Relation of C-reactive protein to body fat distribution and features of the metabolic syndrome in Europeans and South Asians.

OBJECTIVE: To investigate the association between circulating C-reactive protein (CRP) concentrations and indices of body fat distribution and the insulin resistance syndrome in South Asians and Europeans. DESIGN: : Cross-sectional study. SUBJECTS: A total of 113 healthy South Asian and European men and women in West London (age 40-55 y, body mass index (BMI) 17-34 kg/m(2)). MEASUREMENTS: Fatness and fat distribution parameters (by anthropometry, dual-energy X-ray absorptiometry and abdominal CT scan); oral glucose tolerance test with insulin response; modified fat tolerance test; and CRP concentration by sensitive ELISA. RESULTS: Median CRP level in South Asian women was nearly double that in European women (1.35 vs 0.70 mg/1, P=0.05). Measures of obesity and CRP concentration were significantly associated in both ethnic groups. The correlation to CRP was especially strong among South Asians (P0.15). CONCLUSION: We suggest that adiposity and in particular visceral adipose tissue is a key promoter of low-grade chronic inflammation. This observation may in part account for the association of CRP with markers of the metabolic syndrome. Future studies should confirm whether CRP concentrations are elevated in South Asians and whether losing weight by exercise or diet, or reduction in visceral fat mass, is associated with reduction in plasma CRP concentrations

Probabilistic analysis of the upwind scheme for transport

We provide a probabilistic analysis of the upwind scheme for multi-dimensional transport equations. We associate a Markov chain with the numerical scheme and then obtain a backward representation formula of Kolmogorov type for the numerical solution. We then understand that the error induced by the scheme is governed by the fluctuations of the Markov chain around the characteristics of the flow. We show, in various situations, that the fluctuations are of diffusive type. As a by-product, we prove that the scheme is of order 1/2 for an initial datum in BV and of order 1/2-a, for all a>0, for a Lipschitz continuous initial datum. Our analysis provides a new interpretation of the numerical diffusion phenomenon

Model selection with overdispersed distance sampling data

We thank the Robert Bosch Foundation, the Max Planck Society and the University of St Andrews for funding.1. Distance sampling (DS) is a widely used framework for estimating animal abundance. DS models assume that observations of distances to animals are independent. Non‐independent observations introduce overdispersion, causing model selection criteria such as AIC or AICc to favour overly complex models, with adverse effects on accuracy and precision. 2. We describe, and evaluate via simulation and with real data, estimators of an overdispersion factor (ĉ), and associated adjusted model selection criteria (QAIC) for use with overdispersed DS data. In other contexts, a single value of ĉ is calculated from the “global” model, that is the most highly parameterised model in the candidate set, and used to calculate QAIC for all models in the set; the resulting QAIC values, and associated ΔQAIC values and QAIC weights, are comparable across the entire set. Candidate models of the DS detection function include models with different general forms (e.g. half‐normal, hazard rate, uniform), so it may not be possible to identify a single global model. We therefore propose a two‐step model selection procedure by which QAIC is used to select among models with the same general form, and then a goodness‐of‐fit statistic is used to select among models with different forms. A drawback of thi approach is that QAIC values are not comparable across all models in the candidate set. 3. Relative to AIC, QAIC and the two‐step model selection procedure avoided overfitting and improved the accuracy and precision of densities estimated from simulated data. When applied to six real datasets, adjusted criteria and procedures selected either the same model as AIC or a model that yielded a more accurate density estimate in five cases, and a model that yielded a less accurate estimate in one case. 4. Many DS surveys yield overdispersed data, including cue counting surveys of songbirds and cetaceans, surveys of social species including primates, and camera‐trapping surveys. Methods that adjust for overdispersion during the model selection stage of DS analyses therefore address a conspicuous gap in the DS analytical framework as applied to species of conservation concern.PostprintPeer reviewe

The endocanabinnoid system and diabetes - critical analyses of studies conducted with rimonabant

Rimonabant is the first CB1 receptor inhibitor available in the Brazilian market. This new drug has been approved for the treatment of obese or overweight patients associated with cardiovascular risk factors. In this article it is compared the effects of rimonabant treatment in obese patients with cardiovascular risk factors to usual obesity pharmacological treatment

Drugs Associated with More Suicidal Ideations Are also Associated with More Suicide Attempts

In randomized controlled trials (RCTs), some drugs, including CB1 antagonists for obesity treatment, have been shown to cause increased suicidal ideation. A key question is whether drugs that increase or are associated with increased suicidal ideations are also associated with suicidal behavior, or whether drug-induced suicidal ideations are unlinked epiphenomena that do not presage the more troubling and potentially irrevocable outcome of suicidal behavior. This is difficult to determine in RCTs because of the rarity of suicidal attempts and completions.To determine whether drugs associated with more suicidal ideations are also associated with more suicide attempts in large spontaneous adverse event (AE) report databases.Generalized linear models with negative binomial distribution were fitted to Food and Drug Administration (FDA) Adverse Event (AE) Reporting System (AERS) data from 2004 to 2008. A total of 1,404,470 AEs from 832 drugs were analyzed as a function of reports of suicidal ideations; other non-suicidal adverse reactions; drug class; proportion of reports from males; and average age of subject for which AE was filed. Drug was treated as the unit of analysis, thus the statistical models effectively had 832 observations.Reported suicide attempts and completed suicides per drug.832 drugs, ranging from abacavir to zopiclone, were evaluated. The 832 drugs, as primary suspect drugs in a given adverse event, accounted for over 99.9% of recorded AERS. Suicidal ideations had a significant positive association with suicide attempts (p<.0001) and had an approximately 131-fold stronger magnitude of association than non-suicidal AERs, after adjusting for drug class, gender, and age.In AE reports, drugs that are associated with increased suicidal ideations are also associated with increased suicidal attempts or completions. This association suggests that drug-induced suicidal ideations observed in RCTs plausibly represent harbingers that presage the more serious suicide attempts and completions and should be a cause for concern

Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases

The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate. In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance. Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified. These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan

Mid-century emission pathways in Japan associated with the global 2 °C goal: national and global models’ assessments based on carbon budgets

This study assesses Japan’s mid-century low-emission pathways using both national and global integrated assessment models in the common mitigation scenario framework, based on the carbon budgets corresponding to the global 2 °C goal. We examine high and low budgets, equal to global cumulative 1600 and 1000 Gt-CO2 (2011–2100) for global models, and 36 and 31 Gt-CO2 (2011–2050) in Japan for national models, based on the cost-effectiveness allocation performed by the global models. The impacts of near-term policy assumption, including the implementation and enhancement of the 2030 target of the nationally determined contribution (NDC), are also considered. Our estimates show that the low budget scenarios require a 75% reduction of CO2 emissions by 2050 below the 2010 level, which is nearly the same as Japan’s governmental 2050 goal of reducing greenhouse gas emissions by 80%. With regard to near-term actions, Japan’s 2030 target included in the NDC is on track to meet the high budget scenario, whereas it is falling short for the low budget scenario, which would require emission reductions immediately after 2020. Whereas models differ in the type of energy source on which they foresee Japan basing its decarbonization process (e.g., nuclear- or variable renewable energy-dependent), the large-scale deployment of low-carbon energy (nuclear, renewable, and carbon capture and storage) is shared across most models in both the high and low budget scenarios. By 2050, low-carbon energy represents 44–54% of primary energy and 86–97% of electricity supply in the high and low budget scenarios, respectively

Cafeteria Diet Is a Robust Model of Human Metabolic Syndrome With Liver and Adipose Inflammation: Comparison to High-Fat Diet

Obesity has reached epidemic proportions worldwide and reports estimate that American children consume up to 25% of calories from snacks. Several animal models of obesity exist, but studies are lacking that compare high-fat diets (HFD) traditionally used in rodent models of diet-induced obesity (DIO) to diets consisting of food regularly consumed by humans, including high-salt, high-fat, low-fiber, energy dense foods such as cookies, chips, and processed meats. To investigate the obesogenic and inflammatory consequences of a cafeteria diet (CAF) compared to a lard-based 45% HFD in rodent models, male Wistar rats were fed HFD, CAF or chow control diets for 15 weeks. Body weight increased dramatically and remained significantly elevated in CAF-fed rats compared to all other diets. Glucose- and insulin-tolerance tests revealed that hyperinsulinemia, hyperglycemia, and glucose intolerance were exaggerated in the CAF-fed rats compared to controls and HFD-fed rats. It is well-established that macrophages infiltrate metabolic tissues at the onset of weight gain and directly contribute to inflammation, insulin resistance, and obesity. Although both high fat diets resulted in increased adiposity and hepatosteatosis, CAF-fed rats displayed remarkable inflammation in white fat, brown fat and liver compared to HFD and controls. In sum, the CAF provided a robust model of human metabolic syndrome compared to traditional lard-based HFD, creating a phenotype of exaggerated obesity with glucose intolerance and inflammation. This model provides a unique platform to study the biochemical, genomic and physiological mechanisms of obesity and obesity-related disease states that are pandemic in western civilization today