11 research outputs found
Effect of self healing and continuous hydration on the mechanical properties of cyclically loaded early age concrete: A case study of early age cyclic loading on a concrete bridge deck
No full textIn this research work, the possibility of self healing of surface micro-cracks under the fog curing conditions has been studied for early age concrete. Coda Wave Interferometry (CWI) technique has been implemented to detect the micro cracks in concrete caused due to the cyclic loading. 30 load cycles has been for varying load levels and it's effect on the mechanical properties has been analyzed for early age concrete.Civil Engineering | Structural Engineering | Concrete Structure
CPPD crowned dens syndrome with clivus destruction: a case report.
No full textWe report a case of CPPD crowned dens syndrome in an 87 year white old male with a known history of pseudogout, with clinical and radiological features characteristic of this syndrome. Interestingly, there was significant mass effect on the clivus, with clivus erosion and destruction, a finding that has not previously been described with this syndrome. The clinical and radiological characteristics of Crowned Dens syndrome, as well as CPPD are reviewed. We suggest that CPPD crowned dens syndrome may be included in the differential diagnosis when clivus destruction or erosion, in association with a soft tissue mass with calcification, is seen
Meta-Analysis of the Luminal and Basal Subtypes of Bladder Cancer and the Identification of Signature Immunohistochemical Markers for Clinical Use
No full textAbstractBackgroundIt has been suggested that bladder cancer can be divided into two molecular subtypes referred to as luminal and basal with distinct clinical behaviors and sensitivities to chemotherapy. We aimed to validate these subtypes in several clinical cohorts and identify signature immunohistochemical markers that would permit simple and cost-effective classification of the disease in primary care centers.MethodsWe analyzed genomic expression profiles of bladder cancer in three cohorts of fresh frozen tumor samples: MD Anderson (n=132), Lund (n=308), and The Cancer Genome Atlas (TCGA) (n=408) to validate the expression signatures of luminal and basal subtypes and relate them to clinical follow-up data. We also used an MD Anderson cohort of archival bladder tumor samples (n=89) and a parallel tissue microarray to identify immunohistochemical markers that permitted the molecular classification of bladder cancer.FindingsBladder cancers could be assigned to two candidate intrinsic molecular subtypes referred to here as luminal and basal in all of the datasets analyzed. Luminal tumors were characterized by the expression signature similar to the intermediate/superficial layers of normal urothelium. They showed the upregulation of PPARγ target genes and the enrichment for FGFR3, ELF3, CDKN1A, and TSC1 mutations. In addition, luminal tumors were characterized by the overexpression of E-Cadherin, HER2/3, Rab-25, and Src. Basal tumors showed the expression signature similar to the basal layer of normal urothelium. They showed the upregulation of p63 target genes, the enrichment for TP53 and RB1 mutations, and overexpression of CD49, Cyclin B1, and EGFR. Survival analyses showed that the muscle-invasive basal bladder cancers were more aggressive when compared to luminal cancers. The immunohistochemical expressions of only two markers, luminal (GATA3) and basal (KRT5/6), were sufficient to identify the molecular subtypes of bladder cancer with over 90% accuracy.InterpretationThe molecular subtypes of bladder cancer have distinct clinical behaviors and sensitivities to chemotherapy, and a simple two-marker immunohistochemical classifier can be used for prognostic and therapeutic stratification.FundingU.S. National Cancer Institute and National Institute of Health
Abstract 4809: Validation of molecular subtypes of urothelial carcinoma of bladder in multi-institutional and public cohorts
No full textSimulation of uniaxial stress–strain response of 3D-printed polylactic acid by nonlinear finite element analysis
No full text© 2020, The Author(s). Accurate simulation of mechanical properties of 3D-printed objects can provide critical inputs to designers and manufacturers. Polylactic acid, a biodegradable polymer, is particularly important in this regard due to its excellent print quality and a wide range of applications. Herein, an accurate uniaxial stress–strain profile simulation of 3D-printed PLA is reported. Nonlinear Finite Element Analysis (FEA) was used to simulate the uniaxial tensile test and build a material model for the prediction of the stress–strain response. 3D model for this nonlinear FEA study was built in SolidWorks, and several measures were taken to simulate the nonlinear stress–strain response with high accuracy. Von Mises stress, resultant displacement, and strain plots were produced. Comparison with experimental data extracted from the literature was done to validate the FEA model. Fracture behavior was predicted by FEA stress distribution. Deviations between the stress–strain plot obtained by FEA from the experimentally obtained plot were minimal. The entire curve, except the failure zone, could be precisely simulated. Furthermore, the developed von Mises plasticity material model and the boundary conditions also captured the behavior of specimen under uniaxial tension load and the deviation between experimental results was minor. These results suggest that the developed material model could be useful in non-linear FEA studies on 3D printed PLA objects which are expected to withstand tensile stress
Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer
No full textBACKGROUND: TMPRSS2-ERG gene rearrangement, the most common E26 transformation specific (ETS) gene fusion within prostate cancer, is known to contribute to the pathogenesis of this disease and carries diagnostic annotations for prostate cancer patients clinically. The ERG rearrangement status in prostatic adenocarcinoma currently cannot be reliably identified from histologic features on H&E-stained slides alone and hence requires ancillary studies such as immunohistochemistry (IHC), fluorescent in situ hybridization (FISH) or next generation sequencing (NGS) for identification. METHODS: OBJECTIVE: We accordingly sought to develop a deep learning-based algorithm to identify ERG rearrangement status in prostatic adenocarcinoma based on digitized slides of H&E morphology alone. DESIGN: Setting, and Participants: Whole slide images from 392 in-house and TCGA cases were employed and annotated using QuPath. Image patches of 224 × 224 pixel were exported at 10 ×, 20 ×, and 40 × for input into a deep learning model based on MobileNetV2 convolutional neural network architecture pre-trained on ImageNet. A separate model was trained for each magnification. Training and test datasets consisted of 261 cases and 131 cases, respectively. The output of the model included a prediction of ERG-positive (ERG rearranged) or ERG-negative (ERG not rearranged) status for each input patch. Outcome measurements and statistical analysis: Various accuracy measurements including area under the curve (AUC) of the receiver operating characteristic (ROC) curves were used to evaluate the deep learning model. RESULTS AND LIMITATIONS: All models showed similar ROC curves with AUC results ranging between 0.82 and 0.85. The sensitivity and specificity of these models were 75.0% and 83.1% (20 × model), respectively. CONCLUSIONS: A deep learning-based model can successfully predict ERG rearrangement status in the majority of prostatic adenocarcinomas utilizing only H&E-stained digital slides. Such an artificial intelligence-based model can eliminate the need for using extra tumor tissue to perform ancillary studies in order to assess for ERG gene rearrangement in prostatic adenocarcinoma
Urothelial-to-Neural Plasticity Drives Progression to Small Cell Bladder Cancer
No full textWe report a comprehensive molecular analysis of 34 cases of small cell carcinoma (SCC) and 84 cases of conventional urothelial carcinoma (UC), with The Cancer Genome Atlas cohort of 408 conventional UC bladder cancers used as the reference. SCCs showed mutational landscapes characterized by nearly uniform inactivation of TP53 and were dominated by Sanger mutation signature 3 associated with loss of BRCA1/2 function. SCCs were characterized by downregulation of luminal and basal markers and were referred to as double-negative. Transcriptome analyses indicated that SCCs displayed lineage plasticity driven by a urothelial-to-neural phenotypic switch with a dysregulated epithelial-to-mesenchymal transition network. SCCs were depleted of immune cells, and expressed high levels of the immune checkpoint receptor, adenosine receptor A2A (ADORA2A), which is a potent inhibitor of immune infiltration. Our observations have important implications for the prognostication and development of more effective therapies for this lethal bladder cancer variant
Dysregulation of EMT Drives the Progression to Clinically Aggressive Sarcomatoid Bladder Cancer
No full textSummary: Sarcomatoid urothelial bladder cancer (SARC) displays a high propensity for distant metastasis and is associated with short survival. We report a comprehensive genomic analysis of 28 cases of SARC and 84 cases of conventional urothelial carcinoma (UC), with the TCGA cohort of 408 muscle-invasive bladder cancers serving as the reference. SARCs show a distinct mutational landscape, with enrichment of TP53, RB1, and PIK3CA mutations. They are related to the basal molecular subtype of conventional UCs and could be divided into epithelial-basal and more clinically aggressive mesenchymal subsets on the basis of TP63 and its target gene expression levels. Other analyses reveal that SARCs are driven by downregulation of homotypic adherence genes and dysregulation of the EMT network, and nearly half exhibit a heavily infiltrated immune phenotype. Our observations have important implications for prognostication and the development of more effective therapies for this highly lethal variant of bladder cancer. : Guo et al. report that sarcomatoid carcinoma of the bladder evolves by the progression of the basal subtype of conventional urothelial carcinoma with the enrichment of mutagenesis signature 1 and mutations of TP53, RB1, and PIK3CA. It is driven by the dysregulation of the EMT network and shows increased immune infiltrate with overexpression of PD-L1. Keywords: bladder cancer, sarcomatoid carcinoma, urothelial carcinoma, epithelial-mesenchymal transformation, genomic expression, chromatin remodeling, microRNA expression, molecular classification, basal subtype, immune phenotyp
