19 research outputs found
Re-meshing algorithms applied to mould filling Simulations in resin transfer moulding
In injection moulding processes such as Resin Transfer Moulding (RTM) for example, numerical simulations are usually performed with a fixed mesh, on which the displacement of the flow front is predicted by the numerical algorithm. During the injection, special physical phenomena occur on the front, such as capillary effects inside the fibre tows or heat transfer when the fluid is injected at a different temperature than the mould. In order to approximate these phenomena accurately, it is always better to adapt the mesh to the shape of the flow front. This can be achieved by implementing re-meshing algorithms, which will provide not only more accurate solutions, but also faster calculations. In order to represent precisely the shape of the saturated domain in the cavity, the mesh needs to be non-isotropic in the vicinity of the flow front. The size of the elements along the front is connected to the overall accuracy needed for the simulation; the size in the perpendicular direction governs the accuracy on the position of the moving boundary in time. Since these two constraints on element size are not related, the need for non-isotropic mesh refinement is crucial. In the approach proposed here, the mesh is changed at each time step from a background isotropic mesh used as starting point in the refinement algorithm. The solution needs to be projected on the new mesh after each re-meshing. This amounts to adopting a new filling algorithm, which will be validated by comparison to a standard simulation (without re-meshing) and with experimental data
A topological model for the representation of meshing constraints in the context of finite element analysis
International audienc
Simulations in Resin Transfer Moulding
Citations (this article cites 10 articles hosted on th
Impact of microsatellite instability and p53 expression on stage III colon cancer disease-free survival in patients treated by fluorouracil and leucovorin with or without oxaliplatin
Application des dosages par immunoéphélémétrie microparticulaire des caséines alpha, beta et kappa à l'évaluation de la qualité du lait, de sa production à sa valorisation fromagère
National audienc
Expression of MYC, IgM, As Well As Non-Germinal Centre B-Cell Like Immunophenotype and Positive Immunofish Index Predict a Worse Progression Free Survival and Overall Survival in a Series of 670 De Novo Diffuse Large B-Cell Lymphomas Included in Clinical Trials: A GELA Study of the 2003 Program
Introduction: Diffuse large B-cell lymphomas (DLBCL) represent a heterogeneous disease with variable clinical outcome. Identifying phenotypic biomarkers of tumor cells on paraffin sections that predict different clinical outcome remain an important goal that may also help to better understand the biology of this lymphoma. Differentiating non-germinal centre B-cell-like (non-GCB) from Germinal Centre B-cell-like (GCB) DLBCL according to Hans algorithm has been considered as an important immunohistochemical biomarker with prognostic value among patients treated with R-CHOP although not reproducibly found by all groups. Gene expression studies have also shown that IgM expression might be used as a surrogate for the GCB and ABC subtypes with a strong preferential expression of IgM in ABC DLBCL subtype. ImmunoFISH index based on the differential expression of MUM-1, FOXP1 by immunohistochemistry and on the BCL6 rearrangement by FISH has been previously reported (C Copie-Bergman, J Clin Oncol. 2009;27:5573-9) as prognostic in an homogeneous series of DLBCL treated with R-CHOP. In addition, oncogenic MYC protein overexpression by immunohistochemistry may represent an easy tool to identify the consequences of MYC deregulation in DLBCL.
Our aim was to analyse by immunohistochemistry the prognostic relevance of MYC, IgM, GCB/nonGCB subtype and ImmunoFISH index in a large series of de novo DLBCL treated with Rituximab (R)-chemotherapy (anthracyclin based) included in the 2003 program of the Groupe d'Etude des Lymphomes de l'Adulte (GELA) trials.
Methods: The 2003 program included patients with de novo CD20+ DLBCL enrolled in 6 different LNH-03 GELA trials (LNH-03-1B, -B, -3B, 39B, -6B, 7B) stratifying patients according to age and age-adjusted IPI. Tumor samples were analyzed by immunohistochemistry using CD10, BCL6, MUM1, FOXP1 (according to Barrans threshold), MYC, IgM antibodies on tissue microarrays and by FISH using BCL6 split signal DNA probes. Considering evaluable Hans score, 670 patients were included in the study with 237 (35.4%) receiving intensive R-ACVBP regimen and 433 (64.6%) R-CHOP/R-mini-CHOP.
Results: 304 (45.4%) DLBCL were classified as GCB and 366 (54.6%) as non-GCB according to Hans algorithm. 337/567 cases (59.4%) were positive for the ImmunoFISH index (i.e. two out of the three markers positive: MUM1 protein positive, FOXP1 protein Variable or Strong, BCL6 rearrangement). Immunofish index was preferentially positive in the non-GCB subtype (81.3%) compared to the GCB subtype (31.2%), (p<0.001). IgM was recorded as positive in tumor cells in 351/637 (52.4%) DLBCL cases with a preferential expression in non-GCB 195 (53.3%) vs GCB subtype 100(32.9%), p<0.001). MYC was positive in 170/577 (29.5%) cases with a 40% cut-off and in 44/577 (14.2%) cases with a cut-off of 70%. There was no preferential expression of MYC among GCB or non-GCB subtype (p>0.4) for both cut-offs.
Progression-free Survival (PFS) was significantly worse among patients with high IPI score (p<0.0001), IgM positive tumor (p<0.0001), MYC positive tumor with a 40% threshold (p<0.001), ImmunoFISH positive index (p<0.002), non-GCB DLBCL subtype (p<0.0001).
Overall Survival (OS) was also significantly worse among patients with high IPI score (p<0.0001), IgM positive tumor (p=0.02), MYC positive tumor with a 40% threshold (p<0.01), ImmunoFISH positive index (p=0.02), non-GCB DLBCL subtype (p<0.0001).
All significant parameters were included in a multivariate analysis using Cox Model and in addition to IPI, only the GCB/non-GCB subtype according to Hans algorithm predicted significantly a worse PFS among non-GCB subgroup (HR 1.9 [1.3-2.8] p=0.002) as well as a worse OS (HR 2.0 [1.3-3.2], p=0.003). This strong prognostic value of non-GCB subtyping was confirmed considering only patients treated with R- CHOP for PFS (HR 2.1 [1.4-3.3], p=0.001) and for OS (HR 2.3 [1.3-3.8], p=0.002).
Conclusion: Our study on a large series of patients included in trials confirmed the relevance of immunohistochemistry as a useful tool to identify significant prognostic biomarkers for clinical use. We show here that IgM and MYC might be useful prognostic biomarkers. In addition, we confirmed in this series the prognostic value of the ImmunoFISH index. Above all, we fully validated the strong and independent prognostic value of the Hans algorithm, daily used by the pathologists to subtype DLBCL
Molecular Function of TCF7L2: Consequences of TCF7L2 Splicing for Molecular Function and Risk for Type 2 Diabetes.
TCF7L2 harbors the variant with the strongest effect on type 2 diabetes (T2D) identified to date, yet the molecular mechanism as to how variation in the gene increases the risk for developing T2D remains elusive. The phenotypic changes associated with the risk genotype suggest that T2D arises as a consequence of reduced islet mass and/or impaired function, and it has become clear that TCF7L2 plays an important role for several vital functions in the pancreatic islet. TCF7L2 comprises 17 exons, five of which are alternative (ie, exons 4 and 13-16). In pancreatic islets four splice variants of TCF7L2 are predominantly expressed. The regulation of these variants and the functional consequences at the protein level are still poorly understood. A clear picture of the molecular mechanism will be necessary to understand how an intronic variation in TCF7L2 can influence islet function