The use of self-reported measures of chronic disease may substantially underestimate prevalence in low-income and middle-income country settings, especially in groups with lower socioeconomic status (SES). We sought to determine whether socioeconomic inequalities in the prevalence of non-communicable chronic diseases (NCDs) differ if estimated by using symptom-based or criterion-based measures compared with self-reported physician diagnoses.Using population-representative data sets of the WHO Study of Global Ageing and Adult Health (SAGE), 2007–2010 (n=42 464), we calculated wealth-related and education-related concentration indices of self-reported diagnoses and symptom-based measures of angina, hypertension, asthma/chronic lung disease, visual impairment and depression in three ‘low-income and lower middle-income countries’—China, Ghana and India—and three ‘upper-middle-income countries’—Mexico, Russia and South Africa.SES gradients in NCD prevalence tended to be positive for self-reported diagnoses compared with symptom-based/criterion-based measures. In China, Ghana and India, SES gradients were positive for hypertension, angina, visual impairment and depression when using self-reported diagnoses, but were attenuated or became negative when using symptom-based/criterion-based measures. In Mexico, Russia and South Africa, this distinction was not observed consistently. For example, concentration index of self-reported versus symptom-based angina were: in China: 0.07 vs −0.11, Ghana: 0.04 vs −0.21, India: 0.02 vs −0.16, Mexico: 0.19 vs −0.22, Russia: −0.01 vs −0.02 and South Africa: 0.37 vs 0.02.Socioeconomic inequalities in NCD prevalence tend to be artefactually positive when using self-report compared with symptom-based or criterion-based diagnostic criteria, with greater bias occurring in low-income countries. Using standardised, symptom-based measures would provide more valid estimates of NCD inequalities. A significant limitation to the currently available evidence on the magnitude and direction of socioeconomic inequalities in non-communicable chronic diseases (NCDs) is the widespread use of self-reported cases of physician diagnoses as source data. These self-reported data may systematically skew estimated inequalities due to reporting bias. Wealthier and more educated individuals tend to have relatively better access to healthcare as well as greater knowledge about disease conditions, compared with those in lower socioeconomic status (SES) groups.6–8The use of standardised measures of identification of disease  that assume no prior diagnosis or patient knowledge can help minimise reporting bias.In this study, we tested whether and to what extent SES inequalities in the prevalence of NCDs were less marked if estimated using symptom-based or criterion-based measures, which assume no prior diagnosis or patient knowledge, compared with self-reported physician diagnoses. We evaluated the prevalence of five NCDs  in six LMICs. On the basis of the World Bank classification of countries, we grouped China, Ghana and India into ‘low-income and lower middle-income countries’ and Mexico, Russia and South Africa into ‘upper-middle-income countries’. We hypothesise that (1) SES gradients in NCD prevalence would be more likely to be positive if measured by self-reported physician diagnoses than by symptom-based/criterion-based measures, and that (2) these estimated SES inequalities would be greater in China, Ghana and India than in Mexico, Russia and South Africa. We discuss the findings in the light of the observation that lower SES groups in lower-income countries are at a greater disadvantage from their poorer knowledge of NCDs and lower access to healthcare than in richer countries as described above.We used the individual level, cross-sectional data of wave 1 from the WHO Study on Global AGEing and Adult Health (SAGE), covering the years 2007–2010. SAGE is a series of nationally representative samples of persons aged 50+years and younger adults aged 18–49 years in China, Ghana, India, Mexico, Russia and South Africa.The sampling method used for SAGE was based on the design for the World Health Survey 2002–2004, which was drawn from the national census of each country. The sampling details of SAGE have been documented elsewhere.21Standardised survey instruments, interviewer training and translation protocols were used in all SAGE countries. Interviewer-administered questionnaires in the native language of the respondent using local, commonly understood terms, with back translation to English to ensure accuracy and comparability, were used. Interviews were conducted between 2007 and 2010. The pooled wave 1 six-country totals for individual respondents included 34 124 respondents aged 50 years and 8340 aged 18–49 years. The individual level response rates for each country were as follows: China (93%), Ghana (81%), India (68%), Mexico (53%), Russia (83%) and South Africa (75%). SAGE achieved a very high response rate for two reasons. First, the majority of the respondents were participants in the World Health Survey 2002–2004 and followed up. Second, local institutions applied concerted efforts in collaboration with local partners to improve survey response. This included conducting a minimum of three revisits to households.Ethical clearance was obtained from local research review boards for each participating SAGE site, in addition to the WHO Ethical Review Committee. Informed consent was obtained from each respondent prior to interview.Of the total eight NCDs reported in the SAGE survey, we considered five major NCDs: angina, hypertension, chronic lung diseases ) and asthma, visual impairment and depression. We excluded diabetes, stroke and arthritis because data were insufficient or unavailable for developing symptom-based measures.The descriptions of survey questions for self-reported physician diagnoses and the criteria used for deriving symptom-based measures for each NCD were presented in web appendix table 2.We derived symptom-based/criterion-based measures from the literature and previous household surveys. Symptom-based prevalence measures, which were based on the respondent's self-report, were used for angina and depression. Objective measures of prevalence based on internationally accepted standard criteria were employed for hypertension, asthma and chronic lung diseases, and visual impairment. The symptom-based measure for angina was from the WHO-Rose angina questionnaire,We used wealth (asset-score index) and education as two distinct indicators of SES. A validated asset  score index, as originally reported in the WHO SAGE data set, was derived using the WHO standard approach to estimate permanent income from survey data on household ownership of durable goods, neighbourhood and dwelling characteristics, and access to water, sanitation and electricity.i is the ill health of the ith individual, µ is the weighted mean of the ill-health, Ri is the fractional rank of the ith individual in terms of the index of household economic status. The concentration index can vary between −1 (concentrated among lower SES) and +1 (concentrated among the higher SES), and zero when there is no inequality.We estimated wealth-based and education-based concentration indices to estimate the SES inequalities in NCDs. The concentration index has been increasingly used to measure socioeconomic inequalities in health in an objective and readily understandable manner.We adjusted the estimates of concentration index and logistic regression models of symptom-based/criterion-based measures of NCD for the differential healthcare access across SES groups, which can potentially bias the symptom-based/criterion-based measures. For example, the acute pain symptom from angina is often amenable to medication , but otherwise would be largely asymptomatic if the patient is on chronic treatment. Access to these treatments might well be different for different SES respondents and might well account for the differences in the outcomes. In our models, we included a dichotomous variable of whether the respondent has taken medicines/treatments in the past 2 weeks for the criterion-based measure of hypertension, and asthma and chronic lung diseases, undergone surgery to correct visual impairment, and taken medicines/treatments in the past 12 months for the symptom-based angina and depression. Longer time windows for symptom-based angina and depression were used as assessment of these was based on a 12-month recall-period.All statistical estimations were done with STATA V.13.1 .Marked differences in the prevalence levels between self-reported physician diagnoses and symptom-based/criterion-based measures of NCDs were found between countries . In ChinIn Mexico, Russia and South Africa, we found a higher prevalence of hypertension and visual impairment using criterion-based measures, but a reverse trend was evident for asthma and chronic lung disease. In contrast, findings for angina and depression were heterogeneous, with the prevalence of symptom-based angina being lower in Russia and South Africa but higher in Mexico; also, the prevalence of symptom-based depression was lower in Mexico and South Africa, and higher in Russia.Within-country prevalence levels of symptom-based/criterion-based measures were higher among those with lower SES compared to self-reported diagnoses for most NCDs in China, Ghana and India . self-report) for hypertension, angina, visual impairment and depression were more concentrated among higher SES individuals, whereas symptom-based/criterion-based measures (Csymptom or Ccriterion-based) of these NCDs showed either concentration among lower SES individuals or attenuation in the SES inequalities. For example, the age-standardised wealth-related concentration index of angina showed positive values (concentration among higher SES) for self-reported diagnoses and negative values (concentration among lower SES) for symptoms-based diagonoses . Conversely, self-reported diagnoses of asthma and chronic lung diseases in China, Ghana and India were concentrated among lower SES individuals.In China, Ghana and India, the prevalence of most NCDs was concentrated among higher SES groups based on self-reported diagnoses. Conversely, SES patterning was either attenuated or was concentrated in lower SES groups when based on symptom-based/criterion-based measures. Self-reported diagnoses . Self-reported angina was concentrated among higher SES individuals in Mexico (Cself-report 0.19 vs Csymptom −0.22) and South Africa (Cself-report 0.37 vs Csymptom 0.02) while symptom-based angina was concentrated in lower SES individuals in Mexico but turned to get less positive in South Africa. Indicating similar patterns, symptom-based angina in Russia was more common among lower SES individuals. However, the SES concentration of most NCDs such as asthma and chronic lung diseases, visual impairment and depression in Mexico, Russia and South Africa showed more heterogeneous patterns. Web appendix table 7 summarises the main findings on the SES inequalities between self-reported diagnoses and symptom-based measures of specific NCDs across countries.In Mexico, Russia and South Africa, the patterns of SES inequalities between self-reported diagnoses and symptom-based/criterion-based measures showed a mixed picture with some NCDs showing patterns similar to China, Ghana and India and others showing a heterogeneous pattern. More specifically, there was a higher prevalence among lower SES individuals of symptom-based/criterion-based measures of angina and hypertension than self-reported diagnoses. Self-reported hypertension was concentrated among higher SES individuals, whereas criterion-based measure of hypertension was concentrated among lower SES individuals . For example, self-reported and symptom-based angina was more prevalent among women than men across all the six countries, with the exception of India, where a lower prevalence of self-reported angina was reported (3% in women vs 3.2% in men). Prevalence rates using self-reported and symptom-based/criterion-based measures in men and women also varied between NCDs. For example, the criterion-based measure of hypertension was more prevalent among men than women as compared with the self-reported measure in most countries, and a heterogeneous pattern for most of the other NCDs.Patterns of SES inequality in NCDs also differed by sex and country (see web appendix table 9). In all countries except South Africa, the symptom-based measure of angina was more highly concentrated among lower SES men and women. Furthermore the criterion-based measure of visual impairment was amore among lower SES men and women in most countries, with the exception of higher prevalence among higher SES in China and South Africa. In contrast, the symptoms-based measure of depression was more among lower SES women across countries (except Mexico and Russia) and more among higher SES men across countries (except India).Education and wealth-related concentration indices did not always show similar patterns. For instance, both prevalence measures of angina in South Africa showed a concentration among individuals with higher wealth and among the less educated. Furthermore, there was little evidence of concentration of hypertension by education gradient in any country. This was in contrast to the gradient seen for the wealth indicator.Our analysis of NCD inequalities found that self-reported diagnoses of hypertension, angina, visual impairment and depression tended to give rise to positive SES gradients, whereas symptom-based or criterion-based measures tended to display less positive gradients or even negative gradients (concentration in the lower SES groups). These differences in estimated gradients were more pronounced in China, Ghana and India (low-income and lower middle-income countries) than in Mexico, Russia and South Africa (upper-middle-income countries). Moreover, we found higher prevalence rates among women than men for most NCDs across the countries.These findings must, however, be contextualised by important limitations. First, our data do not include younger people (below 18 years). However, this would have a limited bearing on the findings, except for asthma, as most of the conditions studied occur largely in adults. Second, we could not assess the extent of access to healthcare and other disease specific features across different SES groups as explanations for differences in self-reported diagnoses and symptom-based/criterion-based measures. Third, we incorporated standardised measures to identify NCDs to the extent possible, however, some of our symptom-based measures, namely of angina and depression, were based on self-reports of symptoms, and the reliability of such measures are also limited by lack of comprehensiveness and are subject to their own reporting biases. Another related potential source of variance in the results can arise from the variations in the performance on the standard tests between respondents of different SES groups. Furthermore, most symptoms were measured at a single time point. Individuals with angina, hypertension, visual impairment and depression may not always necessarily experience symptoms due to medication or other related reasons, resulting in incomplete case ascertainment using symptom-based measures. Finally, our symptom-based estimates did not consistently detect a higher prevalence of the NCDs than self-reported diagnoses. For example, the spirometric prevalence estimates of asthma and chronic lung diseases were lower than those of self-reported diagnoses, probably due to a misreporting of recurrent acute respiratory diseases such as asthma or COPD, and/or inability of spirometry to detect asthma that is in remission.Our study informs methodological development for producing more robust community-based estimates of NCD prevalence in LMIC settings. We used nationally representative data in China, Ghana, India, Mexico, South Africa and Russia, and employed both self-reported diagnoses and symptom-based measures to estimate prevalence of several NCDs across SES groups. Furthermore, we used asset index and education as two distinct SES indicators.These findings provide salient information for the ongoing debate about whether NCDs in LMICs are concentrated among the rich or the poor, the latter being the case in most high-income countries.Our study findings require further investigation using data from a greater number of LMICs covering a wider spectrum of economic development. Longitudinal or repeat survey data would enable stronger inferences on whether ‘switching’ from a positive to negative gradient within a country occurs over time . Future surveys should incorporate more comprehensive and reliable indicators of pathology such as biomarkers, and also more detailed information on the medications of each NCD so that the issue of differential healthcare across SES can be incorporated for more robust estimates of symptom-based/criterion-based measures of NCDs. Though we found that self-reported diagnoses of most NCDs across countries were generally concentrated among higher SES individuals whereas symptom-based measures were either concentrated among lower SES individuals or more evenly distributed, we did observe considerable between-country heterogeneity. The underlying reasons for this heterogeneity are a topic for further investigation. These are likely to include differential access to healthcare, public awareness of NCD symptoms, and potentially important cultural and social differences in reporting.Our findings suggest that NCD prevalence estimates solely based on self-reported diagnoses may be misleading if used to determine the burden of disease, targeting interventions and exploring social inequalities in NCDs. Standardised diagnostic measures, using clinical assessment augmented by investigations, should be implemented in community surveys to estimate the true prevalence of NCDs and inform policies in LMICs. If this is not feasible due to resource constraints, a more comprehensive set of questions on specific NCDs should be employed to minimise possible bias due to the under-reporting and underdiagnosis among lower SES groups. Better methods of surveillance and monitoring are needed in LMICs to determine trends in incidence and mortality of specific NCDs and to evaluate health programmes for NCDs in terms of their impact on social inequalities in health.48Self-reported measures of non-communicable chronic diseases (NCDs) are likely to under-estimate the true magnitude of the problem in lower socioeconomic groups.Self-reported diagnoses of angina, hypertension, visual impairment and depression tended to give rise to positive socioeconomic status (SES) gradients, gradients (ie concentrated among higher socioeconomic groups) whereas symptom-based or criterion-based measures of these diseases showed either less positive gradients or even concentrated among lower socioeconomic groups.These differences in estimated SES gradients were more pronounced in China, Ghana and India (low-middle and lower middle-income countries) than in Mexico, Russia and South Africa (upper-middle-income countries).Using standardised, symptom-based measures would provide more valid estimates of NCD inequalities.


Most cases of idiopathic autism spectrum disorder (ASD) likely result from unknown environmental triggers in genetically susceptible individuals. These triggers may include maternal exposure of a fetus to minute concentrations of pharmaceuticals, such as carbamazepine (CBZ), venlafaxine (VNX) and fluoxetine (FLX). Unmetabolized pharmaceuticals reach drinking water through a variety of routes, including ineffectively treated sewage. Previous studies in our laboratory examined the extent to which gene sets were enriched in minnow brains treated with pharmaceuticals. Here, we tested the hypothesis that genes in fish brains and human cell cultures, significantly enriched by pharmaceuticals, would have distinct characteristics in an ASD-associated protein interaction network. We accomplished this by comparing these groups using 10 network indices.A network of 7212 proteins and 33,461 interactions was generated. We found that network characteristics for enriched gene sets for particular pharmaceuticals were distinct from each other, and were different from non-enriched ASD gene sets. In particular, genes in fish brains, enriched by CBZ and VNX 1) had higher network importance than that in the overall network, and those enriched by FLX, and 2) were distinct from FLX and non-enriched ASD genes in multivariate network space. Similarly, genes in human cell cultures enriched by pharmaceutical mixtures  and valproate  had similar network signatures, and had greater network importance than genes in the overall ASD network.The results indicate that important gene sets in the ASD network are particularly susceptible to perturbation by pharmaceuticals at environmental concentrations. Autism is a complex neurobiological developmental disorder belonging to a group of conditions known as Autism Spectrum Disorder (ASD) ,2. ASD hIn most other instances, studies suggest that ASD results from unknown environmental triggers acting on genetically susceptible individuals -9. SusceToday, genetically susceptible individuals may be exposed to combinations of 3000 synthetic chemicals via air, food and water . SynthetPimephales promelas) were exposed to fluoxetine (FLX), venlafaxine (VNX) and carbamazepine (CBZ) individually and in mixtures at environmentally relevant concentrations [In a previous study, we investigated psychoactive pharmaceuticals presented at very low concentrations in the environment ,11. Juvetrations , gene extrations .We found previously that fathead minnows exposed to PPCPs had a significantly altered behavioral phenotype compared to a non-exposed (control) group , and thaTo address these hypotheses, we constructed a protein-protein interaction (PPI) network of gene products known to be associated with ASD ,18, and We postulated that proteins within PPCP-enriched groups would have both distinct network characteristics from each other and higher levels of importance in the ASD protein-protein network. Support of this hypothesis would suggest that any dysregulation in the expression of PPCP-enriched proteins would result in large impacts to the network due to ripple effects on downstream proteins. To address this question, we generated an ASD protein-protein interaction network. The network consisted of 7212 nodes, with approximately 2000 primary neighbor proteins and 5000 secondary neighbor proteins , compared to the overall network, for network indices widely deemed to be most important in identifying nodal importance . The omnibus null hypothesis of equal location shifts for groups was rejected for all four of these measures allowing protected pairwise comparisons of groups . In thesF3,1936 = 3.68, P = 0.001). In pairwise PERMANOVA tests CBZ and VNX groups were indistinguishable from each other . Both of these groups, however, were significantly different from FLX  after adjustment for family-wise type I error . Further, both the CBZ and VNX groups were statistically distinct from the non-enriched portion of the ASD network , whereas the FLX group was not significantly different from the non-enriched fraction of the ASD-network . The basis for these results is graphically evident in a non-metric multidimensional scaling (NMDS) dimension reduction of network space  and non-metric multidimensional scaling (NMDS). The fish brain cell genes of the non-enriched portion of the ASD network and individual pharmaceutical groups were significantly different in network space  and valproate (VPA), and carried out transcriptome analysis. We then compared network characteristics of gene set groups, enriched by pharmaceuticals, both to each other, and to the overall network.We found that both the mixture and VPA group locations were significantly higher than the overall network with respect to degree centrality, betweenness centrality, and stress. The mixture and VPA groups were, however, not statistically distinguishable from each other with respect to these measures Figure .F2,1690 = 2.34, P = 0.017). Pairwise differences among groups, however, were not significant after adjustment for family-wise type I error . Characteristics of the VPA and mixture groups that may distinguish them from the overall ASD network are evident in Figure We rejected the omnibus null hypothesis that collective ASD network characteristics were equal for all groups, including the non-enriched portion of the ASD network , Venlafaxine (50 μg/l) and Fluoxetine (10 μg/l) at concentrations, which were detected in the surface waters in US 0 μg/l, V. InteresIn the context of fish brain tissues our primary hypothesis was that human homologs of protein products of genes in synaptic cells, perturbed by exposure of pharmaceuticals, would have distinct ASD network parameters. To test this, we determined the extent to which protein products of genes from gene sets enhanced by individual pharmaceuticals in fish brains were interconnected in the ASD-associated protein-protein interaction network. As predicted, PPCP-enhanced sets had higher degree, closeness, betweenness and stress than the overall network. Further, we found that CBZ and VNX groups had higher degree centrality, closeness centrality, stress and betweenness centrality than FLX group, and were distinct from the FLX group and the non-enriched portion of the ASD-network in multivariate network space Figure  &3. InteTo extend these findings to human tissues, we cultured and differentiated human SK-N-SH neuronal cells and carried out transcriptome analysis after exposing them with the mixture  at environmental concentrations and valproate at a clinical dosage . We thenCarbamazepine is a mood stabilizer and anticonvulsant used in conjunction with valproate to treat bipolar disorders and epilepsy ,24. CBZ Genes connected to a large number of neighbors in the ASD-associated protein-protein interaction network may play an important role in neuronal growth, development, and regulation. We found that protein products from gene sets with enriched expression in fish brains and human neuronal cells, due to an exposure of psychoactive pharmaceuticals, were comparatively more inter-connected to other neighboring proteins than protein products of non-enriched gene sets. Thus, these genes are more likely to experience altered expression upon exposure to PPCPs, causing further dysregulation of the whole interactome due to a ripple effect.http://www.cytoscape.org/ as an open source java application [A list of 304 ASD-associated genes was retrieved from the Autism Database (AutDB) , hereaftlication .We used the MiMi Cytoscape plugin  to creatα = 0.05) enriched by the psychoactive pharmaceuticals carbamazepine, venlafaxine and fluoxetine individually. We merged all single gene sets that were enriched by particular pharmaceuticals into separate groups, resulting in an enriched gene set for each of the pharmaceuticals.  enriched gene sets. Thus, we defined two groups: mixture (MIX) and valproate (VPA) containing all gene sets significantly enriched by the corresponding treatment [In a parallel application, we cultured and differentiated human neuronal SK-N-SH cells with retinoic acid. After differentiation, we treated cells with a mixture treatment  at environmental concentrations ,29. As areatment  . This necessitated the use of robust procedures for hypothesis testing and estimation. For location  summaries we felt that the pseudomedian (Hodges-Lehman location estimator) was the most appropriate measure . For a sP-values for these tests were corrected for family-wise type I error using Holm's procedure [Characteristics of treatments were considered in two ways. First, nodal network outcomes for particular indices were compared to the pseudomedian values of the complete network using one-sample Wilcoxon rank sum tests with upper tailed alternative hypotheses. Second, nodal network outcomes for particular treatment were compared to each other using Brunner-Dette-Munk (BDM) rank-based permutation tests . BDM tesrocedure .P-values were calculated using 10,000 permutations of the vector of treatment assignments with respect to the resemblance matrix. To depict patterns in multivariate network space we used nonmetric multidimensional scaling . This mg .ASD-associated PPI network Cytoscape file. Cytoscape compatible file of Core network is available at Click here for filehttps://sites.google.com/a/isu.edu/aho/Complete gene data sets for fish and human cells . These files are also available at Click here for filehttps://sites.google.com/a/isu.edu/aho/Complete data of gene sets for fish and human cells. Excel files containing a complete data of all gene sets . These files are available at Click here for filehttps://sites.google.com/a/isu.edu/aho/Nodal summary statistics for gene set groups. The file contains summary statistics for all nodes in the network. This file is available at Click here for file


Abiotic stresses  are among the most challenging threats to agricultural system and economic yield of crop plants. These stresses (in isolation and/or combination) induce numerous adverse effects in plants, impair biochemical/physiological and molecular processes, and eventually cause severe reductions in plant growth, development and overall productivity. Phytohormones have been recognized as a strong tool for sustainably alleviating adverse effects of abiotic stresses in crop plants. In particular, the significance of salicylic acid (SA) has been increasingly recognized in improved plant abiotic stress-tolerance via SA-mediated control of major plant-metabolic processes. However, the basic biochemical/physiological and molecular mechanisms that potentially underpin SA-induced plant-tolerance to major abiotic stresses remain least discussed. Based on recent reports, this paper: (a) overviews historical background and biosynthesis of SA under both optimal and stressful environments in plants; (b) critically appraises the role of SA in plants exposed to major abiotic stresses; (c) cross-talks potential mechanisms potentially governing SA-induced plant abiotic stress-tolerance; and finally (d) briefly highlights major aspects so far unexplored in the current context. In facttely 3°C . Hence, tely 3°C .Matricaria chamomilla, 50 and 250 μM SA concentrations were reported to, respectively, promote and inhibit growth (Vigna radiata but an inhibited growth was evidenced with 1.0 mM SA (non-expressor of pathogenesis-related genes 1 (NPR1) has been evidenced  bark and leaves for medicinal purposes. The importance of willow  bark has also been shown in 1763 when the Reverend Edward Stone informed the Royal Society that it contained substances that relieved the symptoms of “ague”  effectively. Until 19th century the active principle of willow was not known, but later on the salicylates, methyl salicylate (MeSA), saligenin , and their glycosides were isolated from extracts of willow and other plants. The SA was isolated and purified from willow and meadowsweet in the first half of the 19th century  bark by Raffaele Piria in 1838. The first commercial production of synthetic SA began in Germany in 1874. Aspirin, a trade name for acetylsalicylic acid, was introduced by the Bayer Company in 1898 and rapidly became one of world’s best-selling drugs and it replaced the use of SA by producing less gastrointestinal irritation yet has similar medicinal properties. With the further advancement in scientific research in 20th century, uses of SA as a treatment for acne, psoriasis, warts, and calluses became common. The use of SA as a skin softener, for removal of dead skin cells, dirt, oil and debris and cleaning of pores is widespread. In spite of the fact that the mode of medicinal action of salicylates is a subject of continual debate, they are being used to treat human diseases ranging from the common cold to heart attacks. As aspirin undergoes spontaneous hydrolysis to SA, the two compounds have similar effects in plants.Centuries ago Americans, Indians, and Greeks used willow tree bark and leaves to cure aches and fevers, but it has been documented that Hippocrates prescribed the compound to relieve pain for women during child birth and fever was later recognized as SA. Ancient texts also indicate that Babylonians, Assyrians, and Chinese  used wil century  and was  century . In 1928 century . The nam century  is origiFigure 1).Salicylic acid is a seven carbon (C) containing, naturally occurring phenolic compound and endogenously synthesized signaling molecule in plants. The shikimic acid pathway and the malonic acid pathway are the two main pathways known to be involved in the synthesis of plant phenolics. The shikimic acid pathway takes part in the biosynthesis of most plant phenolic compounds. It simply converts simple carbohydrate precursors derived from glycolysis and pentose phosphate pathway to the aromatic amino acids including SA precursor, phenylalanine . The mosArabidopsis, ICS has been found to be involved in the biosynthesis of SA during plant defense process  confirmed that in the absence of ICS1, ICS2 can encode a functional ICS enzyme but in limited amounts  in plants helps in their protection against environmental stresses. These enzymes are key regulators of SA functions and are known to be modulated by different abiotic and biotic stress factors. In  process . Synthesolve ICS . SA applthaliana . In addi amounts . Under ssistance . The inva plants . Both Cdcine max . Isolati-1)] exposed Oryza sativa -mediated decrease in cellular malondialdehyde  and ROS -GSH pathway enzymes , and triggering a series of signaling cascades and plant defense responses  on plant growth and development raised concerns on the need of protection mechanisms . IncreasCapsicum annuum leaves  in UV-B-exposed transgenic NahG A. thaliana plants  temperature stress  and high (heat) temperatures have become a potential abiotic stress-threat to crop plants. Temperature stress affects many plant-physiological and biochemical processes and induces molecular mechanisms and gene expression to modulate plants responses . SA-suppe stress . Exogenoe stress .Citrus limon; H. vulgare genotypes. In another report, SA significantly protected ultra-structures in Musa acuminata seedlings under chilling stress (S. lycopersicum fruit as a result of low concentrations of (0.01 mM) MeSA-mediated induction in the synthesis of some stress proteins, such as PR proteins -mediated increased synthesis of total phenolics and the activity of PAL were reported to improve chilling tolerance in cold-stored lemon fruit , increased redox ratios of AsA and GSH, and maintained Ca2+-homeostasis were reported in SA-supplemented and cold/heat treated V. vinifera .The application of 5.0 μM SA induced the expression of genes in Mitragyna speciosa . Among tIn order to enlighten the potential mechanisms underlying SA-mediated improved abiotic stress tolerance in plants, this section briefly appraises recent reports available on the interaction of SA with major osmolytes, mineral nutrients, secondary metabolites, and other phytohormones, and SA-involvement in ROS-signaling and the modulation of antioxidants.To counteract the adverse effects of abiotic stresses-induced excess ROS production, plants have developed mechanisms facilitating their adaptation to osmotic and ionic stresses. Nevertheless, to maintain osmotic balance plants have well developed protective mechanism termed as osmoregulation mediated by osmolytes such GB, Pro, soluble sugars, amines etc. These compounds do not interfere with the other plant metabolic processes and contribute to the turgor-maintenance in stressed plants .Rauwolfia serpentina. Recently, V. radiata. It was shown that SA (at 0.5 mM) induced GB-accumulation through increased methionine content and suppressed excess ethylene formation under salinity stress. Similar effect was observed by these authors with the application of SA-analog, 2, 6, dichloro-isonicotinic acid on GB accumulation and alleviation of salinity-induced adverse effects on photosynthesis and growth.Glycinebetaine is considered as an effective compatible solute for osmotic adjustment and protection against osmotic stress , salt stLens esculenta  alleviated heat stress in in T. aestivum by increasing Pro-production as a result of SA-mediated increase in γ-glutamyl kinase and decrease in Pro oxidase activity  can improve overall plant growth under B-toxicity and salinity stress by stimulating the accumulation of mineral elements including K, Mg, Mn, N, and P  stresses cause imbalance between generation and scavenging of ROS, and eventually lead to a physiological condition known as oxidative stress. Thus, a number of consequences such as oxidative modification of vital biomolecules, cell death, and the arrest of plant growth and development can be possible under uncontrolled oxidative stress  and superoxide-dismutating enzymes (SOD) were also modulated with SA in plants exposed to drought , phospholipid hydroperoxide GPX (GPX2), and DHAR (DHAR), GR (GR), GST (GST1 and GST2), MDHAR (MDHAR), and GSH synthetase (GS) was advocated as a major mechanisms underlying previous role of SA in salinity tolerance via AsA and GSH  by enhancing both SOD and POD (2+ (a second messenger) and caused a transient increase in H2O2 which in turn was argued to induce antioxidant enzymes and eventually to decrease in cellular ROS  and S  mutant plants plays a significant role in auxin-signaling in stressed plants. Furthermore, in these mutants, PR-1 was induced to a great extent as compared with SA-treated wild-type plants, where the negative effect of SA on auxin signaling indicates the occurrence of an antagonism between auxin and SA-signaling pathways -mediated inhibition in ACS activity under salinity stress  maximally compared to exogenous individual SA and SNP under Fe-deficiency (NPR1 gene, a master regulator of SA-mediated defense genes is a critical component of 24-epibrassinloide-mediated increase in thermo- and salinity tolerance in A. thaliana (PR genes can be possible with SA and JA, respectively, (Nitric oxide, a major ubiquitous signal in plant systems, plays significant roles in a wide range of responses to environmental and endogenous cues . SA is aeedlings . SA can eedlings . Under Nficiency . The strficiency . It was thaliana . There othaliana ,b. The actively, .Abiotic stress has been recognized as a major threat to the agricultural system. To cope up the adverse effects of abiotic stress, plants induce several physiological processes and molecular mechanisms. Investigations have shown SA as a strong and potential tool in reducing or alleviating the adverse effects of abiotic stress in plants. Application of SA has been shown to be beneficial for plants either in optimal or stress environments. SA can regulate various plant metabolic processes and modulate the production of varied osmolytes and secondary metabolites, and also maintain plant-nutrient status hence, to protect plants under abiotic stress conditions. Literature appraised herein confirmed the focus of the studies related with SA in abiotic stressed plants mainly on unveiling various physiological/biochemical processes.NPR1, 3, and 4 are discovered as the SA receptor in plants. However, it is required to perform exhaustive molecular studies cross-talking NPR1, NPR3, and NPR4, and their cumulative potential role in SA-perception in orchestrating defense gene expression in abiotic stressed plants. Unveiling intricacies of the complete SA-signaling in abiotic stresses, and the relationship between distinct facets of SA in plant immunity and abiotic stresses responses would be fascinating and rewarding. Meanwhile, more genomics and proteomics studies are expected to broadly reveal SA-responsive genes and proteins upon stresses. Since SA influences the plant functions in a dose dependent manner and a high SA-concentration doesn’t profit stress tolerance, abiotic stress-regulated SA-catabolism maybe a field worth further investigation. Molecular dissection is also required to unravel insights into the SA-mediated control of other the production and/or signaling of specific plant hormones/metabolites, and their feed-back influence in the machinery responsible for controlling SA-endogenous levels. Overall, finer details of SA-mediated defense networks/plant-immunity as well as further insights into the cross-talk of SA with other defense signaling pathways in abiotic stressed plants can be uncovered through adopting an integrated approach incorporating genetics, molecular biology, biochemistry, genomics, bioinformatics techniques, and computational biology.There are still a few of interesting questions awaiting further investigation. For example, 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.


Serum alkaline phosphatase (ALP) levels have been reported to be associated with all-cause and cardiovascular mortality in peritoneal dialysis (PD) patients. However, it is unclear whether serum ALP levels predict infection-related clinical outcomes in PD patients. The aim of this study was to determine the relationships between serum ALP levels, infection-related mortality and hospitalization in PD patients.PD patients from the Clinical Research Center registry for end-stage renal disease, a multicenter prospective observational cohort study in Korea, were included in the present study. Patients were categorized into three groups by serum ALP tertiles as follows: Tertile 1, ALP <78 U/L; Tertile 2, ALP = 78–155 U/L; Tertile 3, ALP >155 U/L. Tertile 1 was used as the reference category. The primary outcomes were infection-related mortality and hospitalization.A total of 1,455 PD patients were included. The median follow-up period was 32 months. The most common cause of infection-related mortality and hospitalization was PD-related peritonitis. Multivariate Cox regression analyses showed that patients in the highest tertiles of serum ALP levels were at higher risk of infection-related mortality  after adjustment for clinical variables. Higher tertiles of serum ALP levels were associated with higher risk of infection-related hospitalization .Our data showed that elevated serum ALP levels were independently associated with a higher risk of infection-related mortality and hospitalization in PD patients. Alkaline phosphatase (ALP) is a hydrolase enzyme that removes phosphate from nucleotides and proteins and is used as an early differentiation marker of osteoblast and osteoblastic activity . In addiPeritoneal dialysis (PD) patients may have different bone metabolism from HD patients , and areHowever, there are few biomarkers predicting infection-related clinical outcomes in PD patients. A previous study demonstrated that bone cell differentiation interplays with B cell differentiation, which indicates that bone metabolism may influence the innate immune system . FurtherTherefore, considering serum ALP levels as an early marker of bone cell differentiation as well as a biomarker of CKD-MBD, we postulated that serum ALP levels may be associated with infection-related clinical outcomes in PD patients. However, limited data are available regarding the relationship between serum ALP levels and infection-related clinical outcomes in PD patients.The aim of this study was to determine whether serum ALP levels are associated with infection-related mortality and hospitalization in PD patients through a multicenter prospective observational cohort study in Korea.All patients in this study participated in the Clinical Research Center (CRC) registry for end-stage renal disease (ESRD). This study is an observational prospective cohort study of patients with ESRD from 31 centers in Korea. The study was performed from April 2009 to April 2015, and included adult (>18 years of age) dialysis patients. A total of 1,801 patients with PD treatment were enrolled in this study. For the present study, patients were excluded for incomplete or missing values that made information unclear and covariate outlier data (n = 346). Finally, 1,455 patients were enrolled. The CRC for ESRD was approved by the medical ethics committees of the participating hospitals and informed consent was obtained from all patients before inclusion.This study was approved by the institutional review board at each center  and performed in accordance to the Declaration of Helsinki. Written informed consent was obtained from all patients.Demographic and clinical data including age, sex, height, weight, body mass index (BMI), co-morbidities, laboratory investigations and therapeutic characteristics were recorded at the time of enrollment. Assessments of dialysis characteristics and measurements of health were performed every 6 months until follow-up was complete. Cardiovascular disease was defined as the presence of coronary artery disease, congestive heart failure, peripheral vascular disease or cerebrovascular disease. Serum hemoglobin, albumin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), calcium, phosphorus, intact parathyroid hormone (PTH), total cholesterol (TC), triglyceride (TG), uric acid and high-sensitivity C-reactive protein (hsCRP) were determined from blood samples. Serum ALP levels were measured at 30°C using fasting blood samples and optimal pH was determined to be 9–10 by a standard method of the International Federation of Clinical Chemistry (IFCC)  PatientsThe primary outcomes were infection-related mortality and hospitalization. All patients were followed until death or the end of the study, with censoring of data at the time that a patient underwent renal transplantation or was lost to follow-up because of patient refusal of further participation or transfer to a nonparticipating hospital. For each death and hospitalization, the principal investigators of the clinical center completed a form including the cause of death or hospitalization according to the CRC for ESRD study classification.Data for continuous variables with normal distributions are presented as mean ± SD and those without normal distribution are presented as the median with ranges as appropriate for the type of variable. Student’s t-test, the Mann–Whitney test, one-way ANOVA, or the Kruskal-Wallis test were used, as appropriate, to determine differences in continuous variables. Categorical variables are presented as percentages. The Pearson’s chi-square test or Fisher’s exact test was used to determine the differences in categorical variables.Absolute mortality rates were calculated per 100 person-years of follow-up. The survival curves were estimated using the Kaplan-Meier method and compared using the log-rank test. The Cox proportional hazard regression model was used to calculate the hazard ratio (HR) with 95% confidence interval (CI) for infection-related mortality and hospitalization, using tertile 1 as the reference category. The Cox models were adjusted for significant or nearly significant (p < 0.1) predictors of all-cause mortality in univariate Cox regression analysis including age, hemoglobin levels, serum levels of ferritin, intact PTH, albumin, ALP and duration of dialysis. For adequate control of confounders, important covariates known to be influential based on prior studies and clinical insight, such as sex, diabetes mellitus, cardiovascular disease and serum hs-CRP levels were retained in the multivariate Cox regression model regardless of their statistical significance. Analyses were adjusted for potential confounders using two models. Model 1 was adjusted for age and sex. Model 2 was adjusted for age, sex, diabetes mellitus, cardiovascular diseases, hemoglobin levels, serum levels of ferritin, hs-CRP, albumin, AST, ALT, TC, calcium and phosphate. A value of P < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS 16.0 software .A total of 1,455 PD patients were included. The median serum ALP level was 104 IU/L . Baseline characteristics of the study population by tertiles of serum ALP levels are shown in Linear regression analysis indicated that serum ALP levels were associated with clinical variables . In the The median follow-up period was 32 months . During the follow-up period, 188 patients left the study. The reasons for censoring included kidney transplantation (n = 91), transfer to a nonparticipating hospital (n = 65), refusal of further participation (n = 11) and other (n = 21). Cardiovascular disease was the leading cause of death , followed by infection-related disease .There were 141 infection-related deaths during the follow-up period. The absolute infection-related mortality rate was 3.6 deaths per 100 person-years. A total of 899 hospitalization events occurred during the follow-up period. The most common cause of hospitalization was infection-related hospitalization . In this prospective observational study, we demonstrated that higher serum ALP levels were associated with increased infection-related mortality and hospitalization in PD patients independent of other markers of CKD-MBD, including serum calcium, phosphorus and intact PTH, and independent of liver disease. To our knowledge, this is the first multicenter prospective study demonstrating associations between serum ALP levels and infection-related mortality and hospitalization in PD patients.Some large cohort studies have demonstrated associations between serum ALP levels and all-cause mortality and cardiovascular mortality in PD patients . HoweverOur findings support the hypothesis that elevated ALP levels can affect infection-related clinical outcomes. Furthermore, because infection-related mortality is one of the most common causes of death in PD patients, our findings underscore the prognostic power of serum ALP level to predict non-cardiovascular clinical outcomes, especially infection-related mortality and hospitalization, in PD patients.The mechanism underlying the association between ALP and infection-related clinical outcomes in PD patients remains unclear. However, some explanations can be proposed.In response to infection, Toll-like receptors (TLRs), especially TLR4 on immune cells (ICs) play a critical role in pathogen recognition by binding to the lipopolysaccharide (LPS) derived from bacteria, which is the endotoxin as an important pathogen-associated molecular pattern causing sepsis through TLR4 signaling . SubsequSerum ALP is a biochemical marker of high-turnover bone disease and is used to monitor the CKD-MBD. CKD-MBD has been reported to be associated with the development of peritoneal calcifications in a PD patient  and the The Dialysis Outcomes and Practice Patterns Study (DOPPS) reported that higher serum ALP levels were related with lower serum albumin levels and higher infection-related mortality in HD patients . It may One of the most interesting findings in our study is that the association between serum ALP levels and infection-related clinical outcomes was independent of liver diseases. Serum ALP levels are used in clinical practice as a biomarker of liver diseases . Liver dAnother interesting finding of our study is that high serum ALP levels were associated with a higher risk of peritonitis and peritonitis-related morbidity and mortality. PD-related peritonitis is one of the most common infectious complications in PD patients. In this study, PD-related peritonitis was the most common cause of death or hospitalization. Ye et al. previously reported that higher serum ALP was associated with higher risk of short-term adverse outcomes of PD-related peritonitis . In thisThe strengths of our study are the relatively large number of PD patients included and the multi-center design, which involved patients from 31 centers in Korea. And, we demonstrated the relationship between ALP and infection-related death or hospitalization.Our study has some potential limitations. First, our study was an observational study rather than a randomized controlled trial. Second, despite the multicenter nature of the study, the cohort consisted solely of ethnic Korean patients. Thus it is uncertain whether our results can be generalized to other ethnic groups with ESRD. Third, serum ALP levels can change over time. However, repeated ALP measurements were not performed in this study. Therefore we were unable to determine the prognostic value of longitudinal changes of serum ALP levels on infection-related clinical outcomes.In conclusion, we demonstrated that high serum ALP levels are an independent risk factor for infection-related mortality and hospitalization in PD patients. Our findings suggest that serum ALP levels are a useful biomarker for predicting infection-related clinical outcomes in PD patients.


Congenital bicuspid aortic valve (CBAV) is the main cause of aortic stenosis (AS) in young adults. However, the histopathological features of AS in patients with CBAV have not been fully investigated.We examined specimens of aortic valve leaflets obtained from patients who had undergone aortic valve re/placement at our institution for severe AS with CBAV , severe AS with tricuspid aortic valve , and severe aortic regurgitation (AR) with CBAV . We compared the histopathological features among the three groups. Pathological features were classified using semi-quantitative methods  by experienced pathologists without knowledge of the patients’ backgrounds. The severity of inflammation, neovascularization, and calcium and cholesterol deposition did not differ between the CBAV-AS and TAV-AS groups, and these four parameters were less marked in the CBAV-AR group than in the CBAV-AS . Meanwhile, the grade of valvular fibrosis was greater in the CBAV-AS group, compared with the TAV-AS and CBAV-AR groups (both p<0.01). In AS patients, thickness of fibrotic lesions was greater on the aortic side than on the ventricular side (both p<0.01). Meanwhile, thickness of fibrotic lesions was comparable between the aortic and ventricular sides in CBAV-AR patients (p = 0.35).Valvular fibrosis, especially on the aortic side, was greater in patients with CBAV-AS than in those without, suggesting a difference in the pathogenesis of AS between CBAV and TAV. Congenital bicuspid aortic valve (CBAV) is a common congenital heart malformation, with an estimated prevalence between 0.5 and 2% , 2. CBAVIn histological studies, stenotic aortic valve and atherosclerosis share several common features, including lipid accumulation, calcification, infiltration of inflammatory cells and neovascularization , 5. The In addition, CBAV is often associated with abnormalities of the ascending aortic media, resulting in aortic bulb dilatation and aortic regurgitation (AR). Patients with AR develop symptoms and undergo aortic valve replacement at a younger age compared with those with AS. Histological comparison of AS and AR in CBAV patients could clarify the time course and mechanisms of the development of AS in CBAV.The aim of this study was to investigate the histopathological characteristics of AS in patients with CBAV, compared with AS patients with TAV and AR patients with CBAV.We examined specimens of aortic valve leaflets obtained from patients who had undergone aortic valve replacement from April 2010 to September 2015 at our institution for severe AS with CBAV . Groups comprising 24 patients with severely stenotic TAV (TAV-AS group) and 24 CBAV patients with severe AR (CBAV-AR group) were enrolled in parallel. We compared patients’ backgrounds and pathological characteristics among patients with CBAV-AS, TAV-AS and CBAV-AR.Valve tissue was collected at the time of the operation. Patients’ medical records were reviewed to assess the clinical data. This study conformed to the principles outlined in the Declaration of Helsinki. In this study, because patients’ information was anonymized and de-identified prior to analyses, written informed consent was not obtained from each patient. However, we publicized the study by posting a summary of the protocol on the website of the National Cerebral and Cardiovascular Center, and clearly informed patients of their right to refuse enrollment. The full study including these procedures for informed consent and enrollment were approved by the Institutional Review Board of the National Cerebral and Cardiovascular Center (M27-076).We reviewed clinical data in the patients’ medical charts. Hypertension was diagnosed if peripheral blood pressure was >140/90 mmHg or if the patient was taking medication for hypertension. Diabetes mellitus was defined as HbA1c ≥6.5% or receiving anti-diabetic medication. Dyslipidemia was diagnosed if total cholesterol was >220 mg/dL, if low-density lipoprotein cholesterol was >140 mg/dL, if triglyceride was >150 mg/dL, if high-density lipoprotein cholesterol was <40 mg/dL, or if the patient was taking a lipid-lowering agent. All patients underwent cardiac catheterization or coronary computed tomography angiography before operation. Coronary artery disease was defined as coronary stenosis of at least 75%  detected by coronary angiography before the operation. All patients also underwent trans-thoracic echocardiography before operation. Severe AS and severe AR were defined according to the guidelines . Severe The valve samples were obtained vertically through the valve cusps near the center of each leaflet. The aortic valve was fixed in 10% buffered formalin and embedded in paraffin using standard histological procedures. Representative lesions of the obtained materials were macroscopically selected for further processing. The paraffin-embedded specimens were sectioned at 4–5 μm thickness, and stained with hematoxylin-eosin (H&E) and Masson’s trichrome (MT) after decalcification with 10% EDTA solution. We assessed the following factors; neovascularization, inflammation, calcification/cholesterol deposition, and valvular fibrosis. We also measured the whole layer thickness of the valve and the thickness of fibrotic lesion (measured on the aortic side and ventricular side) at the mid-portion of the leaflet.Immunohistochemical examinations were performed on 4-5-μm-thick 10% buffered formalin-fixed and paraffin-embedded tissue sections, using monoclonal antibodies to confirm inflammation, neovascularization, calcification, and extracellular matrix deposit besides H&E and MT stainings. All steps were performed using an auto-immunostainer, Bond-III , according to the manufacturer’s instructions. All slides were incubated with primary monoclonal antibodies against CD3 for T cells  for 15 minutes. Representative samples were additionally incubated with primary antibodies against von Willebrand factor  for endothelial cells (neovascularization), osteopontin  for calcium deposits, and tenascin-C , as the extracellular matrix which was reportedly associated with progression of AS , followeImmunohistochemical and histopathological features were classified using semi-quantitative methods  by experienced pathologists without knowledge of the patients’ clinical data. In terms of the semi-quantitative scoring of immunohistochemical staining, positive cells (for T cells)/area were classified as follows; grade 0 was no positive cells/area, grade 1 was <25% cells positive/area, grade 2 was 25–50% cells positive/area, and grade 3 was > 50% cells positive/area . The scoCalcification was also graded on a scale of 0 to 3, as previously described. Briefly, grade 0 valves showed no calcification, grade 1 valves showed early calcific nodules, grade 2 valves showed several calcific nodules with mild structural distortion, and grade 3 valves showed many several calcific nodules with severe structural distortion , 15. ValContinuous variables are expressed as mean ± standard deviation. Categorical variables are presented as numbers and percentages. Categorical variables were compared using the chi-squared test when appropriate; otherwise, Fisher’s exact test was used. Continuous variables were compared among the three groups using one-way analysis of variance. Histopathological scores were analyzed using the Wilcoxon rank sum test. Bonferroni correction was used to adjust for multiple comparison. Comparisons within groups were performed using paired t-test. Multivariate linear regression modeling was used to adjust for suspected confounders. Relevant covariates were selected for inclusion in multivariate models based on prior clinical knowledge. JMP version 10  was used to perform all analyses. Two-sided p values less than 0.05 were considered statistically significant.A total of 24 patients with TAV-AS, 24 patients with CBAV-AS, and 24 patients with CBAV-AR were included in this study. Clinical characteristics, co-morbid conditions, echocardiographic parameters, and laboratory data in the three groups are shown in Representative macroscopic images are shown in Valvular fibrosis was different among the three groups. Patients with CBAV-AS had more marked valvular fibrosis than those with CBAV-AR (p < 0.01). In AS patients, valvular fibrosis was more severe in patients with CBAV-AS compared with those with TAV-AS (p < 0.01, Bicuspid morphology was independently associated with valvular fibrosis even after adjustment for confounders such as age, sex, hypertension, diabetes mellitus, dyslipidemia, and smoking history in multivariate linear regression analysis in AS patients (p < 0.01, Valvular thickness of whole zone and thickness of fibrotic lesions measured on the aortic side and ventricular side are shown in The major findings of this study were as follows: First, the severity of inflammation and neovascularization was comparable between patients with CBAV-AS and those with TAV-AS, and was less in patients with CBAV-AR. Second, fibrosis was more prominent in patients with CBAV-AS than in those with TAV-AS and those with CBAV-AR. Third, the valvular fibrosis was greater on the aortic side than on the ventricular side in AS patients, and it was greater in patients with CBAV-AS than in those with CBAV-AR and TAV-AS. These findings suggest that an inappropriate fibrotic response to chronic inflammation and neovascularization, especially on the aortic side, may contribute to the development of AS in CBAV.Previous reports suggested that CBAV-AS was associated with increased inflammation and neovascularization compared with TAV-AS , 17, 18.In our study, valvular fibrosis and thickness of fibrotic lesions were greater in patients with CBAV-AS than in those with TAV-AS, despite no differences in other pathologic parameters. Bicuspid morphology was an independent predictor of valvular fibrosis in patients with AS. In addition, valvular fibrosis was more marked in patients with CBAV-AS than in patients with CBAV-AR. The pathological features of CBAV-AR might reflect the initial lesions prior to the development of CBAV-AS, since CBAV-AR usually occurs in younger patients. Our study suggested that the increased fibrosis in CBAV-AS might be an acquired response.There are possible explanations for the association between valvular fibrosis and CBAV-AS. First, perturbation of blood flow in CBAV causes valvular thickening and fibrosis. Although the mechanisms by which mechanical forces invoke cellular and molecular responses within the aortic valve are not well understood, cardiovascular tissue generally responds to increased radial stress by increasing in thickness to buffer or neutralize mechanical stress . Second,In terms of the thickness of fibrosis, both patients with CBAV-AS and TAV-AS had thicker fibrosis on the aortic side than on the ventricular side. Calcification of the aortic valve usually begins on the aortic side of valve cusps, with relative sparing of the ventricular side. The aortic side of valve cusps is exposed to high mechanical stress of downstream flow during the diastolic phase. In addition, expression of inhibitors of osteogenic signaling is significantly reduced in endothelium from the aortic side of valve cusps , 26, leaIn the present study, tenascin-C was markedly expressed in the aortic valve of patients with CBAV-AS. Recent reports have suggested that tenascin-C is expressed in association with the development of cardiovascular diseases, and it may accelerate or sustain fibrosis in cardiovascular tissues –30. The Our study had several limitations. First, the number of samples in the present study was too small to possess sufficient statistical power. Second, the degree of the histological findings was only classified using semi-quantitative methods. Third, in this study, we examined specimens with advanced stage requiring aortic valve surgery for severe stenosis and/or regurgitation. We did not investigate normal aortic valves as controls, and we did not obtain specimens of valves with an earlier stage of stenosis and/or regurgitation. Moreover, less valve degeneration occurs in the settings of aortic root dilatation or prolapse of the cusps, which are the main causes of aortic regurgitation . TherefoInflammation, neovascularization, cholesterol deposition, and calcium deposition were more prominent in patients with CBAV-AS than in those with CBAV-AR, but not significantly different between patients with CBAV-AS and those with TAV-AS. Meanwhile, fibrosis of the aortic valve, especially on the aortic side, was significantly more severe in patients with CBAV-AS than in those without, suggesting a difference in the pathogenesis of AS between CBAV and TAV.


A 26-year-old female presented to the emergency department with three days of subjective fevers, dry cough and pleuritic chest discomfort. On exam, her vital signs were significant for a heart rate of 106/minute and oxygen saturation of 95% on room air. Her lung exam revealed decreased breath sounds at the right base. A bedside lung ultrasound and a chest radiograph were performed .Community acquired pneumonia (CAP) is a common disease in the United States and represents the seventh leading cause of death.1While chest computed tomography (CT) is the gold standard diagnostic tool for CAP, its use is limited by both cost and radiation exposure.4On LUS, pneumonia has similar echogenicity to the liver with hyper-echoic foci, representing air bronchograms . ConsoliWhile it is underutilized, point-of-care LUS is a rapid, accessible, safe, and low-cost imaging tool for the diagnosis of pneumonia.


This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at  This is part of the PLOS Computational Biology Education collection.Gene expression is a widely studied process and a major area of focus for functional genomics . Gene exThe RNA-seq method typically consists of identification of suitable biological samples (and replicates), isolation of total RNA, enrichment of nonribosomal RNAs, conversion of RNA to cDNA, construction of a fragment library, sequencing on a high-throughput sequencing platform, generation of single or paired-end reads of 30–300 base pairs in length, alignment or assembly of these reads, and downstream analysis  5,6]. T,6. T5,6]www.rnaseq.wiki, and the videos of these lectures made available at http://bioinformatics.ca/workshops/. Finally, we make available open-access tutorials that cover cloud computing for RNA-seq analysis, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality control, and complete pipelines for expression, differential expression, and alternative splicing analysis . The tutorials represent an example RNA-seq workflow based on the “tuxedo” suite [www.rnaseq.wiki).In this educational piece, we explore molecular biology concepts of RNA-seq that influence RNA-seq analysis workflows and data interpretation. We also provide a detailed introduction to fundamental RNA-seq informatics concepts and common analysis questions. These concepts are covered here, in the Supplementary Materials and lectures made available at o” suite  and othewww.rnaseq.wiki). Since most RNA-seq experiments involve comparisons between and across conditions, it is desirable that these factors be consistent across all samples and replicates within an experiment. In addition to classic sources of batch effects , each of these design parameters can introduce systematic biases. Since there is currently a large amount of diversity across published datasets with respect to these and other factors, meta-analyses that combine publicly available data should be pursued with caution. It is likely that RNA-seq will become increasingly standardized with respect to experimental design, data generation, and analysis strategy. Several efforts aimed at establishing best practices are underway . For these tutorials and the following analysis discussions, we selected the “tuxedo” suite and other commonly used tools to illustrate an example RNA-seq analysis workflow. These specific tools were selected because of their widespread use. In our opinion, they are some of the better-engineered options and have acceptable levels of documentation. However, for each analysis application . This approach has several advantages for both RNA-seq users and instructors. It ensures a consistent computing environment across all students, and the elasticity of cloud computing allows the same tutorials to be run by small or large groups, even allowing for the possibility of a massive open online course (MOOC). We are able to store machine instances that represent multiple states during the tutorial exercises, including the starting point , an intermediate state with all necessary tools installed, and finally an instance with all analyses complete. These represent useful reference points for comparison to the student’s own work. By performing all tutorials on the cloud, the students learn the basics of cloud computing as they learn about RNA-seq. Using the cloud for instruction also allows the student to easily establish an RNA-seq pipeline in his or her own lab that is based directly on the tutorials, operates in the same environment, and does not require purchasing or administering the substantial hardware that may be needed for RNA-seq data analysis. We provide an extensive introduction to cloud-computing concepts and specific cloud administration skills in the Supplementary Tutorials online . Once read trimming is complete, the next step in most RNA-seq applications is alignment [In order to understand RNA-seq raw data and alignments, one must develop an understanding of the file formats and underlying data models they represent. These include the FASTA format for storing reference genome data , the genlignment  or assemlignment ,61. RNA-lignment , Savant lignment , and intlignment  are capalignment  of IGV aOne of the most widely used applications of RNA-seq is the estimation of gene or transcript abundance and comparison of these abundances across biological conditions . Gene abhttp://biorxiv.org/content/early/2014/07/14/007088).While the raw read count methods are well developed and have been validated as a robust alternative to expression microarrays and gold standard assays such as qPCR , they hawww.rnaseq.wiki), we explore the use of both count based and “FPKM style” expression estimation and associated differential expression tools.In order to estimate transcript abundance, Cufflinks first builds transcript isoforms by identifying overlapping “bundles” of fragment alignments. These are assembled, fragments are connected in an overlap graph, and transcript isoforms are inferred from the minimum paths required to cover the graph. Following use of Cufflinks to estimate transcript structures and abundance in each sample, Cuffmerge is used to merge several Cufflinks assemblies together . This ishttp://www.R-project.org) and Bioconductor [Interpretation, summarization, and visualization of expression and differential expression results can be just as involved as generating these results . CummeRbonductor . While wonductor ,72 as a onductor , GAGE , an online question-and-answer forum for bioinformatics [Certain questions consistently arise among researchers performing RNA-seq analysis. To avoid repetition of effort, we advocate for these questions to be asked and answered within “BioStars” (ormatics  in whichwww.rnaseq.wiki) using example data sets (CBW), Cold Spring Harbor Laboratories (CSHL), and future collaborating partners. We recognize that the current example workflow relies heavily on the existence of a reference genome sequence. We hope in the future to add example workflows that use reference-free or alignment-free methods of RNA quantification Click here for additional data file.S2 Data(PDF)Click here for additional data file.S1 TableThere are several downstream analysis goals for which RNA-seq is well suited. The main categories of these are described briefly below with reference to supporting materials. Refer to (PDF)Click here for additional data file.S2 Tablewww.rnaseq.wiki) are referenced below (tool name in bold) along with alternative tools in each category. Whenever possible, a citation is provided. Links are also provided to help the user evaluate the code and the level of maintenance. Whenever possible, the link goes directly to a source controlled repository such as a git repo. Additional lists of tools can be found here: Alamancos et al. (arXiv), the rna-seqblog, and RNA-seq—Protocols and Algorithms. This table is meant to be comprehensive but not exhaustive. Some RNA-seq analysis topics that are not explicitly covered here include co-regulation (co-expression), disease classification, time series, expression compendium databases, outlier expression, data normalization, and miRNA analysis.All tools used in the online tutorial ((PDF)Click here for additional data file.S3 TableSequencing Quality Control (SEQC) consortium, the Encyclopedia of DNA Elements (ENCODE) consortium, the Roadmap Epigenomics Mapping Consortium (REMC), and the Beta Cell Biology Consortium (BCBC).The following table summarizes several key concepts relating to sample preparation and library construction that may influence analysis and interpretation of RNA-seq data. Several initiatives are underway to develop standards and best practices that cover many of these concepts. These include the (PDF)Click here for additional data file.S4 TableA description of three RNA enrichment strategies is provided, along with their anticipated effects on RNA-seq library construction and data interpretation. For a visual depiction of the concepts discussed here, refer to (PDF)Click here for additional data file.S5 TableIGV’s read orientation codes for RNA-seq data viewed in the browser. Also provided are recommended software settings for three additional tools involved in common RNA-seq analysis workflows: TopHat, HTSeq, and Picard. Each of these explanations/settings is provided for several commonly used RNA-seq library construction kits that produce either stranded or unstranded data.This table provides further explanation of (PDF)Click here for additional data file.S6 Tablewww.rnaseq.wiki).The following table describes several file formats used in most RNA-seq analysis workflows as well as several files specific to the expression analysis tools used by the online tutorials that accompany this article (at (PDF)Click here for additional data file.S7 TableThe following table summarizes a list of commonly asked questions relating to RNA-seq analysis, with links to BioStar posts in which these questions have been addressed by the community.(PDF)Click here for additional data file.S8 Tableresources section of the online tutorial at www.rnaseq.wiki.The following table provides a list of general resources to help understand the background of RNA biology, next-generation sequencing, RNA-seq laboratory methods, and RNA-seq analysis. Additional educational resources can be found in the (PDF)Click here for additional data file.S9 Tablehttps://www.biostars.org/p/79845/ and https://www.biostars.org/p/11034/.The following table lists RNA-seq workshops and other tutorials complementary to this article. These examples are limited to online materials or short workshops. Not listed here are formal training programs or degrees in bioinformatics. For ongoing discussion of this topic, refer to these BioStar posts: (PDF)Click here for additional data file.S1 Text(PDF)Click here for additional data file.


To describe the prevalence, characteristics, and predictors of safety-net use for primary care among non-Medicaid insured adults .Cross-sectional analysis using the 2006–2010 National Ambulatory Medical Care Surveys, annual probability samples of outpatient visits in the U.S. We estimated national prevalence of safety-net visits using weighted percentages to account for the complex survey design. We conducted bivariate and multivariate logistic regression analyses to examine characteristics associated with safety-net clinic use.More than one-third (35.0%) of all primary care safety-net clinic visits were among adults with non-Medicaid primary insurance, representing 6,642,000 annual visits nationally. The strongest predictors of safety-net use among non-Medicaid insured adults were: being from a high-poverty neighborhood , being dually eligible for Medicare and Medicaid , and being black  or Hispanic . Compared to non-safety-net users, non-Medicaid insured adults who used safety-net clinics had a higher prevalence of diabetes , hypertension , multimorbidity  and polypharmacy . Nearly one-third (28.9%) of Medicare beneficiaries in the safety-net were dual eligibles, compared to only 6.8% of Medicare beneficiaries in non-safety-net clinics (p<0.001).Safety net clinics are important primary care delivery sites for non-Medicaid insured minority and low-income populations with a high burden of chronic illness. The critical role of safety-net clinics in care delivery is likely to persist despite expanded insurance coverage under the Affordable Care Act. The U.S. health care ‘safety-net’ is a fragmented and heterogeneous network of public hospitals, clinics, community health centers (CHCs), and other healthcare organizations defined only by their shared mission–to provide care to individuals regardless of ability to pay. The safeHowever, given the unique challenges of caring for vulnerable populations, safety-net providers are thought to have a comparative advantage in addressing unmet social needs related to language, culture, employment, and transportation, compared to non-safety-net providers.,3,4 FurtTo address this gap in the literature, we used nationally representative data from the National Ambulatory Medical Care Surveys (NAMCS), which have more systematically included information on the use of safety-net clinics since 2006. Our objective was to assess the national prevalence and characteristics of insured individuals using safety-net settings for primary care. We hypothesized that contrary to popular belief, a substantial number of visits to safety-net clinics are by patients with non-Medicaid insurance, and that higher-need insured individuals, with a greater burden of illness and clinical complexity, are more likely to receive regular care in the safety-net. Greater understanding of the role of the safety-net in caring for non-Medicaid insured individuals is critical to informing the national debate on the appropriate role for and financing of safety-nets in the era of insurance expansion and delivery system reform.We analyzed NAMCS from 2006 to 2010. NAMCS is an annual, nationally representative cross-sectional survey of ambulatory office visits administered by the National Center for Health Statistics (NCHS). NAMCS uses a multi-stage probability sampling design to represent all visits to non-federally employed office-based physicians in the United States engaged in direct patient care. Trained We included all primary care visits by individuals 18 years or older with private insurance or Medicare as the expected primary payer, since individuals with these forms of insurance have the greatest choice in where they receive their care. We excluThe primary outcome was whether a primary care visit occurred in a safety-net clinic. We broadly defined ‘safety-net clinic’ as a community health center (CHC) or a non-federal government-run clinic given that these both are ‘core safety-net providers’ as defined by the Institute of Medicine. Because safety-net clinics are defined by mission rather than a regulatory definition, many are not necessarily designated CHCs, though the majority are operated by non-federal public agencies, such as city and county governments. CHCs werIn addition to primary payer, we defined secondary payers as any additional listed potential payers according to the same hierarchy. We defined ‘dual eligibles’ as individuals with Medicare and Medicaid as primary and secondary payers respectively.Race/ethnicity were defined based on imputed fields in NAMCS, since these data were missing for 22–35% of records per year from 2006–2010 (an approach used in previously published studies). Zip codeThe presence of up to 14 different chronic medical conditions was recorded, independent of visit diagnoses. Up to eiAll analyses accounted for the complex survey design and used visit, strata, and primary sampling unit design weights provided by NAMCS to reflect national estimates. We conducted all analyses using Stata 12.0 . We estimated prevalence of primary care visits in the safety-net using weighted percentages and estimated absolute number of visits per year. We used linear regression with visit year as an ordinal predictor to test for linear trends in safety-net use during the study period. We conducted bivariate and multivariate logistic regression analyses to examine characteristics associated with safety-net use. Due to differences in age distribution among individuals with private insurance versus Medicare, we examined bivariate associations between age and safety-net use separately in these subgroups. Because accounting for the interaction between age and payer did not meaningfully change our findings, we opted to omit this interaction term in our multivariate model for ease of interpretation. The final multivariate model included all sociodemographic characteristics including age, sex, race/ethnicity, dual eligible status, rural area status, geographic region, prevalence of poverty in zip code, prevalence of bachelor’s degree in zip code; clinical characteristics including polypharmacy, multimorbidity, frequent visits (≥5 in the past 12 months); and chronic conditions with p-values ≤0.05 from bivariate analyses. Due to potential co-linearity between polypharmacy, frequency of visits, multimorbidity, and significant chronic conditions, we performed sensitivity analyses assessing each variable independently in the multivariate model and found no meaningful difference in our findings (data not shown).Model fit was assessed using an extension of the Hosmer-Lemeshow goodness-of-fit test for survey weighted data . Given thThis study was deemed exempt from review by the UT Southwestern Medical Center institutional review board.From 2006 to 2010, NAMCS included a total of 53,833 visits by adults to primary care clinics. Of these, 37,155 visits were by individuals with either Medicare or private  insurance . Among iThe 4,156 safety-net clinic visits among non-Medicaid insured adults represent an estimated 35.0% of all safety-net clinic visits for primary care , or 6,642,000 visits annually. Medicare beneficiaries and privately insured individuals accounted for 19.8% and 15.2% of safety-net visits respectively. We did not observe any temporal trend in safety-net clinic use among non-Medicaid insured individuals from 2006 to 2010 .Non-Medicaid insured individuals using the safety-net for primary care were more likely to be black  or Hispanic ; dual eligible (16.3% vs. 2.0%) and be from areas with high rates of poverty and limited education compared to their non-safety-net counterparts . Safety With regard to visit characteristics, 92.3% of all non-Medicaid insured safety-net users were seen before in the practice, confirming that these clinics were regular sources of care. Non-Medicaid insured safety-net users were more likely to have had five or more visits in the past twelve months  and be seen for a chronic problem  compared to non-safety-net users. With respect to clinical characteristics, insured safety-net users had higher prevalence of polypharmacy , multimorbidity , diabetes , hypertension  and chronic obstructive pulmonary disease .Our adjusted analysis confirmed that minority race/ethnicity and residing in a high-poverty neighborhood were among the strongest predictors of safety-net use among insured individuals . Age lesWe found significant regional variation in safety-net use among insured individuals. Specifically, being from the Northeast was associated with nearly a six-fold greater odds of safety-net use  and being from the West as associated with four-fold greater odds of safety-net use  compared to being from the Midwest.We also found that certain clinical characteristics were robust predictors of safety-net use. Having five or more visits in the prior year , and the presence of polypharmacy  or hypertension  were independently associated with safety-net use. However, after adjustment, multimorbidity, diabetes, and chronic obstructive pulmonary disease were no longer significant predictors.Nearly one-third (28.9%) of Medicare beneficiaries in the safety-net were dual eligibles, compared to only 6.8% of beneficiaries not in the safety-net (p<0.001). As a whole, dual eligibles were significantly older than non-dual eligibles . Other characteristics among dual eligibles in the safety-net were otherwise similar to those observed for the overall population of insured safety-net users . PredictTo our knowledge, this is the first comprehensive national study of safety-net use among non-Medicaid insured adults. We found that over one-third of primary care visits in safety-net settings occurred among adults with non-Medicaid insurance. This was surprising, given that safety-net clinic visits only account for 2% of all primary care visits in this population. Despite being younger than their non-safety-net counterparts, safety-net users tended to have higher rates of chronic disease and polypharmacy. The strongest predictors of safety-net use among adults with non-Medicaid insurance were being from high-poverty neighborhoods, being from the Northeast or West, being black or Hispanic, being a dual eligible, being younger than age 65, having frequent visits in the prior year, and having polypharmacy or hypertension. Nearly one-third of Medicare beneficiaries who were safety-net users were dual eligibles . Dual eligibles have the same potential access to primary care providers but have more complex care needs and higher health utilization than other Medicare beneficiaries.Our findings underscore the important but underrecognized role of safety-net clinics as primary care homes for insured individuals with private insurance or Medicare, who account for a disproportionate share of safety-net utilization. Though they account for 35% of safety-net visits overall  they comprise only 25% of total patients and 15% of total national annual revenue in CHCs, the only outpatient safety-net setting for which national data exists.,32,33 AlSupporting the hypothesis that non-Medicaid insured individuals in the safety-net have a greater burden of illness and clinical complexity compared to non-safety-net counterparts, we found that polypharmacy, hypertension, and frequent visits in the prior year were strong predictors of safety-net use. Though we were unable to directly assess the severity of individual chronic conditions using NAMCS data, we considered polypharmacy and frequency of visits as reasonable proxies given their associations with illness severity.,37 We suOur findings confirm that minority and low-income insured individuals with private insurance or Medicare are more likely to use safety-net providers, though it is unclear whether the reason for greater safety-net use is a matter of proximity, access, preference, affordability, loyalty, cultural concordance, or other considerations. Safety net providers are often located by design in ‘medically underserved’ areas; consequently, use of safety-net providers among insured minority and low-income individuals may in part reflect proximity and/or lack of easy access to alternate sites for primary care.,46 HowevAffordability may also be an important consideration for seeking care in the safety-net. Nearly 1 in 8 privately insured adults under 65 years old spend a high share of annual income on health expenses. FinanciaOur study has important implications for understanding the effect of expanded insurance coverage on the safety-net in a post-ACA environment. Expanded insurance coverage that nonetheless remains unaffordable due to high out-of-pocket costs may result in self-selected clustering of needier and sicker insured individuals in more affordable safety-net clinics. Many of the newly covered are likely to have previously gone without care while uninsured, and have higher health care use after receiving insurance coverage.,54 This Our results should be interpreted in light of several limitations. First, our definition of ‘safety-net clinics’ included only officially designated FQHCs/CHCs and non-federal government clinics and excluded many other de facto safety-net settings not captured in NAMCS including emergency and hospital outpatient departments.,45,58–60Non-Medicaid insured adults account for over one-third of primary care visits to safety-net clinics. Given the higher burden of illness and clinical complexity among non-Medicaid insured safety-net users, additional attention to national policy, financing, and support for the safety-net is needed to optimize its function as a medical home for many low-income and minority insured Americans.S1 Table(DOCX)Click here for additional data file.


Over the last 100 years, several persistent misconceptions or ‘false beliefs’ have built up around allergen immunotherapy and its use in allergic rhinitis. This is perhaps because enthusiastic physicians administered complex allergen extracts to a diverse population of patients suffering from heterogeneous atopic conditions. Here, we review evidence that counters seven of these ‘false beliefs.’1. The symptoms of allergic rhinitis can be more heterogeneous, more severe and more troublesome in everyday life than many physicians believe. Large-scale epidemiological surveys show that the majority of allergic rhinitis patients have at least one symptom severe enough to interfere with sleep quality, productivity and/or well-being. 2. Allergen immunotherapy is not necessarily suitable for all allergic rhinitis patients (notably those with mild symptoms). Recent evidence from double-blind, placebo-controlled, randomized clinical trials suggests that the more severe the disease, the greater the treatment effect. 3. Allergen immunotherapy is often accused of lack of efficacy . However, there are now many meta-analyses, systematic reviews and high-quality clinical trials that find overwhelmingly in favor of the efficacy of allergen immunotherapy  in allergic rhinitis induced by pollen and, increasingly, other allergens. 4. Natural-exposure and challenge-chamber trials have shown that symptom relief may become apparent within months or even weeks of the initiation of allergen immunotherapy. 5. In pollen-induced allergic rhinitis, several years of subcutaneous or sublingual allergen immunotherapy are associated with sustained clinical efficacy after subsequent treatment cessation – confirming the disease-modifying nature of this therapy. 6. Most patients seeking treatment for allergic rhinitis are polysensitized, and allergen immunotherapy has proven efficacy in large, robust clinical trials in these groups. Polysensitization is not a contraindication to allergen immunotherapy. 7. Sublingual allergen immunotherapy is safe for home administration. A recent review calculated that 1 billion doses were administered worldwide between 2000 and 2010 and found that the 11 case reports of anaphylaxis  corresponded to non-standard practice.Modern, evidence-based medicine has generated more than enough robust evidence to remove misconceptions about allergen immunotherapy and allergic rhinitis. The Lancet - the first scientific descriptions of clinically effective allergen immunotherapy (AIT) for grass-pollen-induced allergic rhinoconjunctivitis [In 2011, a flurry of events and publications marked the centenary of Leonard Noon and John Freeman's ground-breaking papers in ctivitis . Unsurprctivitis . HistoriIn fact, AR is under-diagnosed and undertreated, and its symptoms are more troublesome than many physicians (and indeed some patients) believe. In a Europe-wide survey, two-thirds of AR patients reported at least one symptom that is severe enough to interfere with sleep quality, cognitive function, work productivity, school performance, psychosocial well-being or overall quality of life . Poor slpost-hoc analysis of large subgroups of AR patients receiving grass pollen sublingual allergen immunotherapy (SLIT) [et al. [International guidelines and consensus statements (such as those issued by the Allergic Rhinitis and its Impact on Asthma group)  make it y (SLIT)  found th [et al.  came to With so many meta-analyses  found that none corresponded to standard practice in SLIT ; in factThere is sound epidemiological evidence to show that the activity of allergic respiratory diseases changes with age and that children develop and/or display atopy within the first years or even months of life . In geneth century. As a result, allergen immunotherapy for AR has long suffered from the persistence of ‘false beliefs’ driven by poor methodology. Despite being a guidelines-recommended treatment, AIT is often not considered by the physician. However, there is now more than enough evidence from recent robust DBPC RCTs, meta-analyses and large-scale epidemiological surveys to allay misconceptions about AIT – the only disease-modifying treatment for respiratory allergies. In appropriately screened patients, modern AIT is undoubtedly safe and effective in the treatment of AR induced by common aeroallergens.Allergic rhinitis is a heterogeneous, under-diagnosed, undertreated, chronic, allergic respiratory condition. If physicians disregard the severity of symptoms, AR sufferers will remain exposed to co-morbidities and poor quality of life. Leonard Noon and John Freeman's ground-breaking papers in 1911 prompted enthusiastic but empirical and sometimes unethical clinical practice and research in the field of allergen immunotherapy in the first half of the 20AIT: Allergen immunotherapy; AR: Allergic rhinitis; DBPC RCT: Double-blind, placebo-controlled, randomized clinical trial; SCIT: Subcutaneous allergen immunotherapy; SLIT: Sublingual allergen immunotherapy.Moisés A. Calderón has received consulting fees, honoraria for lectures and/or research funding from ALK, Stallergenes, Merck, Allergopharma, HAL and Allergy Therapeutics. A. William Frankland has received travel grants from Stallergenes. Pascal Demoly is a consultant for Stallergenes, ALK, Circassia and Chiesi and an investigator for Stallergenes, ALK, Pierre Fabre Médicament, Ménarini and was a speaker for Stallergenes, ALK, Ménarini, Allergopharma, MSD, AstraZeneca and GlaxoSmithKline in 2010–2013.All authors were involved in drafting the manuscript. The authors accept full responsibility for the work and the decision to publish. All authors read and approved the final manuscript.st birthday and still practices at the London Allergy Clinic (in collaboration with another physician). His long scientific and medical career puts him in a unique position to evaluate passing fads and hard facts. Dr. Moises A. Calderon and Dr. Pascal Demoly are active younger members of the European Association of Allergy and Clinical Immunology (EAACI) and have a particular focus on assessing the quality of research evidence in the treatment of respiratory allergies.This article is the fruit of recent discussions at Dr. A. William (‘Bill’) Frankland's London home. Bill Frankland has been described as the ‘grandfather of allergy’ in the UK, starting in 1946 in the Allergy Department at Saint Mary's, where he notably pioneered the use of the controlled, randomized clinical trial in this area. Bill recently celebrated his 101The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1741-7015/11/255/prepub