Hepatitis C virus (HCV) is a risk factor that leads to hepatocellular carcinoma (HCC) development. Epigenetic changes are known to play an important role in the molecular genetic mechanisms of virus-induced oncogenesis. Aberrant DNA methylation is a mediator of epigenetic changes that are closely associated with the HCC pathogenesis and considered a biomarker for its early diagnosis. The ANDSystem software package was used to reconstruct and evaluate the statistical significance of the pathways HCV could potentially use to regulate 32 hypermethylated genes in HCC, including both oncosuppressor and protumorigenic ones identified by genome-wide analysis of DNA methylation. The reconstructed pathways included those affecting protein-protein interactions (PPI), gene expression, proteinactivity, stability, and transport regulations, the expression regulation pathways being statistically significant. It hasbeen shown that 8 out of 10 HCV proteins were involved in these pathways, the HCV NS3 protein being implicatedin the largest number of regulatory pathways. NS3 was associated with the regulation of 5 tumor-suppressor genes,which may be the evidence of its central role in HCC pathogenesis. Analysis of the reconstructed pathways has demonstratedthat following the transcription factor inhibition caused by binding to viral proteins, the expression of a numberof oncosuppressors  was suppressed, while the expression of others  was activated. Thus, the performed gene-network reconstruction has shown that HCV proteins can influencenot only the methylation status of oncosuppressor genes, but also their transcriptional regulation. The results obtainedcan be used in the search for pharmacological targets to develop new drugs against HCV-induced HCC. Liver cancer is the third leading cause of cancer-relateddeath in the world according to year 2020 statistics with over900,000 new cases of this pathology registered the sameyear around the world . Hepatocellularcarcinoma (HCC) has been the dominant type of primaryliver cancer, comprising about 90 % of all the cases . It may be caused by several risk factors suchas aflatoxin exposure, alcohol consumption; hepatitis B orC (HCV) virus infection, liver cirrhosis, non-alcoholic fattyliver disease, non-alcoholic steatohepatitis, metabolic syndrome,obesity, type II diabetes, and genetic predisposition.Currently, a lot of data has been accumulated on HCVassociation with impaired liver function, cirrhosis and HCCdevelopment . Having gotten into a humanbody, HCV seeks to exercise control over the biologicalprocesses occurring in host cells in order to increase its survivaland replication efficiency. In more than 70 % of thoseinitially infected, the disease takes on a chronic course, so thepatients experience progressive liver-tissue fibrosis and cirrhosisaccompanied by long-term inflammation . Using various mechanisms for infected cell cooptation,the virus can inadvertently lead to HCC development. At the same time, the molecular andgenetic mechanisms of virus-induced carcinogenesis remainunderstudied.In addition, HCC pathogenesis is associated with epigeneticmodifications and aberrant DNA methylation being a mediatorof epigenetic changes  thatcan serve as a biomarker for early HCC diagnosis .To establish the functional links between genes and to elucidatethe molecular mechanisms of biological processes, themethods for gene networks reconstruction have been widelyemployed. Previously, we developed the Associative NetworkDiscovery System (ANDSystem) software package designedto reconstruct gene networks based on the knowledge extractedfrom factual databases and scientific publications usingtext-mining techniques . The package has enabled one toreconstruct the molecular mechanisms of a number of pathologiessuch as preeclampsia , tuberculosis, comorbid conditions of asthma andhypertension , COVID-19 , HCV life cycle , etc.In the present study, ANDSystem was employed to reconstructthe regulatory pathways describing the potentialregulation mechanisms of the genes hypermethylated in HCCby HCV proteins. The analysis looked at the 32 genes knownto be hypermethylated HCC markers. Among the 7 types ofreconstructed regulatory pathways including protein-proteininteractions (PPI), gene expression, protein activity, stabilityand transport regulations, those responsible for gene expressionregulation turned out to be statistically significant. Ninemarker genes were identified that could potentially be subjectto regulation by HCV proteins, including three HCC suppressorgenes  that could be negativelyregulated and one apoptosis suppressor gene (TERT ) that canbe positively regulated.Genes hypermethylated in HCC. Information about thehypermethylated genes was taken from publications (Table 1).Only those genes were considered whose hypermethylationwas associated with HCC and confirmed through the analysisand meta-analysis given in the publications. The schematic ofthe data-processing algorithm can be seen in Figure 1.Regulatory pathways reconstruction in ANDSystem.The regulatory pathways were reconstructed using the ANDSystemsoftware package  thathad been designed to perform gene-networks reconstructionbased on automated analysis of scientific texts and factualdatabases. ANDSystem includes a knowledge base with morethan 40 million facts about molecular-genetic interactions,containing physical intermolecular interactions, gene expression,protein activity, stability and transport regulations. In thepackage, it is the the ANDVisio program that reconstructs andanalyzes gene networks using the Pathway Wizard functionperforming search calls to the knowledge base according toa given pattern. A schematic description of the used patternsis given in Table 2For instance, P4 means searching for all possible moleculargenetic pathways in the ANDSystem knowledge base thatsatisfy the following requirement: the first participant inthe pathway is the viral protein (Vp); the second is humanprotein (Hp); the third is a human gene from a list of target genes (Tg); the last member of the pathway is a Tg-encodedprotein (Tp). Further in the text, HCC marker genes will beregarded as target ones. Interactions between pathway participantsare represented by the following types: Vp and Hpare linked by PPIs; Hp and Tg are “expression regulation”interaction type (Exp reg), where Hp regulates Tg gene expression;Tg and Tp are interaction of the “expression” interactiontype (Exp), i. e., the Tp protein is the expression product ofthe Tg gene. Examples of regulatory pathway reconstructionin ANDSystem using the patterns presented in the previouswork .Estimating the statistical significance of pathways. Thepattens from Table 2 were used to calculate the number ofmarker genes K participating in the regulatory pathways,as well as the number of such participants in the sample ofcontrol gene. The likelihood of observing the number K forrandom reasons was estimated using the standard hypergeometricdistribution and the hypergeom function from the SciPy 1.8.0 package (https://scipy.org). For the purposes ofstatistical processing, a group of genes proposed by Hoshidaet al. (2008) as a control to predict HCC outcomes based onthe expression level of genes was takenReconstruction of the potential regulatory pathwaysHCV proteins use to affect HCC marker genesA set of hypermethylated HCC marker genes was used toreconstruct the potential regulatory pathways through whichviral proteins could modulate the genes playing an importantrole in HCC pathogenesis (see Table 1). The set had beenbased on the published results of a genome-wide analysis ofDNA methylation and included 30 genes, the expression ofwhich, according to the studies, was reduced in hepatocellularcarcinoma, and two genes (WT1 and TERT ) with increasedexpressionTo reconstruct the regulatory pathways, the ANDSystemsoftware package was used. The search queries to the knowledgebase were formed using the pathway patterns presentedin Table 2. The patterns described different types of regulatorypathways determined by different combinations of moleculargeneticinteractions, including PPIs, gene expression, proteinactivity, stability, and transport regulationsAnalysis of the statistical significance of the pathwaysautomatically reconstructed by ANDSystem according to thegiven patterns showed that among the seven types of regulatorypathways analyzed, expression regulation ones turnedout to be statistically significant (P4 in Table 3). This patterndescribes the pathways including four participants: (1) viralproteins; (2) human transcription factors (TF) involved in PPIswith viral proteins; (3) marker genes presented in Table 1,whose expression is regulated by (2); (4) protein products ofmarker genes.The gene network describing the regulation pathways ofHCC marker genes included 8 HCV proteins, 7 intermediatehost proteins involved in PPIs with HCV proteins, and 9 genes whose aberrant expression correlated withHCC progression .Analysis of the regulatory pathwaysThe regulatory pathways involved 8 out of 10 HCV proteinsand 6 human genes, which protein products acting as the intermediateparticipants the viral proteins could form proteinheterocomplexes with. The latter included such genes oftranscription factors as STAT3 , NR4A1 (Nuclear receptor subfamily 4group A member 1), JUN (c-Jun/activator protein 1), BCL6(B-cell lymphoma 6 protein), transmembrane receptor NOTC1(Neurogenic locus notch homolog protein 1) and histonemethyltransferase SMYD3 (Lysine methyltransferase SETand MYND domain containing protein 3).Most of the viral proteins were associated with RUNX3 andWT1 regulation. Six of them  interacted with NR4A1 being a general expressionregulator of these two HCC marker genes.HCV protein NS3 (p70) interacted with the largest numberof expression regulators, and through these interactions itcould potentially regulate the expression of five tumor suppressorgenes and that of TERT.Now, let us consider the possibilities of implementing ofthese regulatory pathways in more detail.p8, p21, p68, gp32, p23, NS1/NR4A1/RUNX3, WT1. Thisregulatory pathway suggests six HCV proteins  can possibly affect HCC development by controllingthe activity of the RUNX3 and WT1 genes through theNR4A1 transcription factor. Indeed, NR4A1 directly interactswith the RUNX3 and WT1 promoters, suppressing RUNX3activity and activating that of WT1 . Both factors are involved in apoptosis regulation,hence, RUNX3 promotes activation of the extrinsic,TRAIL-induced apoptosis pathway , whileWT1 controls the mitochondrial  apoptosis pathwaythrough the regulation of the Bcl-2 anti-apoptotic proteingene, and, depending on a cell type, affects the expressionof the Bcl-2 gene in both positive and negative ways . It has been shown that in HCC, anincreased expression of the WT1 gene is observed, which isdue to hypermethylation of its promoter and correlates witha poor prognosis . Thesedata suggest that the role WT1 plays in HCC progression isassociated with blocked apoptosis.Experiments have demonstrated that HCV core proteininhibits at least the NR4A1 and RUNX3 genes expression ininfected cells , contributing to suppressing anexternal apoptosis pathway. The Y2H test (Two Hybrid Test)has shown NR4A1 can interact with such viral proteins asCORE, E1, E2, NS2, NS4A, and NS5B , but except for CORE, the effects of the other HCVproteins on TF activity have not been investigated yet.E1, NS3, Core, p23, NS1, p68/JUN, NOTC1, STAT3/TERT. Aberrant expression of the TERT gene, associated,among other things, with hypermethylation of its promoter, isa prognostic marker of HCC . TERT affects diseaseprogression through stimulation of cell proliferation due toreactivation of its gene expression in carcinoma cells . TERT activity has beenshown to also increase in HCV-infected cells, partly throughdirect interaction of the core protein with the enzyme , however, in general, the mechanisms HCVproteins affect TERT activity are not clear. This regulatorypathway suggests the involvement of the virus NS3, Core,E1, p23, NS1, and NS5B proteins in TERT gene expressionthrough interaction with the JUN (AP-1), STAT3, and NOTC1proteinsIndeed, experiments have shown that there is a possibilityto affect TERT expression through the AP-1 and STAT3 TFs being its direct regulators , as well as through the NOTC1 signaling pathway. Moreover, it has been demonstratedthat the HCV NS3 protein affects NOTC1 activity throughthe SRCAP transcription factor  and theexpression of AP1- and STAT3-regulated genes , however,the specific mechanisms of realization of these influences ininfected hepatocyte cells have not been practically examined.gp32, p70/JUN/WIF1. This regulatory pathway describesthe effect the NS3 and E1 HCV proteins have on WIF1 (Wntinhibitory factor 1) gene expression through interaction withthe c-Jun/AP-1 TF. WIF1 is a tumor suppressor that reducescell growth in HCC , and its expressionlevel is a prognostic indicator of the course of the disease.Experiments have demonstrated that there is both the possibilityof a direct effect of the NS3 and E1 proteins on theactivity of c-Jun/AP-1 , and the lattercan affect the expression of the WIF1 gene through interactionwith the DNMT1 methyltransferase (DNA methyltransferase1), suppressing WIF1 in gallbladder cancer cells . But what mechanisms of WIF1 gene suppressionare initiated in HCV-infected hepatocarcinoma cells remainsunknown.p70/STAT3/MGMT, DAPK1, SOCS1. This regulatorypathway is initiated by NS3 (p70) affecting the activity of theMGMT, SOCS, and DAPK1 genes through interaction withthe STAT3 TF. Proteins DAPK1 (Death-associated proteinkinase 1), MGMT (Methylated-DNA-protein-cysteine methyltransferase),and SOCS1 are considered tumor suppressors, and their low expressionin carcinomas correlates with disease progression .Experiments have demonstrated that NS3 can directly interactwith the STAT3 TF  involvedin the regulation of the expression of the abovementionedgenes , however, the effect of STAT3on MGMT, SOCS, and DAPK1 expression is not unambiguousand may be associated with cell specialization. As forthe mechanisms regulating the expression of these genes inHCV-infected hepatocarcinoma cells, they have not beenstudied yet.p70/BCL6/TP53. TP53 is a key activator of intrinsic apoptosispathway. The NS3 (p70) protein affects TP53 throughinteraction with the BCL6 (B-cell lymphoma 6 protein) TF.TP53 is a HCC marker gene of and its low expression correlateswith poor disease prognosis . BCL6 represses the TP53 gene in lymphoid cells,and its constitutive expression protects B lymphocytes fromDNA damage-induced apoptosis . However, the data describing the effectof HCV has on TP53 and BCL6 expression in these cells areassociated with a possible mutation induction and are mutuallyexclusive . Theinteraction of NS3 and BCL6 is discussed in ,but the specific mechanisms NS3 affects the TF activity havenot been studied yet.The studied set of hypermethylated HCC marker genes (seeTable 1) included 30 downexpressed and two over-expressedgenes. Using ANDSystem, the regulatory pathways by whichHCV proteins are able to influence the expression of thesemarker genes were reconstructed. The relationship betweenthe pathways and HCC-associated key biological processes isshown in Figure 3. According to the published data, the WT1,RUNX3, TP53, and SOCS1 genes are closely associated withapoptosis ,while the MGMT, TERT, RASSF1A, and WIF1 genes – withapoptosis and cell proliferation .The analysis showed the identified pathways could potentiallybe a part of the mechanism HCV proteins affect the activityof HCC marker genes. However, the effects the proteinshave on the function of human regulatory proteins during PPIformation are currently poorly understood. This fact preventsus from unambiguous interpretation of the reconstructedpathways, because what determines if a regulatory pathwayfunctions as an activator or suppressor of target gene expressionis whether or not the ability to regulate gene expressionremains in the host regulatory protein after its interaction withthe viral protein. Investigation of these effects requires furtherexperimental studies and computer molecular modeling.The literature describes the effects viral proteins can have onthe function of host proteins, e. g., the NS5A protein is knownto bind to SMYD3 in the cytoplasm and inhibit SMYD3 translocationto the nucleus . If the regulatoryproteins of a host organism are assumed to lose their ability toregulate gene expression due to the complexes formed withviral proteins, then the following effects can be expected:when considering the pathways regulating onco-suppressorexpression, four of the seven pathways inhibiting RASF1,RUNX3, WIF1, and DAPK1 will be suppressed, which canlead to their activation by HCV proteins, and that, in turn, willprevent carcinogenesis. In the remaining three pathways, theactivation of MGMT, SOCS1 and TP53 will be suppressed,which may possibly have a protumor effect. In the presentedpathways , WT1, MGMT, SOCS1 and TP53 areactivated by the corresponding factors ,while the expression of RASF1, RUNX3, WIF1, and DAPK1genes is negatively controlled .In the case of the TERT and WT1 genes that can be attributedto those with protumor activity, suppression of theWT1 gene can be expected and will lead to a negative effecton carcinogenesis. As for the TERT gene involved in apoptosissuppression and stimulating cell proliferation , according to our results , this gene was controlled through three different regulatorypathways. Its expression was activated by two pathwaysinvolving the STAT3 and NOTC1 host genes , and one of the pathwayssuppressed the expression involving c-JUN/AP-1 . The interaction with these host proteins couldlead to a blockage of these regulatory pathways. The pathwayinvolving c-JUN/AP-1 may be of particular interest in this respect, since inhibition of this TF by viral proteins (gp32 andNS3) could promote TERT activation. These assumptions arein good agreement with the data on differential gene expressionin acute HCV infection when the infected cells showedan increased TERT expression , so thispathway can be a promising pharmacological target.Thus, the considered assumptions lead one to conclude thepresence of multidirectional regulation of the observed expressionof HCC marker genes. This may indicate that not all regulatorypathways controlled by viral proteins can be attributedto HCC risk factors. However, the regulatory pathways thatensure the protumor activity of virus proteins undoubtedlydeserve additional study to understand the mechanisms ofvirus-induced HCC carcinogenesis. In particular, the suppressionof tumor suppressor gene expression by viral proteins canenhance the effect of their methylation in HCC or mimic thiseffect when these genes are not methylated, which can eitherprovoke HCC onset or complicate its course.Using the computer methods for gene network reconstructionavailable in the ANDSystem package, the statisticallysignificant pathways for HCV proteins to regulate HCC genemarkers have been established. The obtained results describethe potential mechanisms of the proteins involvement in HCCpathogenesis and may be useful for planning experimentalstudies to search for new targets for the development of drugsand prophylactic agents to reduce the risk of HCC developingin presence of HCV infectionThe authors declare no conflict of interest.Benderska N., Schneider-Stock R. Transcription control of DAPK.Apoptosis. 2014;19(2):298-305. DOI 10.1007/s10495-013-0931-6.Bragina E.Y., Tiys E.S., Rudko A.A., Ivanisenko V.A., Freidin M.B.Novel tuberculosis susceptibility candidate genes revealed by thereconstruction and analysis of associative networks. Infect. Genet.Evol. 2016;46:118-123. DOI 10.1016/j.meegid.2016.10.030.Chen J., Li Z., Chen J., Du Y., Song W., Xuan Z., Zhao L., Song G.,Song P., Zheng S. Downregulation of MGMT promotes proliferationof intrahepatic cholangiocarcinoma by regulating p21. Clin. Transl.Oncol. 2020;22(3):392-400. DOI 10.1007/s12094-019-02140-9.Chen M., Gan X., Yoshino K., Kitakawa M., Shoji I., Deng L., Hotta H.Hepatitis C virus NS5A protein interacts with lysine methyltransferaseSET and MYND domain-containing 3 and induces activatorprotein 1 activation. Microbiol. Immunol. 2016;60:407-417. DOI10.1111/1348-0421.12383.Chen P., Meng C., Wang Q., Yang X., Huang Z., Xing X., Lin Y.,Liu X., Peng J., Lin Y. Death-associated protein kinase 1 suppresseshepatocellular carcinoma cell migration and invasion by upregulationof DEAD-box helicase 20. Cancer Sci. 2020;111(8):2803-2813.DOI 10.1111/cas.14499.Cheng J., Wei D., Ji Y., Chen L., Yang L., Li G., Wu L., Hou T., Xie L.,Ding G., Li H., Li Y. Integrative analysis of DNA methylation andgene expression reveals hepatocellular carcinoma-specific diagnosticbiomarkers. Genome Med. 2018;10(1):42. DOI 10.1186/s13073-018-0548-z.Choi J., Southworth L.K., Sarin K.Y., Venteicher A.S., Ma W., Chang W.,Cheung P., Jun S., Artandi M.K., Shah N., Kim S.K., ArtandiS.E.TERT promotes epithelial proliferation through transcriptional controlof a Myc- and Wnt-related developmental program. PLoS Genet.2008;4(1):e10. DOI 10.1371/journal.pgen.0040010.de Chassey B., Navratil V., Tafforeau L., Hiet M.S., Aublin-Gex A.,Agaugué S., Meiffren G., Pradezynski F., Faria B.F., Chantier T.,Le Breton M., Pellet J., Davoust N., Mangeot P.E., Chaboud A.,Penin F., Jacob Y., Vidalain P.O., Vidal M., André P., Rabourdin-Combe C., Lotteau V. Hepatitis C virus infection protein network.Mol. Syst. Biol. 2008;4:230. DOI 10.1038/msb.2008.66.Deng Y., Yu B., Cheng Q., Jin J., You H., Ke R., Tang N., Shen Q.,Shu H., Yao G., Zhang Z., Qin W. Epigenetic silencing of WIF-1in hepatocellular carcinomas. J. Cancer Res. Clin. Oncol. 2010;136(8):1161-1167. DOI 10.1007/s00432-010-0763-5.D’souza S., Lau K.C., Coffin C.S., Patel T.R. Molecular mechanismsof viral hepatitis induced hepatocellular carcinoma. World J. Gastroenterol.2020;26(38):5759-5783. DOI 10.3748/wjg.v26.i38.5759.Feng L., Li J., Yan L.D., Tang J. RASSF1A suppresses proliferation ofcervical cancer cells. Asian Pac. J. Cancer Prev. 2014;15(14):5917-5920. DOI 10.7314/apjcp.2014.15.14.5917.Fernández-Barrena M.G., Arechederra M., Colyn L., Berasain C., AvilaM.A. Epigenetics in hepatocellular carcinoma development andtherapy: the tip of the iceberg. JHEP Rep. 2020;2(6):100167. DOI10.1016/j.jhepr.2020.100167.Glotov A.S., Tiys E.S., Vashukova E.S., Pakin V.S., Demenkov P.S.,Saik O.V., Ivanisenko T.V., Arzhanova O.N., Mozgovaya E.V.,ZainulinaM.S., Kolchanov N.A., Baranov V.S., Ivanisenko V.A.Molecular association of pathogenetic contributors to pre-eclampsia(pre-eclampsia associome). BMC Syst. Biol. 2015:9(Suppl.2):S4.DOI 10.1186/1752-0509-9-S2-S4.Gui Y., Yeganeh M., Ramanathan S., Leblanc C., Pomerleau V., FerbeyreG., Saucier C., Ilangumaran S. SOCS1 controls liver regenerationby regulating HGF signaling in hepatocytes. J. Hepatol. 2011;55(6):1300-1308. DOI 10.1016/j.jhep.2011.03.027.Guo N., Chen R., Li Z., Liu Y., Cheng D., Zhou Q., Zhou J., Lin Q.Hepatitis C virus core upregulates the methylation status of theRASSF1A promoter through regulation of SMYD3 in hilar cholangiocarcinomacells. Acta Biochim. Biophys. Sin. (Shanghai). 2011;43(5):354-361. DOI 10.1093/abbs/gmr021.Han Y., Niu J., Wang D., Li Y. Hepatitis C virus protein interactionnetwork analysis based on hepatocellular carcinoma. PLoS One.2016;11(4):e0153882. DOI 10.1371/journal.pone.0153882.Hassan M., Ghozlan H., Abdel-Kader O. Activation of c-Jun NH2-terminal kinase (JNK) signaling pathway is essential for the stimulationof hepatitis C virus (HCV) non-structural protein 3 (NS3)-mediated cell growth. Virology. 2005;333(2):324-336. DOI 10.1016/j.virol.2005.01.008.Hassan M., Selimovic D., Ghozlan H., Abdel-Kader O. Induction ofhigh-molecular-weight (HMW) tumor necrosis factor (TNF) alphaby hepatitis C virus (HCV) non-structural protein 3 (NS3) in livercells is AP-1 and NF-κB-dependent activation. Cell. Signal. 2007;19(2):301-311. DOI 10.1016/j.cellsig.2006.07.002He B., Reguart N., You L., Mazieres J., Xu Z., Lee A.Y., Mikami I.,McCormick F., Jablons D.M. Blockade of Wnt-1 signaling inducesapoptosis in human colorectal cancer cells containing downstreammutations. Oncogene. 2005;24(18):3054-3058. DOI 10.1038/sj.onc.1208511.Hernandez-Meza G., von Felden J., Gonzalez-Kozlova E.E., Garcia-Lezana T., Peix J., Portela A., Craig A.J., Sayols S., Schwartz M.,Losic B., Mazzaferro V., Esteller M., Llovet J.M., Villanueva A.DNA methylation profiling of human hepatocarcinogenesis. Hepatology.2021;74(1):183-199. DOI 10.1002/hep.31659.Hoshida Y., Villanueva A., Kobayashi M., Peix J., Chiang D.Y., CamargoA., Gupta S., Moore J., Wrobel M.J., Lerner J., Reich M.,Chan J.A., Glickman J.N., Ikeda K., Hashimoto M., Watanabe G.,Daidone M.G., Roayaie S., Schwartz M., Thung S., Salvesen H.B.,Gabriel S., Mazzaferro V., Bruix J., Friedman S.L., Kumada H., LlovetJ.M., Golub T.R. Gene expression in fixed tissues and outcomein hepatocellular carcinoma. N. Engl. J. Med. 2008;359(19):1995-2004. DOI 10.1056/NEJMoa0804525.Huang L., Li M.X., Wang L., Li B.K., Chen G.H., He L.R., Xu L.,Yuan Y.F. Prognostic value of Wnt inhibitory factor-1 expression inhepatocellular carcinoma that is independent of gene methylation.Tumour Biol. 2011;32(1):233-240. DOI 10.1007/s13277-010-0117-6.In der Stroth L., Tharehalli U., Günes C., Lechel A. Telomeres andtelomerase in the development of liver cancer. Cancers ( Basel).2020;12(8):2048. DOI 10.3390/cancers12082048Ivanisenko N.V., Seyrek K., Kolchanov N.A., Ivanisenko V.A., LavrikI.N. The role of death domain proteins in host response uponSARS-CoV-2 infection: modulation of programmed cell death andtranslational applications. Cell Death Discov. 2020;6:101. DOI10.1038/s41420-020-00331-w.Ivanisenko T.V., Saik O.V., Demenkov P.S., Ivanisenko N.V., SavostianovA.N., Ivanisenko V.A. ANDDigest: a new web-based module ofANDSystem for the search of knowledge in the scientific literature.BMC Bioinformatics. 2020;21(Suppl.11):228. DOI 10.1186/s12859-020-03557-8.Ivanisenko V.A., Demenkov P.S., Ivanisenko T.V., Mishchenko E.L.,Saik O.V. A new version of the ANDSystem tool for automatic extractionof knowledge from scientific publications with expandedfunctionality for reconstruction of associative gene networks byconsidering tissue-specific gene expression. BMC Bioinformatics.2019;20(Suppl.1):34. DOI 10.1186/s12859-018-2567-6.Ivanisenko V.A., Gaisler E.V., Basov N.V., Rogachev A.D., CheresizS.V., Ivanisenko T.V., Demenkov P.S., Mishchenko E.L., Khripko O.P., Khripko Yu.I., Voevoda S.M., Karpenko T.N., Velichko A.J.,Voevoda M.I., Kolchanov N.A., Pokrovsky A.G. Plasma metabolomicsand gene regulatory networks analysis reveal the role of nonstructuralSARS-CoV-2 viral proteins in metabolic dysregulation inCOVID-19 patients. Sci. Rep. 2022;12:19977. DOI 10.1038/s41598-022-24170-0.Ivanisenko V.A., Saik O.V., Ivanisenko N.V., Tiys E.S., Ivanisenko T.V.,Demenkov P.S., Kolchanov N.A. ANDSystem: an Associative NetworkDiscovery System for automated literature mining in the fieldof biology. BMC Syst. Biol. 2015;9(Suppl.2):S2. DOI 10.1186/1752-0509-9-S2-S2.Iwai A., Takegami T., Shiozaki T., Miyazaki T. Hepatitis C virus NS3protein can activate the Notch-signaling pathway through bindingto a transcription factor, SRCAP. PLoS One. 2011;6(6):e20718. DOI10.1371/journal.pone.0020718.Jardin F., Ruminy P., Bastard C., Tilly H. The BCL6 proto-oncogene:a leading role during germinal center development and lymphomagenesis.Pathol. Biol. ( Paris). 2007;55(1):73-83. DOI 10.1016/j.patbio.2006.04.001.Jaroszewicz J., Flisiak-Jackiewicz M., Lebensztejn D., Flisiak R. Currentdrugs in early development for treating hepatitis C virus-relatedhepatic fibrosis. Expert Opin. Investig. Drugs. 2015;24(9):1229-1239. DOI 10.1517/13543784.2015.1057568.Jiang L.H., Hao Y.L., Zhu J.W. Expression and prognostic value ofHER-2/neu, STAT3 and SOCS3 in hepatocellular carcinoma. Clin.Res. Hepatol. Gastroenterol. 2019;43(3):282-291. DOI 10.1016/j.clinre.2018.09.011.Jing W., Peng R., Li X., Lv S., Duan Y., Jiang S. Study on the prognosticvalues of TTC36 correlated with immune infiltrates and its methylationin hepatocellular carcinoma. J. Immunol. Res. 2022;2022:7267131. DOI 10.1155/2022/7267131.Kim B.R., Park S.H., Jeong Y.A., Na Y.J., Kim J.L., Jo M.J., Jeong S.,Yun H.K., Oh S.C., Lee D.H. RUNX3 enhances TRAIL-inducedapoptosis by upregulating DR5 in colorectal cancer. Oncogene.2019;38:3903-3918. DOI 10.1038/s41388-019-0693-x.Kohsaka S., Wang L., Yachi K., Mahabir R., Narita T., Itoh T., TaninoM., Kimura T., Nishihara H., Tanaka S. STAT3 inhibition overcomestemozolomide resistance in glioblastoma by downregulatingMGMT expression. Mol. Cancer Ther. 2012;11(6):1289-1299. DOI10.1158/1535-7163.MCT-11-0801.Konnikova L., Simeone M.C., Kruger M.M., Kotecki M., Cochran B.H.Signal transducer and activator of transcription 3 (STAT3) regulateshuman telomerase reverse transcriptase (hTERT) expression in humancancer and primary cells. Cancer Res. 2005;65(15):6516-6520.DOI 10.1158/0008-5472.CAN-05-0924.Li B., Li X., Li Y., Guo H., Sun S.Y., He Q.Q., Wang Y., Luo J.,Wen J.F., Zheng H., Feng D.Y. The effects of hepatitis C virus nonstructuralprotein 3 on cell growth mediated by extracellular signalrelatedkinase cascades in human hepatocytes in vitro. Int. J. Mol.Med. 2010;26(2):273-279. DOI 10.3892/ijmm_00000462Lin B., Hong H., Jiang X., Li C., Zhu S., Tang N., Wang X., She F.,Chen Y. c-Jun suppresses the expression of WNT inhibitory factor 1through transcriptional regulation and interaction with DNA methyltransferase1 in gallbladder cancer. Mol. Med. Rep. 2018;17(6):8180-8188. DOI 10.3892/mmr.2018.8890.Liu J., Ma Q., Zhang M., Wang X., Zhang D., Li W., Wang F., Wu E.Alterations of TP53 are associated with a poor out-come for patientswith hepatocellular carcinoma: evidence from a systematic reviewand meta-analysis. Eur. J. Cancer. 2012;48(15):2328-2338. DOI10.1016/j.ejca.2012.03.001.Llovet J.M., Zucman-Rossi J., Pikarsky E., Sangro B., Schwartz M.,Sherman M., Gores G. Hepatocellular carcinoma. Nat. Rev. Dis.Primers. 2016;2:16018. DOI 10.1038/nrdp.2016.18.Loeb D.M. WT1 influences apoptosis through transcriptional regulationof Bcl-2 family members. Cell Cycle. 2006;5(12):1249-1253.DOI 10.4161/cc.5.12.2807Machida K., Cheng K.T., Lai C.K., Jeng K.S., Sung V.M., Lai M.M.Hepatitis C virus triggers mitochondrial permeability transition withproduction of reactive oxygen species, leading to DNA damage andSTAT3 activation. J. Virol. 2006;80(14):7199-7207. DOI 10.1128/JVI.00321-06.Machida K., Cheng K.T., Sung V.M., Shimodaira S., Lindsay K.L.,Levine A.M., Lai M.Y., Lai M.M. Hepatitis C virus induces a mutatorphenotype: enhanced mutations of immunoglobulin and protooncogenes.Proc. Natl. Acad. Sci. USA. 2004;101(12):4262-4267.DOI 10.1073/pnas.0303971101.Mayo M.W., Wang C.Y., Drouin S.S., Madrid L.V., Marshall A.F.,Reed J.C., Weissman B.E., Baldwin A.S. WT1 modulates apoptosisby transcriptionally upregulating the bcl-2 proto-oncogene.EMBO J. 1999;18(14):3990-4003. DOI 10.1093/emboj/18.14.3990.McGlynn K.A., Petrick J.L., El-Serag H.B. Epidemiology of hepatocellularcarcinoma. Hepatology. 2021;73(Suppl.1):4-13. DOI 10.1002/hep.31288Mžik M., Chmelařová M., John S., Laco J., Slabý O., Kiss I., BohovicováL., Palička V., Nekvindová J. Aberrant methylation of tumoursuppressor genes WT1, GATA5 and PAX5 in hepatocellular carcinoma.Clin. Chem. Lab. Med. 2016;54(12):1971-1980. DOI 10.1515/cclm-2015-1198.Nault J.C., Ningarhari M., Rebouissou S., Zucman-Rossi J. The roleof telomeres and telomerase in cirrhosis and liver cancer. Nat. Rev.Gastroenterol. Hepatol. 2019;16(9):544-558. DOI 10.1038/s41575-019-0165-3.Neumann O., Kesselmeier M., Geffers R., Pellegrino R., RadlwimmerB., Hoffmann K., Ehemann V., Schemmer P., Schirmacher P.,Lorenzo Bermejo J., Longerich T. Methylome analysis and integrativeprofiling of human HCCs identify novel protumorigenicfactors. Hepatology. 2012;56(5):1817-1827. DOI 10.1002/hep.25870.Ni Y., Gu J., Wu J., Xu L., Rui Y. MGMT-mediated neuron apoptosis ininjured rat spinal cord. Tissue Cell. 2020;62:101311. DOI 10.1016/j.tice.2019.101311Nowyhed H.N., Huynh T.R., Blatchley A., Wu R., Thomas G.D., HedrickC.C. The nuclear receptor Nr4a1 controls CD8 T cell developmentthrough transcriptional suppression of Runx3. Sci. Rep.2015;5:9059. DOI 10.1038/srep09059.Oversoe S.K., Clement M.S., Pedersen M.H., Weber B., Aagaard N.K.,Villadsen G.E., Grønbæk H., Hamilton-Dutoit S.J., Sorensen B.S.,Kelsen J. TERT promoter mutated circulating tumor DNA as a biomarkerfor prognosis in hepatocellular carcinoma. Scand. J. Gastroenterol.2020;55(12):1433-1440. DOI 10.1080/00365521.2020.1837928.Papic N., Maxwell C.I., Delker D.A., Liu S., Heale B.S., Hagedorn C.H.RNA-sequencing analysis of 5′ capped RNAs identifies many newdifferentially expressed genes in acute hepatitis C virus infection.Viruses. 2012;4:581-612. DOI 10.3390/v4040581.Phan R.T., Dalla-Favera R. The BCL6 proto-oncogene suppresses p53expression in germinal-centre B cells. Nature. 2004;432(7017):635-639. DOI 10.1038/nature03147.Rabaan A.A., Al-Ahmed S.H., Bazzi A.M., Alfouzan W.A., AlsulimanS.A., Aldrazi F.A., Haque S. Overview of hepatitis C infection,molecular biology, and new treatment. J. Infect. Public Health.2020;13(5):773-783. DOI 10.1016/j.jiph.2019.11.015.Revill K., Wang T., Lachenmayer A., Kojima K., Harrington A., Li J.,Hoshida Y., Llovet J.M., Powers S. Genome-wide methylationanalysis and epigenetic unmasking identify tumor suppressor genesin hepatocellular carcinoma. Gastroenterology. 2013;145(6):1424-1435.e1-25. DOI 10.1053/j.gastro.2013.08.055.Saik O.V., Demenkov P.S., Ivanisenko T.V., Bragina E.Y., Freidin M.B.,Goncharova I.A., Dosenko V.E., Zolotareva O.I., Hofestaedt R.,Lavrik I.N., Rogaev E.I., Ivanisenko V.A. Novel candidate genesimportant for asthma and hypertension comorbidity revealed fromassociative gene networks. BMC Med. Genomics. 2018;11(Suppl.1):15. DOI 10.1186/s12920-018-0331-4.Saik O.V., Ivanisenko T.V., Demenkov P.S., Ivanisenko V.A. Interactomeof the hepatitis C virus: literature mining with ANDSystem.Virus Res. 2016;218:40-48. DOI 10.1016/j.virusres.2015.12.003.Sarin K.Y., Cheung P., Gilison D., Lee E., Tennen R.I., Wang E., ArtandiM.K., Oro A.E., Artandi S.E. Conditional telomerase inductioncauses proliferation of hair follicle stem cells. Nature. 2005;436(7053):1048-1052. DOI 10.1038/nature03836Sawangarun W., Mandasari M., Aida J., Morita K.I., Kayamori K.,Ikeda T., Sakamoto K. Loss of Notch1 predisposes oro-esophagealepithelium to tumorigenesis. Exp. Cell Res. 2018;372(2):129-140.DOI 10.1016/j.yexcr.2018.09.019.Schulze K., Imbeaud S., Letouzé E., Alexandrov L.B., Calderaro J.,Rebouissou S., Couchy G., Meiller C., Shinde J., Soysouvanh F.,CalatayudA.L., Pinyol R., Pelletier L., Balabaud C., Laurent A.,Blanc J.F., Mazzaferro V., Calvo F., Villanueva A., Nault J.C., Bioulac-Sage P., Stratton M.R., Llovet J.M., Zucman-Rossi J. Exomesequencing of hepatocellular carcinomas identifies new mutationalsignatures and potential therapeutic targets. Nat. Genet. 2015;47(5):505-511. DOI 10.1038/ng.3252.Sera T., Hiasa Y., Mashiba T., Tokumoto Y., Hirooka M., Konishi I.,Matsuura B., Michitaka K., Udaka K., Onji M. Wilms’ tumour 1gene expression is increased in hepatocellular carcinoma and associatedwith poor prognosis. Eur. J. Cancer. 2008;44(4):600-608.DOI 10.1016/j.ejca.2008.01.008.Song Z., Li Z., Han W., Zhu C., Lou N., Li X., Luo G., Peng S., Li G.,Zhao Y., Guo Y. Low DAPK1 expression correlates with poor prognosisand sunitinib resistance in clear cell renal cell carcinoma.Aging ( Albany NY). 2020;13(2):1842-1858. DOI 10.18632/aging.103638.Takakura M., Kyo S., Inoue M., Wright W.E., Shay J.W. Function ofAP-1 in transcription of the telomerase reverse transcriptase gene(TERT ) in human and mouse cells. Mol. Cell Biol. 2005;25(18):8037-8043. DOI 10.1128/MCB.25.18.8037-8043.2005.Tan Y., Li Y. HCV core protein promotes hepatocyte proliferation andchemoresistance by inhibiting NR4A1. Biochem. Biophys. Res.Commun. 2015;466(3):592-598. DOI 10.1016/j.bbrc.2015.09.091.Tucci F.A., Broering R., Johansson P., Schlaak J.F., Küppers R. B cellsin chronically hepatitis C virus-infected individuals lack a virusinducedmutation signature in the TP53, CTNNB1, and BCL6 genes.J. Virol. 2013;87(5):2956-2962. DOI 10.1128/JVI.03081-12.Xu R.H., Wei W., Krawczyk M., Wang W., Luo H., Flagg K., Yi S.,Shi W., Quan Q., Li K., Zheng L., Zhang H., Caughey B.A., Zhao Q., Hou J., Zhang R., Xu Y., Cai H., Li G., Hou R., Zhong Z.,Lin D., Fu X., Zhu J., Duan Y., Yu M., Ying B., Zhang W., Wang J.,Zhang E., Zhang C., Li O., Guo R., Carter H., Zhu J.K., Hao X.,Zhang K. Circulating tumour DNA methylation markers for diagnosisand prognosis of hepatocellular carcinoma. Nat. Mater. 2017;16(11):1155-1161. DOI 10.1038/nmat4997.Yang C., Zhang Y., Wang J., Li L., Wang L., Hu M., Xu M., Long Y.,Rong R., Zhu T. A novel cyclic helix B peptide inhibits dendriticcell maturation during amelioration of acute kidney graft rejectionthrough Jak-2/STAT3/SOCS1. Cell Death Dis. 2015;6(11):e1993.DOI 10.1038/cddis.2015.338.Ye S., Zhao X.Y., Hu X.G., Li T., Xu Q.R., Yang H.M., Huang D.S.,Yang L. TP53 and RET may serve as biomarkers of prognosticevaluationand targeted therapy in hepatocellular carcinoma. Oncol.Rep. 2017;37(4):2215-2226. DOI 10.3892/or.2017.5494.Zhang C., Li J., Huang T., Duan S., Dai D., Jiang D., Sui X., Li D.,Chen Y., Ding F., Huang C., Chen G., Wang K. Meta-analysis ofDNA methylation biomarkers in hepatocellular carcinoma. Oncotarget.2016;7(49):81255-81267. DOI 10.18632/oncotarget.13221.Zhang H., Weng X., Ye J., He L., Zhou D., Liu Y. Promoter hypermethylationof TERT is associated with hepatocellular carcinomain the Han Chinese population. Clin. Res. Hepatol. Gastroenterol.2015;39(5):600-609. DOI 10.1016/j.clinre.2015.01.002.Zhu Z., Tran H., Mathahs M.M., Moninger T.O., Schmidt W.N. HCVinduces telomerase reverse transcriptase, increases its catalytic activity,and promotes caspase degradation in infected human hepatocytes.PLoS One. 2017;12(1):e0166853. DOI 10.1371/journal.pone.0166853.Zhu Z., Wilson A.T., Gopalakrishna K., Brown K.E., Luxon B.A.,Schmidt W.N. Hepatitis C virus core protein enhances Telomeraseactivity in Huh7 cells. J. Med. Virol. 2010;82(2):239-248. DOI10.1002/jmv.21644.Zong C., Qin D., Yu C., Gao P., Chen J., Lu S., Zhang Y., Liu Y., Yang Y.,Pu Z., Li X., Fu Y., Guan Q., Wang X. The stress-response moleculeNR4A1 resists ROS-induced pancreatic β-cells apoptosis via WT1.Cell Signal. 2017;35:129-139. DOI 10.1016/j.cellsig.2017.03.012.Zucman-Rossi J., Villanueva A., Nault J.C., Llovet J.M. Genetic landscapeand biomarkers of hepatocellular carcinoma. Gastroenterology.2015;149(5):1226-1239.e4. DOI 10.1053/j.gastro.2015.05.061.


Klebsiella pneumoniae, a leading pathogen for mortality associated with antimicrobial resistance (AMR), was responsible for > 250,000 deaths in 2019. Genomic surveillance can guide the development of vaccines and new antibiotics against this pathogen. While AMR disproportionally affects low-and middle-income countries, limited genomic data are available from these countries. To close this gap, this study provides genomic characterization of K. pneumoniae blood isolates recovered in Peru.K. pneumoniae blood culture isolates were collected during an AMR surveillance study (VIRAPERU) from Jul 2017 to Oct 2019, from 15 tertiary hospitals from 13 regions of Peru. DNA extraction , DNA library  and genome sequencing  were conducted. De novo assembling (SPAdes v3.13.1), quality assessment and annotation (Nullarbor v2.0), and identification of species, ST group, K/O loci, AMR (Kleborate v2.0.1) were conducted. Phylogenetic trees were built with Microreact v.192.Consecutive non-duplicate K. pneumoniae isolates, 114 were recovered and confirmed to belong to the Klebsiella taxon. Six species were identified, the most prevalent being K. pneumoniae (106), followed by K. quasipneumoniae (3). Among carbapenem-resistant isolates (n=13), 10 (77%) carried the blaNDM-1 gene, while other three carried blaKPC-2 (1), blaIMP-16 (1) or no carbapenemase (1). Phenotypic co-resistance to colistin was present in 2 isolates, both negative for mcr-1 gene. The most common mechanisms of resistance to 3rd generation cephalosporins, quinolones and to aminoglycosides were CTX-M-15 (74.4%), qnrB (63.6%), aac(6')-Ib-cr (87.5%), respectively. Many other AMR genetic determinants were identified . Sixty ST groups were identified, but only 6 ST groups carried a carbapenemase gene . A wide diversity of K and O locus was also identified (54 distinct K-loci and 14 distinct O-loci).From 119 K. pneumoniae strains, carrying multiple AMR genes. Carbapenem resistance is principally a result of blaNDM-1 carriage, found across 6 specific ST groups.Bloodstream infections in Peru are caused by a wide diversity of Omai Garner, PhD, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Victor Nizet, MD, Cellics Therapeutics: Advisor/Consultant|Clarametyx Biosciences: Advisor/Consultant|Vaxcyte, Inc.: Advisor/Consultant|Vaxcyte, Inc.: Grant/Research Support.


Liver transplanted (LT) patients for hepatocellular carcinoma (LT-HCC) or for other causes (LT-no-HCC) may develop post-transplantation malignancies. Although immune activation and senescence are frequently implicated in cancer development, no data is available on their possible role as biomarkers predictive of tumor onset in this setting. A total of 116 patients were investigated: the 45 LT-HCC patients were older than the 71 LT-non-HCC (p=0.011), but comparable for sex, HCV, HBV infection and immunosuppressive treatment. At baseline, the numbers of activated and senescent-like circulating cells were significantly higher in LT-HCC patients than in LT-no-HCC ones. After a median follow-up of 26.8 months, 6 post-transplant malignancies (PTM) occurred: 4 in LT-HCC (8.9%) and 2 in LT-no-HCC (2.8%) patients. Overall, subjects with high percentages of activated and exhausted T and B cells at baseline were at higher risk of PTM. Notably, within the LT-HCC group, a higher percentage of senescence-like T cells was also associated with cancer development. Moreover, patients with PTM had higher telomere erosion and higher levels of circulating PAMPs (16S rDNA) and DAMPs (mtDNA) when compared with matched patients without PTM. Overall, these findings suggest that immune activation and exhaustion may be useful to predict the risk of PTM occurrence, regardless of the cause of transplantation. In LT-HCC, T-cell senescence represents an additional risk factor for tumor onset. Liver transplantation is the treatment of choice for patients with end-stage liver disease, acute liver failure or hepatocellular carcinoma (HCC). In Italy, a total of 12,519 liver transplants were performed between 2010 and 2020  compared to liver transplanted patients for other causes (LT-no-HCC)  followed by chronic local inflammation –11. Afte+ T cells. Consistently, lower thymic output and shorter telomeres were associated with a higher risk of developing cancer in the same cohort , which have been implicated in both aging and cancer development , 16. In e cohort . Further outcome .Considering the possible clinical relevance of the availability of suitable biomarkers for the prediction of tumor onset in LT patients, in the present study we have characterized immune activation, exhaustion, and senescence markers in the blood of a prospective series of LT patients with the final goal to assess their possible usefulness in the definition of the risk of PTM development.3 = 4/3 x 3.14 x (radius of the tumor nodule in mm3)”. Total tumor volume (TTV) was calculated as the sum of the tumor volume of each nodule. LT-HCC patients were followed for HCC recurrence through CT-scan or MRI every 3 months during the first year, and every 6 months thereafter, according to the European Association for the Study of the Liver/European Organization for Research and Treatment of Cancer (EASL-EORTC) clinical practice guidelines for the management of hepatocellular cancer . Patients’ clinical information were recorded and included personal details , transplant details  score and alpha-fetoprotein levels at liver transplantation) and post-transplantation immunosuppressive schedule, considering modifications during follow-up. For LT-HCC patients, tumor characteristics were assessed through explant pathology evaluation for the following characteristics: number of HCC nodules, maximum nodular diameter, tumor differentiation and presence of macro/micro-vascular invasion. Vital tumor volume was quantified according to the following equation: “Tumor volume mmr cancer . As theyAfter a median follow-up of 26.8 months following liver transplantation, 6 patients developed a PTM (LT-PTM): 5 were DNMs and 1 was an HCC recurrence. DNMs were defined as neoplasms developing after transplantation in patients negative at pre-transplant screening for the HCC, or related pre-malignant lesions/conditions. DNMs were coded according to the International Classification of Diseases and Related Health Problems, 10th revision (ICD-10). Diagnosis of DNMs was established by histology on biopsies or surgical specimens of the tumor. Date of biopsy or surgical procedure was designated as the date of cancer diagnosis. All patients underwent a full pre-transplant screening aimed at excluding any type of cancer other than HCC, or related premalignant lesions/conditions, which was negative in all patients. Moreover, to avoid any accidental missing pre-LT diagnosis, lesions that appeared within 6 months after transplantation were excluded from the definition of DNM. In our cohort, the 5 DNMs were: infiltrating ductal carcinoma of the breast, ovarian cancer, larynx carcinoma, basal cell carcinoma of the external auditory canal, and prostate cancer. Among the 110 patients without PTM (LT-no-PTM), 26 subjects were selected as a matched (m)LT-no-PTM control group according to the following inclusion criteria: age, sex difference, immunosuppressive combined strategies, and a median time interval from baseline to follow-up. This study was approved by the Ethical Committee of Padova University Hospital (Prot. 4231/AO/17).Blood samples were collected in EDTA-containing tubes at baseline (at liver transplantation) and at follow-up . From samples at baseline and at closest time to the tumor onset in LT-PTM patients, or with a median time interval similar for mLT-no-PTM patients, peripheral blood mononuclear cells (PBMC) were isolated by centrifugation on a Ficoll-Paque  gradient. PBMC were cryopreserved in liquid nitrogen, and plasma samples at - 80°C, until use..Immunophenotyping was performed on cryopreserved PBMC. Cells were thawed, washed, stained for 20 min in the dark with the Live/Dead Fixable Near-IR Dead Cell Stain Kit  and the following labelled monoclonal antibodies (mAbs): anti-CD3 [fluorescein isothiocyanate (FITC)], anti-CD4 [peridinin chlorophyll protein (PerCP)], anti-CD38 [phycoerythrin (PE)], anti-HLA-DR [allophycocyanin (APC)], anti-CD279  [PE-Cy7], anti-CD57 [PE], anti-CD21 [BV421], anti-CD27 [PE-Cy7], anti-IgD [PE], anti-CD274  [BV421] ; anti-CD8 [VioGreen], anti-CD28 [APC], anti-CD19 [VioBright515], anti-CD10 [APC] . Cells were then washed and resuspended in phosphate-buffered saline supplemented with 1% paraformaldehyde. All samples were analyzed using LSRII Flow cytometer (Becton-Dickinson). A total of 50000 events were collected in the lymphocyte gate using morphological parameters (forward and side-scatter). Data were processed with FACSDiva Software (Becton-Dickinson) and analyzed using Kaluza Analyzing Software v.1.2 (Beckman Coulter) DNA was extracted from PBMC, using QIAmp DNA Blood Mini Kit  according to the manufacturer’s instructions. Relative telomere length (RTL) was determined by monochrome quantitative multiplex real-time PCR, as previously described , 21.DNA extraction from 200 µl of plasma was performed using QIAamp DNA Mini Kit , and eluted in 50 µl of AE Buffer. A quantitative method based on real-time PCR assay was performed to quantify plasma levels of 16S rDNA with primer pair (forward 5’-AGTTTGATCCTGGCTCAG-3’ and reverse 5’-GWATTACCGCGGCKGCTG-3’) and probe (5’-FAM-GCTGCCTCCCGTAGGAGT-BHQ-3’), as previously described , 23. ResContinuous variables were summarized using median and interquartile range (IQR), categorical variables as frequencies and percentages. The median follow-up time was based on the reverse Kaplan-Meier estimator. Clinical characteristics at baseline were compared between LT-HCC and LT-no-HCC patients using the Kruskal-Wallis test, or Fisher exact test as appropriate. A Mann-Whitney test, adjusted for age, was used to address comparisons of each immunological parameter distribution between groups of interest. The impact of the immunological parameters on the probability of experiencing HCC or PTM was estimated in univariate logistic regression models fitted by penalized maximum likelihood to address low frequency data. Each covariate was considered as a categorical variable according to high and low levels. Optimal cut-points were selected using a criterion based on maximizing the Youden index, being the summary measure of the ROC curve, over all possible cut-points. The odds ratios (ORs) were reported with their 95% confidence interval (CI). ORs were also adjusted for age as continuous variable. Subgroup analyses were performed with explorative intent. All statistical tests were two-sided and a p value <0.05 was considered statistically significant. Statistical analyses were performed using the RStudio .vs 53.0 years (45.5-61.0), p=0.011.The patients’ characteristics are summarized in + T cells and memory B cells were significantly higher in LT-HCC compared to LT-no-HCC patients (%CD8+CD38+HLA-DR+: 10.89 (5.61-18.52) vs 6.59 (4.26-9.25), p=0.003; %CD19+CD10-CD21-CD27+: 10.97 (5.59-20.68) vs 7.60 (3.00-13.72), p=0.040) (+ T cells (%CD4+CD38+HLA-DR+: 7.23 (4.11-14.12) vs 6.21 (3.49-9.23), p=0.092)  vs 7.54 (4.00-12.92), p=0.254; %CD4+PD-1+: 9.28 (5.66-13.50) vs 7.27 (4.54-10.34), p=0.222; %CD19+PD-L1+: 4.96 (3.12-9.75) vs 5.16 (2.18-9.00), p=0.797)  vs 5.92 (3.54-10.97), p=0.006; %CD4+CD28-CD57+: 3.80 (1.36-14.03) vs 1.80 (0.48-3.41), p=0.002; %CD19+CD27-IgD-: 12.20 (6.28-17.67) vs 6.59 (4.24-12.50), p=0.019)  following LT, 6 patients developed a PTM: 4 patients (8.9%) (3 DNMs and 1 an HCC recurrence) were in the LT-HCC group, and 2  were in the LT-no-HCC group Table 1.To evaluate the role of immune activation, exhaustion and senescence as possible markers predictive of the risk of tumor development in this setting, we analyzed these immunological parameters at baseline in samples obtained from the 6 LT-PTM patients in comparison with those of 110 LT-no-PTM patients. At baseline, the two groups did not differ by age, sex, HCV and HBV infection  vs 7.14 (4.48-11.98), p=0.002; %CD4+CD38+HLA-DR+: 14.28 (10.53-16.84) vs 6.26 (3.58-9.77), p=0.0001; %CD19+CD10-CD21-CD27+: 25.57 (10.09-28.57) vs 8.55 (4.20-15.40), p=0.024) (The percentages of activated CD8p=0.024) Table 3.+PD-1+: 19.81 (16.97-28.90) vs 7.78 (4.62-14.67), p=0.000; %CD4+PD-1+: 22.71 (17.96-27.89) vs 7.75 (4.47-10.85), p=0.000; %CD19+PD-L1+: 10.15 (7.82-19.75) vs 5.01 (2.23-9.09), p=0.015) (The percentage of circulating immune cells expressing markers of exhaustion was significantly higher in LT-PTM than in LT-no-PTM patients (%CD8p=0.015) Table 3.+ T cells and B cells tended to be higher in the LT-PTM than in LT-no-PTM patients  vs 10.08 (5.33-12.83), p=0.002), while no difference was observed in senescent-like CD8+ and CD4+ T cells  copies/µl, p=0.008); since no difference occurred in the two groups during follow-up, this level still remained higher at follow-up (64.95 (29.51-106.15) vs 26.99 (11.27-58.74) copies/µl, p= 0.074) (vs 1822 (985-3984) copies/µl, p=0.096), but they become significantly higher at follow-up (3075 (2187-6244) vs 1668 (447-2424) copies/µl, p= 0.040)  vs 1.08 (0.80-1.63), p=0.391). Notably, at follow-up, the levels did not differ between the two groups (RTL: 0.79 (0.73-0.80) vs 0.77 (0.75-0.83), p=0.873), thus indicating that LT-PTM patients tended to have a higher telomere erosion during the same follow-up interval  vs -0.09 , p=0.091).At baseline, relative telomere lengths (RTL) on PBMC were longer, although not statistically significant, in LT-PTM than in mLT-no-PTM patients (RTL: 1.46 (1.03-1.63) de novo malignancies (DNMs) and HCC recurrence are the most common causes of long-term morbidity and death . The patients/participants provided their written informed consent to participate in this study.MRP, SS, MT, PP, DS, PB and ADR, designed the study. MRP, ER, FC, SG, performed the investigations. SS, DS, UC, PB, provided samples and reagents. PDB performed the statistical analysis. MRP wrote the manuscript. SS, MT, SG, PDB, PP, DS, UC, RD, PB and ADR supervised the project, reviewed and editing the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by Ricerca Corrente IRCCS Centro di Riferimento Oncologico, Aviano: Italian Association for Research on Cancer; Grant number: AIRC IG No. 19112; and “Pathogenesis of EBV-driven post-transplant malignancies” granted by Department of Surgery, Oncology and Gastroenterology (DiSCOG), University of Padova, Italy .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.


Bifidobacterium lactis BL-99 (B.lactis BL-99) on the intestinal inflammation and functionsin the zebrafish models. After feeding for 6 hours, B.lactis BL-99 was fully retained in the larval zebrafishintestinal tract and stayed for over 24 hours. B.lactis BL-99 promoted the intestinal motility andeffectively alleviated aluminum sulfate-induced larval zebrafish constipation(p < 0.01). Irregular high glucose diet induced adultzebrafish intestinal functional and metabolic disorders. After fed withB. lactis BL-99, IL-1βgene expression was significantly down-regulated, and IL-10 andIL-12 gene levels were markedly up-regulated in this model(p < 0.05). The intestinal lipase activity was elevatedin the adult zebrafish intestinal functional disorder model afterB. lactis BL-99 treatment(p < 0.05), but tryptase content had no statisticalchanges (p > 0.05). B.lactis BL-99 improved the histopathology of the adultzebrafish intestinal inflammation, increased the goblet cell numbers, andup-and-down metabolites were markedly recovered after treatment ofB. lactis BL-99 (p <0.05). These results suggest that B. lactisBL-99 could relieve intestinal inflammation and promote intestinal functions, atleast in part, through modulating intestinal and microbial metabolism tomaintain intestinal health.This study was designed to explore the therapeutics and the mechanisms of apatented and marked gastric acid and intestine juice-resistant probiotics Probiotics consumption for health promotion and well-being has increased worldwide inrecent years  and variBacillus spp [Bifidobacterium,Lactobacillus, Bacillus, and several otherbacterial species [Aeromonas hydrophila, A.salmonicida, Yersinia ruckeri, andV. anguillarum to intestinal mucus fromrainbow trout (in vitro) [L. rhamnosus also counteracts zebrafishneurotoxicity caused by PFBS [The most studied probiotic candidates in aquaculture belong to the Firmicutes phylum,namely lactic acid-producing bacteria (LAB) and llus spp , 9–13. Allus spp , 15. Stu species –18. Thes species , 20. LAB species ,and somn vitro) . Dietaryn vitro) , and die by PFBS .Bifidobacterium, which makes it difficult to reach and colonizein the intestine through gastric juice [Bifidobacterium lactisBL-99  was originally isolatedfrom the intestines of a Chinese healthy infant [Inability to acid and gastrointestinal juice is a common property ofic juice . Bifidoby infant , 26 and y infant ,28. Thiy infant .B. lactis BL-99 has no exogenous antibioticresistance genes [B.lactis BL-99 was confirmed no dose-dependent mortality andtoxicity throughout multidose oral toxicity tests in mice and rats and thusgenerally recognized as safe (GRAS) status as a probiotic [In vivo experiments inmice showed that B. lactis BL-99 significantlypromoted the growth of intestinal Bifidobacteria and Lactic acidbacteria, and inhibited Desulfovibrio and/orEnterobacter, especially Helicobacter pylori and/orEscherichia-Shiga Bacteria [ce genes  and hasrobiotic . In vivoBacteria , 30. ThiBacteria .The research of probiotics on intestinal microbial balance, intestinal functions,inflammation, and intestinal metabolites, etc. mostly use traditional mammalianmodels. Conventional mammalian enteritis models are chemical-induced, for example,DSS  was used to induce mice colitis , and TNBDanio rerio) intestinal composition is similar to that ofhumans, e.g., connective tissue, external-longitudinal muscle and circular muscle,et al. [B.lactis BL-99 on the digestive enzymes, motility, inflammationand metabolites in the larval and adult zebrafish models.Zebrafish  and adult male zebrafishat 3.5 months post fertilization (3.5 mpf) were used in this study. Zebrafishwere maintained at 28°C in fish water . The zebrafish facility and the laboratory at Hunter Biotechnology, Inc.are accredited by the Association for Assessment and Accreditation of LaboratoryAnimal Care (AAALAC) International , 42, by B. lactis BL-99 was deposited in the ChinaCommon Microbial Culture Collection and Management Center (CGMCC 15650) on April26, 2018 [5’-AGA GTT TGA TCC TGG CTC AG-3’) and 1492R(5’-GGT TAC CTT GTT ACG ACT T T-3’) [B. lactis BL-99 culture was proliferatedwith De Man Rogosa Sharpe (MRS) medium  supplemented with0.05% (w/v) L-cysteine (MRSC) for 12–48 hrs at 37°C aerobically [B.lactis BL-99 was 1.5*1011 CFU / g and preservedat -80°C.26, 2018  andiden T T-3’) . The stawww.dingguo.com). CM-DiI cell-labeling solution  and trizol reagent (cat. # 12183555) were bought from Thermo FisherScientific (China) Co., Ltd. FastKing RT Kit (With gDNase) (cat. # KR116-02) wasbought from TIANGEN BioTec (Beijing) Co., Ltd (www.tiangen.com), and iTaq Universal SYBR(R) Green Supermix waspurchased from BIO-RAD Co., Ltd. (www.bio-rad.com). Fish trypsin ELISA kit (item no. ml064285) wasbought from Shanghai Enzyme-linked Biotechnology Co., Ltd. (www.mlbio.cn). Lipase (LPS) kit (item no.A054-2-1) was bought from Nanjing Jiancheng Bioengineering Institute  (www.njjcbio.com).Tricaine methanesulfonate (cat. # 886-86-2) and aluminum sulfate (cat. #D1909026) were ordered from Shanghai Aladdin Bio-Chem Technology Co., Ltd, nile red (cat. # MKBP6198V) from Sigma-Aldrich , and glucose (lot. # 20201105) was purchased from Sinopharm ChemicalReagent Co., Ltd . Tissue cell fixation solution at 4%concentration (cat. # AR-0211-250 mL) was ordered from Beijing DingguoChangsheng Biotechnology Co., Ltd  containing 0.5% DMSO in PBS [B.lactis BL-99 were treated with larval zebrafish for itsretaining time determination in the intestinal tract and for its effects on theintestinal motility and digestion functions as described below. The dye istransferred from mother to daughter bacteria and fluorescent B.lactis BL-99 were clearly visible in the zebrafishintestinal tract.After collection, O in PBS  at 37°C B. lactis BL-99 at a density of2.42*108 CFU/mL at 28°C. The zebrafish intestinal fluorescentimages were taken periodically at the designated time points to determine theretaining time of this probiotics. After treatment of fluorescentB. lactis BL-99 for 24 hrs, the zebrafishwere transferred into fish water for 4 and 24 hrs, respectively, 10 zebrafishwere randomly selected from each group and at each time point for visualobservation and image acquisition under a fluorescent stereomicroscope , installed with a high-speed video camera .Quantitative image analyses were performed using image-based analysis, the retaining time and lasting period ofB. lactis BL-99 in the larval zebrafishintestine tract were calculated based on the fluorescent intensity. To protectfluorescent B. lactis BL-99 from light-induceddecomposition, experiments were carried out at a constant temperature (28°C) inthe dark. All experiments were performed in duplicate and repeated for at least3 times.Wild-type larval zebrafish at 5 dpf were distributed into 6-well microplates, 30 zebrafish per well in 3 ml fish water and treated withfluorescent B. lactis BL-99at concentrations of 2.42*106, 2.42*107 and2.42*108 CFU/mL, respectively, for 24 hrs. Domperidone was usedas a positive control drug. The zebrafish treated with aluminum sulfate and nilered only served as a model control. The zebrafish without any treatment wereused as a negative control. At the end of treatments, the zebrafish were imagedunder a AZ100 fluorescent stereomicroscope, installed with a high-speed videocamera. The therapeutic effects of B. lactisBL-99 on the larval zebrafish constipation were determined based on theintestinal fluorescent quantitative analyses.The larval zebrafish of AB strain at 5 dpf were distributed into a 6-wellmicroplate, 30 zebrafish per well in 3 ml fish water. The zebrafish constipationmodel was established by treatment with 1 μg/mL aluminum sulfate  at 28°C 6, 2.42*107 and 2.42*108 CFU/mL)were used for B. lactis BL-99 treatment.Untreated control zebrafish were examined in parallel. The adult zebrafish werehoused in a light and temperature-controlled aquaculture facility with astandard 14:10 h light/dark photoperiod. (1) Days 1–3 of the experiment: exceptfor the untreated control zebrafish, the resting groups were not fed and starvedfor 3 days. B. lactis BL-99 groups weretreated with this probiotic at 3 designated concentrations, respectively, asdescribed above in fish water every day during the daytime for 8 hrs and thenlived in fresh fish water; (2) Days 4–17: B.lactis BL-99 groups were treated with this probiotic duringthe daytime for 8 hrs and then transferred into 3% glucose in fish water for 16hrs. The model zebrafish were only treated with 3% glucose for 16 hrs and theuntreated control zebrafish were fed with brine shrimp twice a day. On the 18thday of the experiment, the zebrafish intestinal tissues were collected and theintestinal digestive enzymes, inflammatory and immunity factor genes andhistopathology were examined, respectively, and the interventional effects ofB. lactis BL-99 were assessed.Seventy-five male adult zebrafish of 3.5 mpf (months post fertilization)wild-type AB strain were transferred into 5 L beaker in a volume of 4 Lcontaining 15 zebrafish. In the initial tests, three concentrations, interleukin-10 (IL-10)and interleukin-12 (IL-12) were determined in the adultzebrafish intestines by real-time quantitative PCR (qPCR) [B.lactis BL-99 treatment, total RNA was extracted from 10homogenized zebrafish per group using trizol reagent. About 2 μg total RNA ofeach sample was used for cDNA synthesis using FastQuant RT Kit (With gDNase) andqPCR amplifications were carried out with a CFX Connect detection system  using the iTaq Universal SYBR Green Supermix in which there werethree technical or biological replicates. The qPCR protocol was 2 minutes at95°C-40 cycles of 5 seconds at 95°C-30 seconds at 60°C. Expression data wasnormalized against the expression of β-actin and the relative quantification ofeach gene mRNA among groups was calculated as follows: The relative expressionof RNA = 2^ΔΔC(t); ΔΔC(t) = ΔC(t)Model—ΔC(t)Probiotics;ΔC(t) = ΔC(t)Target gene—ΔC(t)β-actin. The primers used inthis study were as follows: β-ACTIN-FOR:TCGAGCAGGAGATGGGAACC, β-ACTIN-REV:CTCGTGGATACCGCAAGATTC (GenBank accession numbers57934) [IL-1β-FOR: GTCACACTGAGAGCCGGAAG,IL-1β-REV GCAGGCCAGGTACAGGTTAC [IL-10-FOR:TTCAGGAACTCAAGCGGGAT, IL-10-REV:AAGAGCAAATCAAGCTCCCCC  [IL-12-FOR:AACTCCTACAAGCCCAGCAC, IL-12-REV:ACACTCGGTCGTCAAACGAA . Each primer pair was designed usingNCBI/Primer-BLAST.To explore the possible anti-inflammation and the intestinal immune mechanisms ofR (qPCR) . Brieflys57934) , 50,IL- 405770) , IL-10-F 553957) , IL-12-FB. lactisBL-99 on the intestinal functions of the adult zebrafish, ELISA kits were usedto determine the intestinal tissue lipase activity and trypsin content. Theoptical density (OD) values were measured by multifunctional microplate reader at wavelength 595 nm for the protein concentration,580 nm for the lipase activity, and 450 nm for the trypsin content,respectively. The lipase activity and trypsin content per gram of protein inzebrafish intestinal tissues were calculated based on the OD values.In order to evaluate the effects of B. lactis BL-99 intervention, weperformed the gut histopathological examinations on the adult zebrafish. At theend of the experiments, zebrafish intestinal tissues were fixed in 4%paraformaldehyde in 0.1 M phosphate buffered saline for 4 hrs at 4°C, dehydratedin graded series of ethanol solutions before paraffin embedding. Embeddedzebrafish intestines were longitudinally sectioned at 5 μm and stained withhematoxylin and eosin (H&E) [To confirm the intestinal damage caused by the irregular high-sugar diet, and theeffects of in (H&E) , 51.Thip < 0.05 and fold change ≥ 1.2 or fold change ≤ 0.8333and VIP ≥ 1; and statistically significant changes in at least two dose groups.Student’s t test was used for the statistical analyses of the metabolites.Ten adult zebrafish whole guts from each group were used for the intestinalmetabolite extraction and the metabolomic analysis. Twenty-five mg intestinaltissues from each gut were homogenized with 800 μL pre-cold precipitation agent. After sonication on ice for10 minutes, let the mixture stand at -20°C for 120 minutes, followed bycentrifugation at 25000 g for 15 min at 4°C. Six hundred μL of supernatant wastaken and put in a freeze-drying machine to drain and reconstituted in 600 μL of10% methanol solution. After ultrasound and centrifugation, the supernatant waschromatographed using 2777C UPLC system , and the eluted smallmolecules were collected in positive and negative ion modes using Xevo G2-XSQTOF . Metabolite resonances were identified according to theinformation from the Human Metabolome Database (HMDB) and Kyoto Encyclopedia ofGenes and Genomes (KEGG). Significantly changed metabolites between the controland treatment groups were identified following the criteria below:p < 0.05,p < 0.01 and p < 0.001 were allconsidered statistically significant. For quantitative analysis, all data werepresented as mean ± SEM, and results were statistically compared between theprobiotics-treated and model zebrafish groups. All experiments were repeated forat least 3 times. Zebrafish natural death in untreated groups was ≤ 10%, and allintra- and inter-group coefficient of variation (CV) was ≤ 25%.One-way ANOVA followed by the Dunnett’s test was used to compare differencesamong groups. All statistical analyses were performed using the GraphPadsoftware , and B.lactis BL-99 for 2, 6 and 24 hrs, the fluorescentintensities in the larval zebrafish intestinal tracts were 6.02± 0.866,10.7± 1.08 and 13.0 ± 0.601 pixels, respectively. Comparing the fluorescentintensities between 24 hr and 2 hr feeding, p < 0.001,but p > 0.05 when comparing the fluorescent intensitiesbetween 24 hr and 6 hr feeding, suggesting that B.lactis BL-99 effectively retained in the larvalzebrafish intestinal tract after 6 hr feeding.As indicated in B. lactis BL-99from the treatment solutions and transferred the zebrafish into fresh fishwater for 0, 4 and 24 hrs, the larval zebrafish intestinal fluorescence was14.4± 1.31, 11.5± 1.58 and 10.5± 1.57 pixels ,indicating that the larval zebrafish constipation model was successfullyestablished. The positive control drug Domperidone significantly promotedthe intestinal motility . The dose-dependent intestinal fluorescent intensity decreases were found in theconstipation zebrafish treated with B.lactis BL-99 at 2.42*106 (476071 ± 20633pixels), 2.42*107 (456847 ± 15814 pixels) and 2.42*108CFU/mL (414652 ± 11561 pixels), respectively .As demonstrated in IL-1β gene expression. A concentration-dependentdownregulations of the IL-1β gene expression was observedin the model zebrafish treated with 2.42*106, 2.42*107and 2.42*108 CFU/mL of B.lactis BL-99, and the decreases were 0.511± 0.055,0.691± 0.072 and 0.969± 0.049 folds, respectively, relative to the modelgroup .The purity of the extracted RNA (A260/A280) was in the range of 1.95–2.12. Asshown in IL-10 gene expression. After treatment withB. lactis BL-99 at the concentrationsof 2.42*106, 2.42*107 and 2.42*108 CFU/mL,IL-10 and IL-12 expression levels wereelevated to 3.96± 0.219, 1.27± 0.150 and 1.85± 0.176 folds and 1.01± 0.097, 1.51± 0.368 and 4.13±0.745 folds , respectively, relative to the modelgroup .B. lactis BL-99 had no statisticallysignificant effect on the intestinal trypsin content, although it showed anincreased trend as indicated in As shown in B. lactis BL-99 treatmentat 2.42*107 CFU/mL led to the developed high villi, increasedgoblet cells and columnar epithelial cells, and the gut tissue morphologywas closely similar to that of normal zebrafish  adult zebrafish was taken and shown in ebrafish .B. lactis BL-99 with concentration of2.42*107 CFU/mL (BL-99-10-7) and the model group showedcomplete separation , and the degrees of aggregations amongthe BL-99-10-7 treatment groups were obvious. There were 106 positive-ionmetabolites and 218 negative-ion metabolites were statisticallysignificantly changed in the intestines as compared between normal and themodel zebrafish; and 213 positive-ion metabolites and 402 negative-ionmetabolites with significant differences between the model zebrafish and themodel zebrafish treated with B. lactisBL-99.As shown in B.lactis BL-99 (6B). As shown in Tables B.lactis BL-99. Among the 23 significantly differentintestinal metabolites, 13 metabolites were identified with the knownphysiological and pathological functions: citrulline, glycerol,CDP-Ethanolamine, gluconolactone, uridine, uracil, taurine, mesaconic acid,ureidosuccinic acid, orotic acid, 4-hydroxybenzaldehyde,bis-γ-glutamylcystine and R-lipoic acid. The biological significances forthe remaining 10 metabolites below were not known or unclear yet: SAICAR,isonicotinic acid, GDP-d-mannuronate, 3-dehydro-L-gulonate,-3-hydroxybutane-1,2,3-tricarboxylic acid, cob (I) yrinate a,cdiamide, 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol glucuronide,s-(2-chloroacetyl)glutathione,2,4-diacetamido-2,4,6-trideoxy-d-mannopyranose, andcarbamazepine-o-quinone.Heat maps of significantly changed metabolites between the intestinalfunctional disorder zebrafish (model) and normal (untreated) zebrafish wereindicated in B. lactis has been confirmed as a gastric acid andintestinal juice tolerable probiotics [B.lactis BL-99 effectively preserved in the larval zebrafishintestinal tract after 6 hrs of feeding and stayed in the intestinal tract for over24 hrs. B. lactis BL-99 promoted the intestinalmotility and relieved the constipation in aluminum sulfate-induced larval zebrafishmodel. This patented and marked probiotics increased digestive enzyme lipaseproduction, regulated inflammatory and immune responses, and relieved intestinalinflammation in an irregularly high-glucose diet-induced adult zebrafish intestinalfunctional disorder model. These findings imply that B.lactis BL-99 could be an effective and probably potentmodulator of the intestinal functions for both physiological and pathologicalconditions.obiotics  that makL. casei SY13 and exploreits effects on gut microbial structure and diversity in mice, the authors found thatthe stable colonization of L. casei SY13 wasassociated with dosage and treatment days, and thus laid a foundation for studyinginteractions between L. casei SY13 and othermembers of the gut microbiota [B. lactis BL-99 to play itsfunctions in the intestinal health and the disease prevention and treatment.Orally administered probiotics encounter various challenges on their journey throughthe mouth, stomach and intestinal tract. The health benefits of probiotics arediminished mainly due to the substantial reduction of viable probiotic bacteriaunder the harsh conditions in the gastrointestinal cavity and the colonizationresistance caused by commensal bacteria . In a prcrobiota . The lonB. lactisBL-99 promoted the intestinal motility and relief constipation and increased thedigestive enzyme lipase production in the larval and adult zebrafish models,supporting the uses of this probiotics in preventing and treating dyspepsia andmotility disorders.In normal digestion, food is transited through the gastrointestinal tract by rhythmiccontractions called peristalsis. Slow gastrointestinal contractions could lead todigestive function disorders and constipation  that areIL-1β geneexpression, reduced intestinal immune factors IL-10 andIL-12 gene levels, lessened intestinal lipase activity, damagedintestinal histology, and disordered intestinal metabolomics. AfterB. lactis BL-99 treatment, the adult zebrafishintestinal inflammation was alleviated, the intestinal immune responses wereenhanced, and the intestinal mucus barrier and histopathology were ameliorated.Sugar consumption has dramatically increased in the past few decades  and overB.lactis BL-99 treatment recovered these intestinal andmicrobiota metabolites to the levels similar or close to the normal controlzebrafish. These results suggest that B. lactisBL-99 could relieve intestinal inflammation and promote intestinal functions,probably at least in part, through modulating intestinal and microbial metabolism tomaintain intestinal health  and 5 intestinal microbiota-related metabolites were found statistically different in the intestines betweenthe high-glucose fed and untreated control zebrafish. These 11 metabolites, plus 2organic compounds bis-γ-glutamylcystine and R-lipoic acid, were all significantlyincreased in the gut of 3% glucose-fed zebrafish. Surprisedly, l health . These aS1 File(XLS)Click here for additional data file.


Venenivibrio stagnispumantis strain CP.B2T is a thermophilic, chemolithoautotrophic bacterium from the family Hydrogenothermaceae (phylum Aquificota), isolated from Champagne Pool in the Waiotapu geothermal field, Aotearoa-New Zealand. The genome consists of 1.73 Mbp in 451 contigs with a 30.8 mol% G+C content. Venenivibrio, within the phylum Aquificota (family Hydrogenothermaceae), is characterized by thermophilic microaerophilic hydrogenotrophs  of Māori iwi (tribe) Ngāti Tahu-Ngāti Whaoa. The V. stagnispumantis genome has previously been sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) project KMG-II (mana whenua (customary rights) over the bacterium, its genome, and the location in which it was isolated.The bacterial genus notrophs –3. The tt KMG-II   was cultivated using a modified MSH medium  within a headspace consisting of N2/H2/CO2/O2 at ratios of 50:40:7.5:2.5 (vol/vol), respectively (−1) of CP.B2T was performed using a NucleoSpin Soil kit  according to the manufacturer’s protocols. Whole-genome sequencing  was undertaken using the Illumina HiSeq 2500 platform with TruSeq DNA Nano (550) library preparation for paired-end 101-bp reads . Default parameters were used for all assembly, quality control (QC), and annotation software unless otherwise specified. A total of 3.8-Gbp raw sequences (37.32 million reads) were assembled using SPAdes v3.12.0 (JAPEIW010000000) using the GeneMarkS-2+ protein reference set. A functionally equivalent annotation of 47 scaffolds using the Integrated Microbial Genomes annotation pipeline v4.16.4 .The V. stagnispumantis CP.B2T, Sulfurihydrogenibium yellowstonense SS-5T, and Persephonella marina EX-H1T genomes gave <80% similarity for each, confirming the designation of Venenivibrio as a separate genus to sister genera Sulfurihydrogenibium and Persephonella.A pairwise average nucleotide identity (ANI) comparison using FastANI v0.1.3  of the VV. stagnispumantis CP.B2T genome were deposited in the European Nucleotide Archive under the BioProject accession no. PRJEB55610. The assembled genome was deposited in the Genomes Online Database (Ga0591133), for associated annotation with the Integrated Microbial Genomes & Microbiomes platform (2799112217). This Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under accession no. JAPEIW010000000. The version described in this paper is version JAPEIW010000000.1.Raw sequences for the platform  (IMG gen


Enterococcus spp. lower urinary tract infections (UTI). With this rationale, our clinical microbiology laboratory discontinued routine identification on Enterococcus urine isolates in 2012 and report “aminopenicillins are predictably reliable for uncomplicated enterococcal UTI”. The study objective was to compare outcomes of patients treated with aminopenicillins (AP) versus non-aminopenicillins (NAP) for enterococcal cystitis.Aminopenicillins achieve urinary concentrations that overcome aminopenicillin resistance in E. faecalis, enterococcal UTI in past year, review of systems unavailable/altered mental status, urinary instrumentation except for stent/catheter, systemic infection, fever, genitourinary trauma, renal transplant. Primary endpoint: clinical and microbiologic success at 14 days, defined as resolution of symptoms without new symptoms and no repeat culture growth of index organism. Logistic regression evaluated characteristics associated with 14-day failure. Sample size of 178 calculated for non-inferiority using α=0.025, β=0.8, 15% non-inferiority margin.IRB approved, retrospective cohort of adults hospitalized with symptomatic enterococcal cystitis from 2013-2021. Exclusion: definitive 178 subjects included, 89 AP, 89 NAP . VRE identified: 73 (82%) AP and 76 (85%) NAP (P=0.50). Amoxicillin  and ampicillin  used most in AP. Linezolid  and fosfomycin  most common agents in NAP. 14-day clinical composite endpoint was no different between AP and NAP groups, respectively . No variables independently predicted failure (Table 1). Non-inferiority analysis for AP vs. NAP for 14-day composite: mean difference 1.1% . Definite E. faecium subgroup: 14-day clinical composite success for was no different between AP and NAP groups, respectively .E. faecium. This stewardship strategy has implications to preserve VRE active therapies (e.g. linezolid) for serious infections.AP were non-inferior to NAP, supporting their use as first-line therapy for cystitis due to enterococci, including All Authors: No reported disclosures.


Ocimum tenuiflorum L. This study evaluated the antibacterial activity of O. tenuiflorum extract and its interaction with antibacterial drugs against common mastitis pathogens including Staphylococcus aureus, coagulase-negative Staphylococci (CNS), Streptococcus agalactiae, and Escherichia coli. Anti-inflammatory activities in LPS-stimulated RAW264.7 macrophage cells were also studied. The O. tenuiflorum extract exhibited antibacterial activities against S. aureus, CNS, and S. agalactiae with minimum inhibitory concentration (MIC) ranging from 3.9 to 31.2 µg/mL and minimum bactericidal concentration (MBC) ranging from 15.6 to 500 µg/mL. Combinations of O. tenuiflorum with penicillin or amoxicillin-clavulanic acid showed synergistic effects against all tested strains but an additive effect with cefazolin and gentamicin. Pretreatment of the extract significantly decreased the expression of inflammatory molecules  generated by LPS in macrophages. Results suggested O. tenuiflorum effectiveness against various Gram-positive mastitis bacteria, with the potential to reduce antibacterial doses and combat inflammation.Mastitis is the most prevalent global illness affecting dairy cows. This bacterial infection damages and inflames the udder tissues. Several plant extracts have demonstrated synergistic antibacterial activities with standard drugs in mastitis treatment. Scant information exists on  Staphylococcus aureus (S. aureus), Streptococcus agalactiae , Escherichia coli (E. coli), Enterococcus spp., and coagulase-negative Staphylococci (CNS) -bis(4-methoxy6-nitro) benzene sulfonic acid hydrate (XTT), N-methyl dibenzopyrazine methyl sulfate (PMS) were obtained from Sigma-Aldrich . The 2x qPCRBIO SyGreen 1step Lo-ROX was obtained from PCR Biosystems . Tri-RNA Reagent was purchased from Favorgen . IL-6 and PGE2 quantitative sandwich ELISA kits were obtained from Abcam . The Griess reagent was purchased from Promega . All other reagents were obtained from Sigma-Aldrich unless otherwise describedLipopolysaccharide (LPS) from O. tenuiflorum were cleaned with distilled water twice. Then, 500 g of sample was dried at 60 °C and then powdered into fine powder. Two liters of 70% ethanol were added to powdered dried plants and allowed to remain for 24 h at room temperature. The mixture was filtered and evaporated using a rotary evaporator to eliminate the ethanol. The liquid was subsequently freeze-dried and stored at −20 °C until used.Leaves of v/v) formic acid). Authentic standards consisted of syringic acid (>97.0% T), sinapic acid , quercetin , naringenin , myricetin (>97.0% HPLC), luteolin (>98.0% HPLC), kaempferol (>97.0% HPLC), hydroxybenzoic acid , 4–hesperidin , genistein (>98.0% HPLC), ferulic acid , (−)-epigallocatechin gallate (>98.0% HPLC), 3,4-dihydroxybenzoic acid (≥97% T), p-coumaric acid , cinnamic acid (>98.0% HPLC), chlorogenic acid , caffeic acid  and apigenin (>98.0% HPLC) from Tokyo Chemical Industry , vanillic acid (≥97% HPLC), rutin (≥94% HPLC), rosmarinic acid (≥98% HPLC) and gallic acid (97.5–102.5% T) from Sigma-Aldrich , galangin (≥98.0% HPLC) from Wuhan ChemFaces Biochemical Co., Ltd.  and isorhamnetin (≥99.0% HPLC) from Extrasynthese . The LC–ESI-MS/MS chromatograms were shown in The phytochemical profile was analyzed using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) with the conditions and validation following a well-established protocol as previously reported  without S. aureus, S. agalactiae, CNS, and E. coli from clinical bovine mastitis cases were obtained from milk samples and collected from the Dairy Farming Promotion Organization of Thailand (D.P.O.), Saraburi, Thailand. Microorganism isolates were characterized based on their culture, morphological (Gram stain), and biochemical properties and sub-cultured on the selective medium following standard microbiological techniques -bis (4-methoxy-nitro) benzene sulfonic acid hydrate (XTT)-based assay to determine the concentration of 5 cells/well) or 6-well plates (1 × 106 cells/well) and then pretreated for 12 h with media containing different concentrations of O. tenuiflorum extract  before stimulation with LPS (10 ng/mL) for 24 h. Culture supernatants were collected from 96-well plates for interleukin-6 (IL-6), nitric oxide (NO), and prostaglandin E2 (PGE2). Cells were harvested from the 96 or 6-well plates for qPCR analysis.RAW 264.7 cells were cultured overnight in 96-well plates (1 × 10v/v) ratio with Griess reagent -ethylenediamine). After incubation for 10 min at room temperature, absorbance was measured at 540 nm using a microplate reader . A nitrite standard curve was used to calculate nitrite concentration in the supernatant.Nitric oxide generation was assessed by measuring the quantity of nitrite in the culture medium based on the Griess reaction . FollowiO. tenuiflorum extract on LPS-induced RAW 264.7 cell inflammation, the relative mRNA levels of IL-6, tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) were measured by RT-qPCR. Total RNA was extracted by homogenizing the cells in Tri-RNA Reagent according to the manufacturer’s instructions. The RT-qPCR reaction mixture, qPCRBIO SyGreen 1-step Lo-ROX , was made according to the manufacturer’s guidelines. Quantitative polymerase chain reaction (qPCR) was performed by qTOWER3 Real-Time PCR Systems . Thermal cycling conditions were used to amplify the target genes using the following parameters: reverse transcription step at 45 °C for 10 min, polymerase activation step at 95 °C for 2 min, denaturation step at 40 amplification cycles at 95 °C for 5 s, and the final step at 60 °C for 30 s. Relative levels of gene expression were normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA using the 2−ΔΔCT method [To investigate the effects of The levels of IL-6 and PGE2 in RAW 264.7 cell culture supernatants were measured using an enzyme-linked immunosorbent assay (ELISA) kit obtained from Abcam  and performed according to the manufacturer’s instructions.p ≤ 0.05) was considered statistically significant.Statistical analysis was performed using GraphPad Prism ver. 5 software. The values are presented as mean ± standard deviation (SD) from at least three independent replicates. Statistical significance between groups was determined using a one-way ANOVA followed by Tukey’s test. Statistical significance between groups was determined using a one-way ANOVA followed by Tukey’s test. A probability of 0.05 or less (O. tenuiflorum ethanolic extract as follows: (i) O. tenuiflorum had antibacterial effects against Gram-positive bacteria including S. aureus, CNS, and S. agalactiae but not Gram-negative bacteria, (ii) O. tenuiflorum extract showed synergistic effects with penicillin or amoxicillin-clavulanic acid against all tested strains, while cefazolin and amikacin had an additive effect, and (iii) O. tenuiflorum extract showed anti-inflammatory activities, with reduced expression of inflammatory molecules in LPS-treated macrophages. However, further investigations on route and dosage for therapy in animal models are required.This study explored new antibacterial candidates from plants with multi-target abilities in mastitis treatment, covering antibacterial and anti-inflammation activities. Results demonstrated promising anti-mastitis properties of


JCI Insight. 2019;4(13):e125191. https://doi.org/10.1172/jci.insight.125191Original citation: JCI Insight. 2022;7(20):e165600. https://doi.org/10.1172/jci.insight.165600Citation for this corrigendum: The authors recently became aware that representative illustrations presented in n-3 DPA (n-3 DPA), including the gut-protective RvD5n-3 DPA (27) (Using liquid chromatography–tandem mass spectrometry–based (LC-MS/MS–based) LM profiling, we identified mediators from all 4 major fatty acid bioactive metabolomes, including lipoxygenase- and cyclooxygenase-derived LMs that were identified in accordance with published criteria (33). The identity of each of the mediators was further corroborated by evaluating MS/MS spectra obtained in a subset of the samples analyzed and matching at least 6 diagnostic ions with those obtained for reference standards for each of these molecules, as shown for RvD5n-3 DPA  (23). Mun-3 DPA . This sh


Dear Editor,1 However, its function in subverting host translation machinery is still elusive.COVID-19 (Coronavirus Disease 2019) is causing an unprecedented public health crisis. Protein translation is crucial for virus lifecycle. Nucleocapsid (N) protein is among the most abundant SARS-CoV-2 proteins and highly conserved across coronavirus genus.2 , indicating that N mRNAs were much less efficiently translated after NPM1 depletion Fig. . SimilarIn IVT assays, ribosomes from 293T cells with exogenous N showed enhanced translation efficiency when translating N mRNAs, which was suppressed upon NPM1 knockdown Fig. , top row3 We therefore hypothesized that N protein functions via NPM1-binding snoRNAs. We first re-analyzed snoRNA expression in different tissues using public data from ENCODE,4 and found significant overlap of expression profile among lung, liver, and intestine (16/top 20, Supplementary Fig. 3 and their expression was highly correlated with ACE2, TMPRSS2, FURIN (Fig. 5 (Fig. NPM1 has been shown to function as RNA/DNA binding protein regulating 2′-O-methylation of rRNA via direct binding of snoRNAs.RIN Fig. . Exploit. 5 Fig. . This wa. 5 Fig. . Besides. 5 Fig. . Knockdo. 5 Fig. , h. Besi. 5 Fig. .SNORD93 was predicted to target A576 on 18S rRNA for 2′-O-Me modification Fig. , which iWe next explored strategy for SARS-CoV-2 prevention via targeting N protein-related translation machinery components. SARS-CoV-2 infection also enhanced 2′-O-Me modification, as was detected by RTL-P assay (Supplementary Fig. In summary, we found that SARS-CoV-2 N protein enhances host translation efficiency by potentiating the host NPM1-snoRNA translation machinery. By interacting with NPM1 and snoRNAs, N protein significantly promotes ribosome translation efficiency, particularly for viral mRNAs, via enhancement of snoRNA-mediated 2′-O-methylation on rRNAs (Supplementary Fig. Supplementary information


Gordonia rubripertincta NRRL B-16540. Survivors has a 45,436-bp genome encoding 69 predicted protein-coding genes, of which 32 have assigned functions. Based on gene content similarity to sequenced actinobacteriophages, Survivors is assigned to phage cluster CT.Bacteriophage Survivors is a siphovirus isolated from  Gordonia bacteria are opportunistic human pathogens with varied, important roles in bioremediation , using standard protocols from the Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science (SEA-PHAGES) Phage Discovery Guide . The soirphology . The caphttps://phagesdb.org/media/workflow/protocols/pdfs/PCI_SDS_DNA_Extraction_2.2013.pdf), prepared for sequencing using the New England BioLabs Ultra II library kit, and sequenced at the Pittsburgh Bacteriophage Institute using Illumina MiSeq (v3 reagents). There were 236,073 150-base single-end reads providing 735× coverage. The raw reads were assembled and checked for completeness using Newbler v2.9 and Consed v29, respectively, using default settings (CGGTAGGCAT-3′). Genome termini were determined through similarity to known phages, an analysis of read start buildups, and coverage levels across the genome (http://phagesDB.org), Survivors was assigned to cluster CT  (:1 (httpshttp://cobamide2.bio.pitt.edu), Glimmer (v3.02b) (http://phages.wustl.edu/starterator/), Phamerator (Actino_Draft v462)  (ft v462) , BLASTp ft v462) , HHPred ft v462) , ARAGORNft v462) , tRNAscaft v462) , TMHMM (ft v462) , and SOSft v462) . DefaultON970576 and has been assigned Sequence Read Archive (SRA) no. SRX14485091.Survivors GenBank accession no. is


Stolephorusbengalensis  or Stolephorusinsularis Hardenberg, 1933, revealed four distinct species, true S.bengalensis  and three new species, viz., Stolephoruseldoradosp. nov. , Stolephorusdiabolussp. nov.  and Stolephoruseclipsissp. nov. . Characters separating the four species include numbers of gill rakers on each gill arch and vertebrae and pelvic fin and dorsal-fin ray lengths. Two molecular markers  demonstrated the distinction of three of the species examined morphologically and enabled a reconstruction of their phylogenetic relationships. Each species was genetically divergent from the others by 3.5%–7.7% mean uncorrected distance in the mitochondrial cytochrome oxidase I gene.Examination of numerous specimens characterised by predorsal scute, long maxilla, indented preopercle and pelvic scute lacking a spine and previously identified as  Stolephorus Lacepède, 1803 (Teleostei: Clupeiformes: Engraulidae), diagnosed by the presence of prepelvic scutes and an embedded urohyal and lack of postpelvic scutes, currently includes 37 valid species that preferentially inhabit marine and/or estuarine waters in the Indo-Pacific region S.insularis as Stolephorusbengalensis  and regarding the nominal species S.insularis as a junior synonym of Stolephorustri . However, subsequent re-examination of specimens, identified as S.bengalensis, in fact revealed the presence of four species.The anchovy genus c region . AmongstS.bengalensis and describe three new species of Stolephorus from specimens previously regarded as S.insularis or S.bengalensis. In addition to the morphological comparisons, complete mitochondrial cytochrome b gene and partial mitochondrial cytochrome oxidase I (COI) gene sequences from 31 specimens were used to estimate the genetic distinction of three of the latter (the fourth species unavailable) plus one unidentified, but related species from Segara Anakan Lagoon, Central Java, Indonesia  cytochrome b gene and partial (648 bp) COI gene. The cytochrome b gene sequences were published in COI gene was newly sequenced for 19 specimens of S.eldorado, including the holotype and several paratypes (Table COI sequences (available in GenBank) of S.diablocus , S.bengalensis (eight specimens from India), S.eldorado   species of PCR) amplification and sequencing of the COI gene followed standard protocols (COI gene used the following primers: forward COI_FishF1 (5’-TCA ACC AAC CAC AAA GAC ATT GGC AC-3’) and reverse COI_FishR2 (5’-ACT TCA GGG TGA CCG AAG AAT CAG AA-3’)  . PCR prob and COI sequences were determined separately by eye, requiring neither insertions nor deletions. The final alignment combining the two genes (for 31 specimens plus one outgroup) comprised 1788 nucleotide positions. Uncorrected pairwise genetic distances (i.e. p-distances) amongst species were calculated with MEGA X (ML) method of phylogenetic reconstruction using the general time-reversible model of nucleotide substitution with rate heterogeneity following a discrete gamma distribution (GTR + Г), using the software RAxML-NG (S.acinaces and the robustness of each node determined by bootstrap support (500 replicates).Alignments of the cytochrome h MEGA X . The relRAxML-NG  as impleRAxML-NG . The treTaxon classificationAnimaliaClupeiformesEngraulidae67E69026-8C76-5B86-84F8-C5E877CDE39CAnchoviellabaganensisbengalensis Dutt & Babu Rao, 1959: 160  and the anal-fin origin located below the origin of the second to sixth dorsal-fin ray (vs. eighth to eleventh)  in having a predorsal scute and double pigment lines on the dorsum behind the dorsal fin, but differ in having deciduous body scales  and lacking a spine on the pelvic scute (pelvic scute with a hard posteriorly projecting spine)  . Stolephg spine) . CompariStolephorusbengalensis, S.diabolus sp. nov. and S.eldorado sp. nov. were divergent from each other by at least 3.5% COI-based mean uncorrected genetic distance (min-max = 3.5–7.7%) , forming clear intraspecific versus interspecific genetic gaps. The ML phylogenetic tree using COI and cytochrome b markers : IPMB-I 13.00001, 49.7 mm SL, Teluk Bahang, Penang, Malaysia.USMFC 82-0017, 43.7 mm SL, collected with the holotype; USMFC 82-0057, 4 specimens, 40.1–41.1 mm SL, estuary of Merbok River, Jeti Semeling, Malaysia; ZUMT 62056, 5 specimens, 28.5–38.4 mm SL, KAUM–I. 163702, 36.3 mm SL, KAUM–I. 163703, 36.4 mm SL, NSMT-P 143554, 36.4 mm SL, NSMT-P 143555, 36.6 mm SL, Singapore.14 specimens, 28.5–43.7 mm SL. Stolephorus with the following combination of characters: 1UGR 14–16 , 1LGR 20–23 (22), 1TGR 35–38 (38); 2UGR 10 or 11 (11), 2LGR 19 or 20 (20), 2TGR 30 or 31 (31); 3UGR 8 or 9 (9), 3LGR 11 or 12 (12), 3TGR 20 or 21 (21); 4UGR 6 or 7 (7), 4LGR 9 or 10 (9), 4TGR 15–17 (17); prepelvic scutes 5–7 (6); total vertebrae 39; long maxilla, posterior tip just reaching or slightly short of posterior margin of opercle; predorsal scute present; pelvic scute without spine; body scales deciduous; posterior border of pre-opercle concave, indented; paired dark patch on parietal area with little following pigmentation; distinct double pigment lines along dorsum posterior to dorsal fin; black spots below eye and on lower-jaw tip absent; anal-fin base long, 19.8–22.3% (mean 20.7%) of SL; maximum orbit diameter 8.1–8.7% (8.3%) of SL; third dorsal-fin ray short, 17.0–18.5% (18.0%) of SL; pelvic fin rather long, 9.6–11.3% (10.0%) of SL, its posterior tip not reaching to vertical through dorsal-fin origin when depressed in specimens > 40 mm SL; distance between posterior ends of supramaxilla and maxilla 5.7–6.4% (6.1%) of SL.A species of Data for holotype presented first, followed by data for paratypes in parentheses (if different). Counts and measurements, expressed as percentages of SL or HL, given in Tables Body uniformly pale white. A pair of distinct dark patches on parietal region, with little pigmentation on occipital area. No black spots below eye and on lower-jaw tip. Melanophores scattered on posterior margins of scale pockets on dorsum. Double pigmented lines dorsally posterior to dorsal fin. Melanophores scattered along bases of dorsal and anal fins. All fins transparent, melanophores scattered along fin rays of caudal fin and anterior parts of dorsal and anal fins.Stolephorusdiabolus sp. nov. is currently known only from the western coast of the Peninsular Malaysia (Merbok River Estuary and Penang) and Singapore ; 2TGR, 30 or 31 in S.diabolus [vs. 33 or more (rarely 30 or 31 in S.eldorado)]; 3TGR, 20 or 21 in S.diabolus [vs. 22 or more in the other three species (rarely 21 in S.eldorado)]; and 4TGR, 15–17 in S.diabolus (vs. 17 or more)  of SL in S.diabolus vs. 8.2–9.9% (8.9%) in S.eldorado; Fig. S.diabolus is distinguished from S.bengalensis by having a shorter third dorsal-fin ray , shortesis Fig.  and fewesis Fig. .