One of the main mechanisms of epigenetic regulation in higher eukaryotes is based on the methylation of cytosine at the C5 position with the formation of 5-methylcytosine (mC), which is further recognized by regulatory proteins. In mammals, methylation mainly occurs in CG dinucleotides, while in plants it targets CG, CHG, and CHH sequences (H is any base but G). Correct maintenance of the DNA methylation status is based on the balance of methylation, passive demethylation, and active demethylation. While in mammals active demethylation is based on targeted regulated damage to mC in DNA followed by the action of repair enzymes, demethylation in plants is performed by specialized DNA glycosylases that hydrolyze the N-glycosidic bond of mC nucleotides. The genome of the model plant Arabidopsis thaliana encodes four paralogous proteins, two of which, DEMETER (DME) and REPRESSOR OF SILENCING 1 (ROS1), possess 5-methylcytosine-DNA glycosylase activity and are necessary for the regulationof development, response to infections and abiotic stress and silencing of transgenes and mobile elements. Homologuesof DME and ROS1 are present in all plant groups; however, outside A. thaliana, they are poorly studied.Here we report the properties of a recombinant fragment of the ROS1 protein from Nicotiana tabacum (NtROS1),which contains all main structural domains required for catalytic activity. Using homologous modeling, we haveconstructed a structural model of NtROS1, which revealed folding characteristic of DNA glycosylases of the helix–hairpin–helix structural superfamily. The recombinant NtROS1 protein was able to remove mC bases from DNA,and the enzyme activity was barely affected by the methylation status of CG dinucleotides in the opposite strand.The enzyme removed 5-hydroxymethylcytosine (hmC) from DNA with a lower eff iciency, showing minimal activityin the presence of mC in the opposite strand. Expression of the NtROS1 gene in cultured human cells resulted ina global decrease in the level of genomic DNA methylation. In general, it can be said that the NtROS1 protein andother homologues of DME and ROS1 represent a promising scaffold for engineering enzymes to analyze the statusof epigenetic methylation and to control gene activity. DNA methylation is a dedicated mechanism of gene regulation,especially developed in higher eukaryotes. The 5-methylcytosine(mC) nucleobase, formed by cytosine methylationat the C5 position, serves as a reversible epigenetic mark thatplays an important role in the control of gene expression andthe protection of the genome from mobile elements. DNAmethylation occurs in a wide range of multicellular eukaryotes;however, its significance and functions in these organismsdiffer greatly .For example, in mammals, methylation most often occurs inCpG dinucleotides, while in plants, a significant proportionof mC occurs in trinucleotides CHG and CHH (where H is“not G”). The consequences of mC for gene activity are mainlymediated by proteins containing methyl-binding domains thatform complexes with histone deacetylases or themselves havethe activity of histone-specific methyltransferases, chromatinremodeling factors, etc., which leads to chromatin condensationand transcription suppression . Recent studies have shown that an oxidizedderivative of 5-methylcytosine, 5-hydroxymethylcytosine(hmC), also plays an epigenetic role in the mammaliangenome . Unlike mC, hmC is enrichedin promoters and bodies of actively expressed genes and isconsidered an activating epigenetic marker Correct methylation of various sites in the genome is extremelyimportant, since the transcriptional activity of genesdepends on it. Errors in DNA methylation can have graveconsequences. In particular, in humans, global DNA demethylationor hypermethylation of tumor suppressor genes serve ascancer markers. Maintaining the status of DNA methylation incells requires a balance of methylation and active and passivedemethylation. The mechanisms of active demethylation ofthe genomic DNA in higher eukaryotes have only been discoveredin the last decade. In mammals, active demethylationis initiated by regulated damage to mC, which can occur intwo ways: either deamination of mC to T by AID/APOBECenzymes, or oxidation of mC to hmC and further derivatives(5-formylcytosine and 5-carboxycytosine) by TET familydioxygenases . The modified bases are further perceived bycellular repair systems as damaged and are removed by theDNA base excision repair pathway.Unlike mammals, plants have unique enzymes that directlyhydrolyze N-glycosidic bonds of mC nucleotides. These DNAglycosylases – DEMETER (DME) and REPRESSOR OFSILENCING 1   – are involved in theregulation of the methylation status of the sites in the plantgenome that determine gene imprinting during paternal ormaternal inheritance and silence or activate specific promotersduring plant development and stress response .After removal of mC, the resulting apurinic-apyrimidinic site(AP site) is cleaved either by the enzyme’s own AP lyase activityor by the AP endonucleases APE1L or ARP, then a normalnucleotide is incorporated by one of the DNA polymerases,and the nick is ligated by the LIG1 DNA ligase. Interestingly,DME and ROS1 can also excise hmC, which is not regardedas an epigenetic base in plants . The localizationof demethylation by DME/ROS1 is regulated bysmall RNAs that bind to the enzyme itself or to the proteincomplex that contains it .In addition to DME and ROS1, the genome of the modelplant Arabidopsis thaliana contains three more genes that arehomologous to DME and ROS1: DEMETER-LIKE 2 (DML2),DEMETER-LIKE 3 (DML3), and AT3G47830, which has notbeen characterized thus far except for participation of DML2and DML3 in maintaining correct DNA methylation . All these proteins belongto the DNA helix–hairpin–helix (HhH) structural superfamilyof DNA glycosylases. Other members of this superfamily areinvolved in the removal of oxidized, alkylated and deaminatednucleobases from the genome . DME/ROS1 enzymes attract attention as potentialtools for targeted regulation of gene activity: for example, thepossibility of targeted DNA demethylation in human cells byA. thaliana ROS1 (AtROS1) fused to the RNA-guided Cas9protein has been shown , and A. thaliana DME (AtDME) was used to analyze the level ofmC in genomic DNA .In plants other than A. thaliana, there were few studies onthe role of DME-like proteins in active epigenetic demethylation;some data exist for rice, wheat, barley, and tomato . In 2007, a ROS1 homolog from Nicotiana tabacum(NtROS1) was cloned, and the recombinant proteinproducedin insect cell culture was shown to cleave methylatedtobaccogenomic DNA . None of these studiesincluded a detailed biochemical characterization of the protein.We have previously shown that the NtROS1 fragment correspondingto the minimal catalytically active AtROS1 fragmenthas the activity of 5-methylcytosine-DNA glycosylase.Here, in view of the potential value of plant demethylationenzymes as tools for genetic technologies, we characterizethe substrate specificity of the recombinant NtROS1 catalyticfragment on mC and hmC in different contexts of methylatedCpG dinucleotides and show that the expression of NtROS1in human cells causes a global decrease in DNA methylation.ProtoScript II reverse transcriptase, Q5 Hot Start High-FidelityDNA polymerase, Escherichia coli uracil DNA glycosylase,ClaI and SacI restriction endonucleases were purchasedfrom New England Biolabs (USA), and bacteriophage T4polynucleotide kinase, from Biosan .Oligonucleotides listed in the Table were synthesized at theSB RAS ICBFM Laboratory of Biomedical Chemistry usingcommercially available prosphoramidites . If necessary, the oligonucleotides were 32P-labeled atthe 5′-end using γ[32P]ATP (SB RAS ICBFM Laboratory ofBiotechnology) and T4 polynucleotide kinase.To build a model of the NtROS1 catalytic domain in theSwiss-Model program , the AtDME(AF-Q8LK56-F1-model_v1) and AtROS1 (AF-Q9SJQ6-F1-model_v1) templates from the AlphaFold database  were used.To obtain a catalytically inactive NtROS1 with theAsp1359Asnsubstitution, a pLATE31 plasmid with an insertencoding the catalytically active NtROS1 fragment (aminoacid residues 754–1796)  was mutagenizedusing primers D1359Nfwd and D1359Nrev (seethe Table) and the Q5 Site-Directed Mutagenesis Kit (NewEngland Biolabs). The mutation was confirmed by Sangersequencing. Wild-type NtROS1 and NtROS1 D1359N wereoverproduced and purified as described previously .To study the activity of NtROS1, double-stranded substrateswere obtained by annealing oligonucleotides C1, C2,M1, M2, H1, and H2 (see the Table). The reaction mixturecontained 50 nM substrate, 50 mM Tris–HCl (pH 8.0), 1 mMEDTA, 1 mM DTT, 0.1 % bovine serum albumin, and 100 nMNtROS1. The mixture was incubated at 37 °C; aliquots werewithdrawn at various times (2–300 min) and mixed with anequal volume of the stop solution . Ifnecessary, the aliquots were preheated for 2 min at 95 °C inthe presence of 0.1 M NaOH and neutralized with an equimolaramount of HCl. The reaction products were resolvedby electrophoresis in a 20 % polyacrylamide gel containing7.2 M urea, visualized by prosphorimaging using the TyphoonFLA 9500 system , and quantified usingthe Quantity One v4.6.3 software . The apparent rate constants were determined using theSigmaPlot v11.0 software  by nonlinearregression to the equation [P] = [P]max(1 – e−kt ), where[P] is product concentration, [P]max is the maximum productconcentration, k is the reaction rate constant, and t is time.To assess the status of global DNA methylation uponNtROS1 expression in human cells, wild-type and D1359NNtROS1 coding sequences were cloned into the pIRES-eGFPpuroplasmid  at the SacI and ClaI restriction sites. HEK293 Phoenix cells (1.2·106) were transfected with5 μg of the plasmid by the calcium phosphate method andgrown in a monolayer in DMEM with 10 % fetal calf serum. After 24 and 48 h, the medium was changedwith the addition of 3 μg/ml puromycin. Transfection efficiencywas determined by flow cytometry  by detection of the fluorescence ofeGFP encoded by the same plasmid. NtROS1 expression inthe transfected cells was confirmed by reverse transcriptionPCR using β-actin mRNA as a control. Genomic DNA wasisolated from the cells (5·106) using a QIAamp DNA Mini Kit, and the relative content of mC wasdetermined using anti-mC antibodies . The resultswere compared using Student’s t-test.Plant mC-specific DNA glycosylases are proteins of considerablesize: for example, AtDME and AtROS1, as well astheir DML2 and DML3 paralogs, are over 1000 amino acidresidues long . The extended N-terminal regions ofthese polypeptides are unstructured, although some of theirparts are necessary for enzyme activity. The C-terminal regionscontain a conserved HhH catalytic domain and an iron-sulfurcluster (FeS cluster), characteristic of many DNA glycosylasesthat recognize oxidative DNA damage, as well as an RNAbindingmotif  and a CXXCtype permuted zinc finger unique to the DME/ROS1 family. Unlike in all other HhH superfamily DNAglycosylases, the catalytic domain in DME/ROS1 proteinsis disrupted by a long non-conserved insert . Based on the literature data on the AtROS1protein, we previously cloned the NtROS1 cDNA fragmentencoding amino acid residues 754–1796 .This region contains all elements necessary for the catalyticactivity in AtROS1 .Since the structures of the DME/ROS1 family proteins arecurrently unknown, for a more detailed understanding of theorganization of the NtROS1 catalytic fragment, we carriedout homology modeling based on the AtDME and AtROS1models from the AlphaFold template collection . The two resulting models were almost identicalexcept for the structure of the long non-homologous regions.The disrupted HhH domain folded into the α-helical structurecharacteristic of DNA glycosylases of this superfamily,in which a DNA binding groove with the catalytic residuesLys1341 and Asp1359 is evident . In addition,several more peripheral α-helices buttress the HhH domain andthe FeS cluster and are obviously important for maintainingtheir structure. The FeS cluster, zinc finger, and RRM motifform separate structural elements that leave free access to theDNA binding groove . All disordered regions ofthe structure are also located on the side of the protein globuleopposite to the DNA binding groove.To analyze the catalytic activity and substrate specificity ofNtROS1, we performed a cleavage reaction of double-strandedoligonucleotides containing a CpG dinucleotide in which thecytosine was unmethylated, methylated, or hydroxymethylatedin one or both chains . The strand to be cleaved was32P-labeled at the 5′-end. NtROS1 showed virtually no activityon the substrate containing an unmethylated CpG site, whichis consistent with the literature data claiming that the C5 positionof the cytosine must carry a substitution to be cleaved byAtROS1 . Activity towards mC andhmC was observed; however, its level differed markedly forboth types of substrates. Comparing the efficiency of cleavageof M1/C2 and M1/M2 substrates with H1/C2 and H1/H2 substrates (lanes 11 and 14), one cansee that the enzyme prefers to excise mC over hmC bothfrom CpG sites modified at only one strand and from fullymodified sites. Small differences in the cleavage of M1/C2,M1/M2 and M1/H2 substrates  indicatethat modifications in the complementary strand have littleeffect on the removal of mC, and hmC in the complementarystrand might even increase the cleavage. The enzymeshowed no activity against DNA substrates containing uracil or 8-oxoguanine. The NtROS1 D1359N mutant, as expected,exhibited no glycosylase activity against any substrate withvarious combinations of mC and hmC, which confirms theimportance of the Asp residue in the ROS1 catalytic centerfor the removal of modified bases from DNA.AtROS1 was reported to be an enzyme with a very lowturnover number , so it wasnot feasible to use steady-state kinetics to characterize theactivity of NtROS1. To determine the apparent reaction rateconstant, we used the conditions close to the single-turnoverkinetic regime ([E]0 > [S]0). Under these conditions, all DNAsubstrate rapidly binds to the enzyme, and the reaction rateis limited not by substrate binding or product release, butby the chemical step of the pseudo-first order reaction, thehydrolysisof the N-glycosidic bond of the modified nucleotide. Thus, following the accumulation of theproduct over time , one can estimate the reactionrate constant. The time courses for all substrates are shownin Fig. 3, b, and the rate constants calculated from these dataare summarized below:Substrate k·104, s−1*M1/C2 6.5 ± 1.1*M1/M2 2.4 ± 0.5*M1/H2 3.0 ± 0.7*H1/C2 1.9 ± 0.3*H1/M2 1.6 ± 0.6*H1/H2 2.0 ± 0.3*C1/C2 Not cleaved* 32P-labeled strand.In all cases, hmC was a worse substrate for NtROS1 comparedto mC. Based on these results, we conclude that NtROS1cleaves hemimethylated CpG sites most efficiently, while hmCin the context of HG/GM, on the contrary, is the worst substratefor this enzyme. The kinetic constants are consistent with thequalitative data on the relative cleavage efficiency for differentsubstrates .Many slow-turnover DNA glycosylases have lower APlyase activity in comparison with their DNA glycosylaseactivity. In this case, after the removal of the modified base,a part of the reaction product exists as an AP site for a longtime, and the true amount of the product can be revealed onlyupon treatment with alkali or nucleophilic amines . However, in the case of NtROS1, additional treatmentwith NaOH did not lead to a noticeable increase in theaccumulation of the reaction product . Apparently,the rate of the reaction catalyzed by NtROS1 is limitedby the hydrolysis of the N-glycosidic bond, which was alsosuggested for the enzyme from A. thaliana .To assess the ability of the NtROS1 protein to act asa demethylasewhen expressed in mammalian cells, we constructedplasmids based on the pIRES-eGFP-puro vectorencoding wild-type NtROS1 and its catalytically inactivemutant NtROS1 D1359N. Using anti-mC antibodies, we haveestimated the level of this epigenetic base in HEK293 cellsafter transfection with these plasmids. When cells were observedpost-transfection, the proliferation of cells with thepIRES-eGFP-puro-NtROS1 plasmid was reduced by about30 % compared to the control cells transfected with the plasmidwith no insert and the cells transfected with the plasmidencoding the catalytic mutant. The fraction of live cells wasthe same in all cases, which indicates that the cell cycle maybe slower in the presence of active NtROS1 due to the needto repair a large number of breaks introduced into DNA atmC residues. An analysis of the mC level revealed a ~2-folddecrease relative to control samples when wild-type NtROS1 was expressed and the absence of statistically significantchanges with the expression of NtROS1 D1359N . Ingeneral, it can be considered that the transient expression ofthe catalytic domain of 5-methylcytosine–DNA glycosylaseNtROS1 in human cells indeed leads to the global erasure ofmC epigenetic marks. The amount of hmC in cells could notbe measured using anti-hmC antibodies, probably because thismodified base is about an order of magnitude less abundantthan mC .Thus, it can be concluded that NtROS1 is a DNA glycosylasespecific for 5-methylcytosine and, to a lesser extent,for 5-hydroxymethylcytosine. Its biological functions, as inthe case of AtROS1, most likely consist in the regulation ofmethylation status and gene expression during embryonicdevelopment  or in the response toinfections and abiotic stress ,and the regulation of silencing of transgenes and transposableelements . The mechanism of RNA-dependent addressing of DME/ROS1 family proteins to specific demethylation sites,which has not yet been elucidated, is of great interest. TheRRM motif in these polypeptides is homologous to the motifsresponsible for nonspecific interactions with RNA in manyother proteins  and, by its position in thestructure , could bind small RNAs complementaryto the DNA stretch 5′ of the targeted mC. Zinc fingers ofthe CXXC type are used by many mC-recognizing proteins;however, they predominantly bind unmethylated DNA and arepresumably required for accurate positioning of the enzymein the presence of several methylation sites located at a shortdistance .The prospects for using NtROS1 and other proteins of theDME/ROS1 family as tools for genetic technologies largelydepend on the possibility of reducing the size of the catalyticfragment. A deletion of the long insert between the two partsof the HhH domain in AtROS1 fully preserves its activity, buta deletion of the C-terminal tail after the FeS cluster resultsin an inactive enzyme . Judging from thestructural models of AtROS1 and NtROS1, the HhH and RRMdomains interact with each other, and shortening the proteinhere may only be done by trimming the insert between them.In any case, DME/ROS1 proteins, including NtROS1, representa promising scaffold for enzyme engineering to analyzeepigenetic methylation status and control gene activity.The study of the demethylating DNA glycosylase ROS1 fromNicotiana tabacum reported in this work presents the onlybiochemical investigation of ROS1 beyond its homologuefrom Arabidopsis thaliana. In addition to 5-methylcytosine,NtROS1 showed the ability to remove 5-hydroxymethylcytosinefrom DNA, but the efficiency of this reaction was lowerthan for 5-methylcytosine, apparently because plants rarely ifat all use 5-hydroxymethylcytosine as an epigenetic marker.The observed decrease in global methylation upon expressionof NtROS1 in human cells suggests that this protein or itsoptimized variants can be used as a tool for epigenetic regulation,either on its own or as an active module in constructstargeted to certain genome regions.The authors declare no conflict of interest.Agius F., Kapoor A., Zhu J.-K. Role of the Arabidopsis DNA glycosylase/lyase ROS1 in active DNA demethylation. Proc. Natl. Acad. Sci.USA. 2006;103(31):11796-11801. DOI 10.1073/pnas.0603563103Ballestar E., Wolffe A.P. Methyl-CpG-binding proteins. Targetingspecific gene repression. Eur. J. Biochem. 2001;268(1):1-6. DOI10.1046/j.1432-1327.2001.01869.x.Baubec T., Ivánek R., Lienert F., Schübeler D. Methylation-dependentand -independent genomic targeting principles of the MBD proteinfamily. Cell. 2013;153(2):480-492. DOI 10.1016/j.cell.2013.03.011.Bochtler M., Kolano A., Xu G.-L. DNA demethylation pathways: additionalplayers and regulators. Bioessays. 2017;39(1):1-13. DOI10.1002/bies.201600178.Branco M.R., Ficz G., Reik W. Uncovering the role of 5-hydroxymethylcytosinein the epigenome. Nat. Rev. Genet. 2011;13(1):7-13.DOI 10.1038/nrg3080Choi C.-S., Sano H. Identification of tobacco genes encoding proteinspossessing removal activity of 5-methylcytosines from intact tobaccoDNA. Plant Biotechnol. 2007;24(3):339-344. DOI 10.5511/plantbiotechnology.24.339Choi W.L., Mok Y.G., Huh J.H. Application of 5-methylcytosine DNAglycosylase to the quantitative analysis of DNA methylation. Int. J.Mol. Sci. 2021;22(3):1072. DOI 10.3390/ijms22031072.Choi Y., Gehring M., Johnson L., Hannon M., Harada J.J., GoldbergR.B., Jacobsen S.E., Fischer R.L. DEMETER, a DNA glycosylasedomain protein, is required for endosperm gene imprintingand seed viability in Arabidopsis. Cell. 2002;110(1):33-42. DOI10.1016/s0092-8674(02)00807-3.Cléry A., Blatter M., Allain F.H.-T. RNA recognition motifs: boring?Not quite. Curr. Opin. Struct. Biol. 2008;18(3):290-298. DOI10.1016/j.sbi.2008.04.002.Devesa-Guerra I., Morales-Ruiz T., Pérez-Roldán J., Parrilla-DoblasJ.T., Dorado-León M., García-Ortiz M.V., Ariza R.R., Roldán-Arjona T. DNA methylation editing by CRISPR-guided excisionof 5-methylcytosine. J. Mol. Biol. 2020;432(7):2204-2216. DOI10.1016/j.jmb.2020.02.007.Fedorova O.S., Kuznetsov N.A., Koval V.V., Knorre D.G. Conformationaldynamics and pre-steady-state kinetics of DNA glycosylases.Biochemistry (Moscow). 2010;75(10):1225-1239. DOI 10.1134/S0006297910100044Gong Z., Morales-Ruiz T., Ariza R.R., Roldán-Arjona T., David L.,Zhu J.-K. ROS1, a repressor of transcriptional gene silencing inArabidopsis,encodes a DNA glycosylase/lyase. Cell. 2002;111(6):803-814. DOI 10.1016/s0092-8674(02)01133-9.Gruber D.R., Toner J.J., Miears H.L., Shernyukov A.V., Kiryutin A.S.,Lomzov A.A., Endutkin A.V., Grin I.R., Petrova D.V., KupryushkinM.S., Yurkovskaya A.V., Johnson E., Okon M., BagryanskayaE.G., Zharkov D.O., Smirnov S.L. Oxidative damage to epigeneticallymethylated sites affects DNA stability, dynamics, andenzymatic demethylation. Nucleic Acids Res. 2018;46(20):10827-10839. DOI 10.1093/nar/gky893.Hong S., Hashimoto H., Kow Y.W., Zhang X., Cheng X. The carboxyterminaldomain of ROS1 is essential for 5-methylcytosine DNAglycosylase activity. J. Mol. Biol. 2014;426(22):3703-3712. DOI10.1016/j.jmb.2014.09.010.Iyer L.M., Abhiman S., Aravind L. Natural history of eukaryotic DNAmethylation systems. Prog. Mol. Biol. Transl. Sci. 2011;101:25-104.DOI 10.1016/B978-0-12-387685-0.00002-0.Jang H., Shin H., Eichman B.F., Huh J.H. Excision of 5-hydroxymethylcytosineby DEMETER family DNA glycosylases. Biochem.Biophys. Res. Commun. 2014;446(4):1067-1072. DOI 10.1016/j.bbrc.2014.03.060Jumper J., Evans R., Pritzel A., Green T., Figurnov M., Ronneberger O.,Tunyasuvunakool K., Bates R., Žídek A., Potapenko A., Bridgland A.,Meyer C., Kohl S.A.A., Ballard A.J., Cowie A., Romera-Paredes B.,Nikolov S., Jain R., Adler J., Back T., Petersen S., Reiman D., ClancyE., Zielinski M., Steinegger M., Pacholska M., Berghammer T.,Bodenstein S., Silver D., Vinyals O., Senior A.W., Kavukcuoglu K.,Kohli P., Hassabis D. Highly accurate protein structure predictionwith AlphaFold. Nature. 2021;596(7873):583-589. DOI 10.1038/s41586-021-03819-2.Kapazoglou A., Drosou V., Argiriou A., Tsaftaris A.S. The study ofa barley epigenetic regulator, HvDME, in seed development andunder drought. BMC Plant Biol. 2013;13:172. DOI 10.1186/1471-2229-13-172.Kapoor A., Agarwal M., Andreucci A., Zheng X., Gong Z., HasegawaP.M., Bressan R.A., Zhu J.-K. Mutations in a conserved replicationprotein suppress transcriptional gene silencing in a DNAmethylation-independent manner in Arabidopsis. Curr. Biol. 2005;15(21):1912-1918. DOI 10.1016/j.cub.2005.09.013.Le T.-N., Schumann U., Smith N.A., Tiwari S., Au P.C.K., Zhu Q.- H.,Taylor J.M., Kazan K., Llewellyn D.J., Zhang R., Dennis E.S.,Wang M.-B. DNA demethylases target promoter transposable elementsto positively regulate stress responsive genes in Arabidopsis.Genome Biol. 2014;15(9):458. DOI 10.1186/s13059-014-0458-3.Lee T.-F., Zhai J., Meyers B.C. Conservation and divergence in eukaryoticDNA methylation. Proc. Natl. Acad. Sci. USA. 2010;107(20):9027-9028. DOI 10.1073/pnas.1005440107.Li X., Qian W., Zhao Y., Wang C., Shen J., Zhu J.-K., Gong Z. Antisilencingrole of the RNA-directed DNA methylation pathway and ahistone acetyltransferase in Arabidopsis. Proc. Natl. Acad. Sci. USA.2012;109(28):11425-11430. DOI 10.1073/pnas.1208557109.Li Y., Kumar S., Qian W. Active DNA demethylation: mechanism androle in plant development. Plant Cell Rep. 2018;37(1):77-85. DOI10.1007/s00299-017-2215-z.Liu R., How-Kit A., Stammitti L., Teyssier E., Rolin D., Mortain-BertrandA., Halle S., Liu M., Kong J., Wu C., Degraeve-Guibault C.,Chapman N.H., Maucourt M., Hodgman T.C., Tost J., Bouzayen M.,Hong Y., Seymour G.B., Giovannoni J.J., Gallusci P. A DEMETERlikeDNA demethylase governs tomato fruit ripening. Proc. Natl.Acad. Sci. USA. 2015;112(34):10804-10809. DOI 10.1073/pnas.1503362112.Morales-Ruiz T., Ortega-Galisteo A.P., Ponferrada-Marín M.I., Martínez-Macías M.I., Ariza R.R., Roldán-Arjona T. DEMETER andREPRESSOR OF SILENCING 1 encode 5-methylcytosine DNAglycosylases. Proc. Natl. Acad. Sci. USA. 2006;103(18):6853-6858.DOI 10.1073/pnas.0601109103.Ono A., Yamaguchi K., Fukada-Tanaka S., Terada R., Mitsui T.,Iida S. A null mutation of ROS1a for DNA demethylation in riceis not transmittable to progeny. Plant J. 2012;71(4):564-574. DOI10.1111/j.1365-313X.2012.05009.xOrtega-Galisteo A.P., Morales-Ruiz T., Ariza R.R., Roldán-Arjona T.Arabidopsis DEMETER-LIKE proteins DML2 and DML3 are requiredfor appropriate distribution of DNA methylation marks.Plant Mol. Biol. 2008;67(6):671-681. DOI 10.1007/s11103-008-9346-0.Ortega-Galisteo A.P., Morales-Ruiz T., Ariza R.R., Roldán-Arjona T.Arabidopsis DEMETER-LIKE proteins DML2 and DML3 are requiredfor appropriate distribution of DNA methylation marks.Plant Mol. Biol. 2008;67(6):671-681. DOI 10.1007/s11103-008-9346-0.Pastor W.A., Aravind L., Rao A. TETonic shift: biological roles of TETproteins in DNA demethylation and transcription. Nat. Rev. Mol.Cell Biol. 2013;14(6):341-356. DOI 10.1038/nrm3589.Pastor W.A., Pape U.J., Huang Y., Henderson H.R., Lister R., Ko M.,McLoughlin E.M., Brudno Y., Mahapatra S., Kapranov P., TahilianiM., Daley G.Q., Liu X.S., Ecker J.R., Milos P.M., Agarwal S.,Rao A. Genome-wide mapping of 5-hydroxymethylcytosine in embryonicstem cells. Nature. 2011;473(7347):394-397. DOI 10.1038/nature10102.Penterman J., Uzawa R., Fischer R.L. Genetic interactions betweenDNA demethylation and methylation in Arabidopsis. Plant Physiol.2007;145(4):1549-1557. DOI 10.1104/pp.107.107730.Ponferrada-Marín M.I., Parrilla-Doblas J.T., Roldán-Arjona T., ArizaR.R. A discontinuous DNA glycosylase domain in a family of enzymesthat excise 5-methylcytosine. Nucleic Acids Res. 2011;39(4):1473-1484. DOI 10.1093/nar/gkq982.Ponferrada-Marín M.I., Roldán-Arjona T., Ariza R.R. ROS1 5-methylcytosineDNA glycosylase is a slow-turnover catalyst that initiatesDNA demethylation in a distributive fashion. Nucleic Acids Res.2009;37(13):4264-4274. DOI 10.1093/nar/gkp390.Porello S.L., Leyes A.E., David S.S. Single-turnover and pre-steadystatekinetics of the reaction of the adenine glycosylase MutY withmismatch-containing DNA substrates. Biochemistry. 1998;37(42):14756-14764. DOI 10.1021/bi981594+.Roldán-Arjona T., Ariza R.R., Córdoba-Cañero D. DNA base excisionrepair in plants: an unfolding story with familiar and novel characters.Front. Plant Sci. 2019;10:1055. DOI 10.3389/fpls.2019.01055.Waterhouse A., Bertoni M., Bienert S., Studer G., Tauriello G., GumiennyR., Heer F.T., de Beer T.A.P., Rempfer C., Bordoli L., Lepore R.,Schwede T. SWISS-MODEL: homology modelling of proteinstructures and complexes. Nucleic Acids Res. 2018;46(W1):W296-W303. DOI 10.1093/nar/gky427Wen S., Wen N., Pang J., Langen G., Brew-Appiah R.A.T., MejiasJ.H.,Osorio C., Yang M., Gemini R., Moehs C.P., Zemetra R.S., KogelK.-H., Liu B., Wang X., von Wettstein D., Rustgi S. Structuralgenes of wheat and barley 5-methylcytosine DNA glycosylasesand their potential applications for human health. Proc. Natl.Acad. Sci. USA. 2012;109(50):20543-20548. DOI 10.1073/pnas.1217927109.Wu X., Zhang Y. TET-mediated active DNA demethylation: mechanism,function and beyond. Nat. Rev. Genet. 2017;18(9):517-534.DOI 10.1038/nrg.2017.33.Yamamuro C., Miki D., Zheng Z., Ma J., Wang J., Yang Z., Dong J.,Zhu J.-K. Overproduction of stomatal lineage cells in Arabidopsismutants defective in active DNA demethylation. Nat. Commun.2014;5:4062. DOI 10.1038/ncomms5062Yu M., Hon G.C., Szulwach K.E., Song C.-X., Zhang L., Kim A.,Li X., Dai Q., Shen Y., Park B., Min J.-H., Jin P., Ren B., He C.Base-resolution analysis of 5-hydroxymethylcytosine in the mammaliangenome. Cell. 2012;149(6):1368-1380. DOI 10.1016/j.cell.2012.04.027Zahid O.K., Zhao B.S., He C., Hall A.R. Quantifying mammalian genomicDNA hydroxymethylcytosine content using solid-state nanopores.Sci. Rep. 2016;6:29565. DOI 10.1038/srep29565.Zemach A., Zilberman D. Evolution of eukaryotic DNA methylationand the pursuit of safer sex. Curr. Biol. 2010;20(17):R780-R785.DOI 10.1016/j.cub.2010.07.007.Zharkov D.O. Base excision DNA repair. Cell. Mol. Life Sci. 2008;65(10):1544-1565. DOI 10.1007/s00018-008-7543-2.Zhu J., Kapoor A., Sridhar V.V., Agius F., Zhu J.-K. The DNA glycosylase/lyase ROS1 functions in pruning DNA methylation patternsin Arabidopsis. Curr. Biol. 2007;17(1):54-59. DOI 10.1016/j.cub.2006.10.059.


Several validated scales have been developed to measure frailty, yet it remains unknown how these measures are related. We used data from 7,070 community-dwelling older adults who participated in National Health and Aging Trend Study round 5 to construct a crosswalk among frailty measures. We operationalized the 60-item Frailty Index (FI), Study of Osteoporotic Fracture (SOF) Index, FRAIL Scale, Frailty Phenotype, Clinical Frailty Scale (CFS), Vulnerable Elder Survey-13 (VES-13), Tilburg Frailty Indicator (TFI), Groningen Frailty Indicator (GFI), and Edmonton Frailty Scale (EFS). Missing data, needed for the calculation of frailty scores, were imputed using multiple imputation by chained equations method. We then linked the scores of each frailty measure to FI using the equipercentile method, a statistical procedure that links different scales by equating percentile distributions. Participants considered frail on FI (cutpoint of 0.25) corresponded to the following scores on each frailty measure: SOF 1.3, FRAIL 1.7, Phenotype 1.7, CFS 5.3, VES-13 5.5, TFI 4.4, GFI 4.4, and EFS 5.8. Conversely, individuals considered frail on each frailty measure corresponded to the following FI scores: 0.37 (SOF), 0.40 (FRAIL), 0.42 (Phenotype), 0.21 (CFS), 0.19 (VES-13), 0.28 (TFI), 0.22 (GFI), and 0.37 (EFS). The CFS, VES-13, TFI and GFI each discriminates between non-frail and frail people in the pre- to mildly frail spectrum on the FI, whereas the SOF, FRAIL Scale, Phenotype, and EFS detect those in the higher frailty spectrum on the FI. Our results provide clinicians and researchers with a useful tool to convert and interpret frailty across scales.


Retraction Note: J Exp Clin Cancer Res 37, 14 (2018)https://doi.org/10.1186/s13046-018-0681-yThe Editor in Chief has retracted this article. After publication, concerns were raised about Figs. 4d, 5e, and 6h. These were addressed in a Correction . Later,


Stem Cell Res Ther (2021) 12:456 https://doi.org/10.1186/s13287-021-02519-yThe authors have retracted this article. After publication, the authors noticed image duplication errors in Figs. 2A, 5K, 6B, S3E and S10B, some of which also overlapped with the authors' earlier article [All authors agree to this retraction.


Lactobacillus pentosus (L. pentosus) plays a neuron-protective role. This study aimed to investigate the effects of L. pentosus on neurodegenerative diseases.  Neurodegenerative disease is a common neurodegenerative disorder. L. pentosus strain S-PT84. Reverse transcription-quantitative PCR (RT-qPCR) was applied to determine mRNA levels. Western blot was performed to detect protein expression. Cellular behaviors were detected using Cell Counting Kit-8 (CCK-8), flow cytometry, and TdT-mediated dUTP nick-end labeling (TUNEL) assay. The interaction between baculoviral IAP repeat containing 3 (BIRC3) and NLR family CARD domain containing 4 (NLRC4) was predicted by STING and verified by western blot.  Cells were treated with lipopolysaccharide (LPS) to establish neurodegenerative diseases model in vivo and with L. pentosus suppressed LPS-induced pyroptosis and promoted the cell viability of neurons. Additionally, L. pentosus suppressed the release of proinflammatory cytokines (interleukin 1 beta (IL-1β) and IL-18) and the protein expression of pyroptosis biomarkers (cleaved caspase1 (CL-CASP1) and N-terminal fragment gasdermin D (GSDMD-N)). Moreover, L. pentosus upregulated BIRC3, which induced the inactivation of NLRC4. However, BIRC3 knockdown alleviated the effects of L. pentosus and induced neuronal degeneration. L. pentosus may play a neuron-protective role via regulating BIRC3/NLRC4 signaling pathways. Therefore, L. pentosus may be a promising strategy for neurodegenerative diseases. Dementia is a common neurodegenerative disease, characterized by progressive cognitive degeneration, which induces huge burden on public health . Elder nβ and IL-18, and cell death [Pyroptosis is a form of programmed cell death executed by Gasdermin D (GSDMD)  The actill death . Previoull death –12. HoweLactobacillus pentosus (L. pentosus), a member of probiotics from intestinal flora, plays a neuron-protective role and mitigates aging- and scopolamine-induced memory impairment [Probiotics are considered to be a safe alternative therapy for many diseases, including cancer and neural disorders , 14. Accpairment , 17. HowκB) target gene activation to attenuate inflammation, which promotes the development of splenic marginal zone lymphoma [Baculoviral IAP repeat containing 3 (BIRC3) is a member of inhibitor of apoptosis proteins (IAPs) . BIRC3 slymphoma . Moreovelymphoma . However2.Human neuroblastoma cell lines SH-SY5Y were provided by American type culture collection (ATCC), USA. Cells were cultured in Dulbecco's modified Eagle's medium (DMEM) medium containing 10% FBS and 1% penicillin/streptomycin at 37°C with 5% CO5 cells) were incubated with 10 μg/L of lipopolysaccharide (LPS) and/or L. pentosus strain S-PT84 .Cells . Then, PCR was performed using SYBR Premix Ex Taq . GAPDH served as loading control. Relative mRNA levels were calculated using the 2β, IL-18, procaspase1, cleaved caspase1, GSDMD-N, BIRC3, NLRP3, NLRC1, NLRP3, NLRC4, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) at 4°C overnight. Next day, the membranes were incubated with secondary antibodies. GAPDH was used as the loading control. Subsequently, the bands were captured using an efficient chemiluminescence (ECL) kit and analyzed using the ImageJ software.Total protein was extracted from SH-SY5Y cells. Protein concentration was measured using a bicinchonininc acid (BCA) kit. The protein was separated using 12% SDS-PAGE. Afterwards, the separated protein was moved onto polyvinylidene difluoride (PVDF) membranes, which was then sealed by 5% skimmed milk. The membranes were incubated with primary antibodies against IL-1Cells were collected and lysed. Then, cell lysates were centrifuged at 12,000 × g and immunoprecipitated with specific antibodies. Afterwards, the proteins were coprecipitated and isolated using 12% SDS-PAGE. Immunoblotting was analyzed with antianalysis with the indicated primary antibodies against BIRC3, NLRC4, and GAPDH.3 cells/well). After incubated with L. pentosus for 48 h, cells were cultured with Cell Counting Kit-8 (CCK-8) regents for 4 h. Subsequently, optic density was determined using a microplate at 450 nm.Cells were seeded into 24-well plates . Subsequently, a flow cytometry was used to calculate the pyroptosis rates: active caspase1 + PI double positive cells/total cells × 100%.Cells were collected and fixed with 4% paraformaldehyde. After washed with 5% PBS, cells were cultured with TUNEL solutions. Then, the cells were counterstained with DAPI. Finally, TUNEL positive cells were captured using a fluorescence microscope.t-test and one-way ANOVA. P < 0.05 dictated significant difference.All data were evaluated using GraphPad 6.0. and represented as mean ± SD. The comparison was performed using Student's Lactobacillus pentosus (L. pentosus) on neuronal degeneration, cells were cultured with L. pentosus. As shown in To investigate the effects of L. pentosus, SH-SY5Y cells were exposed to LPS. As shown in Figures β and IL-18, which was antagonized by L. pentosus. These results were consistent with that from western blot. L. pentosus treatment markedly alleviated the effects of LPS and suppressed the protein expression of IL-1β and IL-18.Inflammation is a key factor for neuronal degeneration. To verify the effects of L. pentosus significantly decreased PI and active caspase1-positive cells induced by LPS. Additionally, LPS-mediated increase in TUNEL-positive cells was abated by L. pentosus treatment (L. pentosus on LPS-induced neuronal cell death, we determined the protein expression of pyroptosis biomarkers. LPS exposure significantly increased the protein expression of cleaved caspase1 and GSDMD-N (L. pentosus.Cellular functions were detected using flow cytometry and TUNEL assay. As shown in reatment . To furt GSDMD-N , which wL. pentosus treatment significantly increased BIRC3 mRNA levels compared with the LPS group (L. pentosus also increased the protein expression of BIRC3 (Previous studies report that BIRC3 plays a neuron-protective role. We then determined the expression of BIRC3 in neurons. As shown in PS group . Moreoveof BIRC3 .L. pentosus + sh-NC group. BIRC3 knockdown significantly suppressed the cell viability of SH-SY5Y cells (β and IL-18 (Figures The rescue assay was performed to verify the roles of BIRC3 in neuronal degeneration. As shown in 5Y cells . Additio Figures .As shown in Figures We further investigated the underlying molecular mechanisms that BIRC3 inhibited neuronal pyroptosis. The online database STING showed that the potential genes interacts with BIRC3 . The resL. pentosus play a neuron-protective role. L. pentosus suppressed inflammatory response and pyroptosis of neuron cells. Moreover, L. pentosus upregulated BIRC3, suppressing the inactivation of NLRC4 inflammasome. Hence, L. pentosus may be a promising therapy for neurodegenerative diseases.In this study, β, and p-Tau to contribute to neuroinflammation and memory impairment [β [L. pentosus treatment restored neuronal cellular functions, manifested by the increase in cell viability and decrease in pyroptosis rates. Previous studies evidence that L. pentosus promotes cognitive capability and alleviates aging-dependent memory impairment [L. pentosus may be a promising strategy for neurodegenerative diseases.The activation of inflammasomes increases cytotoxicity and contributes to the pyroptosis of neurons, which is a key factor for memory loss and cognitive impairment . For inspairment . High lerment [β . NLRP1 drment [β . These rrment [β , which fpairment , 32. Theβ-induced neuronal apoptosis [L. pentosus alleviated LPS-induced downregulation of BIRC3. However, BIRC3 knockdown alleviated the effects of L. pentosus and promoted inflammation and pyroptosis of neurons. These results suggested that BIRC3 may play a neuron-protective role, which is consistent with previous studies [BIRC3 plays a vital role in neuronal function. For instance, NPD1-mediated upregulation of BIRC3 promotes neural cell survival . Additiopoptosis . Howeverpoptosis  as well poptosis . Hence,  studies .L. pentosus-mediated upregulation of BIRC3 contributed to inactivation of NLRC4 inflammasome, which suppressed neuronal pyroptosis.However, approximately 80% studies focused on the roles of BIRC3 cancer. The reports on its roles in neural disorders are limited. BIRC3 mainly exerts its neuron-protective functions via regulating caspases cascades, which suppresses the neuronal apoptosis . RecentlL. pentosus-induced upregulation of BIRC3 suppressed inflammatory response and pyroptosis of neurons via inactivating NLRC4 inflammasome. Therefore, L. pentosus may be an alternative strategy for neurodegenerative diseases.In conclusion,


Despite tremendous success of molecular targeted therapy together with immunotherapy, only a small subset of patients can benefit from them. Chemotherapy remains the mainstay treatment for most of tumors including non-small cell lung cancer (NSCLC); however, non-selective adverse effects on healthy tissues and secondary resistance are the main obstacles. Meanwhile, the quiescent or dormant cancer stem-like cells (CSLCs) are resistant to antimitotic chemoradiotherapy. Complete remission can only be realized when both proliferative cancer cells and quiescent cancer stem cells are targeted. In the present research, we constructed a cooperatively combating conjugate (DTX-P7) composed of docetaxel (DTX) and a heptapeptide (P7), which specifically binds to cell surface Hsp90, and assessed the anti-tumor effects of DTX-P7 on non-small cell lung cancer. DTX-P7 preferentially suppressed tumor growth compared with DTX in vivo with a favorable distribution to tumor tissues and long circulation half-life. Furthermore, we revealed a distinctive mechanism whereby DTX-P7 induced unfolded protein response and eventually promoted apoptosis. More importantly, we found that DTX-P7 promoted cell cycle reentry of slow-proliferating CSLCs and subsequently killed them, exhibiting a “proliferate to kill” pattern. Collecitvely, by force of active targeting delivery of DTX via membrane-bound Hsp90, DTX-P7 induces unfolded protein response and subsequent apoptosis by degrading Hsp90, meanwhile awakens and kills the dormant cancer stem cells. Thus, DTX-P7 deserves further development as a promising anticancer therapeutic for treatment of various membrane-harboring Hsp90 cancer types.The online version contains supplementary material available at 10.1186/s13045-022-01274-8. To the editor,To address off-target toxicity of conventional chemotherapy, one effort is to enhance the targeted delivery by conjugating therapeutic effector through a cleavable linker to a ligand specific to a drug target, and several conjugates of targeting agents have been approved for application in oncology , 2. HoweHerein, we designed and identified a peptide-conjugated drug comprising P7 and docetaxel (DTX) (namely DTX-P7)  and PI3K-Akt signaling pathway  Chemical structures of DTX and DTX-P7. DTX, molecular formula: C43H53NO14, molecular weight: 807.9 g/mol, white powder. DTX-P7, molecular formula: C84H118N8O25, molecular weight: 1,639.90 g/mol, white powder. b-c) Cell viability of DTX-P7 and DTX in A549 (b) and H1975 (c) cells following 48-h treatment. IC50 values: A549 cells, DTX-P7 11.4 nM, DTX 1.11 nM; H1975 cells, DTX-P7 0.62 nM, DTX 0.50 nM.Additional file 3: Supplementary Figure S2. Biodistribution of DTX-P7 in nude mice bearing A549 xenograft tumor. DTX-P7 was quantified by free DTX released from the conjugate. a) Plasma concentration of DTX and DTX-P7 in plasma samples throughout 72-h treatment. b-e) Distribution of DTX in the heart, liver, spleen, lungs, kidneys, and brain in 1 h (b), 2 h (c), 4 h (d) and 8 h (e) after DTX or DTX-P7 was administrated to mice implanted with A549 xenograft tumor. Data are given as mean ± SD (n = 3). * p < 0.05 vs. DTX group.Additional file 4: Supplementary Figure S3. Proteome changes induced in A549 cells by DTX-P7. a-c) Gene Ontology (GO) annotation analysis of A549 cell proteins that changed more than 1.5-ratio after DTX-P7 treatment, including altered proteins for biological process (a), cellular component (b) and molecular function (c) analyses. d) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation analysis of A549 cell proteins that changed more than 1.5-ratio after DTX-P7 treatment.Additional file 5: Supplementary Figure S4. Cell growth morphology of cancer stem cell-like A549/CD133+ cells and identification of cell surface Hsp90 in A549/CD133+ cells. a) Morphology of A549 and A549/CD133+ cells. b) Hsp90 expression levels were assessed in A549/CD133+ cells by cellular fractionation and Western blotting analysis. c) Immunofluorescence analysis of cell surface Hsp90 in A549/CD133+ cells. d) Immunofluorescence assays of FITC-labeled P7 binding to A549/CD133+ cells. Competition of P7 binding to A549/CD133+ cells by excess free P7.Additional file 6: Supplementary Figure S5. Effects of DTX-P7 on survival of A549/CD133+ cells and PKH26 staining of A549/CD133+ cells. a) Cell viability of DTX-P7 and DTX in A549/CD133+ cells following 48-h treatment. b) A549/CD133+ cells were stained by PKH26 followed by fluorescence detection at Day 0, 1, 6 and 10. c) Representative fluorescence-activated cell sorting profile of A549/CD133+ cells selected for sorting 10 days after PKH26 staining as compared with those of the unstained control (negative control) and Day 0.


Fecal calprotectin (FC) is a sensitive marker of intestinal inflammation, and is used to both discriminate inflammatory bowel disease (IBD) from non-IBD patients and to monitor patients with IBD. It is unclear whether normal values established in adult patients are applicable in pediatrics.To evaluate FC’s ability to differentiate IBD from non-IBD pediatric patients, and to understand factors influencing FC in pediatric IBD(pIBD).Stool FC samples collected on all patients<19 years of age in British Columbia(BC) from May 2020 to August 2022 were run using a Buhlmann ELISA at BC Children’s Hospital(BCCH). The BCCH GI database identified patients with IBD. FC’s ordered by adult IBD providers and patients awaiting endoscopy were excluded. The remaining samples were analysed as non-IBD. The sensitivity(Sn), negative predictive value(NPV) and false positive(FP) of FC were evaluated; comparisons were made using the Wilcoxon rank-sum test and chi-squared.3506 FC samples met inclusion criteria: 1853 IBD and 1653 non-IBD. 221 IBD samples were from prior to diagnosis, with median (IQR) FC 2615ug/g(1090-4183); median FC for non-IBD patients was 54ug/g(24-122). Using the Buhlmann "normal" cutoff of 80ug/g, the Sn was 0.991 (NPV 0.998) with a FP rate of 37%. Young patients were more likely to have FP's: <6yo's (n=305) had a FP rate of 42% vs 36% in those >6yo (n=1348)(p=0.035). With a FC cutoff of 160ug/g, Sn was 0.973 (NPV 0.996), with a FP rate of 20% . At a threshold of 250ug/g, Sn was 0.959 (NPV 0.994) with a FP rate of 13% . For patients <2yo, all 4 new IBD diagnosis had FC>1900ug/g. In the non-IBD population (n=69 samples <2yo), the FP rate was 52%, 30%, and 22% using a threshold of 80, 160, and 250ug/g, respectively.Evaluating FC as a disease-monitoring tool in IBD  found that at 6, 12, 18, and 24+ months post diagnosis, FC decreased from 750(159-1883), 505(110-1566), 351(87-1379), to 308ug/g(85-1129), respectively. Similarly, the proportion of FC’s <250ug/g increased from 4.1% at diagnosis to 30%, 39.7%, 41.5%, 47% during the follow up period.Patients with UC/IBD-U had higher FC’s, and were less likely to achieve FC<250ug/g. By 12 months post diagnosis, median FC of CD patients was 347ug/g(96-1150) and UC/IBD-U was 745ug/g(191-2017)(p=0.036), and at 18 months, CD 273ug/g(61-902) vs UC/IBD-U 932ug/g(144-2229)(p<0.001). At 2+yrs, median FC for CD patients was 259ug/g(76-1038) vs 387ug/g(108-1577) for UC/IC (p=0.017).Patients cared for by an IBD specialist had better FC outcomes vs those managed by non-IBD GIs: median FC at 12 months was 246ug/g(n=79) vs 677ug/g(n=153)(p=0.002), with 51% vs 34% achieving FC<250(p=0.014). Similarly, at 2+yrs post diagnosis, median FC was 243ug/g(n=437) vs 356ug/g(n=407)(p=0.02).Higher FC thresholds are likely required in younger populations compared to established adult cutoffs. In this pIBD cohort, <50% achieve FC levels <250ug/g.NoneNone Declared


We described emergency department (ED) visits by persons with multiple sclerosis (MS) in British Columbia, Canada (1 April2012 to 31 December 2017). We identified 15,350 MS cases using healthadministrative data; 73.4% were women, averaging 51.4 years at study entry. Over4.9 years of follow-up (mean), 56.0% of MS cases visited an ED . A diagnosis was documented for25,698 (69.3%) ED visits, and 18.4%  were infection-related.Inpatient admissions were reported for 20.4%  of all and 29.2%(1380/4725) of infection-related ED visits. Findings suggest that the ED plays asubstantial role in MS healthcare and infection management. For example,persons with MS had 41% more infection-related physician claims  versus a sex-, age-, andregion-matched non-MS population. However, relatively little is known about ED utilization by persons withMS.46 Here, we described overall andinfection-related ED use in an MS population.Emergency department (ED) presentations represent an important aspect of health careutilization in the general population.), including Medical Service Plan Billing Information (providing physician claims); the Discharge Abstract Database ; PharmaNet (for prescriptions filled at outpatient/community pharmacies); Census Geodata(providing socioeconomic status estimates); Registration and Premium Billing files ; Vital Statistics (capturing death dates); and the National Ambulatory Care Reporting System dataset  starting 1 April 2012).We performed a descriptive, population-based study in British Columbia (BC), Canada,using linked health administrative data  code, or first disease-modifyingdrug (DMD) prescription filled, or 1 April 2012 (start of the ED date). All includedpersons were ⩾18 years old and BC residents for ⩾1 year pre-study entry; follow-upended at the earliest of death, emigration, or 31 December 2017. Comorbidities weremeasured using a modified Charlson Comorbidity Index during the 1-year pre-studyentry.1618 MS cases everfilling a DMD prescription during follow-up were described.All MS cases were identified with a validated algorithm.n = 8603) with (vs without) comorbidity at study entrywere older (mean age = 56.5 (SD = 14.3) vs 49.5 (SD = 13.7) years) and averaged moreED visits/person/year (1.3 (SD = 2.4) vs 0.9 (SD = 1.9)). More than a quarter of MScases had ⩾3 ED visits ; of these 1383 (34.0%) of 4064 had ⩾1comorbidity at study entry. Most ED visits by MS cases did not require an ambulance; 28.8% required a ground ambulance  and>95% were of semi-urgent or higher priority .We identified 15,350 MS cases  women; Supplementary Table 2). These visits were made by 74.2%(6384/8603) of MS ED users. Of these, the most frequent primary diagnoses were“abdominal pain/colic” , “urinary tract infection”, and “MS” . When combined, 18.4% of ED visits were infection-related with 32.2% (2056/6384) of MSparticipants having at least one such visit. Nearly one-third of infection-related ED visits led to hospitalization, while 20.4% of all ED visits made by 27.9% (2404/8603) of cases did so (Supplementary Tables 2 and 3).Diagnostic codes were reported for 69.3%  of ED visits (summarizedin Persons who filled ⩾1 DMD prescription(s) during follow-up (“DMD users”) wereyounger at study entry date than non-users (mean age = 41.9 (SD = 11.1) vs 53.8(SD = 13.3) years). However, the proportions accessing an ED at least once weregenerally similar , as was the study follow-up time (4.8 years (SD = 1.6) for DMD usersvs 4.9 (SD = 1.6) for non-users).There were no clear patterns across the socioeconomic quintiles at study entryfor the MS cases: ever/never filling a DMD prescription during follow-up,ever/never being hospitalized subsequent to an ED visit, or for the five mostcommon ED diagnoses (data not shown).Over 50% of persons with MS had more than one ED consultation during our nearly6-year observation period; one-quarter visited an ED three or more times. Nearly 20%of ED visits were infection-related; one-third resulted in hospitalization, whereasone-fifth of all-cause ED visits did so. MS cases with ⩾1 (vs without) comorbidityat study entry averaged more ED visits/person/year. Our intentionally descriptivestudy has several limitations. While the overall burden of infection-related EDvisits was considerable in our MS population, this could be higher as diagnoses wereunavailable for one-third of all ED visits. Furthermore, our study lackedMS-specific clinical information, such as relapses, and a comparison to the generalpopulation. Our 1-year pre-study lookback period may have reduced the detection ofcomorbidities. Strengths of our study included the large cohort of MS casesidentified using a validated algorithm within a geographically defined populationwith universal healthcare coverage, including ED visits. Our results suggest thatthe ED visits by MS cases often lead to hospitalizations, perhaps more so forinfection-related visits. Further studies are necessary to better understand theimportance of ED use by persons with MS.Click here for additional data file.Supplemental material, sj-docx-1-msj-10.1177_13524585221078497 for Emergencydepartment use by persons with MS: A population-based descriptive study with afocus on infection-related visits by Jonas Graf, Huah Shin Ng, Feng Zhu, YinshanZhao, José MA Wijnands, Charity Evans, John D Fisk, Ruth Ann Marrie and HelenTremlett in Multiple Sclerosis JournalClick here for additional data file.Supplemental material, sj-docx-2-msj-10.1177_13524585221078497 for Emergencydepartment use by persons with MS: A population-based descriptive study with afocus on infection-related visits by Jonas Graf, Huah Shin Ng, Feng Zhu, YinshanZhao, José MA Wijnands, Charity Evans, John D Fisk, Ruth Ann Marrie and HelenTremlett in Multiple Sclerosis JournalClick here for additional data file.Supplemental material, sj-docx-3-msj-10.1177_13524585221078497 for Emergencydepartment use by persons with MS: A population-based descriptive study with afocus on infection-related visits by Jonas Graf, Huah Shin Ng, Feng Zhu, YinshanZhao, José MA Wijnands, Charity Evans, John D Fisk, Ruth Ann Marrie and HelenTremlett in Multiple Sclerosis Journal


The immunopathogenesis of chronic spontaneous urticaria (CSU) is poorly understood, but recent research suggests that patients can be divided into autoallergic and autoimmune subtypes. Given that not all patients can be controlled with current treatment regimens, including anti-IgE monoclonal antibodies, a better understanding of the immune pathways involved in CSU may enable the repurposing of monoclonal antibodies used for other dermatologic diseases . Therefore, we investigated the implicated immune cells and pathways by reanalyzing publicly available transcriptomic data.2 fold change| ≥1. Pathway analyses were conducted using ToppGene and KEGG. Cell-type enrichment was determined by CIBERSORT and xCell and was correlated with clinical characteristics.Microarray data of CSU and healthy control (HC) skin and blood were obtained from the Gene Expression Omnibus . Differentially expressed genes were defined as a false discovery rate <0.05 and a |logTh2  and Th17-related  pathways were upregulated in lesional compared to non-lesional and HC samples. In non-lesional versus lesional samples, CIBERSORT analysis revealed increased regulatory T-cells (Treg) and resting mast cells. xCell analysis established that Th1 and Th2 scores were not significantly different between lesional and HC samples. However, Th2 scores in both lesional and non-lesional samples correlated positively with disease severity. Few differentially expressed genes and pathways were identified between CSU and HC blood samples.Our results support the involvement of Th2 and Th17-related genes and pathways in CSU. Th2 scores associate with disease severity, which indicates the clinical relevance of these findings. Increased resting mast cell and Treg scores in non-lesional samples may suggest local suppression of wheal formation. Moreover, disease activity seemed to be restricted to the skin as there were limited findings from blood. Larger studies using next-generation sequencing will be helpful to confirm these results. Chronic spontaneous urticaria (CSU) is defined by the presence of wheals and/or angioedema occurring in the absence of specific external stimuli and persisting for ≥ 6 weeks . CSU is There has been a paradigm shift in the understanding of the pathogenesis of CSU and current evidence suggests that most CSU cases have an autoimmune etiology , 7. AutoSeveral studies support the involvement of dysfunction of adaptive cellular immunity in the immune pathogenesis of CSU , 11. Curin silico quantification of various cell-types from transcriptomic data of a heterogeneous cell population. CIBERSORT is one such RNA deconvolution technique that employs linear support vector regression to quantify relative proportions of cell types  (GSE57178) (Transcriptomic data acquired by microarray were obtained from the Gene Expression Omnibus (GEO) . From GiSE72542) , data waSE57178) , data onDifferentially expressed genes (DEGs) were determined using the GEO2R  online tgetGEO function from the GEOquery package . Select DEGs were presented by violin plots.DEG analysis was performed by The McGill Genome Centre, Montreal, Quebec. Datasets were analyzed separately. For each dataset, the normalized expression values were downloaded from the GEO database using the  package , and line  and 100 permutations to estimate the relative proportions of 22 cell-types . Cell abP-values and Q-values less than 0.05 were considered significant. All statistical tests were performed on RStudio version 1.4.1717 and graphs and figures were rendered using the Ggplot2 package , neutrophil degranulation (Q = 1.69E-23), innate immune system (Q = 4.50E-17), cytokine signaling in immune system (Q = 1.82E-14), staphylococcus aureus infection (Q = 2.85E-11), and signaling by interleukins (Q = 3.05E-11). Th2-related pathways including IL-4 and IL-13 mediated signaling (Q = 1.03E-13) and IL-18 signaling (Q = 2.05E-7) were upregulated. Additionally, IL-10 signaling (Q = 8.42E-14), an immunosuppressive pathway, and IL-12 mediated signaling (Q = 3.80E-3), a Th1 polarizing cytokine, were upregulated (Q = 1.04E-3), an activator directly upstream of the Th17 response, as well as IL-17 signaling (Q = 3.60E-6), and IL-6 mediated signaling events (Q = 8.28E-4)  .Q = 4.42E-15), cytokine-receptor interaction (Q = 3.05E-12), and TNF signaling (Q = 4.02E-8) (Q = 3.75E-8) and Th17 cell differentiation (Q = 0.017) (Upregulated KEGG pathways comprise staphylococcus aureus infection (4.02E-8) . In line= 0.017) . Genes u= 0.017) , whereas= 0.017) . IndividIL-4R was upregulated , cytokine signaling in immune system (Q = 1.70E-10), signaling by interleukins (Q = 2.60E-10), neutrophil degranulation (Q = 1.38E-9), IL-4 and IL-13 signaling (Q = 2.15E-9), IL-18 signaling (Q = 1.72E-4), IL-17 signaling (Q = 1.04E-3), IL-23 mediated signaling events (Q = 5.59E-4), IL-6 mediated signaling events (Q = 1.28E-3), and IL-12 mediated signaling events (Q = 2.57E-2). Additionally, the IL-4 mediated signaling events pathway (Q = 2.89E-2) was also upregulated , TNF signaling (Q = 9.20E-8), and staphylococcus aureus infection (Q = 5.06E-7) (Q = 9.20E-8) and Th17 cell differentiation (Q = 0.019) were upregulated  . Moreoveegulated . Upregulegulated  and Th17egulated  pathwaysQ = 0.033), Th17 cell differentiation (Q = 0.027), IL-5 signaling pathway and Th1/Th2 differentiation (Q = 0.027). Similarly, KEGG analysis demonstrated enriched Th1 and Th2 cell differentiation (Q = 0.045) and Th17 cell differentiation (Q = 0.045). These results must be interpreted with caution, however, because HLA-DRB3  was the only upregulated gene involved in each of these pathways.Five genes were upregulated and seven downregulated in the 20 CSU versus 10 HC blood samples. ToppGene pathway analysis of upregulated genes revealed enriched Th1 and Th2 cell differentiation (Q = 0.029) and CD8+ T-cells (Q = 0.0066) were decreased, whereas CD4+ resting memory T-cells (Q = 0.0081) were increased. Eosinophils were only detected in some lesional skin samples, but not statistically significantly greater than in HC samples. No significant differences were observed in B-cells, natural killer (NK) cells, macrophages, DCs, neutrophils, or Tregs.RNA deconvolution of 15 lesional and 12 HC skin samples was performed by CIBERSORT . In lesiQ = 0.020), CD4+ memory T-cells (Q = 0.039), common lymphoid progenitor cells (Q = 0.025), and class switched memory B-cells (Q = 0.015) had increased cell abundance scores in lesional compared to HC samples. No significant differences were observed in Th1 (Q = 0.30) or Th2 (Q = 0.55) cells; however, gamma delta T-cells (Tgd) had elevated cell abundance scores in lesional samples (Q = 0.015). Th2 scores in lesional samples correlated moderately with UAS7 (p = 0.044). Innate immune cells including M1 macrophages (Q = 0.022), mast cells (Q = 0.039), monocytes (Q = 0.015), and neutrophils (Q = 0.0055) had increased scores in lesional samples in contrast to HC samples. Similarly, total dendritic cells (DC) were elevated in lesional versus HC samples (Q = 0.0010), including activated dendritic cells (aDC) (Q = 0.0010), conventional dendritic cells (cDC) (Q = 0.047), immature dendritic cells (iDC) (Q = 0.0050), and plasmacytoid dendritic cells (pDC) (Q = 0.037). Interestingly, neurons (Q = 0.013) were decreased in lesional compared to HC samples. While basophils were detected in both lesional and HC samples, abundance scores were not significantly different.Cell abundance scores determined by xCell were compared between lesional and HC skin samples . CD4+ efQ = 0.039) in non-lesional samples. Interestingly, Tregs (Q = 0.014) and resting mast cells (Q = 0.014) were increased in non-lesional compared to lesional samples. Eosinophils were only detected in some lesional skin samples, but not statistically significantly greater than non-lesional samples. We did not detect any significant differences in B-cells, NK cells, macrophages, DCs, or neutrophils between lesional and non-lesional samples on CIBERSORT.CIBERSORT RNA deconvolution of 15 lesional versus 15 matched non-lesional samples  revealedQ = 0.012). Moreover, Th2 cell abundance scores of non-lesional samples correlated strongly with UAS7 scores (p = 0.0028), whereas Th1 cell abundance scores correlated negatively with UAS7 scores (p = 0.012). Basophils were detected in both groups but were not significantly different.xCell analysis of lesional versus non-lesional skin samples  revealedQ = 0.018) and decreased monocytes (Q = 0.018) in CSU blood compared to HC blood. No eosinophils were detected in either CSU or HC blood and no significant differences were detected in other cell-types. Although neutrophils were not enriched in CSU blood samples compared to HC blood, neutrophil CIBERSORT scores strongly positively correlated with UAS7 scores (p = 0.00099).RNA deconvolution using CIBERSORT of 20 CSU blood samples and 10 HC blood samples  revealedp = 0.007) and Th2 (p = 0.042) cell abundance scores correlated negatively with UAS7 scores. Basophils were only detected in CSU samples but not statistically significantly greater than in HC samples. Moreover, Th2 cells were significantly decreased in ASST+ samples compared to ASST– samples (p = 0.019), but no difference was observed in Th1 cells (p = 0.82).xCell analysis did not detect differences in cell-type abundance scores between CSU and HC blood samples. Among CSU blood samples, Th1 (Q = 0.014) and resting DCs (Q = 0.014) differed on CIBERSORT analysis. However, significant differences were identified in five cell-types by CIBERSORT and 16 cell-types by xCell in HC samples and six cell-types by CIBERSORT and 13 cell-types by xCell in non-lesional samples.The Giménez-Arnau et al.  and PateRecently, the role of Th2 dysregulation has been proposed as a potential driver of CSU pathogenesis in at least a subset of CSU patients , 31. Th2Th2 response is not only important for IgE antibody production, but also stimulates IgG1 complement binding and IgG4 antibodies underlying other autoimmune conditions . InteresIL-10 expression was shown to be increased in CSU lesions and a CSU mouse model overexpressing IL-10 exhibited increased pruritus and increased IL-2, IL-4, and IFN-γ expression, driven by JAK/STAT signaling  or whether it is an insufficient immunosuppressive response.We showed that the IL-4, IL-13, and IL-18 cytokine signaling pathways were upregulated in lesional CSU biopsies versus both HC and non-lesional samples, which suggest a role in the wheal response. Other studies have shown that cytokines that initiate the Type 2 response  , 34 are ignaling . It is uContrary to a previous study reporting increased Th2 cells in CSU lesions , we did IL-6) were also upregulated in lesional samples compared to non-lesional and HC samples. IL-17 and IL-23 have been shown to be elevated in the serum of CSU patients compared to controls and positively correlate with UAS7 scores . A Th1 response is usually associated with ASST positivity , but in In vivo and in vitro evidence indicate a role for Tregs in the suppression of mast cell degranulation via OX40-OX40L signaling  can be found in the article/PL, EN, IL, and CP designed the study. CP, PL, SG, and ML performed the data analysis. CP and SG prepared the figures and tables. EN, PL, IL, MB-S, and AG-A supervised the study. All authors contributed to writing and editing the manuscript.EN was a consultant and speaker for Novartis and has received an investigator-initiated research grant from Novartis. MB-S was a consultant for Novartis. AG-A was a medical advisor for Uriach Pharma, Genentech, Novartis, FAES, GSK, Sanofi–Regeneron, Amgen, Thermo Fisher Scientific, Almirall, she has research grants supported by Uriach Pharma, Novartis, Grants from Instituto Carlos III- FEDER and performs educational activities for Uriach Pharma, Novartis, Genentech, Menarini, LEO-PHARMA, GSK, MSD, Almirall, Sanofi—Regeneron, AVENE. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Globally, a high-salt diet (HSD) has become a threat to human health as it can lead to a high risk of cardiac damage. Although some studies investigating HSD have been carried out, the majority has been conducted in males, and there are few female-specific studies, thereby ignoring any effects of sex-specific damage on the heart. In this study, we determined how HSD induces different pathways of cardiovascular diseases through sex-specific effects on cardiac damage in mice.An HSD murine model of male and female C57BL/6J mice was fed with sodium-rich chow (4% NaCl). After 8 weeks, cardiac tissues were collected, and the whole gene transcriptome of the hearts of male and female mice was characterized and analyzed using high-throughput RNA sequencing. Immunohistochemistry staining was used to further assess the harmful effects of HSD on protein expression of genes associated with immunity, fibrosis, and apoptosis in male and female mice.HSD drastically altered the cardiac transcriptome compared to that of the normal heart in both male and female mice and had a sex-specific effect on the cardiac composition in the transcriptome. HSD produced various differentially expressed genes and affected different KEGG pathways of the transcriptome in male and female mice. Furthermore, we found that HSD induced different pathways of cardiovascular disease in the male mice and female mice. The pathway of hypertrophic cardiomyopathy is significantly enriched in HSD-treated male mice, while the pathway of dilated cardiomyopathy is significantly enriched in HSD-treated female mice. Finally, metabolism, immunity, fibrosis, and apoptosis in the mouse heart showed sex-specific changes predicting cardiac damage.Our results demonstrate that HSD adversely impacts cardiac structure and function by affecting the metabolism, immunity, fibrosis, and apoptosis in the murine heart and induces the mouse to suffer from sex-specific cardiovascular disease. This study provides a new perspective and basis for the differences in the pharmacology and interventional treatment of sex-specific cardiovascular diseases induced by HSD in men and women. High salt content in diet poses various health risks and contributes to the increase in disease prevalence in high-income countries , 2. SaltExisting evidence suggests that a high-salt diet (HSD) is related to cardiovascular disease , 12, chrTo investigate the effect of sex-specific damage of HSD on the structure and function of heart tissues, we generated an HSD murine model by administering male and female C57BL/6J mice with sodium-rich chow containing 4% NaCl. The whole gene transcriptome of the mouse HSD-treated heart was characterized and analyzed by high-throughput RNA sequencing. This study determined that HSD induces cardiac dysfunction and structural damage and possibly cardiovascular disease by inducing changes to metabolism, immune response, fibrosis, and apoptosis in the hearts of male and female mice. Our research may help to reveal the molecular mechanisms of physiological damage caused by HSD to cardiac tissue and is of great significance for the development of therapeutic intervention methods for HSD-induced cardiovascular-related diseases.A schematic of the experimental design is shown in http://www.gempharmatech.com). Before starting the experiment, all mice were placed in a 12-h LD cycle to adapt to the environment for 2 weeks. Male and female mice were fed a normal diet and HSD (4% NaCl) as the normal and high-salt groups, respectively. All experimental protocols were approved by the Institutional Animal Care and Use Committee of Henan Province People's Hospital.Twelve wild-type C57BL/6J male mice and female mice (6–8 weeks) were purchased from GemPharmatech Co., Ltd . Echocardiography of mice anesthetized with isoflurane was performed in M-mode. Fractional shortening (FS), left ventricular (LV) internal dimension at end-diastole (LVIDd), and diastolic left ventricular thickness (LVPWd) were collected.After 8 weeks following a normal diet or HSD, the hearts of mice were rapidly harvested and weighed after death by cervical dislocation. Tissues were immediately immersed in liquid nitrogen, transported, and stored in a freezer set to maintain −80°C.Immunohistochemistry (IHC) analysis was performed on murine heart samples according to a previously published protocol . ParaffiMasson staining of murine hearts was performed according to a previously published study . All carAll cardiac sections from CONMH, MH8W, CONFH, and FH8W groups were placed in xylene I-III  for 15–20 min and then rinsed with 75–100% ethanol  for 5 min and rinsed with distilled water. The cardiac sections were stained with hematoxylin and eosin dye solution from a hematoxylin-eosin (HE) staining Kit . After the slices were dehydrated, they were mounted with neutral gum . Microscopy, image acquisition, and analysis of cardiac sections were performed using an orthotopic light microscope . For quantification of cardiac cell size, 20 400X field images were randomly selected in a double-blind manner and cell numbers in each field were counted by ImageJ software . Average cell size is calculated as the number of cells in the field divided by the area of the field.http://bgitechsolutions.com/sequencing). Frozen mouse heart tissue was broken up using a mortar and pestle to obtain a piece, macroscopically free of fatty infiltration, fibrosis, and blood. RNA was extracted using the RNA Easy Spin Column Kit  following the TRIzol RNA extraction protocol.All RNA extractions were performed by the Beijing Genomic Institute .The RNA library was prepared according to a previously published study  using thpost-hoc test was set as Tykey-Kramer with 0.95, and the effect size was set as Eta-squared. The other parameters were set to default values.Principal component analysis (PCA) was performed using the Statistical Analysis of Metagenomic Profiles (STAMP) software package . PCA washttp://www.genome.jp/kegg) and NCBI RefSeq GCF_000001635.25_GRCm38.p5 as the reference gene set. Pathways with q ≤ 0.05 were defined as significantly enriched in differentially expressed genes (DEGs). The P value formula used in this study is given as follows:Kyoto encyclopedia of genes and genomes pathway annotation was performed using BLASTALL software  against the KEGG database version 81.0  ≤ 0.05, as the threshold.where rrection , with q http://www.geneontology.org) and calculates the number of genes for each term. The hypergeometric test was then applied to determine the significance of the biological functions of the candidate genes in comparison to the different genetic backgrounds of this species. Referring to the software “GO:: TermFinder” , the calculation formula of this analysis is the same as the KEGG enrichment analysis, N is the number of genes with GO annotations, n is the number of candidate genes in N, and M is the number of genes annotated with a specific GO term in all genes. The calculated P-value was determined using the Bonferroni correction, with q  ≤ 0.05 as the threshold. GO terms that met this condition were defined as significantly enriched.The molecular function and biological process of genes were analyzed by Gene Ontology (GO) , 32. Sighttps://string-db.org/, version 11.5) (Protein-protein association networks (PPANs) for fibrosis, metabolism, immunity, and apoptosis were analyzed using STRING (on 11.5) . The netP < 0.05.GraphPad Prism software  was used to generate bar charts and scatter plots. The Venn diagram plotter, a network tool , was used to compare the number of transcripts between the normal and HSD-treated groups. The expression of transcripts in the normal and HSD groups was visualized using the pheatmap package in R . The data were analyzed using the two-way analysis of variance (ANOVA). The data are presented as mean values ± SEM and were considered statistically significant when P = 0.04) as well as a significant main effect of sex (P < 0.001) and HSD (P = 0.004) on body weight. These analyses revealed that the body weight of HSD-treated mice was significantly lower than that of the normal group in both male and female mice (P = 0.002) and sex (P = 0.024), but not sex × HSD interaction (P = 0.067) on ratios of HW/BW (P < 0.001) and sex (P = 0.031), but not sex × HSD interaction (P = 0.082) on FS; (2) a significant main effect of HSD (P = 0.003) and sex (P = 0.034), but not sex × HSD interaction (P = 0.067) on LVIDd; (3) a significant sex × HSD interaction (P = 0.012) as well as a significant main effect of sex (P = 0.044) and HSD (P = 0.006) on LVPWd. To study the effect of HSD on cardiomyocyte size, HE staining was performed. A two-way ANOVA demonstrated a significant sex × HSD interaction (P = 0.037) as well as a significant main effect of HSD (P < 0.001) on cell size. In males, the cell size of cardiomyocytes  demonstrated a significant sex × HSD interaction  and high-salt-treated (MH8W) groups, respectively ; for femQ value <0.05) was compared between the CONMH and MH8W groups, CONFH and FH8W groups, and CONMH and CONFH groups, respectively. As shown in Principal component analysis was used for data visualization to determine transcriptomic differences between the CONMH and MH8W groups, and CONFH and FH8W groups, respectively . The dimTo investigate the effect of excessive sodium intake on the higher expression genes, we compared the difference between the CONMH and MH8W groups, and CONFH and FH8W groups using Venn plots. As shown in P < 0.05) were identified as being unique to the CONMH group and were divided into four categories: (1) cellular processes: tight junction (P = 2.27E-03), focal adhesion (P = 8.22E-03), and lysosome (P = 4.15E-02); (2) environmental information processing: PI3K-akt signaling pathway (P = 2.89E-03), ECM-receptor interaction (P = 9.86E-03), and Rap1 signaling pathway (P = 1.37E-02); (3) human diseases: AGE-RAGE signaling pathway in diabetic complications (P = 2.39E-04), transcriptional mis-regulation in cancer (P = 3.41E-04), human T-cell leukemia virus 1 infection (P = 3.09E-02), and systemic lupus erythematosus (P = 2.85E-02); (4) organismal systems: oxytocin signaling pathway (P = 3.32E-04), complement and coagulation cascades (P = 3.15E-03), estrogen signaling pathway (P = 1.86E-03), platelet activation (P = 4.45E-03), relaxing signaling pathway (P = 5.37E-03), dopaminergic synapse (P = 6.44E-03), protein digestion and absorption (P = 1.34E-02), cholesterol metabolism (P = 1.85E-02), glucagon signaling pathway (P = 2.11E-02), circadian rhythm (P = 2.38E-02), glutamatergic synapse (P = 3.02E-02), cholinergic synapse (P = 2.90E-02), and adrenergic signaling in cardiomyocytes (P = 3.91E-02) (P < 0.05) were identified in the shared CONMH and MH8W groups and were divided into five categories: (1) cellular processes: autophagy-animal (P = 8.05E-10) and endocytosis (P = 1.02E-07); (2) environmental information processing: phosphatidylinositol signaling system (P = 1.46E-09) and TNF signaling pathway (P = 2.18E-08); (3) genetic information processing: ribosome biogenesis in eukaryotes (P = 5.72E-10), ubiquitin mediated proteolysis (P = 2.31E-09), and RNA degradation (P = 6.35E-08); (4) human diseases: herpes simplex virus 1 infection (P = 1.44E-10) and colorectal cancer (P = 1.80E-08); (5) metabolism: inositol phosphate metabolism (P = 8.35E-09) (P < 0.05) were identified as being unique to the MH8W group and were divided into four categories: (1) environmental information processing: ECM-receptor interaction (P = 1.09E-06), PI3K-Akt signaling pathway (P = 5.40E-04), and WNT signaling pathway (P = 3.63E-03); (2) human diseases: arrhythmogenic right ventricular cardiomyopathy  and dilated cardiomyopathy ; (3) metabolism: tyrosine metabolism (P = 3.96E-03), phenylalanine metabolism (P = 1.07E-02), histidine metabolism (P = 1.25E-02), and glycolysis/gluconeogenesis (P = 1.31E-02); (4) organismal systems: regulation of lipolysis in adipocytes (P = 5.40E-03)  . A total.35E-09) . While 1.40E-03) .P < 0.01) were identified as being unique to the CONFH group and were divided into three categories: (1) environmental information processing: AMPK signaling pathway (P = 8.81E-04), TNF signaling pathway (P = 2.13E-03), PI3K-Akt signaling pathway (P = 4.27E-03), and cytokine-cytokine receptor interaction (P = 7.40E-03); (2) human diseases: transcriptional mis-regulation in cancer (P = 2.66E-05), rheumatoid arthritis (P = 4.23E-04), hypertrophic cardiomyopathy , acute myeloid leukemia (P = 5.06E-03), measles (P = 7.51E-03), and systemic lupus erythematosus (P = 7.51E-03); (3) organismal systems: IL-17 signaling pathway (P = 3.24E-03), chemokine signaling pathway (P = 4.18E-03), intestinal immune network for IgA production (P = 4.33E-03), and adipocytokine signaling pathway (P = 5.38E-03) (P < 0.001) were identified in the shared CONFH and FH8W groups and were divided into six categories: (1) cellular processes: autophagy-animal (P = 1.33E-08), endocytosis (P = 1.63E-05), cell cycle (P = 1.69E-05), adherens junction (P = 8.86E-05), lysosome (P = 1.17E-04), apoptosis (P = 1.34E-04), signaling pathways regulating pluripotency of stem cells (P = 6.37E-04), and apoptosis-fly (P = 9.50E-04); (2) environmental information processing: phosphatidylinositol signaling system (P = 6.48E-08), TNF signaling pathway (P = 1.84E-07), notch signaling pathway (P = 2.33E-07), MAPK signaling pathway (P = 4.83E-07), ERBB signaling pathway (P = 5.01E-07), WNT signaling pathway (P = 2.14E-06), hippo signaling pathway-fly (P = 4.95E-05), RAS signaling pathway (P = 5.79E-05), rap1 signaling pathway (P = 7.87E-05), mTOR signaling pathway (P = 1.29E-04), NF-kappa B signaling pathway (P = 7.18E-04), and hippo signaling pathway-multiple species (P = 3.40E-10); (3) genetic information processing: ribosome biogenesis in eukaryotes (P = 6.93E-05), ubiquitin mediated proteolysis (P = 2.04E-04), RNA degradation (P = 2.59E-04), DNA replication (P = 3.89E-04), basal transcription factors (P = 4.25E-04), nucleotide excision repair (P = 4.46E-04), RNA transport (P = 9.61E-04), mismatch repair (P = 2.88E-06), non-homologous end-joining (P = 1.32E-05), base excision repair (P = 9.84E-05), spliceosome (P = 4.92E-04), Fanconi anemia pathway (P = 6.30E-04), and aminoacyl-tRNA biosynthesis (P = 8.04E-04); (4) human diseases: herpes simplex virus 1 infection (P = 3.40E-10), microRNAs in cancer (P = 7.55E-09), pathways in cancer (P = 1.32E-07), colorectal cancer (P = 6.54E-07), pancreatic cancer (P = 6.45E-06), hepatitis B (P = 1.19E-05), endocrine resistance (P = 1.93E-05), breast cancer (P = 6.12E-05), chronic myeloid leukemia (P = 1.23E-04), small cell lung cancer (P = 1.70E-04), prostate cancer (P = 1.95E-04), endometrial cancer (P = 1.96E-04), hepatocellular carcinoma (P = 2.80E-04), insulin resistance (P = 3.82E-04), AGE-RAGE signaling pathway in diabetic complications (P = 3.82E-04), non-small cell lung cancer (P = 4.08E-04), human papillomavirus infection (P = 5.64E-04), and choline metabolism in cancer (P = 6.17E-04); (5) metabolism: N-Glycan biosynthesis (P = 1.49E-08), inositol phosphate metabolism (P = 1.07E-07), pyrimidine metabolism (P = 2.00E-06), lysine degradation (P = 1.27E-05), terpenoid backbone biosynthesis (P = 5.54E-05), glycosylphosphatidylinositol (GPI)-anchor biosynthesis (P = 6.93E-05), one carbon pool by folate (P = 2.04E-04), purine metabolism (P = 2.59E-04), amino sugar and nucleotide sugar metabolism (P = 3.89E-04), other types of O-glycan biosynthesis (P = 4.25E-04), other glycan degradation (P = 4.46E-04), and seleno-compound metabolism (P = 9.61E-04); (6) organismal systems: axon guidance (P = 2.88E-06), FC gamma R-mediated phagocytosis (P = 1.32E-05), thyroid hormone signaling pathway (P = 9.84E-05), chemokine signaling pathway (P = 4.92E-04), B cell receptor signaling pathway (P = 6.30E-04), osteoclast differentiation (P = 8.04E-04) (P < 0.01) were identified as being unique to the FH8W group and were divided into five categories: (1) cellular processes: gap junction (P = 5.33E-06) and focal adhesion (P = 4.93E-05); (2) environmental information processing: ECM-receptor interaction (P = 6.80E-06), Rap1 signaling pathway (P = 3.88E-05), PI3K-Akt signaling pathway (P = 7.46E-05), calcium signaling pathway (P = 3.39E-03), MAPK signaling pathway (P = 4.49E-03), and WNT signaling pathway (P = 6.38E-03); (3) human diseases: melanoma (P = 4.34E-03), hypertrophic cardiomyopathy , dilated cardiomyopathy , herpes simplex virus 1 infection (P = 6.02E-03), and arrhythmogenic right ventricular cardiomyopathy ; (4) metabolism: tyrosine metabolism (P = 5.33E-03); (5) organismal systems: parathyroid hormone synthesis, secretion and action (P = 2.29E-04), platelet activation (P = 2.29E-04), relaxing signaling pathway (P = 3.79E-03), oxytocin signaling pathway (P = 4.36E-03), thyroid hormone signaling pathway (P = 6.22E-03), and circadian entrainment (P = 6.84E-03)  . A total.04E-04) . While 2.84E-03) .P < 0.01) were identified as being unique to the CONMH group and were divided into four categories: (1) cellular processes: endocytosis (P = 7.91E-03); (2) environmental information processing: calcium signaling pathway (P = 9.34E-03); (3) human diseases: hepatocellular carcinoma (P = 1.23E-03), pancreatic cancer (P = 6.12E-03), and human papillomavirus infection (P = 8.82E-03); (4) organismal systems: vitamin digestion and absorption (P = 5.66E-03), cholesterol metabolism (P = 6.60E-03), and oxytocin signaling pathway (P = 9.12E-03)  were identified as being unique to the CONFH group and were divided into three categories: (1) environmental information processing: PI3K-Akt signaling pathway (P = 8.93E-04), cytokine-cytokine receptor interaction (P = 5.96E-03), and WNT signaling pathway (P = 9.59E-03); (2) human diseases: transcriptional mis-regulation in cancer (P = 6.20E-04), rheumatoid arthritis (P = 2.92E-03), herpes simplex virus 1 infection (P = 7.40E-03), Kaposi sarcoma-associated herpesvirus infection (P = 8.08E-03), and microRNAs in cancer (P = 9.96E-03); (3) organismal systems: IL-17 signaling pathway (P = 8.99E-04), B cell receptor signaling pathway (P = 1.67E-03), osteoclast differentiation (P = 6.27E-03), and axon guidance (P = 6.74E-03)  . Top 10 .12E-03) , which e.74E-03) . AltogetQ = 3.17E-22), dilated cardiomyopathy , arrhythmogenic right ventricular cardiomyopathy , fluid shear stress and atherosclerosis (Q = 1.37E-12), and viral myocarditis (Q = 1.65E-03) (Q = 1.43E-07), peptide antigen binding (Q = 1.91E-05), beta-2-microglobulin binding (Q = 3.35E-05), signaling receptor binding (Q = 5.43E-05), integrin binding (Q = 5.43E-05), T cell receptor binding (Q = 5.43E-05), CX3C chemokine binding (Q = 3.67E-04), metal ion binding (Q = 3.67E-04), neuregulin binding (Q = 4.95E-04), protein-containing complex binding (Q = 6.58E-04), and TAP binding (Q = 9.87E-04); (2) transporter activity, voltage-gated calcium channel activity (Q = 1.91E-05). As shown in Q = 2.31E-06), cell adhesion (Q = 2.33E-05), heterotypic cell-cell adhesion (Q = 3.57E-04), endocardial cushion fusion (Q = 4.71E-04), integrin-mediated signaling pathway (Q = 2.31E-06), positive regulation of T cell mediated cytotoxicity (Q = 7.00E-05), positive regulation of cell migration (Q = 1.10E-04), and positive regulation of epithelial to mesenchymal transition involved in endocardial cushion formation (Q = 6.21E-04); (2) cellular process: mesodermal cell differentiation (Q = 4.31E-05), cell-cell adhesion in response to extracellular stimulus (Q = 1.15E-04), endodermal cell differentiation (Q = 3.76E-04), positive regulation of vascular smooth muscle cell proliferation (Q = 6.21E-04), and cellular response to amyloid-beta (Q = 7.42E-04); (3) developmental process: heart development (Q = 2.31E-06), inner ear development (Q = 2.44E-04), ventricular cardiac muscle tissue morphogenesis (Q = 4.41E-04), and atrial septum primum morphogenesis (Q = 6.21E-04); (4) immune system process: antigen processing and presentation of peptide antigen via MHC class I (Q = 2.33E-05), antigen processing and presentation of endogenous peptide antigen via MHC class Ib (Q = 2.33E-05), antigen processing and presentation of endogenous peptide antigen via MHC class I via ER pathway, TAP-independent (Q = 2.33E-05), and antigen processing and presentation of endogenous peptide antigen via MHC class I via ER pathway, TAP-dependent (Q = 6.21E-04); (5) localization: calcium ion transmembrane transport (Q = 8.76E-05) and cell migration (Q = 1.15E-04); (6) response to stimulus: response to drug (Q = 4.71E-04) and response to hypoxia (Q = 4.81E-04).Evidence from clinical trials indicates that excessive sodium intake is associated with cardiovascular disease , 39. To .65E-03) . The KEGQ = 1.77E-14), ARVC (Q = 9.55E-12), HCM (Q = 3.03E-11), fluid shear stress and atherosclerosis (Q = 1.25E-06), and viral myocarditis (Q = 2.08E-05) , RNA polymerase II activating transcription factor binding (Q = 1.20E-03), transcription factor binding (Q = 1.63E-03), histone methyltransferase binding (Q = 1.63E-03), metal ion binding , R-SMAD binding (Q = 4.48E-03), integrin binding , laminin binding (Q = 5.07E-03), disordered domain-specific binding (Q = 7.41E-03), peptide antigen binding , and protein binding (Q = 8.44E-03); (2) transporter activity: calcium- and calmodulin-responsive adenylate cyclase activity (Q = 6.81E-04), adenylate cyclase activity (Q = 1.63E-03), and phosphorus-oxygen lyase activity (Q = 4.26E-03). As shown in Q value 2.03E-04 vs. 2.33E-05), cell-matrix adhesion , and integrin-mediated signaling pathway ; (2) cellular process: cellular response to cadmium ion (Q = 4.43E-04) and cellular response to reactive oxygen species (Q = 5.75E-04); (3) immune system process: antigen processing and presentation of peptide or polysaccharide antigen via MHC class II (Q = 5.79E-06), antigen processing and presentation of exogenous peptide antigen via MHC class II (Q = 5.24E-05), antigen processing and presentation of peptide antigen (Q = 4.47E-04), and antigen processing and presentation (Q = 6.03E-04); (4) response to stimulus: response to drug . Collectively, these results demonstrate that excessive sodium intake can easily induce cardiovascular disease.To further elucidate the effect of excessive sodium intake, we next compared the expression of cardiovascular disease-related transcripts between normal and high-salt-treated hearts in female mice. As shown in .08E-05) . KEGG an.08E-05) . GO analQ < 0.05)  . As show < 0.05) , S5 and  < 0.05) .F = 9.958; P = 0.002) as well as a significant main effect of HSD , but not sex × HSD interaction . As shown in P < 0.05). Further studies have found that fibrotic changes caused by HSD in the heart of female mice were approximately twice that of male mice (1.75 vs. 2.74%)  . CollectQ < 0.05). Similarly, the HSD had an adverse effect on the expression of 35 metabolism-related genes with significant differences in female mice, causing a serious disorder (Q < 0.05) (P < 0.001) were identified, in six categories: (1) amino acid metabolism: valine, leucine, and isoleucine degradation (Q = 9.10E-07) and glycine, serine, and threonine metabolism (Q = 6.04E-04); (2) carbohydrate metabolism: pyruvate metabolism (Q = 4.56E-06), glycolysis/gluconeogenesis (Q = 2.74E-05), propanoate metabolism (Q = 2.25E-04), fructose and mannose metabolism (Q = 3.04E-04), and butanoate metabolism (Q = 8.03E-04); (3) energy metabolism: biosynthesis of unsaturated fatty acids (Q = 1.56E-05); (4) global and overview maps: oxidative phosphorylation (Q = 1.45E-15), fatty acid metabolism (Q = 1.70E-09), and carbon metabolism (Q = 3.65E-06); (5) lipid metabolism: biosynthesis of amino acids (Q = 5.97E-04) and glycerolipid metabolism (Q = 8.03E-04); (6) metabolism of cofactors and vitamins: porphyrin and chlorophyll metabolism (Q = 7.80E-06) and ubiquinone and other terpenoid-quinone biosynthesis (Q = 1.03E-05) (P < 0.05) were identified, in seven categories: (1) amino acid metabolism: arginine and proline metabolism (Q = 2.31E-02) and lysine degradation (Q = 2.83E-02); (2) biosynthesis of other secondary metabolites: neomycin, kanamycin and gentamicin biosynthesis (Q = 3.27E-02); (3) carbohydrate metabolism: glycolysis/gluconeogenesis ; (4) energy metabolism: sulfur metabolism (Q = 4.88E-02); (5) lipid metabolism: ether lipid metabolism (Q = 2.14E-02), glycerolipid metabolism (Q = 2.83E-02), steroid hormone biosynthesis (Q = 4.18E-02), arachidonic acid metabolism (Q = 4.18E-02), and glycerophospholipid metabolism (Q = 4.31E-02); (6) metabolism of terpenoids and polyketides: insect hormone biosynthesis (Q = 2.60E-02); (7) nucleotide metabolism: purine metabolism (Q = 1.84E-02)  . To furt.03E-05) . For fem.84E-02) . The STR.84E-02) , but not.84E-02) . AltogetP = 0.198), and macrophage infiltration was increased by HSD treatment in the hearts of male and female mice . The STRING database was used to visualize the PPANs of these transcripts to further study the function and relevance of these immune-related genes. As shown in Q < 0.001)  . Collectvia the cytochrome C release pathway (Q < 0.05). As shown in Q = 5.43E-16) and activation of cysteine-type endopeptidase activity involved in the apoptotic process (Q = 2.60E-03) of biological process in male and female mice were identified (P = 0.032). The HSD significantly increased the expression of cleaved caspase-3 in the hearts of both male and female mice. Collectively, these results demonstrated that excessive sodium intake can induce cardiac apoptosis.Studies have shown that a prenatal HSD can induce apoptosis of cardiomyocytes in the heart of offspring mice  pathway  and can  pathway . In thisentified . To furtThe meaningful finding of this study is that HSD can adversely affect the mouse heart by changing metabolism, immunity, fibrosis, and apoptosis and can induce mice to suffer from sex-specific cardiovascular disease. The conclusions of this study are mainly based on the following findings: (1) HSD has a sex-specific effect on the body mass of mice, especially on the mass of heart tissue; (2) the cardiac transcriptome is different in male and female mice; (3) the HSD-treated cardiac transcriptome showed sex-specific differences; (4) compared with the normal group, HSD produced a different number of DEGs and affects different KEGG pathways in male and female mice; (5) HSD affects the expression of genes related to fibrosis, metabolism, immunity, and apoptosis in heart tissue of male and female mice; (6) KEGG pathway enrichment analysis showed that HSD induced HCM in male mice, while HSD induced DCM in female mice. These data help us understand the negative effects of HSD on the heart in different sexes.db/db mice show higher levels of pro-inflammatory cytokines and more immune cell infiltration in the kidneys than female db/db mice after HSD treatment for 4 weeks  can be found in the article/The animal study was reviewed and approved by Henan Province People's Hospital Institutional Animal Care and Use Committee.SH, XC, and HW: conceptualization, funding, resources, and supervision. SH and XC: methodology, investigation, analysis, visualization, and writing—review and editing. All authors contributed to the article and approved the submitted version.Research support was provided by the National Natural Science Foundation of China (Grant Number 82101089 to SH), Natural Science Foundation of Henan Province (Grant Number 222300420361 to XC), the Key R&D and Promotion Special Program of Henan Province (Grant Numbers 212102311011 and 222102310120 to SH and 212102310477 to HW), the Henan Provincial Medical Science and Technology Research Joint Co-construction Project (Grant Numbers LHGJ20200064 to SH and SB201901087 to HW), the Basic Science Project for Youth of Henan Eye Institute/Henan Eye Hospital (Grant Number 20JCQN003 to SH), and the Doctoral Research and Development Foundation of Henan Provincial People's Hospital (Grant Numbers ZC20190146 to SH and ZC20200230 to XC).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Mycobacterium smegmatis mc2155 as a host. The genome of this temperate siphovirus is 75,632 bp long , and BLASTn alignment revealed 99.86% identity with the genome of L3 mycobacteriophage Samty.Subcluster L3 bacteriophage Finnry was isolated from soil collected in Charleston, South Carolina, using  Mycobacterium smegmatis mc2155 using enrichment at 37°C followed by two purification/amplification cycles in 7H9 top agar, as described in the SEA-PHAGES Discovery Guide  Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) program  studied ry Guide . Althougile tail .TCGATCAGCC) were identified using PAUSE (https://cpt.tamu.edu/computer-resources/pause).To extract genomic DNA from high-titer lysates, the Promega Wizard DNA cleanup system was used, and a DNA library was prepared with the NEBNext Ultra II DNA library prep kit. Pittsburgh Bacteriophage Institute sequenced Finnry on an Illumina MiSeq system (MiSeq reagent kit v3) , and 771https://phagesdb.org/DNAMaster). Programs utilized to identify putative genes included GLIMMER v3.02 (https://seaphages.org/forums/topic/5398). Default parameters were used for other software.Annotation was performed with the PECAAN  workflowER v3.02 , PhameraER v3.02 , GeneMarER v3.02 , StarterER v3.02 , ARAGORNER v3.02 , and tRNER v3.02 . FunctioER v3.02 , HHpred ER v3.02 , and theER v3.02  (parametFinnry’s genome contains 130 predicted protein-coding genes (51 with assigned putative functions), 9 tRNAs, and no transfer-messenger RNAs. Potential gene duplications include tandem duplication of the WhiB family transcription factor sequences gp79/gp80 (BLASTp indicated 37.66% identity and 79% query coverage) and displaced duplication of gp121/gp131 (BLASTp indicated 42.59% identity and 93% query coverage).−50) between Finnry and related actinobacteriophages, Phamerator was used  –20. To c–was used . Finnry’was used , 2 phamsGCS scores  and wholThe GenBank and SRA accession numbers for Finnry are presented in


This article has been corrected: Due to errors in figure preparation, the AZ-treated (72 hr) images , is an accidental duplicate of the ‘CTRL’ image in row 3, panel 1 of 1470-1489. https://doi.org/10.18632/oncotarget.28011Original article: Oncotarget. 2021; 12:1470–1489.