There have been limited data on the impact of hyperuricemia on long-term clinical outcomes after percutaneous coronary intervention (PCI) for in-stent restenosis (ISR).From January 2009 to July 2015, 317 patients who underwent repeat PCI for ISR were divided into two groups: patients with normal serum uric acid (UA) levels  and patients with higher serum UA levels (higher UA group). The higher UA group included patients with serum UA levels > 6.8 mg/dL or patients who were taking anti-hyperuricemic medication.p = 0.389, log-rank p = 0.367). Follow-up angiographic data showed similar outcomes of late lumen loss  and binary restenosis rate . Multivariate Cox regression analysis indicated higher levels of low-density lipoprotein cholesterol  and lower left ventricular ejection fraction , but not UA levels, to be the independent risk predictors of MAE.During a median follow-up period of 1088 days, the cumulative incidence rates of major adverse event (MAE), including a composite of all-cause death, non-fatal myocardial infarction, and any revascularization, were similar between the two groups  contains supplementary material, which is available to authorized users. Drug-eluting stent (DES) implantation has remarkably decreased the in-stent restenosis (ISR) rate compared with bare metal stent (BMS) implantation . Long-teMany clinical, lesional, and procedural risk factors for ISR have been reported, including diabetes mellitus, chronic kidney disease, complex lesion, balloon injury, and stent underexpansion –12. PathUric acid (UA) is the main metabolite of purines in the human body . A hyperWe screened all consecutive patients who underwent PCI at Korea University Anam Hospital between January 2009 and July 2015. Among them, 353 patients had ISR lesions (> 50% restenosis in the stent or within 5 mm of the stent edges) and underwent repeat PCI for ISR lesions. Thirty-six patients had missing data on serum UA level and were excluded. Finally, 317 patients (328 lesions) were analyzed in this study. Clinical events were monitored until June 2016 through medical record reviews and telephone calls. The present study was approved by the hospital’s institutional review board (IRB no. AN16238-002) and performed in accordance with the Declaration of Helsinki. The need for written informed consent was waived owing to the retrospective nature of the study.A serum UA level of > 6.8 mg/dL was defined as hyperuricemia for both sexes . This cuThe primary end point, major adverse event (MAE), was defined as a composite of all-cause death; non-fatal myocardial infarction; any revascularization, including target-vessel revascularization (TVR) and non-TVR; and coronary artery bypass graft surgery. Myocardial infarction was defined as present when patients had elevated cardiac enzymes with compatible symptoms or electrocardiographic findings. Stent thrombosis was defined as definite stent thrombosis based on Academic Research Consortium Criteria .Interventional procedures were performed according the standard clinical guidelines. Interventional strategies, including drug-coated balloon (DCB) angioplasty, DES implantation, and use of adjunctive devices and pharmacotherapy, were decided according to the operators’ discretion. Balloon pre-dilatation was performed for all ISR lesions. The first-generation DES included CYPHER®  and TAXUS™ . The second-generation DES included XIENCE™ series  and Endeavor® series . The third-generation DES included BioMatrix  and Nobori . The DCB  became available and was used from July 2010.Laboratory profiles, including lipid panel, creatinine, glucose, hsCRP, and UA levels, were obtained within 4 weeks before the index PCI or at the index admission date. Serum UA level was measured by using an enzymatic method with an automatic biochemistry analyzer . Creatinine clearance was calculated using the Cockcroft and Gault formula .Three radiologic technologists blinded to the patients’ treatment performed analyses with a quantitative coronary angiographic system . By using the guiding catheter for magnification-calibration, the diameter of the reference vessel, minimal luminal diameter, and percent diameter stenosis were measured from diastolic frames in a single, matched view showing the smallest minimal luminal diameter. ISR lesions were classified according to the Mehran classification . Multifot test (or Wilcox test) for continuous variables were performed. Kaplan–Meier survival curves with a log-rank test were generated to compare the long-term incidence of MAE between the two groups. In order to identify the risk predictors of MAE, the multivariate Cox proportional hazard model was used to evaluate the possible contributing factors. The following variables were included in the Cox regression model: age, sex, body mass index, current smoking, hypertension, diabetes mellitus, acute myocardial infarction at the index PCI, low-density lipoprotein (LDL)-cholesterol level, triglyceride level, UA level, creatinine clearance, left ventricular ejection fraction (LVEF), previous first-generation DES implantation, multivessel involvement, chronic total occlusion lesion, ISR type , and PCI type (DES or DCB). Hazard ratios with 95% confidence intervals and p-values were reported. All tests were two-tailed, and p-values < 0.05 were considered statistically significant. All statistical analyses were performed using SPSS software .Categorical variables are reported as count (percentage), and continuous variables are reported as mean ± standard deviation. To compare the baseline clinical characteristics, angiographic features, procedural details, and the cumulative incidence of clinical events between the higher UA and normal UA groups, the chi-square test for categorical variables and Student’s p = 0.002). There was no significant difference between the baseline and follow-up UA levels in the higher UA group . The significant difference in serum UA levels between the normal UA group and the higher UA group was maintained at the follow-up measurement .The baseline characteristics of 317 patients who underwent PCI for ISR lesions are presented in Table p = 0.03) and lower creatinine clearance . The higher UA group showed a trend of higher body mass index than the normal UA group .The serum UA level was 7.4 ± 1.6 mg/dL in the higher UA group and 4.9 ± 1.1 mg/dL in the normal UA group (p < 0.001). The higher UA group had more men . The stent diameter was statistically larger in the higher UA group than in the normal UA group . Qualitative comparative analysis data also showed a trend of larger target lesion reference vessel diameter in the higher UA group than in the normal UA group , the cumulative incidence rates of MAE were similar between the two groups . Multivariate Cox regression analysis revealed that high LDL-cholesterol level and low LVEF were independent predictors of MAE  because of their limited usage (36.9%). Considering that mechanical and technical factors may contribute to ISR, detailed lesional information could provide an insight into the clinical relevance of hyperuricemia. Therefore, our findings should be extended and validated further by other studies.The non-focal-type ISR lesion was more frequent in patients with hyperuricemia. However, hyperuricemia was not associated with poor clinical outcomes after repeat PCI for ISR lesions. Serum LDL-cholesterol level and LVEF were independent risk predictors of poor clinical outcomes.Additional file 1:Table S1. Changes in serum uric acid level, Table S2. In-stent restenosis patterns at the index procedure, Table S3. Cumulative incidence of clinical events between patients with lower uric acid level (≤6.8 mg/dL) and those with higher uric acid level (> 6.8 mg/dL), Table S4. Cumulative incidence of clinical events between patients with lower uric acid level (≤5.3 mg/dL) and those with higher uric acid level (> 5.3 mg/dL), Table S5. Subgroup analyses of the cumulative incidence of clinical events between the low uric acid group and the high uric acid group, Table S6. Cox-proportional hazard models for non-target vessel revascularization, Figure S1. Kaplan–Meier curve for major adverse event between patients with lower uric acid level (≤5.3 mg/dL) and those with higher uric acid level (> 5.3 mg/dL). UA, uric acid. (DOCX 134 kb)


Going back to their discovery in the early 1980s, both the Human T-cell Leukemia virus type-1 (HTLV-1) and the Human Immunodeficiency Virus type-1 (HIV-1) greatly fascinated the virology scene, not only because they were the first human retroviruses discovered, but also because they were associated with fatal diseases in the human population. In almost four decades of scientific research, both viruses have had different fates, HTLV-1 being often upstaged by HIV-1. However, although being very close in terms of genome organization, cellular tropism, and viral replication, HIV-1 and HTLV-1 are not completely commutable in terms of treatment, especially because of the opposite fate of the cells they infect: death versus immortalization, respectively. Nowadays, the antiretroviral therapies developed to treat HIV-1 infected individuals and to limit HIV-1 spread among the human population have a poor or no effect on HTLV-1 infected individuals, and thus, do not prevent the development of HTLV-1-associated diseases, which still lack highly efficient treatments. The present review mainly focuses on the course of HTLV-1 infection, from the initial infection of the host to diseases development and associated treatments, but also investigates HIV-1/HTLV-1 co-infection events and their impact on diseases development. Human T-cell Leukemia Virus type-1 (HTLV-1) was first described by Robert Gallo’s team in 1980 , before HTLV-1 inter-individual transmission has been associated with three main modalities: a vertical transmission from mother-to-child that occurs after prolonged breast-feeding , non-proIn infected individuals, HTLV-1 proviral DNA, i.e., HTLV-1 full-length integrated viral genome, is mainly found in activated CD4+ T-cells . In addiHTLV-1 and HIV-1 viral particles have been morphologically described . ContrarIn vitro, three cell-to-cell transmission mechanisms have been reported so far for HTLV-1: the viral synapse , the virIn vivo, HTLV-1 spread occurs through two mechanisms: neo-infection (the mechanisms of which were described above) or clonal expansion of infected cells . Clonal In three recipients who acquired HTLV-1 infection following transplantation from an HTLV-1 infected donor, kinetics of early HTLV-1 infection suggested that neo-infection and clonal expansion  occurredDendritic cells are believed to play a significant role in the initial steps of HTLV-1 dissemination. Not only are dendritic cells more sensitive to HTLV-1 infection than autologous T-cells , they arTransfer of HTLV-1 virus from dendritic cells to CD4+ T-cells or between CD4+ T-cells themselves through neo-infection mechanisms generates several infected CD4+ T-cell clones, each clone being defined by a unique integration site of HTLV-1 provirus within the host genome. Tax-mediated immortalization of HTLV-1 infected T-cells, and their subsequent mitotic divisions, will lead to the presence of expanded clones of HTLV-1 infected T-cells in infected individuals, which may persist for decades . Even thversus 43 months, respectively [ATLL was described before HTLV-1 discovery , but theectively . In addiectively . Symptomectively . Their pectively ,84,85. Cectively . These pectively . AnotherDrosophila melanogaster and mice expressing Tax [tax gene [tax  and IFN-α showed high response rates in several clinical studies ,168, espIn the last 5 years, several isolated studies have focused on additional promising drugs that inhibit ATLL cell proliferation or induce cell death by several mechanisms. Among them are chemotherapeutic molecules such as lenalidomide  or borteContrary to ATLL, for which current therapies are mainly targeting HTLV-1-infected cells F, the maBecause the majority of TSP/HAM treatments are designed to suppress clinical symptoms rather than eliminate HTLV-1-infected cells, research is now focusing on drugs that could modulate anti-HTLV-1 immune response and induce a decrease in HTLV-1 proviral load. However, as infected cells mainly spread through mitotic divisions, infected cells may not expose viral antigens for immune recognition. One option thus consists in using additional drugs that first induce viral gene expression. For instance, valproate, a histone deacetylase inhibitor, induces HTLV-1 proviral gene expression and can therefore expose virus-infected cells to immune response, notably to HTLV-1-specific cytotoxic lysis. Valproate long-term treatment is safe, but does not improve motor disability . AnalysiStrongyloides stercoralis treatment has been reported in HTLV-1-infected patients compared to HTLV-1 seronegative individuals [Strongyloides stercoralis dissemination. Unfortunately, Strongyloides stercoralis infection stimulates HTLV-1 clonal expansion in asymptomatic individuals [Strongyloides stercoralis infection, HTLV-1-infected individuals with infective dermatitis have an increased abundance of HTLV-1 positive clones [Strongyloides stercoralis and infective dermatitis [Uveitis treatment is based on topical and systemic corticosteroids, in addition to lubricating drops which are used to prevent subsequent ocular complications . Dermatoividuals . This waividuals , thus maividuals . Similare clones . Thus, irmatitis .As discussed above, HIV-1/HTLV-1 co-infection can worsen the clinical outcome of HTLV-1 infection. Indeed, the lifetime risk of TSP/HAM is higher in HIV-1/HTLV-1 co-infected patients than in HTLV-1 mono-infected patients. Moreover, this lifetime risk is even higher in co-infected patients under ART, which seems responsible for neurological complications ,158,206.There is no vaccine to prevent or cure HIV-1 or HTLV-1 infections. The idea of developing an HTLV-1 vaccine already emerged in the 1980s, and it seemed at first easier than developing an HIV-1 vaccine . The feaA therapeutic vaccine based on autologous dendritic cells pulsed with CD8+-specific Tax antigens induced sustained immune responses and showed promising effects on three ATLL patients either by stabilizing disease progression or inducing a partial remission . HoweverMore than three decades of HIV-1 and HTLV-1 studies have greatly improved knowledge regarding their viral cycle as well as the patients’ management. Yet, complete remission of both viruses is not fully achieved, especially with the absence of a preventive or prophylactic vaccine. Furthermore, the lack of an efficient treatment for HTLV-1-associated diseases greatly impedes HTLV-1 cure. Development of new drugs is thus strongly needed. This could, in particular, help to treat HIV-1/HTLV-1 co-infected patients for whom therapeutic options focused on HIV-1 currently worsen HTLV-1-associated clinical outcome. In addition, large-scale clinical studies of HIV-1/HTLV-1 co-infected patients are still necessary to better understand the mutual viral interplay and its influence on diseases development. Recently, an HTLV-1 taskforce was launched by the Global Virus Network, in order to expand epidemiological studies, to increase research on HTLV-1 persistence mechanisms, replication and pathogenesis, to discover effective treatments, but also to develop a vaccine against HTLV-1 . This in


Jasmonates (JAs) are a class of plant hormones that play essential roles in response to tissue wounding. They act on gene expression to slow down growth and to redirect metabolism towards producing defense molecules and repairing damage. These responses are systemic and have dramatic impacts on yields, making JAs a very active research area. JAs interact with many other plant hormones and therefore also have essential functions throughout development, notably during plant reproduction, leaf senescence and in response to many biotic and abiotic stresses. Pseudomonas syringae  are a class of oxidized lipids (oxylipins) that derive from α-linolenic acids (α-LAs). The best-described bioactive JA is (+)-7-iso-Jasmonoyl-L-isoleucine (JA-Ile)  Fig. 1)1). The bSolanum lycopersicum) or female  sterility, indicating an important function in fertility [JAs are produced in response to tissue damage, whether caused by necrotrophic pathogens, insects, herbivores, or mechanical stress. Interestingly, in response to a local stimuli  it is observed that tissues located distally from the bite also produce defense molecules . The sysertility . HoweverJasminum grandiflorum essential oil extracts and called it jasmone [Jasminum essential oil, didn’t have the characteristic scent of jasmine flowers, suggesting one or more constituents were missing. In 1962, methyl jasmonate was eventually isolated and its structure determined, and it was shown to be the missing odorant molecule [A. thaliana JA resistant mutant, coi1 (for CORONATINE INSENSITIVE 1), was isolated in 1994 [In 1899 Hesse and Müller purified an unknown ketone from  jasmone . Its che jasmone . Howevermolecule . It tookmolecule , 17. The in 1994  and form in 1994 , 22.A. thaliana [Arabidopsis) can still make some JA, there are most likely other transporters involved. In the peroxisome, cis-OPDA is reduced by an OPDA REDUCTASE (OPR) and then undergoes three rounds of β-oxydation by ACYL-CoA OXIDASE (ACX) enzymes leading to the production of jasmonic acid (JA) [The JA biosynthetic pathway, also called the octadecanoids pathway (the starting point is the 18 C fatty acid α-linolenic acid 18:3 (α-LA)), takes place in three subcellular compartments: first in the chloroplast, then the peroxisome, and finally the cytoplasm  , 34. JA cid (JA) .How plant cells sense JA-Ile has been well documented and is mechanistically very similar to auxin signaling As for perception, the canonical signaling pathway of JA-Ile is also remarkably similar to auxin . The JA-Amongst the many TFs that interact with JAZ proteins, the basic helix-loop-helix (bHLH) TFs MYC2, MYC3, and MYC4 have been studied extensively –52. WhenThe transcriptional changes induced by JAs on their own, for instance in response to methyl jasmonate in cell culture, will primarily affect genes involved in JA signaling  and in second wave genes involved in metabolism and cell cycle progression . Noir etJAs are also important during the responses to pathogens and herbivores. In these situations, wounding is associated with herbivory- or pathogen-associated molecular patterns (H/P AMPS) . These cOne of the key effects reported in several studies is the “priming” of JA signaling and, more generally, stress responses . Also caBotrytis [Physcomitrella patens, which does not produce JA-Ile but accumulates OPDA, has reduced fertility in aoc mutants, a phenotype that is associated with JAs in higher plants [Several reports clearly suggest JAs might signal through at least one other pathway that is independent of COI1 and that involves the biosynthetic intermediate OPDA (reviewed in ). For inBotrytis . In termr plants . Besidesr plants  and O glr plants . More ger plants . In the Arabidopsis [Arabidopsis, ILL6 and IAR3, and by an IAR3 homologous gene in Nicotiana attenuata, NaJIH1 [Inactivation of JA signaling takes place at least at two different levels. First, in response to JA treatments or wounding, JAZ repressors are amongst the first genes to be induced . This inbidopsis . Interesbidopsis . The hyd, NaJIH1 , 81. StrThe first report of systemic wound responses in plants was in 1972 from the laboratory of Clarence Ryan , 84. How−1 as measured by the production of JA distally to the wounding site (~0.1 cm.s−1) [−1) [Arabidopsis [−1).The actual dynamics of the phenomenon were described using very sensitive detection methods, which showed that the spread of the wound response signal moves at a speed of 3.4–4.5 cm.min cm.s−1) . This is−1) [−1) . There i−1) [−1) , which i−1) [−1) . Measure−1) [−1)  or hydra−1) [−1) . In 2013bidopsis . The autMore recently, using a fluorescent biosensor to monitor JA responses after wounding, it was shown that systemic signaling from shoots to roots after wounding takes places in two successive waves . The firArabidopsis seedlings [Overall, estimates on the proportion of crop losses due to biotic and abiotic stresses range from 20 to 40 % of global yields , 94. Witeedlings . RepetitOur understanding of JA biosynthesis, perception, signaling, and catabolism have progressed considerably over the past 10 years. There are now plenty of transcriptomics datasets from different plant species in response to various stresses available online. From these, several genes have been identified that could potentially be interesting for plant breeders as they might enhance resistance to pathogens and resilience to unfavorable weather. Fundamental research now needs to focus on understanding how plants integrate various types of stresses and how they prioritize their responses as in a real life situation crops will typically not face a single, isolated stress but a combination of stresses that might occur sequentially or at the same time. Publications in this area are more and more frequent and the next few years should see these numbers grow even more.in planta. Transcriptomic studies, as well as evo/devo analyses of JAs signaling in plants, might give a hint, especially since the JA biosynthetic pathway appeared progressively during evolution. Importantly, the identification of stress-specific signaling pathways will allow for the development of biosensors that will help plant growers to monitor their crops more precisely and provide accurate information for when treatments are required to reduce losses.Also, despite the clear evidence that other pathways exist in parallel to the canonical COI1-JAZ module, there are still no molecular mechanisms to explain how these work Finally, further research is required on the transmission of the systemic signal. Are there GLR genes in other plant species that fulfill the same function? Can these be used by crop breeders to select for crops less susceptible to wounding and other stresses? It will be essential to dissect these research areas further for the agriculture of tomorrow.There are many reviews that cover all the aspects of JAs, from biosynthesis, signaling, and catabolism to biological function. The most recent contributions include , 95, 96.


BRACHYURY expression and mesoderm induction; that WNT5A/5B, via ROR2 and noncanonical signaling, regulate MESP1 expression and cardiovascular development; and that later in development WNT2, WNT5A/5B, and WNT11, via FZD4 and FZD6, regulate functional cardiomyocyte differentiation via noncanonical Wnt signaling. Our findings confirm in human development previously proposed roles for canonical Wnt signaling in sequential stages of vertebrate cardiomyogenesis, and identify more precise roles for noncanonical signaling and for individual Wnt signal and Wnt receptor genes in human cardiomyocyte development.Wnt signaling is a key regulator of vertebrate heart development; however, specific roles for human cardiomyocyte development remain uncertain. Here we use human embryonic stem cells (hESCs) to analyze systematically in human cardiomyocyte development the expression of endogenous Wnt signaling components, monitor pathway activity, and dissect stage-specific requirements for canonical and noncanonical Wnt signaling mechanisms using small-molecule inhibitors. Our analysis suggests that WNT3 and WNT8A, via FZD7 and canonical signaling, regulate   •hESCs were used to study Wnt signaling during human cardiomyocyte development•Previously proposed roles for canonical Wnt signaling were confirmed in human•Specific roles for noncanonical Wnt signaling were identified in cardiomyogenesis•Individual Wnt signal and receptor genes were identified in human cardiomyogenesis Wnt signaling is an established key regulator of vertebrate heart development, but its role in human cardiomyocyte development remains unclear. Here, Hoppler and colleagues use hESCs to study canonical and noncanonical Wnt pathway activity and identify Wnt signal and receptor genes during human cardiomyocyte development. They identify roles for Wnt signaling that are relevant for congenital defects studies and regenerative medicine applications. The human heart develops as the first functional organ in the embryo. In the lateral plate mesoderm (LPM) cardiac progenitor cells are induced, which can subsequently differentiate into heart muscle cells (cardiomyocytes) . Wnt sigSeveral studies in mouse and other experimental models have described diverse, and often opposing, effects of canonical and noncanonical Wnt signaling on subsequent cardiomyocyte differentiation, leading to the argument that particularly the JNK-mediated noncanonical pathway may function in this context to antagonize canonical Wnt signaling . In addiIn this study we therefore used human embryonic stem cells (hESCs) to dissect stage-specific requirements of Wnt signaling and to identify endogenous Wnt ligand and receptor genes directing human embryonic cardiomyocyte development.To study sequential stages of human cardiomyocyte development in vitro, we explored established hESC differentiation protocols. With two hESC cell lines (H9 and H7) we used an activin/bone morphogenetic protein (BMP)-based protocol, hereby named the AB + WNTi protocol , and a CConsistent with findings from model systems e.g., , inhibitManipulation of Wnt signaling is a well-established experimental tool for driving cardiomyocyte differentiation in hESC protocols e.g., , suggestWNT3 and WNT5A are particularly highly expressed during mesoderm induction, together with WNT8A and WNT5B. Much later in development, during cardiomyocyte differentiation, high expression of WNT2, WNT5A, WNT5B, and WNT11 was observed  and MIXL1 is found to be reduced following inhibition of canonical Wnt signaling in the AB + WNTi protocol, but only the expression of the earliest cardiogenic marker MESP1  and MSX1  and more delayed MESP1   F. Converl day 2) G, which Hardly anything is currently known about canonical and noncanonical Wnt signaling at later stages of human cardiomyocyte differentiation. We therefore studied molecular differentiation of cardiomyocytes when inhibition of Wnt signaling by IWP2 was experimentally prolonged A, and foAXIN2 expression  expression and mesoderm induction via the canonical pathway, after which WNT5A and WNT5B activate JNK-mediated pathway activity to regulate MESP1 expression, thereby indicating a role for WNT/JNK signaling that goes beyond regulating morphogenesis during gastrulation in the intact embryo. Consistently, our results also show expression of FZD7 and the noncanonical receptor ROR2 during mesoderm induction. Interestingly FZD7 had previously been identified in pluripotent hESCs, where it plays a role in canonical WNT3-mediated self-renewal  were grown on inactivated mouse embryonic fibroblasts, as previously described . All exphESCs (NSCB no. WA09 [H9] and WA07 [H7]) were grown on mTeSR1/Matrigel Platform as per the manufacturer's instructions. All experiments were repeated with both cell lines with comparable results, but results presented here are from H7 culture. Differentiation toward mesoderm, LPM, and beating cardiomyocytes was performed essentially as previously described  with onlS.M. carried out the experiments and analysis, helped in experimental design, and wrote the manuscript. C.N. contributed to design, carried out experiments, and advised on analysis and manuscript. R.J.B. carried out experiments. A.S.B. advised on design, methods, and manuscript, and carried out experiments. K.D. advised on design and manuscript. S.H. designed the study and wrote the manuscript.


It has been shown that the electrode process is purely electrochemical, uncomplicated with catalytic stages. The nanoeffects observed as the reduction of overvoltage and increased current of UA oxidation have been described. These nanoeffects are determined by the size of particles and do not depend on the method of particle preparation (citrate and “green” synthesis). The findings of these studies have been used to select a modifier for carbon screen-printed electrode (CSPE). It has been stated that CSPE modified with gold nanoparticles (5 nm) and 2.5% Nafion (Nf) may serve as non-enzymatic sensor for UA determination. The combination of the properties of nanoparticles and Nafion as a molecular sieve at the selected pH 5 phosphate buffer solution has significantly improved the resolution of the sensor compared to unmodified CSPE. A nanostructured sensor has demonstrated good selectivity in determining UA in the presence of ascorbic acid. The detection limit of UA is 0.25 μM. A linear calibration curve has been obtained over a range of 0.5–600 μM. The 2.5%Nf/Au(5nm)/CSPE has been successfully applied to determining UA in blood serum and milk samples. The accuracy and reliability of the obtained results have been confirmed by a good correlation with the enzymatic spectrophotometric analysis (R Uric acid (UA) plays a dual role in the human body: on the one hand, it exhibits antioxidant properties; on the other hand, it causes formation of urates in the tissues in case of purine metabolic disorder. Abnormalities of UA levels are symptoms of Lesch–Nyhan syndrome, multiple sclerosis, cardiovascular, and renal diseases ,2. In th-necessity of GCEs surface pretreatment before use;-time consuming  ,13,16,18-the use of complex, expensive, non-transportable, malfunctioning flow-injection systems that are difficult to use for on-site analysis ,18;-lack of methods of UA electrochemical determination in food products .To determine UA, electrochemical methods are applied. Electrochemical methods have advantages over other methods, as they are more sensitive, selective and can be easily automated. The methods of electrochemical determination of UA in biological liquids (mainly urine) have been developed, but the methods of electrochemical determination of UA in food stuff have not been dealt with so far. Modified glassy carbon electrodes (GCE) are most frequently used for UA determination ,7,8,9,10In this regard, it is important to develop a simple enzyme-free screen-printed electrode that does not require any additional operations of separation and concentration, but can be used to determine UA in foods  and biological objects with a complex matrix, such as blood serum, as the level of UA in blood serum is an essential diagnostic indicator of some diseases. In our opinion, a practical approach to developing a sensitive and selective UA sensor is the modification of the screen-printed electrode with gold nanoparticles and electrically-conductive perfluorinated membrane (Nafion), which includes a hydrophobic matrix and hydrophilic pores and channels. The reduction of electrode overvoltage and the increase in oxidation currents of compounds diffusing from the solution on the surface of gold nanoparticles , togetheHowever, another fundamental issue to be considered in this work is to establish the mechanism of UA electrooxidation on gold nanoparticles. This is due to the existing contradictory views on this issue and to the fact that the earlier proposed approaches and sensors are based on empirical regularities of the processes only. The choice of the modifier and conditions for UA determination should utilize the knowledge of electrode process mechanisms. The aims of this study are (i) to investigate the type of electrode process for UA oxidation on the nanostructured electrode; (ii) to specify conditions for selective determination of UA in the presence of AA; (iii) to develop a sensor based on carbon screen-printed electrode (CSPE) modified with gold nanoparticles and Nafion, which could be used in portable devices, and (iv) to develop a method of UA determination in blood serum and milk.Mechanism of Uric Acid Oxidation on a Nanoparticle-Modified ElectrodeSome publications look upon UA electrooxidation as an electrocatalytic process, whereby carbon nanotubes/nanoparticle hybrid material , restorean electrochemical process, without intermediate chemical stages;an electrochemical process, including the catalytic stage, where the formation and decay of intermediate products is expected.There are two possible mechanisms for UA electrooxidation:The interpretation of the process taking place on gold nanoparticles as a process involving the catalytic stage might be problematic.In order to develop an optimal method of electrochemical determination of UA it may be useful to know the mechanism of the proceeding process. To answer this question, we have used the earlier proposed approach and mathematical model of electrochemical processes, not complicated by chemical stages, but including catalytic stages and nanoeffects ,22, and -n, number of electrons involved in the process;-F, Faraday constant ;-β, electron transfer coefficient in the anodic phase (0.49 [se (0.49 );-ks, electrode process rate constant(1.00 × 10−4 cm s−1), was determined as described earlier [ earlier , using v-S, electrode area (cm2);-Cs, surface concentration of electroactive substance diffusing to the electrode (mol cm−3);-Ein, initial potential (0.20 V);-E°, redox potential of UA, is given (relative to Ag/AgCl) for red-ox potential in the reaction ∙U2−+e−+H+→UH2− in accordance with [nce with  (0.37 V)-ν, potential scan rate (V s−1);-t, time (s);-R, universal gas constant (8.314 J mol−1 K−1); and-T, temperature (K).The mathematical model described in ,22 was uG°) was calculated using Equation (2) taken from [-σ, surface tension of gold at the air borderline at 700 °C (1200 dyn/cm [0 dyn/cm );-M, molar mass of gold (197 g/mol);-ρ, density of gold (19.3 g/cm−3); and-r, radius of nanoparticles.Gibbs free energy (Δken from :(2)ΔG∘=S = 4.5 × 10−2 cm2). In the other case, the real total surface area of nanoparticles (S = 8.3 × 10−2 cm2) was used for the calculations. A significant increase in the UA oxidation current was observed on the nanoparticles with a larger, than the limited area, surface area. Thus, nanoeffects are demonstrated in the decrease in the overvoltage and the increase in the UA oxidation current. 4 , sodium citrate , Nafion , ascorbic acid , uric acid , glucose , urea , L-tryptophan , and creatinine  were used. Phosphate buffer solutions (PBS) were used as supporting electrolytes. All chemicals were of extra pure grade and chemically pure grade. HCl , HAuClA semi-automatic computerized voltammetric analyzer IVA-5  with a PE-6100 magnetic stirrer and a three-electrode electrochemical cell was employed for voltammetric measurements. Working electrodes were glassy carbon electrode (GCE) , gold disk electrode (Au-bulk)  and carbon screen-printed electrode (CSPE) . A glassy carbon rod and Ag/AgCl (saturated with KCl) were used as the auxiliary electrode and reference electrode, respectively. 4) by sodium citrate (Na3C6H5O7) in accordance with the standard Turkevich method and as described in [4):C(Na3C6H5O7). Two samples of gold sol Aured and Auvio were obtained with the ratio C(HAuCl4):C(Na3C6H5O7) equal to 1:5 and 1:2, respectively.Gold suspension was synthesized by chemical reduction of aqueous solution of chloroauric acid  were used to modify electrodes.The drop casting method was used to modify CSPE: 5 µL of gold nanoparticles suspension was deposited on the CSPE surface area. Then the electrode was air-dried at room temperature. To prepare Nf/Au/CSPE, 10 µL of 0.5, 1.0, 1.5, 2.0, 2.5, and 5.0% Nf were deposited on the Au/CSPE surface area. Then the electrode was air-dried at room temperature. Prior to use, the obtained modified electrode (Nf/Au/CSPE) was washed with distilled water. As shown by our SEM studies ,24, nanoI/dE = f(E) is recorded. Linear sweep voltammetry (LSV) was used in ordinary and derivative modes. The derivative curve presents simply differentiated initial voltammogram, dependence dν = 50 mV/s in the range of potential 0.1–0.8 or 0.1–0.9 V. Derivative voltammograms were used due to poor separation of UA and AA signals in LSV. The measured signal is an amplitude of the derivative voltammogram (dI/dE curve). It is measured as shown in Recording of the anodic voltammograms was carried out using a phosphate buffer (pH 5) at Frozen blood serum samples were provided by the clinical laboratory of Medical Technologies JSC, a multidisciplinary medical center. The results were compared with the data obtained in Medical Technologies JSC, via the method of BioSystems . Milk samples from different manufacturers were purchased from local supermarkets and stored at 4 °C until the study. For analysis, aliquots of blood serum (100 μL) or milk (200 μL) were taken, which were introduced into an electrochemical cell containing 10 mL of phosphate buffer solution. Preliminary preparation of blood serum and milk samples was not required.G° = 7349.22, 1837.31 J mol−1 for Au 5, 20 nm, respectively) as compared to the macroelectrode (ΔG° = 0 J mol−1). These data indicate that nanoeffects in UA electrooxidation on gold nanoparticles are demonstrated. Nanoeffects are observed as a decrease in overvoltage of the electrode process. The effects are greater with a smaller size of nanoparticles, which is due to the contribution of the nanoparticles’ Gibbs free energy to the kinetics of UA electrochemical oxidation. The reason is a lower energy barrier of the reaction [The smaller the size of the nanoparticles, immobilized on different electrodes, the greater the shift. This shift is caused by an increase in the Gibbs free energy of the nanostructured electrode (Δreaction .red = 5 nm), obtained by citrate synthesis and immobilized on GCE, shifts by 50 mV to the cathodic area as compared with larger nanoparticles (Augreen = 14 nm) obtained by “green” synthesis and immobilized on Au-bulk.The observed nanoeffects are independent of the nanoparticles synthesis method and the substrate nature. For example, the half-wave potential of UA oxidation on smaller nanoparticles  were selected for developing the UA sensor. E) of 0.07 V  with a potential difference  on derivative voltammograms (E = 0.34 V) is observed at 2.5% Nafion concentration /CSPE is 0.25 μM. The relative standard deviation of the signal for 5 μM UA is 1.9%.A 100-fold excess of glucose and urea, a 70-fold of creatinine, a 10-fold excess of tryptophan, and a five-fold excess of AA do not interfere with UA determination at the 2.5% Nf/Au(5nm)/CSPE .Analytical characteristics of the 2.5% Nf/Au(5nm)/CSPE remain stable for a month after storage at room temperature.Analytical characteristics of UA determination with the use of the proposed sensor and other modified CSPEs are displayed in 2 = 0.993) /CSPE with the results of the enzymatic spectrophotometric method demonstrated a good correlation (R= 0.993) .r does not exceed 2.5%.The proposed sensor was tested by adding given amounts of analyte standards into the milk samples. The percentage recoveries were found to be 96.5—101.5% as presented in The mathematical modeling and experimental studies have shown that the process of UA electrooxidation with gold nanoparticles is not complicated by catalytic stages. This conclusion proves that the common view that nanoparticles serve as catalysts in electrode processes is not convincing. The data obtained in this paper show that the role of nanoparticles is to contribute the Gibbs free energy to the reaction kinetics.The nanoeffects of the particles obtained by citrate and “green” synthesis are exhibited in a lower UA oxidation potential, and it is greater with a smaller size of gold nanoparticles. These findings allow us to justify the choice of gold nanoparticles Au (5 nm) for developing an UA sensor. 2 = 0.9938) and the “added-found” technique (recovery close to 100%).It was shown for the first time that the CSPE, modified with 5 nm gold nanoparticles and 2.5% Nafion, and pH 5 background electrolyte ensures selective and sensitive determination of UA in the presence of AA. The combination of the properties of nanoparticles and Nafion as a molecular sieve at the selected pH 5 phosphate buffer solution has significantly improved the resolution of the sensor compared to unmodified CSPE. The developed sensor with a linear range of 0.5–600 μM and a detection limit of 0.25 μM has been successfully applied to determining UA in blood serum and milk samples without prior preparation of the electrode surface, time-taking modification and additional UA concentration, and the use of complex equipment and recording, which allows us to recommend the proposed sensor for nonlaboratory analysis. The correctness of the analysis results has been confirmed by a good correlation with the enzymatic spectrophotometric analysis (R


Tumor recurrence occurs in more than 70% of ovarian cancer patients, and the majority eventually becomes refractory to treatments. Ovarian Cancer Stem Cells (OCSCs) are believed to be responsible for the tumor relapse and drug resistance. Therefore, eliminating ovarian CSCs is important to improve the prognosis of ovarian cancer patients. However, there is a lack of effective drugs to eliminate OCSCs because the core signaling pathways regulating OCSCs remain unclear. Also it is often hard for biologists to identify a few testable targets and infer driver signaling pathways regulating CSCs from a large number of differentially expression genes in an unbiased manner. In this study, we propose a straightforward and integrative analysis to identify potential core signaling pathways of OCSCs by integrating transcriptome data of OCSCs isolated based on two distinctive markers, ALDH and side population, with regulatory network (Transcription Factor (TF) and Target Interactome) and signaling pathways. We first identify the common activated TFs in two OCSC populations integrating the gene expression and TF-target Interactome; and then uncover up-stream signaling cascades regulating the activated TFs. In specific, 22 activated TFs are identified. Through literature search validation, 15 of them have been reported in association with cancer stem cells. Additionally, 10 TFs are found in the KEGG signaling pathways, and their up-stream signaling cascades are extracted, which also provide potential treatment targets. Moreover, 40 FDA approved drugs are identified to target on the up-stream signaling cascades, and 15 of them have been reported in literatures in cancer stem cell treatment. In conclusion, the proposed approach can uncover the activated up-stream signaling, activated TFs and up-regulated target genes that constitute the potential core signaling pathways of ovarian CSC. Also drugs and drug combinations targeting on the core signaling pathways might be able to eliminate OCSCs. The proposed approach can also be applied for identifying potential activated signaling pathways of other types of cancers. Over 90% of ovarian cancers are epithelial in origin, and epithelial ovarian cancer, especially the most aggressive subtype high-grade serous ovarian cancer (HGSOC), accounts for the majority of ovarian cancer deaths , 2. MostThough common signaling pathways, e.g., WNT, NOTCH, SHH, JAK/STAT, have been associated with all types of CSCs , 19, theIn this study, we manually searched the ovarian CSC gene expression datasets in NCBI GEO (Gene Expression Omnibus) using the aforementioned markers and “Ovarian” as the keywords, e.g., “CD44, Ovarian”, and only two datasets were found, i.e., GSE33874 and GSE82304. The dataset GSE33874 is the gene expression profile of isolated side population  and main population (MP) of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma . Gene exTo obtain the KEGG signaling pathways, the “Pathview” R package was employed to download KGMLs of humans pathways . Then thFirst, the Fisher’s exact test (using hypo-geometric distribution)  was used+ marker and side-population) using the Fisher’s exact test by integrating the up-regulated genes (Fold_Change > = 2) and the TF-target interactome (gene regulation network) data. In total, 22 TFs are identified (see Table 1). As can be seen, some TFs will be missed using only gene expression fold change because either there is no gene expression data available (NA) or the fold change is small. We conducted the literature search to evaluate these TFs, and surprisingly 15 TFs have been reported to play important roles in cancer stem cell regulation (see Table 2). For example, FOXO3 is essential for maintenance of CSC properties in pancreatic ductal adenocarcinoma [In the two gene expression datasets, there are 1988 and 2528 up-regulated genes (fold change > = 2); and 883 and 2821 down-regulated genes (fold change < = 0.5) respectively. It is difficult for biologists to identify potential targets associated with Ovarian CSCs from such large number of differentially expressed genes. With the aim of discovering testable regulatory signaling networks that maintain Ovarian CSCs, we identify the activated TFs (whose target genes are up-regulated) in both datasets . As can be seen in Fig 1, many target genes (cyan color nodes) of transcription factors, FOXO4, LEF1, NFATC2, SPI1 and TEAD1, are up-regulated (fold_change > = 2) in both datasets. The yellow color nodes represent the starting proteins activating the signaling cascades in KEGG, e.g., the MAP kinases that are often activated by mitogenic and environmental stress, the EGF growth factor, and FLT3 that encodes a class III receptor tyrosine kinase that regulates hematopoiesis, and PPP3R2 that is related to the calcium signaling. These signaling cascades provide potential testable biomarkers of Ovarian CSCs for experimental design.We further uncover the up-stream signaling cascades regulating these activated TFs using KEGG signaling pathways. Out of 22 activated TFs, 10 TFs  are found in KEGG signaling pathways with up-stream signaling cascades link to them . The target information obtained from DrugBank (version 5.0.11) [Fig 2) were selected targeting on different signaling cascades. Through the literature search, we found that 15 drugs have been reported to treat cancer stem cells (see Table 3). For example, Palbociclib can block the propagation of lung, ovarian and breast cancer stem cells by targeting on CDK4 [Table 3 shows more details. In addition to the single drug treatment, combinations of drugs targeting on the different signaling cascades might have better effects to eliminate cancer stem cells. In summary, this analysis can provide testable hypothesis and potential drug candidates to eliminate OCSCs.To investigate potential drugs that can perturb the Ovarian CSCs, we mapped the FDA approved drugs on the integrative signaling network (see  5.0.11) . In tota on CDK4 . Bosutin on CDK4 , 44. Cel on CDK4 . Metform on CDK4 , 47. Mor on CDK4 . Table 3Most ovarian cancer tumors are initially responsive to the conventional chemotherapy. Whereas, more than 70% of patients will experience tumor recurrence, and the majority eventually becomes treatment resistant. Ovarian cancer stem cells (CSCs) are thought to drive the universal recurrence of ovarian cancer, as well as responsible for the development of therapeutic resistance. However, the core signaling pathways regulating Ovarian CSCs remain unclear, and there is still a lack of effective drugs and drug combinations to differentiate and eliminate them to improve cancer survival.In this study, we propose to identify potential core signaling pathways of OCSCs in a data-driven manner by integrating transcriptome data of OCSCs isolated based on two distinctive cell surface markers, ALDH and side population, with prior knowledge, e.g., regulatory network and signaling pathways, to increase the possibility of identifying the true CSC driver genes and signaling pathways. We identified 22 activated transcription factors, and 15 of them have been reported in the association with cancer stem cells. In addition, 10 transcription factors were found in the KEGG signaling pathways, and we extracted the up-stream signaling cascades regulating these transcription factors, which provide potential core signaling mechanism of ovarian CSC regulation. Moreover, we mapped the FDA approved drugs on these up-stream signaling cascades. Forty FDA approved drugs were identified and 15 of these drugs have been reported in cancer stem cell treatment. Combinations of these drugs targeting on different up-stream signaling cascades might be effective to eliminate ovarian cancer stem cells.The proposed approach can be helpful for discovering synergistic and effective drug combinations. It is well known that inhibiting a single target does not ensure the success of effective treatment due to the complicated interplay of multiple signaling pathways . For exaThere are also some limitations of this integrative data analysis. First, the current TF-target interactome data might not be complete and accurate. In the future work, we will integrate new TF-target interaction data resources, e.g., TRUST (text mining)  and GTRD


Supplemental Digital Content is available in the text Hyperuricemia has been demonstrated to be a risk factor for cardiovascular diseases. Though the association between uric acid (UA) and arterial stiffness has been investigated previously in patients with basic diseases, the predictive value of baseline UA level for arterial stiffness has not been conducted. We aimed at identifying the predictive role of UA for arterial stiffness prospectively.A longitudinal follow-up study in a routine health check-up population was performed with an average follow-up of 4.8 years. The demographic information, baseline and follow-up anthropometric parameters, arterial stiffness , and biomarker variables including UA have been measured and analyzed.P values <0.001). The follow-up carotid-femoral PWV  was strongly correlated with baseline UA. At the follow-up cross-section, cf-PWV was also closely associated with UA . Logistic regressions revealed that a higher baseline UA level was an independent predictor of follow-up arterial stiffness assessed by cf-PWV .A total of 1447 valid follow-ups were available for the final analysis. Both of the baseline and follow-up UA levels were significantly higher in the arterial stiffness groups than that in the nonarterial stiffness groups (all A higher baseline level of UA is closely related to arterial stiffness and is an independent predictor of arterial stiffening. Arterial stiffening is also the hallmark of normal vascular aging, and early acceleration of the stiffening process represents one of the major pathologies of the cardiovascular system. There are several methods for quantifying arterial mechanical properties have been proposed.,22 The most commonly used technique is measurement of the pulse-wave velocity (PWV) which provides a noninvasive method of assessing stiffness along an arterial section in the clinical practice.,23 Currently, PWV is used as a reproducible and valid noninvasive “gold standard indicator” in the assessment of arterial stiffness. Nevertheless, PWVs from different arteries usually represent stiffening in distinct regions of the vasculature. Particularly, carotid-femoral PWV (cf-PWV) and carotid-radial PWV (cr-PWV) are often applied to assess stiffness in the aorta and arterioles.It is well known that arterial stiffness is a marker of aging including blood vessel aging, and arterial stiffness has been identified as a risk factor for prepathophysiological processes in numerous cardiovascular (such as hypertension and other cardiovascular diseases) and cerebrovascular diseases.,24 However, most of the studies have been conducted based on the patients with various disorders such as DM, hypertension, and chronic kidney disease, as well as among various ethnic groups.–27 To the best of our knowledge, there are few reports of follow-up studies evaluating the role of the baseline level of UA in arterial stiffness. Thus, we postulated that a higher UA level may also play a critical role in aggravating arterial stiffness as evaluated by cf-PWV, and UA has a critical role in increasing arterial stiffness. We have conducted this follow-up observational study with the aim of providing novel indices for stratification and risk management of arterial stiffness.Though the previous results are inconsistent, evidence is accumulating to indicate an association between serum UA level and arterial stiffness. The previous studies have documented that the UA were associated with hypertension, arterial stiffness, and other vascular alterations.22.1A total of 1680 participants who underwent a routine health examination were recruited between September 2007 and January 2009 from the Pingguoyuan area in the Shijingshan district in this community-based follow-up cohort study. Residents who received a routine health check-up in the community were eligible for inclusion. Subjects with any of the follow conditions were excluded: infection, and neoplastic or severe liver or renal diseases.2.2All participants were followed up for all-cause mortality, cardiovascular disease mortality, arterial stiffness, and the development of DM from the initial screening to September 2013. During a median of 4.8-year follow-up of the 1680 subjects, 181 participants were lost to follow up and were excluded from the final analysis. Thus, 1499 subjects (follow-up rate 89.2%) completed the follow-up, and 52 were excluded because of death. Finally, 1447 participants were valid for the analysis.The present study was reviewed and approved by the Ethics Committee at the People's Liberation Army General Hospital. The study was explained in detail to all of the subjects who agreed to participate in, and all of the subjects signed informed consent forms before their examinations.2.3The participants were followed up by our trained physicians, and a standardized self-report questionnaire form was used to record demographic information, lifestyle factors, prevalent diseases, family history, and medication use. Anthropometrics were evaluated by trained medical doctors. Height was measured in centimeters using a wall-mounted measuring tape, and weight was measured using a digital scale in kilograms (without shoes). Self-reported smoking status was categorized as current, former, or never smoking. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured on the right arm in a sitting position after a 5-minute rest period.2.4am and 10 am after an overnight fast (at least 12 hours). Plasma aliquots were obtained and stored at −80°C for further assays. Plasma UA, fasting blood glucose (FBG), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) concentrations were measured from venous blood samples using commercially available ELISA kits by Roche enzymatic assays . The concentration of plasma creatinine (Cr) was measured by an enzymatic assay (Roche Diagnostics GmbH) on a Hitachi 7600 autoanalyzer . In addition, the non-DM subjects received the standard 75-g oral glucose tolerance test.Venous blood samples were obtained from subjects between 8 All of the biochemical variables were measured from the blood specimens in the Clinical Laboratory Department, Chinese PLA General Hospital, following the criteria of the World Health Organization Lipid Reference Laboratories.2.5Baseline and follow-up arterial stiffness was assessed by automatic carotid-femoral PWV (cf-PWV) measurement using a Complior SP device  after a 5- to 10-minute rest. PWV (m/s) = distance (m)/transit time (s). The detailed procedure was described in Appendix 1 .2.6,28 The detailed definition of variables is described in Appendix 1.Hypertension was defined as a SBP ≥140 mm Hg and/or a DBP ≥90 mm Hg or the use of antihypertensive medications. Other variables such as body mass index (BMI) and smoking were defined in Appendix 1 (definition of variables in detail). Arterial stiffness group (AS-group) was defined as: patients with a follow-up cf-PWV ≥12 m/s.2.7t tests, while the baseline dichotomous variables are presented as numbers (percentages) and compared using the Chi-square test. Nonnormally distributed variables, such as UA levels and other biomarkers, were normalized by natural logarithm transformation as necessary.Normally distributed baseline continuous variables are expressed as the mean ± standard deviation (SD) and were analyzed with Student A Pearson regression analysis, a multivariable linear regression analysis, and a multicollinearity analysis were performed to evaluate the associations of UA  level with arterial stiffness and other parameters at both baseline and the end of the follow-up.Further analysis by a forward stepwise multivariable logistic regression analysis were performed to identify the association between UA (baseline) and the follow-up arterial stiffness (cf-PWV ≥12 m/s vs cf-PWV <12 m/s). Regression models were adjusted for age and sex as the independent variable (Model 1) and additionally adjusted for smoking, alcohol use (g/d), DM, SBP, DBP, TG, LDL-C, HDL-C, and Cr as the independent variables . 33.12. Altogether, 26.26% and 18.93% of the subjects smoke and drink currently. The characteristics of the subjects categorized by UA levels at baseline are shown in Table The mean age of the subjects was 61.40 ± 11.4 years, and 59.98% were women. The body mass index (BMI) of the subjects in the study was 25.41 ± 3.32 kg/m3.2r = 0.183, P < 0.001). Additionally, age , SBP , LDL-C , HDL-C , Cr , and TG  were also closely associated with cf-PWV in the univariate linear analysis (Table 1A in Appendix 2). However, in the multivariable analysis, UA level was not correlated with cf-PWV , which was adjusted by age, DBP, Cr, and TG in the multivariable linear analysis .At baseline, Pearson analysis showed that the UA level was strongly related to baseline cf-PWV , age , SBP , Cr , and TG  were positively correlated with the follow-up cf-PWV, while HDL-C  was negatively associated with the follow-up cf-PWV. Though the multiple linear regression analysis revealed no association between baseline UA and follow-up cf-PWV , the baseline age, SBP, DBP, Cr, and TG were still strongly correlated with the follow-up cf-PWV . Whilst, a higher baseline HDL-C level was a protective factor for arterial stiffness. Furthermore, the age- and gender-adjusted model also revealed that a higher baseline UA level was associated with a greater risk for arterial stiffness . Importantly, a higher baseline UA level remained a predictor of arterial stiffening measured by cf-PWV at follow-up  in Model 2, which was adjusted by age, DBP, SBP, and levels of TG, HDL-C, LDL-C, and Cr. Thus, these results demonstrate that a higher baseline UA level is an independent predictor of central arterial stiffening : 3.536, 95% CI : 2.267–5.515, 4In the present 4.8-year follow-up study, we found that the baseline UA level was associated with a measurement of arterial stiffness, cf-PWV. Furthermore, a higher baseline UA level was an independent predictor of follow-up central arterial stiffness (cf-PWV).4.1,7 However, the predictive role of UA in health examinations is unclear.As the end-product of purine nucleotide metabolism, UA participates in many pathophysiological processes of vascular diseases. Over the past few decades, hyperuricemia has been found to be a risk factor for cardiovascular and cerebrovascular diseases, such as atherosclerosis and hypertension.In the present study, we observed that higher UA levels are accompanied with higher cf-PWV values, indicating that the higher range of UA may contribute to arterial stiffening. This result was partly consistent with previous studies. Furthermore, individuals with higher levels (such as Quartiles 3 and 4) of UA accounted for almost half of the health check-up population and usually presented with multiple cardiovascular risk factors. Thus, individuals with higher UA levels require proper cardiovascular risk stratification and management.4.2,24 In the present study, we employed cf-PWV which is a more specific measurement of central arterial stiffness, and also found an association with baseline UA.Arterial stiffness occurs in both aortic and peripheral arteries. A large number of studies have indicated that UA is related to arterial stiffening as assessed by brachial-ankle PWV or heart-femoral PWV.,24,26,27 the predictive value of UA level for arterial stiffness has not been confirmed. Our longitudinal survey revealed that a high UA level is an independent predictor of arterial stiffness. The present study prospectively revealed that UA correlated with aortic arterial stiffening at baseline and, in particular, a higher baseline UA was independently associated with follow-up arterial stiffness. Subclinical arterial stiffening may already exist in healthy individuals, and a high UA level may be useful in predicting the incidence of arterial stiffening prospectively.Though previous cross-sectional studies have evaluated risk factors for arterial stiffness,,13,29To date, although various studies have focused on the association between UA and arterial stiffness, the mechanisms underlying the UA contribution to arterial stiffening have not been clearly elucidated. Several scientific investigations have demonstrated significant roles of UA in arterial stiffness.–32 Secondly, studies have also indicated that the essential role of UA in arterial stiffness before the development of hypertension may be attributed to the activation of inflammatory pathways (increased levels of C-reactive protein and other proinflammatory factors). Thirdly, UA has also been implicated in endothelial cell dysfunction, which plays a crucial role in arterial stiffening. UA may participate in arterial stiffness via the nitric oxide pathway dysfunction, oxidative stress, and insulin resistance, which cause endothelial cell dysfunction. Endothelial cell dysfunction further leads to increased proliferation and migration of smooth muscle cells and the rearrangement of artery wall components.,29 These changes decrease the compliance and stiffen arteries functionally and structurally.Firstly, UA contributes to the thickening of the vascular wall via promoting proliferation and differentiation of smooth muscle cells. The biological behaviors of smooth muscle cells above-mentioned are triggered by the activated renin-angiotensin system and reactive oxygen species.4.3Further analysis by logistic regressions indicated that a higher baseline UA level was an independent risk factor/predictor of central stiffness. In both adjusted models, higher UA levels were associated with arterial stiffness measured by cf-PWV, indicating that a higher UA level was an independent predictor of central arterial stiffening.,24,25,34 Thus, we conducted this follow-up study and demonstrated that a high UA level is an independent predictor of arterial stiffness. Our observations confirm the association between UA and arterial stiffness and its predictive value for arterial stiffness.Although other cross-sectional studies have identified that UA is risk for arterial stiffness, the predictive value of UA for arterial stiffness has not been confirmed in a long-term longitudinal study.5A higher baseline level of UA is closely related to arterial stiffness and is an independent risk factor for and predictor of arterial stiffness. Thus, plasma UA levels may be useful for arterial stiffness risk stratification and management.6The participants in this study were recruited from 2 districts in Beijing instead of from random sampling all over the country. The results may not be representative of Chinese individuals from other regions. The unavoidable limitation is that a total of 181 subjects (10.7%) were lost to follow-up, which may introduce bias in the conclusions.


People form associations between colors and entities, which influence their evaluations of the world. These evaluations are dynamic, as specific associations become more or less active in people’s minds over time. We investigated how evaluations of colors (color preferences) changed over the course of fall, as color-associated fall entities became more prevalent in the environment. Participants judged their preferences for the same set of colors during nine testing sessions over 11 weeks during fall. We categorized the colors as Leaf and Non-Leaf Colors by matching them to leaves collected during the same period. Changes in preferences for Leaf Colors followed a quadratic pattern, peaking around when the leaves were most colorful and declining as winter approached. Preferences for Non-Leaf Colors did not significantly change. Individual differences in these changes could be explained by preferences for seasonal entities, as predicted by the differential activation hypothesis within the Ecological Valence Theory. The more a given individual liked fall-associated entities, the more their preference for Leaf Colors increased during fall. No analogous relations existed with winter-associated entities or Non-Leaf Colors. These results demonstrate the importance of studying temporal and individual differences for understanding preferences. As people interact with the world, they form associations between colors and entities. They learn that ripe bananas are yellow, clear skies are blue, and fresh leaves are green. They also form abstract color-entity associations: The University of Wisconsin–Madison and Cornell University are associated with reds, Thanksgiving and Halloween are associated with oranges, and the U.S. Democratic Party and Facebook are associated with blues. Evidence suggests that color-entity associations influence people’s responses to colors in a variety of domains. They influence people’s percepts of how colors appear , people’Understanding how color-entity associations influence people’s evaluations and interpretations of the world is a complex problem for two main reasons. First, these mappings are not one-to-one: The same color can be associated with many entities and many colors can be associated with the same entity . For exaEvidence suggests that changes in which entities are active in people’s minds can lead to variations in color preferences. In a controlled laboratory study, priming observers to think about positive or negative entities associated with particular colors resulted in changes in preferences for those colors . For exaIn this study, we aimed to further understand seasonal variations in color preferences by investigating (a) whether changes in color preferences during fall were linked to changes in environmental colors, namely changing leaves, and (b) whether individual differences in seasonal color preference changes were linked to individual differences in preferences for seasonal entities.differential activation hypothesis.The notion that changes in the activation of color-associated entities results in changes in color preferences can be explained within the Ecological Valence Theory EVT; . The EVTtend to change because the direction and magnitude of this change will depend on the valence of the activated entity, relative to all entities associated with the color. Say entity e is associated with color c and the degree to which entity e is active in the mind of observers varies over time. And, say that an observer 1s likes entity e more than their mean liking for all entities associated with color c, observer 2s likes entity e less than their mean, and observer s3 likes entity e equally well as their mean. If all else is equal, the differential activation hypothesis predicts that increasing the activation in entity e will cause an increase in preference for color c for 1s, a decrease for 2s, and no change for 3s. This hypothesis implies that in calculating an individual’s color preferences at a given moment, the mind gives greater weight to color-associated entities that are more relevant to the individual at that time. If color preferences help to steer individuals toward positive outcomes and away from negative ones as the EVT suggests, then it is beneficial for the system to titrate the weight given to different entities that are more or less relevant, depending on the context.The differential activation hypothesis specifies that preferences for particular colors tend to change depending on the degree to which entities associated with those colors are active in an observer’s mind . We assedifferential valence hypothesis. The differential valence hypothesis states that preferences for a particular color will tend to change if preferences for entities associated with that color change over time  but not by WAVEs that coded for seasonal differences in valence (r = .29). WAVEs coding for seasonal variations in activation and valence fit the data no better than WAVEs coding for seasonal activation alone (r = .52). The results suggest that seasonal changes in color preferences are due to differential activation and not differential valences over time.With data from different participants, In this study, we address open questions that were motivated by We addressed these questions by conducting a within-subject longitudinal study, spanning nine testing sessions over 11 weeks around Fall 2014. Participants rated their preferences for each of the Berkeley Color Project 37 (BCP-37) colors  during eageM = 21 years).1 The criteria for including participants were determined a priori: (a) having typical color vision determined using the HRR Pseudoisochromatic Plates  and were shown using an Asus ProArt PA246Q monitor . Participants completed the tasks in a dark, enclosed booth. They viewed the monitor from a distance of approximately 60 cm. Over the course of testing, we documented changes in environmental colors by taking photographs each week. We also collected autumn leaves from the ground to determine which BCP-37 colors best corresponded to the Leaf Colors (described later).All participants completed two kinds of tasks: color preference ratings and entity preference ratings. Displays for both tasks were generated using Presentation software .Participants judged their preferences for the BCP-37 colors . The colnot at all, the right endpoint labeled as very much, and a central marker denoting neutral preference. The colors were presented one at a time in a blocked, randomized design (two blocks), such that participants rated their preference for all of the colors once, in a random order, before judging them a second time in a new random order.2 Participants rated how much they liked each color by sliding a cursor along the response scale and clicking to record their response. The responses were scaled to range from −100 to +100. Trials were separated by a 500-ms intertrial interval. Before starting the task, participants were shown the full set of colors and asked to complete an anchoring procedure  centered on the screen. A 400-pixel-long (10.3°) response scale appeared below the color square with the left endpoint labeled as rocedure  so they Participants reported their color preferences using this procedure on nine separate testing days over 11 weeks see . There wnot at all and very much. Trials were separated by a 500-ms intertrial interval. Before beginning, participants were presented with a set of entity descriptions that varied broadly in valence so they could anchor what liking not at all and liking very much meant for them in the context of this set of entities.At the end of the last session , after participants made their last color preference judgments, they were asked to judge how much they liked seasonal entities. The entity descriptions were presented on the monitor as black text on a white background. First, participants rated their preference for each season  in a random order. Next, they rated their preference for the fall- and winter-associated entities from To track the time course of changes in environmental colors over the course of the study, we took photographs from the same locations outside the lab each week (on Brown University’s campus), as shown in E) between each leaf color sample and all BCP-37 colors in CIELAB space and selecting the BCP-37 color with the smallest ΔE.To compare the colors that we observed in the environment to the colors that participants rated, we matched autumn leaf colors that had fallen from the trees around Week 6 to the closest BCP-37 colors. Doing so allowed us to know which subset of the BCP-37 colors to examine to determine if changes in participants’ ratings were linked to changes in environmental colors. To match the colors, we completed the following procedure: (a) We collected samples of autumn leaves that had fallen to the ground and brought them back to the lab; (b) we determined which Munsell color chips best matched the leaf colors see  while viE matches by having an independent set of five observers view each leaf color sample along with the full set of BCP-37 colors. On each trial, the observers saw one leaf color sample (as a square patch on the screen) and all BCP-37 colors  = 42.91, p < .001,  dislike .Figure F = 9.33, p = .006, F = 13.6 p = .001, F < 1). This pattern is more apparent in F = 3.84, p = .063, In testing for changes in color preference over time, we found an interaction between Color Set and a quadratic contrast over Testing Session, l colors . The peal colors , which wl colors . As the F = 4.53, p = .045, F = 4.65, p = .043, For the most part, the average data points for Leaf Colors follow a smooth quadratic function , but theWe next tested whether individual participants’ changes in color preferences during fall depended on how much they personally liked fall-associated entities, as predicted by the differential activation hypothesis. To do so, we first quantified the change in preference for each individual, which we call Δp. For each participant, we fit a quadratic function to their preferences for Leaf Colors. r(20) = .49, p = .021. Participants who had a greater preference for fall entities showed greater increases in preferences for Leaf Colors during fall. r(20) = .22, p = .332. This result suggests that the relation between Leaf Colors and fall entities (r(20) = .26, p = .246 (r(20) = .13, p = .551  = .18, p = .426. Why might Leaf Color Δps relate to average preference for fall entities but not to the umbrella term to which these entities belong? One possibility is that individuals’ preference ratings for “fall” are single data points, resulting in a noisier measure than average preference ratings for all 43 entities associated with fall. Another possibility is that the term “fall” is too abstract to elicit the affective responses in observers that are elicited by naming particular entities associated with fall . Future research will be necessary to test these hypotheses.We also tested whether there were similar relations between Δp for Leaf Colors and preferences for the season in general . However, the relation between Δp and preference ratings for “fall” was not significant, We investigated how color preferences vary over the course of fall, why such changes might occur, and why they differ among individuals. We assessed the same participants’ color preferences during nine sessions over an 11-week period (late September 2014 to early December 2014). At the beginning of the study, the colors in the environment were as they were in summer—the trees were lush green and the flowers were colorful. By the end, the colors in the environment resembled winter—the trees were bare brown and the flowers were gone. In the interim, the leaves on the trees turned shades of reds, oranges, and yellows. As the colors changed, fall-specific objects, entities and events such as pumpkin spice lattes, hayrides, cooler weather, apple picking trips, Halloween, and Thanksgiving were increasingly prevalent in the region where we conducted our study. Over this time period, we tracked our participants’ preferences for Leaf Colors  and Non-Leaf Colors . Partitioning the colors in this way allowed us to test whether seasonal changes in color preferences correspond to seasonal changes in environmental colors, which are associated with seasonally specific entities.We tested the differential activation hypothesis, which predicted that preferences for fall-associated colors would increase as fall entities became more active in observers’ minds, so long as those entities were relatively liked. In line with this prediction, average preferences for Leaf Colors increased as fall progressed and then decreased as fall ended and winter approached. There was also a small peak in the function around the Thanksgiving holiday, when fall-associated entities would have been especially activated. There were no corresponding changes in preferences for Non-Leaf Colors.The quadratic pattern of average preferences for Leaf Colors also suggests that the previously reported seasonal changes in color preferences were not due to an order effect. We also found extensive individual differences in the degree to which preferences for Leaf Colors changed over fall, which were predicted by how much individuals liked color-associated fall entities. Yet, despite this individual variation, the majority of participants reported liking fall entities and as such showed increases in preferences for Leaf Colors over the testing sessions. If our participants’ preferences for fall entities had more uniformly spanned the range from negative to positive, we would not have observed a systematic change in the average data; the changes at the individual level would have cancelled out. This point emphasizes the need for considering individual differences when studying changes in preferences, and understanding the individualized circumstances that give rise to those changes. Without doing so, diverse and systematic individual changes in preferences could be missed and wrongly interpreted as absent.1s and 2,s took trips to the same farm and partook in the same activities , but their experiences had different valences. Participant 1s had fun with friends , whereas participant 2s broke up with their significant other . The different valences of these two experiences would cause the related activities  to have positive valences for 1s and negative valences for 2.sOur interpretation of the present results is that changes in activation of seasonal entities caused changes in preferences for associated colors, rather than the reverse causal direction. Thus, we propose that individual differences in liking of fall-associated entities caused individual differences in the direction and magnitude of change in preference for Leaf Colors. Our present data do not explain why there are individual differences in preferences for fall entities, but these differences are likely due to personal experiences. For example, imagine two participants, However, it is worth considering the opposite causal direction, which proposes that increased preferences for fall colors causes increased preferences for fall entities. If that were the case, it would still be necessary to explain the increased preferences for fall colors. One possible account is mere exposure , 2001; pIn conclusion, the results of this study support the notion that people’s associations between colors and entities influence the way they evaluate the world. Some aspects of these associations are shared across individuals , but other aspects are highly individualized, including people’s affective responses to these color-associated entities. Further, the relevance of particular color-entity associations to an individual’s goals and desires can change over time . These individual and temporal variations in color-related experiences contribute to systematic temporal and individual differences in color preferences. Color preferences are just one example of how the mind integrates color-entity associations with contextual cues to form judgments about the world, and this study suggests that to understand these effects and preferences more generally, it is important to consider temporal and individual differences.


Few reports have investigated the association between human T-lymphotropic virus type 1 (HTLV-1) and tuberculosis (TB) in countries where both infections are endemic. This study estimates the incidence of TB in a cohort infected with HTLV-1, compared with non-infected individuals, over a ten-year period.Retrospective cohort study involving the cross-matching of records of individuals for whom a HTLV serology was performed at a referral center for HTLV (CHTLV) with a database of TB cases from Sinan—the Information System on Diseases of Compulsory Declaration between 2002 and 2012.p = 0.005) and had lower education levels (p = 0.02). No differences were observed with respect to the clinical/radiological presentation, nor in the outcome of TB and prevalence of HIV infection, when comparing among the HTLV-1-infected and uninfected groups.From a cohort of 6,495 individuals, 1,711 were infected with HTLV-1. A total of 73 TB cases occurred during the study period: 33 HTLV-1-infected patients and 40 uninfected individuals. The incidence density for TB in the HTLV-1 infected group was 3.3 person-years per 1,000 individuals and 1.1 person-years per 1,000 individuals in the group HTLV-1 uninfected group. The relative risk of developing TB in the group of patients infected with HTLV-1 was 2.6 (CI 95 % 1.6–4.2) in comparison with HTLV-1 uninfected group. Compared to individuals with isolated TB, those in the HTLV-1 infected group who had TB were older (Patients infected with HTLV-1 are more susceptible to TB. The epidemiological characteristics of HTLV-1/TB subjects and those infected with TB overlap. Human T-lymphotropic virus type 1 (HTLV-1) infects around 10 million people worldwide, most of whom are concentrated within endemic areas in developing countries. Brazil is one of the largest endemic areas of HTLV-1 in the world , HTLV-1-Several reports have indicated that HTLV-1 may promote some degree of immunosuppression, as an association has been observed between HTLV-1 and Norwegian scabies , 10, disSalvador, the capital of the state of Bahia, located in Northeastern Brazil, has been described as the epicenter of the HTLV-1 endemic in the country, with a high prevalence of infection in blood donors (1.35 %) , pregnanThis retrospective cohort study involved the cross-matching of records of individuals for whom HTLV serology was performed at a referral center for HTLV (CHTLV) of the Bahiana School of Medicine and Public Health (EBMSP), in Salvador – Brazil, between 2002 and 2012. CHTLV is a free public outpatient clinic that has provided comprehensive care to HTLV-infected individuals and their relatives since 2002. Serological testing for HTLV-1/2 was conducted for 6,620 individuals at CHTLV throughout the period of study. This population consisted mainly of blood donors, pregnant women and patients with neurological symptoms, as well as their families, who were referred by blood banks, prenatal physicians or clinicians from the public health system. All individuals who underwent serologic testing for HTLV during the period of the study were included. Individuals with indeterminate serology, as well as those who tested positive for HTLV-2 and whose date of testing was not recorded, were excluded. To perform HTLV-1 diagnosis, all individuals were screened using ELISA  and positive tests were subsequently submitted to Western Blot analysis  to confirm infection. HTLV-1/2 co-infection was determined using WB, in accordance with manufacturer’s instructions: i) HTLV-1: reactivity to GAG (p19 with or without p24) and two ENV (GD21 and rgp46-I) proteins; ii) HTLV-2: reactivity to GAG (p24 with or without p19) and two ENV (GD21 and rgp46-II) proteins. PCR was used only in cases in which HTLV serology was indeterminate; however, these patients with this serological status were excluded. The EBMSP Institutional Review Board approved the present study.Mycobacterium tuberculosis. TB diagnosis was also considered in presence of a positive culture or clinical history of TB associated with complementary tests, for example a suggestive chest X-ray with heterogeneous opacity of the lung parenchyma, cavitation, nodules or consolidations [This retrospective cohort study was based on patient records from CHTLV and on the TB registry from the Information System on Diseases of Compulsory Declaration (Sistema de Informação de Agravos de Notificação—Sinan). TB notification has been mandatory in Brazil since 1998. The number of TB cases reported by the SINAN database was 79,942 in Bahia state between January 2002 and May 2012. After the exclusion of duplicates  or corrupted names (3), the final number of TB cases was 74,454 (93.1 %). Case of tuberculosis was defined as a patient who experienced respiratory symptoms and had a smear-positive test for idations . Search P < 0.05 was considered statistically significant. All analyzes were performed using STATA 13 statistical software .For purposes of analysis, subjects were classified into two groups according to the results of serology for HTLV-1. The independent variable was HTLV-1 and the outcome was the diagnosis of TB. The data were expressed as mean and standard deviation, proportions, measures of central tendency and interquartile range. In order to test the differences between means Student t was used and for proportions, the chi-square test. As measures of frequency, incidence density for both groups was calculated: coinfected (HTLV-1/TB) and isolated TB and the relative risk of TB in those infected with HTLV-1. The date of the serology was considered as the moment of inclusion in the cohort. The TB disease incidence density in both HTLV-1-infected and uninfected groups was calculated as the number of new-TB cases per 1000 person-years of follow-up. The analysis was further stratified by the age and the crude incidence density was adjusted using Mantel-Hansel test. Then, a multivariate analysis using the Poisson model was performed considering person-time and age and sex as potential confounding. A p = 0.000), respectively. The percentage of females was 82.9 % in the HTLV-1 infected group and 67.5 % in the uninfected group (p = 0.000). The final sample consisted of 6,495 individuals, with a total of 46,634 person-years of follow-up (mean 6.4 ± 2.7 years). A total of 73 cases of TB occurred in members of the cohort during the period studied: 33 among patients infected with HTLV-1 and 40 in the uninfected group. No TB cases were found among patients coinfected with both HTLV-1 and HTLV-2. About half the individuals (52 %) received a positive TB diagnosis prior to being diagnosed with HTLV-1, with a mean time difference between TB and HTLV-1 diagnoses of -1 ± 4 years. The overall incidence density for the HTLV-1/TB group was 3.3 person-years per 1,000 individuals and 1.1 person-years per 1,000 individuals in the non-infected control group. The overall relative risk of TB in the HTLV-1-infected group was 2.6 (CI 95 % 1.6–4.2). When the sample was stratified by age, a significantly higher relative risk of TB  was found only in individuals aged 31 to 50. The Poisson model returned a relative risk of TB, adjusted for age and sex, of 2.5 (IC95% 1.6–4.1) for HTLV-1 infected individuals, in comparison with uninfected persons ,  had not completed primary school, while this proportion was 21.7 % in the isolated TB group (p = 0.09). The clinical presentations of TB (pulmonary/extra pulmonary) were similar in all individuals. No significant differences in TB outcomes  were observed when comparing the HTLV-1 infected and uninfected groups, although two HTLV-1-infected individuals died due to TB. TST was performed in 21.2 % of the individuals infected with HTLV-1 and in 30 % of individuals with TB. The proportion of reactive results ≥10 mm was 75.1 % (4 of 7) in the group infected with HTLV-1 and 83 % (10 of 12) in the TB-only group. HIV serology was positive for 6.0 % of the individuals infected with HTLV-1, versus 12.5 % with isolated TB (p = 0.45).Table This is the first retrospective cohort study to assess the risk of developing TB in HTLV-1-infected individuals residing in a high TB-burden country. The results herein indicate that the risk of developing TB in HTLV-1-infected individuals is almost three times greater than in uninfected controls over a 10-year period of follow-up. This finding is particularly relevant because all studies addressing the association between HTLV-1 and TB to date have been carried out in populations that were previously diagnosed with TB. Moreover, several of these studies reported contradictory results; i.e. some found an increased prevalence of TB in HTLV-1 infected individuals –19, whilM. tuberculosis was consistent with the epidemiological characteristics described by a population-based study conducted in Salvador to determine HTLV-1 infection prevalence [Differences in sociodemographic characteristics were observed between patients with HTLV-1+/TB versus the group with TB alone. The epidemiological profile of patients coinfected with HTLV-1/evalence : a mean evalence , this dievalence . These dM. tuberculosis. However, this result should be carefully interpreted since only one-third of the subjects in both groups had TST results registered in their medical records.Clinical features of TB infection between the two groups revealed that the clinical presentations (pulmonary or extra-pulmonary) and the number of chest-X-rays suggestive of TB were similar. Although a greater number of individuals in the coinfected group had higher rates of TB recurrence or returned to treatment after abandonment, this difference was not statistically significant. A positive TST result was more frequently observed among individuals serologically negative for HTLV-1 (25 %), compared with 12.1 % of patients with HTLV-1/TB, which may indicate some degree of immunosuppression in response to antigens of M. tuberculosis cultures were lacking in the majority of patient records.Nonetheless, a decreased response to TST was reported in a cohort of patients infected with HTLV-1 in Japan , and a dM. tuberculosis has been shown to be dependent on INF-γ-activated macrophages and, interestingly, HTLV-1 induces the proliferation and activation of CD4+ T-cells, especially type 1, which consequently produce elevated levels of INF-γ and TNF [M. tuberculosis antigens [The underlying cause surrounding the increased susceptibility to TB observed in individuals infected with HTLV-1 remains unknown. Nonetheless, it is possible that immunological changes induced by HTLV-1 might also affect TB susceptibility. The protective immune response against  and TNF , 34. It antigens . FurtherThe present study is limited by the fact that information regarding the status of diabetes, alcoholism and smoking habits, which are all recognized risk factors for TB, was not available for all individuals. In addition, it was not possible to determine how many patients with TB and HIV infection (in both HTLV-1 infected or uninfected groups) were under antiretroviral treatment. As such, we cannot exclude the possibility that HTLV-1-infected patients were more prone to develop TB as a result of these comorbidities. It is also possible that a portion of the cohort, which was regularly followed due to HTLV-1 infection, presented increased rates of TB due to regular surveillance. As TB and HTLV-1 were diagnosed in different medical settings, 51 % (17/33) of HTLV-1-infected individuals received their TB diagnosis in a primary care setting, while 67 % (27/40) of HTLV-1-infected individuals received a TB diagnosis in secondary/tertiary medical units. In addition, in over half of these coinfected patients, HTLV-1 serological status was not known at the time of TB diagnosis.Unfortunately, it was not possible to determine the successful rate of linkage. However, since these databases were not very large, the results from both databases were also visually verified. Thus, we believe that the linkage rate was likely high. We were also unable to determine the number of persons lost to follow-up during the study period. It is possible that unreported cases resulted from a myriad of factors, including loss of contact, death, change-of-address, etc. Moreover, it is interesting to note that the World Health Organization  estimateIn summary, the risk of developing TB was found to be almost three times greater in people living with HTLV-1 than among those without this viral infection. HTLV-1/TB individuals were more commonly female, aged 50 years or older, and had lower income and educational levels than individuals infected only with TB. These epidemiological features overlap those present in the profile of HTLV-1 infection. Each infection is strongly associated with greater social vulnerability, reinforcing the neglected characteristic of both diseases. The results presented herein indicate that, in countries endemic for both infections, health professionals should actively monitor HTLV-1 infected patients for respiratory symptoms.


RIG-I is a pattern recognition receptor and recognizes cytoplasmic viral double-stranded RNA (dsRNA). Influenza A virus, hepatitis C virus, and several other pathogenic viruses are mainly recognized by RIG-I, resulting in the activation of the innate immune responses. The protein comprises N-terminal two caspase activation and recruitment domains (2CARDs), an RNA helicase domain, and the C-terminal domain (CTD). The CTD recognizes 5′-triphosphate viral dsRNA. After recognition of viral dsRNA, the protein harbors K63-linked polyubiquitination essential for RIG-I activation. First, it was reported that TRIM25 ubiquitin ligase delivered K63-linked polyubiquitin moiety to the 2CARDs. The polyubiquitin chain stabilizes a structure called the 2CARD tetramer, in which four 2CARDs assemble and make a core that promotes the aggregation of the mitochondrial antiviral-signaling (MAVS) protein on mitochondria. MAVS aggregation then triggers the signal to induce the innate immune responses. However, subsequent studies have reported that Riplet, MEX3C, and TRIM4 ubiquitin ligases are also involved in K63-linked polyubiquitination and the activation of RIG-I. MEX3C and TRIM4 mediate polyubiquitination of the 2CARDs. By contrast, Riplet ubiquitinates the CTD. The physiological significance of each ubiquitin ligases has been shown by knockout and knockdown studies, but there appears to be contradictory to evidence reported in the literature. In this review, we summarize recent findings related to K63-linked polyubiquitination and propose a model that could reconcile current contradictory theories. We also discuss the physiological significance of the ubiquitin ligases in the immune system against viral infection. Pattern recognition receptors (PRRs) recognize viral nucleic acids and trigger a signal to induce the innate immune responses during viral infection , 2. RIG-The RIG-I protein comprises two caspase-activation and recruitment domains (2CARDs) at the N-terminal region, an RNA helicase domain, and a C-terminal domain (CTD) –16. ViraThe RIG-I protein harbors Lys 63-linked (K63-linked) polyubiquitination required for its activation . TRIM25 Ubiquitin ligases add a ubiquitin chain at K but not R residues of the target protein. There are 18 K residues in the RIG-I 2CARDs, and mass spectrometry analysis revealed that the 2CARDs fragment carried K63-linked polyubiquitin chains at K99, K169, K172, K181, K190, and K193 . KnockdoEvidence also suggests that TRIM25 produces unanchored K63-linked polyubiquitin chains in response to viral infection and delivered them to RIG-I . The samAn accumulating body of evidence has shown that TRIM25 delivers K63-linked polyubiquitin moiety to RIG-I 2CARDs for RIG-I activation and that the K172 residue is important for the binding of RIG-I to polyubiquitin chains , 27, 32.Riplet, another ubiquitin ligase, is also involved in K63-linked polyubiquitination and activation of RIG-I. Riplet was first isolated by our yeast two-hybrid screening using the RIG-I CTD fragment as a bait . An immuin vivo.To assess the physiological significance of the protein, we generated Riplet knockout mice. Knockout of Riplet severely impaired the type I IFN and IL-6 production in MEF, macrophages, and conventional dendritic cells following influenza A virus and vesicular stomatitis virus (VSV) infections. In addition, Riplet KO mice were susceptible to VSV infection compared with wild-type mice . These oAn RIG-I C-terminal fragment (735–925 aa region), which includes the linker region and the CTD, suppresses the 2CARD activation , and KagDespite the identification of four ubiquitin ligases, we found that knockout of Riplet alone could abolish the polyubiquitination of the endogenous RIG-I protein , 35. RecPreviously, we have postulated a sequential ubiquitination model that Riplet-mediated polyubiquitination of RIG-I C-terminal region is a prerequisite for the polyubiquitination of the 2CARDs Figure . This moMEX3C or TRIM4 might compensate for the defect of TRIM25 under certain experimental conditions, because these two ubiquitin ligases target the 2CARDs in a similar way Figure . AlthougType I IFN exhibits a strong antiviral effect, and hence several viruses have evolved to suppress the type I IFN production. HCV is a major cause of hepatocellular carcinoma and persistently infects hepatocytes over several decades without exclusion by the host immune system. A viral NS3-4A protease is required to cleave viral polypeptides and produce mature viral proteins; however, it is also important to suppress the host innate immune response. NS3-4A of HCV cleaves MAVS, which results in the release of MAVS from mitochondria . SeveralTRIM25 is also called EFP, and it has been shown that TRIM25/EFP mediates the polyubiquitination of 14-3-3σ and promotes its proteolysis to suppress the growth of breast tumor cells . Althoug+ T cells and is required for CD8+ T cell proliferation . LGP2 is an RLR, and the CTD structure of the protein is similar to that of RIG-I . Initialferation . It remaHO and MO wrote the manuscript. TK and YF helped the discussion.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.