-db.org/) was used to construct the PPI networks of DEGs. Interaction score >0.7 was set as the cut-off point. Cytoscape software version 3.6.1 was applied to visualize the PPI network and analyze the interactive relationships. The plugin cytoHubba [The Search Tool for the Retrieval of Interacting Genes (STRING) version 11 (ytoHubba  was usedhttp://v5.nephroseq.org/) and analyzed using the spearman correlation coefficient. P values <0.05 were considered statistically significant.The correlation between hub gene expression and estimated glomerular filtration rate (eGFR) in DN patients was performed in Nephroseq v5 online platform  enriched pathways in glomeruli and 8 of 16 (50%) in tubulointerstitium were involved in the immune system regulation, including chemokine signaling pathway, complement and coagulation cascades, natural killer cell-mediated cytotoxicity, platelet activation, and NOD-like receptor signaling pathway. Of note, upregulated DEGs in both glomeruli and tubulointerstitium were enriched in NF-kappa B signaling pathway, and PI3K-Akt signaling pathway Figures . The anaIn both glomeruli and tubulointerstitium, the upregulated hub genes identified by the MCC algorithm of interactions were associated with inflammatory  and fibrosis  and collagens  were observed to have a negative correlation with eGFR in DN patients Figures . While tAlthough DN is not considered an inflammatory disease, kidney inflammation could be a key pathophysiological mechanism. In our study, the increased hub genes relating to the inflammation in glomeruli and tubulointerstitium included chemokines, i.e., CCL5, CXCL1, CCL19, and CCL21, chemokine receptor CCR2, and complement C3. The hub chemokines CCL5 and CCR2 recruited macrophages , 19, whiOne main pathological characteristic of DN is diffuse extracellular matrix accumulation. Both glomerular and tubular basement membrane thickening occur at an early stage , 33. AndMoreover, GO analysis showed that both glomerular and tubulointerstitial DEGs were enriched for genes located in extracellular vesicles, including exosomes and blood microparticles. Extracellular vesicles are host cell-derived packages of information which mediate intercellular communication . AccumulInjury of renal tubular cells is a prominent histopathological feature of DN and is regarded as an important contributor to impaired kidney function . ExploriOur study has several limitations. First, due to lack of detailed information of patients, it is difficult to control and evaluate the influence of demographic factors or the stage of the disease process on the analysis. Second, renal function impairment among different groups was unmatched. Third, the analysis was based on transcripts, which are not always the same as those on the protein level. Fourth, shared DEGs not enriched in enrichment analysis or selected as hub genes could also play an important role in the DN progression. However, as conventional treatment based on strict control of hypertension, hyperglycemia, and proteinuria fails to prevent DN patients from renal failure, novel therapeutic strategies are urgently needed. And this analysis suggests that strategies focus on impeding renal inflammation and fibrosis, correcting dysregulated tubular lipid metabolism and oxidative-reduction process from an integrative bioinformatics aspect.In summary, our study disclosed the pathogenic molecules and pathways promoting the progression of DN independent of proteinuria. We identified a total of 566 glomerular and 581 tubulointerstitial shared DEGs and highlighted the importance of pathways associated with fibrosis, inflammation, lipid metabolism, and oxidative stress in DN. These genes and pathways could be potential targets for the treatment of DN.


The incidence of type 2 diabetes mellitus (T2DM) has increased year by year, which not only seriously affects people's quality of life, but also imposes a heavy economic burden on the family, society, and country. Currently, the pathogenesis, diagnosis, and treatment of T2DM are still unclear. Therefore, exploration of a precise multitarget treatment strategy is urgent. Here, we attempt to screen out the active components, effective targets, and functional pathways of therapeutic drugs through network pharmacology with taking advantages of traditional Chinese medicine (TCM) formulas for multitarget holistic treatment of diseases to clarify the potential therapeutic mechanism of TCM formulas and provide a systematic and clear thought for T2DM treatment. http://cytoscape.org/,ver.3.5.1) and then analyzed gene function, related biological processes, and signal pathways through the DAVID database.  First, we screened the active components of Da-Chai-Hu Decoction (DCHD) by absorption, distribution, metabolism, excretion, and toxicity (ADME/T) calculation. Second, we predicted and screened the active components of DCHD and its therapeutic targets for T2DM relying on the Traditional Chinese Medicine Systems Pharmacology Analysis Platform (TCMSP database) and Text Mining Tool (GoPubMed database), while using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to obtain T2DM targets. Third, we constructed a network of the active component-target, target-pathway of DCHD using Cytoscape software ( We screened 77 active components from 1278 DCHD components and 116 effective targets from 253 ones. After matching the targets of T2DM, we obtained 38 important targets and 7 core targets were selected through further analysis. Through enrichment analysis, we found that these important targets were mainly involved in many biological processes such as oxidative stress, inflammatory reaction, and apoptosis. After analyzing the relevant pathways, the synthetic pathway for the treatment of T2DM was obtained, which provided a diagnosis-treatment idea for DCHD in the treatment of T2DM.  This article reveals the mechanism of DCHD in the treatment of T2DM related to inflammatory response and apoptosis through network pharmacology, which lays a foundation for further elucidation of drugs effective targets. Type 2 diabetes mellitus (T2DM), as the most common type of diabetes, refers to metabolic imbalance of glucose, protein, lipid, water, and electrolyte, caused by genetic, environmental, and psychological factors. It is pathophysiologically characterized by a declined ability of insulin to regulate glucose metabolism accompanied by a decrease or relative decrease in insulin secretion due to defects of islet B-cell function. If one's random blood glucose is ≥11.1 mmol/L or fasting blood glucose is ≥7.0 mmol/L, the patient can be diagnosed as diabetes when accompanying with typical symptoms including polydipsia, polyuria, polyphagia, and unexplained weight loss , retinopHowever, due to the multicomponent and multitarget characteristics of TCM formulas, the action mechanism of most TCM formulas for diseases is still unclear. Therefore, we attempt to screen out the active components, effective targets, and functional pathways of drugs through network pharmacology and combined with the advantages of TCM classic formulas for the multitarget holistic treatment, to clarify the mechanism of TCM formulas and provide a systematic and clear idea for the treatment of T2DM.xiāo kĕ ” and “splenic pure heat ” in TCM field. The cause of this disease is attributed to external contraction and internal damage. Externally, constraint of the six pathogenic factors results in the invasion of toxin, dryness-heat, and wind-heat pathogens into zang-fu organs, dryness generating, and liquid being damaged, which finally leads to xiāo kĕ. Internally, generation of heat because of emotional disorders and constraint of liver qi, damp-heat generated by intemperate eating, or yin depletion and abnormal exuberance of dryness-heat causes xiāo kĕ. In the early and middle stages of the onset, sturdy patients present with thirst, bitter taste in the mouth, halitosis, polydipsia, polyphagia, irritability, fullness and distension in the hypochondriac regions, dark urine, dry and hard stool, red tongue with yellow coating, and wiry, excess, and powerful pulse. According to pattern differentiation, these symptoms are diagnosed as liver-stomach heat pattern and its typical formula is Da-Chai-Hu Decoction . The application of DCHD was first recorded in Treatise on Febrile and Miscellaneous Diseases. It has a history of more than 2,000 years. DCHD can harmonize shaoyang and drain heat bind in yangming, whose indication is overlap of diseases of shaoyang and yangming. DCHD is composed of Bupleurum, Scutellaria root, peony root, Pinellia Rhizome, immature bitter orange, rhubarb root and rhizome, fresh ginger, and Chinese date. Among them, Bupleurum resolves constraint and soothes the liver and rectifies qi when combined with peony root, one for dissipating and one for contraction. Bupleurum and Scutellaria root can clear liver heat, and immature bitter orange and rhubarb root and rhizome unblock the bowels and discharge heat in the stomach and intestines. Scutellaria root and rhubarb root and rhizome auxiliary with Pinellia Rhizome and fresh ginger open the middle jiao, with acrid herbs opening and bitter herbs promoting descent. Chinese date harmonizes the actions of all herbs in a formula. All herbs together can rectify qi to resolve constraint, clear heat, and dissipate masses so as to resolve constraint and discharge heat in the liver and stomach, and then xiāo kĕ itself resolves. The results of modern pharmacological experimental research show that the ingredients in DCHD can lower blood sugar. Bupleurum is the chief medicinal of DCHD. Jin et al showed that Bupleurum has the effect of treating diabetes [κB inflammatory factors [T2DM belongs to “diabetes . Baicalidiabetes . Naringidiabetes . Peony rdiabetes . Rheum ediabetes . Experim factors .Network pharmacology was first proposed by Hopkins in 2007. It is a discipline that studies the occurrence and development of diseases from the perspective of biological network, recognizes the interaction between drugs and the body, and guides the discovery of new drugs. T2DM is a complex metabolic disease determined by multiple genes and multiple factors, not by a single gene or a single factor. Therefore, complex diseases often cannot be effective by intervening in a single target, and the TCM formula is composed of various components, which can simultaneously act on multiple targets through multiple pathways . Typicalhttp://lsp.nwu.edu.cn/tcmsp.php) [Radix Bupleuri (RB), 138 in Scutellariae Radix (SR), 119 in Radix Paeoniae Rubra (RPR), 116 in Arum Ternatum Thunb (ATT), 65 in Aurantii Fructus Immaturus (AFI), 92 in Radix et Rhizoma Rhei (RERR), 265 in Zingiber Officinale Roscoe, (ZOR), and 134 in Jujubae Fructus (JF). In order to screen out potential active compounds, the active molecules with high oral bioavailability (OB) in the organic metabolism from these components, we use the six principles of generic drugs of molecular weight (MW), AlogP, Hdon, Hacc, OB, and DL for screening in this work. From Radix Bupleuri, 25 in Scutellariae Radix, 4 in Radix Paeoniae Rubra, 4 in Arum Ternatum Thunb, 16 in Aurantii Fructus Immaturus, 5 in Radix et Rhizoma Rhei, 1 in Zingiber Officinale Roscoe, and 14 in Jujubae Fructus  . As a br(1) MW Prediction. MW refers to the mass of a molecule. As one of the parameters of Lipinski's “rule of five,” it plays a critical role in pharmacological or biological activity because the size of MW will affect the size of the molecular fragment, then affecting the membrane absorption of drugs. Generally speaking, small molecules are more easily absorbed and distributed, while macromolecules are not only less easily absorbed, but also more easily excreted by bile. The components with MV from 180 to 500 Dalton are perceived as most available in drug therapy (MW ≤ 500).(2) AlogP Prediction. The AlogP is the logarithm of the ratio of the equilibrium concentration of a compound in a nonaqueous phase to its equilibrium concentration in the aqueous phase in a neutral form. The logarithmic value of the partition coefficient P of the compound in octanol/water system is usually used as a measure of AlogP. Abiding by the Ghose–Crippen method, it is calculated from a regression equation based on the hydrophobicity contribution of 120 atom types, including common bonding of H, C, N, O, and S and the halogens (AlogP ≤5) [logP ≤5) .(3) Hdon and Hacc Prediction. The hydrogen-bond capacity of a drug solute is an important parameter of permeability [eability . To croseability . Consequ(4) OB Prediction. OB is defined as the ratio of the number of active components absorbed into the circulatory system playing roles at the site of action to the sum of active components. OB is one of the most important indicators for evaluating ADME characteristics via bioinformatics. In this work, the OB screening was calculated by a powerful in-house system, OBioavail1.1 [avail1.1 , and theavail1.1 .(5) DL Prediction. DL means that a molecule contains some specific functional group or presents with the same or similar physical characteristics as most drugs. As a qualitative profile, DL is frequently used in drug design to evaluate whether a compound is chemically suitable for the drug, and how DL a molecule is with respect to parameters affecting its pharmacodynamic and pharmacokinetic profiles which will ultimately impact its ADME properties [operties . In thisA represents the descriptor of the new numerator and B indicates all the 6511 molecules selected from the DrugBank database (available online at http://www.drugbank.ca). The average of all descriptors was calculated by Dragon and the compounds with DL ≥ 0.18 were selected [In this equation, selected .From the above, in order to obtain the core active components, the screening principle was defined as follows: MW ≤ 500, AlogP ≤5, Hdon ≤5, Hacc ≤10, OB ≥ 30%, and DL ≥ 0.18.http://www.uniprot.org/) to obtain the official symbol for each protein by inputting the protein names with the species limited to “Homo sapiens.” UniProt database provides the scientific community with comprehensive, high-quality, and free access to protein sequence and functional information [After screening the active components, it was quite critical to find the targets of each component. First, in order to obtain putative targets of potential active components in DCHD, we searched for the corresponding targets based on the systematic drug targeting tool (SysDT) as described in our previous work. Second, we screened out drug targets corresponding to the active components that we screened before. Here, the principle of predicting the corresponding targets of pharmaceutical components was based on two mathematical approaches that effectively integrate large-scale chemical, genomic, and pharmacological information to accurately predict drug-target interactions , with a ormation . Eventuahttp://ctdbase.org/), the Online Mendelian Inheritance in Man database , and the Human Gene Database (http://www.genecards.org/). CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health, which provides curated and inferred chemical-disease associations that are real associations extracted from the literature. All the targets of T2DM were deduced from the CTD database, and 200 targets were filtrated from the inference score of ≥57.56 [Information regarding T2DM-associated target genes was collected from the Comparative Toxicogenomics Database  [All the protein-protein interaction (PPI) data were derived from STRING (r. 10.5) . To be sr. 10.5) .The network construction was performed as follows: (1) active compound-active compound target network of DCHD was constructed; (2) herb-compound target-T2DM target network was built by connecting the eight DCHD herbs with compound targets of each herb and T2DM targets; and (3) active compound targets-T2DM targets-other human proteins' PPI network was established.http://cytoscape.org/, ver. 3.5.1) [We created the networks by utilizing the network visualization software Cytoscape (. 3.5.1) . CytoscaThere are three parameters used to evaluate every node in a network, including degree, node betweenness, and closeness. Degree indicates the number of edges between a node and other nodes in a network . Betweenhttps://david.ncifcrf.gov/, ver. 6.8) [The functional enrichment tool DAVID   was usedThis network contained 238 nodes (161 compound target nodes and 77 active compound nodes), as shown in β, JUN, MAPK3, and tumor protein 53 (TP53). The correlations of these 7 core targets were all over 27, of which the highest degrees were CAT and IL-6, up to 31, followed by TNF (30), and then to IL-1β (28), and to JUN, MAPK3, and TP53 . We found that DC was positively correlated with CC and BC. The larger the target of CC or BC is, the greater its DC value will be, indicating the powerful synergic effect between this target and other targets, as well as the critical role in the treatment of T2DM. With regard to CAT, the expression of catalase in organism can be enhanced by drugs to strengthen the antioxidant state and regulate the metabolic homeostasis and then effectively control blood sugar [β, c-JUN, and MAPK3 to reduce the proinflammatory response and thus to treat T2DM [The 161 targets of DCHD were corresponding to 200 targets of T2DM, and 38 repeat important targets were obtained  all get involved in inflammatory response via TNF signaling pathway. Endothelial nitric oxide synthase (NOS3), glycogen synthase kinase-3β (GSK-3β), peroxisome proliferator antigen receptor-γ (PPAR-γ), and B-cell lymphoma-2 (Bcl-2) get involved in the regulation of apoptosis through PI3K/AKT signaling pathway. Therefore, the therapeutic mechanism of DCHD on T2DM mainly includes the following two modules: inflammation and cell apoptosis.The 38 core targets were imported into the DAVID, and 89 pathways were obtained. Through systematic review of relevant literature and summary of T2DM-related pathogenesis, 20 signal pathways closely related to T2DM were screened. To further integrate T2DM core targets, we finally detected two core pathways , namely,(1) Inflammation Module. T2DM is a low-grade inflammatory response disease [κB signaling pathway mediated by inflammatory factors such as TNF-α and IL-1β. When there is no inflammatory factor stimulation in human body, NF-κB binds to its inhibitor IĸBα in the cytoplasm when NF-κB is not activated. For T2DM patients, inflammatory factors, growth factors, or chemokines can be activated in the body. In the presence of NF-κB stimulation, inflammatory factors bind to TNFR1, and IKKβ complexes are activated by NF-κB-induced kinase phosphorylation, resulting in phosphorylation of IĸBα at the sites of Ser32 and Ser36, followed by degradation of the ubiquitin-proteasome pathway. This results in the dissociation of NF-κB from its inhibitor IĸBα, exposing the nuclear localization sequence of NF-κB. And then, NF-κB is transferred to the nucleus to promote NF-κB-dependent gene transcription. NF-κB mainly regulates the transcriptional effects of IL-6, IL-1β, VCAM-1, COX-2, TNF-α, and JUN [ disease . The inf disease . Due to  disease . Therefo and JUN –67, ther(2) Apoptosis Module. The fundamental pathophysiological mechanism of T2DM is insulin resistance, which results in islet β-cell dysfunction and, in extreme cases, apoptosis of β-cells. Therefore, islet β-cell apoptosis serves as the main pathogenic feature of T2DM. Increasing evidence demonstrates that the PI3K/Akt signaling pathway plays a crucial role in regulating β-cell apoptosis [β-cell apoptosis can be transduced by receptor tyrosine kinase (RTK) and TLR2 receptors. The first is the largest enzyme-linked receptor, which is both an enzyme and a cell surface receptor for cytokines, hormones including insulin, and polypeptide growth factors. The insulin receptor tyrosine kinase (IRTK) in RTKs is a transmembrane receptor composed of two extracellular α-subunits that bind to disulfides and two transmembrane β-subunits [α-subunit of the IRTK, causing a conformational change in the RTK, thereby enhancing transphosphorylation between the transmembrane β-subunits further enhances the phosphokinase activity of the RTK, which in turn phosphorylates the insulin receptor substrate (IRS-1). IRS-1 successively combines with PI3K regulatory subunit p85 and catalytic subunit p110, and the activated PI3K produces the second messenger phospholipid inositol -triphosphate to promote the activation of AKT. The other type is TLR2, which belongs to Toll-like receptor family and is a very conservative innate immune receptor that can recognize pathogen or injury-related molecular patterns, among which TLR2 is the member that recognizes pathogen-related molecular patterns most. When inflammatory factors in T2DM patients bind to TLR2 receptor, TLR2 activates Rac-1 [β-cell dysfunction and ultimately β-cell apoptosis. AKT phosphorylation can also mediate glycogen synthesis by inhibiting GSK3 [β-cell apoptosis activity. Early studies have also shown that insulin inhibits GSK3 activity through phosphorylation induced via the PI3K/AKT signaling pathway and promotes glycogen synthesis and glucose utilization, thereby inhibiting apoptosis in β-cell cells [β-cell apoptosis. TNFR2 is a type II receptor of TNF-α in TNF signaling pathway, promoting cell migration, regeneration, and proliferation. TNFR2 activates JNK through its domain III binding to c-Jun-N-terminal kinase- (JNK-) specific signaling molecule AIP1. JNK is an important intracellular signal transduction pathway [β-cells [β-cell apoptosis downstream of the PI3K/AKT signaling pathway include Bcl-2, TNF, and PPAR-γ. Bcl-2 is one of the oncogenes closely related to apoptosis [β-cell apoptosis is caused by the concentration of proapoptotic Bcl-2 protein in the β-cell exceeding the concentration of antiapoptotic protein on the mitochondrial membrane of the intrinsic pathway [α-mediated inflammatory responses initiate the onset of islet β-cell apoptosis [γ is an important cell differentiation transcription factor, mainly expressed in adipose and skeletal muscle tissues. Activation of PPAR-γ in such mature cells can induce the expression of genes involved in the insulin signaling cascade, thereby improving insulin sensitivity and islet structure, and increase β-cells, and therefore, PPAR-γ has an effect of inhibiting β-cell apoptosis [β-cell apoptosis. Promotion of anti-β-cell apoptosis targets including Bcl-2 prosurvival protein and PPAR-γ, and inhibition of other pro-β-cell apoptosis targets such as TNF can inhibit β-cell apoptosis, thereby effectively controlling the development of T2DM.poptosis . PI3K issubunits . In insues Rac-1 , which bes Rac-1 . Activates Rac-1  and AKT es Rac-1 . In patiing GSK3 . GSK3 isll cells . In addi pathway . JNK act[β-cells . Targetspoptosis . A commopoptosis . Many stpoptosis –81. Ther pathway . TNF is poptosis . PPAR-γ poptosis . In summIn the present study, by network pharmacology, we deeply analyzed the two major pathological mechanisms of T2DM mediated by inflammation and apoptosis from the corresponding pathways of T2DM targets. Taking DCHD as an example, we explored the therapeutic effect of drugs on T2DM by blocking the corresponding inflammatory or apoptotic pathway leading to T2DM, which is of great significance in guiding the treatment of T2DM. However, the results obtained in this study have not been experimentally verified. Therefore, further experimental validation to increase the accuracy and feasibility of the research results is warranted.As a traditionally prepared formula, DCHD is an important complementary and alternative medicine for the treatment of T2DM and has also been widely used in the treatment of T2DM in modern clinical practice. In this study, we attempted to clarify the relevant targets and related pathways for the treatment of T2DM with DCHD by integrating systematics, pharmacology, and genomics. Our research shows that the eight herbs in DCHD play a synergistic effect to some extent, mainly through the inflammatory signaling pathway represented by TNF signaling pathway and the apoptotic signaling pathway represented by PI3K/Akt signaling pathway. The targets in these two pathways may be the targets of T2DM. To sum up, network pharmacology established in this study preliminarily reveals the modern application value of TCM formula in multitarget treatment for related diseases at the molecular level and also provides a paradigm for studying multitarget treatment of diseases, which is of great practical significance.


This is a clear indication that protein kinases still represent major drug targets for the pharmaceutical industry. In a previous work, we have introduced PKIDB, a publicly available database, gathering PKIs that have already been approved (Phase 4), as well as those currently in clinical trials (Phases 0 to 3). This database is updated frequently, and an analysis of the new data is presented here. In addition, we compared the set of PKIs present in PKIDB with the PKIs in early preclinical studies found in ChEMBL, the largest publicly available chemical database. For each dataset, the distribution of physicochemical descriptors related to drug-likeness is presented. From these results, updated guidelines to prioritize compounds for targeting protein kinases are proposed. The results of a principal component analysis (PCA) show that the PKIDB dataset is fully encompassed within all PKIs found in the public database. This observation is reinforced by a principal moments of inertia (PMI) analysis of all molecules. Interestingly, we notice that PKIs in clinical trials tend to explore new 3D chemical space. While a great majority of PKIs is located on the area of “flatland”, we find few compounds exploring the 3D structural space. Finally, a scaffold diversity analysis of the two datasets, based on frequency counts was performed. The results give insight into the chemical space of PKIs, and can guide researchers to reach out new unexplored areas. PKIDB is freely accessible from the following website:  Protein kinases constitute one of the largest protein families encoded by the human genome and counts 518 members  [The reversible phosphorylation of proteins plays a preeminent role in cell cycle regulation. This process, which consists in the transfer of a phosphoryl group POncluded) , as wellncluded) . The majncluded) , and thencluded) ,10. Thesncluded) . Since thttp://www.icoa.fr/pkidb). As of 11th of December 2019, it contains 218 inhibitors: 60 approved and 158 in various stages of clinical trials (from Phase 0 to Phase 3).In addition to approved PKIs, many novel compounds are currently being evaluated in clinical trials throughout the pharmaceutical industry. Taken collectively, these compounds show new trends in terms of structures, physicochemical properties, and biological activities that foreshadows changes in the PKI landscape. To collect and organize this data as well as keep up to date with their evolution, we developed PKIDB , a curatIn this study, we compared PKIDB to a large dataset of 76,504 PKIs retrieved from ChEMBL . The objective is to be able to better select PKIs from public databases based on structural and physicochemical property information of PKIs already in clinical trials. Firstly, we performed a principal component analysis (PCA), and compared the projection of both datasets in a common factorial space. We also assessed the structural shape diversity of PKIs using a principal moments of inertia (PMI) analysis. Secondly, in addition to comparisons at the global molecular structure level, we performed a substructure analysis based on PKI scaffolds. In medicinal chemistry, scaffolds are mostly used to represent core structures of bioactive compounds. They are relevant for the medicinal and/or computational chemists, and have proved to be useful in the identification of “privileged substructures”  in “scafThe balance between the molecular diversity of scaffolds, and their frequency is an important parameter in a chemical database. A high frequency associated to a small number of scaffolds corresponds to a focused library composed of structurally similar molecules, bearing varying substituents. Contrarily, a low frequency associated to a large number of scaffolds reflects a high molecular diversity . Thus, tThe description and analysis of PKIDB have been reported in a previous study by Carles et al. . ReferenAmong these 38 compounds, nine were FDA-approved in 2017, eight in 2018, and seven in 2019. Fasudil, a ROCK inhibitor, approved in China and in Japan in 1995 was therefore the first kinase inhibitor that reached the market, but it is not FDA approved. Those compounds were automatically added to PKIDB database thanks to their name stem. Indeed, since the first release of PKIDB, the INN made an update on the stems that assign the molecules with the “aurin” and “udil” suffixes to the kinase inhibitor class. Moreover, the stem ‘cidib’ was also updated and has been replaced by ‘ciclib’ (see cumulative USAM stem list from AMA ). HoweveIn addition to those compounds, This brings the total number of approved drugs on the market referenced in our database to 60. As described in PKIDB, most of the PKIs are targeting more than one protein kinases, and since the first version of PKIDB, new targets have emerged, such as the Wee1-like protein kinase inhibited by adavosertib .To describe a molecule, it is common to compute its physicochemical properties to obtain information on the size, the lipophilicity, the atomic composition, etc. Some descriptors, as described by Lipinski or Veber, are still widely used to evaluate the potential oral bioavailability of a compound ,26. LipiIn a previous study , we analWe found that 62% and 68% of PKIs in PKIDB and in ChEMBL, respectively, do not violate any Lipinki’s rule. One single violation occurs in 28% and 24% of the PKIs for PKIDB and ChEMBL, respectively, and two violations occur for about 10% of the PKIs in the two datasets. Finally, few PKIs in ChEMBL dataset violates more than two rules (0.2%), and none for the PKIs in PKIDB. These results may vary, depending on how the LogP is calculated. Here, we used Wildman-Crippen approach . CompareThe ratio of PKIs having descriptors out of the Lipinski’s or Veber’s rule are given in From these calculations, we propose a range of descriptors to guide the design of kinase inhibitors. The proposed ranges do not consider the property values beyond two standard deviations from the mean . Thus, the upper and lower limits of molecular descriptors better represent the current chemical space of kinase inhibitors, either approved or in clinical trials.One can notice that despite new PKIs in PKIDB, these guidelines have not changed much compared to the ones presented in our first study. This shows that the define PKI chemical space seems well defined.A molecular weight (MW) between 314 and 613 Da (average of 463.4 Da);A ClogP ) between 0.7 and 6.3 (average of 3.5);Between 0 and 4 hydrogen bond donors (HBD) (average of 2.2);Between 3 and 10 hydrogen bond acceptors (HBA) (average of 6.4);2 (average of 96.6 Å2);A topological polar surface area (TPSA) comprised between 55 and 138 ÅBetween 1 and 11 rotatable bonds (NRB) (average of 6.0);Number of aromatic rings (NAR) between 1 and 5 (average of 3.4);Number of chiral atoms (NCA) between 0 and 2 (average of 0.5).Considering all PKIs from PKIDB, the guidelines for prioritization are:To compare the chemical space of the kinase inhibitors from PKIDB and from ChEMBL (PKI_ChEMBL), we performed a principal component analysis (PCA). Each molecule was described using 10 classical physicochemical descriptors  well suited to characterize chemical structures. The goal here is to compare PKI_ChEMBL to PKIDB.The PCA plot  illustraThe two first principal components explain 35.6% and 20.0% of the total variance respectively. PC3, not shown here, encompasses 13.2%. Thus, the 2D scatterplot of the factorial space illustrated here represents around 56% of the total variance .Each dot on the graph a represeIn view of these results, PCA confirms our preliminary observations that there are few outliers in PKI_ChEMBL dataset (dots on the upper right quadrant). It appears that these compounds correspond to either small-modified peptides or macrocyclic lactones with high TPSA values. These molecules, such as everolimus, were removed from PKIDB, since they do not inhibit protein kinases directly, however, the macrocycles in PKI_ChEMBL are active on protein kinases and, thus, were not removed from the dataset. Regarding the compounds in PKIDB, semaxanib, has the lowest MW . The two dots outside the circle and on the middle right of the quadrant corresponds to barasertib  and fostamatinib (Approved_PKI in red). Both of these molecules contain phosphate group, increasing their TPSA, and therefore explaining their position on the PCA map.Until now, we only analyzed the molecules using 2D descriptors; therefore, to evaluate the shape diversity, we represented the molecules on a principal moments of inertia (PMI) plot . In a trThe PMI plot  reveals Here again, there is a great resemblance between the two datasets, PKIDB being well encompassed in PKI_ChEMBL regarding shape diversity.To get a deeper insight on the molecular diversity of PKIs, we focused on scaffolds and ring systems of these compounds. The results of scaffold analysis are summarized in The different types of molecular scaffolds are shown in In PKIDB dataset, among 218 molecules, 207 present a unique BM scaffold and 195 a unique graph framework (GF). Whereas, for the 76,504 PKIs present in ChEMBL, only 28,732 and 13,331 BM scaffolds and GF, respectively, are found . In otheThe most represented BM scaffold in PKIDB, the indolinone derivative , is retrThen, for each unique BM scaffold in PKIDB, we checked how many PKIs are obtained in PKI_ChEMBL. From the 207 unique BM scaffolds available in PKIDB, only 107 are present in PKI_ChEMBL, which represent 2423 molecules out of a total of 76,504 (3.2%). This result is surprising. Firstly, we might expect that many analogues would be systematically provided for each PKI and, thus, would be available in a public database. Secondly, because PKIDB covers similar chemical space to PKI_ChEMBL according to PCA and PMI comparisons. Finally, using all unique graph frameworks from PKIDB, we were able to match 7686 compounds (10.0%) in PKI_ChEMBL.In PKIs, rings are making hydrogen bonds, van der Waals or π-stacking interactions with residues of the active site. As example, an heterocycle may form hydrogen bonds, as does adenine in ATP with protein kinase . We applIn both datasets, we found bicycles in around 65% of the molecules, demonstrating their importance as a core during hit to lead or lead optimization steps. In PKIDB, we found 56 unique bicyclic scaffolds among the total of 172. More surprising, 31 out of these 56 bicycles are singletons, i.e., the bicyclic scaffold is found only once in the dataset. For the PKI_ChEMBL dataset, there are 918 unique bicycles for a total of 57,438. However, among those 918 unique bicycles, only 26 are singletons. Since the PKI_ChEMBL dataset contains more analogues of chemical series compared to PKIDB, this could explain the lowest ratio of unique fused rings.The number and the frequency of the top 10 most retrieved bicycles are illustrated in In PKIDB is a freely available database containing all kinase inhibitors on the market or in clinical trials gathered using their international nonproprietary name (INN). This database, regularly updated, contains information on the structure of the kinase inhibitors, their physicochemical properties, their protein kinase targets, as well as their therapeutic indications. It also contains links to various external databases. We analyzed this dataset and compared it to active PKIs found in the ChEMBL database. Classical physicochemical descriptors, such as Lipinski’s or Veber’s, showed that a significant number of protein kinase inhibitors, either approved or in clinical trials, do not follow the recommended drug-like thresholds, especially regarding molecular weight and calculated LogP. Moreover, all PKI present in PKIDB violate a maximum of only two Lipinski’rules. Therefore, for this typical class of compounds, we propose new boundaries to better characterize the chemical space of kinase inhibitors. Moreover, all PKIS in PKIDB have a maximum of two chiral centers and five aromatic rings.The projection of the chemical space resulting from a principal component analysis shows that most of the inhibitors shared the same chemical space. However, the PKIs available in ChEMBL fill a larger chemical space in the PCA plot compared to PKIs in PKIDB. The distribution of the physicochemical descriptors for both datasets do not present major differences. This suggests that most active PKIs available in the ChEMBL have drug-like properties.Concerning the molecular shape of the PKIs, the PMI plot reveals that PKIs from ChEMBL exhibit a larger shape diversity compared to the ones in PKIDB. However, the majority of PKIs remain clustered around the rod-disc axis because they target a common ATP binding site in the kinase domain, which is highly conserved in this protein family. Yet, PKIs under development tend to explore wider topology, particularly near the disc edge. More frequent macrocyclic structures could contribute to this specific molecular shape. Moreover, moving to new chemical space will help medicinal chemists to escape from a crowded intellectual property (IP) space. Regarding PKIs in ChEMBL, we also found some compounds escaping from this rod-disc axis and get closer to the spherical form. This information could be used to design new chemically-diverse kinase inhibitors.Concerning the molecular scaffold analysis of the two datasets, it appears that PKIs in PKIDB exhibit a great molecular scaffold diversity compared to the ones in ChEMBL. More than 100 scaffolds from PKIDB are not present in the ChEMBL. Each molecule present in PKIDB and, more particularly, the corresponding scaffold, was patented, preventing the design of analogues. Thus, each molecule present in PKIDB is in fact a representative of a chemical series, but only one new molecular entity (NME) was selected to continue its development in clinical phases. Most pharmaceutical companies will not unveil all chemical analogues of the selected NMEs, limiting information on the chemical series. On the opposite, in a public database such as ChEMBL, there are often lots of available analogues for a specific scaffold. The ring analysis performed on the two datasets indicates a similar number of bicycle singletons despite the large size difference in the two datasets, 218 vs. 76,504 molecules for PKIDB and PKI_ChEMBL, respectively. By considering the position and the type of the substituents, a significant part of the scaffolds in PKIDB are absent in ChEMBL, because most of the structures of pharmaceutical companies are protected by patents.http://www.icoa.fr/pkidb. We hope that this resource will assist researchers in their quest for novel kinase inhibitors.The PKIDB database is regularly updated and is accessible from this website: For the creation and maintenance of PKIDB please refer to our previous study . All exp50, Ki or Kd, on a protein kinase with a pchembl value > 6 (< 1000 nM). We then removed duplicates, empty SMILES and molecules from PKIDB. It is composed of 76,504 molecules. Both datasets (PKIDB and PKI_ChEMBL) have been prepared and standardized with VSPrep [The PKI_ChEMBL dataset results from ChEMBL . To be included in this dataset, a compound must have at least one recorded activity, either ICh VSPrep , and for


Bladder cancer is the 11th most common cancer in the world. Bladder cancer can be roughly divided into muscle invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer (NMIBC). The aim of the present study was to identify the key genes and pathways associated with the progression of NMIBC to MIBC and to further analyze its molecular mechanism and prognostic significance. We analyzed microarray data of NMIBC and MIBC gene expression datasets (GSE31684) listed in the Gene Expression Omnibus (GEO) database. After the dataset was analyzed using R software, differentially expressed genes (DEGs) of NMIBC and MIBC were identified. These DEGs were analyzed using Gene Ontology (GO) enrichment, KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein–protein interaction (PPI) analysis. The effect of these hub genes on the survival of bladder cancer patients was analyzed in The Cancer Genome Atlas (TCGA) database. A total of 389 DEGs were obtained, of which 270 were up-regulated and 119 down-regulated. GO and KEGG pathway enrichment analysis revealed that DEGs were mainly involved in the pathway of protein digestion and absorption, extracellular matrix (ECM) receiver interaction, phantom, toll-like receptor (TLR) signaling pathway, focal adhesion, NF-κB signaling pathway, PI3K/Akt signaling pathway, and other signaling pathways. Top five hub genes COL1A2, COL3A1, COL5A1, POSTN, and COL12A1 may be involved in the development of MIBC. These results may provide us with a further understanding of the occurrence and development of MIBC, as well as new targets for the diagnosis and treatment of MIBC in the future. Bladder cancer is the 11th most common cancer in the world, causing 3.2 deaths per 100000 males and 0.9 deaths per 100000 females every year , immune In recent years, gene expression chip technology, which has been widely used in oncology research, has been used to explore the gene expression profile of tumor cells more completely, and this biological information is of great significance for the diagnosis, treatment, and prognosis of the tumor . With thIn the present paper, a microarray dataset of gene expression profiles (GSE31684) was accessed. After the dataset was analyzed using R software, differentially expressed genes (DEGs) of NMIBC and MIBC were identified. These DEGs were analyzed using Gene Ontology (GO) enrichment, KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein–protein interaction (PPI) analysis. The effect of these hub genes on the survival of bladder cancer patients was analyzed in The Cancer Genome Atlas (TCGA) database. Based on the above analysis, we have obtained the DEGs related to the occurrence and development of bladder cancer muscle invasion. In the present paper, we discuss the cell biological functions, biological signal pathways, and the interaction networks of the encoded proteins involved in these DEGs, so as to provide new ideas and possible diagnostic and treatment targets of bioinformatics-related changes involved in the occurrence and development of bladder cancer.https://www.ncbi.nlm.nih.gov/geo/). GSE31684 has a total of 15 NMIBC samples and 78 MIBC samples  [NMIBC and MIBC gene expression datasets GSE31684 were downloaded from Gene Expression Omnibus  . The clihttps://www.r-project.org/). The ID corresponding to the probe name was converted into the gene symbol and saved in the txt file. The limma package for bioconductor (http://www.bioconductor.org/) was used to analyze the progressive gene differential expression between NMIBC and MIBC. The conditions were set as P<0.05, log fold change (FC) > 1. TXT text results were retained for subsequent analysis.The downloaded dataset was analyzed and searched for DEGs using R software 3.4.0 (https://david.ncifcrf.gov/) released in 2003 contains a complete high levels of evidence biological database and a comprehensive analysis tools for systematic and integrative annotation and enrichment analysis that can be used to reveal biological meaning related to large gene lists. We used DAVID to analyze the function and pathway enrichment of the obtained DEGs. GO enrichment analysis was carried out on the webpage using DAVID’s online tools, including biological process (BP), molecular function (MF), and cell component (CC). In addition, GO full analysis was carried out using Cytoscape’s bioapplication program. KEGG path analysis was also carried out on the web using DAVID’s online tools. All the above results were displayed with P<0.05.The online gene annotation, visualization, and integrated discovery bioinformation resource database  for PPI network analysis, each point represents a gene, protein, or molecule, and the connection between points represents the interaction between the two molecules. The results in this database are obtained from experimental data, databases, text mining, and predictive bioinformatics data. This type of analysis can show the molecular action and pathway relationship of the DEGs involved in progression from NMIBC to MIBC. However, the gene represented by the central point may be the key protein or candidate gene with important physiological regulatory function. The results of PPI network analysis of hub genes were analyzed using the cytoHubba application of Cytoscape and sorted according to the scores.Using the STRING database  was used to verify the expression of the top five hub genes, and Kaplan–Meier curves were used to compare the impact of these expressed genes on overall survival.TCGA database  method. After difference analysis of the GSE31684 dataset using the limma package, a total of 389 DEGs were obtained; the difference expression volcano map of two different tissue samples in the dataset is shown in P-value <0.05. In GO enrichment analysis, DEGs were divided into three parts: BP, MF, and CC. The statistical results of GO enrichment analysis are shown in Using the online analytical tool of DAVID to annotate the DEGs obtained from microarray data integration analysis, the GO function of the DEGs was enriched with a Using the DAVID online analysis tool to analyze the KEGG signal pathway enrichment of the DEGs obtained from microarray data integration analysis, we found that the main enrichment of DEGs was in protein digestion and absorption, ECM receiver interaction, phantom, toll-like receptor (TLR) signaling pathway, focal adhesion, NF-κB signaling pathway, PI3K/Akt signaling pathway, and other signaling pathways. The results are shown in http://string-db.org), and the PPI network formed by them is shown in The proteins expressed by the DEGs, 389 in total, were analyzed in the PPI network using the STRING database (P<0.05)  were significantly associated with OS (P<0.05) .Bladder cancer, as a common malignant tumor, can be divided into MIBC and NMIBC depending on whether it invades the muscle layer or not. Treatment of most NMIBC patients can achieve a good therapeutic effect . Once itGene chip technology and high-throughput sequencing technology have been widely used in the research of various diseases. These technologies can let us directly describe the expression of thousands of genes. At present, many related articles and data have been published and uploaded to public databases for further research by other scientists.In the present paper, GSE31684 gene expression profile datasets of bladder cancer were available in the GEO database, and these datasets were analyzed using R software. A total of 389 DEGs were found, including 270 up-regulated and 119 down-regulated genes. After GO enrichment analysis of these genes, it was found that these DEGs were mainly enriched in ECM formation, collagen synthesis and metabolism, cell adhesion, and inflammatory response.The function of epithelial cells, including cell differentiation, migration and invasion, is regulated by interaction with ECM , meanwhiKEGG signal pathway enrichment analysis showed that the DEGs were mainly enriched in protein digestion and absorption, ECM receiver interaction, phagosome, TLR signaling pathway, focal adhesion, NF-κB signaling pathway, PI3K/Akt signaling pathway, and other signaling pathways.The PI3K/Akt signaling pathway is an important signaling pathway in the development of many tumors and in inflammation. It has been proved that the PI3K/Akt signaling pathway plays an important role in promoting the proliferation of tumor cells and can regulate cell metabolism, tumor development, migration, and cytoskeleton remodeling, leading to the occurrence, development, and metastasis of tumor cells ,17. The The NF-κB signaling pathway plays an important role in promoting tumor cell proliferation, vascular production, invasion, and metastasis in the development of bladder cancer, especially bladder urothelial cancer . TLRs anNext, we used DEGs to build the PPI network  and idenIn addition, collagen can promote tumor progression through immune regulation; for example, signaling factors related to neutrophils are significantly increased in the high-density collagen-type breast cancer microenvironment . COL1 caCollagen also has an important relationship with angiogenesis. The inhibition of collagen metabolism has an anti-angiogenic effect. Angiogenesis and survival are closely related to the appropriate collagen synthesized and deposition in the basement membrane , especiaBy analyzing the bladder cancer dataset GSE31684 in the GEO database using R software and other tools, a total of 389 DEGs were identified, including 270 up-regulated and 119 down-regulated genes. Through GO function enrichment analysis and KEGG pathway analysis, we found that these genes were enriched in ECM formation, collagen synthesis and metabolism, cell adhesion, inflammation, and other functions, as well as protein digestion and absorption, ECM receiver interaction, phagosome, TLR signaling pathway, focal adhesion, NF-κB signaling pathway, and PI3K/Akt signaling pathway. The PPI network of DEGs was constructed, and the most important ten genes were screened using cytoHubba. Survival analysis of the top five hub genes was carried out using TCGA database data. Our research found that the key genes, including COL1A2, COL3A1, COL5A1, POSTN, and COL12A1, played an important role in the development of MIBC. These results may provide us with a further understanding of the occurrence and development of MIBC, as well as new targets for the diagnosis and treatment of MIBC in the future. However, there were some limitations in the present study that should be declared. The data from GSE31684 have a total of 15 NMIBC samples and 78 MIBC samples, the difference in sample size between the two groups may lead to statistical limitation. Besides, the hub genes on gene expression were only validated in TCGA database and these genes needs to be further validated with more experiment. Future studies will aim to use polymerase chain reaction or Western blotting to verify expression levels of the key genes in samples between MIBC and NMIBC.Click here for additional data file.


GBA.The type 1 interferon (IFN) response is part of the innate immune response and best known for its role in viral and bacterial infection. However, this pathway is also induced in sterile inflammation such as that which occurs in a number of neurodegenerative diseases, including neuronopathic Gaucher disease (nGD), a lysosomal storage disorder (LSD) caused by mutations in Mice were injected with conduritol B-epoxide, an irreversible inhibitor of acid beta-glucosidase, the enzyme defective in nGD. MyTrMaSt null mice, where four adaptors of pathogen recognition receptors (PRRs) are deficient, were used to determine the role of the IFN pathway in nGD pathology. Activation of inflammatory and other pathways was analyzed by a variety of methods including RNAseq.Elevation in the expression of PRRs associated with the IFN response was observed in CBE-injected mice. Ablation of upstream pathways leading to IFN production had no therapeutic benefit on the lifespan of nGD mice but attenuated neuroinflammation. Primary and secondary pathological pathways  were distinguished, and a set of ~210 genes including those related to sphingolipid, cholesterol, and lipoprotein metabolism, along with a number of inflammatory pathways related to chemokines, TNF, TGF, complement, IL6, and damage-associated microglia were classified as primary pathological pathways, along with some lysosomal and neuronal genes.Although IFN signaling is the top elevated pathway in nGD, we demonstrate that this pathway is not related to mouse viability and is consequently defined as a secondary pathology pathway. By elimination, we defined a number of critical pathways that are directly related to brain pathology in nGD, which in addition to its usefulness in understanding pathophysiological mechanisms, may also pave the way for the development of novel therapeutic paradigms by targeting such pathways. GBA, which encodes the lysosomal hydrolase, acid beta-glucosidase (GCase). GD is divided into neuronopathic (types 2 and 3) (nGD) and non-neuronopathic forms (type 1), depending on the involvement of symptoms associated with the central nervous system  on braip adjusted < 0.05) in WT + CBE versus WT + PBS (599 upregulated and 168 downregulated), and 467 genes were DE in MyTrMaSt + CBE versus MyTrMaSt + PBS   and 5 (138 genes) display similar decreased expression in the two CBE-treated groups. The genes in clusters 3 and 4 (143 and 345 genes) displayed reduced expression in MyTrMaSt + CBE compared with the WT + CBE group. Comparison of the DEGs in the WT + CBE group versus WT + PBS with our previous high-throughput studies [A total of 13,866 genes were detected by RNAseq. Principle component analysis (PCA) revealed that PBS-injected mice clearly separate from CBE-injected mice, with the exception of one outlier WT mouse , whereas there are 301 DEGs common to the two groups (mainly in clusters 3 and 4). A total of 166 genes   in MyTrMaSt mice compared with WT mice injected with CBE Table . Althougdroplets , was oneGfap), supporting the notion that abrogating the IFN response does not attenuate key pathways in neuroinflammation related to nGD symptoms. This is supported by the elevated level of some  is involved in neurodegeneration [In addition, and in line with data shown in Fig. neration , 31.Further to our recent study suggesting that the IFN pathway does not play a critical role in nGD pathology , we haveEven though we are able to exclude a role for the IFN pathway in primary pathology, components of this pathway are nevertheless the top elevated pathway in the nGD brain and are also elevated in a number of other LSDs, including mucolipidosis type IV and Krabbe disease , 33, aloBy a process of elimination, we were able to cut down the number of genes associated with primary pathological pathways to ~210, by considering only genes whose expression changed consistently in both WT and MyTrMaSt mice injected with CBE, each compared with its respective PBS-injected control Table . In addinot DE in the current study using MyTrMaSt null mice, along with those that were DE in the SRT study, are likely to be those that are critically involved in pathophysiology. By way of example, three DEGs in the SL metabolic pathway remained elevated in MyTrMaSt null mice but were reduced by SRT , which remained elevated in MyTrMaSt null mice but were reduced to some extent after SRT. Importantly, Trem2 overexpression attenuates neuroinflammation in Parkinson’s disease [Apoe which was reduced to some extent in response to SRT, Table In contrast, functional significance can be advocated for genes associated with a novel microglia type, namely disease-associated microglia (DAM), which have been ascribed roles in Alzheimer’s disease  and in s disease . PhosphoAnother critical gene family appears to be the complement system. The complement system is considered the first line of defense against pathogens, mediates the clearance of immune complexes and regulates inflammatory responses. Our data supports the notion that complement activation in nGD is through activation of the classical pathway . The comFinally, three metalloproteases are involved with primary pathology, which may be related to neuronal function. Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMP) have been implicated in the pathology of Parkinson’s and Alzheimer’s diseases, where MMP can cleave amyloid beta . SimilarMT1/2 were also implicated in Parkinson’s disease where their elevation was proposed to have a protective role against neurotoxicity . MT1/2 wWe have differentiated between two types of pathways that are activated in nGD, namely those directly related to disease pathology and those that appear only to be secondarily related Fig. . While tAdditional file 1. Primers used for RT-PCR


Other fibers from the His bundle and fascicle to the right ventricle (RV) (fasiculoventricular fibers) and from the AV node to the right bundle (nodofascicular fibers) were subsequently defined later.2Historically, it was suggested by Ivan Mahaim in 19383 or with cryo energy4 revealed, however, total AV block with preserved preexcitation due to conduction over an accessory pathway (AP) connecting the right atrium with the RV. These decremental anterograde-conducting connections, not localized in the AV node or the distal part of the conduction system, were mentioned as being Mahaim-like APs. However, more in detail, the definition of these fibers is as follows: decrementally conducting accessory AV pathways connecting the right atrium with a part of the right bundle branch (RBB), or atriofascicular (AF) pathways.Creating AV block with direct-current energyThese decrementally conducting APs (which can be either short or long in length) may have their atrial origins all along the border of the “saddle”-shaped tricuspid valve (TV). Catheter mapping of the TV is very challenging because of its oval shape, which changes further during RV contraction. Notably, the TV is not located in a single horizontal plane like the mitral valve; rather, the anteroseptal part of the TV is superior and the posteroseptal part is inferior, respectively, in relation to the major part of the oval body of the TV.In light of this information, one question to consider is: how can one localize the decremental AP in Mahaim-related tachycardias?My first approach strategy is to try to localize the atrial origin of the pathway. In fast-conducting pathways (Kent bundles)—which are, in general, short in length—the shortest A–V time provides key information about the atrial and the ventricular insertions of the AP. Sometimes, the anatomy can be complicated, like in the posteroseptal region of the heart, since the AP may cross from the right atrium to the summit of the left ventricle and from the left atrium to the summit of the RV. In general, the atrial and ventricular connections of the AP are quite close to one another in the vertical plane. In contrast, the AF pathways may be short, though they can also be very long, extending deep into the RV and connecting to the right bundle or its branches.5), the M potential cannot be localized.The most helpful criterion to localize the atrial insertion of the AF pathway is the presence of the Mahaim potential . The best circumstance to delineate the M potential is during atrial pacing or antidromic tachycardia (AT). However, the M potential is not always easy to locate along the TV border due to its complex anatomy (see above) and dynamic behavior present during RV contraction. One should realize that the M potential can be very sensitive for catheter manipulation and can be (for a prolonged time!) blocked by mechanical force. Sometimes  does not indicate the ventricular insertion of the AP and, as such, is not helpful in determining the optimal ventricular site for catheter ablation.Figure 4,6 the distal radiofrequency signal in the preexcited complexes demonstrates a sharp deflection from the distal conduction system followed by immediate ventricular activation. In contrast, in the nonpreexcited complex, the QRS complex seems to be somewhat later relative to the spike of the conduction system, indicating a slight change in activation locally in the absence/connection of the AF fiber. Depending on the site of radiofrequency application, RBB conduction may change or even lead to RBB block.To localize the ventricular insertion of the AF pathway, the RV must be mapped extensively, which can be very time-consuming to do. The earliest ventricular activation preceding the V signal on the 12-lead electrocardiogram should be the target to look for. This earliest ventricular signal should preferably be preceded by a sharp deflection . In Lokhandwala et al.’s The last wide QRS complex is not preceded by a signal from the conduction system (no spike visible) and is most likely due to a ventricular premature beat.MD (jsmeets58@gmail.com)1Joep L. R. M. Smeets, 1Radboud University Medical Center, Radboud University, Nijmegen, the NetherlandsThe author reports no conflicts of interest for the published content.1.Benatt MahaimINouvelles recherches sur les connexions superiors de la branche gauche du faisceau de His-Tawara avec cloison interventriculaire.Cardiologia.19381611202.AndersonRHBeckerAEBrechenmacherCDaviesMJRossiLVentricular preexcitation. A proposed nomenclature for its substrates.Eur J Cardiol.1975312736[PubMed]11324073.BhandariAMoradyFShenENCatheter induced His Bundle ablation in a patient with reentrant tachycardia associated with a nodoventricular tract.J Am Coll Cardiol.198443611616[CrossRef][PubMed]64703434.KleinGJGuiraudonGMKerrCR“Nodoventricular” accessory pathway: evidence for a distinct accessory pathway with atrioventricular node-like properties.J Am Coll Cardiol.198811510351040[CrossRef][PubMed]31285865.KothariSGuptaAKLokhandwalaYYVoraAKerkarPGThakurRKAtriofascicular pathways: where to ablate?Pacing Clin Electrophysiol.2006291112261233[CrossRef][PubMed]171006756.LokhandwalaYVyasAA wide complex tachycardia in a structurally normal heart: what is the mechanism? Where to ablate?J Innov Cardiac Rhythm Manage.20191013504350710.19102/icrm.2018.0912027.SternickEBLokhandwalaYBohoraSIs the 12-lead electrocardiogram during antidromic circus movement tachycardia helpful in predicting the ablation site in atriofascicular pathways?Europace.2014161116101618[CrossRef][PubMed]246817621 nicely demonstrates some classic electrophysiology findings of an anterograde slowly conducting AF (“Mahaim”) AP with successful catheter ablation.3 This case study notably highlights the importance of alternative target sites for ablation when the AP potential cannot be identified along the tricuspid annulus.The case by Lokhandwala and VyasFigure 1B shows the termination of tachycardia in response to an atrial premature stimulus. Although the atrial signals on the coronary sinus catheter remain on-time, septal atrial activation (His bundle and right bundle electrograms) is clearly advanced. This does not rule out AV nodal reentrant tachycardia (AVNRT) with a bystander Mahaim conduction. However, a late right-free-wall atrial premature delivery that occurred after the septal A was committed resulted in a resetting of the tachycardia (both V and A) . This conclusively excludes the possibility of AVNRT, since such late ventricular depolarization cannot advance the subsequent atrial activation in AVNRT, thereby confirming AV reentrant tachycardia using the AF pathway as the antegrade limb of the reentrant circuit.Lokhandwala et al.’s 5 The atrial insertions of Mahaim pathways are often located at the right anterolateral to posterolateral TV, and catheter ablation is highly effective when targeting AP potential.4 However, AP potentials along the TV annulus may not be identified in a significant minority of patients.6 In the present report, the Mahaim potential could not recorded when mapping the lateral TV annulus, and targeting the earliest local ventricular activation successfully eliminated preexcitation .The anatomical variants of so-called “Mahaim” pathways include AF and AV insertions that can have either short or long connections..7 Ablation of the Mahaim pathway targeting the distal insertion was first reported during atrial fibrillation.8 However, the distal insertion of the Mahaim fiber may be highly arborized over a wide area with diffuse activation, and unsuccessful ablation is often associated with a change in the preexcitation pattern.5 It is, therefore, important not only to map the earliest local ventricular activation but also to identify the precise fascicular/ventricular insertion sites by way of the high-frequency presystolic AP potential recordings . Despite this, mapping and ablation of the Mahaim fibers guided by careful mapping of AP potentials along the TV annulus is still preferable, as the annular target site is more discrete and localized in this instance.AP potential can also be identified along the course of the Mahaim fiber between the TV annulus and the RV insertion sites, either on the free wall or near the septal right bundle MD, FHRS (henry.hsia@ucsf.edu)1 and Jose M. Sanchez, MD1Henry H. Hsia, 1University of California, San Francisco, San Francisco, CA, USAThe authors report no conflicts of interest for the published content.1.LokhandwalaYVyasAA wide complex tachycardia in a structurally normal heart: what is the mechanism? Where to ablate?J Innov Cardiac Rhythm Manage.20191013504350710.19102/icrm.2018.0912022.LüderitzBIvan Mahaim (1897–1965).J Interv Card Electrophysiol.200382155[CrossRef][PubMed]127665083.KatritsisDGWellensHJJosephsonMEMahaim accessory pathways.Arrhythm Electrophysiol Rev.2017612932[CrossRef][PubMed]285077444.McClellandJHWangXBeckmanKJRadiofrequency catheter ablation of right atriofascicular (Mahaim) accessory pathways guided by accessory pathway activation potentials.Circulation.199489626552666[PubMed]82056785.HaïssaguerreMCauchemezBMarcusFCharacteristics of the ventricular insertion sites of accessory pathways with anterograde decremental conduction properties.Circulation.199591410771085[PubMed]78509446.KothariSGuptaAKLokhandwalaYYVoraAMKerkarPGThakurRKAtriofascicular pathways: Where to ablate?Pacing Clin Electrophysiol.2006291112261233[CrossRef][PubMed]171006757.GuptaAHsiaHHLoRZeiPCElectroanatomic localization of a slowly conductiong atrioventricular (Mahaim) accessory pathway.J Interv Card Electrophysiol.2011312119124[CrossRef][PubMed]199430998.MillerJMHarperGRRothmanSAHsiaHHRadiofrequency catheter ablation of am atriofascicular pathway during atrial fibrillation: a case report.J Cardiovasc Electrophysiol.1994510846853[CrossRef][PubMed]78743301 presents an interesting dilemma. A Mahaim potential was not targeted for ablation since it was not observed in the tricuspid annular (TA) region. How, then, should one approach ablating an AF pathway when the optimal choice is not available? The approach under such circumstances is dictated by the anatomic course of the pathway. An AF pathway originates in the atrial tissue bordering the anterolateral to posterolateral tricuspid annulus, traverses the TA region, and inserts into the distal RBB in the region of the apical third RV free wall along the course of the moderator band or its insertion into the anterior papillary muscle. Therefore, it may be useful to consider approaching the pathway from any of three anatomic sites, as follows.The case by Lokhandwala and VyasOne option is to atrially pace circumferentially adjacent to the TA annulus, concentrating on the anterior/lateral regions and determining the site that produces maximal preexcitation and the shortest AV interval. This presumably would be the site of the atrial insertion and would be an appropriate ablation target. It has also been suggested that ablating from the ventricular aspect of the tricuspid annulus, directly opposite the optimal atrial pacing site, can be an effective approach, even though it doesn’t correspond to the earliest site of ventricular activation. A more cumbersome option would be mapping and ablating from the site that marks the longest atrial extrastimulus coupling interval that resets preexcited antidromic reciprocating tachycardia during septal atrial refractoriness.AF pathways are particularly susceptible to temporary catheter bump suppression. These pathways may take several hours to resume conduction. If the site of mechanical abolition of AF conduction is annotated on an electroanatomical mapping system, empiric ablation could be performed at this site, albeit with a relatively low probability of long-term success. Although neither optimal nor elegant, if preexcitation is absent for any reason, a series of ablation applications could be made along the most likely TA course of the pathway .1 was an appropriate and practical option, since the Mahaim potential was not identified. They mapped the site of earliest ventricular activation relative to QRS onset during atrial pacing, which is presumably near the distal insertion site of the pathway. A variation of this approach would be to map the RV free wall, identifying early Purkinje potentials (in the region of the moderator band–anterior papillary muscle interface), which correspond to the insertion site of the AF pathway into the distal RBB. These potentials likely originate from the distal RBB and precede earliest ventricular activation. Intracardiac echocardiography (ICE) may help to facilitate positioning of the ablation catheter in the region of the moderator band and anterior papillary muscle. Alternative approaches include ventricular pace-mapping and identification of the site with the best QRS match as well as entraining during antidromic reciprocating tachycardia from this site and confirming that the postpacing interval is equivalent to the tachycardia cycle length. There are several caveats to be mindful of when ablating at the distal insertion site. First, the distal end of the pathway may arborize, so the placement of a discrete lesion at a single site may not be successful. Furthermore, damaging but not completely eliminating the distal insertion site may result in damage to the RBB, giving rise to a subsequent slower and incessant tachycardia, due to retrograde conduction over the left bundle. To maximize catheter stability, ablation should be performed during atrial pacing.The approach taken by Lokhandwala and Vyas in their case studyMD (blerman@med.cornell.edu)1 and Steven M. Markowitz, MD1Bruce B. Lerman, 1Department of Medicine, Division of Cardiology, Cornell University Medical Center, New York, NY, USAThe authors report no conflicts of interest for the published content.1.LokhandwalaYVyasAA wide complex tachycardia in a structurally normal heart: what is the mechanism? Where to ablate?J Innov Cardiac Rhythm Manage.20191013504350710.19102/icrm.2018.0912021 have presented a nicely documented case of Mahaim antidromic tachycardia with successful ablation, despite not being able to record a discrete Mahaim potential on the tricuspid annulus. I’d like to start by pointing out that working with Mahaim pathways is fun! When I was a fellow training at the University of California, San Francisco, we could always get Mel Scheinman excited by simply asking “could this be a Mahaim?” with regard to any wide QRS tachycardia, and this would lead to a wonderful five- or 10-minute teaching session on the evaluation of wide complex tachycardias and maneuvers to prove Mahaim pathways.Drs. Lokhandwala and Vyas2 If one observes a sudden loss of preexcitation with this maneuver, then you’ve found it (“bump mapping”). If you don’t bump it, then I would expect that the delivery of radiofrequency energy at the candidate site would cause Mahaim automaticity, essentially an irregular wide complex accelerated rhythm with the same morphology as that of a fully preexcited QRS, and then a sudden loss of preexcitation. I have found Mahaim automaticity to be one of the most helpful observations when performing ablations in this substrate.The case presented demonstrates nearly all of the classic criteria for Mahaim AF pathways. Just to add, the maneuver of introducing premature atrial beats (PACs) into antidromic tachycardia, at a time at which the low septal atrial electrogram is committed, proves that the pathway is AF rather than nodofascicular, which is a useful piece of information if a Mahaim potential is not found on the tricuspid annulus. Termination by the PACs without advancing the ventricle excludes ventricular tachycardia, which is also a useful maneuver. Notably, in their report, the authors wonder whether or not there are other maneuvers for mapping a Mahaim pathway. One of the oldest techniques is to pace on the atrial side of the tricuspid annulus at various sites around the ring and measure stimulus-to-V times; the shortest should get you close.MD1George F. Van Hare, 1Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USAThe author reports no conflicts of interest for the published content.1.LokhandwalaYVyasAA wide complex tachycardia in a structurally normal heart: what is the mechanism? Where to ablate?J Innov Cardiac Rhythm Manage.20191013504350710.19102/icrm.2018.0912022.KleinLSHackettFKZipesDPMilesWMRadiofrequency catheter ablation of Mahaim fibers at the tricuspid annulus.Circulation.1993873738747[PubMed]8443894Mapping and ablation of an AF pathway participating in an antidromic tachycardia is typically focused on a putative pathway potential along the tricuspid annulus or on the RV free wall at the insertion into the RBB.Several factors can make the mapping and ablation of these pathways challenging, as follows: (1) the location along the lateral tricuspid annulus and RV free wall, (2) the concern of “bumping the pathway” and losing the pathway potential, (3) the concern of perforation with placement of the ablation catheter along the RV free wall, (4) suboptimal catheter contact and stability, (5) the concern of causing a RBBB or an incessant tachycardia with ablation at the distal insertion of the pathway into the RV, and (6) the potential for varying lengths of the AF pathway.1 the authors describe a case of an AF pathway where they could not identify a pathway potential along the tricuspid annulus and thus performed mapping for the earliest ventricular electrogram, which was mapped to the apical RV. The authors were able to successfully ablate the pathway at this location consistent with the presence of a long AF pathway with insertion into the apical ventricle.In Lokhandwala and Vyas’s report of distal ablation for an AF pathway,For suspected AF pathways, I typically utilize a duodecapolar catheter with placement of the catheter arranged to record activation along the lateral tricuspid annulus, the cavotricuspid isthmus, and the proximal coronary sinus. This ensures coverage along the inferior, inferolateral, lateral, and superior tricuspid annulus in order to bracket the earliest ventricular activation and pathway potential along the tricuspid annulus. To maximize catheter stability, I typically use an Agilis™ medium or long curl sheath  with a contact force catheter and ICE guidance. This provides me with greater confidence with regard to catheter stability at the location of interest as well as the ability to monitor for the potential of a perforation/pericardial effusion with the ablation catheter along the lateral tricuspid annulus and the RV free wall. By using contact force, one can also try to minimize mechanical trauma to a pathway location that may result in loss of antegrade preexcitation via the pathway. Finally, with mapping the RV fascicular system, which has branches along the moderator band, ICE is very useful for ensuring catheter stability during mapping and ablation.2 the correct AF pathway location cannot be identified reliably using the 12-lead electrocardiogram. As a result, my practice has been to focus on the mapping of an AF pathway potential along the tricuspid annulus. If a pathway potential cannot be identified along the tricuspid annulus, I then focus on mapping the earliest ventricular activation along the RV free wall. Since these pathways typically insert into the apical third of the RV, I start with mapping along the moderator band of the RV, where I can identify a right bundle potential and proceed with mapping towards the RV free wall to identify the earliest AF pathway potential into the right-sided conduction system. This helps to avoid prolonged catheter manipulation along the RV free wall and enables one to focus mapping and ablation efforts on the potential insertion site of the pathway.As Sternick et al. showed,MD, FACC, FHRS (fredhan@ucsd.edu)1Frederick T. Han, 1Section of Cardiac Electrophysiology, Division of Cardiovascular Medicine, University of California, San Diego, La Jolla, CA, USAThe author reports no conflicts of interest for the published content.1.LokhandwalaYVyasAA wide complex tachycardia in a structurally normal heart: what is the mechanism? Where to ablate?J Innov Cardiac Rhythm Manage.20191013504350710.19102/icrm.2018.0912022.SternickEBLokhandwalaYBohoraSIs the 12-lead electrocardiogram during antidromic circus movement tachycardia helpful in predicting the ablation site in atriofascicular pathways?Europace.2014161116101618[CrossRef][PubMed]24681762