[11C]-l-Methionine positron emission tomography in the management of children and young adults with brain tumors

Only a few Methyl-[11C]-l-methionine (MET) positron emission tomography (PET) studies have focused on children and young adults with brain neoplasm. Due to radiation exposure, long scan acquisition time, and the need for sedation in young children MET-PET studies should be restricted to this group of patients when a decision for further therapy is not possible from routine diagnostic procedures alone, e.g., structural imaging. We investigated the diagnostic accuracy of MET-PET for the differentiation between tumorous and non-tumorous lesions in this group of patients. Forty eight MET-PET scans from 39 patients aged from 2 to 21 years (mean 15 ± 5.0 years) were analyzed. The MET tumor-uptake relative to a corresponding control region was calculated. A receiver operating characteristic (ROC) was performed to determine the MET-uptake value that best distinguishes tumorous from non-tumorous brain lesions. A differentiation between tumorous (n = 39) and non-tumorous brain lesions (n = 9) was possible at a threshold of 1.48 of relative MET-uptake with a sensitivity of 83% and a specificity of 92%, respectively. A differentiation between high grade malignant lesions (mean MET-uptake = 2.00 ± 0.46) and low grade tumors (mean MET-uptake = 1.84 ± 0.31) was not possible. There was a significant difference in MET-uptake between the histologically homogeneous subgroups of astrocytoma WHO grade II and anaplastic astrocytoma WHO grade III (P = 0.02). MET-PET might be a useful tool to differentiate tumorous from non-tumorous lesions in children and young adults when a decision for further therapy is difficult or impossible from routine structural imaging procedures alone

Characterisation of five candidate genes within the ETEC F4ab/ac candidate region in pigs

BACKGROUND: Enterotoxigenic Escherichia coli (ETEC) that express the F4ab and F4ac fimbriae is a major contributor to diarrhoea outbreaks in the pig breeding industry, infecting both newborn and weaned piglets. Some pigs are resistant to this infection, and susceptibility is inherited as a simple dominant Mendelian trait. Indentifying the genetics behind this trait will greatly benefit pig welfare as well as the pig breeding industry by providing an opportunity to select against genetically susceptible animals, thereby reducing the number of diarrhoea outbreaks. The trait has recently been mapped by haplotype sharing to a 2.5 Mb region on pig chromosome 13, a region containing 18 annotated genes. FINDINGS: The coding regions of five candidate genes for susceptibility to ETEC F4ab/ac infection (TFRC, ACK1, MUC20, MUC4 and KIAA0226), all located in the 2.5 Mb region, were investigated for the presence of possible causative mutations. A total of 34 polymorphisms were identified in either coding regions or their flanking introns. The genotyping data for two of those were found to perfectly match the genotypes at the ETEC F4ab/ac locus, a G to C polymorphism in intron 11 of TFRC and a C to T silent polymorphism in exon 22 of KIAA0226. Transcriptional profiles of the five genes were investigated in a porcine tissue panel including various intestinal tissues. All five genes were expressed in intestinal tissues at different levels but none of the genes were found differentially expressed between ETEC F4ab/ac resistant and ETEC F4ab/ac susceptible animals in any of the tested tissues. CONCLUSIONS: None of the identified polymorphisms are obvious causative mutations for ETEC F4ab/ac susceptibility, as they have no impact on the level of the overall mRNA expression nor predicted to influence the composition of the amino acids composition. However, we cannot exclude that the five tested genes are bona fide candidate genes for susceptibility to ETEC F4ab/ac infection since the identified polymorphism might affect the translational apparatus, alternative splice forms may exist and post translational mechanisms might contribute to disease susceptibility

Novel methodology for predicting the critical salt concentration of bubble coalescence inhibition

Bubble coalescence in some salt solutions can be inhibited if the salt concentration reaches a critical concentration Ccr. There are three models available for Ccr in the literature, but they fail to predict Ccr correctly. The first two models employ the van der Waals attraction power laws to establish Ccr from the discriminant of quadratic or cubic polynomials. To improve the two models, the third model uses the same momentum balance equation of the previous models but different intermolecular force generated by water hydration with exponential decaying. The third prediction for Ccr requires the experimental input for film rupture thickness and is incomplete. We show further in this paper that the third model is incorrect. We propose a novel methodology for determining C cr which resolves the mathematical uncertainties in modeling C cr and can explicitly predict it from any relevant intermolecular forces. The methodology is based on the discovery that Ccr occurs at the local maximum of the balance equation for the capillary pressure, disjoining pressure, and pressure of the Gibbs-Marangoni stress. The novel generic approach is successfully validated using nonlinear equations for complicated disjoining pressure

Identification of novel target genes of nerve growth factor (NGF) in human mastocytoma cell line (HMC-1 (V560G c-Kit)) by transcriptome analysis

<p>Abstract</p> <p>Background</p> <p>Nerve growth factor (NGF) is a potent growth factor that plays a key role in neuronal cell differentiation and may also play a role in hematopoietic differentiation. It has been shown that NGF induced synergistic action for the colony formation of CD34 positive hematopoietic progenitor cells treated with macrophage-colony stimulating factor (M-CSF or CSF-1), or stem cell factor (SCF). However, the exact role of NGF in hematopoietic system is unclear. It is also not clear whether NGF mediated signals in hematopoietic cells are identical to those in neuronal cells.</p> <p>Results</p> <p>To study the signal transduction pathways induced by NGF treatment in hematopoietic cells, we utilized the mastocytoma cell line HMC-1(V560G c-Kit) which expresses the NGF receptor, tropomyosin-receptor-kinase (Trk)A, as well as the constitutively activated SCF receptor, V560G c-Kit, which can be inhibited completely by treatment with the potent tyrosine kinase inhibitor imatinib mesylate (imatinib). NGF rescues HMC-1(V560G c-Kit) cells from imatinib mediated cell death and promotes proliferation. To examine the NGF mediated proliferation and survival in these cells, we compared the NGF mediated upregulated genes (30 and 120 min after stimulation) to the downregulated genes by imatinib treatment (downregulation of c-Kit activity for 4 h) by transcriptome analysis. The following conclusions can be drawn from the microarray data: Firstly, gene expression profiling reveals 50% overlap of genes induced by NGF-TrkA with genes expressed downstream of V560G c-Kit. Secondly, NGF treatment does not enhance expression of genes involved in immune related functions that were down regulated by imatinib treatment. Thirdly, more than 55% of common upregulated genes are involved in cell proliferation and survival. Fourthly, we found Kruppel-like factor (KLF) 2 and Smad family member 7 (SMAD7) as the NGF mediated novel downstream genes in hematopoietic cells. Finally, the downregulation of KLF2 gene enhanced imatinib induced apoptosis.</p> <p>Conclusion</p> <p>NGF does not induce genes which are involved in immune related functions, but induces proliferation and survival signals in HMC-1(V560G c-Kit) cells. Furthermore, the current data provide novel candidate genes, KLF2 and SMAD7 which are induced by NGF/TrkA activation in hematopoietic cells. Since the depletion of KLF2 causes enhanced apoptosis of HMC-1(V560G c-Kit), KLF2 may play a role in the NGF mediated survival signal.</p

Ecological networks: Pursuing the shortest path, however narrow and crooked

International audienceRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point checklist to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies. The last two decades have witnessed an exponential increase in the use of graph analysis in ecological and conservation studies (see refs. 1,2 for recent introductions to network theory in ecology and evolution). Networks (graphs) represent agents as nodes linked by edges representing pairwise relationships. For instance, a food web can be represented as a network of species (nodes) and their feeding relationships (edges) 3. Similarly, the spatial dynamics of a metapopulation can be analyzed by connecting the patches of suitable habitat (nodes) with edges measuring dispersal between patches 4. Data might either simply report the presence/absence of an edge (binary, unweighted networks), or provide a strength for each edge (weighted networks). In turn, these weights can represent a variety of ecologically-relevant quantities, depending on the system being described. For instance, edge weights can quantify interaction frequency (e.g., visitation networks 5), interaction strength (e.g., per-capita effect of one species on the growth rate of another 3), carbon-flow between trophic levels 6 , genetic similarity 7 , niche overlap (e.g., number of shared resources between two species 8), affinity 9 , dispersal probabilities (e.g., the rate at which individuals of a population move between patches 10), cost of dispersal between patches (e.g., resistance 11), etc. Despite such large variety of ecological network representations, a common task is the identification of nodes of high importance, such as keystone species in a food web, patches acting as stepping stones in a dispersal network , or genes with pleiotropic effects. The identification of important nodes is typically accomplished through centrality measures 5,12. Many centrality measures has been proposed, each probing complementary aspects of node-to-node relationships 13. For instance, Closeness centrality 14,15 highlights nodes that are "near" to all othe

Distinct IL-1α-responsive enhancers promote acute and coordinated changes in chromatin topology in a hierarchical manner

How cytokine-driven changes in chromatin topology are converted into gene regulatory circuits during inflammation still remains unclear. Here, we show that interleukin (IL)-1α induces acute and widespread changes in chromatin accessibility via the TAK1 kinase and NF-κB at regions that are highly enriched for inflammatory disease-relevant SNPs. Two enhancers in the extended chemokine locus on human chromosome 4 regulate the IL-1α-inducible IL8 and CXCL1-3 genes. Both enhancers engage in dynamic spatial interactions with gene promoters in an IL-1α/TAK1-inducible manner. Microdeletions of p65-binding sites in either of the two enhancers impair NF-κB recruitment, suppress activation and biallelic transcription of the IL8/CXCL2 genes, and reshuffle higher-order chromatin interactions as judged by i4C interactome profiles. Notably, these findings support a dominant role of the IL8 “master” enhancer in the regulation of sustained IL-1α signaling, as well as for IL-8 and IL-6 secretion. CRISPR-guided transactivation of the IL8 locus or cross-TAD regulation by TNFα-responsive enhancers in a different model locus supports the existence of complex enhancer hierarchies in response to cytokine stimulation that prime and orchestrate proinflammatory chromatin responses downstream of NF-κB