46 research outputs found
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A precise determination of the void percolation threshold for two distributions of overlapping spheres
The void percolation threshold is calculated for a distribution of overlapping spheres with equal radii, and for a binary sized distribution of overlapping spheres, where half of the spheres have radii twice as large as the other half. Using systems much larger than previous work, the authors determine a much more precise value for the percolation thresholds and correlation length exponent. The values for the percolation thresholds are shown to be significantly different, in contrast with previous, less precise works that speculated that the threshold might be universal with respect to sphere size distribution
Evaluating parallel relational databases for medical data analysis.
Hospitals have always generated and consumed large amounts of data concerning patients, treatment and outcomes. As computers and networks have permeated the hospital environment it has become feasible to collect and organize all of this data. This raises naturally the question of how to deal with the resulting mountain of information. In this report we detail a proof-of-concept test using two commercially available parallel database systems to analyze a set of real, de-identified medical records. We examine database scalability as data sizes increase as well as responsiveness under load from multiple users
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Parallel tempering Monte Carlo in LAMMPS.
We present here the details of the implementation of the parallel tempering Monte Carlo technique into a LAMMPS, a heavily used massively parallel molecular dynamics code at Sandia. This technique allows for many replicas of a system to be run at different simulation temperatures. At various points in the simulation, configurations can be swapped between different temperature environments and then continued. This allows for large regions of energy space to be sampled very quickly, and allows for minimum energy configurations to emerge in very complex systems, such as large biomolecular systems. By including this algorithm into an existing code, we immediately gain all of the previous work that had been put into LAMMPS, and allow this technique to quickly be available to the entire Sandia and international LAMMPS community. Finally, we present an example of this code applied to folding a small protein
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Applications of Transport/Reaction Codes to Problems in Cell Modeling
We demonstrate two specific examples that show how our exiting capabilities in solving large systems of partial differential equations associated with transport/reaction systems can be easily applied to outstanding problems in computational biology. First, we examine a three-dimensional model for calcium wave propagation in a Xenopus Laevis frog egg and verify that a proposed model for the distribution of calcium release sites agrees with experimental results as a function of both space and time. Next, we create a model of the neuron's terminus based on experimental observations and show that the sodium-calcium exchanger is not the route of sodium's modulation of neurotransmitter release. These state-of-the-art simulations were performed on massively parallel platforms and required almost no modification of existing Sandia codes
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Deciphering the genetic regulatory code using an inverse error control coding framework.
We have found that developing a computational framework for reconstructing error control codes for engineered data and ultimately for deciphering genetic regulatory coding sequences is a challenging and uncharted area that will require advances in computational technology for exact solutions. Although exact solutions are desired, computational approaches that yield plausible solutions would be considered sufficient as a proof of concept to the feasibility of reverse engineering error control codes and the possibility of developing a quantitative model for understanding and engineering genetic regulation. Such evidence would help move the idea of reconstructing error control codes for engineered and biological systems from the high risk high payoff realm into the highly probable high payoff domain. Additionally this work will impact biological sensor development and the ability to model and ultimately develop defense mechanisms against bioagents that can be engineered to cause catastrophic damage. Understanding how biological organisms are able to communicate their genetic message efficiently in the presence of noise can improve our current communication protocols, a continuing research interest. Towards this end, project goals include: (1) Develop parameter estimation methods for n for block codes and for n, k, and m for convolutional codes. Use methods to determine error control (EC) code parameters for gene regulatory sequence. (2) Develop an evolutionary computing computational framework for near-optimal solutions to the algebraic code reconstruction problem. Method will be tested on engineered and biological sequences
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Detection and reconstruction of error control codes for engineered and biological regulatory systems.
A fundamental challenge for all communication systems, engineered or living, is the problem of achieving efficient, secure, and error-free communication over noisy channels. Information theoretic principals have been used to develop effective coding theory algorithms to successfully transmit information in engineering systems. Living systems also successfully transmit biological information through genetic processes such as replication, transcription, and translation, where the genome of an organism is the contents of the transmission. Decoding of received bit streams is fairly straightforward when the channel encoding algorithms are efficient and known. If the encoding scheme is unknown or part of the data is missing or intercepted, how would one design a viable decoder for the received transmission? For such systems blind reconstruction of the encoding/decoding system would be a vital step in recovering the original message. Communication engineers may not frequently encounter this situation, but for computational biologists and biotechnologist this is an immediate challenge. The goal of this work is to develop methods for detecting and reconstructing the encoder/decoder system for engineered and biological data. Building on Sandia's strengths in discrete mathematics, algorithms, and communication theory, we use linear programming and will use evolutionary computing techniques to construct efficient algorithms for modeling the coding system for minimally errored engineered data stream and genomic regulatory DNA and RNA sequences. The objective for the initial phase of this project is to construct solid parallels between biological literature and fundamental elements of communication theory. In this light, the milestones for FY2003 were focused on defining genetic channel characteristics and providing an initial approximation for key parameters, including coding rate, memory length, and minimum distance values. A secondary objective addressed the question of determining similar parameters for a received, noisy, error-control encoded data set. In addition to these goals, we initiated exploration of algorithmic approaches to determine if a data set could be approximated with an error-control code and performed initial investigations into optimization based methodologies for extracting the encoding algorithm given the coding rate of an encoded noise-free and noisy data stream
Lesson of the month: novel method to quantify neutrophil uptake in early lung cancer using SPECT-CT
Neutrophils play an important role in the lung tumour microenvironment. We hypothesised that radiolabelled neutrophils coupled to single-photon emission CT (SPECT) may non-invasively quantify neutrophil uptake in tumours from patients with non-small cell lung cancer. We demonstrated increased uptake of radiolabelled neutrophils from the blood into tumours compared with non-specific uptake using radiolabelled transferrin. Moreover, indium-111-neutrophil activity in the tumour biopsies also correlated with myeloperoxidase (MPO)-positive neutrophils. Our data support the utility of imaging with In-111-labelled neutrophils and SPECT-CT to quantify neutrophil uptake in lung cancer
Ventilation Strategies During Extracorporeal Membrane Oxygenation for Neonatal Respiratory Failure: Current Approaches Among Level IV Neonatal ICUs
To describe ventilation strategies used during extracorporeal membrane oxygenation (ECMO) for neonatal respiratory failure among level IV neonatal ICUs (NICUs).
Design: Cross-sectional electronic survey.
Setting: Email-based Research Electronic Data Capture survey.
Patients: Neonates undergoing ECMO for respiratory failure at level IV NICUs.
Interventions: A 40-question survey was sent to site sponsors of regional referral neonatal ECMO centers participating in the Children\u27s Hospitals Neonatal Consortium. Reminder emails were sent at 2- and 4-week intervals.
Measurements and main results: Twenty ECMO centers responded to the survey. Most primarily use venoarterial ECMO (65%); this percentage is higher (90%) for congenital diaphragmatic hernia. Sixty-five percent reported following protocol-based guidelines, with neonatologists primarily responsible for ventilator management (80%). The primary mode of ventilation was pressure control (90%), with synchronized intermittent mechanical ventilation (SIMV) comprising 80%. Common settings included peak inspiratory pressure (PIP) of 16-20 cm H2O (55%), positive end-expiratory pressure (PEEP) of 9-10 cm H2O (40%), I-time 0.5 seconds (55%), rate of 10-15 (60%), and Fio2 22-30% (65%). A minority of sites use high-frequency ventilation (HFV) as the primary mode (5%). During ECMO, 55% of sites target some degree of lung aeration to avoid complete atelectasis. Fifty-five percent discontinue inhaled nitric oxide (iNO) during ECMO, while 60% use iNO when trialing off ECMO. Nonventilator practices to facilitate decannulation include bronchoscopy (50%), exogenous surfactant (25%), and noninhaled pulmonary vasodilators (50%). Common ventilator thresholds for decannulation include PEEP of 6-7 (45%), PIP of 21-25 (55%), and tidal volume 5-5.9 mL/kg (50%).
Conclusions: The majority of level IV NICUs follow internal protocols for ventilator management during neonatal respiratory ECMO, and neonatologists primarily direct management in the NICU. While most centers use pressure-controlled SIMV, there is considerable variability in the range of settings used, with few centers using HFV primarily. Future studies should focus on identifying respiratory management practices that improve outcomes for neonatal ECMO patients
Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context
Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas
Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN