N = 1412) and a sample of university students (N = 377). Exploratory factor analysis indicated a five-factor structure including three previous subscales , an evaluative/critical factor, and a new positive/regulatory factor. Confirmatory factor analysis then replicated this structure in sample 2. Hierarchical regression analyses also replicated a number of relations between inner speech, hallucination-proneness, anxiety, depression, self-esteem, and dissociation.Inner speech is a common experience for many but hard to measure empirically. The Varieties of Inner Speech Questionnaire (VISQ) has been used to link everyday phenomenology of inner speech – such as inner dialogue – to various psychopathological traits. However, positive and supportive aspects of inner speech have not always been captured. This study presents a revised version of the scale – the VISQ-R – based on factor analyses in two large samples: respondents to a survey on inner speech and reading ( While many people will report frequent inner speech , operationalizing inner speech as a measurable process is extremely challenging, with some doubting that it is even possible . It is, Inner speech has been extensively studied as a cognitive process in research on executive functioning in children and adults, and has been linked to verbal working memory , evaluative/motivational inner speech, other people in inner speech, and condensation of inner speech (i.e. abbreviation of sentences in which meaning is retained). In its initial development with university students, the VISQ demonstrated good internal and test-retest reliability, and significant relations with self-reported rates of anxiety, depression, and proneness to auditory but not visual hallucinations  may have neglected other aspects of inner speech phenomenology, such as use of metaphorical language, speaker position, and feelings of passivity. For example, Here we present a revised edition of the VISQ with the aim of addressing some of these concerns and expanding the phenomenological scope of the measure. First, an extended 35-item version of the scale was trialled as part of a larger study on reading imagery , social media and publicity at the Edinburgh International Book Festival. The participants that responded to at least 80% of the new VISQ items were included in the analysis . Responses primarily came from English-speaking countries  were recruited from university settings. The study was advertised through a departmental participant pool. Ethical approval was given by a university research ethics committee. Participants received course credit or gift vouchers for their participation. Surveys for both sample 1 and sample 2 were delivered on the Bristol Online Survey platform.377 participants , aged 18–56 , plus members of the research team with expertise in phenomenology, analytic philosophy, and cognitive science (BAD & SW). A large set of items were initially generated (>50) in response to the aims of the scale, and then these were refined down to a manageable number for exploratory testing.Phenomenological properties of inner speech were evaluated with the 35-item Varieties of Inner Speech Questionnaire – Revised (VISQ-R). In addition to the original 18 items on α > .80) and moderate to high test–retest reliability (>.60). See Responses were made on a seven-item frequency scale where respondents evaluated how frequently the inner speech experiences occurred, ranging from “Never” (1) to “All the time” (7). This differed from the original 6-point rating scale based on agreement with statements (e.g. “Certainly applies to me”), in an attempt to be more precise about how often such experiences occur cf. . Each su2.2.2This scale included nine items used by 2.2.3Levels of anxiety and depression were assessed with the 14-item Hospital Anxiety and Depression Scale HADS; . This sc2.2.4Frequency of dissociative experiences was measured with the 28-item self-report Dissociative Experiences Scale. Participants are asked to indicate what percentage of the time they experience dissociative states, such as feelings of derealisation or absorption (e.g. “Some people sometimes have the experience of feeling that their body does not belong to them”). Answers can range from 0% to 100%. The original DES has a mean internal reliability of .93 .2.2.5The 10-item Rosenberg Self-Esteem Scale includes five positive and five negative statements on self-concept and social rank . Responses are made on a four-point scale ranging from “Strongly agree” to “Strongly disagree”. The scale has been shown to have high test–retest and internal reliability e.g. .2.3All data were analysed in SPSS 20, with the exception of the confirmatory factor analysis (which was conducted using AMOS 22) and the mediation analysis (for which we used the “medmod” package in jamovi (Version 0.9). Relations between variables were assessed using Pearson’s product correlation co-efficient tests and hierarchical linear regression. Alpha values for correlations were Bonferroni corrected to account for multiple comparisons.33.1Missing data constituted less than 1% of total responses for the extended VISQ and were replaced by mean values. Exploratory factor analysis (EFA) was performed using Principal Component Analysis (PCA) with oblique rotation (direct oblimin), allowing for inter-correlation of the VISQ factors. Items were removed based on communalities under 0.4 or if they failed to load >0.5 onto a single factor . For allThe initial solution returned by the analysis produced 8 factors with eigenvalues over 1 (68% of variance explained). However, items 24, 26, 29, and 33 had either low communalities or low factor loadings, and these were subsequently removed from the analysis. The following model identified 7 factors with eigenvalues over 1 and accounted for a greater amount of variance (72%) but this included one factor with only one item (item 23). Inspection of the scree plot suggested five main factors with eigenvalues over 2, with two more factors barely above 1. Forcing a five-factor solution (62% variance explained) led to five items not loading on a single factor  of which three also failed the communalities test .2X (325) = 23773.10, p < .001). The five factors, displayed in evaluative/critical factor  and a new, 4-item positive/regulatory factor . As for the previous VISQ, internal reliability of each factor was excellent . With a total of nine items removed, a stable model was found with five factors (68.43% of variance explained), with all items loading on at least one factor over 0.5 and with all communalities > 0.4 . Frequency of responses for each item  are displayed in 2 value, χ2 (2 6 0) = 562.53, p < 0.001, but acceptable CMIN/DF ratio of 2.16. Fit statistics for the model were also in a satisfactory/good range: CFI = 0.925, RMSEA = 0.056 (90% C.I = 0.048–0.062), Hoelter index = 200.This resulted in a stable model with a significant χ3.3evaluative inner speech dimension, followed by dialogic, condensed and positive inner speech. The lowest mean scores were recorded for other people in inner speech. Reliability for dialogic, evaluative and other people in inner speech was high (α > 0.8) but lower for positive inner speech (α = 0.6). Cronbach’s α was also found to be adequate for visual hallucination-proneness, HADS anxiety, HADS depression RSES and DES (α > 0.7), but on the boundary of acceptability (0.67) for auditory hallucination-proneness.Using sample 2, we then attempted to replicate our previous findings using the new VISQ-R. evaluative, dialogic and other people in inner speech, and visual hallucination-proneness. A similar pattern was observed for visual hallucination-proneness. Evaluative and other people in inner speech also correlated positively with HADS Anxiety scores, HADS Depression scores, and lower self-esteem. Frequency of dissociative experiences (DES) was positively correlated with dialogic and other people in inner speech. For exploratory purposes, we also compared male and female participants’ scores on the new VISQ-R factors using independent samples t-tests: the only difference observed was for evaluative/critical inner speech (t (372) = −2.84, p = 0.005), with female participants  scoring higher than male participants .3.3.1F  = 21.05, p < 0.001) and Block 2  = 12.47, p < 0.001) significantly predicted auditory hallucination-proneness. In Block 1 (2R = 0.22), only visual hallucination-proneness was found to be a significant predictor of auditory hallucination-proneness . In Block 2  = 3.26, p = 0.007), visual hallucination-proneness, β = 0.42, p < 0.001, and other people in inner speech, β = 0.13, p = 0.005, significantly predicted auditory hallucination-proneness.A hierarchical multiple linear regression was performed to assess unique contributions of the five dimensions of inner speech (VISQ-R), depression and anxiety (HADS) in predicting auditory hallucination-proneness. Age, gender, depression, anxiety and proneness to visual hallucinations were entered in the first step, and five subscales of the VISQ-R in a second step, with auditory hallucination-proneness (LSHS Auditory) as a dependent variable. Measures of multicollinearity were in an acceptable range. Both Block 1  = 41.55, p < 0.001) and Block 2  = 21.51, p < 0.001) were significant, but importantly only auditory hallucination-proneness, β = 0.36, p < 0.001, and depression, β = 0.32, p < 0.001, were observed to significantly predict visual hallucinations in the final model: all of the VISQ-R factors were non-significant (p > 0.11). Therefore inner speech characteristics appeared to be relevant to predicting auditory hallucination-proneness specifically.To test for the specificity of this relationship, we then reran the above analysis with visual hallucination-proneness as the dependent variable and auditory hallucination-proneness as a predictor variable in Block 1. Both Block 1 (3.3.2p > 0.05). The addition of the five dimensions of VISQ-R in Block 2 made a significant change to the model  = 8.16, p < 0.001), where other people in inner speech, β = 0.21, p < 0.001, and evaluative inner speech, β = 0.13, p = 0.023, both significantly predicted auditory hallucination-proneness  = 6.077, p < 0.001). The addition of the self-esteem measure (RES) to Block 3 did not make a significant change to the model , and self-esteem did not significantly predict hallucination-proneness (p > 0.05). The addition of dissociation scale (DES) scores to Block 4 resulted in a significant change to the model  = 83.88, p < 0.001), with dissociation found to significantly predict auditory hallucination-proneness, β = 0.44, p < 0.001, as well as other people in inner speech, β = 0.17, p < 0.001  = 15.281, p < 0.001).A multiple regression was performed to assess the contribution of different types of inner speech (VISQ-R), self-esteem (RSES) and dissociative tendencies (DES). Age and Gender were entered in the first step, followed by the five subscales of VISQ-R in the second step. Self-esteem (RSES) was entered in the third block, and dissociative tendencies (DES) in the fourth block. The first model with age and gender as predictors of auditory hallucination-proneness was not significant  and indirect  paths, with the latter accounting for 27.9% of the total effect. This suggested that dissociation partially (rather than fully) mediated the effect of other people in inner speech on hallucination-proneness, and that most of this effect was in fact direct.As in 3.3.3other people subscale. When this was done for the present data, the analysis showed the same results as the regression model 1 , and visual hallucinations  and other people in inner speech significantly predicted auditory hallucinations in the second block . The analysis also showed the same results as in regression model 2  and other people in inner speech  were found to be significant predictors of auditory hallucination-proneness. The addition of self-esteem scores did not make a significant change to the model (p > 0.05). In Block 4, both dissociation scores  and other people in inner speech were found to be significant predictors of auditory hallucination-proneness .Finally, we reran our main analysis accounting for some potential confounds in the data. One concern with the original VISQ is the inclusion of items that refer to experiencing “actual voices” of other people in their inner speech, which may be thought to index similar experiences as the auditory items of the LSHS. To address this,  1 i.e., , in thatl 2 i.e. , where bn = 297) showed the same results as reported in regression model 1, in that visual hallucination-proneness  and other people in inner speech  were significant predictors of auditory hallucination-proneness in the final model. Similarly, for regression model 2, other people in inner speech  and dissociation scores in  were significant predictors of auditory hallucination-proneness in the final model. Identical results were observed when the analyses were rerun only in people without a psychiatric diagnosis.Other factors which may have affected our data include the presence of non-native speakers and people with a self-declared psychiatric diagnosis. To address these, we reran our main analyses of sample 2 first excluding non-native English speakers, and second excluding those with a psychiatric diagnosis. For the former, the results for the native speakers group (n = 43) and without a psychiatric diagnosis (n = 326) on the five subscales of the VISQ-R (8 participants preferred not to report their diagnostic status). The independent-sample t-tests showed that there was a significant difference in the level of reported dialogic inner speech between the two groups (t (367) = 2.08, p = 0.038), with the sample with psychiatric diagnoses reporting higher levels of dialogic inner speech . A similar pattern was evident for evaluative inner speech (t (367) = 5.43, p < 0.001), with lower scores in the sample without a diagnosis . No group differences were found in levels of condensed, positive and other people in inner speech (p > 0.05).Finally, we compared those with . The inter-correlations of evaluative and positive subscales in sample 1 (r = 0.40) and sample 2 (r = 0.29) also highlight that these are related but ultimately separable factors, rather than positive and negative poles of the same scale.Compared to the original scale, the VISQ-R captures a broader range of phenomenology associated with the experience of self-directed speech, in line with the primary aim of the study. In particular, new items relating to positive and negative states of inner speech, including the use of inner speech to regulate mood, survived the various stages of scale development. The inclusion of these new items appears to have elaborated the concept of evaluative inner speech captured in the original VISQ . EvaluatA secondary aim for the new scale was to capture the potential for inner speech to have positive psychological effects, as this is important for drawing together disparate strands of research on self-directed speech. In sports psychology and similar fields, self-talk has often been associated with improved focus and performance . HoweverThe cognitive benefits of positive/regulatory inner speech may also be evidenced in the spheres of creativity and imagination. To give one example, the presence of an imaginary companion in childhood has been linked to greater levels of self-talk in general in childhood  and aduldialogic factor predicted auditory hallucination-proneness more strongly than other factors in the original study, in the present study only other people in inner speech did so. It seems unlikely that this is due to the new scale structure: with the original VISQ, pairwise correlations between dialogic inner speech and hallucination-proneness were often evident ; dissociation appeared to mediate this relationship (hypothesis 2); and a subset of inner speech characteristics also correlated with scores for anxiety, depression, and self-esteem  raises the risk of measurement overlap. We have taken steps to address this issue: for example, by showing that the relation between other people in inner speech and auditory hallucination-proneness remains even when potentially overlapping items are removed, concerns about direct conceptual overlap are to some degree minimised. Moreover, we have endeavoured to design VISQ-R items that focus on the form and phenomenology of inner speech, rather than its contents (to avoid confounding the content of a thought or mood and its structure). Nevertheless, ideally such issues would be explored more extensively in a procedure that would enable clarification and disambiguation, such as a one-to-one interview. This would seem to be particularly important when dealing with patients who may struggle to report on their own inner experience .Guardian newspaper  in those who are blind or deaf is still meagre (for exceptions, see In conclusion, inner speech has been proposed as a key tool for unlocking creative, exploratory, and abstract thought. Our results, with the revision of the VISQ, provide new avenues for probing these relationships while continuing to explore the important connections between the phenomenology of self-talk and psychopathology. By expanding the horizons of inner speech, and picking up a greater range of experiences, a richer narrative will be available to turn


In addition, moderate and/or high PA increased the odds for higher life satisfaction , greater happiness  and better perceived health . Programmes that reduce SB and increase PA may promote life satisfaction, happiness and perceived health status in this university student population.The aim of this investigation was to estimate the independent and combined associations of sedentary behaviour (SB) and physical activity (PA) with life satisfaction, happiness and perceived health in university students. In a cross-sectional survey, 12,492 university students  from 24 countries responded to a questionnaire on SB, PA and well-being indicators. In adjusted linear regression, higher SB (4 to <8 h and ≥8 h) was associated with poorer life satisfaction ( In a systematic review, evidence was found for an association between sedentary behaviour (SB), physical inactivity and various forms of morbidity, including depression and anxiety, and also mortality ,2. Less Few studies among different age groups, predominantly in countries with high income, found a negative association between SB and a positive association between PA and life satisfaction, happiness and perceived health. For example, among university students in Ireland, PA was associated with happiness and better perceived health . Among uAmong European adults from 15 countries, higher PA levels were in a positive dose-response relationship associated with greater happiness . Among oA cross-sectionally administered survey included 12,492 university students  with complete sedentary and physical activity measurements from 24 low- and middle-income countries . Methodological procedures have been described previously [SB and PA were assessed with the “International Physical Activity Questionnaire (IPAQ) short form” [rt form” . SB was rt form” , and PA rt form” .Life satisfaction was assessed with the question, “All things considered, how satisfied are you with your life as a whole?” Responses ranged from 1 = very satisfied to 5 = very dissatisfied and were reverse scored so that higher scores represent greater life satisfaction .Happiness was assessed with a four-item Subjective Happiness Scale (SHS) , with hiPerceived health status was measured with one item, “In general, would you say that your health is … 1 = excellent, 2 = very good, 3 = good, 4 = fair or 5 = poor?” . ResponsSocio-demographic items included age, sex, country income and subjective wealth status.Social support was sourced from three questions of the Social Support Questionnaire  ?” (“yes” or “no”) . Binge alcohol use (past month) was measured with the item, “How often do you have (for men) five or more and (for women) four or more drinks on one occasion?” . Body mass index (BMI) was assessed “with standard anthropometric measurements” .p < 0.05 was considered significant. Statistical analysis was performed with STATA software version 14.0 . Parametric statistical procedures were used to show differences in proportions. Multivariable linear regression was used to calculate coefficient estimates and confidence intervals of associations of SB and PA with life satisfaction, happiness and perceived health status. In addition, linear regression was used to estimate the combined relationship of SB and PA with life satisfaction, happiness and perceived health status. Multivariable models were adjusted for relevant confounders, including sex, wealth status, country, social support, tobacco use, binge drinking and body mass index. For the combined linear regression analysis, “the sample was sub-divided based on sedentary and physical activity levels into four groups: (1) high sedentary time (≥8 h) plus low physical activity group (reference category), (2) high sedentary time (≥8 h) plus moderate or high physical activity group, (3) low or moderate sedentary time (<8 h) plus low physical activity group, and (4) low or moderate sedentary time (<8 h) plus moderate or high physical activity group” . MissingStudy participants engaged in <4 h (23.5%), 4 to <8 h (42.5%) and ≥8 h (34.0%) SB per day. The PA levels of the participants were as follows: 42.2% low, 36.5% moderate and 21.2% high PA. The mean life satisfaction was 3.14 (range 1–5), happiness 13.08 (range 4–20) and self-rated health status 2.98 (range 1–5). Older students had lower life satisfaction and self-rated health scores than younger students. Happiness scores were higher in students with higher wealth status, living in a country with higher income (middle-income country) see .In the final adjusted linear regression model, higher SB (4 to <8 h and ≥8 h) was associated with lower life satisfaction and lower happiness, while higher SB (≥8 h) was associated with lower perceived health, and moderate SB (4 to <8 h) was associated with higher perceived health. In addition, moderate and/or high PA was associated with higher life satisfaction, greater happiness and better perceived health see . Compared to participants with high SB (≥8 h) and low PA, students who had less than 8 h SB and engaged in moderate or high PA had a significantly greater life satisfaction and better perceived health status, after adjusting for relevant confounders. In unadjusted analysis, students who engaged <8 h in SB and in moderate or high PA had greater happiness see . Analysis of survey data from a large sample of undergraduate university students from 24 low- and middle-income countries showed a significant independent association between higher SB and moderate and/or high PA with higher life satisfaction, happiness and perceived health. These associations remained statistically significant after controlling for relevant confounders. These findings are consisted with results from studies among university students and other populations in high-income countries ,4,5,8. OFinally, the findings seem to confirm previous results from studies of university students in the USA , adolescSince this was a cross-sectional investigation, we cannot draw causal conclusions. Results from this study only included university students and cannot be generalised to the general population. In this study, SB and PA were assessed by self-reporting. In the future, objective measures should also be included. The assessment of two of the outcome variables, life satisfaction and perceived health status, were only assessed with single items, and future studies may include more comprehensive measures. The current study showed an independent association of low SB and moderate or high PA with life satisfaction, happiness and perceived health status, in addition to a combined association of low SB and moderate or high PA with life satisfaction and perceived health status. Reducing SB and increasing PA may promote life satisfaction, happiness and perceived health status in this university student population.


The intestinal epithelium constitutes an indispensable single-layered barrier to protect the body from invading pathogens, antigens or toxins. At the same time, beneficial nutrients and water have to be absorbed by the epithelium. To prevent development of intestinal inflammation or tumour formation, intestinal homeostasis has to be tightly controlled and therefore a strict balance between cell death and proliferation has to be maintained. The proinflammatory cytokine tumour necrosis factor alpha (TNFα) was shown to play a striking role for the regulation of this balance in the gut. Depending on the cellular conditions, on the one hand TNFα is able to mediate cell survival by activating NFκB signalling. On the other hand, TNFα might trigger cell death, in particular caspase-dependent apoptosis but also caspase-independent programmed necrosis. By regulating these cell death and survival mechanisms, TNFα exerts a variety of beneficial functions in the intestine. However, TNFα signalling is also supposed to play a critical role for the pathogenesis of inflammatory bowel disease (IBD), infectious diseases, intestinal wound healing and tumour formation. Here we review the literature about the physiological and pathophysiological role of TNFα signalling for the maintenance of intestinal homeostasis and the benefits and difficulties of anti-TNFα treatment during IBD. The Tumour Necrosis Factor (TNF) Superfamily is composed of 19 ligands and 29 receptors . In geneThe TNFα protein is produced by many different cell types in the human body, however the main producers are the cells from the monocytic lineage, for example, macrophages . TNFα plThe TNFα protein is generated as a bioactive, 26 kDa transmembrane type 2 polypeptide precursor (mTNFα) . CleavagA1/Bfl1, LBcl-X, cIAP or xIAP, which exert antiapoptotic functions . TN. TN26]. unctions ,39,40. Tpression . Besidespression .In addition to mediating cell survival and proliferation, TNFα is also described to be an important regulator of cell death . DependiInterestingly, in 1988, Laster and colleagues observed that stimulation of certain cell types with TNFα does not only induce apoptotic cell death but also necrotic cell death, which is characterized by the lack of nuclear disintegration, the formation of a balloon-like plasma membrane and finally cell lysis . SubsequBesides TNFR1-mediated regulation of cell death and survival, TNFα can also signal via TNFR2. This receptor, in contrast to TNFR1, does not contain any intracellular death receptor domain. However, under certain conditions, binding of TNFα to TNFR2 was also shown to induce NFκB signalling, which in this case is mediated by recruitment of TRAF2 and subsequently TRAF1, as well as cIAP1 and 2 to TNFR2 ,67,68,69In summary, these studies underline that TNFα is a powerful pleiotropic cytokine which is able to regulate NFκB-mediated cell survival but also caspase-dependent and independent cell death via two different receptors and various pathways and protein complexes.The gastrointestinal tract is the biggest surface of the body with close contact to environmental factors. The intestine is lined with a single epithelial cell layer which separates the underlying tissue from the luminal contents. The intestinal lumen contains the microflora, consisting of fungi, viruses and bacteria, as well as nutrients, water and environmental toxins. The intestinal epithelial cell layer is characterized by an enormous self-renewing capacity (every 4-5 days), underlined by a tremendous turnover rate of the epithelial cells. In order to maintain the epithelial barrier, intestinal stem cells at the crypt bottom divide asymmetrically and give rise to new stem cells, as well as new daughter cells, which differentiate towards cells of the secretory and absorptive lineage along the crypt-villus axis. At the villus tips in the small intestine, differentiated epithelial cells are shed in the intestinal lumen. Only the secretory Paneth cells escape this migration towards the villus tip. Interestingly, they fully differentiate, remain at the crypts of Lieberkühn and survive for more than 3 weeks . A stricdeltaARETNF mice) are characterized by spontaneous development of Crohn’s like inflammation in the small intestine [-/-IL10 or ΔIECCasp8 mouse models, are characterized by increased TNFα levels in the intestinal mucosa [Tnfa expression in the gut in a mouse model of chronic intestinal inflammation mediated by a single viral protein [Tnfa gene were no longer susceptible to acute or chronic TNBS-induced colitis [Tnfa were more susceptible to chronic TNBS-induced colitis [Tnfa knockout, aggravated DSS- induced colitis in acute models [Tnfa gene expression was not increased in colon samples as compared to controls. However, therapeutic administration of TNFα reduced colitis and histopathology [TNFα is mainly described as a proinflammatory cytokine which plays a critical role for maintaining the intestinal integrity but conversely also for the pathogenesis of intestinal inflammation. In the gut, beside immune cells, also intestinal epithelial cells, namely Paneth cells, have been shown to produce TNFα constitutively in mice as well as during inflammation in patients suffering from chronic inflammation ,80. Morentestine . Additiol mucosa ,88,89,90 protein . Interese models ,93. Conve models , implicaathology , TNFα miathology , TNFα miUnder steady state conditions, during renewal of the intestinal epithelium, epithelial cells are shed into the lumen at the villus tip. Historically, intestinal cell shedding was considered to be a rather passive effect, where aged epithelial cells simply fall off the villus tip ,96. HoweΔIECCasp8) were characterized by spontaneous development of ileitis accompanied by necroptotic RIP-dependent epithelial cell death and increased Tnfa gene expression, features which are also seen in patients suffering from Crohn’s disease. This spontaneous phenotype was dramatically worsened after additional TNFα administration in this model [ΔIECCasp8 mice, which was shown by the fact that additional deletion of TNFR1 in this model did not protect the animals from spontaneous inflammation and cell death [Tnf knockout could ameliorate but not completely abolish intestinal pathology in the colon, again suggesting that TNFα might contribute to development of intestinal inflammation. However, being in line with the study mentioned above, TNFα was not the main driver of inflammation and epithelial cell death in the small intestine [Interestingly, in the gut it was shown that besides apoptosis, TNFα is also able to trigger caspase-independent necroptosis. Mice lacking caspase-8 in IECs  are known to induce diarrhoea and gastrointestinal disease worldwide especially in children [Citrobacter rodentium infection model. Interestingly, during C. rodentium infection in mice, TNFα is increased in the gut, however the absence of TNFα signalling due to Tnfr knockout in this model did not protect animals from infectious colitis. In contrast, the mice were even more susceptible to infectious colitis [C. rodentium infection. Beside C. rodentium, also Salmonella enterica is a frequent cause of gastrointestinal infections in humans and animals worldwide every year. Salmonella Typhimurium infections lead to development of intestinal inflammation accompanied by diarrhoea, abdominal pain and vomiting [S. Typhimurium ex vivo induced increased Tnfa gene expression levels. Moreover blocking of TNFα by administration of anti-TNFα antibodies prior to S. Typhimurium infection reduced gastrointestinal pathology, suggesting a rather harmful function of TNFα in the early phase of Salmonella infection [S. Typhimurium induced colitis after streptomycin treatment, intestinal inflammation was also accompanied by increased levels of TNFα [Clostridium difficile. C. difficile induced intestinal pathology ranges from mild diarrhoea to severe colitis [C. difficile infection were characterized by elevated TNFα plasma and serum levels as compared to healthy controls [C. difficile also led to increased Tnfa gene expression in the colon of infected mice [C. difficile toxins [C. difficile infection, enhanced TNFα levels might be beneficial, since treatment of mice with anti-TNFα antibody shortly before C. difficile infection increased the inflammatory response and colonic histopathology [Enteropathogenic and enterohemorrhagic children . One mod colitis , suggestvomiting . Interesnfection . Interes of TNFα ,135. Ano colitis . Interescontrols ,138. In ted mice . Moreovee toxins ,141. Intathology .Beside bacteria, also viruses mediate gastrointestinal pathology. for example Rotavirus is known to induce gastroenteritis worldwide, especially in children younger than 5 years . RotavirTnfr1 knockout [S. Typhimurium infected ΔIECCasp8 mice were characterized by reduced survival and an exacerbated course of infection as compared to controls and additional knockout of TNFR1 improved survival of infected mice [As a response to infection, the host might activate cell death programs to limit further pathogen spreading. Many pathogens also evolutionary counteracted this induction of host cell death by expressing apoptosis inhibitors ,150. As knockout , suggestted mice .-/- mice, which had a mutated TNFα that could not be cleaved into sTNFα [CD and UC represent the major entities of IBD, which are defined as relapsing disorders of the gastrointestinal tract that are pathologically characterized by mucosal inflammation and epithelial damage not due to identifiable pathogens . The clito sTNFα . Furtherto sTNFα . Fittingto sTNFα  and the to sTNFα .Several data in recent years have shown that expression of the target molecule in the inflamed tissue may affect response to anti-TNFα therapy in IBD. Our own studies have shown that anti-TNFα agents may bind to mTNFα expressing macrophages, thereby inducing apoptosis in TNFR2 expressing mucosal T cells lacking mTNFα-dependent co-stimulation. The mTNFα/TNFR2 signalling pathway is thus a crucial regulator in mediating resistance to apoptosis in intestinal T cells and may contribute to disease chronicity . Indeed,Further understanding of the mechanism of action of anti-TNFα antibodies in IBD and the molecular resistance pathways that lead to non-response to TNFα inhibition will provide rational prediction of response, alternative molecular targets in no-responders and altogether a better therapeutic utilization of this substance class.Taken together, the proinflammatory cytokine TNFα plays a fundamental role for the maintenance of intestinal homeostasis. It is believed to exert pivotal functions during physiological and pathophysiological conditions in the gut. Regulation of TNFα levels via anti-TNFα treatment is already an important therapeutic option for patients suffering from IBD. However, besides inflammation, several studies implicate a role of TNFα signalling during tumour development and also infectious diseases, therefore anti-TNFα treatment might be a starting point for additional therapeutic strategies to cure intestinal diseases.


Obesity—with its increased risk of obesity-associated metabolic diseases—has become one of the greatest public health epidemics of the twenty-first century in affluent countries. To date, there are no ideal drugs for treating obesity. Studies have shown that activation of brown adipose tissue (BAT) can promote energy consumption and inhibit obesity, which makes browning of white adipose tissue (WAT) a potential therapeutic target for obesity. Our objective was to identify genes and molecular pathways associated with WAT and the activation of BAT to WAT browning, by using publicly available data and computational tools; this knowledge might help in targeting relevant signaling pathways for treating obesity and other related metabolic diseases.In this study, we used text mining to find out genes related to brown fat and white fat browning. Combined with biological process and pathway analysis in GeneCodis and protein-protein interaction analysis by using STRING and Cytoscape, a list of high priority target genes was developed. The Human Protein Atlas was used to analyze protein expression. Candidate drugs were derived on the basis of the drug-gene interaction analysis of the final genes. Our study identified 18 genes representing 6 different pathways, targetable by a total of 33 drugs as possible drug treatments. The final list included 18 peroxisome proliferator-activated receptor gamma (PPAR-γ) agonists, 4 beta 3 adrenoceptor (β3-AR) agonists, 1 insulin sensitizer, 3 insulins, 6 lipase clearing factor stimulants and other drugs.Drug discovery using in silico text mining, pathway, and protein-protein interaction analysis tools may be a method of exploring drugs targeting the activation of brown fat or white fat browning, which provides a basis for the development of novel targeted therapies as potential treatments for obesity and related metabolic diseases. Obesity is a global public health issue . ExcessiFor a condition as dangerous as obesity, obesity is a dangerous condition and surprisingly, we know a little about its causes and its prevention. In recent years, the gradual in-depth understanding of the adipose tissue differentiation mechanism has provided new therapeutic targets for the development of obesity treatment. Adipose tissues, which are mainly composed of white adipose tissue (WAT), beige fat, and brown adipose tissue (BAT), are important in energy storage and regulation. WAT is the largest energy reservoir in the body, mainly storing energy in the form of triacylglycerol (TG) and release free fatty acids (FAs) in the fasting state for the maintenance of the metabolism and the other activities of the body. Compared with white adipocytes, fat in brown adipocytes usually store TG in the form of small fat droplets, while in white adipocytes, it is stored as large fat droplets. In addition, brown adipocytes are rich in mitochondria, the content of which far exceeds that of white adipocytes. In addition, there is a unique uncoupling protein 1 (UCP1) present on the mitochondrial inner membrane. A large number of protons in the intermembrane space are transferred into the mitochondrial matrix, which uncouples oxidative phosphorylation, thereby reducing mitochondrial membrane potential, increasing mitochondrial electron transport rate, and ultimately leading to heat production and consumption of large amounts of chemical energy .Previously, human BAT was thought to exist only in newborns and regress with increasing age and become less related to metabolism in adults. However, several independent research teams confirmed their presence and function in the human body through the technology of positron emission tomography-computed tomography (PET-CT) . This leWhile the existing drug efficacy is limited and the traditional approach to new drug discovery is time-consuming and costly, drug repositioning, which refers to the identification of new indications from existing drugs and the newly identified drugs, may serve as a new way to treat diseases more effectively and less expensive . This stP value (P = 1.00e−07) as the cutoff, because a P value cutoff (P = 1.00e−08) would exclude biological processes which contribute significantly to the process of brown-fat-like development, such as “cellular lipid metabolic process”, while the selection of P value (P = 1.00e−06) would include biological processes irrelevant to the process of brown-fat-like development, which would affect the precision and accuracy of the results. Therefore, to ensure that only the most enriched biological processes relevant to brown-fat-like development were selected, a P value (P = 1.00e−07) was chosen as the cutoff, which resulted in 16 sets of annotations containing 70 genes (Table P = 8.31e−21), (2) “response to cold” (P = 7.85e−16), and (3) “positive regulation of transcription from RNA polymerase II promoter” (P = 2.92e−12), including 12, 10, and 20 genes, respectively, among which the lower P value indicates that the biological process is more relevant to brown-fat-like development. Other highly enriched biological process annotations included “lipid biosynthetic process”, “cellular lipid metabolic process”, “glucose homeostasis”, and “response to insulin stimulus”. In the analysis of enriched KEGG pathway annotations, the P value cutoff was set to P = 1.00e−06, which resulted in 28 genes in six pathways above the cutoff (Table P = 1.28e−14), (2) “adipocytokine signaling pathway” (P = 3.87e−13), (3) “pathways in cancer” (P = 1.10e−09), (4) “insulin signaling pathway” (P = 4.39e−09), (5) “prostate cancer” (P = 1.89e−07), and (6) “type II diabetes mellitus” (P = 2.15e−07).According to the data mining strategy described in Fig. alue P = .00e−07 aFADS2, was found isolated from other nodes, which means there is no interaction between FADS2 and other genes. The visualization of the network of 27 genes yielded from STRING was demonstrated in Cytoscape , ADRB3 (adrenoceptor beta 3), and CEBPB (CCAAT/enhancer-binding protein beta). These proteins were positively expressed in adipose tissue Fig. .Fig. 5TPPARG”, “CREBBP”, “LEP”, “INS”, “ADIPOQ”, “LPL”, “FABP4”, “IL6”, “PIK3R1”, “MRAP”, “PPARGC1A”, “SLC2A4”, “ADIG”, “ADRB1”, “PRDM16”, “ADRB3”, “CEBPB”, and “UCP1”. Using these 18 genes as potential targets in drug-gene interaction analysis, a list of 622 drugs was initially obtained. After filtering those by the status of “launched”, “phase I/II/III clinical trial”, “pre-registration” or “registered”, a list of 158 drugs was selected. We took a close look at the details of each drug, especially the “Trialtrove Trials”, excluded those drugs that were not detailed in the development process, and got 81 drugs. Notably, considering the efficacy and safety of the drugs and their possible potential hazards to other systems, drugs including beta 1 adrenoceptor antagonists and agonists, interleukin-6 antagonists, and CREB-binding protein inhibitors were removed from the drug lists. Finally, a list of 33 drugs was selected as a possible drug treatment for brown-fat-like development. According to the therapeutic targets, including PPARG, ADRB1, ADRB3, SLC2A4, INS, and LPL, these drugs can be divided into PPAR-γ agonists, β3-AR agonists, insulin sensitizer, insulin, lipase clearing factor stimulant, and other drugs.Considering the fact that the most enriched biological process, “brown fat cell differentiation”, contributes significantly to the process of brown-fat-like development and the genes related to this process may serve as the potential targets, we supplemented the 12 genes from the query set of “brown fat cell differentiation” to the final list. After deleting the duplications, 18 genes made up the final list, including “ADRB3 are selected as possible therapeutic agents for the treatment of obesity, consistent with the biological process of “brown fat cell differentiation”. In physiological conditions, cold stimulation activates BAT by releasing adrenaline through sympathetic nerves, increasing the expression of genes involved in heat production and lipid metabolism, promoting the accumulation of beige fat [Among these drugs, four drugs targeting eige fat . Agonisteige fat . The otheige fat .Eighteen of the drugs in the final drug list were PPAR-γ agonists, which is in accordance with the most enriched pathway “PPAR signaling pathway”. Among these, several drugs belonging to the thiazolidinedione (TZD) class are used in the treatment of type 2 diabetes. Pioglitazone is used as an adjunct to diet, exercise, and other diabetes medications  to manage type 2 diabetes by stimulating the nuclear receptor PPAR-γ, promoting insulin sensitivity and improving the uptake of blood glucose , 19. OthLPL which is present in “PPAR signaling pathway”, “lipid metabolic process”, and “triglyceride biosynthetic process”. The activation of BAT and beige adipocytes is accompanied by a significant increase in intravascular LPL activity, driving FA into thermogenic adipocytes. Accordingly, the activation of BAT may lower plasma TG and obesity [INS and SLC2A4, respectively. Vanadium, a trace metal, plays a crucial role in maintaining blood glucose homeostasis possibly through its insulin-mimetic effects [Among the list, seven drugs work as lipase clearing factor stimulants targeting  obesity . Among t obesity , 31. Oth effects . Noticea effects , 34.Obesity is becoming one of the greatest public health epidemics in the twenty-first century, with approximately two billion adults worldwide currently classified as overweight or obese which is related to many metabolic diseases . HoweverBAT is a specialized tissue responsible for heat production, more specifically for adaptive non-shivering thermogenesis that corresponds to adaptation to cold environments or diet modifications . Cold exAgonist-mediated activation of β3-AR is considered as a targeted therapeutic strategy. Previous phase II clinical trials with β3-AR agonists demonstrated improved glucose tolerance, increased FA oxidation, and resting metabolic rate, but none of them eventually passed the trials and achieved the approval for the treatment of obesity –48. LimiPPARG, INS, PPARGC1A, PRDM16, ADRB3, CEBPB, and UCP1.When β3-AR/cAMP/PKA signaling is activated, the key downstream activation of p38 mitogen-activated protein kinase (MAPK) stimulates the activating transcription factor 2 (ATF-2), driving PGC1-α transcription . PGC1-α PPARs are a family of nuclear transcription factors that is very important in the regulation of energy metabolism, including lipids, adipogenesis, and glucose control. Among the three subtypes of PPARs, α, β/δ, and γ, PPAR-α is a major activator of FA oxidation pathways and is the target of the hypolipidemic fibrate drugs, expressed mainly in high-energy requiring tissues such as the skeletal muscles, liver, heart, and BAT, while PPAR-γ is predominantly expressed in WAT and BAT, where it is a major regulator of adipogenesis as well as a whole-body lipid metabolism and insulin sensitivity . ActivatFibrate drugs  are also potent activators of PPAR-α, which are used in hypercholesterolemia primarily due to their ability to substantially increase HDL levels and lower TG levels. In humans, the activation of PPAR-α by fibrate has shown to increase the circulating levels of antiatherosclerotic HDL-cholesterol that lowers TG levels, liberates FA and apolipoprotein CIII (apo-CIII), improves the overall atherogenic plasma lipid profile, and has beneficial effects on inflammation, insulin resistance, and metabolic syndrome. Fibrates also improve HDL and TG levels via induction of apo-AI, apo-AII, and apo-AV, respectively . As showUnexpectedly, one combination medication, metoprolol + tesofensine, is on our final drug list based on the drug-gene interaction, the former of which targets ADRB1. Tesofensine is a presynaptic reuptake inhibitor of serotonin, norepinephrine, and dopamine . AccordiThe limitations of this study stem from the databases we used and the criteria we set in each screening step. Thus, our analysis may have to be repeated when databases become more comprehensive. Additionally, different rational criteria could be set up to further explore the best outcome.In conclusion, we presented a method to explore potential drugs that target the pathways that are relevant to BAT or the browning of WAT to ameliorate obesity and associated comorbidities. Such methods may be used at intervals when databases and analytical tools evolve and improve. As a result, with the method presented, we identified a total of 33 potential drugs, including 18 PPAR-γ agonists, 4 β3-AR agonists, 1 insulin sensitizer, 3 insulins, 6 lipase clearing factor stimulants, and other drugs. Our list of candidate drugs participates and regulates the process of the activation of BAT or white fat browning through different pathways and mechanisms, which provides a basis for the development of novel targeted therapies as potential treatments for obesity and related metabolic diseases.Homo sapiens”. We selected “Ensembl Gene ID” and “Associated Gene Name” under GENE and deselected “MEDLINE: PubMed ID” under PUBMED2ENSEMBL FEATURES. “Search for PubMed IDs” and “filter on Entrez: PMID” drop-down menus were chosen in the search of every query. Then, the queries returned three lists of genes, the intersection of which was then used as the starting point for the next steps.Text mining is the process of deriving genomic data from published biomedical literatures. In this study, we used pubmed2ensembl  to perfoWe used GeneCodis  for an eHomo sapiens” as the organism. To screen the genes with a strong interaction, the confidence score was set to the highest score (0.900) in this study. Then the protein-protein interaction network of the target genes was obtained.The STRING  was usedTo further narrow the candidate gene field, we used the Cytoscape  software to analyze the interaction network. Cytoscape is a software platform for visualizing, analyzing, and interpreting biomedical interaction networks supported by diverse annotations, gene expression profiles, and experimental data . We impoThe Human Protein Atlas  is a frePharmaprojects  is an onAdditional file 1. Candidate drugs targeting genes associated with brown fat or white fat browning. (XLSX 24 kb)


Studies of changes in cerebral neocortical thickness often rely on small control samples for comparison with specific populations with abnormal visual systems. We present a normative dataset for FreeSurfer-derived cortical thickness across 25 human visual areas derived from 960 participants in the Human Connectome Project. Cortical thickness varies systematically across visual areas, in broad agreement with canonical visual system hierarchies in the dorsal and ventral pathways. In addition, cortical thickness estimates show consistent within-subject variability and reliability. Importantly, cortical thickness estimates in visual areas are well described by a normal distribution, making them amenable to direct statistical comparison. •Normative neocortical thickness values for human visual areas measured with FreeSurfer.•A gradient of increasing neocortical thickness with visual area hierarchy.•Consistent within- and between-subject variability in neocortical thickness across visual areas. The hetin vivo, indirect quantification has become possible through MRI methods, particularly surface-based cortical ribbon reconstruction  stands out for its unusually thin band of cortex in contrast to surrounding cortical territory. Cortical thickness may then serve as a marker segregating ‘lower’ sensory from ‘higher’ associative and integrative regions. In addition, abnormal cortical thickness has been reported in developmental disorders , congeniAn outstanding issue with these approaches is that measures of cortical thickness in clinical populations are typically compared against a matched control group of similar size, typically less than 20 participants . The HCP is a rich resource with high-resolution MRI and state of the art pre-processing routines optimized for obtaining anatomical metrics including cortical thickness. In addition to presenting normative values for 25 visual areas, we show that areas are discriminable based on cortical thickness with clusters along the dorsal and ventral pathways, that inter-subject variability in cortical thickness is stable across visual areas, and that within-subject variability is consistent both within and across visual areas. This resource, publicly available on 22.1Data were provided by the Human Connectome Project  S1200 reThe sample has a narrow age range (22–37 years), is gender balanced  and is drawn from a population with varied demographic, phenotypic and genotypic backgrounds, making it ideal as a baseline for a young adult population more broadly.2.20 field maps acquired at 2 mm isotropic resolution. Images were pre-processed to correct for distortions introduced by gradient non-linearities, remove readout distortions, correct for bias field distortions and align the images to the MNI space template , where each visually-responsive vertex is assigned membership to a single visual area  were extracted for each subject in 25 regions of interest covering human visual areas that display retinotopic organization. Visual areas were defined by their maximum intensity projection in the  atlas, aCorrelation analysis was conducted by taking an individual subject’s mean cortical thickness in each visual area, and correlating across subjects, yielding a correlation matrix of visual area pairs. The correlation matrix was subsequently clustered using an agglomerative hierarchical cluster tree procedure . Statist2) sampled in 100 bins across subjects. The effects of demographic factors on mean cortical thickness were assess with a mixed-factorial ANOVA (3 factors), with age and gender as between-subject factors and visual area as the within-subject independent factor.The group distributions of mean cortical thickness were fitted with a one-dimensional Gaussian model to obtain standardized population parameters for each visual area. Deviations from the normal distribution were assessed with the Anderson-Darling test, with FDR correction for multiple comparisons. The model goodness of fit was assessed with the coefficient of determination  . Within-In addition, a hemispheric bias metric was calculated by subtracting the mean cortical thickness, in mm, for the left hemisphere against the right hemisphere, in each subject, in each visual area. Hemispheric biases were assessed with a series of one-sample t-tests to ascertain if the mean bias across participants originated from a distribution with a mean of zero. FDR correction for multiple comparisons was applied.33.1At the group level, cortical visual areas display significant variability in cortical thickness . In agreHowever, it is unclear whether the gradient increase is a feature present at the level of individual subjects, or an emergent feature of group averaging. To answer this question, we conducted a correlation analysis comparing the within-subject mean cortical thickness in one visual area with the within-subject mean cortical thickness in all other visual areas. The resulting Pearson’s correlation coefficients were then grouped using an agglomerative hierarchical cluster tree procedure , with re3.2Establishing a baseline for between-subject variability in cortical thickness is critical for statistical assessment in small-sampled studies. The large sample size of the HCP dataset allows us to estimate the inter-individual variability in cortical thickness across an adult population with varied demographic backgrounds, as a benchmark for studies of cortical thickness.Surface-corrected mean cortical thickness estimates for each subject, at each visual area across both hemispheres, are shown in p < 0.05, see 2), calculated over 100 equally spaced bins for each visual area . This result confirms the intuition that cortical thickness in the left and right hemispheres is more similar within an individual than matching hemispheres are across individuals.We assessed whether the cortical thickness in left and right hemispheres of a given subject are more similar than two matching hemispheres from two unrelated subjects. The absolute agreement in cortical thickness was assessed with the two-way, single score interclass correlation coefficient (ICC) . First, p < 0.05, see d > 0.3), with areas V3v, PHC1, IPS2, PS3 and IPS3 showing thicker cortex in the left hemisphere and areas PHC2, V3d, V3B, and IPS0 showing thicker cortex in the right hemisphere.Following this, hemispheric bias was calculated as the difference in mean cortical thickness between the left and right hemispheres, with positive bias indicating thicker cortex in the left hemisphere and negative bias indicating thicker cortex in the right hemisphere . Hemisph3.4One factor that predicts cortical thickness is a person’s age. Beyond the initial cortical expansion during childhood development , in adulF  = 2.07, p = 0.009, η2 = 0.03), with a mean decrease in cortical thickness of 0.002 mm (±0.001 SD) per year. This effect is comparable to previous reports of cortical thinning due to normal aging  = 0.12, p = 0.729, η2 = 10−3), and no interaction between age and gender on cortical thickness  = 1.27, p = 0.219, η2 = 0.02). Summary plots of age and gender effects shown in We detected no effect of gender  = 0.11, p = 0.7417, partial η2 = 10−6), indicating the variance in the cortical thickness estimate is consistent across the HCP population. A significant main effect was observed for visual area  = 543.33, p = 10−16, partial η2 = 0.35). This highlights that some regions, particularly the parahippocampal areas PHC1 and PHC2, contain more variability in cortical thickness, either due to true differences in cortical thickness within the cortical areas, or due to unreliability in measurement at this anatomical locus. Finally, no significant interaction effect between visual area and subject was detected  = 0.61, p = 0.929, partial η2 = 10−3), showing that despite variability between visual regions, cortical thickness variance is consistent across subjects.To answer the first question, we looked at the standard deviation of cortical thickness within subjects. For a given visual area, each vertex contains an independent estimate of cortical thickness for that region, and therefore variability in the estimate is observable within areas, on an individual basis. p-out resampling procedure  can be affected . An exam4.5An important consideration for investigators who wish to use the present study for normative purposes, is whether the values reported here are comparable with other cortical thickness estimates performed outside the context of the HCP. We highlight three relevant considerations; (1) the particular MRI scanner and imaging sequence used, (2) the analysis pipeline implemented and (3) population differences.First, it is not always possible to match the equipment and sequence parameters across studies, resulting in biases in imaging data leading to differing estimates of cortical thickness. Previous studies have assessed the cross-site, test-retest reliability of FreeSurfer cortical thickness estimates with scans performed on the same individuals, on different MRI systems. Such studies report excellent mean reliability with intraclass correlation coefficients (ICC) ranging between 0.81 and 0.95 . In real5We present a normative dataset of cerebral cortical thickness for human visual areas in a large sample population in the HCP, with the aim of creating a common baseline for studies of cortical thickness in special populations of interest. Across this large population, thickness varies systematically with cortical visual hierarchy, consistent with the dorsal/ventral organization of the visual system. Moreover, cortical thickness is well described by the normal distribution across visual areas and presents consistent within-subject variability and reliability.


Nitrogen (N) is an important macronutrient that controls the productivity of ecosystems and biological nitrogen fixation (BNF) is a major source of N in terrestrial systems, particularly tropical forests. Bamboo dominates theses forests, but our knowledge regarding the role of bamboo in ecosystem functioning remains in its infancy. We investigated the importance of a native bamboo species to the N cycle of a Neotropical forest.2 each) in a pristine montane Atlantic Forest, in Brazil. We counted all the clumps and live culms of Merostachys neesii bamboo and calculated the specific and total leaf area, as well as litter production and respective N content. Potential N input was estimated based on available data on BNF rates for the same bamboo species, whose N input was then contextualized using information on N cycling components in the study area.We selected 100 sample units  and 19.6 kg N ha−1 in winter (July to September). When extrapolated for annual values, M. neesii could contribute more than 60 kg N ha−1y−1.With 4,000 live culms haM. neesii closely regulates N input and may better explain the high diversity and carbon stocks in the area. This is the first time that a study has investigated BNF using free-living N fixers on the phyllosphere of bamboo.The bamboo species’ contribution to N input may be due to its abundance  and the composition of the free-living N fixer community on its leaves (demonstrated in previous studies). Although some N is lost during decomposition, this input could mitigate the N deficit in the Atlantic Forest studied by at least 27%. Our findings suggest that  Woody bamboos are typical plants in many tropical forests . Their rNitrogen (N) controls the productivity and composition of plant species  and is a−1  is an important pathway for N input in ecosystems . StudiesMerostachys neesii (Poaceae: Bambusoideae), including groups of putative free-living diazotrophs that account for a significant amount of N fixation. Studying the same bamboo species, M. neesii in a pristine montane forest does not seem to alter the overall forest structure and diversity (−1) , iversity , carbon iversity  or tree ity (−1) . The preic soils .2 concentration and produce additional biomass  in the functioning of a Neotropical forest. The major objectives were: (i) to assess the abundance of bamboo in an Atlantic Forest area; (ii) to understand the amount of N added to the system by M. neesii via free-living diazotrophs in its phyllosphere; (iii) to calculate the amount of N that returns to the system through M. neesii litter; and (iv) to contextualize the N added by M. neesii using information about N cycling components in the study area.The present paper sought to provide insights on the role of bamboo (2 each) within previously established permanent plots (−1) (−1)  . We selent plots . The phynt plots . A densent plots . Both abots (−1)  and flor−1) (−1)  are high−1) (−1) . The mos−1) (−1) .Merostachys neesii Rupr. (Poaceae: Bambusoideae), a native species of the Brazilian Atlantic Forest  based on (i) culm density; (ii) leaf biomass per culm (Lb); and (iii) specific leaf area (SLA). Lb was previously determined by MCG Padgurschi, TS Reis, LF Alves, SA Vieira, CA Joly  via destructive harvesting of 20 healthy culms around the study area . For SLA, we randomly chose 50 bamboo leaves in the field, dried at 65 °C until constant weight, weighed to obtain the dry weight, and the leaf area was calculated using an LI-3100 area meter . The leaf dry weight and leaf area (n = 50) were then used to calculate SLA. Leaf area per culm (LAc) was determined as follows: LAt) (m2 ha−1) by: Habitat availability (bamboo leaf area) was estimated in order to determine N input by free-living diazotrophs in the phyllosphere. We calculated the total bamboo leaf area (2 each). The traps were made of malleable plastic pipes with nylon mesh (2 mm) and supported by PVC pipes about 1 m above the ground. The content of the traps was collected twice a month over a year, from April 2014 to April 2015, sufficient time to capture this variable (−1y−1); MA = average monthly litter production (kg ha−1); CA = litter collector area (m2). For N chemical analysis of the bamboo leaves, we randomly selected three samples for each season  and ground them to obtain a compound sample per season (results are expressed in kg N ha−1). The analysis was performed at the Soil and Plant Laboratory (LAGRO), in São Paulo, Brazil, using the Kjeldahl method of N determination. The study was performed with permits COTEC/IF 010.323/2013, 002.766/2013 and 010.631/2013 and IBAMA/SISBIO #33217.Among the 100 sample units, we randomly selected 40 to install circular litter traps  (Nf expressed in kg N ha−1y−1) as follows: Hl is the hours of light in summer or winter  . Finallyr winter .M. neesii, data on the N cycling in the Atlantic Forest were obtained from the literature. The two dominant N input pathways , we used litterfall to predict net primary productivity (NPP). The NPP fraction allocated to leaves influences litterfall rates, making it a good predictor of productivity in neotropical forests when the main components of NPP cannot be measured . Based o1—−1 y−1  and N co1—−1 y−1  were use2O and NO losses via soil emissions were included as outputs  presence of bamboo; (iv) pH 3.8  pH 3.8 . All ana) pH 3.8 .−1 and 4,000 live culms ha−1 of M. neesii bamboo were counted. The specific leaf area (SLA) was 204.4 cm2 g−1  which, by applying equation one, resulted in LAc = 10.3 m2 and 4.1 ×104 m2 ha−1 of total leaf area (LAt) for microbial colonization. These and other data are shown in A total of 579 clumps haM. neesii can contribute up to 11.7 kg N ha−1 in summer (January to March), and 19.6 kg N ha−1 in winter (July to September), via free-living diazotrophs on its phyllosphere. When these values were extrapolated on an annual basis, M. neesii contributed more than 60 kg N ha−1y−1, representing a decline of at least 27.8% in the N deficit of the AF we studied   . The N c< 0.001) ; as such)  provide a substantial habitat (leaf area) for microbial colonization , almost equal to the rate reported for evergreen tropical forests (Spathacanthus hoffmannii (Acanthaceae), Chamaedorea tepejilote (Arecaceae), Brosimum utile (Moraceae), Caryocar costaricense (Caryocaraceae), Staminodella manilkara (Sapotaceae), Qualea paraensis (Vochysiaceae) and Schizolobium parahybum (Fabaceae)  is lower than that of several tropical and subtropical bamboo species, except for Dendrocalamus strictus  was similar to that reported in other studies (1.2% by −1y−1 was reported in this study) .In an agroforestry system in Indonesia, the litterfall of different species of the genus  Mg ha−1 ; in an E ha−1y−1 ; 1.2 andrilensis , and 2.9in India     found inity (−1) , contradity (−1) . Nonetheity (−1) . Thus, t10.7717/peerj.6024/supp-1Supplemental Information 1Click here for additional data file.


Cercospora zeae-maydis and Cercospora zeina, is one of the most impactful diseases in maize worldwide. The aim of the present study is to identify the resistance genes and understand the molecular mechanisms for GLS resistance.Gray leaf spot (GLS), which is caused by the necrotrophic fungi Two cultivars, ‘Yayu889’ and ‘Zhenghong532,’ which are distinguished as resistant and susceptible cultivars, respectively, were challenged with the GLS disease and a RNA-seq experiment was conducted on infected plants at 81, 89, 91, and 93 days post planting (dap). Compared with the beginning stage at 81 dap, 4666, 1733, and 1166 differentially expressed genes (DEGs) were identified at 89, 91, and 93 dap, respectively, in ‘Yayu889,’ while relatively fewer, i.e., 4713, 881, and 722 DEGs, were identified in ‘Zhenghong532.’ Multiple pathways involved in the response of maize to GLS, including ‘response to salicylic acid,’ ‘protein phosphorylation,’ ‘oxidation-reduction process,’ and ‘carotenoid biosynthetic process,’ were enriched by combining differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). The expression of 12 candidate resistance proteins in these pathways were quantified by the multiple reaction monitoring (MRM) method. This approach identified two candidate resistance proteins, a calmodulin-like protein and a leucine-rich repeat receptor-like protein kinase with SNPs that were located in QTL regions for GLS resistance. Metabolic analysis showed that, compared with ‘Zhenghong532,’ the amount of salicylic acid (SA) and total carotenoids in ‘Yayu889’ increased, while peroxidase activity decreased during the early infection stages, suggesting that increased levels of SA, carotenoids, and reactive oxygen species (ROS) may enhance the defense response of ‘Yayu889’ to GLS.By combining transcriptome and proteome analyses with comparisons of resistance QTL regions, calmodulin-like protein and leucine-rich repeat receptor-like protein kinase were identified as candidate GLS resistance proteins. Moreover, we found that the metabolic pathways for ROS, SA, and carotenoids are especially active in the resistant cultivar. These findings could lead to a better understanding of the GLS resistance mechanisms and facilitate the breeding of GLS-resistant maize cultivars.The online version of this article (10.1186/s12864-018-5072-4) contains supplementary material, which is available to authorized users. Cercospora zeae-maydis and Cercospora zeina, is one of the most serious foliar diseases in maize among almost all maize-growing regions worldwide [. Cercospora spores overwinter on maize plant debris in diseased fields, and conidia begin to germinate under suitable climatic conditions  in the next planting season [Gray leaf spot (GLS), which is caused by the necrotrophic fungi orldwide , 2. Cercg season , 4. The g season , and theg season . This dig season  owing toCompared with regular methods for disease control by chemicals, cultivation of GLS-resistant hybrids is urgently needed, as it is a cost-effective and environmentally friendly approach for reducing yield loss caused by GLS. Thus, a better understanding of the genetic architecture and the underlying genes and mechanisms could contribute to crop improvement and disease management. In general, plant immunity to necrotrophic infections is associated with complex biological and physiological processes , includiC. zeina of both germplasms adapted to the southern African climate [RNA-Seq can provide an efficient way to assess the global expression variation in coding genes and identify gene-based markers at the whole genome level. Recently, RNA-Seq analysis of resistant and susceptible sub-tropical maize lines showed that zealexins and kauralexins are accumulated after infection by  climate . Several climate . RNA-Seq climate .‘Yayu889,’ as a maize cultivar with high proven resistance to GLS in field conditions of China, renders itself an excellent material for understanding maize resistance to GLS. To facilitate our analysis, the susceptible cultivar ‘Zhenghong532’ was used as a reference strain. The transcriptional response of these two maize cultivars to GLS was analyzed during four stages of infection by using RNA-Seq, and both common and specific differentially expressed genes (DEGs) associated with the defense response to GLS in the two cultivars were investigated. To the best of our knowledge, this study is the first to report the induced defense response to GLS in maize by using a comparative transcriptome analysis. By screening global gene expression profiles for DEGs followed by quantitative analysis of protein and comparisons to resistance QTL regions previously reported, we have identified candidate genes for GLS resistance. Moreover, we found several pathways involved in maize responses to GLS by metabolic analysis. This may ultimately help to reveal the molecular mechanisms of maize–GLS interactions, which forms an important step towards developing molecular markers-assisted selection (MAS) for GLS-resistant genetic materials.Two commercial maize lines, ‘Yayu889’ and ‘Zhenghong 532,’ were used in our study, and both of them were provided by Sichuan Nongda Zhenghong Bio. Co., Ltd., China. Both of them were planted in Guangyuan , Sichuan Province, China, where GLS outbreaks occur every year. For each line, seeds were sown in three replicate rows of 10 plants. Before this study, a natural infection experiment was conducted for three consecutive years in the field, confirming that ‘Yayu889’ and ‘Zhenghong532’ were resistant and susceptible, respectively.Leaf samples of three biological replicates were collected at 81, 89, 91, and 93 days post planting (dap) and stored in liquid nitrogen. Disease symptoms were evaluated at 81, 89, 91, 93, and 123 dap, respectively, based on a 1–5 scale with 0.25 increments, according to disease progression on the ear leaf .Total RNA was isolated and purified from leaf tissues with TRIzol reagent  according to the manufacturer’s instructions. To ensure that the RNA meets the requirements for transcriptome sequencing, a Nanodrop spectrophotometer , Qubit RNA Kit , and 2100 Bioanalyzer  were used to determine the purity, concentration, and integrity of samples, respectively.ftp://ftp.ensemblgenomes.org/pub/release-32/plants/fasta/zea_mays/dna/. The sequence Alignment generated by Tophat2 was then processed by the software package Cufflinks to assemble the Sequence Alignment/Map file into transcript fragments. FPKM [Both cDNA library preparation and sequencing were conducted by the Biomarker Technology Company in Beijing, China. All 24 libraries were sequenced using an Illumina HiSeq™4000 . The raw data were filtered with the FASTQ_Quality_Filter tool from the FASTX-toolkit. After preprocessing the RNA-Seq data, the reads were mapped to the maize reference genome version 4 (B73 RefGen_v4) using Tophat2 , which wts. FPKM  was usedP-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate (FDR). Genes with an adjusted P-value < 0.05 and log2 (fold change) > 1 (according to DESeq) were assigned as differentially expressed.Differential expression analysis was performed using the DESeq R package (1.10.1) . DESeq pGene Ontology (GO) enrichment analysis of the DEGs was implemented using the GOseq R packages based on the Wallenius non-central hyper-geometric distribution , which cWeighted Gene Co-expression Network Analysis (WGCNA) is a statistical tool for clustering transcripts that have a similar expression pattern across a group of samples , 34. WGCTo validate RNA-seq results, qPCR was performed. RNA samples were reverse-transcribed into cDNA using the PrimeScript® RT reagent Kit . Expression profiles of genes were examined in triplicate using SYBR® Premix Ex TaqTM II  in LightCycler 480  following the 20-μL Real Time system, including 10 of μL SYBR® Premix Ex TaqTM II (2X), 0.6 μL of forward and reverse primer (6 μM) with a final concentration of 0.3 μM, 1.0 μL of cDNA (50 ng/μL), and 7.8 of μL sterile distilled water. Two-step PCR was performed according to the manufacturer’s procedure, and the initial denaturation step was conducted at 95 °C for 30 s, followed by 40 cycles of 95 °C for 5 s and 60 °C for 30 s, and then 72 °C for 60 s. All primers are listed in Additional file Proteins dissolved in solution were precipitated by adding samples to three sample volumes of pre-cooled acetone . White protein precipitates were observed upon mixing. To maximize the efficiency of protein precipitation, each sample was incubated at − 20 °C overnight (approximately 12 h). Precipitated proteins were then collected by centrifugation with a benchtop centrifuge at max speed (approximately 14 k) for 15 mins. The protein pellet was washed twice with equal volumes of pre-cooled acetone. For the washing step, a shorter centrifugation time of 5 mins was used. Residual acetone was removed by drying in a biosafety cabinet or light blowing with air.Proteins were re-suspended in 8 M urea and reduced with 20 mM DTT at 60 °C for 1 h. Proteins were then alkylated with 40 mM IAA at room temperature for 30 min in darkness. Alkylation reactions were quenched with 10 mM DTT. Samples were diluted to 2 M urea concentrations with HPLC grade water. Protein concentrations of the samples were determined with a modified Lowry’s assay  with the use of bovine serum albumin (BSA) to construct a calibration curve. An appropriate amount of trypsin was then added to the samples to reach an enzyme-to-substrate ratio of 1:100. Digestion was performed with 100 mM triethylammonium bicarbonate  at 37 °C for 18 h. Digested proteins were desalted with ZipTip  for LC-MS/MS analysis.HR workflow and Scheduled MRMHR workflow. High resolution mode  was used to capture MS spectra with the accumulation time being 250 ms per spectra. We performed full scan MS/MS under high-sensitivity mode, and optimized the accumulation time per-cycle. Rolling collision energy was used to set collision energy that spread of 5 V. The retention time windows used for datasets were 2.5 min.Separation of protein digests was performed on an Eksigent NanoLC-Ultra® 2D System and cHiPLC® system  in serial column mode. For each injection, the sample was desalted on a 75 μm × 15 mm analytical column, then eluted onto a second analytical column to create a 30-cm column length for separation. Both column chips were filled with ChromXP™ C18-CL 3 μm 120 Å phase . Peptides were separated using a linear gradient formed by A  and B , from 12 to 32% of B over 60 min at a flow rate of 250 nL/min. Each injection was performed using a full loop injection with a 1-μL sample loop. The MS analysis was performed on a TripleTOF® 5600 system  using both the MRMwww.peptideatlas.org), and the XICs for specific m/z values of different peptides were viewed by PeakView (version 1.1.1.2 by AB Sciex). The MS/MS spectrum detected by the mass spectrometer and the theoretical fragmentation spectrum for the peptides were manually checked to confirm the presence of the peptide in the XIC profile. Multiquant (version 2.0.2 by AB Sciex) was used to calculate peak area integration for the top three transitions selected from the MS/MS spectra.ProteinPilot (Version 4.5.0.0 by AB Sciex) was used for sample profiles with the Paragon method to source possible peptide matches from the UniProt protein database (release 2013_08). The following search parameters in the Paragon algorithm in ProteinPilot were used: Sample type, identification; Cys alkylation, Iodoacetamide; Digestion, trypsin; Instrument, TripleTOF 5600; Special Factors, none; and Search Effort, Thorough ID. FDR analysis in the ProteinPilot software was performed, and FDR < 1% was used for the protein identification threshold. The candidate peptides were verified by using PeptideAtlas  were assessed using enzyme linked immunosorbent assay (ELISA) test kits  according to the manufacturer’s instructions.Leaf tissues with fresh weights of 100 mg were homogenized and extracted in 900 μL of 0.05 M phosphate saline buffer . The homogenate was centrifuged at 1 × 102O2. The absorbance was monitored at 470 nm for at least 5 min at 1-min intervals; an absorbance change of 0.01 represented one unit of POD activity.The crude enzyme extraction method was the same as those outlined above. Peroxidase (POD) activity was determined using the method of Upadhyaya et al.  with minThe total carotenoids were determined by the method of Yang et al.  with sliP < 0.05.Data obtained in the experiments were used to evaluate the disease index and MRM were subjected to an analysis of variance (ANOVA) using the Statistical Package for Social Science  version 17.0. The statistical significance was judged at a threshold of ‘Yayu889’ and ‘Zhenghong532’ were cultivated in 2012 and 2011, respectively, in southwestern China. They showed similar growth rates and developmental progressions throughout the sampling period. The growing cycle from sowing to tassel lasted 98 days for ‘Yayu889’ and 100 days for ‘Zhenghong532.’ The growing cycle from sowing to maturity lasted 170 days for ‘Yayu889’  and 163 days for ‘Zhenghong532’ , while different resistance levels were exhibited in response to GLS. The development of disease symptoms of the two maize cultivars was investigated at 81, 89, 91, and 93 dap, respectively, and GLS symptoms were scored at 123 dap.Of the two cultivars evaluated against GLS, ‘Yayu889’ was resistant , while ‘Zhenghong532’ was susceptible , while 487 genes were common DEGs among all three time points in ‘Yayu889’ Fig. . The numFunctional annotations of the DEGs available from seven public databases were used to investigate the functions and roles in response to GLS. Several categories of defense-related genes, which were already reported in plant immunity to necrotrophic fungi infection –44, are WAK) at 89, 91, and 93 dap, respectively, and seven of them were shared among all three assayed phases  were down-regulated in ‘Zhengong532’ at 89 dap and exhibited baseline expression at 91 and 93 dap. Six, four, and two mitogen-activated protein kinases (MAPK) were identified in ‘Yayu889’ at 89, 91, and 93 dap, respectively, while ten, three, and one MAPK genes were found in ‘Zhenghong532’  were down-regulated in ‘Zhenghong532’ at the same phase. ‘Yayu889’ exhibited induction of 16, 20, and 4 WRKY genes at 89, 91, and 93 dap, respectively. In contrast, ‘Zhenghong532’ exhibited induction of only eleven, eight, and zero WRKY genes, respectively  genes in ‘Yayu889’ at 89, 91, and 93 dap. While the number of up-regulated GST genes was four, one, and zero in ‘Zhenghong532’  were down-regulated in Zhenghong532 at 89 dap.At 89, 91, and 93 dap we found ten, six, and three chitinases that were differentially expressed in ‘Yayu889,’ while seven, one, and one were up-regulated in ‘Zhenghong532,’ respectively Fig. . ‘Yayu88ses Fig. . ‘ZhenghTo validate the RNA-Seq data, 12 DEGs were randomly selected for qRT-PCR assays based on their expression patterns at three time points. The results of the selected DEGs showed that the qRT-PCR results were consistent with the RNA-Seq results, as both RNA-Seq and qRT-PCR analyses showed similar expression patterns of up- and down-regulation, indicating that the RNA-seq analysis was well suited for analysis of GLS-induced maize leaf transcriptomes  genes and CML genes from these two pathways compared to ‘Zhenghong532’  were specifically up-regulated in ‘Yayu889’ (91 dap), while baseline expression was exhibited in ‘Zhenghong532’  were subjected to WGCNA. A total of 5046 transcripts were assigned to 13 co-expression modules, named after randomly assigned colors Fig. . Six of MAPK (Zm00001d048027 and Zm00001d047758) and LYK5 (Zm00001d053695), were up-regulated in ‘Yayu889’ and expressed at the baseline level in ‘Zhenghong532’  of this module were significantly up-regulated at 91 and 93 dap compared to 81 dap, while baseline expression of these genes was observed at these two stages in ‘Zhenghong532’  were listed for further analysis. We applied GO enrichment analysis to investigate the functional enrichment of transcripts in these three modules, respectively. In module DG, several biological processes related to GLS disease were enriched, including ‘protein phosphorylation,’ ‘response to chitin,’ ‘hormone-mediated signaling pathway,’ and ‘ionotropic glutamate receptor signaling’ .GLS resistance pathways were identified by transcriptome profiling and data from the published literature, revealing a total of 56 DEGs that were associated with disease resistance Fig. . To deveCo-localization of QTLs with DEGs facilitates the screening of candidate genes for GLS resistance, and the impact of intraspecific allelic variation on gene expression may lead to phenotypic variation, including the possibility of hybrid vigor as a beneficial trait to be exploited in crop breeding. As shown in Table MYB genes, alpha-dioxygenase 1, and a HSPRO2 gene, were identified; ‘Yayu889’ expressed a putative MYB gene (Zm00001d051149) at all three phases and another MYB gene (Zm00001d017268) at 91 and 93 dap. However, in ‘Zhenghong532,’ both of the genes only showed a weaker up-regulation at 91 dap  that belong to this GO term were up-regulated in ‘Yayu889,’ but either down-regulated or expressed at baseline levels in ‘Zhenghong532’  was specifically enriched in ‘Yayu889’ at 91 and 93 dap, and several DEGs, including two 51 was spdap Fig. . Additio32’ Fig. . Next, tThe GO term ‘oxidation-reduction process’ (GO:0055114) was specifically found in ‘Zhenghong532.’ Protein SRG1 and four important redox enzymes of cytochrome P450, acyl-desaturase 2, geraniol 8-hydroxylase, and indolin-2-one monooxygenase were enriched. In order to verify this GO term from the metabolic level, the POD activity associated with this pathway was measured. As shown in Fig. The GO term ‘carotenoid biosynthetic process’ (GO:0016117) was overrepresented solely in ‘Zhenghong532.’ The total carotenoid content of the two cultivars was thus measured. As shown in Fig. These results indicate that SA, carotenoids, and POD may participate in the regulation of maize’s defense response to GLS.GLS is a significant threat to maize cultivation in China owing to the current lack of resistant cultivars and the suitability of the climate of many regions to GLS. In this study, sets of genes were identified that respond to fungal infection in susceptible and resistant maize cultivars and define how each cultivar perceived the intruder and programmed its defense system. A limitation of this study is the genetic diversity between both maize lines. To reduce the impact of diverse genetic backgrounds on the results of the analysis, the datasets were filtered step by step. First, six major gene families, reported to be related to plant immunity –44, wereArabidopsis [Arabidopsis [l-phenylalanine catabolic process in module PU, which contains four phenylalanine ammonia-lyase (PAL) proteins, was reported to participate in the biosynthesis of defense-related phytohormone SA and phytoalexin in rice [Three expression modules associated with GLS responses were observed by WGCNA. The RING-H2 finger protein ATL2A, which belongs to module DG Table , was an bidopsis , 46. Anobidopsis , 48 by rbidopsis . We hypo in rice . Additio in rice .HSPRO2 (Zm00001d012321) was specifically activated in ‘Yayu889’ Additional file 2:Evaluation of sequencing quality. Y and Z represent ‘Yayu889’ and ‘Zhenghong532,’ respectively; 1, 2, 3, and 4 represent 81, 89, 91, and 93 days after planting, respectively; a, b, and c represent each of the three biological replicates of each time point, respectively. (DOCX 17 kb)Additional file 3:Mapping efficiency statistics. Y and Z represent ‘Yayu889’ and ‘Zhenghong532,’ respectively; 1, 2, 3, and 4 represent 81, 89, 91, and 93 days after planting, respectively; a, b, and c respectively represent each of the three biological replicates of each time point, respectively. (DOCX 19 kb)Additional file 4:Correlation coefficients between each pair of three biological replicates. (XLSX 14 kb)Additional file 5:Up-regulated and down-regulated chitinases in ‘Yayu889’ and ‘Zhenghong532’ at 89, 91, and 93 days post planting, respectively. (XLSX 15 kb)Additional file 6:Up-regulated and down-regulated PR genes in ‘Yayu889’ and ‘Zhenghong532’ at 89, 91, and 93 days post planting, respectively. (XLSX 11 kb)Additional file 7:Up-regulated and down-regulated wall-associated kinases in ‘Yayu889’ and ‘Zhenghong532’ at 89, 91, and 93 days post planting, respectively. (XLSX 16 kb)Additional file 8:Up-regulated and down-regulated MAP kinases in ‘Yayu889’ and ‘Zhenghong532’ at 89, 91, and 93 days post planting, respectively. (XLSX 14 kb)Additional file 9:Up-regulated and down-regulated WRKY transcription factors in ‘Yayu889’ and ‘Zhenghong532’ at 89, 91, and 93 days post planting, respectively. (XLSX 15 kb)Additional file 10:S-transferase in ‘Yayu889’ and ‘Zhenghong532’ at 89, 91, and 93 days post planting, respectively. (XLSX 15 kb)Up-regulated and down-regulated glutathione Additional file 11:List of differentially expressed genes (DEGs) involved in the ‘Plant-pathogen pathway’ in ‘Yayu889’ and ‘Zhenghong532’. (XLSX 28 kb)Additional file 12:Top GO_BP of three co-expression modules in ‘Yayu889’. (XLSX 18 kb)Additional file 13:List of 56 candidate resistance genes obtained by combining transcription profiling and co-expression network analysis. (XLSX 37 kb)