Z-score, leptin, insulin, and HOMA-IR. Acyl-ghrelin had a significant negative correlation with MDA as an index of oxidative stress. Conclusion: Ghrelin is decreased and obestatin is elevated in obesity. Both of these hormones are associated with insulin resistance, and ghrelin is associated with oxidative stress. The balance between ghrelin and obestatin seems to be disturbed in obesity.Background: Ghrelin is a 28-amino acid peptide with an orexigenic property, which is predominantly produced by the stomach. Acylated ghrelin is the active form of this hormone. Obestatin is a 23-amino acid peptide which is produced by post-translational modification of a protein precursor that also produces ghrelin. Obestatin has the opposite effect of ghrelin on food intake. The aim of this study was to evaluate acylated ghrelin and obestatin levels and their ratio in obese and normal-weight children and adolescents, and their association with metabolic syndrome (MetS) parameters. Methods: Serum acyl-ghrelin, obestatin, leptin, insulin, fasting plasma glucose (FPG), lipid profile, and malondialdehyde (MDA) were evaluated in 73 children and adolescents (42 obese and 31 control). Insulin resistance was calculated by a homeostasis model assessment of insulin resistance (HOMA-IR). MetS was determined according to IDF criteria. Results: Acyl-ghrelin levels were significantly lower in obese subjects compared to the control group and lower in obese children with MetS compared to obese subjects without MetS. Obestatin was significantly higher in obese subjects compared to that of the control, but it did not differ significantly among those with or without MetS. Acyl-ghrelin to obestatin ratio was significantly lower in obese subjects compared to that in normal subjects. Acyl-ghrelin showed significant negative and obestatin showed significant positive correlations with body mass index (BMI), BMI  The prevalence of obesity in children is increasing worldwide. The American Obesity Association estimates that 30% of children between the ages of 6 and 19 are overweight, and 15% meet the criteria for obesity . InsulinO-acyltransferase system has recently been found to play a crucial role in both the development of steatosis and its progression to nonalcoholic steatohepatitis [Investigations have focused on two gastric hormones, ghrelin and obestatin, and their role in the regulation of food intake in the children with obesity. Ghrelin and obestatin exert a marked effect on the motivation to eat and food intake, and are modulated during puberty by habitual physical activity levels. Ghrelin is a 28-amino acid peptide predominantly produced by the stomach and expressed in many other central and peripheral tissues . In addiepatitis . Obesityepatitis .Ghrelin circulates in two forms, simply differing in the acylation, the most abundant of which is non-acylated ghrelin, while the acylated form is considered to be the active hormone . It has Several in vitro and in vivo studies have shown that ghrelin may regulate insulin and glucose metabolism . StudiesObestatin, a 23-amino acid peptide, is produced by the post-translational modification of a protein precursor that also produces ghrelin and is mainly found in the stomach. Studies in animal models have shown that the effect of obestatin on food intake is opposite to ghrelin, and obestatin has been suggested to provide a new target for the control of obesity ,16. BothBased on the previous studies and the influence of these hormones on appetite and insulin secretion, we hypothesized that children with obesity and MetS, compared with age-matched controls, would have impairment in acyl-ghrelin and obestatin levels, as well as in acyl-ghrelin-to-obestatin ratios. According to the antioxidant property of ghrelin, its association with oxidative stress was also investigated. Lipid peroxidation, which follows oxidative stress, generates a variety of relatively stable end products, including malondialdehyde (MDA) which is increased in various disease states  and has Seventy-three children and adolescents, aged 7–16 years, were included in this study. Obesity was defined as a body mass index (BMI) above the 95th percentile for age and sex. With this definition, 42 subjects were considered obese. Thirty-one age- and sex-matched lean subjects with BMIs between the 5th and 84th percentiles were also included as the control group. The sample size was calculated on the basis of the results of a previous study , with 80A thorough history and physical examination was obtained for all the subjects. Apart from obesity, no other clinical or laboratory signs of systemic illness or endocrine perturbation, including diabetes mellitus and hypothyroidism, were observed in obese subjects. Control subjects were selected from those referred to outpatient clinics for check-up and growth evaluations and found to be completely healthy. None of the subjects were receiving medications or supplements other than conventional multivitamins. They had normal physical activity and were not on any special diets. Taking into account the above considerations, case and control subjects were carefully selected and matched.2, and BMI z-score was determined for all subjects. Blood pressure (BP) was measured by mercury sphygmomanometer. Waist circumference (WC) was measured at the end of a normal expiration, with the measuring tape positioned at the level of noticeable waist narrowing or at the level of the lower floating rib, while the subjects were in a standing position. WC percentiles were determined according to age and gender of each subject [Anthropometric measurements were performed in the morning after an overnight fast. Weight was determined using a digital electronic weighing scale, with subjects being bare-footed and wearing light clothes. Height was determined in the upright position using a digital stadiometer. Body mass index (BMI) was calculated as kg/m subject . Puberta subject .Written informed consent was obtained from subjects or their parents or both, and the study was approved by the ethics committee of Tehran University of Medical Sciences.Homeostatic model assessment of insulin resistance (HOMA-IR) was used as an index of insulin resistance (IR). It was calculated by the formula: serum insulin (µIU/mL) × FPG (mg/dL)/405 . Those wThe IDF consensus definition of MetS in children and adolescents was used for the diagnosis of MetS . AccordiVenous blood samples were collected in the morning after an overnight fast (12 h). Serum and plasma samples were separated and stored at −80 °C until analysis. Fasting plasma glucose (FPG), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured by colorimetric methods using commercial kits .Serum MDA levels were measured by a colorimetric method using trichloroacetic acid and thiobarbituric acid . The absPlasma concentrations of insulin were determined by an enzyme-linked immunosorbent assay (ELISA) using a commercial assay kit . Plasma leptin levels were also determined by an ELISA kit . Acyl-ghrelin assessment was carried out in plasma using an enzyme immunometric assay (EIA)  by a double-antibody sandwich technique. Plasma obestatin was also measured by an EIA kit .U test (non-parametric) and independent-samples t-test (parametric). The statistical differences were considered significant if the p-value was lower than 0.05. Correlations between variables were evaluated using Pearson’s and Spearman’s correlation tests for parametric and non-parametric variables, respectively. To control for confounding factors, partial correlation was used. All the statistical analyses were performed using SPSS software version 16.0 .Normal distribution of data was evaluated by a Kolmogorov–Smirnov test. Data are presented either as the mean ± standard deviation (SD) or the median (interquartile range). The differences between the patients and the control group were analyzed using the Mann–Whitney z-scores, and WCs compared to normal-weight children and adolescents. Sixty-two percent of obese subjects had WCs above the 95th percentile. Systolic BP was significantly higher in obese subjects than that in normal subjects.The anthropometric and biochemical characteristics of the studied subjects are shown in FPG, TG, TC and HDL-C were not significantly different among the studied subjects; nevertheless, obese children and adolescents had significantly higher levels of LDL-C. Compared to control subjects, leptin levels in obese subjects were also significantly higher.Plasma Ac-ghrelin levels were significantly lower than those of normal-weight children. On the other hand, obestatin concentrations were significantly higher than those of normal-weight children. There were no gender-specific differences in the assessed variables. Furthermore, no differences between the pre-pubertal and pubertal stages were observed.n = 22) of obese subjects had insulin resistance (IR). None of the control subjects were insulin-resistant. Both Ac-ghrelin and obestatin levels were significantly different in subjects with or without insulin resistance. Ac-ghrelin levels were lower in subjects with IR compared to those without IR (59 (18–75) pg/mL vs. 74 (53–149) pg/mL, respectively) (p < 0.01), and obestatin levels were significantly higher in subjects with IR compared to those without IR (246 (155–437) pg/mL vs. 199 (134–275) pg/mL, respectively) (p < 0.05).Compared to control subjects, obese subjects had significantly higher insulin levels and HOMA-IR. Based on HOMA-IR, 61% (p < 0.01). Obestatin levels were not significantly different with regard to MetS.Normal subjects did not have the features of MetS. On the contrary, MetS was diagnosed in 33% of obese children and adolescents. Both Ac-ghrelin and obestatin levels were analyzed in obese subjects with or without MetS; among them, Ac-ghrelin levels were found to be significantly lower in obese children with MetS compared to obese children without MetS (22.65 (14.9–64) pg/mL vs. 60.0 (22.04–70.0) pg/mL, respectively) (z-score, TG, LDL-C, HDL-C, insulin, HOMA-IR, and leptin. On the other hand, Ac-ghrelin showed significant negative correlations with BMI, BMI z-score, LDL-C, insulin, HOMA-IR, and leptin, as well as MDA. Nevertheless, a partial correlation analysis with BMI or BMI z-score as the confounding factor did not give any significant correlation between studied parameters.The correlations between Ac-ghrelin, obestatin, and other variables are summarized in MDA, which is considered an index of lipid peroxidation and oxidative stress, was significantly higher in obese children and adolescents compared to normal-weight subjects.Ac-ghrelin-to-obestatin ratios were also calculated. This ratio was significantly lower in obese subjects compared with control subjects , but it Obesity is the result of complex interactions among genes, dietary intake, physical activity, and the environment. Obesity is a critical risk factor for the development of insulin resistance in children ,28. Chilz-score, and serum leptin levels. The mechanism by which ghrelin level is reduced in obesity has not been elucidated [Ghrelin and obestatin are two secreted peptides which play an important role in the regulation of food intake and body weight ,31,32. Sucidated , but ourucidated  and typeucidated . Circulaucidated , food inucidated ,41, and ucidated . TherefoIn this study, we demonstrated that acyl-ghrelin correlated negatively with TG, LDL-C, insulin, and HOMA-IR as components of metabolic syndrome and insulin resistance. Ghrelin and insulin are two hormones which play a relevant role in body weight regulation . SeveralMoreover, ghrelin has been shown to be protective against oxidative stress . It reduWe measured fasting plasma obestatin levels in obese children as well as normal-weight children. We found that the fasting plasma obestatin levels in obese children were higher than that in the controls, which is in agreement with some previous findings in adults . We alsoSeveral studies in animal models have shown that obestatin has the opposite effect of ghrelin, suggesting that it may provide new targets for the control of obesity ,16,53,54Since ghrelin and obestatin are products of a single gene, their levels may be under specific regulation, and the balance between ghrelin and obestatin might play an important role in obesity ,56,57,58We demonstrated that, compared to obese children without MetS, plasma acyl-ghrelin levels were significantly lower in obese children with MetS. However, we did not observe a significant difference in obestatin levels in obese children with MetS compared to obese children without MetS. Ghrelin has been shown to be associated with metabolic syndrome components , and leaBoth ghrelin and obestatin are deregulated in obesity and associated with insulin and insulin resistance and thus may be considered a suitable target for the management of insulin resistance. Ghrelin, but not obestatin, is associated with metabolic syndrome and oxidative stress. The balance between ghrelin and obestatin seems to be an important factor in obesity and its related complications.


With the remarkable increase in genomic sequence data from various organisms, novel tools are needed for comprehensive analyses of available big sequence data. We previously developed a Batch-Learning Self-Organizing Map (BLSOM), which can cluster genomic fragment sequences according to phylotype solely dependent on oligonucleotide composition and applied to genome and metagenomic studies. BLSOM is suitable for high-performance parallel-computing and can analyze big data simultaneously, but a large-scale BLSOM needs a large computational resource. We have developed Self-Compressing BLSOM (SC-BLSOM) for reduction of computation time, which allows us to carry out comprehensive analysis of big sequence data without the use of high-performance supercomputers. The strategy of SC-BLSOM is to hierarchically construct BLSOMs according to data class, such as phylotype. The first-layer BLSOM was constructed with each of the divided input data pieces that represents the data subclass, such as phylotype division, resulting in compression of the number of data pieces. The second BLSOM was constructed with a total of weight vectors obtained in the first-layer BLSOMs. We compared SC-BLSOM with the conventional BLSOM by analyzing bacterial genome sequences. SC-BLSOM could be constructed faster than BLSOM and cluster the sequences according to phylotype with high accuracy, showing the method's suitability for efficient knowledge discovery from big sequence data. As genome sequencing technologies represented by next-generation sequencers provide higher throughput performance, genome analyses of a very wide range of organisms can be conducted, and genomic sequence data have increased exponentially, resulting in a huge amount of data compiled in international nucleotide sequence databases (DDBJ/ENA/GenBank), which may soon reach the petascale. To enable efficient knowledge discovery from such big sequence data, it is important to examine the data comprehensively for clarifying the whole picture of all genome data available. This is especially important for phylogenetic classification of huge quantity of metagenomic data, which should contain a wide variety of novel prokaryotic and eukaryotic genomes poorly characterized previously.We have focused on oligonucleotide composition in genomic sequences and developed a “Batch-Learning Self-Organizing Map (BLSOM),” which allows us to panoramically grasp the sequence characteristics unique to organism species by analyzing an ultralarge amount of genomic sequences. We have so far applied it to gene, genome, and metagenome analyses –3. The mIn this study, we have developed the “Self-Compressing BLSOM (SC-BLSOM),” which provides higher-speed computation and better clustering performance than the conventional BLSOM for species-known genomic sequences. The SC-BLSOM achieves higher speed by dividing input data into phylogenetic subclasses and structuring BLSOMs in a hierarchical manner. As mentioned before, the conventional BLSOM can cluster genomic sequences according to phylotypes, based only on similarities in oligonucleotide composition. Therefore, this unsupervised learning method can phylogenetically classify genomic sequences even derived from a novel gene, for which an orthologous sequence set required for constructing a reliable phylogenetic tree covering a wide range of phylotypes is not available. This shows the usefulness of BLSOM for phylogenetic classification of metagenomic sequences containing a large amount of novel genes and genetic fragments. In more detail, the conventional method of phylogenetic classification of metagenomic sequences in our previous studies –6 was thhttp://www.ncbi.nlm.nih.gov/Genbank/. When the number of undetermined nucleotides (Ns) in a sequence exceeded 10% of the window size, the sequence was omitted from the analysis. When the number of Ns was less than 10%, the oligonucleotide frequencies were normalized to the length without Ns and included in the analysis.Nucleotide sequences were obtained from wij) were arranged in the two-dimensional lattice denoted by i  and j . Weight vectors (wij) were set and updated as described previously. A BLSOM program suitable for PC cluster systems and a PC program for mapping of new sequences on a large-scale BLSOM constructed with high-performance supercomputers can be obtained from our web site (http://bioinfo.ie.niigata-u.ac.jp/?BLSOM).Multivariate analyses such as factor corresponding analysis and principal component analysis (PCA) have been used successfully to investigate variations in gene sequences . HoweverA conventional BLSOM performs clustering by means of reflecting the characteristics of input data onto the weight vectors, which are arranged on a two-dimensional lattice in the same format as the input data; that is, characteristics of the input data are summarized and compressed into weight vectors. The SC-BLSOM is an analytical method that fully takes advantage of the BLSOM, and In Step 1, input data are divided according to data classification criteria “phylotype,” addition of phylogenetic information. As we use the genome sequence data of known prokaryotes for input data in this study, phylogenetic affiliation of the known prokaryote was used as the first-layer classification: Divisions 1–5 in In the SC-BLSOM, more BLSOMs are constructed than in the conventional BLSOM, but they need much shorter computation time than the BLSOM for all data input at once, because the division of data in the first-layer BLSOM has significantly reduced the number of input data pieces for each divided BLSOM. As mentioned before, BLSOM takes computation time proportional to approximately the cube of the quantity of input data. Smaller number of vectorial data pieces in the second-layer BLSOM than the original amount of data also cut computation time. Hence, shorter computation time can be expected for the SC-BLSOM compared with the conventional BLSOM.http://dx.doi.org/10.1155/2015/506052).To test the basic performance of SC-BLSOM, its computation time and clustering performance were measured and compared with those for the conventional BLSOM. This test used genomic sequence data obtained by randomly picking out genomic sequences of 10 Kb from 817 different complete genomes of prokaryotes and merging them until the sequence length was one-tenth of the original data; BLSOM and SC-BLSOM were constructed with a degenerated tetranucleotide composition in a window size of 5 Kb; the frequencies of pairs of complementary tetranucleotides  in each fragment were summed up and abbreviated as DegeTetra . The numThe analyses were conducted in a computer environment comprising Intel(R) Xeon(R) CPU E5-2680@2.70 GHz, 256 gigabytes of memory, and CentOS 5.11. The SC-BLSOM accomplished a reduced computation time approximately one-sixth of the time required for a conventional BLSOM, and as for the clustering performance the SC-BLSOM showed an improvement of about 3% over the conventional BLSOM. Additionally, in order to check whether the SC-BLSOM sufficiently reflected the characteristics of the original input data, the clustering performance was measured by plotting the original input data onto the second- layer SC-BLSOM . As the Computation time and clustering performance of the SC-BLSOM should be affected to a large degree by changing the number of weight vectors in the first-layer BLSOM. For this reason, we examined, in more detail, what the effects were from the quantity of weight vectors in the first-layer BLSOM. The number of weight vectors for the first SC-BLSOM was set to 25% of the quantity of input data, instead of 50% of the number of input data pieces used in Change in the condition for the first-layer BLSOM affects speed and clustering performance, showing a trade-off relationship between them. For example, if the aim is to quickly understand the whole picture of target species in a comparative genome analysis using all available genomes, a higher compression rate may be applied, as it suffices to grasp main features of each species. However, in estimating the biological phyla of metagenome sequences in detail, which should include sequences from a wide variety of unculturable species, BLSOMs with high clustering performance are required, and the aforementioned lower limit should be applied in order to get accurate clustering even for small-size data sets, which should be poorly represented in the current DNA databank. The level of clustering performance and computation speed should be set after taking into consideration the nature of the target data and the purpose of analysis.To verify the actual performance of the SC-BLSOM for large quantities of genome sequence data, SC-BLSOM and BLSOM for all species-known prokaryote genomes currently available were constructed with DegeTetra composition; this covers a total of 3,500,000 5 kb sequences from 3,157 species, for which at least 10 kb of sequence was available from DDBJ/ENA/GenBank. By comparing the two BLSOMs, applicability of the SC-BLSOM to large-scale, comparative genome analyses was tested. In more detail, SC-BLSOM was arranged in three layers, with the data dividing criterion of family (divided into 301 divisions) for the first layer and phylum (divided into 38 divisions) for the second layer. The weight vectors were arranged so that they represent 50% of the quantity of input data. For computation of the SC-BLSOM, an Intel Xeon Phi 5110P  mounted-PC server was used. On the other hand, the conventional BLSOM was constructed using the Earth Simulator ES2, one of the leading supercomputer systems in Japan, to perform a parallel computation with 144 CPUs.Comparative genome analyses using the conventional BLSOM for oligonucleotide composition can reveal which oligonucleotides contribute to the formation of species- and phylotype-specific clusters, providing profound information about molecular evolutionary mechanisms establishing the species-specific oligonucleotide composition “genome signature” and possible biological functions of individual oligonucleotides , 11–16. We have developed a Self-Compressing BLSOM (SC-BLSOM), which provides higher-speed and better clustering performance than the conventional BLSOM. This high-speed is achieved by dividing input data according to phylogenetic group and structuring the layered BLSOMs. Actual application to the comparative genome analyses of more than 3,000 prokaryotic genomes currently available demonstrated the method's effectiveness. The SC-BLSOM performs analyses in a layered manner, and, therefore, it performs faster as the data are divided further; the smaller number of data pieces in the first-layer BLSOM reduces the map size, resulting in shorter computation time. Furthermore, the SC-BLSOM can be easily performed in parallel using multiple computers without requiring special techniques, because the first-layer BLSOM processes are completely independent of one another.The SC-BLSOM can be applied to both comparative genome analyses and phylogenetic estimation of metagenomic sequence , 17–22. Supplementary data list the numbers of species and sequence fragments that were used in SC-BLSOM and conventional BLSOM, and the BLSOM created for each phylum in the first layer at Figure 2. Supplementary Table S1. Numbers of species and sequence fragments that were used in SC-BLSOM and BLSOM at Figure 2. Supplementary Figure S1. BLSOM with DegeTetra in 5-Kb sequences from each phylum in the first layer. (a) Actinobacteria, (b) Alphaproteobacteria, (c) Aquificae, (d) Bacteroidetes, (e) Betaproteobacteria, (f) Chlamydiae, (g) Chlorobi, (h) Chloroflexi, (i) Crenarchaeota, (j) Cyanobacteria, (k) Deinococcus-Thermus, (k) Deltaproteobacteria, (l) Epsilonproteobacteria, (m) Euryarchaeota, (n) Firmicutes, (o) Firmicutes, (p) Fusobacteria, (q) Gammaproteobacteria, (r) Spirochaetes, (s) Tenericutes, (t) Thermotogae.


Low-level environmental exposure to lead has been associated with both reduced intelligence and symptoms of attention deficit/hyperactivity disorder (ADHD). However, few studies have estimated the association of lead and intelligence independent of ADHD, and it is not clear from previous studies whether lead is associated with both inattention and impulsivity ADHD symptoms.We estimated mutually adjusted associations of environmental lead exposure with both intelligence and ADHD symptoms, and associations between lead and specific ADHD-related domains.Blood lead concentrations were measured in a general population of 1,001 children 8–11 years of age. We used multivariable linear regression models to estimate associations of blood lead concentrations with IQ scores, teacher and parent ratings of ADHD symptoms, and measures of inattention and impulsivity. Models were adjusted for demographic variables and other environmental exposures .Associations of blood lead with lower IQ and higher impulsivity were robust to adjustment for a variety of covariates. When adjusted for demographic characteristics, other environmental exposures, and ADHD symptoms or IQ, a 10-fold increase in blood lead concentration was associated with lower Full-Scale IQ  and higher parent- and teacher-rated hyperactivity/impulsivity scores  and commission errors . Blood lead was not significantly associated with inattention in adjusted models.Low-level lead exposure was adversely associated with intelligence in school-age children independent of ADHD, and environmental lead exposure was selectively associated with impulsivity among the clinical features of ADHD.http://dx.doi.org/10.1289/ehp.1307420Hong SB, Im MH, Kim JW, Park EJ, Shin MS, Kim BN, Yoo HJ, Cho IH, Bhang SY, Hong YC, Cho SC. 2015. Environmental lead exposure and attention deficit/hyperactivity disorder symptom domains in a community sample of South Korean school-age children. Environ Health Perspect 123:271–276;  Lead is an environmental neurotoxicant known to interfere with brain development . Even loThus far, the findings have been inconclusive on whether lead is associated with both the domains of ADHD symptoms , or with only one of the two domains. Profound and pervasive neurological consequences of high-level lead exposure may result in an undifferentiated worsening of ADHD-like symptoms , but it For example, the Continuous Performance Test (CPT) differentially measures sustained attention and response inhibition , and, coThus, the primary aim of the current study was to differentiate the specific aspects of attentional and behavioral impairments associated with low-level lead exposure by measuring the intelligence level, ADHD-related behaviors (rated by multiple informants), and CPT performance in a large community sample of school-age children.Secondarily, we aimed to confirm the link between environmental lead exposure and intelligence, independent of ADHD symptoms. If environmental lead exposure is associated with ADHD symptoms, given that ADHD symptoms may interfere with the child’s performance in intelligence test , it woulAnother important issue is potential confounding by other environmental exposures such as mercury, manganese, phthalate metabolites, and bisphenol A (BPA), as well as cotinine (a biomarker for tobacco exposure), each of which may be associated with ADHD . Few stun = 667) of the present study’s participants , we previously explored the relationship between lead exposure and ADHD-related problems (a) differentially affects intelligence and ADHD, b) predominantly affects impulsivity among the ADHD-related problems, and c) independently affects childhood neurobehavioral outcomes after adjusting for a wide range of potential confounders.Using data from an initial subsample  who was unaware of the child’s toxicant levels.Children’s Verbal, Performance, and Full-Scale IQs were measured via the abbreviated form of the Korean Educational Development Institute’s Wechsler Intelligence Scales for Children (KEDI-WISC) , which ta) omission errors ; b) commission errors ; c) response time for correct responses; and d) the standard deviation of these response times . The CPT was standardized for age among Korean children and adolescents, and its reliability and validity have been established   to evalu DSM-IV;  criteria DSM-IV; .Parents also completed a questionnaire about demographic and other possibly relevant data, such as paternal education level and socioeconomic status.Measurement of blood lead. Venous blood (5 mL) was collected from each child in metal-free tubes, and the samples were frozen and stored at –20°C. Before the analysis, the blood samples were brought to room temperature and vortexed well after thawing. The samples (0.1 mL) were diluted in 1.8 mL of matrix modifier reagent (composed of Triton X-100 and ammonium hydrogen phosphate dibasic), and then were mixed well using the vortex mixer and assayed using an atomic absorption spectrometer–graphite furnace . The limit of detection for lead using this method was 0.058 μg/dL. The samples were analyzed in duplicate, and we modeled the mean value of the two assays; when the coefficient of variation of the two assays was ≥ 10%, we analyzed the sample again (in duplicate) until we obtained a mean value with a coefficient of variation < 10%. The inter-run coefficients of variation were 1.74%.n-butyl phthalate, MnBP; mono-2-ethyl-5-oxohexyl phthalate, MEOHP; mono-2-ethylhexyl phthalate, MEHP)   and BPA e, MEHP)  were alsAll analyses were carried out by Neodin Medical Institute , a laboratory certified by the Korean Ministry of Health and Welfare. For the internal quality assurance and control, commercial reference materials were obtained from the German External Quality Assessment Scheme . As part of the external quality assurance and control, the institute passed the G-EQUAS operated by Friedrich-Alexander University; the Centers for Disease Control and Prevention (CDC)’s Lead and Multi-element Proficiency (LAMP) program ; and the Quality Assurance Program operated by the Korea Occupational Safety and Health Agency .Statistical analyses. Differences between the children included in and excluded from the main analyses were estimated using Student’s t-tests for continuous variables and chi-square tests for categorical variables. Blood lead concentrations (micrograms per deciliter) followed a log-normal distribution and were therefore log10-transformed for the statistical analysis. Simple and multiple linear regression analyses were performed to assess whether IQ  or ADHD-related scores (ADHD-RS and CPT) were predicted by blood lead level. First, the analyses were unadjusted for potential confounders. Then, in the first adjusted model, the analyses were conducted while controlling for age (continuous), sex, residential region , paternal education level (continuous), and socioeconomic status . Next, we added Full-Scale IQ (when predicting ADHD-RS or CPT scores) or ADHD-related variables  as covariates. Last, we further controlled for log10-transformed concentrations of mercury, manganese, cotinine, phthalate metabolites, and BPA, in addition to the covariates described above. The confounding variables were selected based on known predictors of neurodevelopment and previous publications .ications . We perfp = 0.002) and a higher proportion of rural residents (35.2% compared with 17.3%) and lower proportion of urban residents .A total of 1,089 children were initially recruited, among whom a blood sample was available for 1,005 children. Four children were further excluded from the analyses, because two had a history of seizure disorder, one of neonatal hypoxia, and one of head trauma accompanied by cerebral hemorrhage. The characteristics of the 1,001 participants are described in 2 = 165.88, p = 0.876).A total of 839 children had complete data for all model covariates and outcomes . Next, we performed the analysis adjusting for each ADHD-RS score separately  . Last, we estimated the association between lead burden and ADHD-related problems  adjusting for either Verbal IQ or Performance IQ, instead of the Full-Scale IQ . Across the various tests, the findings were similar, and did not alter the conclusion of the study.The present study confirmed previous findings that low-level environmental lead exposure is associated with lower intelligence in school-age children. In addition, our results suggest that environmental lead exposure may be selectively associated with impulsivity among the clinical features of ADHD.The negative associations between lead burden and IQ were robust, as evidenced by the largely comparable strength and statistical significance of the associations with and without the covariates. Most studies investigating the impact of lead on intelligence have relied on observational design rather than a randomized trial, which limits our ability to infer causal relationships. In this regard, it is noteworthy that concurrent rather than earlier blood lead levels have shown the strongest association with IQ in school-age children . GeneralAnother important issue that remains equivocal in the literature is the specific domain of neurobehavioral impairment associated with lead exposure. Previous findings have been inconsistent regarding whether lead contributes to inattention in addition to impulsivity , 2006. IAs predicted, associations with lead exposure varied between the specific domains of ADHD as measured by the CPT. Specifically, blood lead levels were selectively associated with commission errors, a measure of impulse control. In addition, decreased CPT response time in combination with increased commission errors is considered to indicate that the child is highly impulsive . Indeed,Reduction in lead burden has been linked to a decline in antisocial behavior   but not The present study did have some limitations. First, the cross-sectional nature of the study design and a single, concurrent measurement of lead and other environmental chemicals limit our ability to conclude that exposures preceded the outcomes. Second, other environmental exposures that have been linked to ADHD in prior studies were not adjusted for, such as prenatal tobacco exposure  and orgaIn conclusion, we demonstrated that low-level lead exposure was associated with lower intelligence in school-age children independent of associations with attentional and behavioral problems, and that environmental lead exposure was selectively associated with impulsivity among the clinical features of ADHD. The findings further highlight the need for understanding the mental health effects of co-exposure to different combinations of environmental neurotoxicants.(366 KB) PDFClick here for additional data file.


Crohn’s disease (CD) is a chronic remitting and relapsing disease. Fibrostenosing complications such as intestinal strictures, stenosis and ultimately obstruction are some of its most common long-term complications. Despite recent advances in the pathophysiological understanding of CD and a significant improvement of anti-inflammatory therapeutics, medical therapy for stricturing CD is still inadequate. No specific anti-fibrotic therapy exists and the incidence rate of strictures has essentially remained unchanged. Therefore, the current therapy of established fibrotic strictures comprises mainly endoscopic dilation as well as surgical approaches. However, these treatment options are associated with major complications as well as high recurrence rates. Thus, a specific anti-fibrotic therapy for CD is urgently needed. Importantly, there is now a growing body of evidence for prevention as well as effective medical treatment of fibrotic diseases of other organs such as the skin, lung, kidney and liver. In face of the similarity of molecular mechanisms of fibrogenesis across these organs, translation of therapeutic approaches from other fibrotic diseases to the intestine appears to be a promising treatment strategy. In particular transforming growth factor beta (TGF-β) neutralization, selective tyrosine kinase inhibitors, blockade of components of the renin-angiotensin system, IL-13 inhibitors and mammalian target of rapamycin (mTOR) inhibitors have emerged as potential drug candidates for anti-fibrotic therapy and may retard progression or even reverse established intestinal fibrosis. However, major challenges have to be overcome in the translation of novel anti-fibrotics into intestinal fibrosis therapy, such as the development of appropriate biomarkers that predict the development and accurately monitor therapeutic responses. Future clinical studies are a prerequisite to evaluate the optimal timing for anti-fibrotic treatment approaches, to elucidate the best routes of application, and to evaluate the potential of drug candidates to reach the ultimate goal: the prevention or reversal of established fibrosis and strictures in CD patients. A comprehensive literature search was performed to assess all relevant citations found in Embase, Medline  and the National Institutes of Health (NIH)) and the Cochrane Library for the following key words: (‘Crohn’s disease (CD’) OR ‘Crohn’s’ AND (‘stricture’ OR ‘fibrosis’), (‘kidney’ OR ‘liver’ OR ‘skin’ OR ‘lung’ OR ‘systemic nephrogenic’ AND ‘fibrosis’ OR ‘anti-fibrotic therapy’). Additionally, references of cited original articles and reviews were further assessed for relevant work. The search included studies between 1960 and 2013. These data together with the authors’ personal experience in the field represent the basis of this review.Crohn’s disease (CD) is a chronic remitting and relapsing disease. During in vitro and in vivo[Fibrosis is defined as the accumulation of collagen-rich extracellular matrix (ECM) in response to tissue damage and is a common complication of multiple chronic diseases. Repetitd in vivo. Contracd in vivo. Additiod in vivo. In contd in vivo.IL-17A was found to possess pro-fibrotic activity in various cell types including cardiac fibroblasts, hepaticThe core mediator in various organs for both, the initiation as well as the maintenance of fibrosis is TGF-β. This grIn addition to the above mentioned mediators, the imbalance of MMPs and TIMPs, which are physiologically involved in maintaining a state of ‘healthy’ remodeling and restitution, can aggravate structural changes of the bowel wall,49.Restoring the integrity of the intestinal barrier, culminating in epithelial wound closure may help to resolute and regress fibrosis, since continuous barrier defects appear to be one potential trigger for chronic inflammation promoting pro-fibrotic alterations. To this aim ECM-producing mesenchymal cells are recruited. These cells may migrate from neighboring tissue, originaBeside chronic inflammation as a major driver of intestinal fibrosis, inflammation-independent mechanisms deserve closer attention. In particular, activated mesenchymal cells, also referred to as disease-activated myofibroblasts, produce and secrete high levels of several collagen types, such as type I, III and V-61 and EIn summary, despite different physiological functions and unique features of the human gut, such as the high load of microbial components, intestinal fibrosis shares pathological core features with fibrosis of other organs, such as the lung, kidney, skin or liver. Consequin vivo and in vitro[in vivo, recent data revealed no link between anti-TNF administration with intestinal stricture formation[Commonly used drugs for the anti-inflammatory therapy of CD have been observed to possess at least minor anti-fibrotic properties in other organs. For example, corticosteroids were found to decrease pro-collagen expression  in vitro as well  in vitro. Cortico in vitro, systemi in vitro and idio in vitro. In cont in vitro. In stri in vitro. The lon in vitro and fibr in vitro,76. In C in vitro, however in vitro,78. TNF- in vitro-82 and a in vitro, pulmona in vitro and syst in vitro suggest  in vitro. In cont in vitro. After iormation. Informaormation and antiormation.In daily clinical practice, most CD patients present with established strictures, representing the end-stage of the fibrotic process, and most clinicians see this scenario as an inevitable progression to a likely surgical intervention. This does not have to be so, as the theoretical and practical feasibility to stop or even reverse intestinal fibrosis is supported by the observation that tissue alterations in experimental models of intestinal fibrosis disappear after elimination of the pro-fibrotic stimulus. No therAnti-fibrotic strategies used in the kidney, lung, liver, heart or skin can be grouped into strategies modulating growth factors, inflammation or oxidative stress, intracellular enzymes, and ECM production or assembly Figure . We herein vitro and in vivo studies indicate an anti-fibrotic activity using anti-TGF-β antibodies, soluble TGF-β receptor, blockade of TGF-β activation by decorin, a small-molecule inhibitor of TGF-β receptors[Feasibility of TGF-β1 blockade to treat fibrotic diseases has been shown in IPF. In this condition, TGF-β is driving fibrotic alterations and epithelium-dependent fibroblast activation. In murieceptors, adminiseceptors and throeceptors. In humaeceptors. Moreoveeceptors was obseeceptors. Substraeceptors.in vitro and in vivo studies, to date limited experience with tyrosine kinases in human fibrotic diseases is available[In addition to the Smad-signaling cascade, non-Smad pathways comprising TGF-β1 activated MAPKs and several tyrosine kinases have been targeted for anti-fibrotic actions. For example, c-Abelson (c-Abl), a component of the Bcr-Abl oncogene, can be effectively blocked by selective tyrosine kinase inhibitors such as imatinib. This agent inhibits PDGF as well and thus potentially regulates fibroblast proliferation and transformation. Despitevailable,108. Of vailable, while bvailable. In contvailable. In addivailable,113 of fvailable.in vitro as well as in vivo observations. For example, intestinal TGF-β overexpression in mice leads to colonic fibrosis and obstruction[+ T cells[in vivo, as an anti-fibrotic approach in CD may be highly problematic, as this may actually lead to disease exacerbation given the potent anti-inflammatory and immunoregulatory properties of this cytokine.The scientific rationale to target TGF-β signaling in stricturing CD comes from truction, while dtruction. In humatruction. Althougtruction,117. Fortruction,119. Thitruction and is m T cells. Similar T cells,123. Fur T cells. Possiblin vitro[in vitro findings, HMG-CoA reductase inhibitors revealed various anti-fibrotic effects in murine models of nephropathy and fibrosis[HMG-CoA reductase inhibitors were developed with the intention to decrease cholesterol levels. More recently, they were found to mediate anti-inflammatory as well as anti-fibrotic effects in vitro, includiin vitro-128. Corfibrosis,127. In fibrosis and redufibrosis. Furtherfibrosis leading,fibrosis. In addifibrosis. NeverthIn vivo administration of the ACE inhibitor enalaprilate has been proven to reduce weight loss and histological damage in murine dextran sulfate sodium (DSS)-induced colitis[Angiotensin II (AT II) is the major mediator of the renin-angiotensin system (RAS). AT II may increase ECM accumulation through plasminogen activator inhibitor-1-mediated decrease of MMPs and enhance TGF-β1 production in cardiac and renal fibrosis,135. The colitis. ACE inh colitis and this colitis,149.Of note, through its AT1 receptor, AT II enhances the expression of CTGF, and administration of AT II inhibitors and AT1 receptor antagonists significantly ameliorates or reverses fibrotic alterations in experimental colitis reflected by reduced collagen amounts and TGF-β1 mRNA levels,151. Exiin vivo. IL-13 mediates, through binding to its IL-13Rα, an increased production of TGF-β and is a key player in the initiation of fibrotic alterations in the intestine[Pro-inflammatory cytokines contributing to the pathogenesis of IBD could also be involved in the development of intestinal fibrosis in CD. For example, IL-1 modulates myofibroblast activation, chemokine production, MMP secretion and is intestine. Confirmntestine,157. In ntestine,158-160.The process of inflammation and fibrosis are likely to be intertwined through angiogenesis and lymphangiogenesis. Increased levels of factors implicated in angiogenesis have been documented in IBD patients, such as vascular endothelial growth factor A (VEGF-A). At a ceThe imbalance between deposition and degradation of ECM in fibrotic disease is a logical target for anti-fibrotic treatment approaches. Stimulation of MMPs as central regulators of ECM disassembly were expected to reverse fibrotic alterations, however, clinical studies in patients with nephrosclerosis failed to show efficacy. LikewisThe mammalian target of rapamycin (mTOR) protein is a serine/threonine protein kinase that consists of several complexes among which mTOR complex 1 regulates protein synthesis, proliferation as well as fibrotic actions. mTOR inPeroxisome proliferator-activated receptor gamma (PPAR-γ) is a nuclear receptor that modulates gene expression and is involved in various physiological and pathological processes including inflammation and fibrosis. After sA summary of compounds used as anti-fibrotic therapies in other organs and their mode of action is depicted in Figure The most efficient anti-fibrotic treatment approach still remains the elimination of the primary cause of intestinal injury, which would mean nothing less than curing CD. However, since a magic bullet for CD is not and will most likely not be available in the near future, clinical evaluation and optimization of anti-fibrotic drug candidates for stricturing CD is a justifiable and promising treatment strategy.However, the simple transfer of these agents into CD treatment is premature and multiple obstacles have to be overcome to make use of the above described mediators and mechanisms.First, the ideal anti-fibrotic drug should target something uniquely expressed in a specific fibrotic complication in a particular organ and should not display any systemic side effects. This is particularly true in case of concomitant injury elsewhere in the body. To date, however, no specific target for intestinal fibrosis or other fibrotic disease has been identified, which supports the hypothesis that mechanisms of fibrosis are shared between different organs.Second, the optimal timing to commence anti-fibrotic treatment is of utmost importance to CD patients, however, is not defined yet. It is obvious that an early use of anti-fibrotics is expected to be associated with a better outcome in patients prone to this complication. Pre-existing fibrosis and concomitantly increased tissue stiffness can perpetuate fibrosis even in the absence of inflammation. Data from experimental fibrosis seems to confirm that there might be a critical point in evolution of fibrosis when the progress becomes irreversible. TherefoThird, a patient-tailored anti-fibrotic treatment approach necessitates the identification of biomarkers to enable individual risk stratifications for stricturing disease and to follow the individual evolution of fibrosis. As opposed to other organs, such as liver,188 or lFourth, the best route of application for anti-fibrotic agents in stricturing CD has to be elucidated. In line with the beneficial effects of systemic administration of anti-fibrotics in other organs, intraveFinally, a general limitation to evaluating potential anti-fibrotic agents is the long-lasting evolution of fibrotic complications in patients with CD requiring clinical trials of long duration and large patient populations, making them very expensive and impractical.It is unclear and in the realm of speculation, which of the reviewed drugs has the highest potential for success as an anti-fibrotic treatment in CD. Combining drugs with a known safety profile and anti-fibrotic efficacy, such as HMG-CoA reductase inhibitors, mTOR inhibitors or inhibitors of the angiotensin system, could serve as a starting point. Given the effect of most substances on a reduction of TGF-β1 proper precaution needs to be taken for carefully monitoring intestinal inflammation. Novel drug delivery systems, such as the Multi Matrix System (MMX®), allowing oral administration of a compound with the substance being released in a defined area of the gastrointestinal tract  can circumvent systemic side effects, such as hypotension for angiotensin blockade.To move forward with specific anti-fibrotic therapies in the future we need to focus on identifying mechanisms of fibrogenesis and to develop new and better animal models for this disease Figure . What, hStricturing CD is still an unresolved problem with strong implications for the patients and a high socioeconomic burden due to frequent hospitalizations and surgery. Despite6-MP: 6-Mercaptopurine; ACE: Angiotensin-converting enzyme; ALK: Activin receptor-like kinase; AT II: Angiotensin II; AZA: Azathioprine; bFGF: Basic fibroblast growth factor; c-Abl: c-Abelson; CD: Crohn’s disease; CTGF: Connective tissue growth factor; DSS: Dextran sulfate sodium; ECM: Extracellular matrix; ED: Endoscopic dilation; EMT: Epithelial-mesenchymal transition; EndoMT: Endothelial-mesenchymal transition; HMG-CoA: 3-Hydroxy-3-methyl-glutaryl-coenzyme A; IBD: Inflammatory bowel disease; IGF: Insulin-like growth factor; IL: Interleukin; IPF: Idiopathic pulmonary fibrosis; MAPK: Mitogen-activated protein kinase; MMP: Matrix metalloproteinase; mTOR: Mammalian target of rapamycin; NF-κB: Nuclear factor kappa-light-chain-enhancer of activated B cells; NIH: National Institutes of Health; NLM: National Library of Medicine; PDGF: Platelet-derived growth factor; PG-PS: Peptidoglycan-polysaccharide; PPAR: Peroxisome proliferator-activated receptor; RAS: Renin-angiotensin system; ROCK: Rho-associated protein kinase; SAP: Serum amyloid P component; TGF: Transforming growth factor; THBS: Thrombospondin; TIMP: Tissue inhibitor of metalloproteinase; TLR: Toll-like receptor; TNBS: 2,4,6-Trinitrobenzene sulfonic acid; TNF: Tumor necrosis factor; VEGF: Vascular endothelial growth factor.The authors declare that they have no competing interests.DB and FR developed the review concept, performed the literature review and wrote the manuscript. Both authors read and approved the final version of the manuscript.


The interaction among different types of small RNA molecules reveals an even more complicated and elaborate pattern of RNA regulation during gene expression than previously thought. We developed a method for mining ta-siRNA sequences and evaluated the performance of our novel method using data from Arabidopsis thaliana. Additionally, using small RNA and degradome data for the human brain, we identified 155 small RNAs that satisfied ta-siRNA characteristics. The DRAXIN and ATCAY genes, which are preferentially expressed in the human brain, were predicted to be the targets of 12 potential ta-siRNAs.Endogenous small non-coding RNAs play pivotal roles in regulating gene expression in eukaryotes. Many studies have investigated the function and molecular mechanism of microRNAs in the development and disease of various organisms via mRNA repression of protein-coding genes. Recent findings indicate microRNAs might trigger the generation of  Endogenous non-coding small RNAs (20–25 nt) that regulate gene expression are important to the growth and development of organisms. Two classes of small RNAs that have been widely studied are microRNAs (miRNAs) and small interfering RNAs (siRNAs). In general, miRNAs are about 21 nt in length, are encoded by eukaryotic nuclear DNA, and are involved in transcriptional and post-transcriptional regulation during gene expression. A given miRNA may have different mRNA targets, and the target mRNA sequence may be subject to regulation by numerous miRNAs. In the nucleus, genes corresponding to a miRNA are transcribed by RNA polymerase II to produce an imperfect, self-complementary, hairpin-loop structure known as Pri-miRNA [The biogenesis of siRNAs and the mechanisms by which they engage in post-transcriptional suppression differ from those of miRNAs. Endogenous siRNAs are generated from inverted or direct repeat sequences . Double-et al. [et al. [trans-acting siRNAs (ta-siRNAs). Their biogenesis is initiated by miRNA-directed cleavage of primary transcripts, thus providing a link between miRNA and siRNA regulation [Arabidopsis thaliana. The biogenesis of certain ta-siRNAs requires dual miRNA cleavage sites [Despite the many differences between miRNAs and siRNAs, they are both induced and processed by proteins during their biogenesis. Peragine et al.  and Vazq [et al.  identifigulation ,12. Thesge sites . It has ge sites ,14,15.A. thaliana: TAS1 , TAS2, TAS3 , and TAS4 [TAS gene produces a number of ta-siRNAs that can regulate genes whose functions range from RNA editing to cell fate [Four TAS gene families have been identified in and TAS4 ,12,16. Eell fate ,18. Ta-sell fate , rice [1ell fate ,20, maizell fate , grapeviell fate , apple [ell fate  and peacell fate .TAS genes and ta-siRNAs in the human brain through the use of small RNA and degradome datasets.The discovery of ta-siRNA molecules has provided a link between miRNA and siRNA regulation. Ta-siRNAs are able to enhance the impact of miRNAs through tandem cascade amplification effects . One or A. thaliana were used. We identified six ta-siRNAs and seven TAS genes in A. thaliana , where “hs” indicates Homo sapiens. Some of the predicted TAS genes were uncharacterized protein genes or non-protein coding genes. The other TAS genes were related to an extensive range of metabolic processes, such as vesicle-mediated transport, phosphorylation, phosphate metabolic processes, and ribonucleotide binding. The ta-siRNAs generated from these TAS genes could regulate a wide range of genes and thus have an extensive effect on different aspects of biological processes  Similarities of ta-siRNAs in the human brain and mice; (b) Similarity of a mouse ta-siRNA with three human ta-siRNAs.-related family members, which are also the targets of miR828. To date, three TAS3 loci have been identified in A. thaliana: TAS3a, TAS3b, and TAS3c [A. thaliana from the juvenile to the adult stage. Although only four TAS families have been classified, the members of these families have been shown to have remarkable effects on A. thaliana. The generation of ta-siRNAs is initiated by miRNAs, and can target genes in a similar way as miRNAs. Thus, the effects of miRNAs can be amplified, resulting in further regulation of target genes. The majority of plant miRNAs function through mRNA cleavage, and several mammalian miRNAs employ this mechanism of action. The siRNA-like mode of plant miRNAs action may therefore be an ancestral mechanism. In support, miRNA has been found to frequently regulate targets via cleavage in members of the ancient phylum Cnidaria. Therefore, it is possible that miRNAs in plants and animals share a common ancestry and that these ancestral miRNAs act via slicing. Slicing generally has fewer targets and a stronger effect on target silencing than do other modes of miRNA action [The ta-siRNA class of RNA molecules was first identified in  binding . The PPR in rice . TAS4 isnd TAS3c . These tA action . miRNA-tCaenorhabditis elegans and Drosophila melanogaster RNAi have revealed the transitive RNAi model, in which dsRNA is amplified to ensure the RNAi response is maintained [et al. also found that small amounts of dsRNA can effectively initiate gene silencing [The predicted ta-siRNAs identified in this study result from a small number of reads. Studies of intained ,48,49. Filencing . TherefoThe protein complex RdRP appears to be an important component in the generation of plant ta-siRNAs. In higher eukaryotes, such as the fly, human, and mouse, the role of RdRP may be performed by various functional homologs ,52,53,54TAS1 loci in A. thaliana [TAS3 loci in Vitis vinifera [In plants, some ta-siRNAs are from the 21-nt phase positions on the transcripts cleaved by miRNAs, such as ta-siRNAs arising from the thaliana . Howevervinifera . Our preAlthough research into ta-siRNAs is not as popular as miRNA research, their importance in regulating the relationship between miRNAs and mRNAs is crucial. There are many ta-siRNA-related mechanisms and functions that remain unclear, and are thus potential avenues of future research. Understanding more about ta-siRNAs would likely help us better understand miRNAs and siRNAs, and their interactions. The prediction pipeline we have designed offers a new method to identify potential ta-siRNAs, which could be applied to future studies.http://www.ncbi.nlm.nih.gov/gds, Small RNA datasets sequenced by Illumina, and degradome datasets were downloaded from the Gene Expression Omnibus repository  were predicted because ta-siRNAs can amplify tandem cascades with respect to miRNA functions. We used the same parameters that were employed for miRNA target prediction. If fragments cleaved by the ta-siRNA candidate matched the sequence from the degradome data, it was regarded as a potential ta-siRNA. The whole prediction flow is shown in A. thalianaTAS genes to evaluate the performance of our prediction pipeline. The mRNA sequences of the relevant A. thalianaTAS genes were from The Arabidopsis Information Resource . We downloaded the small RNA data from Arabidopsis MPSS Plus [We used known PSS Plus ,63, whilTo investigate the conservation of ta-siRNAs between mice and humans, we predicted murine ta-siRNAs using our pipeline and compared them with known human ta-siRNAs.A. thaliana to estimate its accuracy. Seven ta-siRNAs were predicted, of which four were known ta-siRNAs with the remaining three were predicted by other algorithms. Our prediction results in A. thaliana were highly specific. When our prediction analysis was applied to humans, we identified 324 potential TAS genes and 155 potential ta-siRNAs. In mice, 499 potential TAS genes and 77 potential ta-siRNAs were identified. Among these predicted ta-siRNAs, three ta-siRNAs in humans were similar to a single ta-siRNA in mice. The trigger miRNAs of ta-siRNAs predicted in human brain and mice are also poorly conserved. These findings suggest that ta-siRNAs are weakly conserved, which is in accordance with a recent finding that non-coding genes exhibit relatively low levels of conservation [Based on the process by which ta-siRNAs are generated, we designed a prediction pipeline to identify novel ta-siRNAs in humans. As the research continues, many new characteristics of miRNAs have been shown. In our algorithm, we designed a new method to predict the targets of miRNAs. The differences between our method and other target prediction tools are: (1) we do not require the conservation of mRNAs; (2) the targets of miRNAs are not restricted to the 3' UTR; (3) the “seed” sequence can be 1–7 nts. The criteria for target prediction were set based on miRNA properties and experimental experiences. The binding energy of miRNA to its target was below −25 kcal/mol and the least continuous match was 7 bp based on the “seed sequence” of miRNAs. Our prediction pipeline was first applied to ervation .


Androgen receptor (AR) is a ligand-activated transcription factor that is the main target for treatment of non-organ-confined prostate cancer (CaP). Failure of life-prolonging AR-targeting androgen deprivation therapy is due to flexibility in steroidogenic pathways that control intracrine androgen levels and variability in the AR transcriptional output. Androgen biosynthesis enzymes, androgen transporters and AR-associated coregulators are attractive novel CaP treatment targets. These proteins, however, are characterized by multiple transcript variants and isoforms, are subject to genomic alterations, and are differentially expressed among CaPs. Determining their therapeutic potential requires evaluation of extensive, diverse datasets that are dispersed over multiple databases, websites and literature reports. Mining and integrating these datasets are cumbersome, time-consuming tasks and provide only snapshots of relevant information. To overcome this impediment to effective, efficient study of AR and potential drug targets, we developed the Regulators of Androgen Action Resource (RAAR), a non-redundant, curated and user-friendly searchable web interface. RAAR centralizes information on gene function, clinical relevance, and resources for 55 genes that encode proteins involved in biosynthesis, metabolism and transport of androgens and for 274 AR-associated coregulator genes. Data in RAAR are organized in two levels: (i) Information pertaining to production of androgens is contained in a ‘pre-receptor level’ database, and coregulator gene information is provided in a ‘post-receptor level’ database, and (ii) an ‘other resources’ database contains links to additional databases that are complementary to and useful to pursue further the information provided in RAAR. For each of its 329 entries, RAAR provides access to more than 20 well-curated publicly available databases, and thus, access to thousands of data points. Hyperlinks provide direct access to gene-specific entries in the respective database(s). RAAR is a novel, freely available resource that provides fast, reliable and easy access to integrated information that is needed to develop alternative CaP therapies.Database URL: http://www.lerner.ccf.org/cancerbio/heemers/RAAR/search/ The androgen receptor (AR) is a member of the ligand-activated family of nuclear receptors. Upon activation by androgens, AR binds to androgen response elements (AREs) where it assembles the transcriptional complexes to control the expression of target genes , 2. The At the prereceptor level, efforts focus on targeting the key cellular events that control androgen biosynthesis in CaP cells , 12, 13.At the post-receptor level, the characterization of the AR cistrome and AR-dependent transcriptome has facilitated recognition of gene-specific contribution of coregulators and secondary transcription factors to AR-dependent transcription , 25–27. Renewed insights into the mechanisms by which CaP recurs despite ADT are uncovering novel approaches for therapeutic intervention at the AR pre-receptor and post-receptor levels , 9. The To overcome this barrier to the study of AR in CaP, we have developed a novel tool, the Regulators of Androgen Action Resource (RAAR) database. The goal of RAAR is to accrue and provide information in a user-friendly and freely available manner to facilitate the development of novel therapies to inhibit AR action in CaP.RAAR gives access to information at two levels. First, it provides an up-to-date database of genes involved in pre-receptor and post-receptor regulation of AR signaling axis activity. Second, RAAR integrates access to well-established and well-curated databases that provide user-friendly and ready-to-use comprehensive information on gene function, clinical relevance, and technical details for research resources for each RAAR entry. Currently, RAAR contains entries for 329 genes involved in AR action in CaP and links to > 30 databases.RAAR gene entries are classified according to the function for which the gene is known, either pre-receptor or post-receptor. To date, the scenario in which a gene can be entered under both the pre-receptor and post-receptor sections applies only to the AKR1C3 gene. A wealth of reports substantiate AKR1C3’s involvement in multiple intracrine androgen biosynthesis pathways , but onlde novo synthesis of DHT, which starts from acetate  compared to our previously reported inventory  a gene-specific entry (see below) could not be established in the pre- or post-receptor sections, yet the resource itself is relevant for study of the gene of interest listed in RAAR or may give more detail on entry-specific insights derived from the pre-receptor or post-receptor section. Information maintained in other databases is complementary but not identical to what is provided already in RAAR . Links to databases providing specific tools that allow one to compare and analyze genes and gene signatures and regulatory DNA sequences in more detail  are included also. A link to Nucleic Acid Research’s Molecular Biology Databases, several of which may be helpful in enhancing the value of RAAR-derived insights, and links to homepages of the databases listed in http://www.lerner.ccf.org/cancerbio/heemers/RAAR/search/) that is accessible also via a link on the senior author’s (H.V. Heemers) laboratory web site (http://www.lerner.ccf.org/cancerbio/heemers/). Gene lists of critical regulators of intra-CaP androgen biosynthesis and AR-associated coregulators were converted into CSV format files, which were used as input for a MySQL database. Database access is provided by a user interface in PHP and AJAX and a web interface that runs on a Linux (2.6.18)—Apache (2.0) MySQL (5.0.77)—PHP (5.3.6) platform. The MyISAM database storage engine manages non-transactional tables, provides high-speed storage and retrieval and supports full-text searching. The search interface allows searching the pre-receptor and the post-receptor databases by official gene symbol; the other resources database is searched by database name .For some RAAR entries, no content is available in the selected external databases. In those cases, RAAR includes no hyperlink for that entry, which is reflected in a ‘no information’ statement on the results page. Hyperlinks for these RAAR entries will be added as the corresponding database information becomes available.RAAR content is curated manually by Heemers lab members every 3 months. The content of the external databases to which hyperlinked access is provided is monitored frequently. In the event that major updates or additions to external databases occur prior to scheduled RAAR maintenance, RAAR will be updated at an accelerated schedule.RAAR@ccf.org.RAAR strives to be a resource that provides fast, reliable and easy access to integrated information on key regulators of AR action. Recommendations for updates, improvements and additions are welcome. Readers and users are encouraged to forward their suggestions to Improving ADT so that treatment is biomarker-driven and individualized requires complementary expertise in molecular biology, genomics, clinical urology and bioinformatics. RAAR provides not only an up-to-date overview of key regulators of AR activation and transcriptional activity, but brings together in one place an array of diverse resources to facilitate access to multidisciplinary information via simple, user-friendly searches. An advantage of the compendium side of RAAR is it the ease with which the user can study simultaneously the co-operativity, or redundancy, between genes in RAAR. This is an important consideration in view of compensatory mechanisms that govern the activity of both steroidogenic enzymes and coregulators. At the molecular level, RAAR allows the user to, for instance, identify and compare easily the catalytic sites that are present in different steroidogenic enzymes. From a translational perspective, the RAAR user can determine co-expression patterns of regulators and downstream effectors of AR action, correlate differential expression with CaP outcome and survival, and verify the CaP-specificity of these events. For example, merging molecular and clinical aspects, RAAR allows one to evaluate the impact of a genomic alteration that is associated with clinical CaP progression on its protein function, protein interactome and technical resources that are available to pursue the observation further at the bench.The topic of RAAR, namely the genomic action of a nuclear receptor, is similar to, but does not overlap with, other publicly available resources, such as those included in Nucleic Acids Research’s Molecular Biology Database Collection. The AR mutation database , which pRAAR was established by CaP researchers seeking to understand better and target more efficiently AR action in this endocrine cancer. The wealth of diverse data on AR action that is included also makes RAAR a valuable resource for investigators who study other human conditions in which AR is a viable but poorly understood target for therapy. For instance, AR is starting to be recognized as attractive target in triple-negative (ER-/PR-/Her2-) breast cancer  and may


Previous studies have shown that patients with hepatitis B virus-related cirrhosis (HBV-RC) without overt hepatic encephalopathy (OHE) are associated with a varying degree of cognitive dysfunction. Several resting-state functional magnetic resonance imaging (fMRI) studies have been conducted to explore the neural correlates of such cognitive deficits, whereas little effort has been made to investigate the cortical integrity in cirrhotic patients without OHE. Here, using cortical thickness, surface area and local gyrification index (lGI), this study performed a comprehensive analysis on the cortical morphometry of patients with HBV-RC without OHE (HBV-RC-NOHE) vs. matched healthy controls. Compared with healthy controls, we found significantly increased cortical thickness in the bilateral lingual and parahippocampal gyrus, right posterior cingulate cortex, precuneus, peri-calcarine sulcus and fusiform gyrus in patient with HBV-RC-NOHE, which may closely relate to be the low-grade brain edema. Cortical gyrification analysis showed significantly increased lGI in the left superior and inferior parietal cortex as well as lateral occipital cortex, which was speculated to be associated with disruptions in white matter connectivity and sub-optimal intra-cortical organization. In addition, the mean cortical thickness/lGI of the regions with structural abnormalities was shown to be negatively correlated with psychometric hepatic encephalopathy score (PHES) of the patients with HBV-RC-NOHE. These morphological changes may serve as potential markers for the preclinical diagnosis and progression of HBV-RC-NOHE. Hepatitis B virus-related cirrhosis (HBV-RC) is one of the most serious public health problems in Asia, which is associated with high infection, morbidity and mortality rates , various morphometric approaches have been developed to identify macroscopic changes in the human brain. In cirrhotic patients, most of existing morphometric studies were performed by using voxel-based morphometry  vs. matched healthy controls. Based on previous studies  with chronic liver cirrhosis caused by HBV infection were included in this study. All patients had HBV-RC diagnosed by biopsy or on the basis of case history, clinical examination, biochemical and imaging findings. OHE was diagnosed when the West Haven criteria indicated stage I disease or higher. Patients were excluded if they had current symptoms of OHE at the time of recruitment, any history of OHE, other types of viral hepatitis, gastrointestinal hemorrhage or bacterial infection (within 1 month before the study), a transjugular intrahepatic portosystemic or a surgical portocaval shunt, diffuse hepatocellular carcinoma, or were taking drugs that could alter cerebral function. All patients underwent a detailed clinical examination. The severity of liver disease was determined according to the Child-Pugh score.For comparison, 22 healthy controls  matched for age, sex and years of education, without disease of liver and other systems, were recruited via advertising within the hospital. All controls received detailed clinical and neurological examinations on the same day as the MRI scans. Exclusion criteria for all patients and controls included age lower than 18 or greater than 70 years, alcoholism, neurological or psychiatric diseases, a history of substantial head trauma that resulted in unconsciousness or at least in substantially altered mental status, infection with human immunodeficiency virus, hypertension, diabetes, poor vision, other major medical illness, left-handedness, and any focal abnormality detected on routine brain MRI examinations.This study was approved by the Medical Research Ethics Committee of Nanfang Hospital, Southern Medical University. Written informed consent was obtained from all the participants before the study. Detailed clinical and demographic data of patients with HBV-RC-NOHE and healthy controls are shown in Table The PHES battery, a psychometric test that involves visual perception, construction, visual/spatial orientation, motor speed and accuracy, concentration, and attention  pulse sequence was used to produce 155 1-mm-thick contiguous axial images .FreesurferEach scan was processed using Cortical thickness was defined at each point on the pial surface (as well as its counterpart on the gray/white matter surface because of the one-to-one correspondence) as the mean of the two shortest distances  was deemed significant.The Mann-Whitney U test was used to analyze the differences in PHES test performance between the two groups. Analyses were conducted using commercially available statistical software , and a P value was obtained using random field theory  and PHES controlling sex and age. The level of significance for the correlation analyses was set at P < 0.05.Vertex-by-vertex contrasts of cortical thickness, surface area and lGI were performed between normal controls and patients with HBV-RC-NOHE. Specifically, each contrast was entered into a vertex-by-vertex GLM including diagnosis, sex and age as covariates. Subsequently, a corrected cluster-wise P < 0.001). Vertex-wise contrasts of the surface-based measurements revealed increased cortical thickness and gyrification in patients with HBV-RC-NOHE. Cortical thickness analysis found three CODs involving the bilateral lingual and parahippocampal gyrus, right posterior cingulate cortex, precuneus, pericalcarine sulcus and right fusiform gyrus (Figure Compared with healthy controls, cirrhotic patients performed worse on the PHES test (−3 −9–1] for patients vs. 0 −2–3] for controls;  for pati–3 for cor = −0.5173, p = 0.0115 for COD 1; r = −0.6973, p = 0.0002 for COD 2; r = −0.6333, p = 0.0012 for COD 3; correlation between lGI and PHES: r = −0.432, p = 0.0395 for COD 4; Figure Within the patients group, correlation analyses revealed significant negative correlations between the average cortical thickness/lGI of the corresponding COD and PHES (correlations between cortical thickness and PHES: In the current study, surface-based morphometry was applied to quantify the cortical thickness, area and gyrification in well-matched samples of patients with HBV-RC-NOHE vs. healthy controls. We observed increased cortical thickness and lGI in patients with HBV-RC-NOHE. In addition, we also revealed negative correlations between the mean cortical thickness/lGI of each COD and PHES.In the present study, we observed significantly increased cortical thickness in patients with HBV-RC-NOHE. The regions showing significantly increased cortical thickness are functionally relevant to the neurocognitive deficits in patients with HBV-RC-NOHE. Specifically, the lingual gyrus, calcarine sulcus, fusiform gyrus and parahippocampal gyrus are key nodes of ventral visual pathway, abnormalities in which may relate to impaired visual information processing in cirrhotic patients. The posterior cingulate cortex and precuneus have reciprocal connections with other parietal areas, such as the operculum, and inferior and superior regions of the lateral posterior parietal lobe (Selemon and Goldman-Rakic, The observed cortical thickness increase in cirrhotic patients seems to contradict a previous report of cortical thickness reduction in patients with MHE (Montoliu et al., Given that cortical thickness measures the size, density and arrangement of cells, cortical thickness alterations may correspond to substantial pathological changes in the underlying cell counts and organization (Narr et al., Compared with controls, patients with HBV-RC-NOHE showed greater gyrification in the left inferior and superior parietal cortex as well as lateral occipital cortex. The inferior and superior parietal cortex as well as the lateral occipital cortex are key nodes of the dorsal visual pathway, which is generally accepted to be responsible for motion perception, spatial awareness, and vision for action (Laycock et al., The exact mechanism underlying the cortical gyrification changes is not clear, although a number of theories about the ontogenesis of cortical gyrification have surfaced (White et al., A novel finding in this study was the identification of negative correlations between performance on PHES and the mean cortical thickness/lGI of the CODs, suggesting that the more serious the cognitive impairments, the more obvious is the dysfunction detected in those regions. Our findings further suggest that the visual-related cortical dysfunction might be involved in the pathophysiology of deficits in visual processing in cirrhotic patients. In addition, the correlations between the cortical thickness/lGI and the PHES indicate that such indices in these brain regions may serve as potential biomarkers to reflect the severity of cognitive changes in patients with HBV-RC-NOHE.There are several limitations that should be addressed. First, as a preliminary study, our results are limited to a small patient cohort, which may have an effect on the power of the statistical analysis of this study. Further studies with more patients are needed to replicate the current findings. Second, given the nature of cross-sectional study, the present study does not allow for the investigation of the dynamic development of the structural abnormalities in these patients from HBV-RC-NOHE to OHE. Further studies adopting a longitudinal design is needed to unveil the dynamic pattern of the structural abnormalities as the disease progresses.In conclusion, the present study performed a comprehensive analysis on the cortical morphometry of patient with HBV-RC-NOHE. Compared with healthy controls, we found increased cortical thickness and gyrification in patients with HBV-RC-NOHE. In addition, we revealed significant negative correlations between the mean cortical thickness/lGI of each COD and PHES in patients with HBV-RC-NOHE. These morphological changes may serve as potential markers for the preclinical diagnosis and progression of HBV-RC-NOHE.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.


Accurate quantification of the activity distribution in positron emission tomography (PET) mandates attenuation correction (AC). Unlike in PET/CT, AC in PET/MR is, however, challenging, since information about the attenuation properties of the patient tissue distribution is not available directly. Standard MR-based AC (MRAC) does not account for the presence of bone and, thus, yields an underestimation of the activity distribution. We propose an algorithm to simultaneously reconstruct the activity and attenuation distribution using MR images as anatomical prior information for non time-of-flight PET/MR. The proposed algorithm is an extension of the existing maximum-likelihood reconstruction of attenuation and activity (MLAA). The MR images are used to obtain an initial attenuation map and to derive voxel-dependent expectations on the attenuation coefficients. These expectations are modeled using pre-defined attenuation values and Gaussian-like probability functions. An iterative reconstruction scheme incorporating the prior information on the attenuation coefficients is used to update attenuation and activity distribution in an alternating manner. The algorithm, called MR-MLAA, is evaluated for simulated 2D PET data for two patients with artificial lesions in the head region. The proposed algorithm helps recover bone attenuation information. However, for both patients, some misclassifications of air (considered as bone) and bone (considered as air or soft tissue) were observed. Nevertheless, PET quantification in lesions located close to bone tissue is greatly improved when using MR-MLAA. Errors in activity estimation are reduced to ranges of -9% to +1% whereas MRAC yields errors of -22% to -10%. In conclusion, MR-MLAA has the potential to improve quantification in hybrid PET/MR, especially in regions adjacent to dense bone tissue.


Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes.  Comparative analysis is implemented for comparing two or more organisms to identify their similarities as well as mechanisms for diversification toward various key biological processes such as reproduction, defense response, metabolic pathways, photosynthesis, and many more. It involves comparison of either different species of same family or different taxonomic organisms of same species  in aerial   retrieval and pre-processing of datasets, (2) identification of differentially expressed genes, (3) construction and validation of gene co-expression networks, (4) evaluation of network robustness, (5) functional annotation and enrichment analysis of modules, and (6) comparison of gene co-expression networks.In order to compare R. serpentina (8) and C. roseus (6) were retrieved from the Medicinal Plant Genomics Resource database  . An e-value cutoff of 1e-05 was used to identity orthologous genes, and top hit annotations were preserved for further analyses. Expression data  of different tissues were obtained for R. serpentina  and C. roseus . For comparative analysis expression data of only common transcripts was considered to construct gene co-expression networks that were further probed to elucidate species-specific regulation of secondary metabolism. As an initial refinement step, genes with excessive missing values and sample outliers were excluded to reduce the noise, leaving behind most informative genes , and genes with low variance (≤ 30%) were excluded. Variance among samples was computed as follows:n1 and n2 are number of observations, and SD1 and SD2 are standard deviation of R. serpentina, and C. roseus datasets, respectively.Two sample t-test was implemented again to select significant genes  adjusted p-value   was performed to determine overall expression patterns between both datasets.The v 3.0.1. After initial data pre-processing, expression values of significant DEGs were used to construct two independent signed networks (networks that preserve the sign of correlations among expression profiles) for both datasets. For each weighted network, Pearson correlation matrices (corresponding to gene expression dataset) were computed, which were further transformed into matrices of connection strengths using a power function (β) that fits best to its scale-free behavior  library  is described as follows:aij is network adjacency.In order to reduce the complexity of whole networks comparison, clustering was performed independently that led to generation of distinct set of grouped genes with similar functional characteristics. Dissimilarity matrices were generated from corresponding TOMs to identify modules through average linkage hierarchical clustering by applying dynamic tree cut algorithm , betweenness centrality (BC), closeness centrality (CC), and eigenvector centrality (EC), were computed to identify central nodes. Further, a certain fraction (ρ) of nodes were removed in decreasing order of centrality, with uniform random removal of nodes as a control, to examine variations in size of the largest component [σ(ρ)]. The change in σ as a function of ρ was used to determine robustness of networks in response to node deletion in the form of R-index (R)  is fraction of nodes in the largest connected cluster. The normalization factor 1∕N allows comparison of robustness of networks with different sizes , a value complementary to R-index (R), as follows:During this analysis, co-expression networks were treated as unweighted in order to reduce computation complexity while determining their robustness. Additionally, vulnerability of networks to a given scheme of vertex removal was quantified by computing V-index , respectively.Co-expression networks were compared using a composite index by combining V-indices of each of the centrality measures. The idea is to define a composite http://bioinfo.cau.edu.cn/agriGO/)  was implemented to obtained statistically significant terms. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of significant modules were performed using a web-based program, Database for Annotation, Visualization and Integrated Discovery (DAVID) v 6.7  algorithm of agriGO web based tool (R. serpentina) were mapped on the test network (C. roseus). Module preservation was also quantified in terms of significant overlap in genes, using overlapTable function  for module assignments of these datasets were calculated. Further, on the basis of intramodular connectivity (Ki) for each module pair, genes were compared to determine hubs that illustrate gene centrality in a given module. Genes with high Ki in each of the modules from reference plant, and their corresponding module from test plant, were characterized as hubs  were considered. Ki represents normalized connectivity of gene and was computed using following equation:ki and kmax is connectivity and maximal connectivity of the gene i, respectively.To assess the module perseveration (on module-by-module basis) between these closely related species, a permutation test protocol was implemented to calculate Z-summary score using modulePreservation function in the WGCNA library  using PMR metabolomic-transcriptomic co-analysis tool at a significant PCC threshold of 0.80 . Multiple testing corrections were performed to reduce the false positives during statistical validation. PCA was performed using all DEGs that reduces dimensionality of multivariate data while preserving most of variance for easy data perception and visualization  are primarily responsible for variations across various species that reflects in the form of differences in gene expression levels. These differences in expression level associated with the variations in regulatory mechanism which is manifested in speciation and adaptation  and C. roseus (6). Earlier studies support sufficiency of the number of samples for this expression data to identify new candidate genes using co-expression analysis  could be easily anticipated from gene dendrograms.Co-expression networks are generated on the basis of correlation patterns among various samples which facilitates the characterization of candidate genes involved in important biological processes  against reference network (R. serpentina), Z-summary score of modules preservation were in range from –0.95 to 6.69  against turquoise and blue modules of C. roseus, respectively. This significant overlap of genes strongly complemented by high preservation score highlights functional importance of turquoise module in Apocynaceae family and may represents a signature pathway , response to abiotic stimulus (GO:0009628), response to chemical stimulus (GO:0042221), response to inorganic substance (GO:0010035), response to temperature stimulus (GO:0009226), response to water deprivation (GO:0009414), response to stress (GO:0006950), photosynthesis (GO:0015979), photosynthesis, light reaction (GO:0019684), oxidation reduction (GO:0055114), metabolic process (GO:0008152), generation of precursor metabolites (GO:0006091), and cellular nitrogen compound metabolic process (GO:0034641). Turquoise module was also found to have high tissue-specific expression in leaves of R. serpentina (both young as well as mature leaves)  , porphyrin metabolic process (GO:0006778), tetrapyrrole metabolic process (GO:0033013), and pigment biosynthetic process (GO:0046148). The blue module was also represented with tissue-specific expression in both immature and mature leaves  Figure  and C. r) Figure . Tissue-s Figure : chlorops Figure . These se Figure  presentee Figure  and blueR. serpentina was found to have significant overlap of genes (>30%) with brown module of C. roseus , biological regulation (GO:0065007), localization (GO:0051179), establishment of localization (GO:0051234), transport (GO:0006810), macromolecule metabolism process (GO:0043170), biosynthetic process (GO:0009058), protein metabolic process (GO:0019538), cellular macromolecule metabolic process (GO:0044260), and cellular biosynthetic process (GO:0044249). In addition, the GO enrichment analysis also revealed important enriched terms such as macromolecular and protein biosynthetic processes, transport etc., indicative of preferential shift of active metabolism to cellular proliferation activities which are further involved in plant reproductive systems  with green module of C. roseus , response to abiotic stimulus (GO:0009628), response to chemical stimulus (GO:0042221), response to inorganic substance (GO:0010035), response to organic substance (GO:0010033), response to stress (GO:0006950), defense response (GO:0006952), response to carbohydrate stimulus (GO:0009743), response to chitin (GO:0010200), biological regulation (GO:0065007), regulation of biological process (GO:0050789), regulation of cellular process (GO:0050794), regulation of metabolic process (GO:0019222), nitrogen compound metabolic process (GO:0006807), regulation of nitrogen compound metabolic process (GO:0051171), regulation of cellular metabolic process (GO:0031323), regulation of primary metabolic process (GO:0080090), regulation of nucleobase, nucleoside, nucleotide, and nucleic acid metabolic process (GO:0019219), nucleobase, nucleoside, nucleotide, and nucleic acid metabolic process (GO:0006139), regulation of biosynthetic process (GO:0009889), biosynthetic process (GO:0009058), cellular biosynthetic process (GO:0044249), regulation of cellular biosynthetic process (GO:0031326), regulation of macromolecule metabolic process (GO:0060255), regulation of transcription (GO:0045449), RNA metabolic process (GO:0016070), regulation of macromolecule biosynthetic process (GO:0010556), macromolecule metabolic process (GO:0043170), cellular macromolecule metabolic process (GO:0044260), transcription (GO:0006350), cellular macromolecule biosynthetic process (GO:0034645), macromolecule biosynthetic process (GO:0009059), regulation of gene expression (GO:0010468), protein metabolic process (GO:0019538), cellular protein metabolic process (GO:0044267), gene expression (GO:0010467), macromolecule modification (GO:0043412), protein modification process (GO:0006464), and post-translational protein modification (GO:0043687). These enriched terms have been reported to be associated with synthesis of specialized secondary metabolites under various stimuli   Figure  were not) Figure . These p) Figure , augment) Figure  (Yao et ) Figure , complemR. serpentina in contrast to phenylpropanoid synthesis in C. roseus. These indole alkaloids are reported to be synthesized in roots of R. serpentina and flowers of C. roseus, which is further complemented by tissue-specific expression of these modules  that are possibly involved in synthesis of major indole alkaloids under various stresses in s Figure . These fDespite of significant sharing Figure , brown-gR. serpentina had 17 shared genes with green module of C. roseus  had significant difference in connectivity. These genes had higher intramodular connectivity (Ki) in C. roseus as compared to R. serpentina  is reported to be involved in stamen and petal development  may be responsible for differences in tissue-specific as well as species-specific metabolite synthesis between these medicinal plants as evident from data in Figure Brown module from us Table  at the tna Table , anthocyna Table , and repna Table . AT1G725R. serpentina and C. roseus, respectively, were found to have significant correlation with at least one metabolite reported in PMR. Out of 17 shared genes  were found to be associated with the synthesis of metabolites  known to be produced in aerial parts  Figure , these mes Table , 6 and 2R. serpentina and C. roseus, respectively, on gene-metabolite networks and further by extending these subgraphs to include first neighbors. Interestingly, the gene-metabolite network of R. serpentina was found to be more complex as compared to the network obtained from C. roseus  and two other genes  was identified to be responsible for tissue-specific as well as species-specific synthesis of metabolites. The network robustness of R. serpentina network as compared to that of C. roseus was also complemented by complexity of its gene-metabolite network which may have evolved due to its complex metabolic mechanisms. Our study presents a strategy for identification of key genes responsible for diversification of pathways between closely related species, and thereby for revealing their evolutionary relationship.This work comprises meta-data analysis of RNA sequencing data through identification of differentially expressed genes to compare closely related medicinal plants SP conceived the idea, designed and conducted the experiments, analyzed data and wrote the manuscript. GB and PA contributed to data analysis and interpretation as well as manuscript writing.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.