Neural Stem/Progenitor Cells from the Adult Human Spinal Cord Are Multipotent and Self-Renewing and Differentiate after Transplantation

Neural stem/progenitor cell (NSPC) transplantation is a promising therapy for spinal cord injury (SCI). However, little is known about NSPC from the adult human spinal cord as a donor source. We demonstrate for the first time that multipotent and self-renewing NSPC can be cultured, passaged and transplanted from the adult human spinal cord of organ transplant donors. Adult human spinal cord NSPC require an adherent substrate for selection and expansion in EGF (epidermal growth factor) and FGF2 (fibroblast growth factor) enriched medium. NSPC as an adherent monolayer can be passaged for at least 9 months and form neurospheres when plated in suspension culture. In EGF/FGF2 culture, NSPC proliferate and primarily express nestin and Sox2, and low levels of markers for differentiating cells. Leukemia inhibitory factor (LIF) promotes NSPC proliferation and significantly enhances GFAP expression in hypoxia. In differentiating conditions in the presence of serum, these NSPC show multipotentiality, expressing markers of neurons, astrocytes, and oligodendrocytes. Dibutyryl cyclic AMP (dbcAMP) significantly enhances neuronal differentiation. We transplanted the multipotent NSPC into SCI rats and show that the xenografts survive, are post-mitotic, and retain the capacity to differentiate into neurons and glia

Identification of Common Differentially Expressed Genes in Urinary Bladder Cancer

BACKGROUND: Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays. PURPOSE: Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays. METHODOLOGY/PRINCIPAL FINDINGS: BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways. CONCLUSIONS/SIGNIFICANCE: The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers

Urine metabolome profiling of immune-mediated inflammatory diseases

Background: Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn?s disease, and ulcerative colitis. Methods: Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls. Results: In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (PFDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (PFDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an overrepresentation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways. Conclusions: This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs

Postnatal depression among rural women in South India: do socio-demographic, obstetric and pregnancy outcome have a role to play?

INTRODUCTION: Postnatal depression (PND) is one of the most common psychopathology and is considered as a serious public health issue because of its devastating effects on mother, family, and infant or the child. OBJECTIVE: To elicit socio-demographic, obstetric and pregnancy outcome predictors of Postnatal Depression (PND) among rural postnatal women in Karnataka state, India. DESIGN: Hospital based analytical cross sectional study. SETTING: A rural tertiary care hospital of Mandya District, Karnataka state, India. SAMPLE: PND prevalence based estimated sample of 102 women who came for postnatal follow up from 4th to 10th week of lactation. METHOD: Study participants were interviewed using validated kannada version of Edinburgh Postnatal Depression Scale (EPDS). Cut-off score of ≥ 13 was used as high risk of PND. The percentage of women at risk of PND was estimated, and differences according to socio-demographic, obstetric and pregnancy outcome were described. Logistic regression was applied to identify the independent predictors of PND risk. MAIN OUTCOME MEASURES: Prevalence, Odds ratio (OR) and adjusted (adj) OR of PND. RESULTS: Prevalence of PND was 31.4% (95% CI 22.7-41.4%). PND showed significant (P < 0.05) association with joint family, working women, non-farmer husbands, poverty, female baby and pregnancy complications or known medical illness. In binomial logistic regression poverty (adjOR: 11.95, 95% CI:1.36-105), birth of female baby (adjOR: 3.6, 95% CI:1.26-10.23) and pregnancy complications or known medical illness (adjOR: 17.4, 95% CI:2.5-121.2) remained as independent predictors of PND. CONCLUSION: Risk of PND among rural postnatal women was high (31.4%). Birth of female baby, poverty and complications in pregnancy or known medical illness could predict the high risk of PND. PND screening should be an integral part of postnatal care. Capacity building of grass root level workers and feasibility trials for screening PND by them are needed

On the Arrangement of Cliques in Chordal Graphs with respect to the Cuts

A cut (A, B) (where B = V - A) in a graph G = (V, E) is called internal if and only if there exists a vertex x in A that is not adjacent to any vertex in B and there exists a vertex y is an element of B such that it is not adjacent to any vertex in A. In this paper, we present a theorem regarding the arrangement of cliques in a chordal graph with respect to its internal cuts. Our main result is that given any internal cut (A, B) in a chordal graph G, there exists a clique with kappa(G) + vertices (where kappa(G) is the vertex connectivity of G) such that it is (approximately) bisected by the cut (A, B). In fact we give a stronger result: For any internal cut (A, B) of a chordal graph, and for each i, 0 &lt;= i &lt;= kappa(G) + 1 such that vertical bar K-i vertical bar = kappa(G) + 1, vertical bar A boolean AND K-i vertical bar = i and vertical bar B boolean AND K-i vertical bar = kappa(G) + 1 - i. An immediate corollary of the above result is that the number of edges in any internal cut (of a chordal graph) should be Omega(k(2)), where kappa(G) = k. Prompted by this observation, we investigate the size of internal cuts in terms of the vertex connectivity of the chordal graphs. As a corollary, we show that in chordal graphs, if the edge connectivity is strictly less than the minimum degree, then the size of the mincut is at least kappa(G)(kappa(G)+1)/2 where kappa(G) denotes the vertex connectivity. In contrast, in a general graph the size of the mincut can be equal to kappa(G). This result is tight

On the Structure of Contractible Edges in k-connected Partial k-trees

Contraction of an edge e merges its end points into a new single vertex, and each neighbor of one of the end points of e is a neighbor of the new vertex. An edge in a k-connected graph is contractible if its contraction does not result in a graph with lesser connectivity; otherwise the edge is called non-contractible. In this paper, we present results on the structure of contractible edges in k-trees and k-connected partial k-trees. Firstly, we show that an edge e in a k-tree is contractible if and only if e belongs to exactly one (k + 1) clique. We use this characterization to show that the graph formed by contractible edges is a 2-connected graph. We also show that there are at least |V(G)| + k - 2 contractible edges in a k-tree. Secondly, we show that if an edge e in a partial k-tree is contractible then e is contractible in any k-tree which contains the partial k-tree as an edge subgraph. We also construct a class of contraction critical 2k-connected partial 2k-trees

On the Structure of Contractible Edges in k-connected Partial k-trees

Contraction of an edge e merges its end points into a new single vertex, and each neighbor of one of the end points of e is a neighbor of the new vertex. An edge in a k-connected graph is contractible if its contraction does not result in a graph with lesser connectivity; otherwise the edge is called non-contractible. In this paper, we present results on the structure of contractible edges in k-trees and k-connected partial k-trees. Firstly, we show that an edge e in a k-tree is contractible if and only if e belongs to exactly one (k + 1) clique. We use this characterization to show that the graph formed by contractible edges is a 2-connected graph. We also show that there are at least |V(G)| + k - 2 contractible edges in a k-tree. Secondly, we show that if an edge e in a partial k-tree is contractible then e is contractible in any k-tree which contains the partial k-tree as an edge subgraph. We also construct a class of contraction critical 2k-connected partial 2k-trees

Proteomic profiling of high glucose primed monocytes identifies cyclophilin A as a potential secretory marker of inflammation in type 2 diabetes

Hyperglycemia is widely recognized to be a potent stimulator of monocyte activity, which is a crucial event in the pathogenesis of atherosclerosis. We analyzed the monocyte proteome for potential markers that would enhance the ability to screen for early inflammatory status in Type 2 diabetes mellitus (T2DM), using proteomic technologies. Monocytic cells (THP-1) were primed with high glucose (HG), their protein profiles were analyzed using 2DE and the downregulated differentially expressed spots were identified using MALDI TOF/MS. We selected five proteins that were secretory in function with the help of bioinformatic programs. A predominantly downregulated protein identified as cyclophilin A (sequence coverage 98%) was further validated by immunoblotting experiments. The cellular mRNA levels of cyclophilin A in various HG-primed cells were studied using qRT-PCR assays and it was observed to decrease in a dose-dependent manner. LC-ESI-MS was used to identify this protein in the conditioned media of HG-primed cells and confirmed by Western blotting as well as ELISA. Cyclophilin A was also detected in the plasma of patients with diabetes. We conclude that cyclophilin A is secreted by monocytes in response to HG. Given the paracrine and autocrine actions of cyclophilin A, the secreted immunophilin could be significant for progression of atherosclerosis in type 2 diabetes. Our study also provides evidence that analysis of monocyte secretome is a viable strategy for identifying candidate plasma markers in diabetes