PVP2009-78040 GROWTH BEHAVIOR OF TWO INTERACTING SURFACE CRACKS OF DISSIMILAR SIZE

ABSTRACT When multiple cracks approach to each other, the stress intensity factor is likely to change due to the interaction of the stress field. This causes change in the growth rate and the shape of cracks. Because of the orientation with respect to the loading, and existing of K II and K III which can develop and increase with interaction, the shape of cracks becomes non-planar. In this study, the complex growth of interacting cracks is evaluated by using the S-Version finite element method, in which local detailed finite element mesh (local mesh) is superposed on coarse finite element model (global mesh) representing the global structure. The effect of relative size and spacing of cracks on the growth behavior is investigated. It is shown that the smallest crack stops growing due to the interaction when the difference in size of two cracks is large enough. INTRODUCTION Fatigue fracture of mechanical components sometimes causes a catastrophic accident. It is very important to predict the fatigue crack growth. Fracture mechanics can predict the crack growth rate by using Paris' law. Under mixed mode loading condition, crack growth direction can also be estimated well. For these predictions, precise numerical analysis is needed. Presently, FEM is generally used for this purpose

Aberrantly methylated genes in human papillary thyroid cancer and their association with BRAF/RAS mutation

Cancer arises through accumulation of epigenetic and genetic alteration. Aberrant promoter methylation is a common epigenetic mechanism of gene silencing in cancer cells. We here performed genome-wide analysis of DNA methylation of promoter regions by Infinium HumanMethylation27 BeadChip, using 14 clinical papillary thyroid cancer samples and 10 normal thyroid samples. Among the 14 papillary cancer cases, 11 showed frequent aberrant methylation, but the other three cases showed no aberrant methylation at all. Distribution of the hypermethylation among cancer samples was non-random, which implied existence of a subset of preferentially methylated papillary thyroid cancer. Among 25 frequently methylated genes, methylation status of six genes (HIST1H3J, POU4F2, SHOX2, PHKG2, TLX3, HOXA7) was validated quantitatively by pyrosequencing. Epigenetic silencing of these genes in methylated papillary thyroid cancer cell lines was confirmed by gene re-expression following treatment with 5-aza-2′-deoxycytidine and trichostatin A, and detected by real-time RT-PCR. Methylation of these six genes was validated by analysis of additional 20 papillary thyroid cancer and 10 normal samples. Among the 34 cancer samples in total, 26 cancer samples with preferential methylation were significantly associated with mutation of BRAF/RAS oncogene (P = 0.04, Fisher's exact test). Thus, we identified new genes with frequent epigenetic hypermethylation in papillary thyroid cancer, two subsets of either preferentially methylated or hardly methylated papillary thyroid cancer, with a concomitant occurrence of oncogene mutation and gene methylation. These hypermethylated genes may constitute potential biomarkers for papillary thyroid cancer

Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma

To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma between radiologists and a deep learning (DL) system.Ninety patients (50 men, 40 women; mean age, 66 years; range, 40-88 years) who underwent pre-operative chest computed tomography (CT) with 0.625-mm slice thickness were included in this retrospective study. Twenty-four cases of adenocarcinoma in situ (AIS), 20 cases of minimally invasive adenocarcinoma (MIA), and 46 cases of invasive adenocarcinoma (IVA) were pathologically diagnosed. Three radiologists of different levels of experience diagnosed each nodule by using previously documented CT findings to predict pathological invasiveness. DL was structured using a 3-dimensional (3D) convolutional neural network (3D-CNN) constructed with 2 successive pairs of convolution and max-pooling layers, and 2 fully connected layers. The output layer comprises 3 nodes to recognize the 3 conditions of adenocarcinoma (AIS, MIA, and IVA) or 2 nodes for 2 conditions (AIS and MIA/IVA). Results from DL and the 3 radiologists were statistically compared.No significant differences in pathological diagnostic accuracy rates were seen between DL and the 3 radiologists (P>. 11). Receiver operating characteristic analysis demonstrated that area under the curve for DL (0.712) was almost the same as that for the radiologist with extensive experience (0.714; P=. 98). Compared with the consensus results from radiologists, DL offered significantly inferior sensitivity (P=. 0005), but significantly superior specificity (P=. 02).Despite the small training data set, diagnostic performance of DL was almost the same as the radiologist with extensive experience. In particular, DL provided higher specificity than radiologists

In vitro generation of cytotoxic and regulatory T cells by fusions of human dendritic cells and hepatocellular carcinoma cells

<p>Abstract</p> <p>Background</p> <p>Human hepatocellular carcinoma (HCC) cells express WT1 and/or carcinoembryonic antigen (CEA) as potential targets for the induction of antitumor immunity. In this study, generation of cytotoxic T lymphocytes (CTL) and regulatory T cells (Treg) by fusions of dendritic cells (DCs) and HCC cells was examined.</p> <p>Methods</p> <p>HCC cells were fused to DCs either from healthy donors or the HCC patient and investigated whether supernatants derived from the HCC cell culture (HCCsp) influenced on the function of DCs/HCC fusion cells (FCs) and generation of CTL and Treg.</p> <p>Results</p> <p>FCs coexpressed the HCC cells-derived WT1 and CEA antigens and DCs-derived MHC class II and costimulatory molecules. In addition, FCs were effective in activating CD4⁺and CD8⁺T cells able to produce IFN-γ and inducing cytolysis of autologous tumor or semiallogeneic targets by a MHC class I-restricted mechanism. However, HCCsp induced functional impairment of DCs as demonstrated by the down-regulation of MHC class I and II, CD80, CD86, and CD83 molecules. Moreover, the HCCsp-exposed DCs failed to undergo full maturation upon stimulation with the Toll-like receptor 4 agonist penicillin-inactivated <it>Streptococcus pyogenes</it>. Interestingly, fusions of immature DCs generated in the presence of HCCsp and allogeneic HCC cells promoted the generation of CD4⁺CD25^highFoxp3⁺Treg and inhibited CTL induction in the presence of HCCsp. Importantly, up-regulation of MHC class II, CD80, and CD83 on DCs was observed in the patient with advanced HCC after vaccination with autologous FCs. In addition, the FCs induced WT1- and CEA-specific CTL that were able to produce high levels of IFN-γ.</p> <p>Conclusion</p> <p>The current study is one of the first demonstrating the induction of antigen-specific CTL and the generation of Treg by fusions of DCs and HCC cells. The local tumor-related factors may favor the generation of Treg through the inhibition of DCs maturation; however, fusion cell vaccination results in recovery of the DCs function and induction of antigen-specific CTL responses in vitro. The present study may shed new light about the mechanisms responsible for the generation of CTL and Treg by FCs.</p