Amplified fragment length homoplasy: in silico analysis for model and non-model species

<p>Abstract</p> <p>Background</p> <p>AFLP markers are widely used in evolutionary genetics and ecology. However the frequent occurrence of non-homologous co-migrating fragments (homoplasy) both at the intra- and inter-individual levels in AFLP data sets is known to skew key parameters in population genetics. Geneticists can take advantage of the growing number of full genome sequences available for model species to study AFLP homoplasy and to predict it in non-model species.</p> <p>Results</p> <p>In this study we performed <it>in silico </it>AFLPs on the complete genome of three model species to predict intra-individual homoplasy in a prokaryote (<it>Bacillus thuringiensis </it>ser. <it>konkukian</it>), a plant (<it>Arabidopsis thaliana</it>) and an animal (<it>Aedes aegypti</it>). In addition, we compared <it>in silico </it>AFLPs to empirical data obtained from three related non-model species (<it>Bacillus thuringiensis </it>ser. <it>israelensis, Arabis alpina </it>and <it>Aedes rusticus</it>). Our results show that homoplasy rate sharply increases with the number of peaks per profile. However, for a given number of peaks per profile, genome size or taxonomical range had no effect on homoplasy. Furthermore, the number of co-migrating fragments in a single peak was dependent on the genome richness in repetitive sequences: we found up to 582 co-migrating fragments in <it>Ae. aegypti</it>. Finally, we show that <it>in silico </it>AFLPs can help to accurately predict AFLP profiles in related non-model species.</p> <p>Conclusions</p> <p>These predictions can be used to tackle current issues in the planning of AFLP studies by limiting homoplasy rate and population genetic estimation bias. ISIF (In SIlico Fingerprinting) program is freely available at <url>http://www-leca.ujf-grenoble.fr/logiciels.htm</url>.</p

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

System integration of wind and solar power in Integrated Assessment Models: A cross-model evaluation of new approaches

Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs. In this study, we qualitatively and quantitatively evaluate the last years' modeling progress and study the impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newly-developed modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourly-resolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050–2100 is 62% of electricity generation, 24%-points higher than with the old model version

Chimpanzee identification and social network construction through an online citizen science platform

Abstract Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a myriad of scientific questions. However, the rise in popularity of citizen science has also been accompanied by concerns about the quality of data emerging from citizen science research projects. We assessed data quality in the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees (Pan troglodytes) and other species across Equatorial Africa. In particular, we compared detection and identification of individual chimpanzees by citizen scientists with that of experts with years of experience studying those chimpanzees. We found that citizen scientists typically detected the same number of individual chimpanzees as experts, but assigned far fewer identifications (IDs) to those individuals. Those IDs assigned, however, were nearly always in agreement with the IDs provided by experts. We applied the data sets of citizen scientists and experts by constructing social networks from each. We found that both social networks were relatively robust and shared a similar structure, as well as having positively correlated individual network positions. Our findings demonstrate that, although citizen scientists produced a smaller data set based on fewer confirmed IDs, the data strongly reflect expert classifications and can be used for meaningful assessments of group structure and dynamics. This approach expands opportunities for social research and conservation monitoring in great apes and many other individually identifiable species

Visceral, subcutaneous abdominal adiposity and liver fat content distribution in normal glucose tolerance, impaired fasting glucose and/or impaired glucose tolerance

Q1Q1Objectives: To examine the specific distribution of liver fat content, visceral and subcutaneous adiposity in normal glucose tolerance (NGT/NGT), isolated impaired fasting glucose (iIFG), isolated impaired glucose tolerance (iIGT) and combined conditions (IFG+IGT), as well as with newly diagnosed type 2 diabetes (nT2D). Design: Multicenter, international observational study: cross-sectional analysis. Subjects: Two thousand five hundred and fifteen patients (50.0% women, 54.5% non-Caucasian) without previously known diabetes were recruited from 29 countries. Abdominal fat distribution was measured by computed tomography (CT). Liver fat was estimated using the CT-liver mean attenuation. Results: Compared with NGT/NGT patients, increased visceral adiposity was found in iIFG, iIGT, IFG+IGT and nT2D; estimated liver fat progressively increased across these conditions. A one-s.d. increase in visceral adiposity was associated with an increased risk of having iIFG (men: odds ratio (OR) 1.41 (95% confidence interval (CI) 1.15–1.74), women: OR 1.62 (1.29–2.04)), iIGT (men: OR 1.59 (1.15–2.01), women: OR 1.30 (0.96–1.76)), IFG+IGT (men: OR 1.64 (1.27–2.13), women: OR 1.83 (1.36–2.48)) and nT2D (men: OR 1.80 (1.35–2.42), women: OR 1.73 (1.25–2.41)). A one-s.d. increase in estimated liver fat was associated with iIGT (men: OR 1.46 (1.12–1.90), women: OR 1.81 (1.41–2.35)), IFG+IGT (men: OR 1.42 (1.14–1.77), women: OR 1.74 (1.35–2.26)) and nT2D (men: OR 1.77 (1.40–2.27), women: OR 2.38 (1.81–3.18)). Subcutaneous abdominal adipose tissue showed an inverse relationship with nT2D in women (OR 0.63 (0.45–0.88)). Conclusions: Liver fat was associated with iIGT but not with iIFG, whereas visceral adiposity was associated with both. Liver fat and visceral adiposity were associated with nT2D, whereas subcutaneous adiposity showed an inverse relationship with nT2D in women

TNF-alpha Is Required for the Attraction of Mesenchymal Precursors to White Adipose Tissue in Ob/ob Mice

Most adult tissues harbour a stem cell subpopulation (Mesenchymal Precursors or MPs) that represent a small proportion of the total cell number and have the potential to differentiate into several cell types within the mesenchymal lineage. In adipose tissue, adipocytes account for two-thirds of the total cell number. The remaining cells include blood and endothelial cells, along with adipocyte precursors (adipose MPs). Obesity is defined as an excess of body fat that frequently results in a significant impairment of health. The ob/ob mice bear a mutation in the ob gene that causes a deficiency in the hormone leptin and hence obesity. Here, we present evidence that ob/ob mice have a dramatic decrease in the resident MP pool of several tissues, including squeletal muscle, heart, lung and adipose tissue. Moreover, we show that that there is a migration of MP cells from distant organs, as well as homing of these cells to the adipose tissue mass of the ob/ob mice. We call this process adipotaxis. Once in the adipose tissue, migrant MPs undergoe adipose differentiation, giving rise to new differentiated adipocytes within the adipose mass. Finally, we provide evidence that adipotaxis is largely explained by the production of high levels of Tumor Necrosis Factor-alpha (TNF-α) within the ob/ob adipose tissue. The therapeutic implications for human obesity as well as for regenerative medicine are further discussed in this paper

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

Waist circumference cut-off values for the prediction of cardiovascular risk factors clustering in Chinese school-aged children: a cross-sectional study

Background: Waist circumference has been identified as a valuable predictor of cardiovascular risk in children. The development of waist circumference percentiles and cut-offs for various ethnic groups are necessary because of differences in body composition. The purpose of this study was to develop waist circumference percentiles for Chinese children and to explore optimal waist circumference cut-off values for predicting cardiovascular risk factors clustering in this population.----- ----- Methods: Height, weight, and waist circumference were measured in 5529 children (2830 boys and 2699 girls) aged 6-12 years randomly selected from southern and northern China. Blood pressure, fasting triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and glucose were obtained in a subsample (n = 1845). Smoothed percentile curves were produced using the LMS method. Receiver-operating characteristic analysis was used to derive the optimal age- and gender-specific waist circumference thresholds for predicting the clustering of cardiovascular risk factors.----- ----- Results: Gender-specific waist circumference percentiles were constructed. The waist circumference thresholds were at the 90th and 84th percentiles for Chinese boys and girls respectively, with sensitivity and specificity ranging from 67% to 83%. The odds ratio of a clustering of cardiovascular risk factors among boys and girls with a higher value than cut-off points was 10.349 (95% confidence interval 4.466 to 23.979) and 8.084 (95% confidence interval 3.147 to 20.767) compared with their counterparts.----- ----- Conclusions: Percentile curves for waist circumference of Chinese children are provided. The cut-off point for waist circumference to predict cardiovascular risk factors clustering is at the 90th and 84th percentiles for Chinese boys and girls, respectively

Plasma triglyceride concentrations are rapidly reduced following individual bouts of endurance exercise in women

It is known that chronic endurance training leads to improvements in the lipoprotein profile, but less is known about changes that occur during postexercise recovery acutely. We analyzed triglyceride (TG), cholesterol classes and apolipoproteins in samples collected before, during and after individual moderate- and hard-intensity exercise sessions in men and women that were isoenergetic between intensities. Young healthy men (n = 9) and young healthy women (n = 9) were studied under three different conditions with diet unchanged between trials: (1) before, during and 3 h after 90 min of exercise at 45% VO2peak (E45); (2) before, during and 3 h after 60 min of exercise at 65% VO2peak (E65), and (3) in a time-matched sedentary control trial (C). At baseline, high-density lipoprotein cholesterol (HDL-C) was higher in women than men (P < 0.05). In men and in women, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), HDL-C, apolipoprotein A-I (apoA-I), apolipoprotein B (apoB), and LDL peak particle size were unaltered by exercise either during exertion or after 3 h of recovery. In women, but not in men, average plasma TG was significantly reduced below C at 3 h postexercise by approximately 15% in E45 and 25% in E65 (P < 0.05) with no significant difference between exercise intensities. In summary, plasma TG concentration rapidly declines following exercise in women, but not in men. These results demonstrate an important mechanism by which each individual exercise session may incrementally reduce the risk for cardiovascular disease (CVD) in women

Do obese but metabolically normal women differ in intra-abdominal fat and physical activity levels from those with the expected metabolic abnormalities? A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Obesity remains a major public health problem, associated with a cluster of metabolic abnormalities. However, individuals exist who are very obese but have normal metabolic parameters. The aim of this study was to determine to what extent differences in metabolic health in very obese women are explained by differences in body fat distribution, insulin resistance and level of physical activity.</p> <p>Methods</p> <p>This was a cross-sectional pilot study of 39 obese women (age: 28-64 yrs, BMI: 31-67 kg/m²) recruited from community settings. Women were defined as 'metabolically normal' on the basis of blood glucose, lipids and blood pressure. Magnetic Resonance Imaging was used to determine body fat distribution. Detailed lifestyle and metabolic profiles of participants were obtained.</p> <p>Results</p> <p>Women with a healthy metabolic profile had lower intra-abdominal fat volume (geometric mean 4.78 l [95% CIs 3.99-5.73] vs 6.96 l [5.82-8.32]) and less insulin resistance (HOMA 3.41 [2.62-4.44] vs 6.67 [5.02-8.86]) than those with an abnormality. The groups did not differ in abdominal subcutaneous fat volume (19.6 l [16.9-22.7] vs 20.6 [17.6-23.9]). A higher proportion of those with a healthy compared to a less healthy metabolic profile met current physical activity guidelines (70% [95% CIs 55.8-84.2] vs 25% [11.6-38.4]). Intra-abdominal fat, insulin resistance and physical activity make independent contributions to metabolic status in very obese women, but explain only around a third of the variance.</p> <p>Conclusion</p> <p>A sub-group of women exists who are metabolically normal despite being very obese. Differences in fat distribution, insulin resistance, and physical activity level are associated with metabolic differences in these women, but account only partially for these differences. Future work should focus on strategies to identify those obese individuals most at risk of the negative metabolic consequences of obesity and on identifying other factors that contribute to metabolic status in obese individuals.</p