Haematopoietic stem cell migration to the ischemic damaged kidney is not altered by manipulating the SDF-1/CXCR4-axis

Background. Haematopoietic stem cells (HSC) have been shown to migrate to the ischemic kidney. The factors that regulate the trafficking of HSC to the ischemic damaged kidney are not fully understood. The stromal cell-derived factor-1 (SDF-1)/CXCR4-axis has been identified as the central signalling axis regulating trafficking of HSC to the bone marrow. Therefore, we hypothesized that SDF-1/CXCR4 interactions are implicated in the migration of HSC to the injured kidney

MicroRNA-146a and AMD3100, two ways to control CXCR4 expression in acute myeloid leukemias

CXCR4 is a negative prognostic marker in acute myeloid leukemias (AMLs). Therefore, it is necessary to develop novel ways to inhibit CXCR4 expression in leukemia. AMD3100 is an inhibitor of CXCR4 currently used to mobilize cancer cells. CXCR4 is a target of microRNA (miR)-146a that may represent a new tool to inhibit CXCR4 expression. We then investigated CXCR4 regulation by miR-146a in primary AMLs and found an inverse correlation between miR-146a and CXCR4 protein expression levels in all AML subtypes. As the lowest miR-146a expression levels were observed in M5 AML, we analyzed the control of CXCR4 expression by miR-146a in normal and leukemic monocytic cells and showed that the regulatory miR-146a/CXCR4 pathway operates during monocytopoiesis, but is deregulated in AMLs. AMD3100 treatment and miR-146a overexpression were used to inhibit CXCR4 in leukemic cells. AMD3100 treatment induces the decrease of CXCR4 protein expression, associated with miR-146a increase, and increases sensitivity of leukemic blast cells to cytotoxic drugs, this effect being further enhanced by miR-146a overexpression. Altogether our data indicate that miR-146a and AMD3100, acting through different mechanism, downmodulate CXCR4 protein levels, impair leukemic cell proliferation and then may be used in combination with anti-leukemia drugs, for development of new therapeutic strategies

Mutation analysis of the CHK2 gene in breast carcinoma and other cancers

BACKGROUND: Mutations in the CHK2 gene at chromosome 22q12.1 have been reported in families with Li-Fraumeni syndrome. Chk2 is an effector kinase that is activated in response to DNA damage and is involved in cell-cycle pathways and p53 pathways. METHODS: We screened 139 breast tumors for loss of heterozygosity at chromosome 22q, using seven microsatellite markers, and screened 119 breast tumors with single-strand conformation polymorphism and DNA sequencing for mutations in the CHK2 gene. RESULTS: Seventy-four of 139 sporadic breast tumors (53%) show loss of heterozygosity with at least one marker. These samples and 45 tumors from individuals carrying the BRCA2 999del5 mutation were screened for mutations in the CHK2 gene. In addition to putative polymorphic regions in short mononucleotide repeats in a non-coding exon and intron 2, a germ line variant (T59K) in the first coding exon was detected. On screening 1172 cancer patients for the T59K sequence variant, it was detected in a total of four breast-cancer patients, two colon-cancer patients, one stomach-cancer patient and one ovary-cancer patient, but not in 452 healthy individuals. A tumor-specific 5' splice site mutation at site +3 in intron 8 (TTgt [a → c]atg) was also detected. CONCLUSION: We conclude that somatic CHK2 mutations are rare in breast cancer, but our results suggest a tumor suppressor function for CHK2 in a small proportion of breast tumors. Furthermore, our results suggest that the T59K CHK2 sequence variant is a low-penetrance allele with respect to tumor growth

In Vivo Deficiency of Both C/EBPβ and C/EBPε Results in Highly Defective Myeloid Differentiation and Lack of Cytokine Response

The CCAAT/enhancer binding proteins (C/EBPs) are transcription factors involved in hematopoietic cell development and induction of several inflammatory mediators. Here, we generated C/EBPβ and C/EBPε double-knockout (bbee) mice and compared their phenotypes to those of single deficient (bbEE and BBee) and wild-type (BBEE) mice. The bbee mice were highly susceptible to fatal infections and died within 2–3 months. Morphologically, their neutrophils were blocked at the myelocytes/metamyelocytes stage, and clonogenic assays of bone marrow cells indicated a significant decrease in the number of myeloid colonies of the bbee mice. In addition, the proportion of hematopoietic progenitor cells [Lin(−)Sca1(+)c-Kit(+)] in the bone marrow of the bbee mice was significantly increased, reflecting the defective differentiation of the myeloid compartment. Furthermore, microarray expression analysis of LPS- and IFNγ-activated bone marrow-derived macrophages from bbee compared to single knockout mice revealed decreased expression of essential immune response-related genes and networks, including some direct C/EBP-targets such as Marco and Clec4e. Overall, the phenotype of the bbee mice is distinct from either the bbEE or BBee mice, demonstrating that both transcription factors are crucial for the maturation of neutrophils and macrophages, as well as the innate immune system, and can at least in part compensate for each other in the single knockout mice

Connectivity precedes function in the development of the visual word form area

What determines the cortical location at which a given functionally specific region will arise in development? We tested the hypothesis that functionally specific regions develop in their characteristic locations because of pre-existing differences in the extrinsic connectivity of that region to the rest of the brain. We exploited the visual word form area (VWFA) as a test case, scanning children with diffusion and functional imaging at age 5, before they learned to read, and at age 8, after they learned to read. We found the VWFA developed functionally in this interval and that its location in a particular child at age 8 could be predicted from that child's connectivity fingerprints (but not functional responses) at age 5. These results suggest that early connectivity instructs the functional development of the VWFA, possibly reflecting a general mechanism of cortical development.National Institutes of Health (U.S.) (Grant F32HD079169)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (Grant F32HD079169)National Institutes of Health (U.S.) (Grant R01HD067312)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (Grant R01HD067312

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases

Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

Short-term learning induces white matter plasticity in the fornix

Magnetic resonance imaging (MRI) has greatly extended the exploration of neuroplasticity in behaving animals and humans. Imaging studies recently uncovered structural changes that occur in gray and white matter, mainly after long-term training. A recent diffusion tensor imaging (DTI) study showed that training in a car racing game for 2 h induces changes in the hippocampus and parahippocampal gyri. However, the effect of short-term training on the white matter microstructure is unknown. Here we investigated the influence of short learning tasks on structural plasticity in the white matter, and specifically in the fornix, in humans and rats. Human subjects performed a 2 h spatial learning task, and rats underwent training for 1 d in a Morris water maze. Between tasks, subjects were scanned with DTI, a diffusion MRI framework sensitive to tissue microstructure. Using tract-based spatial statistics, we found changes in diffusivity indices in both humans and rats. In both species, changes in diffusion in the fornix were correlated with diffusion changes in the hippocampus, as well as with behavioral measures of improvement in the learning tasks. These results, which provide the first indication of short-term white matter plasticity in the human brain, suggest that the adult brain white matter preserves dynamic characteristics and can be modified by short-term learning experiences. The extent of change in white matter was correlated with their extent in gray matter, suggesting that all components of the neural network are capable of rapid remodeling in response to cognitive experiences

Short-term learning induces white matter plasticity in the fornix

Magnetic resonance imaging (MRI) has greatly extended the exploration of neuroplasticity in behaving animals and humans. Imaging studies recently uncovered structural changes that occur in gray and white matter, mainly after long-term training. A recent diffusion tensor imaging (DTI) study showed that training in a car racing game for 2 h induces changes in the hippocampus and parahippocampal gyri. However, the effect of short-term training on the white matter microstructure is unknown. Here we investigated the influence of short learning tasks on structural plasticity in the white matter, and specifically in the fornix, in humans and rats. Human subjects performed a 2 h spatial learning task, and rats underwent training for 1 d in a Morris water maze. Between tasks, subjects were scanned with DTI, a diffusion MRI framework sensitive to tissue microstructure. Using tract-based spatial statistics, we found changes in diffusivity indices in both humans and rats. In both species, changes in diffusion in the fornix were correlated with diffusion changes in the hippocampus, as well as with behavioral measures of improvement in the learning tasks. These results, which provide the first indication of short-term white matter plasticity in the human brain, suggest that the adult brain white matter preserves dynamic characteristics and can be modified by short-term learning experiences. The extent of change in white matter was correlated with their extent in gray matter, suggesting that all components of the neural network are capable of rapid remodeling in response to cognitive experiences