Expression of Interleukin-1 and Interleukin-1 Receptors Type 1 and Type 2 in Hodgkin Lymphoma

Signaling through the IL-1-receptor type 1 (IL-1R1), IL-1 is required for initiation and maintenance of diverse activities of the immune system. A second receptor, IL-1R2, blocks IL-1 signal transduction. We studied expression of IL-1beta, IL-1R1, and IL-1R2 in 17 Hodgkin lymphomas (HL) by in situ hybridization (ISH). IL-1beta expressing cells, morphologically consistent with endothelial cells and fibroblasts, occurred in all HL tissues with elevated transcript levels in areas of active fibrosis. Hodgkin and Reed-Sternberg (HRS) cells of all cases expressed low IL-1R1 transcript levels in some tumor cells, and high levels of IL-1R2 in large proportions of HRS cells. Only few bystander cells showed low levels of IL-1R1 and IL-1R2 RNA. Supernatants of 4 out of 7 HL-derived cell lines contained soluble IL-1R2 protein at high levels. HL patient sera carried variably amounts of IL-1R2 protein with significantly increased titers in patients with active disease compared to patients in complete remission and control individuals without HL. Western blots and co-immunoprecipitations showed binding of the IL-1R2 to the intracellular IL-1R-accessory protein (IL-1IRAcP). These data suggest functions of the IL-1R2 as a „decoy-receptor” sequestrating paracrine IL-1 extracellularly and intracellularly by engaging IL-1IRAcP, thus depriving IL1-R1 molecules of their extracellular and intracellular ligands. Expression of IL1-R2 by HRS cells seems to contribute to local and systemic modulation of immune function in HL

Stabilized immersed isogeometric analysis for the Navier-Stokes-Cahn-Hilliard equations, with applications to binary-fluid flow through porous media

Binary-fluid flows can be modeled using the Navier-Stokes-Cahn-Hilliard equations, which represent the boundary between the fluid constituents by a diffuse interface. The diffuse-interface model allows for complex geometries and topological changes of the binary-fluid interface. In this work, we propose an immersed isogeometric analysis framework to solve the Navier-Stokes-Cahn-Hilliard equations on domains with geometrically complex external binary-fluid boundaries. The use of optimal-regularity B-splines results in a computationally efficient higher-order method. The key features of the proposed framework are a generalized Navier-slip boundary condition for the tangential velocity components, Nitsche's method for the convective impermeability boundary condition, and skeleton- and ghost-penalties to guarantee stability. A binary-fluid Taylor-Couette flow is considered for benchmarking. Porous medium simulations demonstrate the ability of the immersed isogeometric analysis framework to model complex binary-fluid flow phenomena such as break-up and coalescence in complex geometries

Identification of common variants associated with human hippocampal and intracranial volumes

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer\u27s disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7))

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA\u27s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way

Bounds on the diameter of Cayley graphs of the symmetric group

In this paper we are concerned with the conjecture that, for any set of generators S of the symmetric group of degree n, the word length in terms of S of every permutation is bounded above by a polynomial of n. We prove this conjecture for sets of generators containing a permutation fixing at least 37% of the points.Comment: 17 pages, 6 table

Least Dependent Component Analysis Based on Mutual Information

We propose to use precise estimators of mutual information (MI) to find least dependent components in a linearly mixed signal. On the one hand this seems to lead to better blind source separation than with any other presently available algorithm. On the other hand it has the advantage, compared to other implementations of `independent' component analysis (ICA) some of which are based on crude approximations for MI, that the numerical values of the MI can be used for: (i) estimating residual dependencies between the output components; (ii) estimating the reliability of the output, by comparing the pairwise MIs with those of re-mixed components; (iii) clustering the output according to the residual interdependencies. For the MI estimator we use a recently proposed k-nearest neighbor based algorithm. For time sequences we combine this with delay embedding, in order to take into account non-trivial time correlations. After several tests with artificial data, we apply the resulting MILCA (Mutual Information based Least dependent Component Analysis) algorithm to a real-world dataset, the ECG of a pregnant woman. The software implementation of the MILCA algorithm is freely available at http://www.fz-juelich.de/nic/cs/softwareComment: 18 pages, 20 figures, Phys. Rev. E (in press

Existence of Weak Solutions for a Diffuse Interface Model for Two-Phase Flows of Incompressible Fluids with Different Densities

We prove existence of weak solutions for a diffuse interface model for the flow of two viscous incompressible Newtonian fluids in a bounded domain in two and three space dimensions. In contrast to previous works, we study a new model recently developed by Abels, Garcke, and Gr\"un for fluids with different densities, which leads to a solenoidal velocity field. The model is given by a non-homogeneous Navier-Stokes system with a modified convective term coupled to a Cahn-Hilliard system. The density of the mixture depends on an order parameter.Comment: 33 page

Multi‐model GWAS reveals key loci for horticultural traits in reconstructed garden strawberry

The cultivated garden strawberry (Fragaria × ananassa) has a rich history, originating from the hybridization of two wild octoploid strawberry species in the 18th century. Two-step reconstruction of Fragaria × ananassa through controlled crossings between pre-improved selections of its parental species is a promising approach for enriching the breeding germplasm of strawberry for wider adaptability. We created a population of reconstructed strawberry by hybridizing elite selections of F. virginiana and F. chiloensis. A replicated field experiment was conducted to evaluate the population's performance for eleven horticulturally important traits, over multiple years. Population structure analyses based on Fana-50 k SNP array data confirmed pedigree-based grouping of the progenies into four distinct groups. As complex traits are often influenced by environmental variables, and population structure can lead to spurious associations, we tested multiple genome-wide association study (GWAS) models. GWAS uncovered 39 quantitative trait loci (QTL) regions for eight traits distributed across twenty chromosomes, including 11 consistent and 28 putative QTLs. Candidate genes for traits including winter survival, flowering time, runnering vigor, and hermaphrodism were identified within the QTL regions. To our knowledge, this study marks the first comprehensive investigation of adaptive and horticultural traits in a large, multi-familial reconstructed strawberry population using SNP markers

Total late effect burden in long-term lymphoma survivors after high-dose therapy with autologous stem-cell transplant and its effect on health-related quality of life

Lymphoma survivors after high-dose therapy with autologous stem-cell transplant (HDT-ASCT) are at risk of several late effects, which might impair their health-related quality of life (HRQoL). We assessed the total late effect burden in this population, and how it affects HRQoL. All lymphoma survivors treated with HDT-ASCT as adults in Norway between 1987 and 2008 were identified, and 271 (68%) attended both a comprehensive clinical assessment and completed a questionnaire. Severity of 45 conditions in 12 organ-system categories were graded as mild, moderate, severe or life-threatening, according to a modified version of CTCAEv4.03. At a median of 8 years after HDT-ASCT, 98% of survivors had at least one moderate or more severe late effect and 56% had severe or life-threatening late effects. Fourteen percent had low, 39% medium and 47% high late effect burden, defined as having moderate or more severe late effects in 0-1, 2-3 and >3 organsystems, respectively. Female sex, increasing age, B-symptoms at diagnosis and >1 treatment line prior to HDT-ASCT were independently associated with having high late effect burden. The survivors had significantly poorer physical and mental HRQoL assessed by the Short Form-36 compared to age- and sex-matched controls. The prevalence of poor physical and mental HRQoL increased with higher late effect burden (both P<0.001), and the low burden group had better physical HRQoL than controls (P<0.001). In conclusion, lymphoma survivors after HDT-ASCT have impaired HRQoL, seemingly driven by a high late effect burden. This highlights the importance of prevention, regular assessments for early detection and treatment of late effects and modifiable risk factors