A cis-regulatory logic simulator

<p>Abstract</p> <p>Background</p> <p>A major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The development of computational methods to decode the interactions among cis-regulatory elements has been slow, in part, because it is difficult to know, without extensive experimental validation, whether a particular method identifies the correct cis-regulatory interactions that underlie a given set of expression data. There is an urgent need for test expression data in which the interactions among cis-regulatory sites that produce the data are known. The ability to rapidly generate such data sets would facilitate the development and comparison of computational methods that predict gene expression patterns from promoter sequence.</p> <p>Results</p> <p>We developed a gene expression simulator which generates expression data using user-defined interactions between cis-regulatory sites. The simulator can incorporate additive, cooperative, competitive, and synergistic interactions between regulatory elements. Constraints on the spacing, distance, and orientation of regulatory elements and their interactions may also be defined and Gaussian noise can be added to the expression values. The simulator allows for a data transformation that simulates the sigmoid shape of expression levels from real promoters. We found good agreement between sets of simulated promoters and predicted regulatory modules from real expression data. We present several data sets that may be useful for testing new methodologies for predicting gene expression from promoter sequence.</p> <p>Conclusion</p> <p>We developed a flexible gene expression simulator that rapidly generates large numbers of simulated promoters and their corresponding transcriptional output based on specified interactions between cis-regulatory sites. When appropriate rule sets are used, the data generated by our simulator faithfully reproduces experimentally derived data sets. We anticipate that using simulated gene expression data sets will facilitate the direct comparison of computational strategies to predict gene expression from promoter sequence. The source code is available online and as additional material. The test sets are available as additional material.</p

Addition of a dairy fraction rich in milk fat globule membrane to a high-saturated fat meal reduces the postprandial insulinaemic and inflammatory response in overweight and obese adults.

Meals high in SFA, particularly palmitate, are associated with postprandial inflammation and insulin resistance. Milk fat globule membrane (MFGM) has anti-inflammatory properties that may attenuate the negative effects of SFA-rich meals. Our objective was to examine the postprandial metabolic and inflammatory response to a high-fat meal composed of palm oil (PO) compared with PO with an added dairy fraction rich in MFGM (PO+MFGM) in overweight and obese men and women (n 36) in a randomised, double-blinded, cross-over trial. Participants consumed two isoenergetic high-fat meals composed of a smoothie enriched with PO with v. without a cream-derived complex milk lipid fraction ( dairy fraction rich in MFGM) separated by a washout of 1-2 weeks. Serum cytokines, adhesion molecules, cortisol and markers of inflammation were measured at fasting, and at 1, 3 and 6&nbsp;h postprandially. Glucose, insulin and lipid profiles were analysed in plasma. Consumption of the PO&nbsp;+&nbsp;MFGM v. PO meal resulted in lower total cholesterol (P&nbsp;=&nbsp;0·021), LDL-cholesterol (P&nbsp;=&nbsp;0·046), soluble intracellular adhesion molecule (P&nbsp;=&nbsp;0·005) and insulin (P&nbsp;=&nbsp;0·005) incremental AUC, and increased IL-10 (P&nbsp;=&nbsp;0·013). Individuals with high baseline C-reactive protein (CRP) concentrations (≥3&nbsp;mg/l, n 17) had higher (P&nbsp;=&nbsp;0·030) insulin at 1&nbsp;h after the PO meal than individuals with CRP concentrations &lt;3&nbsp;mg/l (n 19). The addition of MFGM attenuated this difference between CRP groups. The addition of a dairy fraction rich in MFGM attenuated the negative effects of a high-SFA meal by reducing postprandial cholesterol, inflammatory markers and insulin response in overweight and obese individuals, particularly in those with elevated CRP

Consumption of a high-fat meal containing cheese compared with a vegan alternative lowers postprandial C-reactive protein in overweight and obese individuals with metabolic abnormalities: a randomised controlled cross-over study.

Dietary recommendations suggest decreased consumption of SFA to minimise CVD risk; however, not all foods rich in SFA are equivalent. To evaluate the effects of SFA in a dairy food matrix, as Cheddar cheese, v. SFA from a vegan-alternative test meal on postprandial inflammatory markers, a randomised controlled cross-over trial was conducted in twenty overweight or obese adults with metabolic abnormalities. Individuals consumed two isoenergetic high-fat mixed meals separated by a 1- to 2-week washout period. Serum was collected at baseline, and at 1, 3 and 6 h postprandially and analysed for inflammatory markers (IL-6, IL-8, IL-10, IL-17, IL-18, TNFα, monocyte chemotactic protein-1 (MCP-1)), acute-phase proteins C-reactive protein (CRP) and serum amyloid-A (SAA), cellular adhesion molecules and blood lipids, glucose and insulin. Following both high-fat test meals, postprandial TAG concentrations rose steadily (P &lt; 0·05) without a decrease by 6 h. The incremental AUC (iAUC) for CRP was significantly lower (P &lt; 0·05) in response to the cheese compared with the vegan-alternative test meal. A treatment effect was not observed for any other inflammatory markers; however, for both test meals, multiple markers significantly changed from baseline over the 6 h postprandial period (IL-6, IL-8, IL-18, TNFα, MCP-1, SAA). Saturated fat in the form of a cheese matrix reduced the iAUC for CRP compared with a vegan-alternative test meal during the postprandial 6 h period. The study is registered at clinicaltrials.gov under NCT01803633

HIPAD - A Hybrid Interior-Point Alternating Direction algorithm for knowledge-based SVM and feature selection

We consider classification tasks in the regime of scarce labeled training data in high dimensional feature space, where specific expert knowledge is also available. We propose a new hybrid optimization algorithm that solves the elastic-net support vector machine (SVM) through an alternating direction method of multipliers in the first phase, followed by an interior-point method for the classical SVM in the second phase. Both SVM formulations are adapted to knowledge incorporation. Our proposed algorithm addresses the challenges of automatic feature selection, high optimization accuracy, and algorithmic flexibility for taking advantage of prior knowledge. We demonstrate the effectiveness and efficiency of our algorithm and compare it with existing methods on a collection of synthetic and real-world data.Comment: Proceedings of 8th Learning and Intelligent OptimizatioN (LION8) Conference, 201

Developing a clinical trial unit to advance research in an academic institution

AbstractResearch, clinical care, and education are the three cornerstones of academic health centers in the United States. The research climate has always been riddled with ebbs and flows, depending on funding availability. During a time of reduced funding, the number and scope of research studies have been reduced, and in some instances, a field of study has been eliminated. Recent reductions in the research funding landscape have led institutions to explore new ways to continue supporting research. Mayo Clinic in Rochester, MN has developed a clinical trial unit within the Department of Medicine, which provides shared resources for many researchers and serves as a solution for training and mentoring new investigators and study teams. By building on existing infrastructure and providing supplemental resources to existing research, the Department of Medicine clinical trial unit has evolved into an effective mechanism for conducting research. This article discusses the creation of a central unit to provide research support in clinical trials and presents the advantages, disadvantages, and required building blocks for such a unit

Low-Level Radioactive Waste (LLW) Management at the Nevada Test Site (NTS)

In 1978, the Department of Energy, Nevada Operations Office (DOE/NV), established a managed LLW disposal project at the Nevada Test Site (NTS). Two, sites which were already accepting limited amounts of on-site generated waste for disposal and off-site generated Transuranic Waste for interim storage, were selected to house the disposal facilities. In those early days, these sites, located about 15 miles apart, afforded the DOE/NV the opportunity to use at least two technologies to manage its waste cost effectively. The Area 5 Radioactive Waste Management Site (RWMS) uses engineered shallow-land burial cells to dispose packaged waste while the Area 3 RWMS uses subsidence craters formed from underground testing of nuclear weapons for the disposal of packaged and unpackaged bulk waste. The paper describes the technical attributes of both Area 5 and Area 3 facilities, the acceptance process, the disposal processes, and present and future capacities of both sites