Metabolic syndrome and the risk of cardiovascular disease in older adults.

OBJECTIVES: The purpose of this study was to assess whether metabolic syndrome (MetSyn) predicts a higher risk for cardiovascular events in older adults. BACKGROUND: The importance of MetSyn as a risk factor has not previously focused on older adults and deserves further study. METHODS: We studied the impact of MetSyn (38% prevalence) on outcomes in 3,035 participants in the Health, Aging, and Body Composition (Health ABC) study (51% women, 42% black, ages 70 to 79 years). RESULTS: During a 6-year follow-up, there were 434 deaths overall, 472 coronary events (CE), 213 myocardial infarctions (MI), and 231 heart failure (HF) hospital stays; 59% of the subjects had at least one hospital stay. Coronary events, MI, HF, and overall hospital stays occurred significantly more in subjects with MetSyn (19.9% vs. 12.9% for CE, 9.1% vs. 5.7% for MI, 10.0% vs. 6.1% for HF, and 63.1% vs. 56.1% for overall hospital stay; all p < 0.001). No significant differences in overall mortality was seen; however, there was a trend toward higher cardiovascular mortality (5.1% vs. 3.8%, p = 0.067) and coronary mortality (4.5% vs. 3.2%, p = 0.051) in patients with MetSyn. After adjusting for baseline characteristics, patients with MetSyn were at a significantly higher risk for CE (hazard ratio [HR] 1.56, 95% confidence interval [CI] 1.28 to 1.91), MI (HR 1.51, 95% CI 1.12 to 2.05), and HF hospital stay (HR 1.49, 95% CI 1.10 to 2.00). Women and whites with MetSyn had a higher coronary mortality rate. The CE rate was higher among subjects with diabetes and with MetSyn; those with both had the highest risk. CONCLUSIONS: Overall, subjects over 70 years are at high risk for cardiovascular events; MetSyn in this group is associated with a significantly greater risk.

Deciphering the global organization of clustering in real complex networks

We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.

The metabolic syndrome, a multifaceted disease of affluence

Metabolic syndrome developed in consequence of an evolutionary inadequacy: the human body was unprepared for a dietary excess of nutrients, especially lipids (largely in detriment of carbohydrate). This excess awakens metabolic signals akin to those of starvation, in which the main energy staple is the body"s own lipid reserve. Lipid dietary abundance prevents the use of glucose, which in turn limits the oxidation of amino acids. To ward against a subsequent avalanche of substrates, the immune system and hypertrophied tissues (for example, adipose) elicit a series of defence responses. This response is probably the ultimate basis of a disease that is manifested as various pathologies, which were initially defined as distinct entities but which are slowly being seen as a single pathognomic unit in the literature. Based on their common origin of the ample availability of food in our modern society, the cluster of diseases comprising the metabolic syndrome is probably best described as a single multifaceted disease.

Increased male offspring's risk of metabolic-neuroendocrine dysfunction and overweight after fructose-rich diet intake by the lactating mother.

An adverse endogenous environment during early life predisposes the organism to develop metabolic disorders. We evaluated the impact of intake of an iso-caloric fructose rich diet (FRD) by lactating mothers (LM) on several metabolic functions of their male offspring. On postnatal d 1, ad libitum eating, lactating Sprague-Dawley rats received either 10% F (wt/vol; FRD-LM) or tap water (controls, CTR-LM) to drink throughout lactation. Weaned male offspring were fed ad libitum a normal diet, and body weight (BW) and food intake were registered until experimentation (60 d of age). Basal circulating levels of metabolic markers were evaluated. Both iv glucose tolerance and hypothalamic leptin sensitivity tests were performed. The hypothalamus was dissected for isolation of total RNA and Western blot analysis. Retroperitoneal (RP) adipose tissue was dissected and either kept frozen for gene analysis or digested to isolate adipocytes or for histological studies. FRD rats showed increased BW and decreased hypothalamic sensitivity to exogenous leptin, enhanced food intake (between 49-60 d), and decreased hypothalamic expression of several anorexigenic signals. FRD rats developed increased insulin and leptin peripheral levels and decreased adiponectinemia; although FRD rats normally tolerated glucose excess, it was associated with enhanced insulin secretion. FRD RP adipocytes were enlarged and spontaneously released high leptin, although they were less sensitive to insulin-induced leptin release. Accordingly, RP fat leptin gene expression was high in FRD rats. Excessive fructose consumption by lactating mothers resulted in deep neuroendocrine-metabolic disorders of their male offspring, probably enhancing the susceptibility to develop overweight/obesity during adult life.

Bayesian networks and the evaluation of scientific evidence in forensic science

Résumé Ce travail de thèse étudie des moyens de formalisation permettant d'assister l'expert forensique dans la gestion des facteurs influençant l'évaluation des indices scientifiques, tout en respectant des procédures d'inférence établies et acceptables. Selon une vue préconisée par une partie majoritaire de la littérature forensique et juridique - adoptée ici sans réserve comme point de départ - la conceptualisation d'une procédure évaluative est dite 'cohérente' lors qu'elle repose sur une implémentation systématique de la théorie des probabilités. Souvent, par contre, la mise en oeuvre du raisonnement probabiliste ne découle pas de manière automatique et peut se heurter à des problèmes de complexité, dus, par exemple, à des connaissances limitées du domaine en question ou encore au nombre important de facteurs pouvant entrer en ligne de compte. En vue de gérer ce genre de complications, le présent travail propose d'investiguer une formalisation de la théorie des probabilités au moyen d'un environment graphique, connu sous le nom de Réseaux bayesiens (Bayesian networks). L'hypothèse principale que cette recherche envisage d'examiner considère que les Réseaux bayesiens, en concert avec certains concepts accessoires (tels que des analyses qualitatives et de sensitivité), constituent une ressource clé dont dispose l'expert forensique pour approcher des problèmes d'inférence de manière cohérente, tant sur un plan conceptuel que pratique. De cette hypothèse de travail, des problèmes individuels ont été extraits, articulés et abordés dans une série de recherches distinctes, mais interconnectées, et dont les résultats - publiés dans des revues à comité de lecture - sont présentés sous forme d'annexes. D'un point de vue général, ce travail apporte trois catégories de résultats. Un premier groupe de résultats met en évidence, sur la base de nombreux exemples touchant à des domaines forensiques divers, l'adéquation en termes de compatibilité et complémentarité entre des modèles de Réseaux bayesiens et des procédures d'évaluation probabilistes existantes. Sur la base de ces indications, les deux autres catégories de résultats montrent, respectivement, que les Réseaux bayesiens permettent également d'aborder des domaines auparavant largement inexplorés d'un point de vue probabiliste et que la disponibilité de données numériques dites 'dures' n'est pas une condition indispensable pour permettre l'implémentation des approches proposées dans ce travail. Le présent ouvrage discute ces résultats par rapport à la littérature actuelle et conclut en proposant les Réseaux bayesiens comme moyen d'explorer des nouvelles voies de recherche, telles que l'étude de diverses formes de combinaison d'indices ainsi que l'analyse de la prise de décision. Pour ce dernier aspect, l'évaluation des probabilités constitue, dans la façon dont elle est préconisée dans ce travail, une étape préliminaire fondamentale de même qu'un moyen opérationnel.

Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks

Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.

Body composition phenotypes in pathways to obesity and the metabolic syndrome.

Dynamic changes in body weight have long been recognized as important indicators of risk for debilitating diseases. While weight loss or impaired growth can lead to muscle wastage, as well as to susceptibility to infections and organ dysfunctions, the development of excess fat predisposes to type 2 diabetes and cardiovascular diseases, with insulin resistance as a central feature of the disease entities of the metabolic syndrome. Although widely used as the phenotypic expression of adiposity in population and gene-search studies, body mass index (BMI), that is, weight/height(2) (H(2)), which was developed as an operational definition for classifying both obesity and malnutrition, has considerable limitations in delineating fat mass (FM) from fat-free mass (FFM), in particular at the individual level. After an examination of these limitations within the constraints of the BMI-FM% relationship, this paper reviews recent advances in concepts about health risks related to body composition phenotypes, which center upon (i) the partitioning of BMI into an FM index (FM/H(2)) and an FFM index (FFM/H(2)), (ii) the partitioning of FFM into organ mass and skeletal muscle mass, (iii) the anatomical partitioning of FM into hazardous fat and protective fat and (iv) the interplay between adipose tissue expandability and ectopic fat deposition within or around organs/tissues that constitute the lean body mass. These concepts about body composition phenotypes and health risks are reviewed in the light of race/ethnic variability in metabolic susceptibility to obesity and the metabolic syndrome.

Metabolic alterations and increased liver mTOR expression precede the development of autoimmune disease in a murine model of lupus erythematosus

Although metabolic syndrome (MS) and systemic lupus erythematosus (SLE) are often associated, a common link has not been identified. Using the BWF1 mouse, which develops MS and SLE, we sought a molecular connection to explain the prevalence of these two diseases in the same individuals. We determined SLE- markers (plasma anti-ds-DNA antibodies, splenic regulatory T cells (Tregs) and cytokines, proteinuria and renal histology) and MS-markers (plasma glucose, non-esterified fatty acids, triglycerides, insulin and leptin, liver triglycerides, visceral adipose tissue, liver and adipose tissue expression of 86 insulin signaling-related genes) in 8-, 16-, 24-, and 36-week old BWF1 and control New-Zealand-White female mice. Up to week 16, BWF1 mice showed MS-markers (hyperleptinemia, hyperinsulinemia, fatty liver and visceral adipose tissue) that disappeared at week 36, when plasma anti-dsDNA antibodies, lupus nephritis and a pro-autoimmune cytokine profile were detected. BWF1 mice had hyperleptinemia and high splenic Tregs till week 16, thereby pointing to leptin resistance, as confirmed by the lack of increased liver P-Tyr-STAT-3. Hyperinsulinemia was associated with a down-regulation of insulin related-genes only in adipose tissue, whereas expression of liver mammalian target of rapamicyn (mTOR) was increased. Although leptin resistance presented early in BWF1 mice can slow-down the progression of autoimmunity, our results suggest that sustained insulin stimulation of organs, such as liver and probably kidneys, facilitates the over-expression and activity of mTOR and the development of SLE.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

An overview of the metabolic differences between Bradyrhizobium japonicum 110 bacteria and differentiated bacteroids from soybean (Glycine max) root nodules: an in vitro 13C- and 31P-nuclear magnetic resonance spectroscopy study.

Bradyrhizobium japonicum is a symbiotic nitrogen-fixing soil bacteria that induce root nodules formation in legume soybean (Glycine max.). Using (13)C- and (31)P-nuclear magnetic resonance (NMR) spectroscopy, we have analysed the metabolite profiles of cultivated B. japonicum cells and bacteroids isolated from soybean nodules. Our results revealed some quantitative and qualitative differences between the metabolite profiles of bacteroids and their vegetative state. This includes in bacteroids a huge accumulation of soluble carbohydrates such as trehalose, glutamate, myo-inositol and homospermidine as well as Pi, nucleotide pools and intermediates of the primary carbon metabolism. Using this novel approach, these data show that most of the compounds detected in bacteroids reflect the metabolic adaptation of rhizobia to the surrounding microenvironment with its host plant cells.

Metabolic and physiologic effects of an endotoxin challenge in healthy obese subjects.

Aim: The obesity epidemic has increased the number of obese patients admitted to the ICU. In vitro studies suggest that adipose tissue response to inflammation is enhanced: in vivo data are not conclusive yet. The aim of this study was to test the physiologic response of healthy obese subjects to a standardized intravenous LPS challenge.Methods: Prospective single-blind, randomized, cross-over study in eight subjects (four men, four women), aged 34 +/- 7 years, BMI 34.7 +/- 4.2, without glucose intolerance and lipid abnormalities, testing the impact of intravenous LPS (2 ng kg(-1) of actual body weight) versus placebo.Results: Temperature, hemodynamic variables, indirect calorimetry and blood samples (TNF-alpha, IL-6, stress hormones, hs-CRP) were collected. After LPS temperature, heart rate. TNF-alpha and IL-6 concentrations and stress hormones (cortisol and glucagon) increased significantly, with maximal responses between 120 and 240 min after the injection. The pattern, the timing and the magnitude of change were similar to those observed in lean subjects.Conclusion: This study shows that healthy obese subjects have a similar response pattern to intravenous LPS as described in lean subjects.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

Metabolic fate of fructose ingested with and without glucose in a mixed meal.

Ingestion of pure fructose stimulates de novo lipogenesis and gluconeogenesis. This may however not be relevant to typical nutritional situations, where fructose is invariably ingested with glucose. We therefore assessed the metabolic fate of fructose incorporated in a mixed meal without or with glucose in eight healthy volunteers. Each participant was studied over six hours after the ingestion of liquid meals containing either 13C-labelled fructose, unlabeled glucose, lipids and protein (Fr + G) or 13C-labelled fructose, lipids and protein, but without glucose (Fr), or protein and lipids alone (ProLip). After Fr + G, plasma 13C-glucose production accounted for 19.0% ± 1.5% and 13CO2 production for 32.2% ± 1.3% of 13C-fructose carbons. After Fr, 13C-glucose production (26.5% ± 1.4%) and 13CO2 production (36.6% ± 1.9%) were higher (p < 0.05) than with Fr + G. 13C-lactate concentration and very low density lipoprotein VLDL 13C-palmitate concentrations increased to the same extent with Fr + G and Fr, while chylomicron 13C-palmitate tended to increase more with Fr + G. These data indicate that gluconeogenesis, lactic acid production and both intestinal and hepatic de novo lipogenesis contributed to the disposal of fructose carbons ingested together with a mixed meal. Co-ingestion of glucose decreased fructose oxidation and gluconeogenesis and tended to increase 13C-pamitate concentration in gut-derived chylomicrons, but not in hepatic-borne VLDL-triacylglycerol (TG). This trial was approved by clinicaltrial. gov. Identifier is NCT01792089.

Efficiency of informational transfer in regular and complex networks

We analyze the process of informational exchange through complex networks by measuring network efficiencies. Aiming to study nonclustered systems, we propose a modification of this measure on the local level. We apply this method to an extension of the class of small worlds that includes declustered networks and show that they are locally quite efficient, although their clustering coefficient is practically zero. Unweighted systems with small-world and scale-free topologies are shown to be both globally and locally efficient. Our method is also applied to characterize weighted networks. In particular we examine the properties of underground transportation systems of Madrid and Barcelona and reinterpret the results obtained for the Boston subway network.