Ising-Based Consensus Clustering on Specialized Hardware

Cost reduction and availability of specialized hardware for image processing have made it reasonable to purchase a stand-alone interactive work station for computer aided analysis of micrographs. Some features of such a system are: 1) Ease of selection of points of interest on the micrograph. A cursor can be quickly positioned and coordinates entered with a switch. 2) The image can be nondestructively zoomed to a higher magnification for closer examination and roaming (panning) can be done around the picture. 3) Contrast and brightness of the picture can be varied over a very large range by changing the display look-up tables. 4) Marking items of interest can be done by drawing circles, vectors or alphanumerics on an additional memory plane so that the picture data remains intact. 5) Color pictures can easily be produced. Since the human eye can detect many more colors than gray levels, often a color encoded micrograph reveals many features not readily apparent with a black and white display. Colors can be used to construct contour maps of objects of interest. 6) Publication quality prints can easily be produced by taking pictures with a standard camera of the T.V. monitor screen.

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Consensus Clustering Using Weighted Association

10.21528/cbic2011-001 ◽

2016 ◽

Author(s):

Aparajita Nanda ◽

Arun K. Pujari

Keyword(s):

Consensus Clustering

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DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

Cancer Control ◽

10.1177/1073274820988519 ◽

2021 ◽

Vol 28 ◽

pp. 107327482098851

Author(s):

Zeng-Hong Wu ◽

Yun Tang ◽

Yan Zhou

Keyword(s):

Breast Cancer ◽

Dna Methylation ◽

Molecular Subtypes ◽

Methylation Status ◽

The Cancer Genome Atlas ◽

Training Dataset ◽

Consensus Clustering ◽

Breast Cancer Patients ◽

Cancer Subtypes ◽

Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

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Adaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software

ACM Transactions on Mathematical Software ◽

10.1145/3441850 ◽

2021 ◽

Vol 47 (2) ◽

pp. 1-28

Author(s):

Goran Flegar ◽

Hartwig Anzt ◽

Terry Cojean ◽

Enrique S. Quintana-Ortí

Keyword(s):

Linear Algebra ◽

Graphics Processing Units ◽

High Performance ◽

Numerical Algorithms ◽

Mixed Precision ◽

Before And After ◽

Memory Accesses ◽

Specialized Hardware ◽

The Individual ◽

Graphics Processing

The use of mixed precision in numerical algorithms is a promising strategy for accelerating scientific applications. In particular, the adoption of specialized hardware and data formats for low-precision arithmetic in high-end GPUs (graphics processing units) has motivated numerous efforts aiming at carefully reducing the working precision in order to speed up the computations. For algorithms whose performance is bound by the memory bandwidth, the idea of compressing its data before (and after) memory accesses has received considerable attention. One idea is to store an approximate operator–like a preconditioner–in lower than working precision hopefully without impacting the algorithm output. We realize the first high-performance implementation of an adaptive precision block-Jacobi preconditioner which selects the precision format used to store the preconditioner data on-the-fly, taking into account the numerical properties of the individual preconditioner blocks. We implement the adaptive block-Jacobi preconditioner as production-ready functionality in the Ginkgo linear algebra library, considering not only the precision formats that are part of the IEEE standard, but also customized formats which optimize the length of the exponent and significand to the characteristics of the preconditioner blocks. Experiments run on a state-of-the-art GPU accelerator show that our implementation offers attractive runtime savings.

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FSMP-06. IN VIVO MONITORING OF LDHA EXPRESSION IN GLIOBLASTOMA USING QUANTITATIVE EXCHANGED-LABEL TURNOVER 1H MRS TECHNIQUE

Neuro-Oncology Advances ◽

10.1093/noajnl/vdab024.070 ◽

2020 ◽

Vol 3 (Supplement_1) ◽

pp. i17-i17

Author(s):

Puneet Bagga ◽

Laurie Rich ◽

Mohammad Haris ◽

Neil Wilson ◽

Mitch Schnall ◽

...

Keyword(s):

Magnetic Resonance ◽

Lactate Production ◽

Deuterium Labeling ◽

1H Mrs ◽

In Vivo Monitoring ◽

Lactate Turnover ◽

Crucial Information ◽

Specialized Hardware

Abstract Most cancers, including glioblastomas (GBMs), rely extensively on glycolysis to support growth, proliferation, and survival. A hallmark of this elevated glycolysis is overexpression of Lactate dehydrogenase-A (LDHA) protein leading to increased uptake of glucose and overproduction of lactate. Various clinical trials using LDHA as a target for diagnosis and treatment have yielded encouraging results. However, in vivo monitoring of LDHA expression has been challenging due to either requirement of administration of radioactive substrates or specialized hardware. In this presentation, we will demonstrate a new method-quantitative exchanged-label turnover MRS (QELT, or simply qMRS)-that increases the sensitivity of magnetic resonance-based metabolic mapping without the requirement for specialized hardware. qMRS relies on the administration of deuterated (2H-labeled) substrates to track the production of downstream metabolites. Since 2H is invisible on 1H MRS, replacement of 1H with 2H due to metabolic turnover leads to an overall reduction in 1H MRS signal for the corresponding metabolites. We applied our qMRS technique to monitor the rate of lactate production in a preclinical GBM model. Infusion of [6,6’-2H2]glucose led to downstream deuterium labeling of lactate, thereby resulting in a reduction in the 1.33 ppm lactate-CH3 peak on 1H MRS over time. The subtraction of post-administration 1H MR spectra from the pre-infusion spectra aided in the determination of the kinetics of the lactate turnover. We believe that the detection and quantification of lactate production kinetics may provide crucial information regarding tumor LDHA expression non-invasively in GBMs without requiring biopsies. Hence, qMRS is expected to open up new opportunities to probe LDHA expression differences in a variety of gliomas, including GBMs and astrocytomas. This method takes advantage of the universal availability and ease of implementation of 1H MRS on all clinical and preclinical magnetic resonance scanners.

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N6-Methyladenosine RNA modification in cerebrospinal fluid as a novel potential diagnostic biomarker for progressive multiple sclerosis

Journal of Translational Medicine ◽

10.1186/s12967-021-02981-5 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Fei Ye ◽

Tianzhu Wang ◽

Xiaoxin Wu ◽

Jie Liang ◽

Jiaoxing Li ◽

...

Keyword(s):

Gene Expression ◽

Multiple Sclerosis ◽

Clustering Analysis ◽

Roc Curves ◽

Progressive Multiple Sclerosis ◽

Rna Modification ◽

Diagnostic Model ◽

Consensus Clustering ◽

Rna Methylation ◽

M6a Rna Methylation

Abstract Background Progressive multiple sclerosis (PMS) is an uncommon and severe subtype of MS that worsens gradually and leads to irreversible disabilities in young adults. Currently, there are no applicable or reliable biomarkers to distinguish PMS from relapsing–remitting multiple sclerosis (RRMS). Previous studies have demonstrated that dysfunction of N6-methyladenosine (m6A) RNA modification is relevant to many neurological disorders. Thus, the aim of this study was to explore the diagnostic biomarkers for PMS based on m6A regulatory genes in the cerebrospinal fluid (CSF). Methods Gene expression matrices were downloaded from the ArrayExpress database. Then, we identified differentially expressed m6A regulatory genes between MS and non-MS patients. MS clusters were identified by consensus clustering analysis. Next, we analyzed the correlation between clusters and clinical characteristics. The random forest (RF) algorithm was applied to select key m6A-related genes. The support vector machine (SVM) was then used to construct a diagnostic gene signature. Receiver operating characteristic (ROC) curves were plotted to evaluate the accuracy of the diagnostic model. In addition, CSF samples from MS and non-MS patients were collected and used for external validation, as evaluated by an m6A RNA Methylation Quantification Kit and by real-time quantitative polymerase chain reaction. Results The 13 central m6A RNA methylation regulators were all upregulated in MS patients when compared with non-MS patients. Consensus clustering analysis identified two clusters, both of which were significantly associated with MS subtypes. Next, we divided 61 MS patients into a training set (n = 41) and a test set (n = 20). The RF algorithm identified eight feature genes, and the SVM method was successfully applied to construct a diagnostic model. ROC curves revealed good performance. Finally, the analysis of 11 CSF samples demonstrated that RRMS samples exhibited significantly higher levels of m6A RNA methylation and higher gene expression levels of m6A-related genes than PMS samples. Conclusions The dynamic modification of m6A RNA methylation is involved in the progression of MS and could potentially represent a novel CSF biomarker for diagnosing MS and distinguishing PMS from RRMS in the early stages of the disease.

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Efficiently Solving Partial Differential Equations in a Partially Reconfigurable Specialized Hardware

IEEE Transactions on Computers ◽

10.1109/tc.2021.3060700 ◽

2021 ◽

Vol 70 (4) ◽

pp. 524-538

Author(s):

Bahar Asgari ◽

Ramyad Hadidi ◽

Tushar Krishna ◽

Hyesoon Kim ◽

Sudhakar Yalamanchili

Keyword(s):

Partial Differential Equations ◽

Differential Equations ◽

Partial Differential ◽

Specialized Hardware

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Visceral pressure stimulator for exploring hollow organ pain: a pilot study

BioMedical Engineering OnLine ◽

10.1186/s12938-021-00870-y ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Michael DeLong ◽

Mauricio Gil-Silva ◽

Veronica Minsu Hong ◽

Olivia Babyok ◽

Benedict J. Kolber

Keyword(s):

Visceral Pain ◽

Bladder Pressure ◽

Abdominal Muscles ◽

Analog To Digital ◽

In Vivo Experiments ◽

Digital Pressure ◽

Hollow Organ ◽

Specialized Hardware ◽

And Control

Abstract Background The regulation and control of pressure stimuli is useful for many studies of pain and nociception especially those in the visceral pain field. In many in vivo experiments, distinct air and liquid stimuli at varying pressures are delivered to hollow organs such as the bladder, vagina, and colon. These stimuli are coupled with behavioral, molecular, or physiological read-outs of the response to the stimulus. Care must be taken to deliver precise timed stimuli during experimentation. For example, stimuli signals can be used online to precisely time-lock the stimulus with a physiological output. Such precision requires the development of specialized hardware to control the stimulus (e.g., air) while providing a precise read-out of pressure and stimulus signal markers. Methods In this study, we designed a timed pressure regulator [termed visceral pressure stimulator (VPS)] to control air flow, measure pressure (in mmHg), and send stimuli markers to online software. The device was built using a simple circuit and primarily off-the-shelf parts. A separate custom inline analog-to-digital pressure converter was used to validate the real pressure output of the VPS. Results Using commercial physiological software (Spike2, CED), we were able to measure mouse bladder pressure continuously during delivery of unique air stimulus trials in a mouse while simultaneously recording an electromyogram (EMG) of the overlying abdominal muscles. Conclusions This device will be useful for those who need to (1) deliver distinct pressure stimuli while (2) measuring the pressure in real-time and (3) monitoring stimulus on–off using physiological software.

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