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

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

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

Why growth equals power - and why it shouldn't : constructing visions of China

When discussing the success of China's transition from socialism, there is a tendency to focus on growth figures as an indication of performance. Whilst these figures are indeed impressive, we should not confuse growth with development and assume that the former necessarily automatically generates the latter. Much has been done to reduce poverty in China, but the task is not as complete as some observers would suggest; particularly in terms of access to health, education and welfare, and also in dealing with relative (rather than absolute) depravation and poverty. Visions of China have been constructed that exaggerate Chinese development and power in the global system partly to serve political interests, but partly due to the failure to consider the relationship between growth and development, partly due to the failure to disaggregate who gets what in China, and partly due to the persistence of inter-national conceptions of globalised production, trade, and financial flows

Detection of Multiple Variants of Grapevine Fanleaf Virus in Single Xiphinema index Nematodes

Grapevine fanleaf virus (GFLV) is responsible for a widespread disease in vineyards worldwide. Its genome is composed of two single-stranded positive-sense RNAs, which both show a high genetic diversity. The virus is transmitted from grapevine to grapevine by the ectoparasitic nematode Xiphinema index. Grapevines in diseased vineyards are often infected by multiple genetic variants of GFLV but no information is available on the molecular composition of virus variants retained in X. index following nematodes feeding on roots. In this work, aviruliferous X. index were fed on three naturally GFLV-infected grapevines for which the virome was characterized by RNAseq. Six RNA-1 and four RNA-2 molecules were assembled segregating into four and three distinct phylogenetic clades of RNA-1 and RNA-2, respectively. After 19 months of rearing, single and pools of 30 X. index tested positive for GFLV. Additionally, either pooled or single X. index carried multiple variants of the two GFLV genomic RNAs. However, the full viral genetic diversity found in the leaves of infected grapevines was not detected in viruliferous nematodes, indicating a genetic bottleneck. Our results provide new insights into the complexity of GFLV populations and the putative role of X. index as reservoirs of virus diversity

Thermodynamic State Ensemble Models of cis-Regulation

A major goal in computational biology is to develop models that accurately predict a gene's expression from its surrounding regulatory DNA. Here we present one class of such models, thermodynamic state ensemble models. We describe the biochemical derivation of the thermodynamic framework in simple terms, and lay out the mathematical components that comprise each model. These components include (1) the possible states of a promoter, where a state is defined as a particular arrangement of transcription factors bound to a DNA promoter, (2) the binding constants that describe the affinity of the protein–protein and protein–DNA interactions that occur in each state, and (3) whether each state is capable of transcribing. Using these components, we demonstrate how to compute a cis-regulatory function that encodes the probability of a promoter being active. Our intention is to provide enough detail so that readers with little background in thermodynamics can compose their own cis-regulatory functions. To facilitate this goal, we also describe a matrix form of the model that can be easily coded in any programming language. This formalism has great flexibility, which we show by illustrating how phenomena such as competition between transcription factors and cooperativity are readily incorporated into these models. Using this framework, we also demonstrate that Michaelis-like functions, another class of cis-regulatory models, are a subset of the thermodynamic framework with specific assumptions. By recasting Michaelis-like functions as thermodynamic functions, we emphasize the relationship between these models and delineate the specific circumstances representable by each approach. Application of thermodynamic state ensemble models is likely to be an important tool in unraveling the physical basis of combinatorial cis-regulation and in generating formalisms that accurately predict gene expression from DNA sequence

Combining comparative genomics with de novo motif discovery to identify human transcription factor DNA-binding motifs

BACKGROUND: As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gene regulations. RESULTS: We developed a novel method to combine comparative genomics with de novo motif discovery to identify human transcription factor binding motifs that are overrepresented and conserved in the upstream regions of a set of co-regulated genes. The method is validated by analyzing a well-characterized muscle specific gene set, and the results showed that our approach performed better than the existing programs in terms of sensitivity and prediction rate. CONCLUSION: The newly developed method can be used to extract regulatory signals in co-regulated genes, which can be derived from the microarray clustering analysis

Birtamimab plus standard of care in light-chain amyloidosis: the phase 3 randomized placebo-controlled VITAL trial

Amyloid light-chain (AL) amyloidosis is a rare, typically fatal disease characterized by the accumulation of misfolded immunoglobulin light chains (LCs). Birtamimab is an investigational humanized monoclonal antibody designed to neutralize toxic LC aggregates and deplete insoluble organ-deposited amyloid via macrophage-induced phagocytosis. VITAL was a phase 3 randomized, double-blind, placebo-controlled clinical trial assessing the efficacy and safety of birtamimab + standard of care (SOC) in 260 newly diagnosed, treatment-naive patients with AL amyloidosis. Patients received 24 mg/kg IV birtamimab + SOC or placebo + SOC every 28 days. The primary composite end point was the time to all-cause mortality (ACM) or centrally adjudicated cardiac hospitalization ≥91 days after the first study drug infusion. The trial was terminated early after an interim futility analysis; there was no significant difference in the primary composite end point (hazard ratio [HR], 0.826; 95% confidence interval [CI], 0.574-1.189; log-rank P = .303). A post hoc analysis of patients with Mayo stage IV AL amyloidosis, those at the highest risk of early mortality, showed significant improvement in the time to ACM with birtamimab at month 9 (HR, 0.413; 95% CI, 0.191-0.895; log-rank P = .021). At month 9, 74% of patients with Mayo stage IV AL amyloidosis treated with birtamimab and 49% of those given placebo survived. Overall, the rates of treatment-emergent adverse events (TEAEs) and serious TEAEs were generally similar between treatment arms. A confirmatory phase 3 randomized, double-blind, placebo-controlled clinical trial of birtamimab in patients with Mayo stage IV AL amyloidosis (AFFIRM-AL; NCT04973137) is currently enrolling. The VITAL trial was registered at www.clinicaltrials.gov as #NCT02312206