As a critical process during embryonic development, cancer progression and cell fate conversions, epithelial-mesenchymal transition (EMT) has been extensively studied over the last several decades. To further understand the nature of EMT, we performed meta-analysis of multiple microarray datasets to identify the related generic signature. In this study, 24 human and 17 mouse microarray datasets were integrated to identify conserved gene expression changes in different types of EMT. Our integrative analysis revealed that there is low agreement among the list of the identified signature genes and three other lists in previous studies. Since removing the datasets with weakly-induced EMT from the analysis did not significantly improve the overlapping in the signature-gene lists, we hypothesized the existence of different types of EMT. This hypothesis was further supported by the grouping of 74 human EMT-induction samples into five distinct clusters, and the identification of distinct pathways in these different clusters of EMT samples. The five clusters of EMT-induction samples also improves the understanding of the characteristics of different EMT types. Therefore, we concluded the existence of different types of EMT was the possible reason for its complex role in multiple biological processes. It is w decades , 3. Howe decades , 5. SuchOn the other hand, a sequential process including an early EMT and a late MET is also interesting. During cancer progression, MET has been reported after cancer metastasis or when cells re-gain epithelial characteristics at secondary tumor sites . MultiplIn previous studies, multiple investigations were performed to identify the conserved gene expression changes across different EMT. In 2012, a 130-gene list (referred as PO-list in following text) was identified from 18 published Gene Expression Omnibus (GEO) datasets to characterize EMT . In addiIn this study, 74 paired samples from 24 human microarray datasets and 31 paired samples from 17 mouse microarray datasets were analyzed together to identify generic signatures for EMT, and compared with the previous three reported lists, PO-list, EM-list, and SC-list. We clustered the paired samples and analyzed the clusters to demonstrate the possible existence of different types of EMT. In addition, we further validated the hypothesis by removing samples with weakly-induced EMT and functional analysis by Gene Ontology and pathways.All the datasets were downloaded from GEO. Searching “epithelial-mesenchymal transition” or “EMT” in GEO resulted in 144 human and 59 mouse microarray datasets. We first removed the datasets that focus on primary cancer sample/tissues because of the complexity in cancer initiation and the difficulty in identifying proper controls to determine the intensity of induced-EMT. Secondly, only the datasets for studying the EMT induced by transforming growth factor-β (TGFβ) or Snai1/Snai2/Twist over-expression were selected for further analysis, since it is widely accepted that these genes induce typical EMT , 22. TheThe biological replicates of the same treatment were averaged and further normalized with the control samples. If there are multiple treatments to induce EMT in one dataset, the same control sample was used. In the two-channel array datasets, dual fluorescence dyes are labeled in both treatment and control samples for the ratio, the normalizing step was omitted for these datasets. Finally, the probes measuring the expression of the same gene were averaged in all the samples.http://informatics.jax.org/)). The same list for human genes was downloaded from HUGO Gene Nomenclature Committee . The gene names in each dataset were replaced with their official symbols in the downloaded annotations. The gene names that were not included in the two lists were manually searched in NCBI and Ensemble datasets to identify their official symbols. The datasets were merged based on the official symbols. The results were then transformed into log2 values. Finally, the data tables  was utilized to find the dissimilarity between every pair of samples in the integrated datasets. The samples were merged in close proximity using the farthest neighbor clustering method in linkage criteria, i.e. complete linkage. In each iteration, the current clusters were further grouped into larger clusters until the complete hierarchical tree was formed. In the hierarchical tree, the samples with more similar expression profiles are connected by deeper branches. The hierarchical clustering results for human and mouse data were used for further analyses. The pairwise correlation coefficients matrices are shown under the hierarchical trees.To further validate the hierarchical clustering, a consensus clustering method that has been widely applied to gene expression data analysis for robust clustering was also used to cluster 74 human and 31 mouse EMT-induction pairs .2 values of expression changes in selected EMT-induction samples with two-tailed student t-test. The t-test was applied to all the EMT-induction samples to identity the overall generic signature and the samples in each cluster to identify cluster-specific signature. The significant gene expression changes were identified with human and mouse EMT-induction samples separately. To identify EMT generic signature conserved in both human and mouse, the mouse gene symbols and human gene symbols were converged to match their homologous genes (if available) with the annotation from MGI. In the comparison, 579 genes up-regulated/down-regulated in 31 mouse and 74 human EMT-induction samples were summarized in Significant gene expression changes  were identified by analyzing log2 values in Cluster I should be over 0.585 or below -0.585 (over 150% or below 67%). The p-value criteria for the other four clusters was also 0.05, while the expression criteria were ±0.585,±1.322 (>250% or <40%), ±0.585, and ±0.322(>125% or < 80%) for Cluster II, III, IV, and V, respectively.Significant gene expression changes in human clusters were identified with slightly modification in order to identify similar number of expression changes in each cluster. For example, in addition to a smaller p-value less than 0.05, the average of the logPO-list contained 130 genes and was obtained from the EMT generic signature identified previously . The 377Cdh1 and Cdh2 are widely accepted EMT markers and have been identify in almost all lists [Cdh2 and down-regulation of Cdh1 during EMT were used as the forth scoring system to evaluate the induced EMT in different samples. The four scoring systems were used independently and weighted equally during the evaluation.To derive the levels of induced EMT in each sample, four scoring systems were used to evaluate the induced EMT. The expression changes of 128 genes  in PO-list and 407 genes  in EM-list were used to score each EMT-induction sample . In addill lists , the up-Cdh1/2. The SC-list is not included because the gene list was curated from literature instead of being derived from experimental data. The genes in all the four scoring system were classified as mesenchymal genes and epithelial genes depending on previous reports [2 values of mesenchymal gene expression changes minus the average log2 values of epithelial gene expression changes to obtain the score for evaluation. The scores in each evaluation system were further normalized by the average score of all EMT-induction samples, and the final score for each EMT-induction samples was generated by averaging the four normalized scores. Genes in these four scoring system were used to evaluate mouse EMT-induction samples only if they have homologous between human and mouse basing on homologous information from MGI.Four scoring systems based on different gene lists were used to score each EMT-induction sample separately. The four gene lists were, 128 genes in PO-list, 407 genes in EM-list, 107 genes identified in at least two of those three lists, and the gene  reports , 14. ForThe EMT-induction samples with a final score lower than 0.10 were classified as samples with weakly-induced EMT, while the other classified as samples with strong or medium EMT by a threshold of 0.45 in human and at 0.70 in mouse.When evaluating the EMT during neuron trans-differentiation, the scores of all 31 mouse EMT-induction samples were further normalized by the mean into comparable scores among mouse EMT-induction samples.2 values of gene with opposite expression changes from the summary of genes with consistent expression changes.Overlapping score between EMT during neuron trans-differentiation and those in one of the five clusters was calculated by subtracting the absolute logKyoto Encyclopedia of Genes and Genomes annotation analysis were performed with DAVID (https://david.ncifcrf.gov/) [GO and rf.gov/) , 25.The statistical analysis was performed with GraphPad Prism 5.0. The build-in packages for two-tailed student t-test, one-way ANOVA with Dunnett’s test as a post-hoc, and Fisher’s Exact test were used.To identify the generic signature of EMT, 24 human and 17 mouse microarray datasets were downloaded from GEO and processed as described in Materials and Methods . After iCdh2, Fn1, Tgfb1/2, and Zeb2  were only identified in one list . The thrCdh1/2, Fn1, and Epcam, which are highly linked to cell adhesion and cell mobility, each type might engage distinct mechanisms and pathways involved in the EMT.If removing the samples with weakly-induced EMT did not improve the overlapping significantly, the different levels of EMT-induction should not be the major reason for the low overlapping rates. Thus, we further investigate another possibility that there were multiple types of EMT. Although the different types of EMT shared some generic signatures like To test the hypothesis mentioned above, the 74 human and 31 mouse EMT-induction samples were subjected for clustering analysis. As indicated in To further confirm the clustering results, consensus clustering  which isBy using a modified strategy , the five clusters of human EMT-induction samples were used to establish five gene lists, which contained 2631 genes together with only about 13% genes been identified in more than one cluster . The lowThe 2631 genes identified in each cluster were then subjected for GO and KEGG analysis. The GO annotation terms with significant enrichment in any one of the five clusters were then used for further analysis. Although there were only about 13% of the 2631 genes been identified in more than one cluster, there were several GO terms with significant enrichment in at least three clusters . These GSox2, Eed and Sp1 were only identified in Cluster I. Since Sox2 highly expresses in stem cells such as pluripotent stem cells and neuron stem cells, we hypothesized this Cluster I EMT as stemness EMT, which will provide new information for understanding the roles that EMT play during cancer progression and generation of iPSCs [The genes identified in the five clusters of human EMT-induction samples also revealed significant differences in the enriched functions and pathways. The enrichment analysis by GO and KEGG suggested that genes identified in Cluster I were enriched on stem cell maintenance, glucosylation and glycosphingolipid biosynthesis (KEGG) , possiblof iPSCs , 11.Cdh1, Fn1, and Tuba1a were identified in this cluster, suggesting this EMT was highly related to re-organization of cell-cell contact. In addition, samples in Cluster II have the highest EMT scores than samples in other clusters , which have enhanced tumorigenicity, partial stemness as in self-renewal and differentiation, and CD44 surface , 64. Indpulation . Up-regupulation . In addi SC-list . The shaIntroducing certain transcriptional factors could induce direct trans-differentiations from somatic cells to functional neurons , 67 and Ezh2, Kdm3a, Ctbp1 and Bmi1 were only identified in SC-list, which was manually curated from literature and could not be considered as the generic signature for EMT. The low identification of genes related to epigenetic modulation might due to the changes in protein activity can not be revealed in microarray analysis or the expression changes of these genes are not conserved among different EMT. By grouping the 74 human EMT-induction samples into five clusters, several genes related to epigenetic modulation was identified  and normal stem cells of the corresponding tissue differed significantly in details. Taking This study clustered the EMT samples into five clusters that represent five types of EMT. These five types of EMT had no difference in the intensities of induced EMT but explained the low productivity of previously identified generic signatures.S1 Table24 human and 17 mouse microarray datasets were selected and used for current analysis. The detailed information of species, GEO accession number (GEO Acc. No.), cell types, EMT inducers, platform used for micro-array analysis, number of samples under corresponding GEO accession number (Sample No.), Remarks , and related publication for each dataset was included.(XLSX)Click here for additional data file.S2 Table24 human microarray datasets were merged under the official gene symbols provided by HGNC. Experiment with treatment and its corresponding control were considered as one EMT-induction pair, and the log2 values of the gene expression ratio in this EMT-induction pair were applied in the analysis. 74 human EMT-induction pairs were listed in the table.(XLSX)Click here for additional data file.S3 Table17 mouse microarray datasets were merged under the official gene symbols provided by MGI. Experiment with treatment and its corresponding control were considered as one EMT-induction pair, and the log2 values of the gene expression ratio in this EMT-induction pair were applied in the analysis. 31 mouse EMT-induction pairs were listed in the table.(XLSX)Click here for additional data file.S4 Table579 genes which had significant expression changes in human samples and their homologues had significant changes in mouse samples were listed with official symbol, ensemble gene ID, p-values and averages. The official symbol, ensemble gene ID, p-values and averages of their homologues in mouse samples were also listed.(XLSX)Click here for additional data file.S5 TableGenes in PO-list, EM-list, and SC-list were combined together to generate an 805-gene list. This list was further shortened to a 773-gene list because of missing in current analysis. The genes used in the four scoring systems to evaluate EMT were marked.(XLSX)Click here for additional data file.S6 Table74 human and 31 mouse EMT-induction samples were evaluated with four scoring systems to determine the degree of induced EMT. The scores from four scoring systems and the normalized scores with average scores of human and mouse samples were provided. The classification and grouping of all the 105 samples were also listed.(XLSX)Click here for additional data file.S7 Table105 EMT-induction samples were classified into three groups with distinct EMT induced, strong, medium and weak. Three gene lists were generated from these three groups of samples.(XLSX)Click here for additional data file.S8 TableGene expression changes in 74 human and 31 mouse EMT-induction samples were clustered with consensus clustering method again to confirm the five clusters generated with hierarchical clustering. K was set from 2 to 10 for human or mouse samples. The resulted cluster number of provided.(XLSX)Click here for additional data file.S9 Table74 human EMT-induction samples were grouped into five clusters. Five gene lists were generated from these three five clusters.(XLSX)Click here for additional data file.S10 Table74 human EMT-induction samples were grouped into five clusters. Five gene lists were generated from these three five clusters and subjected for GO analysis. The Go terms with significant enrichment in any one of the five lists were list in the table. Some GO terms were clustered together and listed in Figs (XLSX)Click here for additional data file.


This study discusses improvement of popular rice varieties under drought through the identification and marker-assisted introgression of drought yield QTLs without any adverse effect on yield under normal conditions. qDTY1.1, qDTY2.2, qDTY3.1, qDTY3.2, qDTY6.1, and qDTY12.1) showed an effect against two or more high-yielding genetic backgrounds in both the lowland and upland ecosystem, indicating their usefulness in increasing the grain yield of rice under drought. The yield of popular rice varieties IR64 and Vandana has been successfully improved through a well-planned marker-assisted backcross breeding approach, and QTL introgression in several other popular varieties is in progress. The identification of large-effect QTLs for grain yield under drought and the higher yield increase under drought obtained through the use of these QTLs  indicate that rice, because of its continuous cultivation in two diverse ecosystems , has benefited from the existence of larger genetic variability than in other cereals. This can be successfully exploited using marker-assisted breeding.The increased occurrence and severity of drought stress have led to a high yield decline in rice in recent years in drought-affected areas. Drought research at the International Rice Research Institute (IRRI) over the past decade has concentrated on direct selection for grain yield under drought. This approach has led to the successful development and release of 17 high-yielding drought-tolerant rice varieties in South Asia, Southeast Asia, and Africa. In addition to this, 14 quantitative trait loci (QTLs) showing a large effect against high-yielding drought-susceptible popular varieties were identified using grain yield as a selection criterion. Six of these ( Around 90% of rice is grown and consumed in Asia. The semi-aquatic nature of rice and high water requirements for its cultivation make it much more prone to losses from drought than other cereals such as wheat and maize, which are better adapted to be grown with less water. As a result of the reduction in water availability and recent climate change scenarios, rice production is likely to be more severely affected by drought in Asia. Prior to the Green Revolution, traditional varieties adapted to the respective rice-growing ecosystems were cultivated across these areas. However, in the post-Green Revolution era, these varieties were replaced by a few fertilizer-responsive high-yielding varieties adapted to the irrigated ecosystem. These varieties were never screened for tolerance of drought and they suffer heavy yield losses even under mild stress conditions  identification programmes were started, using yield as a selection criterion. This manuscript reports on the progress achieved in developing drought-tolerant varieties through new conventional breeding approaches based on direct selection for grain yield under drought, the identification of large-effect QTLs for grain yield under drought, and marker-assisted breeding using the identified QTLs to improve the grain yield of popular high-yielding but drought-susceptible varieties under drought.Aus, Indica, and Basmati accessions. These accessions were evaluated for drought tolerance along with popular high-yielding varieties such as IR64, Swarna, and Sambha Mahsuri as checks, using grain yield as the selection criterion. Drought-tolerant lines identified through these experiments were evaluated for rice blast disease (caused by Magnaporthe oryzae) to identify lines tolerant of both drought and blast. These tolerant lines were crossed to popular high-yielding varieties to develop segregating populations for conventional breeding programmes and for developing mapping populations. Three main kinds of mapping populations were commonly used for the identification of QTLs for grain yield under drought. The first of these were recombinant inbred lines (RILs) developed by crossing two parents contrasting for the trait of interest followed by subsequent selfing and advancement through the single seed descent (SSD) method to achieve nearly homozygous lines (n=1–3) followed by self-pollination through the SSD method to develop BCnF3:4 populations. Advanced backcross (AB) populations proved to be specifically advantageous as they allowed the identification of lines with high yield potential and good plant and grain type because of the high percentage of the recipient parent. These could be used directly for testing and release in the target environment or could be used as parents for further backcross programmes to develop near-isogenic lines (NILs) of the recipient parent.Before the initiation of any breeding programme or mapping experiments, drought-tolerant donors were identified through screening of germplasm material. A majority of this material involved traditional –1 in lowland and upland, respectively. P and K were applied as basal, and N was applied in three splits, the first as basal, the second at maximum tillering, and the third at panicle initiation, in both lowland and upland. In order to control snails, Bayluscide  was sprayed just after transplanting. At 4 days after transplanting , Sofit  was sprayed to control weeds, followed by Furadan  at 5 DAT and Cymbush ±Dimotrin  at 16 DAT to control insect pests.Screening of donors and mapping and segregating populations was conducted under upland and/or lowland reproductive-stage drought stress (RS) and irrigated non-stress (NS) conditions in dry season (DS) experiments at the International Rice Research Institute (IRRI). The experiments were planted in an α-lattice design with two replications in single or two-row plots with 5 m row length in lowland and 2.0–3.0 m row length in upland. Lowland experiments were carried out under transplanted conditions in which 21-day-old seedlings were transplanted in the field with a single seedling per hill. However, upland experiments were dry direct seeded. The row-to-row and plant-to-plant spacing of 20 cm×20cm in lowland and 25 cm×25cm in upland was maintained. Nitrogen, phosphorus, and potassium (NPK) were applied at the rate of 120:30:30 and 100:40:40kg haIn upland conditions, donors and mapping populations were screened in sprinkler-irrigated dry direct-seeded trials. Up to 45 days after sowing , the trials were irrigated by sprinkler twice a week during establishment and early vegetative growth . Stress In lowland conditions, transplanted experiments were drained at 30 DAT and irrigation was withheld to impose drought stress at the reproductive stage . Stress –1.Data for days to 50% flowering (DTF), plant height (PHT), and grain yield (GY) were recorded. DTF was recorded when 50% of the panicles of the plants of each plot were exerted. PHT (cm) was measured at maturity from the soil surface to the tip of the panicle on the main tiller from three random plants of each plot and then the mean was calculated. Harvesting for GY was done at physiological maturity. Samples were harvested and dried to 12% moisture before weighing, and weights were converted to kg haIn the drought grain yield QTL identification as well as introgression programme, rice microsatellite [simple sequence repeat (SSR)] markers were widely used  and bacterial blight (caused by Xanthomonas oryzae pv. oryzae)—and grain and cooking quality traits. Selected lines from evaluation at IRRI for all these traits were tested under national/state trials in different countries. IR64 introgressed lines with qDTY2.2 and qDTY4.1—IR87707-445-B-B-B and IR87707-446-B-B-B—together with IR64 as a check were evaluated together at 51 locations in 2011 and 2012 under the All India Coordinated Rice Improvement Program in India and under the drought breeding programme in Nepal. IR84984-83-15-481-B, a qDTY12.1 NIL in the Vandana background, along with Vandana as a check were evaluated in 12 experiments conducted at the IRRI and at three locations in India in 2011–2012.Selected NILs were screened under reproductive-stage drought (RS) and irrigated non-stress (NS) conditions. The introgressed lines along with the recipient high-yielding variety and drought-tolerant donors were evaluated first at IRRI for yield under RS and NS conditions. This was followed by evaluation of the selected lines for diseases—blast . For example, a majority of the drought-tolerant landraces show early flowering, tall plant height, low tillering, and low yield compared with medium to late flowering, semi-dwarf plant height, high tillering, and high yield of the high-yielding popular varieties. Some of these landraces have also been known to possess deep roots up to 70cm below the soil surface. Greater root length density at depth has also been reported in drought-tolerant genotypes such as Dular, Azucena, and Rayada compared with high-yielding drought-susceptible varieties such as IR64  were rejected. Single-plant selections were screened under reproductive-stage drought stress conditions in the F3 generation, and tolerant plants were selected based on grain yield. In F4 and F5 generations, selection was carried out in non-stress conditions with grain quality traits evaluated in the F5 generation. In the F6 generation, lines were screened under both reproductive-stage drought stress and non-stress conditions, and lines with high yield under both conditions were advanced to an observational yield trial (OYT). All trials until the F6 generation were conducted as unreplicated trials. In the OYT, lines were divided into groups based on crop duration, and lines belonging to each group were planted with checks in replicated yield trials in larger plots. Selected lines from OYTs constituted an advanced yield trial (AYT). These trials were conducted at IRRI and in the target environments in an α-lattice design with large plot sizes. Lines performing well in the target environment were advanced for release by the respective national systems. Combining high yield under reproductive-stage drought stress and non-stress in one genotype is the goal that breeders have been targeting for a long time. This is mainly because, in the years with well-distributed rainfall in these areas, the drought-tolerant varieties should provide high yield comparable with that of the popular high-yielding varieties. This cannot be achieved through direct cultivation of drought-tolerant landraces because of their low yield potential. The breeding programme described above allowed the development of several high-yielding drought-tolerant lines. Multilocation testing of these lines has led to the release of 17 varieties across South and Southeast Asia and Africa over the past 6–7 years —and across environments—QTL×environmental interaction (Q×E)—has been another factor limiting the use of QTLs in molecular breeding . The effect of both these QTLs was also seen on other traits such as DTF and PHT. BSA was successfully used for the first time to identify such large-effect QTLs for grain yield under reproductive-stage drought  from donor N22  to show an effect against Swarna, a popular variety in India, Nepal, and Bangladesh; six QTLs  to show an effect in the background of IR64, a popular variety in many countries of South and Southeast Asia; two QTLs (qDTY3.2 and qDTY12.1) to show an effect against the background of Sabitri, a popular variety from Nepal; three QTLs  to show an effect against TDK1, a popular variety from Laos; and one QTL (qDTY3.1) to show an effect against BR11, a popular variety from Bangladesh.In summary, the studies identified four QTLs  identified in two different populations were validated for their effect in Nepal by phenotyping the full mapping population in Nepal in the second season  to be interacting with qDTY12.1 and significantly enhancing the yield of qDTY12.1-positive lines  under lowland stress conditions  and upland . Although the set of identified QTLs mentioned above will bring about yield improvement under reproductive-stage drought in a majority of the high-yielding backgrounds, it is not necessary that they be the best combination of QTLs for every background. This is due to the interaction between the QTLs and the genetic background of the recipient varieties. In such cases, the development of a BC1F3 BIL population to identify the best QTL combination before proceeding further in the pyramiding programme could be an appropriate strategy.QTL identification studies at the IRRI identified a set of QTLs with large effects in the background of rice varieties Swarna, IR64, TDK1, Sabitri, and BR11, and enlisted the set of QTLs that should be used to improve varieties for grain yield under reproductive-stage drought in lowland (DTY QTLs link tightly to traits such as plant height and earliness. It becomes important to develop large BCnF1 (n being the number of backcrosses) populations in each cycle of backcrossing to allow enough recombination to break these linkages. It is also required that a large number of BCnF2 segregants with different QTL combinations be selected and precisely phenotyped under reproductive-stage drought as against the selection of fewer plants practised for traits with simpler genetic control. Proper drought phenotyping of different combinations of QTLs allows the selection of lines with a positive interaction between different QTLs and the genetic background of the recipient variety, allowing breeders to capture a high yield advantage under reproductive-stage drought.In many cases, DTY QTLs at the IRRI. A marker-assisted breeding programme for seven popular varieties, Swarna, IR64, Vandana, Sabitri, TDK1, Anjali, and Sambha Mahsuri, was undertaken. For Swarna, a combination of three QTLs  was pyramided along with Sub1, the large-effect QTL for tolerance of submergence. Lines tolerant of both drought and submergence are at the final stages for testing in the target environment. Similarly, IR64 introgression lines with qDTY2.2 and qDTY4.1 were developed and have been tested in a wide range of environments for tolerance of drought. Two upland rice varieties were also improved through marker-assisted introgression of DTY QTLs: Vandana and Anjali. qDTY12.1 was introgressed in Vandana, and qDTY12.1 and qDTY3.1 were introgressed in Anjali. Three large-effect QTLs  were identified and introgressed in TDK1, a popular variety from Lao PDR. Similar to Swarna, these QTLs were pyramided along with Sub1 to confer tolerance of both drought and submergence. Two other varieties, Sabitri and Sambha Mahsuri, that are popular in Nepal and in India, respectively, are also in the marker-assisted breeding pipeline. Sabitri is being introgressed with qDTY3.2 and qDTY12.1. The effect of these two QTLs in Nepal has already been validated in two separate QTL identification programmes  were tested in 51 experiments conducted across India and Nepal. Both lines showed increased yield at most of the sites, where drought conditions varied from irrigated conditions with no drought to mild drought and moderate drought, to very severe drought (0.05 details in Supplementary Table S1 at JXB online). Under severe reproductive-stage drought stress conditions in a rainout shelter as well as in the field, the IR64 NILs showed a yield advantage of 100–500 percentage points over the recurrent parent IR64 . The introgression of different combinations of DTY QTLs has also allowed researchers to understand the effect of specific combinations of the QTLs and the yield improvement achieved in different cultivars. For example, the introgression of one QTL in Vandana led to an increase in yield of 0.5 t ha–1 under drought, and the introgression of two QTLs led to an increase in yield of >1.0 t ha–1 in IR64 and Sambha Mahsuri, whereas the introgression of three QTLs in Swarna showed a yield advantage of >1.5 t ha–1 under drought  of IR87707-445-B-B-B, IR87707-446-B-B-B, and IR64, and LSD0.05 values for experiments conducted across India and Nepal.Table S2. Mean grain yield (kg ha–1) of IR84984-83-15-481-B and Vandana, and LSD0.05 values for experiments conducted across India and at IRRI.


Neuroanatomical differences between individuals with and without autism spectrum disorder (ASD) were inconsistent in the literature. Such heterogeneity may substantially originate from age-differential effects.Voxel-based morphometry was applied in 86 males with ASD and 90 typically developing control (TDC) males (aged 7 to 29 years). Three steps of statistical modeling  were performed to dissect the moderating effects of age on diagnostic group differences in neuroanatomy.Across ages, males with and without ASD did not differ significantly in total gray matter (GM) or white matter (WM) volumes. For both groups, total GM volumes decreased and WM volumes increased with age. For regional volume, comparing with the model only held the age constant (model 1), the main effect of group altered when diagnosis-by-age interaction effects were considered (model 2). Here, participants with ASD had significantly greater relative regional GM volumes than TDC in the right inferior orbitofrontal cortex and bilateral thalamus; for WM, participants with ASD were larger than TDC in the bilateral splenium of corpus callosum and right anterior corona radiata. Importantly, significant diagnosis-by-age interactions were identified at the bilateral anterior prefrontal cortex, bilateral cuneus, bilateral caudate, and the left cerebellum Crus I for GM and left forceps minor for WM. Finally, age-stratified analyses (model 3) showed distinct patterns in GM and WM volumetric alterations in ASD among subsamples of children, adolescents, and adults.Our findings suggest that the heterogeneous reports on the atypical neuroanatomy of ASD may substantially originate from age variation in the study samples. Age variation and its methodological and biological implications have to be carefully delineated in future studies of the neurobiology of ASD.The online version of this article (doi:10.1186/s13229-015-0022-3) contains supplementary material, which is available to authorized users. Autism spectrum disorder (ASD) is a heterogeneous syndrome collectively characterized by early-onset difficulties in social communication and interactions and repetitive, restricted behaviors and interests ,2. NeuroConverging evidence across different studies points to the possibility that neuroanatomical differences between individuals with ASD and typically developing control (TDC) individuals are substantially age-dependent. Previous studies found that individuals with ASD have greater global  and lobaGlobal brain developmental trajectories between ASD and TDC may also be age-dependent. Longitudinal and cross-sectional data from participants aged 12 months to 50 years  demonstrversus model 2 helps demonstrate how considering age-differential effects will alter the inferred main effects of diagnosis. Finally, the age-dependent main effect of diagnosis is further delineated in model 3 by age stratification  and by model selection to decide whether diagnosis-by-age interaction should be further modeled in these stratified, age-confined analyses. We hypothesized that the main effects of diagnosis would be different in different age ranges, and there would be no significant diagnosis-by-age interaction in model 3 owing to the more circumscribed age range. In this scenario, findings from model 3 will reveal the most interpretable diagnostic group differences in specific age bands, which at the same time clarifies how exactly age moderates diagnostic effects. Owing to the substantial heterogeneity in earlier reports of neuroanatomical studies in ASD [However, to our knowledge, there have not been studies exploring how exactly the morphometric alterations for ASD may be obscured if age dependence is not formally modeled statistically. To dissect age moderation effects on diagnostic group differences in neuroanatomy with cross-sectional data, here, we adopted a three-step statistical modeling approach in a whole-brain VBM analysis. In model 1, we adopted a commonly used approach in past literature that investigated alterations in brain structure in individuals with and without ASD ‘controlled for’ the effect of age. The interpretation to the findings from this approach is about group differences when age is held constant. However, under this approach, it is unknown whether such main effect of diagnosis is directly interpretable, as the diagnosis-by-age interaction effect is not modeled and tested for. Therefore, one step further in model 2, we explicitly modeled the effect of diagnosis-by-age interaction. Given that previous studies have demonstrated potential different trajectories of brain development between individuals with and without ASD, we hypothesized that the diagnosis-by-age interaction effect would be evident in several brain regions. From the findings of model 2, the main effect of diagnosis is clearer and more interpretable, as (i) if regions showing main effects of diagnosis do not overlap with those showing diagnosis-by-age interaction, such main effects could be more reliably and directly interpreted, yet (ii) if regions showing main effects of diagnosis overlap with those showing diagnosis-by-age interaction, such main effects cannot be directly interpreted, and age-stratified analyses are indicated to disentangle the moderating effect of age on diagnostic effects. Besides, the comparison between the main effects identified in model 1 s in ASD , we did The Research Ethics Committee at the National Taiwan University Hospital (NTUH) approved this study prior to implementation . The procedures and purpose of the study were explained face to face to the participants and their parents, who then provided written informed consent. All participants underwent the same clinical and MRI assessments, except that only the ASD group received the Chinese version of the Autism Diagnostic Interview-Revised (ADI-R) assessment.We recruited 102 Taiwanese high-functioning males with ASD consecutively from the child psychiatry outpatient clinic of NTUH, and 90 TDC males from similar geographical districts . Participants with ASD were clinically diagnosed according to the DSM-IV-TR and ICD-10 criteria by the corresponding author and further confirmed by interviewing the parents using the Chinese version of the ADI-R  . Thirteen = 86, participants in the final analyses following image quality control as indicated below) were described in Additional file TDC participants were recruited if they did not have any current or lifetime DSM-IV psychiatric disorder based on the Chinese version of the K-SADS-E interview  and its Intellectual function was assessed by the Wechsler Intelligence Scale for Children-3rd edition (WISC-III)  in parti3; matrix size = 256 × 256 × 192; voxel size = 1 mm3 isotropic). Three ASD participants were excluded from further imaging processing owing to excessive in-scanner head motion by visual quality control inspection, yielding a final sample of 86 males with ASD and 90 TDC males.High-resolution T1-weighted images were acquired with a 3D magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence on a 3 T MRI scanner  using a 32-channel phased arrayed head coil  to produce native space GM, WM, and cerebral spinal fluid (CSF) images. During segmentation, for all individuals below the age of 18 years, age- and sex-matched study-specific tissue probability maps generated from the Template-O-Matic toolbox  were used; for individuals above 18 years old, default tissue probability map in New Segment was used. The native space GM and WM images of all participants  were then registered to a study-specific template using a high-dimensional non-linear diffeomorphic registration algorithm (DARTEL) . A modult-tests while handedness was examined by chi-square test , with the main effect of group (Gi) as a fixed factor and age (linear term) (Ai), full-scale IQ (FSIQ), and comorbidity status (Comorbidity) as nuisance covariates, to investigate between-group difference when the effect of age was held constant.In this first model, we fitted a general linear model at each voxel (i*Ai) to model 1, to test for diagnosis/group (Gi) by age (Ai) interaction effects. Significant interaction indicates that group differences in neuroanatomy are dependent on age.In this second model, we fitted a general linear model by further adding in an interaction term , adolescents (13 to 17 years), and young adults (18 to 29 years). The results of age-stratified analyses only partialling out age effects as done in model 1 were provided in Additional file P < 0.005 and a spatial extent threshold . WM structures were labeled by overlaying the significant clusters with standard space WM tracts defined from JHU diffusion tensor imaging-based white matter atlases [Age was mean-centered across all subjects before entering into all the models. We conducted all analyses with full-scale IQ (FSIQ) and the status of the comorbidity  included as nuisance covariates  were provided in Additional file ionarity ,37) that atlases ,39.Considering the uneven age distribution between the two groups, and the fact that around 80% of participants with ASD aged within 10 to 19 years, which might result in unintended biases, we performed subsidiary analyses (using model 1 and model 2) by narrowing the age range of participants to 10- to 19-year-olds to ensure the age distribution of the two groups are even and rectangular  and CSF  volumes increased significantly with age, whereas total GM volume decreased with age . Total brain volume decreased significantly with age in TDC  but was not associated with age in ASD . For intracranial volume, there was no significant age-volume correlation   as identified in the main analysis were not significant anymore  and right anterior corona radiata (not identified as a main effect of diagnosis in model 1) Figure . No regiImportantly, model 2 identified significant diagnosis-by-age interaction effects in several regions including the GM of bilateral anterior PFC , bilateral cuneus (BA 17 to 19), left cerebellum Crus I, and bilateral caudate Table  and the In the statistical models without controlling for full-scale IQ, participants with ASD had significantly smaller relative regional GM volumes than TDC in the left temporo-parieto-occipital junction  but smaller GM volumes in the right post-central gyrus and left parieto-occipital junction than TDC children Figure , Table 2Second, in the adolescent subgroup, there were no significant group differences in relative regional GM volume, regardless of whether full-scale IQ effects were controlled for. However, in the statistical model controlling for IQ, adolescences with ASD had greater relative regional WM volumes in the right anterior corona radiata Table .Third, adults with ASD had greater relative regional GM volumes than TDC in the right dorsal mPFC (BA 9/10), left dorsal mPFC (BA10), left lateral frontal cortex (BA10), and right cuneus BA 18) Figure . In the  Figure .In the subsidiary analyses using participants with restrained age range (10 to 19 years), model 1 identified that regional volume of the lingual gyrus was smaller in ASD relative to TDC, while this main effect of diagnosis was not found in model 2 (considering diagnosis-by-age interaction effects). Model 2 further identified significant diagnosis-by-age interaction effects, that relative GM volume of the bilateral cuneus and left cerebellar tonsil, alongside WM volume of the anterior limb of internal capsule, increased with age in ASD but decreased in TDC, whereas relative GM volume of the right superior temporal gyrus decreased with age in ASD but increased in TDC . Using model 2, age dependency of atypical brain volume was identified in the GM of the bilateral anterior PFC, bilateral cuneus, left cerebellum crus I, and bilateral caudate, alongside the WM of the left forceps minor. Further stratification by age (in model 3) demonstrated substantial age-dependent regional brain volumetric differences between males with and without ASD. These findings were revealed after controlling for individual differences in tissue-specific brain volume, full-scale IQ, and comorbidity status. This three-step modeling approach adds evidence to support our speculation that the heterogeneity in morphometric alterations in ASD in the literature is substantially contributed by age variation in the samples. This suggests the necessity to account for age effects in neuroimaging research for ASD.post hoc pair-wise comparisons demonstrated no significant differences between the child and adolescent subgroups. This might reflect an atypical developmental pattern  of total GM volume by adulthood in ASD, in comparison to the continuous GM volumetric reduction with age since early teenage found in typically developing individuals [Our findings of negative age total GM volumes correlations in ASD were in accordance with an earlier cross-sectional report . Nonetheividuals . It alsoividuals . At the ividuals ,26,40 anividuals -22,27, iividuals . Explanaividuals ).Regarding regional neuroanatomy, we posited that findings  of volumetric group differences might be different between using models with or without considering diagnosis-by-age interaction effects. The different findings from model 1 and model 2 supported this speculation. Based on this, we suggest that for any group comparison between individuals with and without ASD, it is best to first test for diagnosis-by-age interaction. In the modeling approach of the present study, only if the localization of group differences revealed in model 1 and model 2 overlap, that we are confident to say that diagnosis-by-age interaction is not producing substantial effects. The discrepant group difference findings between the two models suggest this is not the case in our sample; thus, it is a more appropriate modeling strategy to apply model 2 for main statistical inferences. Furthermore, when using model 2, if the localization of group effect and diagnosis-by-age effect overlap, the main effect of group becomes uninterpretable as how group difference presents itself is dependent upon the age of the individual. On the other hand, if the two does not overlap, both effects can be interpreted, separately. Under the latter circumstances (which is what we found), the noted diagnostic differences indicate regions where group differences are independent of age, and the noted regions showing diagnosis-by-age interaction effects indicate structures where group differences are substantially dependent on the age examined, potentially giving candidates for future longitudinal studies investigating group differential developmental trajectories. This view is also supported by a previous VBM meta-analysis  demonstret al. [versus longitudinal design . In addition, different structural imaging protocols, that is, DARTEL under SPM8 in the current study versus surface-based analysis using FreeSurfer [et al. [www.fmrib.ox.ac.uk/fsl), surface-based morphometry using FreeSurfer, operator manual-tracing regional analyses, and so on, is still needed to disentangle the heterogeneous findings in autism neuroimaging [Our results corroborate with previous reports on the age dependency of atypical brain growth patterns in ASD -27,40,45et al. . This ineeSurfer  in Lange [et al. , may dir [et al. . Surface [et al. . Using aoimaging ,28, partMoreover, as we applied a mass univariate analysis approach (VBM), only isolated locales with the largest group differences (or with large diagnosis-by-age interaction effects) would be revealed. However, this should not be taken to mean that our results reject the idea that abnormalities in multiple regions and neural systems characterize the neurobiology of autism. It is simply that the methodology applied here is less powerful in detecting systems-level atypicality, which will be more readily revealed by multivariate methodologies.The subsidiary analyses using a confined-age group (10 to 19 years) identified similar age-dependent change in the cuneus region to the main finding, suggesting the robustness of such finding. However, disparity exists in other regions showing diagnosis-by-age interaction and main effect of diagnosis. Despite the relatively large sample size, we acknowledge that the small number of children (younger than 10 years old) and young adults (older than 20 years old) in the ASD group might introduce unintended bias from potential outliers in the diagnosis-by-age interaction analyses. These discrepancies in the regions demonstrating the main effect of diagnosis also further underscore that morphometric differences in ASD are largely dependent on the age window investigated. Future studies investigating age-related volumetric differences in ASD should investigate well-powered samples at younger and older ages. Otherwise, narrow-banded age-stratified analyses, as undertaken in model 3, on well-powered large samples, would provide a solution to this complex issue.Following this argument, we posit that comparing groups in a wide age range sample without attempting to stratify by age may elude important developmental information. For example, in age-stratified analyses, we found age-specific diagnostic differences in GM of several brain regions. We also demonstrated that for the same region , ASD-TDC differences were opposite in direction between the child and adult age subgroups . A VBM meta-analysis  shows grper se [Whether or not including IQ as a covariate in the model may also partially account for conflicting reports, as the present work showed that regional volumetric alteration in ASD did not exactly overlap between the statistical models with and without regressing out IQ effects. IQ is suggested to be related to the volume in several Brodmann areas, including BA 19 (corresponding to the cuneus) , and fluper se . Additioper se . Owing tIn the present study, many regions showing atypical regional volume and age-dependent trends in ASD have been reported as major cortical and subcortical structures and white matter tracts implicated in the pathophysiology of ASD. The orbitofrontal cortex  exhibited atypical regional volume in ASD, consistent with prior studies ,54. Incrversus volume) as well as other methodological issues discussed earlier. Other regions  demonstrating atypical age-dependent trends are first reported in the present study.The aPFC, caudate nucleus, and cerebellum Crus I, alongside forceps minor, represent the major cortical, subcortical hubs, and white matter tract of the cognitive control network ,69. BesiThe aPFC has been suggested to contribute to a range of higher-order cognitive functions, including multitasking , memory A growing body of evidence indicates that the cerebellum is involved in the pathophysiology of ASD ,87, in rThe brain structural differences in ASD might be the product of atypical neurogenesis/gliogenesis, neuronal cell shrinkage/death, synaptic pruning, or myelination. Consistent with the present findings, postmortem studies on the neuropathology of ASD demonstrate altered cytoarchitectural organization , perturbOverall, our findings in the context of the biological, methodological, and clinical heterogeneity of ASD raise several questions to be further addressed: What drives the atypical developmental trajectories of brain growth in individuals with ASD compared to typically developing individuals? How are these neurobiological atypicalities associated with the developmental changes in cognition and behavior?Our findings should be interpreted in the light of other limitations not indicated above. First, the cross-sectional design limits the capacity in directly addressing developmental trajectories, for example, any non-linear trends. The age dependency shown in this work should be interpreted in combination with findings from longitudinal studies ,27, giveIn summary, our three-step statistical modeling approach demonstrated highly age-dependent atypical brain morphometry in ASD. Diagnosis-by-age interaction should be regularly examined, and age-stratified analyses should be further performed in future studies into the developmental neurobiology of ASD. Our findings, together with comparisons with earlier reports, indicate that prior discrepant structural neuroimaging findings in ASD may substantially originate from the various age range examined, as well as different statistical approach dealing with age dependency effects. Besides, different imaging protocols and the biological heterogeneity of ASD could further contribute to the discrepancy in the literature. Longitudinal studies with more even age distributions and better-powered designs, alongside the conjoint use of several imaging analysis pipelines can help directly clarify plausible differential growth trajectories in the life span neurodevelopment in ASD.


Denosumab and abiraterone were approved by the United States Food and Drug Administration in 2011 for the treatment of metastatic castration-resistant prostate cancer. Neither denosumab nor abiraterone is known to cause rhabdomyolysis.A 76-year-old Caucasian man with metastatic prostate cancer presented with non-oliguric severe acute kidney injury (AKI) 3 weeks after receiving simultaneous therapy with denosumab and abiraterone. The patient had been on statin therapy for more than 1 year with no recent dose adjustments. His physical exam was unremarkable. Blood work on admission revealed hyperkalemia, mild metabolic acidosis, hypocalcemia, and elevated creatine kinase (CK) at 44,476 IU/L. Kidney biopsy confirmed the diagnosis of rhabdomyolysis-induced AKI. The patient responded well to intravenous isotonic fluids and discontinuation of denosumab, abiraterone, and rosuvastatin, with normalization of CK and recovery of kidney function.We report the first case of biopsy-proven rhabdomyolysis-induced AKI in a cancer patient acutely exposed to denosumab and abiraterone. Whether one of these drugs individually, or the combination, was the bona fide culprit of muscle breakdown is unknown. Nonetheless, our report is hypothesis-generating for further investigations on the effect of these drugs on muscle cells. Rhabdomyolysis is characterized by muscle breakdown leading to leakage of sarcoplasmic proteins, electrolytes, and myoglobin into the circulation . SeveralOne of the common complications of rhabdomyolysis is acute kidney injury (AKI). In the US, rhabdomyolysis is the cause of up to 10 % of all cases of AKI  and the Pharmacologic agents constitute important causes of non-exertional and non-traumatic rhabdomyolysis , 8. SeveIn 2011, denosumab and abiraterone were approved by the United States Food and Drug Administration for the treatment of metastatic castration-resistant prostate cancer. We present the case of a 76-year-old Caucasian man with a history of metastatic prostate cancer who developed rhabdomyolysis-induced AKI after acute exposure to denosumab and abiraterone.A 76-year-old Caucasian man with a history of type 2 diabetes, chronic kidney disease (CKD) stage 3A, essential hypertension, hypothyroidism, antiphospholipid antibody syndrome, prior cerebellar strokes, and prostate cancer Gleason 10) with widespread metastasis to the bone presented with non-oliguric severe AKI 3 weeks after receiving simultaneous therapy with denosumab (120 mg subcutaneous injection once) and abiraterone . The patient had failed prior antineoplastic therapy with leuprolide acetate, bicalutamide, and nilutamide. On admission, his serum creatinine (SCr) was elevated at 5.7 mg/dL from a baseline of 1.2 mg/dL , inhibiting osteoclast-mediated bone resorption . It is uin vitro, which may theoretically affect OATP1B1-mediated uptake of rosuvastatin, increase its levels, and therefore predispose to toxicity [Prior to the development of abiraterone and its approval as an adrenal androgen synthesis inhibitor, ketoconazole was the only CYP17 inhibitor that was used to treat metastatic castration-resistant prostate cancer . Howevertoxicity –23. To oOver the past few years, genetic experiments have unveiled numerous functions of the RANKL/RANK system . The besRANKL mRNA and protein are found in skeletal muscle . HoweverWe report the first case of rhabdomyolysis leading to severe AKI in association with acute exposure to denosumab and abiraterone. From our case we are unable to determine whether rhabdomyolysis was caused by one of these two drugs, their mutual interaction, or their interaction with another commonly used drug, rosuvastatin. Nonetheless, this case exposes the need to carefully monitor patients exposed to denosumab and abiraterone to recognize potential severe adverse effects associated with these novel therapies. In addition, our report is hypothesis-generating to further investigate the effect of these drugs on muscle cells. In conclusion, we recommend monitoring for early signs of rhabdomyolysis in high-risk patients exposed to either denosumab or abiraterone, particularly if other identifiable risk factors are present Table , such asThe patient was deceased at the time of preparation of this manuscript. Written informed consent was obtained from his next-of-kin for publication of this Case Report and any accompanying images.


NO-sensitive guanylyl cyclase (NO-GC) is accepted to be the major receptor for the signaling molecule NO. Deletion of NO-GC in mice leads to disturbed NO/cGMP signaling. As a result, these mice show abolished NO-dependent relaxation of smooth muscle-containing tissues in the cardiovascular and gastrointestinal systems. Mice with general deletion (GCKO) suffer from increased blood pressure, reduced bleeding time, erectile dysfunction and die prematurely due to gastrointestinal dysmotility. Mice lacking NO-GC specifically in smooth muscle cells (SMC) show an elevated blood pressure similar to that seen in GCKO animals.Crosstalk between cGMP and cAMP signaling has been reported to occur in many different cells. Phosphodiesterase 3 (PDE3) is thought to be one of the prominent mediators of this crosstalk. Through its inhibitory action on PDE3, cGMP may regulate cAMP levels and cAMP-mediated signaling. Here, we reasoned that, in animals deficient in NO-GC, lack of NO-induced cGMP synthesis might affect cGMP/cAMP crosstalk on the level of PDE3. Smooth muscle relaxation induced by forskolin to stimulate adenylyl cyclase was similar in WT, GCKO and SMC-GCKO aortae. RIA-based detection of basal cAMP levels in aortic tissue from these mice did not reveal differences. Similarly, FRET measurements showed that PGE1-induced cAMP synthesis in isolated smooth muscle cells was unaffected by NO-GC deletion. However, aortae from GCKO and SMC-GCKO animals were more sensitive to milrinone, a specific inhibitor of PDE3, as the concentration curve for relaxation was shifted to the left. Analysis of PDE3 expression in aorta showed an approximately 50% reduction in PDE3 protein and specific enzyme activity. Similar reduction was detected in platelets but not in heart tissue of GCKO animals.Induction of SMC-specific NO-GC deletion by tamoxifen led to a parallel decline of NO-GC and PDE3 expression. Both proteins were strongly reduced already 5 days after the last tamoxifen injection. In contrast, systolic blood pressure in these animals started to rise only after 10 days and was maximal after 50 days. These data indicate that cGMP, not the increase in blood pressure, is responsible for the expression regulation of PDE3. We conclude that cGMP modulates PDE3 expression in SMC in order to keep up functional cAMP signaling.


Gender-based differences in disease onset in murine models of malignant peripheral nerve sheath tumor (MPNST) and in patients with Neurofibromatosis type-1-(NF-1)-associated or spontaneous MPNST has not been well studied.mGFAP-Cre+;Ptenloxp/+;LSL-K-rasG12D/+ mice were observed for tumor development and evaluated for gender disparity in age of MPNST onset. Patient data from the prospectively collected UCLA sarcoma database  and 39 published studies on MPNST patients (n = 916) were analyzed for age of onset differences between sexes and between NF-1 and spontaneous MPNST patients.Forty-three Our murine model showed gender-based differences in MPNST onset, with males developing MPNST significantly earlier than females . In the UCLA patient population, males also developed MPNST earlier than females . Patients with NF-1-associated MPNST had significantly earlier age of onset compared to spontaneous MPNST . However, expanded analysis of 916 published MPNST cases revealed no significant age difference in MPNST onset between males and females. Similar to the UCLA dataset, patients with NF-1 developed MPNST at a significantly younger age than spontaneous MPNST patients  and this disparity was maintained across North American, European, and Asian populations.Although our preclinical model and single-institution patient cohort show gender dimorphism in MPNST onset, no significant gender disparity was detected in the larger MPNST patient meta-dataset. NF-1 patients develop MPNST 13 years earlier than patients with spontaneous MPNST, with little geographical variance.The online version of this article (doi:10.1186/1471-2407-14-827) contains supplementary material, which is available to authorized users. The significance of gender as a fundamental variable to be studied in the development and progression of disease has been a long standing topic of interest . Men andMesenchymal glioblastoma multiforme (GBM), which is thought to stem from similar biomolecular pathways as malignant peripheral nerve sheath tumors (MPNST) including loss of neurofibromin (NF1) and TP53 function , 7, alsoHowever, gender differences in the development of MPNSTs have not specifically been examined. MPNST is an aggressive soft tissue sarcoma (STS) that accounts for up to 10 percent of all STS . It is oAlthough not all gender-based disparities are felt to be based on hormonal differences, there does appear to be a notable association amongst neurofibromas (NF), benign peripheral nerve sheath tumors that are a hallmark of neurofibromatosis, and circulating hormone levels. In NF-1 patients, MPNSTs are often found in the context of a preexisting NF. Although MPNST is felt to more commonly arise from epineural and perineural NFs such as subcutaneous and plexiform NF, the subtype of dermal NF shows considerable hormone responsiveness. Dermal NFs often appear at puberty, reportedly increase in number and size during pregnancy, and may regress after delivery, implicating a possible hormonal influence on tumor growth –18. It hN-ethyl-N-nitrosurea (ENU)-induced rat model and the Nf1-/+;Tp53-/+ cis (i.e. B6-NPcis) mouse model have both shown males to develop MPNSTs at an earlier age than females, even while accounting for confounding factors such as parental gender in the B6-NPcis model ) OR MPNST[Title]) OR neurogenic sarcoma[Title]) OR malignant schwannoma[Title]) OR atypical neurofibromas[Title]) OR peripheral nerve sheath tumors[Title]) OR peripheral nerve sheath tumours[Title]) NOT case report[Title]” for published articles from 1960–2011. For this study, only references written in the English language were used. Studies evaluating Neurofibromatosis type 2 were excluded. 990 hits were collected, and abstracts browsed to identify relevant articles. The full manuscripts were reviewed to identify studies that listed individual patients with age of diagnosis, NF-1 status, gender, and geographic data. Ten PubMed suggested articles or citations outside of our original search were included, and met the above criteria. A total of 39 published studies with data on 916 patients with MPNST was collected and aggregated to form the meta-dataset  and R software (R-package version 2.13).Pten tumor suppressor gene and activation of the K-rasG12D oncogene in the Schwann progenitor cells (driven by the mGFAP-Cre line) [Pten and acquisition of high FDG-PET uptake, reminiscent of human NF-to-MPNST malignant transformation [mGFAP-Cre+;Ptenloxp/+;LSL-K-rasG12D/+ littermates, 24 males and 19 females, for MPNST development. Mice developed MPNST at a median time of 155 days. In the context of gender-specific differences in tumor development, a significant disparity in age of MPNST onset was identified. Male mice developed MPNST at a significantly earlier age than female mice  . All neuormation , 26. To The gender dimorphism observed in the rat and mouse MPNST models prompted us to examine the age of MPNST onset in our UCLA cohort of 113 unique MPNST patients. The average age at initial MPNST diagnosis was 40 years . Sixty-one patients (54%) were male, and 52 patients (46%) were female. Thirty patients (26%) developed MPNST in the context of NF-1, and 83 patients (74%) developed MPNST spontaneously.Evaluation of age of MPNST diagnosis by gender revealed a trend toward males developing MPNST at an earlier age than females , compared to the median age of 31 years in females (n = 465) however this discrepancy was not significant  was not pursued further as it was not replicated in the larger patient meta-dataset. The gender disparity in the UCLA patient population is likely due to the relative rarity of MPNST, as our MPNST patient population was relatively small (n = 113). The limitation of this initial result underscores the need for collaborative effort in the study of STS subtypes. In rare cancers, such as sarcoma, collective pursuits of clinical research should be encouraged to increase the power and effect-size of the analysis. When our initial result was tested in a larger “meta-dataset” cohort, we believe a clearer picture of MPNST onset was revealed and gender-based differences were not observed.Additionally, recent literature supports multidisciplinary management of patients with STS at a nationally recognized sarcoma center. Age of diagnosis is likely influenced by non-clinical factors such as adherence to guidelines, referral pathways, and time to referral to a sarcoma center, which were not analyzed in this study. Earlier age of MPNST diagnosis is likely favored by prompt referral to a sarcoma center, and should therefore be encouraged in patients with suspicious tumors.Analysis of the meta-dataset from 39 published studies on MPNST revealed a 13 year difference in median age of diagnosis between NF-1 and spontaneous MPNST patients. Using a larger multinational meta-dataset of 916 patients, we were able to confirm the findings of earlier reports on smaller cohorts , 27. Givmax measurements, the gap in time between actual MPNST development and formal diagnosis can be truncated.This disparity between NF-1 and spontaneous patients may also reflect the earlier and increased frequency of routine physical exams and surveillance for MPNSTs in NF-1 patients. Clinical manifestations of malignant transformation classically rely on reported symptoms of new neurological deficits, rapid increase in size, change in palpated density from soft to hard, and unremitting pain. Patients with NF-1 and clinicians who treat them are often aware of the 10% lifetime risk of MPNST, and might be more apt to notice these changes. The malignant transformation event, whereby a NF degenerates into a MPNST, is distinct from the time at which a patient is formally diagnosed with MPNST. The interval between MPNST development and diagnosis can be shortened with the use of FDG-PET, as it has emerged as an accurate method to distinguish NF from MPNST based on the glycolytic phenotype . Using qLimitations of this study are ones inherent in studying a rare disease. First, patient diagnosis from both our UCLA and meta-datasets spans decades, covering a time period in which the diagnostic tools for MPNST detection were greatly improved. Improved detection through computerized tomography and magnetic resonance imaging has likely led to earlier detection of MPNST. However, for the same time period, this would affect patients of either sex equally, and affect both NF-associated and spontaneous MPNST patients equally. Second, there may be reporting bias, as most datasets were from surgically-resected patients only, and exclude patients with biopsy-proved but unresectable MPNST.This study focused on MPNST age of onset only, and did not include analysis of clinical factors such as age of NF-1 diagnosis or disease stage at MPNST diagnosis, due to lack of data reporting in the majority of the studies used in the meta-analysis. Patient gender may influence the development and progression of MPNST, however reports are conflicting. A recent analysis by Kolberg et al. , found nIn conclusion, the difference in age of onset between MPNST formation in NF-1 associated cases and spontaneous cases is reflected in both the actual age of onset and in the population age distribution. This suggests that the two branches of MPNST development are likely rooted in distinct and separate origins, influenced by different genetic and environmental factors.Supplemental Materials. Figure S1. Genetic homology to rat Mss4 locus on chromosome 6q24, including human homologs ERB2 and ERBB, which encode for estrogen receptors. Table S1. External datasets used in this study [Additional file 1:is study , 29–66.


This treatment strategy represents a promising therapeutic approach for simultaneously reducing or eliminating both primary auditory injury and nonauditory changes associated with bTBI-induced hippocampal neurodegeneration.Traumatic brain injury (TBI) can lead to early onset dementia and other related neurodegenerative diseases. We previously demonstrated that damage to the central auditory pathway resulting from blast-induced TBI (bTBI) could be significantly attenuated by a combinatorial antioxidant treatment regimen. In the current study, we examined the localization patterns of normal Tau and the potential blast-induced accumulation of neurotoxic variants of this microtubule-associated protein that are believed to potentiate the neurodegenerative effects associated with synaptic dysfunction in the hippocampus following three successive blast overpressure exposures in nontransgenic rats. We observed a marked increase in the number of both hyperphosphorylated and oligomeric Tau-positive hilar mossy cells and somatic accumulation of endogenous Tau in oligodendrocytes in the hippocampus. Remarkably, a combinatorial regimen of 2,4-disulfonyl  Traumatic brain injury (TBI) is a serious clinical challenge that negatively impacts millions of people worldwide. Repetitious low-impact concussive events or a single severe TBI can lead to early onset dementia and other related neurodegenerative diseases. Blast-induced TBI (bTBI) is a common form of TBI suffered in both military and civilian populations. Axonal injury is one of the common sequelae of bTBI –5. DiffuLike CTE, the ongoing neurodegeneration associated with bTBIs has been shown to be a Tau protein-linked disorder, or tauopathy , 11. In  in vitro and in vivo that aberrant Tau phosphorylation is potentiated by oxidative stress and is a reflection of the extent to which neuronal cells can combat free radical-induced oxidative and nitrosative damage resulting from neurodegenerative mitochondrial dysfunction , mouse anti-phospho-PHF-Tau pSer202/Thr205 antibody , or rabbit anti-oligomeric Tau antibody . After washing with PBS/T, either biotinylated anti-rabbit IgG or anti-mouse IgG  was applied to the slides for one hour, and Vectastain ABC and DAB kits  were used for the immunolabeling visualization. Immunopositive cells exhibited a brown reaction product at the sites of the target epitopes. Methyl green was used for nuclear counterstaining.To identify the cell types that differentially accumulated hyperphosphorylated or oligomeric Tau, brain sections were coincubated with mouse anti-Tau-1 and either rabbit oligodendrocyte specific protein antibody , rabbit anti-calretinin IgG , or rabbit anti-GluR 2/3 IgG ; with mouse anti-AT8 IgG and either rabbit anti-calretinin IgG or rabbit anti-GluR 2/3 IgG; and with mouse anti-AT8 IgG and rabbit anti-T22 serum. After washing with PBS, the sections were then incubated with appropriate Alexa Fluor 488 or 568 secondary antibodies . DAPI  was used to label nuclei. Fluorescence labeling was examined with either an Olympus BX51 microscope  or a Zeiss LSM-710 confocal microscope . Negative controls were prepared for each staining by omitting the primary antibody incubation step to control for specificity of immunolabeling.μm to ensure nonduplicate counting. The total number of positive cells within each area was counted using Image J software , and cell density was calculated (cells/mm2) and statistically analyzed as detailed below. Only cells with dark brown cytoplasmic staining (Tau-1 and AT8) or both cytoplasmic and nuclear staining (T22) were counted. Cell counting was blindly conducted by a technician who was unaware of the identity of each slide.For quantification of immunostaining, images were collected from the polymorphic layer (PoDG) and the infrapyramidal blade of the granular cell layer of the dentate gyrus (GrDG) of 5-6 sections of each brain. A modified two-dimensional quantification method was employed to count positive immunostained cells in these regions , 25. Imap value of less than 0.05 was considered to be significant.All parameters measured are expressed as means ± standard error of the mean (SEM). One-way ANOVA (SPSS 14.0 for windows) was used to determine if there were statistically significant differences among the three experimental groups  at each time point. When a significant difference among groups was found, a post hoc test (Tukey HSD) was used to determine if there were statistically significant differences between group pairings . Statistical analyses were conducted using GraphPad Prism 4 software . A p < 0.001, In uninjured brains, Tau localization is restricted to axons, resulting in a diffuse immunoreactivity pattern throughout the cortex and subcortical regions Figures  27]. Ho. Ho27]. p < 0.01 or 0.001, p > 0.05, We previously demonstrated that a combinatorial treatment regimen with the antioxidants HPN-07 and NAC could attenuate blast-induced neurodegeneration in several regions of the brain, including the hippocampus [Dysregulation of Tau phosphorylation can lead to progressive pathological processes that culminate in neuronal cell death . To discp > 0.05, p < 0.001, p < 0.05, p > 0.05, To confirm these observations, AT8-positive somata in the PoDG were quantified, and cell densities were calculated and statistically analyzed. While no statistical differences in the number of AT8-positive somata were observed at 24 hours after blast  ergic neurons within the adult hippocampus [The blast-induced accumulation of hyperphosphorylated and oligomeric Tau in the PoDG of the hippocampus occurred primarily in cells that were morphologically distinct from the oligodendrocytes in which somatic Tau-1 immunoreactivity was primarily observed Figures , and 6. pocampus , 40, whipocampus , 42.A majority of the AT8-positive cells in blast-exposed animals exhibited colabeling with the GluR2/3 antibody Figures . These rTo identify the cell types in which pathologic Tau oligomers accumulated within the PoDG in response to bTBI and the potential for their colocalization with hyperphosphorylated Tau, we performed dual labeling immunofluorescence with the T22 and AT8 antibodies. This analysis confirmed the blast-induced accumulation of oligomeric Tau in the PoDG of the hippocampus Figures  and also N-acetylcysteine and HPN-07. Consistent with these observations, blast-induced neurotraumas have been shown to induce metabolic cascades that result in both diffuse axonal injury and neuron loss in the hippocampus in the acute period following blast exposures and progressive losses thereafter [In the present study, we evaluated the effects of a combinatorial antioxidant treatment regimen on the histopathology of the microtubule-associated protein, Tau, in the brains of nontransgenic rats following three successive, 14 psi blast overpressure exposures. In untreated brains, we discerned that the vast majority of atypical Tau accumulation in response to blast occurred in the hippocampus and that this effect could be significantly attenuated by therapeutic intervention with the antioxidants,ereafter , 43 and ereafter , 45. As ereafter –23, the In our model of successive blast overpressure exposure, normal Tau markedly accumulated in the somata of oligodendrocytes. Oligodendrocytes are myelin-forming glial cells of the CNS, which are highly sensitive to oxidative stress, excitotoxicity, deprivation of trophic factors, and activation of apoptotic pathways . While nPrevious studies have shown that somatic Tau accumulation can be detected in oligodendrocytes as early as a few hours after a TBI in both rodents and humans , 48–50. β and cyclin-dependent kinase 5 [Phosphorylation of Tau is regulated by a host of serine/threonine kinases, including glycogen synthase kinase-3kinase 5 . In uninkinase 5 . Under ckinase 5 , 62. Redkinase 5 , 64.In response to mild successive blast overpressures, we observed a marked increase in the number of cells immunopositive for hyperphosphorylated and oligomeric variants of Tau in the rat hippocampus, indicative of Tau dysfunction in this region of the brain. Using differential immunofluorescence, we were able to discern that both of these pathological Tau variants preferentially accumulated within the somata of hilar mossy cells within the polymorphic layer of the dentate gyrus. Mossy cells are the major excitatory neurons in the PoDG, where they participate in recurrent excitatory circuits with granule cells and play an important role in normal signal processing associated with learning and memory , 65, 66. in vivo [Historically, NFTs, primarily composed of hyperphosphorylated Tau, have been considered the main histopathological hallmarks for neurodegenerative tauopathies, such as Alzheimer's and Parkinson's diseases . It has  in vivo .β precursor protein (APP) accumulates to high levels in the hippocampus during this acute time period following blast exposure [A positive correlation exists between oxidative stress and the induction of aberrant patterns of Tau functional regulation . In tranexposure . In lighexposure , the earWe had previously demonstrated that antioxidant intervention protects against progressive injury to the central auditory pathway in rats following exposure to blast overpressures , 24. In α-phenyl-tert-butyl-nitrone  pretreatment regimen has also been shown to reduce the number of Tau-positive oligodendrocytes by 55% in the brains of rats subjected to ischemic brain injury [ in vitro and in vivo by inhibiting toxin or trauma-induced apoptosis and glutamate-excitotoxicity and enhancing mitochondrial protection [Consistent with these observations, HPN-07 has been shown to inhibit the production of reactive oxygen species and reduce cognitive dysfunction when administered to animals following percussion-induced traumatic brain injury or in experimental models of stroke –86. Moren injury . NAC treotection –90. Admiotection , 92. in vitro studies with M17 neuroblastoma cells have demonstrated that loss of glutathione through inhibition of glutathione synthesis promotes oxidizing conditions that lead to hyperphosphorylation of Tau [In our model of bTBI, NAC and HPN-07 likely cooperate to oppose Tau dysregulation through both their antioxidant and anti-inflammatory properties, consistent with the strong links between oxidative stress, inflammation, and Tau hyperphosphorylation , 93–96. n of Tau , 99. UndκB induced by acute neurotoxic insults [In addition to their ability to scavenge free radicals, the known pharmacological effects of nitrones  are primarily anti-inflammatory . Many ne insults . More sp insults . Thus, tOther antioxidants have shown positive treatment effects for reducing Tau hyperphosphorylation and improving spatial learning and memory in animal models of Alzheimer's disease –108. Mor


Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. The investigation of the functional architecture of the human brain by means of resting-state functional magnetic resonance imaging (rs-fMRI) has rapidly become a major topic in neuroscience –7. The aExploring the relationship between functional connectivity and conscious experiences in the resting state is important, because in the absence of overt external task demands cognitive processes tend to become internally directed—comparable to what is commonly experienced during mind wandering . The resDifferent arguments support that BOLD-signal fluctuations during rs-fMRI could partially reflect neuronal activities governing conscious thoughts, for instance (1) BOLD-signal variation within ICNs is similar in magnitude to responses to stimuli in task-based fMRI , (2) theThe study protocol was approved by the institutional review board of the VU University Medical Centre, Amsterdam, The Netherlands. All participants provided written informed consent prior to enrolment in the study.M ± SD = 30.2 ± 9.6 years; 53 females). Exclusion criteria were neurological disease and contraindications for MRI .The current study was part of a larger study on sex differences in brain development that recruited individuals from the Netherlands Twin Register, a large database that contains longitudinal survey data from adult twins and their parents, siblings and spouses. In total, 106 self-declared healthy individuals participated in the present study; 1 monozygotic twin pair, 42 dizygotic opposite sex twin pairs, 4 dizygotic same sex twin pairs, 11 of their siblings and one unrelated individual from a pilot session; in the age range between 19 and 52 years  and two rs-fMRI scans  were acquired. Scans were separated by approximately 45 minutes of task-related fMRI. Participants received consistent instructions before  and after  each rs-fMRI scan. During the 45 minutes in between two runs of resting-state fMRI participants performed the Tower of London task (probing planning and working memory) and the Stroop task (probing selective attention and processing speed).Imaging was performed in a Philips Intera 3T MRI machine with an 8-channel head coil. For each participant, a high-resolution structural scan (3D Tt(105) = -1.067, P = .29). To avoid potential (recollection) bias, the ARSQ item order was randomized across trials and participants.To quantify thoughts and feelings during the resting-state session, participants completed a computerized version of the Amsterdam Resting-State Questionnaire (ARSQ: ) immediaImaging data were pre-processed using FSL  and have been mapped onto “behavioral domains”  in the BrainMap database [r = .45 & .51) with the default mode ICN, giving a total of 10 ICNs to be associated with ARSQ scores. The weakest spatial correlation in the 10 paired maps is r = .25. A correction for the spatial degrees of freedom is given via Gaussian random field theory and empirical smoothness estimation [r-to-Z transform by using degrees-of-freedom 500, converting to a P-value and multiplying by 200 to correct for multiple comparisons, we obtain P = 2.5 * 10−6, hence, the weakest pairing corresponds to  P = 10−5 (corrected).After single-session ICA and FIX denoising, ICA with principal component analysis-driven automatic dimensionality reduction  was perfdatabase . As we htimation , 49; forFor each session, voxel-wise estimates of functional connectivity were obtained using a regression technique referred to as the “dual-regression” approach , 51. TheTo investigate whether our results can be generalized to ICNs defined in an independent dataset, we repeated dual regression using the nine spatial maps derived from an ICA on BrainMap task-based fMRI data in a separate analysis.P < .01 (one-tailed) and corrected for family-wise error (FWE) within the spatial mask using Gaussian random field theory at a cluster-wise Bonferroni-corrected (2 directions * 10 ICNs * 10 ARSQ factors) significance threshold of PFWE< .00025 through Monte Carlo simulations using the 3dClustSim tool in AFNI. To derive a functionally relevant measure of functional connectivity from each ICN and each session, the clusters that showed a relation of functional connectivity with ARSQ measures were used to extract mean functional connectivity values from each individual spatial map using FSL tools. This mean functional connectivity value is used for scatter plots to illustrate the associations with the different ARSQ factors. In addition to the ICA-derived masks, linear mixed-effects modeling was performed using BrainMap masks.To investigate the association between an ARSQ measure and functional connectivity while properly taking into account both correlations among sessions from the same participant and the family relationship of our subjects (twins and siblings), we implemented a linear mixed-effects (LME) model. The ten 4-dimensional files containing voxel-wise functional connectivity estimates were analyzed in an LME model for each of the 10 ICA-derived ICN components and each ARSQ measure separately. The fixed effects were the intercept and the association between the ARSQ measure and functional connectivity, while the random effects included how families deviated from overall intercepts and slopes. The LME framework allowed us to specify a generic correlation structure among the random effects and account for the correlations among sessions from the same participant as well as among twins and siblings from the same family. Analyses were performed using the 3dLME software tool  in AFNI r ≤ .75, P < .001) and also exhibited substantial between-subject variation along the rating scale as can be seen from The ARSQ  was compPFWE = .00025  that subjects think about the same things and 2) that their overall brain state is constant throughout the measurement . EEG in We have previously observed that ARSQ scores on Sleepiness correlate positively with clinical measures of insomnia, anxiety, and depression . As netwConsidering the importance of the resting state in neuroimaging and the critical role of ongoing brain activity for the emergence of inner experiences, strikingly little has been done to investigate this relationship. As of yet, we are aware of only three studies , 38, 39.n = 45) and testing all these combinations for their associations with the 10 ARSQ dimensions would require Bonferroni correction for the additional 450 tests. We would not expect our study to have the power to support such stringent statistical correction and will leave this option for future investigation. A recently developed self-report questionnaire is more similar to the ARSQ as statements related to thought content and form were rated on a standardized (9-point) scale [A pioneering study on fMRI activation patterns and inner experiences during the resting state, focusing specifically on DMN connectivity and self-reports, identified a positive correlation with past and future thoughts . Howevert) scale . Still, t) scale .All of the studies that have used retrospective scoring of mind wandering during rs-fMRI—including the present one—have included more than 100 participants in the analysis. From this perspective, one may consider the number of associations between thoughts, feelings and BOLD signals surprisingly low. In our case, 10 ICNs and 10 dimensions of resting-state cognition could have revealed 200 significant effects when including also the possibility of negative associations. After Bonferroni correction, however, only 11 and 15 associations remained significant for the ICA and BrainMap masks, respectively. Apart from the conservative statistical approach, important factors contributing to a limited number of significant associations presumably include the very large brain regions used to assess the functional connectivity compared to the anticipated greater functional-anatomical specialization involved, e.g., in specific acts of Theory of Mind, Self- or Planning-related processing, thereby favoring dimensions in the ARSQ that index general changes in brain state. Furthermore, over the course of a 5-minute scanning session, both the content and quality of mind wandering—as well as the functional connectivity may vary greatly , and theRemarkably few fMRI studies have explicitly addressed the relationship between brain activation  and functional connectivity . A positive association may seem natural to assume, because coherent fluctuations are best detected with high signal-to-noise ratio BOLD fluctuations. However, different lines of evidence suggest an alternative model. For example, during natural viewing conditions, functional connectivity decreased markedly between non-homologous visual areas during visual stimulation relative to rest, which was interpreted as decoupling between visual areas that engage in specialized processing . SimilarResting-state neuroimaging features prominently in the clinical literature S1 FigExamples of “good”  and “artefactual”  components for the first participant. For good components, spectral power lies primarily between 0 and 0.05 Hz and the signal above threshold follows cortical gyrification. For movement-related artefacts, the signal above threshold is essentially at the edges of the brain and the frequencies of the power spectra are disparately distributed. In components due to cardiac pulsation and arterial contribution, the signal above threshold in the spatial maps is essentially located in the ventricles, or following the main arteries . For components relating to large veins, the signal above threshold in the spatial maps is essentially following the sagittal sinus. Additionally, one may find artefactual components due to MRI acquisition/reconstruction, limited to the white matter or due to susceptibility-motion. For a detailed description of ICA-based artifact removal, see , 46.(PDF)Click here for additional data file.