scholarly journals 126.A repository of ENU mutant mouse lines and their potential for male fertility research

2004 ◽  
Vol 16 (9) ◽  
pp. 126
Author(s):  
C. L. Kennedy ◽  
A. E. O’Connor ◽  
L. G. Sanchez-Partida ◽  
C. C. Goodnow ◽  
D. M. De Kretser ◽  
...  
Keyword(s):  
Male Fertility ◽  
High Performance ◽  
Large Scale ◽  
Mutation Screening ◽  
Point Mutations ◽  
Serum Levels ◽  
Reproductive Technologies ◽  
Specific Gene ◽  
Contraceptive Agents ◽  
Wide Range

One in 25 western men are infertile and the causal factor is frequently unknown, although it is expected that many are genetic in origin. My project aims to identify genes critical to mouse spermatogenesis using ENU mutagenesis. A further aim was to develop a repository of mutant mice and data on their fertility parameters for use by the reproductive biology community. This research will aid the diagnosis and development of specific treatments for human infertility and the development of contraceptive agents. The potent mutagen N-ethyl-N-nitrosourea (ENU) was utilized to generate libraries of C57BL/6 mice with random point mutations throughout their genomes. A 3 generational breeding program produced mice that were homozygous for a number of mutations. I subsequently performed a number of large scale screens on 3rd generation males, identifying lines carrying recessive mutations specifically affecting male fertility. Thus far we have observed a wide range of abnormal testis phenotypes including Sertoli Cell only, hypospermatogenesis, meiosis arrest, abnormal sperm morphology and abnormal hormone levels. From these analyses a repository including all data and tissues collected from 1200 3rd generation male mice from 122 different lines has been developed and will become publicly available. This includes testis and epididymal histology and serum levels of FSH, LH, activin A and inhibin. Further, I have stored gDNA long term and cryopreserved sperm to enable regeneration of lines in the future. In addition, I have developed a high throughput mutation screening protocol for the detection of mutations within genes of interest using denaturing high performance liquid chromatography (DHPLC). Collectively, our repository and gene screening techniques can be used in conjunction with artificial reproductive technologies to generate mouse models reflective of human conditions and altered specific gene function.

scholarly journals Process Design Kit and Design Automation for Flexible Hybrid Electronics

2019 ◽  
Vol 16 (3) ◽  
pp. 117-123
Author(s):  
Tsung-Ching Huang ◽  
Ting Lei ◽  
Leilai Shao ◽  
Sridhar Sivapurapu ◽  
Madhavan Swaminathan ◽  
...  
Keyword(s):  
Process Design ◽  
Design Automation ◽  
High Performance ◽  
Large Scale ◽  
Low Cost ◽  
Thin Film Transistor ◽  
Solution Process ◽  
Oxide Semiconductor ◽  
Wearable Electronics ◽  
Wide Range

Abstract High-performance low-cost flexible hybrid electronics (FHE) are desirable for applications such as internet of things and wearable electronics. Carbon nanotube (CNT) thin-film transistor (TFT) is a promising candidate for high-performance FHE because of its high carrier mobility, superior mechanical flexibility, and material compatibility with low-cost printing and solution processes. Flexible sensors and peripheral CNT-TFT circuits, such as decoders, drivers, and sense amplifiers, can be printed and hybrid-integrated with thinned (<50 μm) silicon chips on soft, thin, and flexible substrates for a wide range of applications, from flexible displays to wearable medical devices. Here, we report (1) a process design kit (PDK) to enable FHE design automation for large-scale FHE circuits and (2) solution process-proven intellectual property blocks for TFT circuits design, including Pseudo-Complementary Metal-Oxide-Semiconductor (Pseudo-CMOS) flexible digital logic and analog amplifiers. The FHE-PDK is fully compatible with popular silicon design tools for design and simulation of hybrid-integrated flexible circuits.

Mutations in the AML1 Gene Define an Unfavorable Subgroup in Acute Myeloid Leukemia with FAB M0.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4340-4340
Author(s):  
Frank Dicker ◽  
Mirjam Klaus ◽  
Torsten Haferlach ◽  
Wolfgang Kern ◽  
Wolfgang Hiddemann ◽  
...  
Keyword(s):  
High Performance ◽  
De Novo ◽  
Mutation Screening ◽  
Point Mutations ◽  
Gene Mutations ◽  
Normal Karyotype ◽  
Runt Domain ◽  
Screening Efficiency ◽  
Genetic Aberration ◽  
Aml1 Gene

Abstract The AML1/RUNX1 gene is the most frequent target for chromosomal translocations in leukemia. Recently point mutations in the AML1 gene have been demonstrated as another mode of genetic aberration. AML1 mutations have been reported in de novo MDS and AML, as well as in therapy related MDS and AML. The AML M0 subtype has been found to be most frequently affected by sporadic AML1 gene mutations. We analysed AML1 gene mutations in a cohort of 49 M0 patients. Mutation screening was performed either with SSCP (n=21) and/or denaturating High Performance Liquid Chromatography (dHPLC) (n=33), 5 cases were analyzed by both methods. SSCP screening of exons 3–5 of the AML1 gene was carried out at the genomic level. These exons cover the socalled Runt domain, which is most frequently mutated. Fragments with aberrant mobility were sequenced. With this method 5 cases were found to be mutated. Subsequently, to improve the screening efficiency an assay using dHPLC was established. Hereby, we screened the cDNA of patient samples for mutations in amino acid codons 1–277 of the AML1b transcript, where the Runt domain is located between codons 49 and 178. All 5 cases detected by SSCP were confirmed by dHPLC. Nine mutations were detected in the cohort of 28 cases (32%) which had not been analyzed by SSCP. In total, 14 of the 49 samples (29%) tested were identified to be mutated, which is a slightly higher frequency than previously reported. In the cohort of 35 AML1 non-mutated cases 20 (57%) had a normal karyotype and 15 (43%) an aberrant karyotypes, whereas only 6 of the 14 AML1 mutated cases (43%) had a normal karyotype (p=0.001). Three of the AML1 mutated cases (21%) also had FLT3 mutations. One had an FLT3-LM, one an FLT3-TKD mutation, and one case both LM and TKD mutations. Clinical follow up data were available for 33 patients (22 AML1 non- mutated, 11 AML1 mutated). The median OS and EFS of the AML1 non-mutated versus the mutated group was 276 days versus 63 days (p = 0.0679) and 276 vs. 63 days (p=0.0630) respectively. Thus the AML1 mutated cases tend to have a worse clinical outcome. When other AML subtypes were screened for AML1 mutations, i.e. M1 (n=26), M2 (n=21) and M4 (n=3), only 1 additional AML1 mutation was detected, confirming the highest prevalence of AML1 mutations in M0. In conclusion, 1) we established a new assay to screen for AML1 mutations. 2) We confirmed the high incidence of AML1 gene mutations in AML M0, both in cases with normal and aberrant karyotype. 3) For the first time we demonstrated that AML1 mutations define an unfavorable subentity in AML M0.

scholarly journals Performance Evaluation of Modularity Based Community Detection Algorithms in Large Scale Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Vinícius da Fonseca Vieira ◽  
Carolina Ribeiro Xavier ◽  
Nelson Francisco Favilla Ebecken ◽  
Alexandre Gonçalves Evsukoff
Keyword(s):  
Spectral Method ◽  
Community Detection ◽  
High Performance ◽  
Large Scale ◽  
Fine Tuning ◽  
Detection Algorithms ◽  
Research Areas ◽  
Structure Detection ◽  
Wide Range ◽  
Large Scale Networks

Community structure detection is one of the major research areas of network science and it is particularly useful for large real networks applications. This work presents a deep study of the most discussed algorithms for community detection based on modularity measure: Newman’s spectral method using a fine-tuning stage and the method of Clauset, Newman, and Moore (CNM) with its variants. The computational complexity of the algorithms is analysed for the development of a high performance code to accelerate the execution of these algorithms without compromising the quality of the results, according to the modularity measure. The implemented code allows the generation of partitions with modularity values consistent with the literature and it overcomes 1 million nodes with Newman’s spectral method. The code was applied to a wide range of real networks and the performances of the algorithms are evaluated.

scholarly journals High-Sensitivity Flexible Pressure Sensor-Based 3D CNTs Sponge for Human–Computer Interaction

Polymers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 3465
Author(s):  
Jianli Cui ◽  
Xueli Nan ◽  
Guirong Shao ◽  
Huixia Sun
Keyword(s):  
Pressure Sensor ◽  
High Performance ◽  
Large Scale ◽  
Low Cost ◽  
Pressure Sensors ◽  
Chemical Vapor ◽  
High Sensitivity ◽  
Wearable Electronics ◽  
Wide Range ◽  
Flexible Pressure Sensors

Researchers are showing an increasing interest in high-performance flexible pressure sensors owing to their potential uses in wearable electronics, bionic skin, and human–machine interactions, etc. However, the vast majority of these flexible pressure sensors require extensive nano-architectural design, which both complicates their manufacturing and is time-consuming. Thus, a low-cost technology which can be applied on a large scale is highly desirable for the manufacture of flexible pressure-sensitive materials that have a high sensitivity over a wide range of pressures. This work is based on the use of a three-dimensional elastic porous carbon nanotubes (CNTs) sponge as the conductive layer to fabricate a novel flexible piezoresistive sensor. The synthesis of a CNTs sponge was achieved by chemical vapor deposition, the basic underlying principle governing the sensing behavior of the CNTs sponge-based pressure sensor and was illustrated by employing in situ scanning electron microscopy. The CNTs sponge-based sensor has a quick response time of ~105 ms, a high sensitivity extending across a broad pressure range (less than 10 kPa for 809 kPa−1) and possesses an outstanding permanence over 4,000 cycles. Furthermore, a 16-pixel wireless sensor system was designed and a series of applications have been demonstrated. Its potential applications in the visualizing pressure distribution and an example of human–machine communication were also demonstrated.

scholarly journals CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

2015 ◽  
Author(s):  
Donovan H Parks ◽  
Michael Imelfort ◽  
Connor T Skennerton ◽  
Philip Hugenholtz ◽  
Gene W Tyson
Keyword(s):  
Large Scale ◽  
Single Cells ◽  
Metagenomic Data ◽  
Marker Genes ◽  
Specific Gene ◽  
Diverse Range ◽  
Automated Method ◽  
A Genome ◽  
Wide Range

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. While this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of ‘marker’ genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate, single cell and metagenome derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination, and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.

scholarly journals Micromechanical Process Integration and Material Optimization for High Performance Silicon-Germanium Bolometers

2012 ◽  
Vol 1437 ◽  
Author(s):  
Gunnar B. Malm ◽  
Mohammadreza Kolahdouz ◽  
Fredrik Forsberg ◽  
Niclas Roxhed ◽  
Frank Niklaus
Keyword(s):  
Integrated Circuits ◽  
Silicon Germanium ◽  
High Performance ◽  
Large Scale ◽  
Process Integration ◽  
Low Frequency ◽  
Single Layer ◽  
Sige Layer ◽  
Frequency Noise ◽  
Wide Range

ABSTRACTSemiconductor-based thermistors are very attractive sensor materials for uncooled thermal infrared (IR) bolometers. Very large scale heterogeneous integration of MEMS is an emerging technology that allows the integration of epitaxially grown, high-performance IR bolometer thermistor materials with pre-processed CMOS-based integrated circuits for the sensor read-out. Thermistor materials based on alternating silicon (Si) and silicon-germanium (SiGe) epitaxial layers have been demonstrated and their performance is continuously increasing. Compared to a single layer of silicon or SiGe, the temperature coefficient of resistance (TCR) can be strongly enhanced to about 3 %/K, by using thin alternating layers. In this paper we report on the optimization of alternating Si/SiGe layers by advanced physically based simulations, including quantum mechanical corrections. Our simulation framework provides reliable predictions for a wide range of SiGe layer compositions, including concentration gradients. Finally, our SiGe thermistor layers have been evaluated in terms of low-frequency noise performance, in order to optimize the bolometer detectivity.

scholarly journals From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

2013 ◽  
Vol 21 (1-2) ◽  
pp. 1-16 ◽  
Author(s):  
Marek Blazewicz ◽  
Ian Hinder ◽  
David M. Koppelman ◽  
Steven R. Brandt ◽  
Milosz Ciznicki ◽  
...  
Keyword(s):  
Code Generation ◽  
High Performance ◽  
Large Scale ◽  
Einstein Equations ◽  
Efficient Manner ◽  
Code Transformations ◽  
Wide Range ◽  
Problem Description ◽  
Physics Model ◽  
High Level

Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, theChemoraframework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretization is based on higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.

Design of wide-band dual–polarized aperture array antennas

2012 ◽  
Vol 4 (3) ◽  
pp. 373-378 ◽  
Author(s):  
Yongwei Zhang ◽  
Anthony K. Brown
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Wide Band ◽  
Array Antennas ◽  
Wide Range ◽  
Square Kilometer Array ◽  
Aperture Array ◽  
Dual Polarized ◽  
Rf Performance ◽  
The Cost

This paper describes the design of high-performance compact aperture array antennas for radio astronomy and other applications. Three recent antenna developments for square kilometer array design study (SKADS) have been investigated and the performances are compared. In addition to the radio frequency (RF) performance, an essential requirement for the square kilometer array application is the cost per square area. Based on initial large–scale finite array studies, prototypes with different geometries have been fabricated and measured. Guidelines are derived for large–scale wide–band dual-polarized array designs in applications where low cross-polarization and a wide range of scan angles are required.

A Distributed Computing Tool for Generating Neural Simulation Databases

2006 ◽  
Vol 18 (12) ◽  
pp. 2923-2927 ◽  
Author(s):  
Robert J. Calin-Jageman ◽  
Paul S. Katz
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Model Neuron ◽  
Scale Model ◽  
Large Set ◽  
Experimental Conditions ◽  
Entry Level ◽  
Neural Simulation ◽  
Wide Range ◽  
Parameter Values

After developing a model neuron or network, it is important to systematically explore its behavior across a wide range of parameter values or experimental conditions, or both. However, compiling a very large set of simulation runs is challenging because it typically requires both access to and expertise with high-performance computing facilities. To lower the barrier for large-scale model analysis, we have developed NeuronPM, a client/server application that creates a “screen-saver” cluster for running simulations in NEURON (Hines & Carnevale, 1997). NeuronPM provides a user-friendly way to use existing computing resources to catalog the performance of a neural simulation across a wide range of parameter values and experimental conditions. The NeuronPM client is a Windows-based screen saver, and the NeuronPM server can be hosted on any Apache/PHP/MySQL server. During idle time, the client retrieves model files and work assignments from the server, invokes NEURON to run the simulation, and returns results to the server. Administrative panels make it simple to upload model files, define the parameters and conditions to vary, and then monitor client status and work progress. NeuronPM is open-source freeware and is available for download at http://neuronpm.homeip.net . It is a useful entry-level tool for systematically analyzing complex neuron and network simulations.

scholarly journals MetaMap: An atlas of metatranscriptomic reads in human disease-related RNA-seq data

2018 ◽  
Author(s):  
LM Simon ◽  
S Karg ◽  
AJ Westermann ◽  
M Engel ◽  
AHA Elbehery ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Human Disease ◽  
High Performance ◽  
Large Scale ◽  
Expression Patterns ◽  
Rna Seq ◽  
Wide Range ◽  
Eukaryotic Gene ◽  
Public Repositories ◽  
Performance Computing

AbstractBackgroundWith the advent of the age of big data in bioinformatics, large volumes of data and high performance computing power enable researchers to perform re-analyses of publicly available datasets at an unprecedented scale. Ever more studies imply the microbiome in both normal human physiology and a wide range of diseases. RNA sequencing technology (RNA-seq) is commonly used to infer global eukaryotic gene expression patterns under defined conditions, including human disease-related contexts, but its generic nature also enables the detection of microbial and viral transcripts.FindingsWe developed a bioinformatic pipeline to screen existing human RNA-seq datasets for the presence of microbial and viral reads by re-inspecting the non-human-mapping read fraction. We validated this approach by recapitulating outcomes from 6 independent controlled infection experiments of cell line models and comparison with an alternative metatranscriptomic mapping strategy. We then applied the pipeline to close to 150 terabytes of publicly available raw RNA-seq data from >17,000 samples from >400 studies relevant to human disease using state-of-the-art high performance computing systems. The resulting data of this large-scale re-analysis are made available in the presented MetaMap resource.ConclusionsOur results demonstrate that common human RNA-seq data, including those archived in public repositories, might contain valuable information to correlate microbial and viral detection patterns with diverse diseases. The presented MetaMap database thus provides a rich resource for hypothesis generation towards the role of the microbiome in human disease.

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