TLR3 and TLR4 expression in healthy and diseased human endometrium

<p>Abstract</p> <p>Background</p> <p>Toll-like receptors (TLRs) play an essential role in the innate immune system by initiating and directing immune response to pathogens. TLRs are expressed in the human endometrium and their regulation might be crucial for the pathogenesis of endometrial diseases.</p> <p>Methods</p> <p>TLR3 and TLR4 expression was investigated during the menstrual cycle and in postmenopausal endometrium considering peritoneal endometriosis, hyperplasia, and endometrial adenocarcinoma specimens (grade 1 to 3). The expression studies applied quantitative RT-PCR and immunolabelling of both proteins.</p> <p>Results</p> <p>TLR3 and TLR4 proteins were mostly localised to the glandular and luminal epithelium. In addition, TLR4 was present on endometrial dendritic cells, monocytes and macrophages. TLR3 and TLR4 mRNA levels did not show significant changes during the menstrual cycle. In patients with peritoneal endometriosis, TLR3 and TLR4 mRNA expression decreased significantly in proliferative diseased endometrium compared to controls. Interestingly, ectopic endometriotic lesions showed a significant increase of TLR3 und TLR4 mRNA expression compared to corresponding eutopic tissues, indicating a local gain of TLR expression. Endometrial hyperplasia and adenocarcinoma revealed significantly reduced receptor levels when compared with postmenopausal controls. The lowest TLR expression levels were determined in poor differentiated carcinoma (grade 3).</p> <p>Conclusion</p> <p>Our data suggest an involvement of TLR3 and TLR4 in endometrial diseases as demonstrated by altered expression levels in endometriosis and endometrial cancer.</p

t8code - scalable and modular adaptive mesh refinement

t8code is a versatile open source library for parallel adaptive mesh refinement on hybrid meshes. [1] It is exascale-ready and capable of efficiently managing meshes with up to a trillion elements distributed on a million of cores as already shown in a peer-reviewed research paper. [2] On the top-level, t8code uses forests of trees to represent unstructured meshes with complex geometries. Space-filling curves index individual elements within a forest, which requires only minimal amounts of memory allowing for efficient and scalable algorithms of mesh management. In contrast to existing solutions, t8code has the capability to manage an arbitrary number of tetrahedra, hexahedra, prisms and pyramids within the same mesh. With this poster we want to present the first official release (v1.0) of our software and give a quick overview over its main features. Besides presenting the core algorithms of t8code, we give application scenarios on how our library integrates into major simulation frameworks for weather forecasting, climate modeling and engineering; and how they benefit from our approach to do AMR. [1] https://github.com/DLR-AMR/t8code [2] https://epubs.siam.org/doi/abs/10.1137/20M138303

t8code

t8code is a C/C++ library to manage parallel adaptive meshes with various element types. t8code uses a collection (a forest) of multiple connected adaptive space-trees in parallel and scales to at least one million MPI ranks and over 1 Trillion mesh elements. t8code uses space-filling curves (SFCs) to manage the adaptive refinement and efficiently store the mesh elements and associated data

The Power of Modular Tree-Based AMR - Resolving Hanging Nodes and Cutting Holes

We discuss recent developments in scalable adaptive mesh refinement (AMR). The t8code library offers fast and efficient tree-based (space-filling curve) adaptive mesh refinement solutions for application codes that require meshes. t8code extends the space-filling curve (SFC) techniques from quadrilaterals and hexahedra to all element shapes via an abstract interface. In particular we offer implementations for vertices, lines, quads, triangles, tetrahedra, hexahedra, prisms and pyramids, and also support meshes including different element shapes. The abstract interface allows us to further extend the SFC techniques to non-standard use cases that enable fast and scalable AMR for a variety of use cases. In particular we present the feature deleting elements from the mesh and the feature subelements. Subelements itself are very powerful in that they allow for a variety of new AMR option. One application of us is to remove hanging nodes from quad based AMR. Other applications include the definition of boundary layer (for example around airfoils), anisotropic refinement or subgrids for GPU computations

t8code v. 1.0 - Modular Adaptive Mesh Refinement in the Exascale Era

In this note we present version 1.0 of our software library t8code for scalable dynamic adaptive mesh refinement (AMR) officially released in 2022. t8code is written in C/C++, open source, and readily available at www.dlr-amr.github.io/t8code. The library provides fast and memory efficient parallel algorithms for dynamic AMR to handle tasks such as mesh adaptation, load-balancing, ghost computation, feature search and more. t8code can manage meshes with over one trillion mesh elements and scales up to one million parallel processes. It is intended to be used as mesh management back end in scientific and engineering simulation codes paving the way towards high-performance applications of the upcoming exascale era

Generation of two human iPSC lines (HIMRi002-A and HIMRi003-A) derived from Caveolinopathy patients with rippling muscle disease

Here we introduce the human induced pluripotent stem cell lines (hiPSCs), HIMRi002-A and HIMRi003-A, generated from cultured dermal fibroblasts of 61-year-old (HIMRi002-A) and 38-year-old (HIMRi003-A) female patients, carrying a known heterozygous pathogenic variant ($\it p.A46T$) in the $\textit {Caveolin 3}$ ($\it CAV3$) gene, via lentiviral expression of OCT4, SOX2, KLF4 and c-MYC. HIMRi002-A and HIMRi003-A display typical embryonic stem cell-like morphology, carry the $\it p.A46T$ $\it CAV3$ gene mutation, express several pluripotent stem cell markers, retain normal karyotype (46, XX) and can differentiate in all three germ layers. We postulate that the HIMRi002-A and HIMRi003-A iPSC lines can be used for the characterization of $\it CAV3$-associated pathomechanisms and for developing new therapeutic options