Literature Survey on the Dynamics of Plate and Shell Structures

The aim of this report is to outline and summarize the study that has been done in the area of vibration of plate and shell structures. A brief description of vibration of grids is also made. The Rayleigh-Ritz method appears to be the most useful method for finding a reasonable approximate solution for natural frequencies of vibration of thin elastic plates and shells. This literature survey will serve the first step towardthe complete comprehension of the vibration problems in plate and shell structures; it will be very beneficial in future investigations of this problem.Civil Engineerin

Correlation of BACH1 and hemoglobin E/Beta-thalassemia globin expression

Objective: The diverse clinical phenotype of hemoglobin E (HbE)/β-thalassemia has not only confounded clinicians in matters of patient management but has also led scientists to investigate the complex mechanisms involved in maintaining the delicate red cell environment where, even with apparent similarities of α- and β-globin genotypes, the phenotype tells a different story. The BTB and CNC homology 1 (BACH1) protein is known to regulate α- and β-globin gene transcriptions during the terminal differentiation of erythroid cells. With the mutations involved in HbE/β-thalassemia disorder, we studied the role of BACH1 in compensating for the globin chain imbalance, albeit for fine-tuning purposes. Materials and Methods: A total of 47 HbE/β-thalassemia samples were analyzed using real-time quantitative polymerase chain reaction and correlated with age, sex, red blood cell parameters, globin gene expressions, and some clinical data. Results: The BACH1 expression among the β-thalassemia intermedia patients varied by up to 2-log differences and was positively correlated to age; α-, β-, and γ-globin gene expression level; and heme oxygenase 1 protein. BACH1 was also negatively correlated to reticulocyte level and had a significant correlation with splenectomy. Conclusion: This study indicates that the expression of BACH1 could be elevated as a compensatory mechanism to decrease the globin chain imbalance as well as to reduce the oxidative stress found in HbE/β-thalassemia

Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns

In financial markets, appearances of chart patterns in time series are commonly considered as potential signals for imminent change in the direction of price movement. To identify chart patterns, time series data is usually segmented before it can be processed by different classification methods. However, existing segmentation methods are less effective in classifying 16 curve-shaped chart patterns from financial time series. In this paper, we propose three novel segmentation methods for classification of curveshaped chart patterns based on direct least squares fitting of ellipses. These methods are implemented based on the principles of sliding windows, turning points, and bottom-up piece wise linear approximation. To further enhance the efficiency of classifying chart patterns from real-time streaming data, we propose a novel algorithm called Accelerating Classification with Prioritized Rules (ACPR). Experiments based on real datasets from financial markets reveal that the proposed approaches are effective in classifying curveshaped patterns from time series. Experiment results reveal that the proposed segmentation methods with ACPR can significantly reduce the total execution time

Evaluation of noise removal algorithms for imaging and reconstruction of vascular networks using micro-CT

Micro-computed tomography systems are widely used for high-resolution, non-destructive analysis of internal microvascular networks. When the scale of the targeted vessel approaches the imaging resolution limit, the level of noise becomes a limiting factor for accurate reconstruction. Denoising algorithms provided by vendors are often suboptimal for enhancing SNR of fine (vessel) features. Furthermore, the performance of existing methods has not been systematically analyzed in the context of final network reconstruction and graph model extraction. This work evaluates several standard and state-of-the-art noise reduction techniques using both in silico and physical phantoms, and ex vivo rat coronary data for their ability to improve vascular network analysis. We compared five noise reduction approaches, including vendor-supplied (Gaussian smoothing), conventional (median filter) and advanced (i.e. wavelet filter with soft thresholding, block-matching collaborative filtering (BM3D), and isotropic and anisotropic total variation denoising) techniques. The latter two methods were chosen for their reported ability to preserve fine details, a prerequisite for a successful microvascular extraction. The full evaluation pipeline included the reconstruction from projection images, denoising, vascular segmentation and graph model extraction to be performed on all simulated and real image data sets. SNR, CNR and 3D NPS were quantified from denoised images, and where the ground truth was known, Sørensen–Dice coefficients, Jaccard index metrics were calculated as measures of segmentation error. The performance of the image denoising algorithms where the ground-truth was available has been assessed by computing the correlation coefficients between the residual images (obtained between the noise-free data and the denoised data) and the first derivative of the noise-free data were computed. Overall, simpler denoising techniques including the median and wavelet filters and the vendor-supplied implementations have been found to perform inadequately for segmentation of fine vessel features, particularly on real images. BM3D technique performed well in most of our tests, however isotropic total variation (ITV) was the optimal choice for noise reduction and feature preservation in real data as shown by the extracted network models. Globally, ITV increased the SNR from 10.2 to 31.7 dB in a Shepp Logan phantom, doubled SNR and CNR values in a scanned physical phantom compared with BM3D, enabled the smallest vessels to be fully recovered in an in silicon phantom and achieved a near-ideal outcome in the rat coronary data

Analysis of a1 and a2 globin genes among patients with hemoglobin Adana in Malaysia

Hemoglobin (Hb) Adana [HBA2: c179G>A (or HBA1); p.Gly60Asp] is a non-deletional α-thalassemia variant found in Malaysia. An improvement in the molecular techniques in recent years has made identification of Hb Adana much easier. For this study, a total of 26 Hb Adana α-thalassemia intermedia and 10 Hb Adana trait blood samples were collected from patients. Common deletional and non-deletional α-thalassemia genotypes were determined using multiplex gap polymerase chain reaction (PCR) and multiplex ARMS PCR techniques. Identification of the Hb Adana location on the α-globin gene was carried out using genomic sequencing and the location of the mutation was confirmed via restriction fragment length polymorphism-PCR. Among the 36 samples, 24 (66.7%) had the -α3.7/αCd59α mutation, while the -α3.7/αCd59α mutation accounted for 2 samples (5.6%) and the remaining 10 (27.8%) samples were α/αCd59α. All 36 samples were found to have the Hb Adana mutation on the a2-globin gene. The position of the α-globin gene mutation found in our cases was similar to that reported in Indonesia (16%) but not to that in Turkey (0.6%). Our results showed that the Hb Adana mutation was preferentially present in the a2-globin genes in Malays compared to the other ethnicities in Malaysia. Thus, the Malays might have similar ancestry based on the similarities in the Hb Adana position

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation

Sox2, a stemness gene, regulates tumor-initiating and drug-resistant properties in CD133-positive glioblastoma stem cells

AbstractBackgroundGlioblastoma multiforme (GBM) is the most lethal type of adult brain cancer and performs outrageous growth and resistance regardless of adjuvant chemotherapies, eventually contributing to tumor recurrence and poor outcomes. Considering the common heterogeneity of cancer cells, the imbalanced regulatory mechanism could be switched on/off and contribute to drug resistance. Moreover, the subpopulation of GBM cells was recently discovered to share similar phenotypes with neural stem cells. These cancer stem cells (CSCs) promote the potency of tumor initiation. As a result, targeting of glioma stem cells has become the dominant way of improving the therapeutic outcome against GBM and extending the life span of patients. Among the biomarkers of CSCs, CD-133 (prominin-1) has been known to effectively isolate CSCs from cancer population, including GBM; however, the underlying mechanism of how stemness genes manipulate CSC-associated phenotypes, such as tumor initiation and relapse, is still unclear.MethodsTumorigenicity, drug resistance and embryonic stem cell markers were examined in primary CD133-positive (CD133+) GBM cells and CD133+ subpopulation. Stemness signature of CD133+ GBM cells was identified using microarray analysis. Stem cell potency, tumorigenicity and drug resistance were also tested in differential expression of SOX2 in GBM cells.ResultsIn this study, high tumorigenic and drug resistance was noticed in primary CD-133+ GBM cells; meanwhile, plenty of embryonic stem cell markers were also elevated in the CD-133+ subpopulation. Using microarray analysis, we identified SOX2 as the most enriched gene among the stemness signature in CD133+ GBM cells. Overexpression of SOX2 consistently enhanced the stem cell potency in the GBM cell lines, whereas knockdown of SOX2 dramatically withdrew CD133 expression in CD133+ GBM cells. Additionally, we silenced SOX2 expression using RNAi system, which abrogated the ability of tumor initiation as well as drug resistance of CD133+ GBM cells, suggesting that SOX2 plays a crucial role in regulating tumorigenicity in CD133+ GBM cells.ConclusionSOX2 plays a crucial role in regulating tumorigenicity in CD133+ GBM cells. Our results not only revealed the genetic plasticity contributing to drug resistance and stemness but also demonstrated the dominant role of SOX2 in maintenance of GBM CSCs, which may provide a novel therapeutic target to overcome the conundrum of poor survival of brain cancers

The use of Taqman genotyping assays for rapid confirmation of B-thalassaemia mutations in the Malays: accurate diagnosis with low DNA concentrations

Introduction: In Malaysia, β-thalassaemia is a common inherited blood disorder in haemoglobin synthesis with a carrier rate of 4.5%. Currently, PCR-incorporating techniques such as amplification refractory mutation system (ARMS) or reverse dot blot hybridization (RDBH) are used in β-thalassaemia mutation detection. ARMS allows single-mutation identification using two reactions, one for wild type and another for mutant alleles. RDBH requires probe immobilization and optimization of hybridization and washing temperatures which is time consuming. The aim of our study was to investigate whether β-thalassaemia mutations can be identified in samples with low DNA concentrations. Methods: Genotype identification of common β-thalassaemia mutations in Malays was carried out using Taqman genotyping assays. Results: Results show that the Taqman assays allow mutation detection with DNA template concentrations as low as 2-100 ng. In addition, consistent reproducibility was observed in the Taqman assays when repeated eight times and at different time intervals. Conclusion: The developed sensitive Taqman assays allow molecular characterization of β-thalassaemia mutations in samples with low DNA concentrations. The Taqman genotyping assays have potential as a diagnostic tool for foetal blood, chorionic villi or pre-implantation genetic diagnosis where DNA is limited and precious

Enhancement of radiosensitivity in human glioblastoma cells by the DNA N-mustard alkylating agent BO-1051 through augmented and sustained DNA damage response

<p>Abstract</p> <p>Background</p> <p>1-{4-[Bis(2-chloroethyl)amino]phenyl}-3-[2-methyl-5-(4-methylacridin-9-ylamino)phenyl]urea (BO-1051) is an N-mustard DNA alkylating agent reported to exhibit antitumor activity. Here we further investigate the effects of this compound on radiation responses of human gliomas, which are notorious for the high resistance to radiotherapy.</p> <p>Methods</p> <p>The clonogenic assay was used to determine the IC₅₀and radiosensitivity of human glioma cell lines (U87MG, U251MG and GBM-3) following BO-1051. DNA histogram and propidium iodide-Annexin V staining were used to determine the cell cycle distribution and the apoptosis, respectively. DNA damage and repair state were determined by γ-H2AX foci, and mitotic catastrophe was measure using nuclear fragmentation. Xenograft tumors were measured with a caliper, and the survival rate was determined using Kaplan-Meier method.</p> <p>Results</p> <p>BO-1051 inhibited growth of human gliomas in a dose- and time-dependent manner. Using the dosage at IC₅₀, BO-1051 significantly enhanced radiosensitivity to different extents [The sensitizer enhancement ratio was between 1.24 and 1.50 at 10% of survival fraction]. The radiosensitive G₂/M population was raised by BO-1051, whereas apoptosis and mitotic catastrophe were not affected. γ-H2AX foci was greatly increased and sustained by combined BO-1051 and γ-rays, suggested that DNA damage or repair capacity was impaired during treatment. <it>In vivo </it>studies further demonstrated that BO-1051 enhanced the radiotherapeutic effects on GBM-3-beared xenograft tumors, by which the sensitizer enhancement ratio was 1.97. The survival rate of treated mice was also increased accordingly.</p> <p>Conclusions</p> <p>These results indicate that BO-1051 can effectively enhance glioma cell radiosensitivity <it>in vitro </it>and <it>in vivo</it>. It suggests that BO-1051 is a potent radiosensitizer for treating human glioma cells.</p

Comparison of Artificial Neural Network and Logistic Regression Models for Predicting In-Hospital Mortality after Primary Liver Cancer Surgery

BACKGROUND: Since most published articles comparing the performance of artificial neural network (ANN) models and logistic regression (LR) models for predicting hepatocellular carcinoma (HCC) outcomes used only a single dataset, the essential issue of internal validity (reproducibility) of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model. METHODOLOGY/PRINCIPAL FINDINGS: Patients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC) curves, Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive) parameter affecting in-hospital mortality followed by age and lengths of stay. CONCLUSIONS/SIGNIFICANCE: In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data