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 < 0·05) without a decrease by 6 h. The incremental AUC (iAUC) for CRP was significantly lower (P < 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

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 h postprandially. Glucose, insulin and lipid profiles were analysed in plasma. Consumption of the PO + MFGM v. PO meal resulted in lower total cholesterol (P = 0·021), LDL-cholesterol (P = 0·046), soluble intracellular adhesion molecule (P = 0·005) and insulin (P = 0·005) incremental AUC, and increased IL-10 (P = 0·013). Individuals with high baseline C-reactive protein (CRP) concentrations (≥3 mg/l, n 17) had higher (P = 0·030) insulin at 1 h after the PO meal than individuals with CRP concentrations <3 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

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

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia

Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals

Hereditary transthyretin amyloidosis: baseline characteristics of patients in the NEURO-TTR trial

Background: Hereditary transthyretin (ATTRm) amyloidosis is a rare, progressive and fatal disease with a range of clinical manifestations.Objective: This study comprehensively evaluates disease characteristics in a large, diverse cohort of patients with ATTRm amyloidosis.Methods: Adult patients (N = 172) with Stage 1 or Stage 2 ATTRm amyloidosis who had polyneuropathy were screened and enrolled across 24 investigative sites and 10 countries in the NEURO-TTR trial (www.clinicaltrials.gov, NCT01737398). Medical and disease history, quality of life, laboratory data, and clinical assessments were analyzed.Results: The NEURO-TTR patient population was diverse in age, disease severity, TTR mutation, and organ involvement. Twenty-seven different TTR mutations were present, with Val30Met being the most common (52%). One third of patients reported early onset disease (before age 50) and the average duration of neuropathy symptoms was 5.3 years. Symptoms affected multiple organs and systems, with nearly 70% of patients exhibiting broad involvement of weakness, sensory loss, and autonomic disturbance. Over 60% of patients had cardiomyopathy, with highest prevalence in the United States (72%) and lowest in South America/Australasia (33%). Cardiac biomarker NT-proBNP correlated with left ventricular wall thickness (p<.001). Quality of life, measured by Norfolk QoL-DN and SF-36 patient-reported questionnaires, was significantly impaired and correlated with disease severity.Conclusions: Baseline data from the NEURO-TTR trial demonstrates ATTRm amyloidosis as a systemic disease with deficits in multiple organs and body systems, leading to decreased quality of life. We report concomitant presentation of polyneuropathy and cardiomyopathy in most patients, and early involvement of multiple body systems

Effect of promoter architecture on the cell-to-cell variability in gene expression

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect noise in gene expression in a systematic rather than case-by-case fashion. In this article, we make such a systematic investigation, based on a simple microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcription product from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can discriminate between different kinetic models of gene regulation.Comment: 35 pages, 6 figures, Submitte

Synthetic biology: Understanding biological design from synthetic circuits

An important aim of synthetic biology is to uncover the design principles of natural biological systems through the rational design of gene and protein circuits. Here, we highlight how the process of engineering biological systems — from synthetic promoters to the control of cell–cell interactions — has contributed to our understanding of how endogenous systems are put together and function. Synthetic biological devices allow us to grasp intuitively the ranges of behaviour generated by simple biological circuits, such as linear cascades and interlocking feedback loops, as well as to exert control over natural processes, such as gene expression and population dynamics

FOXM1 binds directly to non-consensus sequences in the human genome.

BACKGROUND: The Forkhead (FKH) transcription factor FOXM1 is a key regulator of the cell cycle and is overexpressed in most types of cancer. FOXM1, similar to other FKH factors, binds to a canonical FKH motif in vitro. However, genome-wide mapping studies in different cell lines have shown a lack of enrichment of the FKH motif, suggesting an alternative mode of chromatin recruitment. We have investigated the role of direct versus indirect DNA binding in FOXM1 recruitment by performing ChIP-seq with wild-type and DNA binding deficient FOXM1. RESULTS: An in vitro fluorescence polarization assay identified point mutations in the DNA binding domain of FOXM1 that inhibit binding to a FKH consensus sequence. Cell lines expressing either wild-type or DNA binding deficient GFP-tagged FOXM1 were used for genome-wide mapping studies comparing the distribution of the DNA binding deficient protein to the wild-type. This shows that interaction of the FOXM1 DNA binding domain with target DNA is essential for recruitment. Moreover, analysis of the protein interactome of wild-type versus DNA binding deficient FOXM1 shows that the reduced recruitment is not due to inhibition of protein-protein interactions. CONCLUSIONS: A functional DNA binding domain is essential for FOXM1 chromatin recruitment. Even in FOXM1 mutants with almost complete loss of binding, the protein-protein interactions and pattern of phosphorylation are largely unaffected. These results strongly support a model whereby FOXM1 is specifically recruited to chromatin through co-factor interactions by binding directly to non-canonical DNA sequences.We would like to acknowledge the Genomics and bioinformatics core at the CRUK Research Institute for the Illumina sequencing and the Proteomics core for the LC/MS-MS protein analysis for the RIME experiments. We acknowledge the support from The University of Cambridge and Cancer Research UK. The Balasubramanian Laboratory is supported by core funding from Cancer Research UK (C14303/A17197). SB is a Wellcome Trust Principle Investigator.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13059-015-0696-