Metabolomics has emerged as a powerful tool in the quantitative identification of physiological and disease-induced biological states. Extracellular metabolome or metabolic profiling data, in particular, can provide an insightful view of intracellular physiological states in a noninvasive manner.iMM904, to investigate how changes in the extracellular metabolome can be used to study systemic changes in intracellular metabolic states. The iMM904 metabolic network was reconstructed based on an existing genome-scale network, iND750, and includes 904 genes and 1,412 reactions. The network model was first validated by comparing 2,888 in silico single-gene deletion strain growth phenotype predictions to published experimental data. Extracellular metabolome data measured in response to environmental and genetic perturbations of ammonium assimilation pathways was then integrated with the iMM904 network in the form of relative overflow secretion constraints and a flux sampling approach was used to characterize candidate flux distributions allowed by these constraints. Predicted intracellular flux changes were consistent with published measurements on intracellular metabolite levels and fluxes. Patterns of predicted intracellular flux changes could also be used to correctly identify the regions of the metabolic network that were perturbed.We used an updated genome-scale metabolic network model of Saccharomyces cerevisiae, Our results indicate that integrating quantitative extracellular metabolomic profiles in a constraint-based framework enables inferring changes in intracellular metabolic flux states. Similar methods could potentially be applied towards analyzing biofluid metabolome variations related to human physiological and disease states. In addition, there is a rapidly growing literature and accompanying databases that compile this information. This has provided the basis for the assembly of genome-scale metabolic networks for various microbial and eukaryotic organisms -11. Thesin silico simulations of allowable network states based on governing physico-chemical and genetic constraints [E. coli metabolism [A genome-scale network reconstruction is a structured collection of genes, proteins, biochemical reactions, and metabolites determined to exist and operate within a particular organism. This network can be converted into a predictive model that enables straints ,13. A wistraints -16. Moststraints . Insteadtabolism  as well tabolism .Network reconstructions provide a structured framework to systematically integrate and analyze disparate datasets including transcriptomic, proteomic, metabolomic, and fluxomic data. Metabolomic data is one of the more relevant data types for this type of analysis as network reconstructions define the biochemical links between metabolites, and recent advancements in analytical technologies have allowed increasingly comprehensive intracellular and extracellular metabolite level measurements ,21. The Metabolite secretion by a cell reflects its internal metabolic state, and its composition varies in response to genetic or experimental perturbations due to changes in intracellular pathway activities involved in the production and utilization of extracellular metabolites . VariatiSince metabolic networks describe mechanistic, biochemical links between metabolites, integration of such data can allow a systematic approach to identifying altered pathways linked to observed quantitative changes in secretion profiles. Measured secretion rates of major byproduct metabolites can be applied as additional exchange flux constraints that define observed metabolic behavior. For example, a recent study integrating small-scale EM data with a genome-scale yeast model correctly predicted oxygen consumption and ethanol production capacities in mutant strains with respiratory deficiencies . The resIn this study, we implemented a constraint-based sampling approach on an updated genome-scale network of yeast metabolism to systematically determine how EM level variations are linked to global changes in intracellular metabolic flux states. By using a sampling-based network approach and statistical methods Figure , EM chanS. cerevisiae metabolic network, iMM904; and (ii) the systematic inference of intracellular metabolic states from two yeast EM data sets using a constraint-based sampling approach. The first EM data set compares wild type yeast to the gdh1/GDH2 (glutamate dehydrogenase) strain [This study was divided into two parts and describes: (i) the reconstruction and validation of an expanded ) strain , which i) strain ,32. The ) strain . We analiND750, a fully compartmentalized and elementally-balanced S. cerevisiae metabolic network, was used as the basis for reconstructing the iMM904 network [iND750 network were also re-evaluated to update the model based on existing literature. The iMM904 network was reconstructed using the SimPheny® modeling software . Existing gene-protein-reaction (GPR) associations from iND750 were also reviewed and several were modified to include additional genes and proteins. GPR associations are Boolean representations of the logical relationship between ORFs and their corresponding transcripts, proteins, and reactions to enable mapping of genes to their respective functions. The included model text files [see Additional file The previously reconstructed  network . The net network . The detS containing the stoichiometric coefficients of the reactions in the network. The steady-state solution space containing possible flux distributions is determined by calculating the null space of S: S . v = 0, where v is the reaction flux vector. Minimal media conditions were set through constraints on exchange fluxes corresponding to the experimental measured substrate uptake rates. All the model-based calculations were done using the Matlab COBRA Toolbox [The network reconstruction was converted to a constraint-based model using established procedures . Network Toolbox  utiliziniMM904 model was initially validated by simulating wild type yeast growth in aerobic and anaerobic carbon-limited chemostat conditions and comparing the simulation results to published experimental data on substrate uptake and byproduct secretion in these conditions [iFF708 model in a previous study [in silico growth rate to the measured dilution rate, which are equivalent under continuous culture growth, and minimizing the glucose uptake rate. The accuracy of in silico predictions of substrate uptake and byproduct secretion by the iMM904 model was similar to the accuracy obtained using the iFF708 model and results are shown in Figure S1 [see Additional file The nditions . The stuus study . The preiMM904 network was further validated by performing genome-scale gene lethality computations following established procedures to determine growth phenotypes under minimal medium conditions and compared to published data. A modified version of the biomass function used in previous iND750 studies was set as the objective to be maximized and gene deletions were simulated by setting the flux through the corresponding reaction(s) to zero. The biomass function was based on the experimentally measured composition of major cellular constituents during exponential growth of yeast cells and was reformulated to include trace amounts of additional cofactors and metabolites with the assumed fractional contribution of 10-6. These additional biomass compounds were included according to the biomass formulation used in the iLL672 study to improve lethality predictions through the inclusion of additional essential biomass components [in silico strain with the appropriate supplements at non-limiting, but low levels. Furthermore, trace amounts of essential nutrients that are present in the experimental minimal media formulation  were supplied in the simulations [The mponents . The modulations .Three distinct methods to simulate the outcome of gene deletions were utilized: Flux-balance analysis (FBA) -38, Miniin silico deletion phenotypes involved choosing a threshold for the predicted relative growth rate of a deletion strain that is considered to be viable. We used standard ROC curve analysis to assess the accuracy of different prediction methods and models across the full range of the viability threshold parameter, with results shown in Figure S2 [see Additional file a priori [The comparison between experimental and a priori . The opta priori . The MCCThe method implemented in this study is shown schematically in Figures Relative levels of quantitative EM data were incorporated into the constraint-based framework as overflow secretion exchange fluxes to simulate the required low-level production of experimentally observed excreted metabolites. The primary objective of this study is to associate relative metabolite levels that are generally measured for metabonomic or biofluid analyses to the quantitative ranges of intracellular reaction fluxes required to produce them. However, without detailed kinetic information or dynamic metabolite measurements available, we approximated EM datasets of relative quantitative metabolite levels to be proportional to the rate in which they are secreted and detected (at a steady state) into the extracellular media. This approach is analogous to approximating uptake rates based on metabolite concentrations from a previous study performing sampling analysis on a cardiomyocyte mitochondrial network to identify differential flux distribution ranges for various environmental (i.e. substrate uptake) conditions .gdh1/GDH2 strains were flask cultured under minimal glucose media conditions; thus, glucose and oxygen uptake rates were set at 15 and 2 mmol/hr/gDW, respectively, for the gdh1/GDH2 strain study. In the anaerobic case the oxygen uptake rate was set to zero, and sterols and fatty acids were provided as in silico supplements as described in [The raw data was normalized by the raw maximum value of the dataset (thus the maximum secretion flux was 1 mmol/hr/gDW) with an assumed error of 10% to set the lower and upper bounds and thus inherently accounting for sampling calculation sensitivity. The ribed in . For theA modified FBA method with minimization of the 1-norm objective function between two optimal flux distributions was used to determine optimal intracellular fluxes based on the EM-constrained metabolic models. This method determines two optimal flux distributions simultaneously for two differently constrained models (e.g. wild type vs. mutant) – these flux distributions maximize biomass production in each case and the 1-norm distance between the distributions is as small as possible given the two sets of constraints. This approach avoids problems with alternative optimal solutions when comparing two FBA-computed flux distributions by assuming minimal rerouting of flux distibution between a perturbed network and its reference network. Reaction flux changes from the FBA optimization results were determined by computing the relative percentage fold change for each reaction between the mutant and wild-type flux distributions.We utilized artificial centering hit-and-run (ACHR) Monte Carlo sampling ,41 to unDue to the overall shape of the metabolic flux solution space, most of the sampled flux distributions resided close to the minimally allowed growth rate (i.e. biomass production) and corresponded to various futile cycles that utilized substrates but did not produce significant biomass. In order to study more physiologically relevant portions of the flux space we restricted the sampling to the part of the solution space where the growth rate was at least 50% of the maximum growth rate for the condition as determined by FBA. This assumes that cellular growth remains an important overall objective by the yeast cells even in batch cultivation conditions, but that the intracellular flux distributions may not correspond to maximum biomass production .Z-scores (see below) are not significantly affected by either the portion of the solution space sampled or the exact scaling of secretion rates. The final overall sample used was created by combining the samples for all minimum growth rate thresholds for the highest extracellular metabolite secretion rate (maximum 1 mmol/hr/gDW). This approach allowed biasing the sampling towards physiologically relevant parts of the solution space without imposing the requirement of strictly maximizing a predetermined objective function. The samples obtained with no EM data were used as control samples to filter reporter metabolites/subsystems whose scores were significantly high due to only random differences between sampling runs.To test the sensitivity of the results to the minimum growth rate threshold, separate Monte Carlo samples were created for each minimum threshold ranging from 50% to 100% at 5% increments. We also tested the sensitivity of the results to the relative magnitude of the extracellular metabolite secretion rates by performing the sampling at three different relative levels . For each minimum growth rate threshold and extracellular metabolite secretion rate, the ACHR sampler was run for 5 million steps and a flux distribution was stored every 5000 steps. The sensitivity analysis results are presented in Figures S3 and S4 [see Additional File Since the experimental data used in this study was generated in chemostat conditions, and previous studies have indicated that chemostat flux patterns predicted by FBA are close to the experimentally measured ones , we assuZ-score based approach was implemented to quantify differences in flux samples between two conditions  flux difference vectors for each pair of conditions considered (e.g. mutant or perturbed environment vs. wild type). Based on this flux difference sample, the sample mean  and standard deviation  between the two conditions was calculated for each reaction i. The reaction Z-score was calculated as:A s Figure . First, which describes the sampled mean difference deviation from a population mean change of zero (i.e. no flux difference between perturbation and wild type). Note that this approach allows accounting for uncertainty in the flux distributions inferred based on the extracellular metabolite secretion constraints. This is in contrast to approaches such as FBA or MoMA that would predict a single flux distribution for each condition and thus potentially overestimate differences between conditions.Z-scores can then be further used in analysis to identify significantly perturbed regions of the metabolic network based on reporter metabolite [ Z-scores. These reporter regions indicate, or "report", dominant perturbation features at the metabolite and pathway levels for a particular condition. The reporter metabolite Z-score for any metabolite j can be derived from the reaction Z-scores of the reactions consuming or producing j (set of reactions denoted as Rj) as:The reaction tabolite  or subsytabolite  Z-scoresNj is the number of reactions in Rj and mmet,j is calculated aswhere Z-score was normalized by computing μmet,Nj and σmet,,Nj corresponding to the mean mmet and its standard deviation for 1,000 randomly generated reaction sets of size Nj. Z-scores for subsystems were calculated similarly by considering the set of reactions Rk that belongs to each subsystem k. Hence, positive metabolite and subsystem scores indicate a significantly perturbed metabolic region relative to other regions, whereas a negative score indicate regions that are not perturbed more significantly than what is expected by random chance. Perturbation subnetworks of reactions and connecting metabolites were visualized using Cytoscape [To account and correct for background distribution, the metabolite ytoscape .S. cerevisiae network, iND750, was used as the basis for the construction of the expanded iMM904 network. Prior to its presentation here, the iMM904 network content was the basis for a consensus jamboree network that was recently published but has not yet been adapted for FBA calculations [iND750 content was carried over and further expanded on to construct iMM904, which accounts for 904 genes, 1,228 individual metabolites, and 1,412 reactions of which 395 are transport reactions. Both the number of gene-associated reactions and the number of metabolites increased in iMM904 compared with the iND750 network. Additional genes and reactions included in the network primarily expanded the lipid, transport, and carbohydrate subsystems. The lipid subsystem includes new genes and reactions involving the degradation of sphingolipids and glycerolipids. Sterol metabolism was also expanded to include the formation and degradation of steryl esters, the storage form of sterols. The majority of the new transport reactions were added to connect network gaps between intracellular compartments to enable the completion of known physiological functions. We also added a number of new secretion pathways based on experimentally observed secreted metabolites [A previously reconstructed ulations . The majabolites .iND750 reactions, but the genes encoding these proteins were not associated with their corresponding GPRs. Other examples include glycogenin and NADPH cytochrome p450 reductases (CPRs), which are required in the assembly of glycogen and to sustain catalytic activity in cytochromes p450, respectively. These additional proteins were included in iMM904 as part of protein complexes to provide a more complete representation of the genes and their corresponding products necessary for a catalytic activity to occur.A number of gene-protein-reaction (GPR) relationships were modified to include additional gene products that are required to catalyze a reaction. For example, the protein compounds thioredoxin and ferricytochrome C were explicitly represented as compounds in S. cerevisiae networks associated with quinone, beta-alanine, and riboflavin biosynthetic pathways were essentially inferred from known reaction mechanisms based on reactions in previous network reconstructions of E. coli [iMM904 network contents as well as a detailed list of changes between iND750 and iMM904 is included [see Additional file Major modifications to existing reactions were in cofactor biosynthesis, namely in quinone, beta-alanine, and riboflavin biosynthetic pathways. Reactions from previous  E. coli ,47. ThesiMM904 metabolic network was validated by comparing in silico single-gene deletion predictions to in vivo results from a previous study used to analyze another S. cerevisiae metabolic model, iLL672 [iFF708 network [iND750 network [iLL672 model consisted of 3,360 single-gene knockout strain phenotypes evaluated under minimal media growth conditions with glucose, galactose, glycerol, and ethanol as sole carbon sources. Growth phenotypes for the iMM904 network were predicted using FBA [The updated genome-scale , iLL672 . This ne network , which wsing FBA -34, MoMAsing FBA , and liniMM904 has 212 more genes than iLL672 with experimental data, we also present results for the subset of iMM904 predictions with genes included in iLL672 (reduced iMM904 set). When the same gene sets are compared, iMM904 improves gene lethality predictions under glucose, galactose, and glycerol conditions over iLL672 somewhat, but is less accurate at predicting growth phenotypes under the ethanol condition. It should be noted that the iLL672 predictions were obtained directly from [iMM904 predictions. Overall, when viability cutoff is chosen as indicated above for each method separately, the three prediction methods  perform similarly.Since tly from  and thusiMM904 greatly increased the number of true viable predictions, the full model also made significantly more false viable predictions compared with reduced iMM904 and iLL672 predictions. However, it is important to note that 143 reactions involved in dead-end biosynthetic pathways were actually removed from iFF708 to build the iLL672 reconstruction [While the full gene complement in truction . As moretruction .gdh1/GDH2 mutant strain was previously developed [Gdh1, was deleted and the NADH-dependent form of the enzyme, Gdh2, was overexpressed. The net effect is to allow efficient assimilation of ammonia into glutamate using NADH instead of NADPH as a cofactor. While growth characteristics remained unaffected, relative quantities of secreted metabolites differed between the wild-type and mutant strain under aerobic and anaerobic conditions.The eveloped ,50 in orgdh1/GDH2 and wild-type strains reported in [iMM904 network [see Additional file Z-scores were calculated from the sampling analysis to quantify flux changes between the mutant and wild-type strains, with Zreaction > 1.96 corresponding to a two-tailed p-value < 0.05 and considered to be significantly perturbed [see Additional file We analyzed EM data for the orted in  under aeorted in , primarip < 0.05) between mutant and wild-type. Statistical measures of recall, accuracy, and precision were calculated and represent the predictive sensitivity, exactness, and reproducibility respectively. From the sampling analysis, a considerably larger number of significantly perturbed reactions are predicted in the anaerobic case  than in aerobic . The top percentile of FBA flux changes equivalent to the percentage of significantly perturbed sampling reactions were compared to the intracellular data. Results from both analyses are summarized in Table To validate the predicted results, reaction flux changes from both FBA and sampling methods were compared to differential intracellular metabolite level data measured from the same study. Intracellular metabolites involved in highly perturbed reactions (i.e. reactants and products) predicted from FBA and sampling analyses were identified and compared to metabolites that were experimentally identified as significantly changed  and subsystem (oxidative phosphorylation), is certainly feasible as NADH is a primary reducing agent for ATP production. Pentose phosphate pathway and NAD biosynthesis also appears among the most perturbed anaerobic subsystems, further suggesting perturbed cofactor balance as a common, dominant effect under both conditions.Perturbations under aerobic conditions largely consisted of pathways involved in mediating the NADH and NADPH balance. Among the highest scoring aerobic subsystems are TCA cycle and pentose phosphate pathway – key pathways directly involved in the generation of NADH and NADPH. Reporter metabolites involved in these subsystems – glyceraldehyde-3-phosphate, ribulose-5-phosphate, and alpha-ketoglutarate – were also identified. These results are consistent with flux and enzyme activity measurements of the nditions , which rgdh1/GDH2 modification in both aerobic and anaerobic conditions. For example, the proline biosynthesis pathway that uses glutamate as a precursor was significantly perturbed in both conditions, as supported by significantly changed intracellular and extracellular levels. There were differences, however, in that more amino acid related subsystems were significantly affected in the anaerobic case  significantly perturbed amino acid subsystems, 2) a broad perturbation subnetwork converging on glutamate  e Figure .A recent study reported that potassium limitation resulted in significant growth retardation effect in yeast due to excess ammonium uptake when ammonium was provided as the sole nitrogen source . The proiMM904 model and the EM profile analysis method to analyze amino acid secretion profiles for a range of low potassium and high ammonia conditions reported in [iMM904 model, sampled the allowable solution space, computed reaction Z-scores for changes from a reference condition , and finally summarized the resulting changes using reporter metabolites. Figure In order to elucidate the differences in internal metabolic states, we utilized the orted in . As befogdh1/GDH2 strain data. Taken together with the anaerobic gdh1/GDH2 data, the results consistently suggest highly perturbed threonine and folate metabolism when amino acid-related pathways are broadly affected.In addition to perturbed amino acids, a secondary effect notably appears at high ammonia levels in which metabolic regions related to folate metabolism are significantly affected. As highlighted in green in Figure In both ammonium-toxic and potassium-limited environments, impaired cellular growth was observed, which can be attributed to high energetic costs of increased ammonium assimilation to synthesize and excrete amino acids. However, under high ammonium environments, reporter metabolites related to threonine and folate metabolism indicated that their perturbation, and thus purine supply, may be an additional factor in decreasing cellular viability as there is a direct relationship between intracellular folate levels and growth rate . Based ogdh1/GD2 mutant) and environmental (excess ammonium and limited potassium) perturbations, and the predicted intracellular metabolic changes were consistent with previously published experimental data including measurements of intracellular metabolite levels and metabolic fluxes. Our reanalysis of previously published EM data on ammonium assimilation-related genetic and environmental perturbations also resulted in testable hypotheses about the role of threonine and folate pathways in mediating broad responses to changes in ammonium utilization. These studies also demonstrated that the sampling-based method can be readily applied when only partial secreted metabolite profiles (e.g. only amino acids) are available.The method presented in this study presents an approach to connecting intracellular flux states to metabolites that are excreted under various physiological conditions. We showed that well-curated genome-scale metabolic networks can be used to integrate and analyze quantitative EM data by systematically identifying altered intracellular pathways related to measured changes in the extracellular metabolome. We were able to identify statistically significant metabolic regions that were altered as a result of genetic (With the emergence of metabolite biofluid biomarkers as a diagnostic tool in human disease ,56 and tConceived and designed the experiments: MLM MJH BOP. Performed experiments: MLM MJH. Analyzed the data: MLM MJH. Wrote the paper: MLM MJH BOP. All authors have read and approved the final manuscript.iMM904 network content. The data provided represent the content description of the iMM904 metabolic network and detailed information on the expanded content.Click here for fileiMM904 model files. The data provided are the model text files of the iMM904 metabolic network that is compatible with the available COBRA Toolbox [ Toolbox . The modClick here for fileSupplemental figures. The file provides the supplemental figures and descriptions of S1, S2, S3, and S4.Click here for fileGdh mutant aerobic and anaerobic analysis results. The data provided are the full results for the exometabolomic analysis of aerobic and anerobic gdh1/GDH2 mutant.Click here for file


It is therefore suggested that the increasing malignancy of the tumours studied was associated with a change in the tumour rather than increasing immunodepression in successive hosts.Spontaneously occurring A-strain mouse mammary carcinomata were individually passaged, at equal intervals into separate groups of isogenic hosts. The tumours showed evidence of increasing autonomy as judged either by the decreasing host lymphoid hyperplasia they evoked, or their decreased killing time, as passaging continued. However, in general, no reduction was found in the ability of spleen cells from hosts bearing succeeding passages of the same tumour to induce a graft-versus-host reaction in (A × CBA)F


Coordinated gene transcript levels across tissues (denoted “gene synchrony”) reflect converging influences of genetic, biochemical and environmental factors; hence they are informative of the biological state of an individual. So could brain gene synchrony also integrate the multiple factors engaged in neuropsychiatric disorders and reveal underlying pathologies? Using bootstrapped Pearson correlation for transcript levels for the same genes across distinct brain areas, we report robust gene transcript synchrony between the amygdala and cingulate cortex in the human postmortem brain of normal control subjects . Coordinated expression was confirmed across distinct prefrontal cortex areas in a separate cohort (n = 19 subjects) and affected different gene sets, potentially reflecting regional network- and function-dependent transcriptional programs. Genewise regional transcript coordination was independent of age-related changes and array technical parameters. Robust shifts in amygdala-cingulate gene synchrony were observed in subjects with major depressive disorder  , significantly affecting between 100 and 250 individual genes . Biological networks and signal transduction pathways corresponding to the identified gene set suggested putative dysregulated functions for several hormone-type factors previously implicated in depression . In summary, we showed that coordinated gene expression across brain areas may represent a novel molecular probe for brain structure/function that is sensitive to disease condition, suggesting the presence of a distinct and integrated hormone-mediated corticolimbic homeostatic, although maladaptive and pathological, state in major depression. Major depression affects more individuals than all other psychiatric illnesses combined, and a significant number of patients do not remit after pharmacological or behavioral treatment (i) driven by various molecular mechanisms, genetic make-up and function-dependent synchronization, (ii) central to cellular function, (iii) link genes of common biological functions How can brain region activities be investigated at the molecular and gene levels? We hypothesized that pathological mechanisms leading to depression may affect the coordination of gene expression patterns in the brain, and tested this hypothesis within a set of related brain areas, the amygdala and the subgenual anterior cingulate cortex. Our assay makes use of the fact that correlations in gene transcript levels across samples and datasets (“coexpression” or “coregulation”) represent intrinsic attributes of cellular and biological systems Transcripts for a particular gene are synchronized between two regions if they display significantly higher correlation across brain regions compared to permutated data. Here, using gene array data in the human postmortem brain of control subjects Age-related genes could produce correlations between gene expression levels across samples because numerous genes have strong correlations with age A genetic confound for these effects was also extremely unlikely as allelic frequencies for very large gene numbers would need to be similar within cohort, while being significantly different across cohorts, in order to generate the observed differences. Moreover, transcripts with reported impact of genetic variant on array hybridization and signal level RMA-based methods (as used here) have superior low-level detection capability compared to GCOS-MAS5 array = 0.19 in amygdala and cingulate) compared to qPCR values . This higher CVqPCR potentially reflects the exponential amplification of PCR reactions compared to the linear hybridization detection by arrays, and effectively limits the potential of confirming coregulation by qPCR in this and related studies. These results are consistent with other studies on microarray-based gene network, where qPCR is typically used to validate the mean absolute expression level qPCR confirmation typically relies on measuring group differences 20% or greater in magnitude and averaged over multiple samples. Accordingly, the technical reliability of the array data used here was previously validated by independent qPCR measurements  We next tested the hypothesis that pathological mechanisms leading to depression may affect the coordination of gene expression patterns between the amygdala and cingulate cortex. Array data from subjects with major depression To gain insight into biological functions affected by these changes, we overlaid the top 80 genes (∼20% FDR) under both conditions (gain or loss of synchrony) onto the global molecular network of the Ingenuity knowledge database. The top gene networks in both categories displayed similarities, as they included numerous signal transduction and transcription components of the mitogen-activated protein kinase pathway  and otheOur findings demonstrate that regional gene synchrony, as measured by gene-wise correlated transcript levels across brain regions within individuals, is a major component of gene expression patterns in the human brain . These pWhile data from the amygdala/cingulate cortex and from the two prefrontal cortex areas supports the contention that gene coordination may reflect an overall, or network-specific, concerted brain region function, our results are independent of these larger hypotheses, as we only considered here the functional significance of those genes which show significant depression-related alteration in gene synchrony between two regions known to be functionally affected by depression. Accordingly, by bootstrapping correlations and controlling the FDR, we identified a robust and conservative collection of genes that displayed significant gains or losses of amygdala-cingulate gene transcript coordination in subjects with depression  which i.de novo, although pathological, state. The integrative nature of this deregulated state departs from reductionist approaches and has critical implications for our understanding and modeling of pathological mechanisms of depression.Notably, changes in amygdala-cingulate gene synchrony suggest a combined dysregulated function for several hormone-type modulators ; Table 1As coregulated gene expression reflect the influences of genetic, biochemical and environmental factors (1) Insulin shared potential control over genes forming the most robust networks under conditions of gain and loss of synchrony ((2) Thyroid hormone influences brain physiology through regulating basal metabolism and neuronal maturation. Low thyroid function is associated with increased incidence of depression, while thyroid adjuvant therapy augments antidepressant therapy, potentially through deactivation of limbic regions (3) Although associated with mood changes in female subjects, the relevance of altered estradiol function to this male group is underscored by local aromatase–mediated conversion of testosterone to estradiol, including in the amygdala, where it modulates anxiety and depressive-like behaviors (4) IL1 is a potent pro-inflammatory cytokine, which mediates aspects of the “sickness behavior”, a syndrome sharing similarities with major depression (5) Finally, as potential core inducing-factors of the illness Consistent with the above-proposed model, the unbiased analysis of biological modulators associated with networks formed by genes with altered amygdala-cingulate coregulation, identified factors previously implicated in depression or in its treatment , which now interacts with individual genetic make-up or additional environmental disturbances (stress or infection). Thus this model connects and potentially synergizes distinct and previously-proposed pathophysiological mechanisms for depression. Accordingly, pathways to a depressive state are not likely to be explained by any single factor, but may reflect the disruption of several hormone-type factors acting on different timeframes . Here our results suggest that in depression these factors may converge on intracellular pathways , mitochondria and energy metabolism, and on other neurochemical pathways, such as SAT1 and polyamines - The present findings demonstrate that regional gene coordination represents a biological feature of the human brain across related areas, and that alterations in this phenomenon are useful for measuring integrated multi-scale effects in complex disorders such as depression. Our results provide the basis for further mapping of gene coordination structure onto specific functional brain networks. Indeed, the extent to which gene coordination follow the boundaries of known anatomical/functional networks is still to be determined. For instance, the amygdala is an anatomical and functional hub - Similarly, the question of a control brain region in depression is often discussed but not clarified. Indeed, it is not know whether the primary pathology of the illness is region-specific or widespread and data has been provided for both cases 1) differential expression level, 2) coregulation and 3) functional implications, which in turn require different analytical approaches. Coregulation relies on changes of small magnitude across samples that are difficult to replicate by qPCR. Our results provide a technical reason for the usual absence of such confirmatory approaches in coregulation studies, which is that the variability of qPCR measurement is higher than the one observed in array data. Such information had to our knowledge not yet been provided in the rapidly growing field of coregulation studies. Instead, coregulation methods rely on assessing the probability of confirming the observed effects in other array datasets and on the probability of results belonging to common biological pathways. Here, we provide very robust statistical findings for these two types of validation, using bootstrap and other resampling statistical approaches. An implication of these observations is that it may not be wise to rely on single key genes as modulators of the observed effects, as the statistical reliability of any individual genes is moderate, compared to the robust statistical significance of coregulated or functionally-related gene groups. Here we relied on a process of convergent confirmation of mediators of depression, across groups of genes through the well-validated Ingenuity's literature-based database.- With regards to validating gene coexpression, it is becoming increasingly clear that there are different types of independent validation of array data for: - The mostly positive coordinated patterns may be surprising, based on known biological interactions between areas and cell types. Studies in regions with well-characterized neurotransmitter structures, such as raphe/cortex or ventral tegmental area/nucleus accumbens may help resolve this question. Notably, the proposed assay  does not identify a single area of origin of disease-related changes (an intrinsic limitation of the approach), but rather suggests changes in factors supporting synchronization of gene function across brain areas in depression.- Other factors are likely engaged in the illness, for which the size and composition of the cohorts did not allow us to identify. For instance, early developmental events and indirect modulation (e.g. through monoamine regulation) may be more challenging to identify and are not necessarily well characterized in currently available functional gene networks. Finally, although we ruled out the contribution of several factors  we only speculate that function-dependent regulation may be at play in supporting the depression-related correlation shifts. Hence, it will be of critical interest to assess whether correlated patterns return to control states in remitted subjects and if such patterns are measurable in rodent models of the illness. Finally, it is notable that robust coordinated patterns were observed in a relatively small and heterogeneous cohort of subjects. Indeed, it is likely that demographic and clinical parameters, such as sex, race, lifetime stress exposure and antidepressant exposure for instance, will influence regional gene synchrony, although much larger cohorts and multi-region gene arrays datasets will be necessary to investigate the full extent of these effects. Despite all of these potentially confounding influences, gene coordination remains a strong influence on patterns of gene expression across areas, and for which alterations in depressed subjects correspond to known and suspected abnormalities in the illness.Human cohort 1  includes samples from 28 white male subjects: 14 control subjects and 14 subjects with familial major depression. Subject description, array sampling and parameters were previously described Gene-wise bootstrapped Pearson correlation r-values were used to ensure an accurate estimation of the “real” underlying distribution and to avoid spurious findings due to outlying data. Because gene coordination relies on multiple samples to form a single measure, we used the percentile bootstrap method to ensure that the shifts were robust and significant (p<0.05) and then applied the Benjamini-Hochberg FDR While methods exist to optimize cutoff values in coexpression networks While baseline comparison of age  did not www.ingenuity.com). This network is composed of ∼2 million literature-based biological links between genes and bioactive molecules, and sub-networks are built on genes of interest based on their connectivity within this global network. Gene networks were limited to 35 nodes. The score for a network takes into account the relative numbers of network eligible molecules, of molecules analyzed and the total number of molecules in Ingenuity's knowledge base. These scores are based on the hypergeometric distribution and represent the negative log of the right-tailed Fisher's Exact Test p-value. Disease links are based on literature-based association with illness. The major functions of gene clusters were determined by DAVID functional clustering (http://david.abcc.ncifcrf.gov).Selected genes were overlaid on the global molecular network developed from information contained in the Ingenuity Pathway knowledge base , we resampled the Ingenuity database 100 times of with random gene lists of equivalent sizes. The process was repeated with variable sizes of selected genes (60 to 200 genes). Finally, the probability of finding the identified modulators in the top gene networks was assessed bootstrap resampling.File S1Cohort descriptions and array parameters; AMY-ACC probeset correlations.(0.12 MB PDF)Click here for additional data file.File S2Complete per-probeset amygdala-anterior cingulate cortex coordination levels and p-values.(0.75 MB XLS)Click here for additional data file.


Mouse xenograft models, in which human cancer cells are implanted in immune-suppressed mice, have been popular for studying the mechanisms of novel therapeutic targets, tumor progression and metastasis. We hypothesized that we could exploit the interspecies genetic differences in these experiments. Our purpose is to elucidate stromal microenvironment signals from probes on human arrays unintentionally cross-hybridizing with mouse homologous genes in xenograft tumor models.By identifying cross-species hybridizing probes from sequence alignment and cross-species hybridization experiment for the human whole-genome arrays, deregulated stromal genes can be identified and then their biological significance were predicted from enrichment studies. Comparing these results with those found by the laser capture microdissection of stromal cells from tumor specimens resulted in the discovery of significantly enriched stromal biological processes.http://www.lussierlab.org/publications/StromaUsing this method, in addition to their primary endpoints, researchers can leverage xenograft experiments to better characterize the tumor microenvironment without additional costs. The Xhyb probes and R script are available at  However, genome-wide expression analyses of the tumor and its microenvironment have not kept pace. Tearing apart cancer cells from stromal tissues in whole tissue expression requires time consuming and costly laser microdissection of the tumor before RNA extraction [Characterizing the tumor microenvironment is essential as it relates to clinical prognoses, metastatic potential, and treatment-related outcomes . Innovattraction ,3. Computraction . Yet thiIn this paper, we describe a computational method of exploiting interspecies differences in the mouse tumor xenograft model in which human cancer cells are grown in immune-suppressed mice. This model is popular for studying the mechanisms of preclinical drug trials, tumor progression and the development of metastasis. Mouse xenografts consist of both human tumor cells and mouse stromal tissues , thus diTumor/stromal interactions have been examined by modeling the diffusion of the nutrients in the stroma, invasion of single cells into the stroma, and characterizing the function of the stromal elements -10. To oGO) biological processes) from deregulated genes using the human array probes unintentionally cross-hybridizing with the mouse homolog. This assumption is based on the observation that 1) the majority of the cross-hybridizing probes designed for human genes also target their mouse homolog, and 2) the majority of Gene Ontology [We hypothesized that we could identify stromal microenvironment signals .For this study, we selected the Agilent 44k whole human genome oligo microarray which allows for custom design. The Agilent microarray is designed with one or more 60-mer probes per gene rather than the more complex Affymetrix probe-sets containing multiple shorter (25-mer) probes voting for each gene  probes between human and mouse RNA were determined by combining a computational method (BLAST [(i) mouse RNA, (ii) human RNA, or (iii) both. For simplicity, these genes are hereafter referred to as “Xhyb genes” whose probes were highly expressed when exposed to mouse universal RNAs but lower when exposed to human universal RNAs. We hypothesized that the mouse-specific, and thus stromal-specific, signals are enriched in these cross-species hybridizing probes. From the identified genes with only cross-species hybridizing probes, the proportion of homologous genes between the two species were calculated. This last step was important to justify the GO enrichment studies conducted over cross-hybridizing probes of the human array that were used to produce sets of GO terms describing the biological processes in the stroma  and a bμ represents the overall mean value for a probe, i, originally designed for its Homo sapiens (Hs) target (noted as Hsiμ) or Mus musculus (Mm) homolog if cross-hybridizing (noted as Mmiμ). The notation c is the main effect of a clinical phenotype, j, additive to the probe expression. The notation ε is the stochastic error [Hsiμ+ HSjc) is stochastic (centered at zero) and thus, part of the error ε. Consequently, the equation for the expression of a cross-hybridizing probe becomes:where ic error  that incε’ represents stochastic errors. Therefore, the differential expression of a Xhyb probe between two phenotypes, a and b, is really a stromal gene response rather than a cancer cell response on a log scale:Where ε, ε’ and ε”. As shown in Figure remaining genes) that are putatively enriched in cancer cell signal, the majority of gene expressions were contributed by designed targets which reflect the tumor biological processes of human tumor tissues.We make standard stochastic assumptions about the errors A stromal GO term is contributed by genes where cross-species hybridization is more likely to occur as presented in Table Xenograft models of human cancer and mouse stroma are generally analyzed using human arrays for deregulated genes, and the expression profiles are generally attributed to the human gene's biological processes or functions. To assess the stromal effect among the reported tumor contributing genes, we searched the PubMed resource by keywords “xenograft, Agilent, cancer, gene expression”. Two of the resulting publications fit the criteria using the same platform (GEO:GPL6480) as shown in Table GOstats [Enrichment a , the list of literature-reported genes , the Xhyb subset of the literature-reported genes were compared to all Xhyb genes in the microarray that we had identified. In Enrichment c , the remaining (non-Xhyb) subset of reported genes were compared to the remaining (non-Xhyb) genes in the microarray. In Enrichment d , the subset of reported genes whose probes cross-hybridized with their mouse homolog were compared to all the genes with cross-hybridized probes on the array. Note that since we could not know which cross-hybridizing probes targeted which homolog on the entire array without experimental evidence, test d) used all genes with cross-hybridizing probes as the background resulting in an estimated statistic. Alternatively, approach b) uses an evaluation by proxy based on the observation that the majority of mouse GO Annotations were identical to human GO Annotations, and the majority of the cross-hybridizing genes target their corresponding mouse homolog  contained 61 biological processes in the differentially expressed breast stromal genes that were identified by comparing laser microdissected stromal tissues (adjusted to cancer) with paired normal epithelium [(GS2) compared gene expression profiles of breast tumor stroma captured by laser capture microdissection, and reported the overrepresented GO terms associated with poor-prognosis, good-prognosis and mixture-outcome, respectively [We validated our methodology using two gold standards; each one was based on an independently published list of biological processes (GO terms) enriched in differentially expressed genes derived from microarray experiments of cancer stroma microdissected out of whole tumors ,3. The Felium [GS comparedelium [GS comparedRgraphviz and GOstats. An additional evaluation for the union of statistically significant GO terms were performed as described in . We examined multiple conditions in the M-Xhyb3 and developed an optimized model  induction in the stroma [p=0.004), suggesting a different stromal/tumor cell cross-talk and was further demonstrated by differences in angiogenesis and in necrosis [The identified Xhyb subset of the literature-reported tumor deregulated genes is listed in Additional file e stroma . Accordinecrosis .Methods, Enrichment d) significantly overlapped with the known stromal gold standard terms as defined in Methods, Evaluation of the methodology section. As shown in Figure p=7x10-6). In contrast, none of the 15 GO terms enriched among remaining non-cross-hybridized genes  matched the GS1  overlap with GS2 (Fisher’s exact tested p=0.001). On the other hand, there was only one overlap from the remaining gene enriched GO terms   also resulted in significant overlap between the two gold standards  for Xhyb gene enriched GO terms. Noteworthy, there was no overlap between Xhyb gene enriched GO terms  and the whole tumor annotations from the subset with good prognosis. This finding corroborates the hypothesis that biological process annotations associated with poor prognosis contain more stromal components.The biological process terms associated with cross-hybridizing probes that targeted mouse homologs  Figure . MoreoveFigure  are significantly better at predicting biological processes of stromal cells when compared to the the remaining genes (Enrichment c) and the full reported gene list (Enrichment a) annotations in both studies. Conversely, Additional file Enrichment c, orange triangles) or the full gene list  are better at predicting biological processes associated to cancer cells.In addition, as presented in Additional file Limitations and future studies. This study focused on human probes that were inadvertently cross-hybridized with mouse RNAs. The confounded expression of 5,000 human and mouse genes can thus be assessed; however, these measures are limited in that they are not genome-wide. The platform-specific cross-species hybridizing probes, thus, limits our study as we are indirectly measuring the stromal microenvironment effects as compared to the direct measurements that could arguably be obtained with species-specific mouse probes.For future studies, we plan to use knowledge extracted from the literature to further refine the interpretation using BioMedLEE [ioMedLEE  in a higin silico approach allows us to extract additional stromal knowledge from current xenograft tumor arrays without needing to perform further in vivo/in vitro experiments. In future studies, we intend to examine these cross-species enrichments for biological interactions between cancer cells and stromal cells, an important initiative of the National Cancer Institute Tumor Microenvironment Think Tank [In this paper, we introduced a novel design to detect biological processes of the stroma using human arrays with probes of which approximately 25% cross-hybridized with mouse genes. We also conclude that the majority of our identified cross-hybridized genes target their corresponding homolog. Although human and mouse RNA gene expression are confounded in this subset of probes, we have demonstrated that an appropriately performed Gene Ontology enrichment analysis can identify significant stroma-associated GO terms by evaluating our findings with GO annotations from previous laser capture microdissections of the stroma. These results suggest that our method may be a reasonable alternative to laser microdissection in a specially designed chip. Our results also suggest that human chip probes cross-hybridizing with mouse genes are, in fact, over-annotated with stroma-associated biological processes. This leads us to believe that xenograft gene expression contain confounded cell signals and stromal cell signals which must be accounted for. An additional benefit of this methodology is that from a cost perspective, this ink Tank .The authors declare that they have no competing financial or other interest in relation to the work reported here.YAL supervised experiment design, computational methods, results and the manuscript redaction; XY conducted the majority of the analyses of data; YL performed the Blasten programming; HY conducts the online custom Agilent array design; HRX designed and supervised the biological experiments; YAL, HRX and YH contributed to the biological interpretation of the results; everyone contributed to the interpretation of the results. All authors read and approved the final manuscript.Click here for fileS. Table 1: Xhyb subset of previous xenograft studies reported cancer deregulated genes.S. Table 2: The significant (p<1%) GO terms among the deregulated genes in a published glioblastoma xenograft model.S. Table 3: Xhyb subset of the differential expressed genes in a previous xenograft study and their corresponding probes in the Agilent array (GPL6480).S. Table 4: Xhyb subset of the 28 deregulated genes reported by a previous colon tumor xenograft study and their corresponding Agilent array (GPL6480) probes. Genes in bold are those identified as Xhyb. According to the author , HT-29-derived 5M21 which displayed a constitutive invasive behavior in type I collagen, while TATI was shown in this study to be a major autocrine and transforming factor produced by HT-29-derived 5M21 cells to control colon cancer cell invasion and metastasis.S. Table 5: The human probes in S. Table 3 that target their mouse homologs.S. Table 6: The identified stromal associated GO terms  that also reported by two gold standards using laser microdissection technology.Click here for filep<1%) BP terms among the genes with mouse homologous cross-hybridizing probes, and their overlapping with two gold standards. The identified BP terms with their nearest parent-terms of the gold standard are listed below the network graph.Significantly enriched  are significant (proxy p<5%). Panel b shows that the Xhyb subset of deregulated genes are the worst at predicting cancer processes compared to the other two kinds of gene lists with lower precision and recall.Comparison of the overrepresented biological processes (BPs) derived from three GO en-richment tests for the reported gene list. Different data points are the proxy recall and precision under a serial of thresholds for GO enrichment test. Click here for file


Comparing the effectiveness of interventions is now a requirement for regulatory approval in several countries. It also aids in clinical and public health decision-making. However, in the absence of head-to-head randomized trials (RCTs), determining the relative effectiveness of interventions is challenging. Several methodological options are now available. We aimed to determine the comparative validity of the adjusted indirect comparisons of RCTs with the mixed treatment comparison approach.n and outcomes. We conducted fixed effects meta-analysis of each intervention versus mutual comparator and then applied the adjusted indirect comparison. We conducted a mixed treatment meta-analysis on all trials and compared the point estimates and 95% confidence/credible intervals (CIs/CrIs) to determine important differences.Using systematic searching, we identified all meta-analyses evaluating more than 3 interventions for a similar disease state with binary outcomes. We abstracted data on each clinical trial including population a priori consistency rule, we found 2 examples where the analytic comparisons were statistically significant using the mixed treatment comparison over the adjusted indirect comparisons and 1 example where this was vice versa. We found 6 examples where the direction of effect differed according to the indirect comparison method chosen and we found 9 examples where the confidence intervals were importantly different between approaches.We included data from 7 reviews that met our inclusion criteria, allowing a total of 51 comparisons. According to the In most analyses, the adjusted indirect comparison yields estimates of relative effectiveness equal to the mixed treatment comparison. In less complex indirect comparisons, where all studies share a mutual comparator, both approaches yield similar benefits. As comparisons become more complex, the mixed treatment comparison may be favoured. Acknowledging their enormous value for health intervention decision-making, clinicians, drug manufacturers, regulatory agencies and the public are now requiring meta-analysis to identify the most effective intervention among a range of alternatives. As meta-Until recently, meta-analysis addressed indirect comparisons using flawed methods that examined only intervention groups and ignored control event rates. In the lThe adjusted indirect comparison, first reported by Bucher et al., enables The multiple treatment approaches, based on developing methods by several investigators,,7most reThe adjusted indirect comparison and the mixed treatment comparison approach can be implemented through a range of methods, including frequentist, Bayesian and various subspecies of each.The basic assumptions underlying the adjusted indirect comparison and mixed treatment comparison approaches are similar to but more complex than the assumptions concerning the standard meta-analysis approach. Just like standard meta-analysis, both approaches rely on the homogeneity assumption, which states that trials are sufficiently homogeneous to be quantitatively combined. In addition, both approaches require a similarity assumption - namely, that trials are similar for moderators of relative treatment effect. The mixed treatment comparison approach also requires a consistency assumption, which is needed to quantitatively combine direct and indirect evidence.Both adjusted indirect comparison and mixed treatment comparison approaches to evaluating the relative impact of multiple alternative treatments have strengths and weaknesses. The multMeta-analysts, agencies, and readers are now attempting to gain further insight into the relative merits of the two approaches. New US gWe included systematic reviews of randomized clinical trials involving at least 4 different treatments , as networks of three health interventions have already received considerable study.,3,16 If Antifungal treatment for systemtic candida infectons: A mixed treatment comparison meta-analysis. Unpublished).. As with the mixed treatment analyses, we applied the fixed effects method. Once we obtained the summary estimates of pooled head-to-head evaluations with CIs, we applied the adjusted indirect comparison approach.a priori determined consistency rule stating that the lower and upper endpoints of the two types of intervals should not differ by more than 0.25 and 0.75, respectively, and the estimated ORs should not differ by more than 0.5. EM and IG performed all statistical analyses.For each systematic review, we determined if there were important inconsistencies between the adjusted indirect comparison and mixed treatment comparison approaches by comparing the 95% CrI produced by the former approach against the 95% CI produced by the latter approach for the OR of each feasible treatment comparison. We diagnosed inconsistency by assessing departures from an Antifungal treatment for systemtic candida infectons: A mixed treatment comparison meta-analysis. Unpublished).[Antifungal treatment for systemtic candida infectons: A mixed treatment comparison meta-analysis. Unpublished) [We identified 44 potentially relevant systematic reviews of the effectiveness of multiple treatments for different health conditions, including two of our own reviews that were ongoing during the search period . We narroblished) ,19-22witAntifungal treatment for systemtic candida infectons: A mixed treatment comparison meta-analysis. Unpublished). [Antifungal treatment for systemtic candida infectons: A mixed treatment comparison meta-analysis. Unpublished). [The seven systematic reviews retained in our analyses included between 4 and 8 treatments. Four reviews did not have a no-treatment control intervention . ,22 The nlished).  There weAnalyses 1-3 figures , 3 reprea priori consistency rule, the estimated ORs and associated uncertainty intervals were importantly different between the two approaches for only four pairwise treatment comparisons.We evaluated the impact of drug-eluting stents compared to bare-metal stents on the outcome of target lesion revascularization event rates on the basis of 18 2-arm randomised trials comparing 7 different treatments. Figure We evaluated the effects of 7 different interventions for acute pain from 29 trials that included 58 trial arms, for a possible 21 comparisons. See Figure We evaluated the role of 4 statin interventions compared to placebo/standard care for the prevention of cardiovascular mortality in primary prevention of cardiovascular disease populations. See Figure We evaluated the role of topical antibiotics for the prevention of ear discharge for patients with eardrum perforations using 18 2-arm randomised trials comparing 4 different treatments. Figure We evaluated the role of antifungal agents for preventing mortality in solid organ transplant recipients on the basis of 10 2-arm randomised trials comparing 5 different treatments. The network of evidence for these trials is shown in Figure We evaluated 4 different interventions from 22 trials with 44 trial arms, allowing a possible 6 comparisons. See Figure We evaluated the effectiveness of 8 different treatments from 19 trials, allowing 38 arms, for a possible 28 comparisons. See Figure Our paper presents important evidence on the relative performance of the adjusted indirect comparison and mixed treatment comparison approaches to evaluating multiple health interventions in the absence of sufficient direct evidence.For the 3 star-networks considered in this paper, we found that both approaches led to similar results, as they could use all the available information in the data. In general, some slight difference may exist between the results produced by the two approaches for this type of network since the adjusted indirect comparison approach uses (approximate) normal likelihood while the mixed treatment comparison approach uses (exact) binomial likelihood. If one chooses to ignore such a slight difference, the adjusted indirect comparison approach is easier to use for star-networks than the mixed treatment comparison approach.For the 2 single-loop networks included in this paper, we found that the adjusted indirect comparison and mixed treatment comparison approached yielded comparable estimates of relative treatment effectiveness. However, the two approaches will be expected to yield different results for general single-loop networks, simply because the mixed treatment comparison approach is based on all available information in the data but the adjusted indirect comparison approach is not.Finally, we found that both the adjusted indirect comparison and the mixed treatment comparison approach produced comparable estimates of relative treatment effectiveness for the two multi-loop networks considered in this paper. As pointed out by one of the referees during peer-review, in general, the adjusted indirect comparison approach may be difficult, if not impossible, to apply for this type of network. As an illustration, suppose we are interested in the indirect estimate for the OR of the pairwise comparison of treatments C and D in Figure The adjusted indirect comparison approach may be preferred for star-networks, as it is typically easier to implement than the mixed treatment comparison approach and provides similar results. For single-loop networks, one could use either approach, though the results produced by the two approaches might generally be different, reflecting the fact that the mixed treatment comparison approach relies on all of the information available in the data but the adjusted indirect comparison approach does not. For multi-loop networks, it might be difficult, if not impossible, to implement the adjusted indirect comparison approach in some situations, rendering the mixed treatment comparison as the preferred choice for this type of network.There are strengths and limitations that should be considered when interpreting this manuscript. Strengths include our extensive searching of systematic reviews and inclusion of unpublished systematic reviews. It is possible that we missed systematic reviews that may have met our inclusion criteria, however our searches were extensive, were supplemented with others' systematic reviews.,13 and wSalanti and others have discussed the merits and challenges of the mixed treatment approach.,23,24 ThFor less complex analyses, such as star-shaped networks, the adjusted indirect comparison may be easier for meta-analysts to apply in their general practice. One of us (GG) was involved in the development of this approach. The adjuThere is also concern that both the adjusted indirect comparison and mixed treatment comparison approaches will have less power than the direct approach and may sometimes lead to indeterminate results, in the form of wide uncertainty intervals for relative intervention effects. Inferences based on such findings may therefore be limited. In addition, it is not clear yet how to interpret results that differ substantially between the two approaches. Finally, although the choice of approach may differ only marginally in treatment effect estimates, the impact of small differences may affect future analyses based on study findings, such as cost-effectiveness models. There is a clear need to evaluate whether one method may importantly impact cost-effectiveness projections over another.In conclusion, both the mixed treatment comparison approach and the adjusted indirect comparison approach provide compelling inferences about the relative effectiveness of interventions. In less complex indirect comparisons, where a mutual comparator exists, the adjusted indirect comparison may be favourable due to its simplicity. In more complex models, the mixed treatment comparison appears to offer benefits for comparisons that other methods cannot.stent; BMS: bare-metal stents, PES; EES: everolimus-eluting stent; MES: micophenolate-eluting stent; PES: paclitaxel-eluting stent; SES: sirolimus-eluting stent; RCT: randomized clinical trial; OR: odds ratio; CI: confidence interval; CrI: credible interval; D: Dapsone; D/P: dapsone/pyrimethamine; AP: aerosolized pentamidine; TMP-SMX: trimethoprim-sulfamethoxazole.AES: actinomycin-d-eluting None declared. COR has previously been employed by Pfizer Ltd. and is currently employed by Merck, Sharpe & Dohme (MSD) Ltd. MSD had no role in the development, execution or publication of the paper. EM has consulted to Pfizer Ltd. and received unrestricted research grants from Pfizer Ltd., GG has received unrestricted research grants from several for-profit companies. IG runs a statistical consulting firm.COR, EM, IG and GG were responsible for the study concept. COR, EM and OE were responsible for the study searches. COR, EM, EO, IG and GG were responsible for study extraction and analysis. COR, EM, IG and GG were responsible for study writing. COR, IG, EO, GG and EM approved the submitted manuscript.


Multivesicular endosomes/bodies (MVBs) sort endocytosed proteins to different destinations. Many lysosomally directed membrane proteins are sorted onto intralumenal vesicles, whilst recycling proteins remain on the perimeter membrane from where they are removed via tubular extensions. MVBs move to the cell centre during this maturation process and, when all recycling proteins have been removed, fuse with lysosomes. Recent advances have identified endosomal-sorting complex required for transport (ESCRT)-dependent and ESCRT-independent pathways in intralumenal vesicle formation and mechanisms for sorting recycling cargo into tubules. Cytoskeletal motors, through interactions with these machineries and by regulating MVB movement, help to co-ordinate events leading to a mature, fusion-competent MVB. The early endosome is a pleiomorphic structure composed of vacuolar and tubular domains that exhibit extensive connectivity but maintain their identity by virtue of their specific complement of Rab GTPases see . With tiGiven the iterative nature of receptor recycling coupled with the high fidelity of sorting achieved, it is not surprising that MVB maturation can be extended (30 min or more in EGF-stimulated cells ); perhapHere we review recent data pointing towards mechanisms underlying intralumenal vesicle formation and the generation of recycling tubules and discuss how molecular connections between these events and membrane movement could contribute to the co-ordination of MVB maturation.VPS) mutants in yeast and collectively termed Class E VPS proteins. These proteins package cargo onto intralumenal vesicles of MVBs. Most Class E VPS proteins are found within the endosomal-sorting complex required for transport (ESCRT) 0–III, and the role of these complexes in sorting ubiquitinated cargo has recently been reviewed elsewhere [Lysosomal targeting of endocytosed membrane proteins requires specific signals, of which the best characterised is ubiquitination. Ubiquitinated cargo engages a series of proteins/protein complexes, first identified from studies of vacuolar protein sorting  could achieve this. CHMPs are likely to multimerise to form a flat lattice on the perimeter membrane of the endosome •. Such lHowever, despite the range of structural data, evidence for a direct role for ESCRTIII in intralumenal vesicle formation remains elusive. In mammalian cells, for example, although depletion of a component of ESCRTIII, VPS24/CHMP3, reduced the number of internal vesicles per MVB, EGFRs were still sorted onto the smaller number of intralumenal vesicles that formed . This imAlthough ESCRTs may well play a role in intralumenal vesicle formation, accumulating data suggest that, at least in mammalian cells, other mechanisms/machineries also participate in this process and that an interaction of the protein machinery with the lipids of the underlying membrane is crucial to both ESCRT-dependent and ESCRT-independent mechanisms.2. ESCRTIII binds PI3,5P2 [LBPA is a cone-shaped lipid that has been implicated in either inward vesiculation or back-fusion of internal vesicles with the limiting membrane in a manner promoted by Alix, which binds to LBPA-containing liposomes . Alix pr PI3,5P2 , which m PI3,5P2 . Perturb PI3,5P2 , but MVB PI3,5P2 , suggest PI3,5P2 . This coin vitro and so one possible mode of action is for it to bring opposing membranes of the invaginating intralumenal bud together to promote fission [EGF-stimulated intralumenal vesicle formation requires the calcium-binding and phospholipid-binding protein, annexin 1 •. Annexi fission .Further evidence of ESCRT-independent pathways of intralumenal vesicle formation has come from studying the protein Pmel17, a main component of the c fibrils of premelanosomes, which is targeted to intralumenal vesicles of MVBs independently of ubiquitination, ESCRT0 and ESCRTI . HoweverAs EGFR is concentrated into intralumenal vesicles, membrane cargoes destined for a range of other compartments are filtered away into tubular elements (reviewed in ). ‘GeomeMannose-6-phosphate receptors (MPRs) deliver soluble hydrolases to the endosomal system. After ligand dissociation, the vacant receptors return to the TGN. Retrieval may occur at different points during endosomal maturation, with each pathway using a distinct sorting apparatus. One population of MPR is retrieved late, consistent with the localisation of a portion of MPR to mature MVB •. Routinin vitro [MPR and sortilin localise to SNX1-enriched tubules (termed endosome–TGN transport carriers or ETCs) that emanate from relatively early MVBs. Indeed, retromer links cargo selection with tubule generation, since the VPS26/29/35 retromer subcomplex binds cargo  and clusin vitro ••.Transferrin receptor (TfR) is recycled from the early endosome back to the cell surface, either directly, or more slowly via an endosomal-recycling compartment (ERC). TfR is found within a convoluted tubular endosomal network (TEN) , which cOne emerging area of interest is the role of cytoskeletal motors in separating recycling receptors away from degradative cargo and delivering them to their target organelles. The early endosome moves towards the cell centre as it matures. This movement is mediated by cytoplasmic dynein (dynein ), a minuin vitro when dynein is present [in vivo [An important question yet to be addressed is whether cytoskeletal motors merely translocate pre-formed tubular carriers towards their target, or contribute to the formation, extension or scission of recycling tubules. Certainly, SNX1 tubules require microtubules for their stability •. In add present . The ten present  and this present , scissio[in vivo ••. EHD p[in vivo ••. Howev[in vivo , presuma[in vivo •. In add[in vivo  and myos[in vivo .MVB maturity is marked by the complete removal of recycling proteins and the acquisition of the ability to fuse with the lysosome. How are the two co-ordinated? One way would be to ensure that MVBs and lysosomes do not come into close proximity until recycling proteins have been removed. Dynein not only regulates removal of TfR from the maturing MVB and movement of the MVB to the cell centre  but alsoProteins on the MVB required for MVB–lysosome fusion include Rab7, the tethering proteins, which comprise the HOPs and CORVET complexes, and a specific set of SNAREs (reviewed in ). The HOThe past few years have seen a great advance in our understanding of the molecular requirements for the events leading to MVB maturation. Components needed for inward and outward budding of the MVB perimeter membrane to generate intralumenal vesicles and recycling tubules, respectively, have begun to be identified. However, the mechanics of these processes are not yet clear and the requirements for scission of intralumenal vesicles and recycling tubules remain unknown. Some of the machinery required for cargo selection, intralumenal vesicle formation, recycling tubule formation and MVB–lysosome fusion interact with each other, with Rab proteins and with components of the cytoskeleton. Determining how these processes are coupled mechanistically and hence co-ordinate MVB maturation is a major future challenge.• of special interest•• of outstanding interestPapers of particular interest, published within the period of review, have been highlighted as:


EvoPrinter, a web-accessed genomics tool that provides a single uninterrupted view of conserved sequences as they appear in a species of interest. An EvoPrint reveals with near base-pair resolution those sequences that are essential for gene function.Multi-genome comparative analysis has yielded important insights into the molecular details of gene regulation. We have developed EvoPrinterHD, a 2nd-generation comparative genomics tool that automatically generates from a single input sequence an enhanced view of sequence conservation between evolutionarily distant species. Currently available for 5 nematode, 3 mosquito, 12 Drosophila, 20 vertebrate, 17 Staphylococcus and 20 enteric bacteria genomes, EvoPrinterHD employs a modified BLAT algorithm [enhanced-BLAT (eBLAT)], which detects up to 75% more conserved bases than identified by the BLAT alignments used in the earlier EvoPrinter program. The new program also identifies conserved sequences within rearranged DNA, highlights repetitive DNA, and detects sequencing gaps. EvoPrinterHD currently holds over 112 billion bp of indexed genomes in memory and has the flexibility of selecting a subset of genomes for analysis. An EvoDifferences profile is also generated to portray conserved sequences that are uniquely lost in any one of the orthologs. Finally, EvoPrinterHD incorporates options that allow for (1) re-initiation of the analysis using a different genome's aligning region as the reference DNA to detect species-specific changes in less-conserved regions, (2) rapid extraction and curation of conserved sequences, and (3) for bacteria, identifies unique or uniquely shared sequences present in subsets of genomes.We describe here EvoPrinterHD is a fast, high-resolution comparative genomics tool that automatically generates an uninterrupted species-centric view of sequence conservation and enables the discovery of conserved sequences within rearranged DNA. When combined with cis-Decoder, a program that discovers sequence elements shared among tissue specific enhancers, EvoPrinterHD facilitates the analysis of conserved sequences that are essential for coordinate gene regulation. EvoPrinterHD is a second-generation alignment tool that automates the comparative analysis to rapidly identify a significantly higher percentage of conserved sequences shared among evolutionarily distant orthologs even if they exist within rearranged DNA. In contrast to most comparative multi-sequence alignment tools . We hrthologs . Generatrthologs , an EvoPiewed by ), which EvoPrinter alignment algorithms is the BLAT algorithm .The mosquito genome sequence files for ASY, YL and YF participated in the design and implementation of the algorithms. JR participated in the web page design and tutorial. TB and WFO conceived the study, participated in the design and coordination of the algorithms and prepared the manuscript. All authors have read and approved the final draft of the manuscript.


In this study, the role of spastin was examined in Drosophila photoreceptor development.Mutations in spastin mutation in developing pupal eyes causes a mild mislocalization of the apical membrane domain at the distal section, but the apical domain was dramatically reduced at the proximal section of the developing pupal eye. Since the rhabdomeres in developing pupal eyes grow from distal to proximal, this phenotype strongly suggests that spastin is required for apical domain maintenance during rhabdomere elongation. This role of spastin in apical domain modulation was further supported by spastin's gain-of-function phenotype. Spastin overexpression in photoreceptors caused the expansion of the apical membrane domain from apical to basolateral in the developing photoreceptor. Although the localizations of the apical domain and adherens junctions (AJs) were severely expanded, there were no defects in cell polarity.The spastin is essential for apical domain biogenesis during rhabdomere elongation in Drosophila photoreceptor morphogenesis.These results strongly suggest that  Hereditary spastic paraplegia (HSP) comprises a heterogeneous group of neurological disorders Drosophila is an attractive system for testing in vivo function of spastin. Drosophila contains a highly conserved spastin homolog Drosophila spastin were analyzed in developing neuromuscular junctions using genetic mutational studies. Together, these data provide the first in vivo evidence that Spastin regulates microtubule stability and show that this function of Spastin strongly modulates both synaptic architecture and neurotransmission strength in neuromuscular junctions Drosophila eye. Photoreceptor cells are formed in eye imaginal discs of third-instar larvae. During pupal development, photoreceptor cells undergo the distal to proximal elongation  stage, Crb remains at the apical surface of photoreceptors. At 45% pd , Crb begDrosophila photoreceptors, these stable microtubules may have some potential functions for photoreceptor development.The developing pupal eyes at 45% pd stage were checked by the anti acetylated-tubulin antibody. The acetylated-tubulin is highly enriched in the basal to apical domain , betweenDrosophila homolog of Spastin appears to affect the abundance and distribution of acetylated microtubules in Drosophila neuromuscular junctions Drosophila photoreceptor development, the subcellular localization of Spastin in the mid-stage developing pupal eyes (45% pd) was examined by immunostaining and confocal microscopy. Spastin is highly enriched in the stable microtubules , 1∶1000; mouse anti-α-tubulin (Sigma), 1∶500; mouse anti-β-tubulin (Sigma), 1∶500; rat anti-DE-cadherin (DSHB), 1∶10; rat anti-Crb


Myocardial involvement is an important prognostic factor in patients with systemic sclerosis, and early diagnosis and staging of the disease have been sought after. Since myocardial damage is characterized by connective tissue disease, including fibrosis and diffuse vascular lesions or microcirculation, nuclear myocardial perfusion imaging has been a promising option for evaluating myocardial damages in early stages. In addition to the conventional stress-rest perfusion imaging, the current use of quantitative electrocardiographic gated imaging has contributed to more precise evaluation of cardiac perfusion, ventricular wall motion, and diastolic function, all of which have enhanced diagnostic ability of evaluating myocardial dysfunction. Abnormal sympathetic imaging with Iodine-123 metaiodobenzylguanidine might be another option for identifying myocardial damage. This paper deals with approaches from nuclear cardiology to detect perfusion and functional abnormality as an early sign of myocardial involvement as well as possible prognostic values in patients with abnormal imaging results. The role of nuclear cardiology in the era of multiple imaging modalities is discussed. Systemic sclerosis (SSc) is a connective tissue disease characterized by diffuse vascular lesions and fibrosis, and it systemically involves various organs such as skin (scleroderma), heart, lung, kidney and gastrointestinal tracts –6. Of th201Tl) myocardial perfusion imaging [SSc is usually classified into two subsets of diffuse and limited cutaneous types (dcSSc and lcSSc) . The maj imaging . A resea imaging . It was  imaging –13.In nuclear cardiology, myocardial perfusion imaging has been used extensively for evaluating coronary artery disease, which includes diagnosis of ischemic heart disease, physiological assessment of known coronary stenosis, viability assessment after acute coronary syndrome, reevaluation after coronary intervention, and risk stratification for future cardiac events . The dia201Tl perfusion imaging with circumferential profile analysis that added quantitative support [201Tl [201Tl defects [201Tl and Technetium-99m (99mTc)-labeled radiopharmaceuticals have shown that either stress-induced ischemia or persistent perfusion defects occur in SSc patients [201Tl SPECT in patients with SSc and systemic lupus erythematosus showed a high incidence of (82%) of abnormal findings by 201Tl SPECT [In more than three decades of history of nuclear medicine in cardiology, an early finding of myocardial perfusion abnormality in SSc was documented in 1984 by planar  support , 17. Cort [201Tl . The autpatients –24. AfteTl SPECT . The aut201Tl myocardial perfusion: the mean number of segments with perfusion defects decreased from resting condition after dipyridamole [201Tl myocardial perfusion with nifedipine in patients with progressive systemic sclerosis [Based on a pathophysiological viewpoint, abnormalities of microcirculation seemed to play an important role leading to myocardial damages . Focal mridamole . The samclerosis . In cont201Tl scanning, except for subtle abnormality [201Tl perfusion defects appeared to be related to left ventricular function, which showed that patients with perfusion defect had scores above the median value. In contrast, several patients with diffuse scleroderma had prominently abnormal EF at rest with further prominent deterioration during exercise [Resting left ventricular ejection fraction (EF) and its response to exercise also appeared to be unrelated to the findings on ormality . Howeverexercise . Thus, a99mTc methoxy-isobutyl-isonitrile (MIBI) study with ECG-gating of 16 frames per cardiac cycle in 34 patients with SSc [In a Japanese population, we performed a stress with SSc . Comparewith SSc , 31. A dwith SSc , 33. Diastolic dysfunction as detected by either gated myocardial perfusion imaging or radionuclide ventriculography was not specific to the findings of SSc. Diastolic dysfunction may have occurred even without any systolic dysfunction in patients with ischemic heart disease, hypertrophic cardiomyopathy, hypertensive heart diseases, and secondary cardiomyopathies –37. In pThus, we postulate that myocardial perfusion SPECT abnormality is correlated to the severity of cardiac dysfunction. In mild dysfunctional patients, even when left ventricular contractility is normal, diastolic dysfunction may be related in some cases. A stress myocardial perfusion scan might show reversible perfusion defect in patients with mild to moderate severity. In patients with more advanced severe dysfunction, fixed perfusion defects and regional wall motion abnormality would occur accompanied by global decrease in EF. However, whether or not the slight degree of perfusion abnormality and diastolic dysfunction would result in further deterioration of cardiac function should be investigated in a long-term follow-up study.The reason for the relatively low incidence of perfusion abnormality in our study might be explained by the selection bias of our study population, which might not have included the severer type of SSc. As for another possible reason, it might have been caused by differences in the sex and race of the patients, since ethnic differences have also been demonstrated in a Japanese population , 39.Our experience with SSc patients has shown that large perfusion defects and induced ischemia do not seem to be so common as described previously. Instead, small regional abnormality has become evident by the help of quantitative analysis. Current nuclear cardiology technology uses sophisticated computer-aided diagnosis for quantification. As an example, a patient with SSc is shown in 99mTc MIBI using stress-rest protocol. During exercise, only a slight decrease in perfusion was observed in the apical anteroseptal walls. A polar map display, with a 17-segment model overlaid, showed a localized decrease in perfusion in the anteroseptal region. The summed stress score and rest score namely, semi-quantitative defect scores during exercise and at rest were 3 and 1, which was judged as only a slight abnormality. In the polar map, wall motion and systolic thickening were apparently reduced in the anteroseptal region, particularly after exercise. A three-dimensional ventricular contour display showed apical anterior hypokinesis. A volume curve by gated SPECT showed characteristics of diastolic dysfunction. The time to peak filling rate (TPFR) as defined from the time points from end-systole to peak filling rate was prolonged to 352 msec ). The early diastolic parameter of 1/3 mean filling rate was 0.94 /sec ) [A 66-year old male patient diagnosed with dcSSc was referred to our department for nuclear cardiology for the purpose of evaluating possible cardiac involvement. His onset of disease was Raynaud's phenomenon 5 years ago prior to his visit. Scleroderma progressed since 2 years ago extending from hands, forearms, anterior chest to abdominal skin, and the MRSS indicated moderate severity (score 25 of 51). Significant pulmonary fibrosis was observed by X-ray computed tomography (CT). Myocardial perfusion SPECT was performed with 0 /sec)) . Instead123I-metaiodobenzylguanidine (MIBG) studies [123I-MIBG is known as an analogue of norepinephrine and shares its metabolic pathways with catecholamine uptake and excretion. Sympathetic abnormality has been detected by decreased uptake and rapid clearance from the heart. Initial experiences of MIBG support its use in ischemic heart diseases, typically shown as regional denervation of the heart in acute coronary syndromes and cardiomyopathies. Currently, 123I-MIBG has been used for patients with heart failure as well as neurological disorders involving Lewy-body diseases [Myocardial perfusion imaging is fundamental for evaluating myocardial damage. In addition, patients with SSc have a high frequency of diastolic dysfunction and sympathetic abnormality as shown by  studies , 42. 123diseases –45. It hdiseases ). MIBG wdiseases ). In condiseases , 48. How123I-MIBG provided additional discrimination in analyses of interactions between B-type natriuretic peptide, LVEF and H/M ratio. Although pathophysiological evidences of heart failure in the study could not be readily applicable to SSc patients, the MIBG imaging may provide new insights into the nature and prognosis of myocardial damage in SSc.The use of MIBG imaging has also been validated by a large prognostic multicenter trial in patients with heart failure of New York Hear Association (NYHA) functional class II/III and LVEF of 35% or less . The two111In-antimyosin antibody, which was a marker of the myocardial damage or necrosis [An article reported a case of systemic sclerosis with a subacute episode of myocardial disease assessed by necrosis . However201Tl perfusion defect. A study followed up 48 patients who underwent a perfusion scan in the 1980s. Notably, the survival information over the last 10 years revealed that the size of the initial defect was the best predictor of later adverse events compared with other disease-related features. These kinds of long-term prognostic study, which has been accumulating in the field of coronary artery disease, should also be conducted in SSc patients both retrospectively and prospectively.Large-scale prospective cohort studies have been performed extensively in the field of coronary artery disease, although such prognostic studies are still limited in patients with SSc. However, it has been recognized that cardiopulmonary involvement has been considered to be a poor prognostic factor since renal involvement is no longer a major cause of death in SSc, , 27, 51.Although we have focused on nuclear cardiology methods, echocardiography remains the mainstream tool for heart evaluation in SSc patients , 27, 53.When cardiac abnormalities are suspected by the initial screening tests, the next step would be diverse, depending on the clinical problems in the individual patient. In patients with pulmonary arterial hypertension (PAH), guidelines from both the American College of Chest Physicians (ACCP) and European Society for PAH recommended chest-X-ray, ECG and Doppler echocardiography as evidence-based approaches , 55. TheAccording to our study, it is apparent that all patients diagnosed with SSc are not indicated for a SPECT study. Based on our study population, it is noteworthy that patients with the lcSSc type or MRSS less than 10 showed neither significant perfusion defect nor ventricular dysfunction . TherefoThe best diagnostic approach or decision tree for cardiac evaluation has not been defined yet, although chest X-ray and echocardiography would be the first-step imaging method readily available in any hospital. While several possible diagnostic approaches have been proposed, some of them might have practical values for diagnosis, and others may provide pathophysiological insight or prognostic information. The determination of the appropriate role of imaging is of great concern in the era of multimodality cardiac imaging.Myocardial involvement as part of diffuse organ fibrosis and vascular changes is commonly observed in SSc. Even when severe fibrosis as evidenced by myocardial perfusion defects is not observed, perfusion reserves or functional abnormality might be detected as an earlier sign of myocardial damage. The aid of computer-assisted diagnosis will enhance the diagnostic ability for identifying abnormalities. The relationship of nuclear imaging and prognosis should be evaluated to confirm the role of functional imaging for patients with SSc. Finally, the roles or effectiveness of various current imaging modalities remain to be defined.