The mRNA expression of SETD2 in human breast cancer: Correlation with clinico-athological parameters

BACKGROUND: SET domain containing protein 2 (SETD2) is a histone methyltransferase that is involved in transcriptional elongation. There is evidence that SETD2 interacts with p53 and selectively regulates its downstream genes. Therefore, it could be implicated in the process of carcinogenesis. Furthermore, this gene is located on the short arm of chromosome 3p and we previously demonstrated that the 3p21.31 region of chromosome 3 was associated with permanent growth arrest of breast cancer cells. This region includes closely related genes namely: MYL3, CCDC12, KIF9, KLHL18 and SETD2. Based on the biological function of these genes, SETD2 is the most likely gene to play a tumour suppressor role and explain our previous findings. Our objective was to determine, using quantitative PCR, whether the mRNA expression levels of SETD2 were consistent with a tumour suppressive function in breast cancer. This is the first study in the literature to examine the direct relationship between SETD2 and breast cancer. METHODS: A total of 153 samples were analysed. The levels of transcription of SETD2 were determined using quantitative PCR and normalized against (CK19). Transcript levels within breast cancer specimens were compared to normal background tissues and analyzed against conventional pathological parameters and clinical outcome over a 10 year follow-up period. RESULTS: The levels of SETD2 mRNA were significantly lower in malignant samples (p = 0.0345) and decreased with increasing tumour stage. SETD2 expression levels were significantly lower in samples from patients who developed metastasis, local recurrence, or died of breast cancer when compared to those who were disease free for > 10 years (p = 0.041). CONCLUSION: This study demonstrates a compelling trend for SETD2 transcription levels to be lower in cancerous tissues and in patients who developed progressive disease. These findings are consistent with a possible tumour suppressor function of this gene in breast cancer

1/10 PROCESS FOR MAKING CHANGES IN WG1 QUALITY

Version: 2.

Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning

Cardiovascular disease accounts for 1 in every 4 deaths in United States. Accurate estimation of structural and functional cardiac parameters is crucial for both diagnosis and disease management. In this work, we develop an ensemble learning framework for more accurate and robust left ventricle (LV) quantification. The framework combines two 1st-level modules: direct estimation module and a segmentation module. The direct estimation module utilizes Convolutional Neural Network (CNN) to achieve end-to-end quantification. The CNN is trained by taking 2D cardiac images as input and cardiac parameters as output. The segmentation module utilizes a U-Net architecture for obtaining pixel-wise prediction of the epicardium and endocardium of LV from the background. The binary U-Net output is then analyzed by a separate CNN for estimating the cardiac parameters. We then employ linear regression between the 1st-level predictor and ground truth to learn a 2nd-level predictor that ensembles the results from 1st-level modules for the final estimation. Preliminary results by testing the proposed framework on the LVQuan18 dataset show superior performance of the ensemble learning model over the two base modules.Comment: Jiasha Liu, Xiang Li and Hui Ren contribute equally to this wor

Graphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/122409/1/sim6926_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/122409/2/sim6926.pd

Dimensional reduction in numerical relativity: Modified Cartoon formalism and regularization

We present in detail the Einstein equations in the Baumgarte-Shapiro-Shibata-Nakamura formulation for the case of $D$ dimensional spacetimes with $SO(D-d)$ isometry based on a method originally introduced in Ref.1. Regularized expressions are given for a numerical implementation of this method on a vertex centered grid including the origin of the quasi-radial coordinate that covers the extra dimensions with rotational symmetry. Axisymmetry, corresponding to the value $d=D-2$, represents a special case with fewer constraints on the vanishing of tensor components and is conveniently implemented in a variation of the general method. The robustness of the scheme is demonstrated for the case of a black-hole head-on collision in $D=7$ spacetime dimensions with $SO(4)$ symmetry.U.S. is supported by the H2020 ERC Consolidator Grant “Matter and strong-field gravity: New frontiers in Einstein’s theory” grant agreement No. MaGRaTh–646597, the H2020-MSCA-RISE-2015 Grant No. StronGrHEP-690904, the STFC Consolidator Grant No. ST/L000636/1, the SDSC Comet and TACC Stampede clusters through NSF-XSEDE Award Nos. PHY-090003, the Cambridge High Performance Computing Service Supercomputer Darwin using Strategic Research Infrastructure Funding from the HEFCE and the STFC, and DiRAC’s Cosmos Shared Memory system through BIS Grant No. ST/J005673/1 and STFC Grant Nos. ST/H008586/1, ST/K00333X/1. P.F. and S.T. are supported by the H2020 ERC Starting Grant “New frontiers in numerical general relativity” grant agreement No. NewNGR- 639022. P.F. is also supported by a Royal Society University Research Fellowship. W.G.C. and M.K. are supported by STFC studentships.This is the final version of the article. It first appeared from the World Scientific Publishing Company via http://dx.doi.org/10.1142/S021827181641013

Nitrate removal using Purolite A520E ion exchange resin: batch and fixed-bed column adsorption modelling

© 2014, Islamic Azad University (IAU). Removing excessive nitrate from water is essential because it causes eutrophication which in turn has a harmful effect on aquatic life, resulting in a reduction in biodiversity and posing a danger to people’s health when the water is used for drinking. In this study, nitrate removal from aqueous solutions was studied using an ion exchange resin (Purolite A520E) in batch and fixed-bed column experiments. Batch adsorption kinetics was very well described by pseudo-first-order, pseudo-second-order and homogeneous surface diffusion models for resin doses 1.5 and 3.0 g/L at a nitrate concentration 20 mg N/L. Column kinetic data satisfactorily fitted to the empirical Thomas model and a numerical model based on advection–dispersion equation for filtration velocities 2.5 and 5.0 m/h at a column height of 12 cm and inlet concentration 20 mg N/L. The experimental and Thomas model predicted breakthrough adsorption capacity ranges for the two filtration rates were 12.0–13.5 and 8.2–9.7 mg N/g, respectively, whereas the maximum adsorption capacity determined using Langmuir adsorption isotherm model in the batch study was 32.2 mg N/g

Mathematical modelling of nitrate removal from water using a submerged membrane adsorption hybrid system with four adsorbents

© 2018 by the authors. Excessive concentrations of nitrate in ground water are known to cause human health hazards. A submerged membrane adsorption hybrid system that includes a microfilter membrane and four different adsorbents (Dowex 21K XLT ion exchange resin (Dowex), Fe-coated Dowex, amine-grafted (AG) corn cob and AG coconut copra) operated at four different fluxes was used to continuously remove nitrate. The experimental data obtained in this study was simulated mathematically with a homogeneous surface diffusion model that incorporated membrane packing density and membrane correlation coefficient, and applied the concept of continuous flow stirred tank reactor. The model fit with experimental data was good. The surface diffusion coefficient was constant for all adsorbents and for all fluxes. The mass transfer coefficient increased with flux for all adsorbents and generally increased with the adsorption capacity of the adsorbents