994 resultados para FAT SOURCES


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An analysis of the dietary content of haematophagous insects can provide important information about the transmission networks of certain zoonoses. The present study evaluated the potential of polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis of the mitochondrial cytochrome B (cytb) gene to differentiate between vertebrate species that were identified as possible sources of sandfly meals. The complete cytb gene sequences of 11 vertebrate species available in the National Center for Biotechnology Information database were digested with Aci I, Alu I, Hae III and Rsa I restriction enzymes in silico using Restriction Mapper software. The cytb gene fragment (358 bp) was amplified from tissue samples of vertebrate species and the dietary contents of sandflies and digested with restriction enzymes. Vertebrate species presented a restriction fragment profile that differed from that of other species, with the exception of Canis familiaris and Cerdocyon thous. The 358 bp fragment was identified in 76 sandflies. Of these, 10 were evaluated using the restriction enzymes and the food sources were predicted for four: Homo sapiens (1), Bos taurus (1) and Equus caballus (2). Thus, the PCR-RFLP technique could be a potential method for identifying the food sources of arthropods. However, some points must be clarified regarding the applicability of the method, such as the extent of DNA degradation through intestinal digestion, the potential for multiple sources of blood meals and the need for greater knowledge regarding intraspecific variations in mtDNA.

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Objective: to assess the between and within-device reproducibility, as well as within-day variability of body fat measurements. Methods: body fat percentage (%BF) was measured twice on seventeen female students aged between 18 and 20 with a body mass index of 21.9 22.6 kg/m2 (mean SD) using seven bipolar bioelectrical impedance devices (BF-306) according to the manufacturer's recommendations. Each student was also measured each hour between 7:00 and 22:00. Statistical analysis was conducted using a general linear model for repeated measurements. Results: the correlation between first and second measurements was very high (Pearson r between 0.985 and 1.000, p<0.001), as well as the correlation between devices (Pearson r between 0.986 and 0.999, all p<0.001). Repeated measurements analysis showed no differences were between devices (F test=0.83, p=0.59) or readings (first vs. second: F test=0.12, p=0.74). Conversely, significant differences were found between assessment periods throughout the day, measurements made in the morning being lower than those made in the afternoon. Assuming an overall daily average of 100 (based on all measurements), the values were 95.8 3.2 (mean SD) at 8:00 versus 101.3 3.0 at 20:00, corresponding to a mean change of 2.2 1.1 in %BF (F test for repeated values=6.58, p<0.001). Conclusions: the between and within-device reproducibility for measuring body fat is high, enabling the use of multiple devices in a single study. Conversely, small but significant changes in body fat measurements occur during the day, urging body fat measurements to be performed at fixed times.

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C57BL/6J mice were fed a high-fat, carbohydrate-free diet (HFD) for 9 mo. Approximately 50% of the mice became obese and diabetic (ObD), approximately 10% lean and diabetic (LD), approximately 10% lean and nondiabetic (LnD), and approximately 30% displayed intermediate phenotype. All of the HFD mice were insulin resistant. In the fasted state, whole body glucose clearance was reduced in ObD mice, unchanged in the LD mice, and increased in the LnD mice compared with the normal-chow mice. Because fasted ObD mice were hyperinsulinemic and the lean mice slightly insulinopenic, there was no correlation between insulin levels and increased glucose utilization. In vivo, tissue glucose uptake assessed by 2-[(14)C]deoxyglucose accumulation was reduced in most muscles in the ObD mice but increased in the LnD mice compared with the values of the control mice. In the LD mice, the glucose uptake rates were reduced in extensor digitorum longus (EDL) and total hindlimb but increased in soleus, diaphragm, and heart. When assessed in vitro, glucose utilization rates in the absence and presence of insulin were similar in diaphragm, soleus, and EDL muscles isolated from all groups of mice. Thus, in genetically homogenous mice, HFD feeding lead to different metabolic adaptations. Whereas all of the mice became insulin resistant, this was associated, in obese mice, with decreased glucose clearance and hyperinsulinemia and, in lean mice, with increased glucose clearance in the presence of mild insulinopenia. Therefore, increased glucose clearance in lean mice could not be explained by increased insulin level, indicating that other in vivo mechanisms are triggered to control muscle glucose utilization. These adaptive mechanisms could participate in the protection against development of obesity.

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OBJECTIVE: Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI. METHODS: FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated. RESULTS: FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively. CONCLUSION: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.

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BACKGROUND Compared to food patterns, nutrient patterns have been rarely used particularly at international level. We studied, in the context of a multi-center study with heterogeneous data, the methodological challenges regarding pattern analyses. METHODOLOGY/PRINCIPAL FINDINGS We identified nutrient patterns from food frequency questionnaires (FFQ) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study and used 24-hour dietary recall (24-HDR) data to validate and describe the nutrient patterns and their related food sources. Associations between lifestyle factors and the nutrient patterns were also examined. Principal component analysis (PCA) was applied on 23 nutrients derived from country-specific FFQ combining data from all EPIC centers (N = 477,312). Harmonized 24-HDRs available for a representative sample of the EPIC populations (N = 34,436) provided accurate mean group estimates of nutrients and foods by quintiles of pattern scores, presented graphically. An overall PCA combining all data captured a good proportion of the variance explained in each EPIC center. Four nutrient patterns were identified explaining 67% of the total variance: Principle component (PC) 1 was characterized by a high contribution of nutrients from plant food sources and a low contribution of nutrients from animal food sources; PC2 by a high contribution of micro-nutrients and proteins; PC3 was characterized by polyunsaturated fatty acids and vitamin D; PC4 was characterized by calcium, proteins, riboflavin, and phosphorus. The nutrients with high loadings on a particular pattern as derived from country-specific FFQ also showed high deviations in their mean EPIC intakes by quintiles of pattern scores when estimated from 24-HDR. Center and energy intake explained most of the variability in pattern scores. CONCLUSION/SIGNIFICANCE The use of 24-HDR enabled internal validation and facilitated the interpretation of the nutrient patterns derived from FFQs in term of food sources. These outcomes open research opportunities and perspectives of using nutrient patterns in future studies particularly at international level.

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FNDC5/irisin has been recently postulated as beneficial in the treatment of obesity and diabetes because it is induced in muscle by exercise, increasing energy expenditure. However, recent reports have shown that WAT also secretes irisin and that circulating irisin is elevated in obese subjects. The aim of this study was to evaluate irisin levels in conditions of extreme BMI and its correlation with basal metabolism and daily activity. The study involved 145 female patients, including 96 with extreme BMIs (30 anorexic (AN) and 66 obese (OB)) and 49 healthy normal weight (NW). The plasma irisin levels were significantly elevated in the OB patients compared with the AN and NW patients. Irisin also correlated positively with body weight, BMI, and fat mass. The OB patients exhibited the highest REE and higher daily physical activity compared with the AN patients but lower activity compared with the NW patients. The irisin levels were inversely correlated with daily physical activity and directly correlated with REE. Fat mass contributed to most of the variability of the irisin plasma levels independently of the other studied parameters. Conclusion. Irisin levels are influenced by energy expenditure independently of daily physical activity but fat mass is the main contributing factor.

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Résumé Lors d'une recherche d'information, l'apprenant est très souvent confronté à des problèmes de guidage et de personnalisation. Ceux-ci sont d'autant plus importants que la recherche se fait dans un environnement ouvert tel que le Web. En effet, dans ce cas, il n'y a actuellement pas de contrôle de pertinence sur les ressources proposées pas plus que sur l'adéquation réelle aux besoins spécifiques de l'apprenant. A travers l'étude de l'état de l'art, nous avons constaté l'absence d'un modèle de référence qui traite des problématiques liées (i) d'une part aux ressources d'apprentissage notamment à l'hétérogénéité de la structure et de la description et à la protection en terme de droits d'auteur et (ii) d'autre part à l'apprenant en tant qu'utilisateur notamment l'acquisition des éléments le caractérisant et la stratégie d'adaptation à lui offrir. Notre objectif est de proposer un système adaptatif à base de ressources d'apprentissage issues d'un environnement à ouverture contrôlée. Celui-ci permet de générer automatiquement sans l'intervention d'un expert pédagogue un parcours d'apprentissage personnalisé à partir de ressources rendues disponibles par le biais de sources de confiance. L'originalité de notre travail réside dans la proposition d'un modèle de référence dit de Lausanne qui est basé sur ce que nous considérons comme étant les meilleures pratiques des communautés : (i) du Web en terme de moyens d'ouverture, (ii) de l'hypermédia adaptatif en terme de stratégie d'adaptation et (iii) de l'apprentissage à distance en terme de manipulation des ressources d'apprentissage. Dans notre modèle, la génération des parcours personnalisés se fait sur la base (i) de ressources d'apprentissage indexées et dont le degré de granularité en favorise le partage et la réutilisation. Les sources de confiance utilisées en garantissent l'utilité et la qualité. (ii) de caractéristiques de l'utilisateur, compatibles avec les standards existants, permettant le passage de l'apprenant d'un environnement à un autre. (iii) d'une adaptation à la fois individuelle et sociale. Pour cela, le modèle de Lausanne propose : (i) d'utiliser ISO/MLR (Metadata for Learning Resources) comme formalisme de description. (ii) de décrire le modèle d'utilisateur avec XUN1 (eXtended User Model), notre proposition d'un modèle compatible avec les standards IEEE/PAPI et IMS/LIP. (iii) d'adapter l'algorithme des fourmis au contexte de l'apprentissage à distance afin de générer des parcours personnalisés. La dimension individuelle est aussi prise en compte par la mise en correspondance de MLR et de XUM. Pour valider notre modèle, nous avons développé une application et testé plusieurs scenarii mettant en action des utilisateurs différents à des moments différents. Nous avons ensuite procédé à des comparaisons entre ce que retourne le système et ce que suggère l'expert. Les résultats s'étant avérés satisfaisants dans la mesure où à chaque fois le système retourne un parcours semblable à celui qu'aurait proposé l'expert, nous sommes confortées dans notre approche.

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A forensic intelligence process was conducted over cross-border seizures of false identity documents whose sources were partly known to be the same. Visual features of 300 counterfeit Portuguese and French identity cards seized in France and Switzerland were observed and integrated in a structured database developed to detect and analyze forensic links. Based on a few batches of documents known to come from common sources, the forensic profiling method could be validated and its performance evaluated. The method also proved efficient and complementary to conventional means of detecting connections between cases. Cross-border links were detected, highlighting the need for more collaboration. Forensic intelligence could be produced, uncovering the structure of counterfeits' illegal trade, the concentration of their sources and the evolution of their quality over time. In addition, two case examples illustrated how forensic profiling may support specific investigations. The forensic intelligence process and its results will underline the need to develop such approaches to support the fight against fraudulent documents and organized crime.

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Activation of the peroxisome proliferator-activated receptor (PPAR)-alpha increases lipid catabolism and lowers the concentration of circulating lipid, but its role in the control of glucose metabolism is not as clearly established. Here we compared PPARalpha knockout mice with wild type and confirmed that the former developed hypoglycemia during fasting. This was associated with only a slight increase in insulin sensitivity but a dramatic increase in whole-body and adipose tissue glucose use rates in the fasting state. The white sc and visceral fat depots were larger due to an increase in the size and number of adipocytes, and their level of GLUT4 expression was higher and no longer regulated by the fed-to-fast transition. To evaluate whether these adipocyte deregulations were secondary to the absence of PPARalpha from liver, we reexpresssed this transcription factor in the liver of knockout mice using recombinant adenoviruses. Whereas more than 90% of the hepatocytes were infected and PPARalpha expression was restored to normal levels, the whole-body glucose use rate remained elevated. Next, to evaluate whether brain PPARalpha could affect glucose homeostasis, we activated brain PPARalpha in wild-type mice by infusing WY14643 into the lateral ventricle and showed that whole-body glucose use was reduced. Hence, our data show that PPARalpha is involved in the regulation of glucose homeostasis, insulin sensitivity, fat accumulation, and adipose tissue glucose use by a mechanism that does not require PPARalpha expression in the liver. By contrast, activation of PPARalpha in the brain stimulates peripheral glucose use. This suggests that the alteration in adipocyte glucose metabolism in the knockout mice may result from the absence of PPARalpha in the brain.

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Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.

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OBJECTIVE: Little is known about the influence of different training types on relative fat mobilization with exercise. The purpose of this study was to analyze the changes induced by aerobic training (AT), resistance (RT) or a combination of both (AT+RT) on total fat mass (TFM) and regional fat mass (RFM). Further, the relative contribution of different regions, upper limbs (UL), lower limbs (LL), and trunk (Tr), were compared. DESIGN AND METHODS: Forty-five overweight and premenopausal women were randomized in either AT, RT or AT+RT. All training groups exercised for the same duration (60 min), 3 times per week for 5 months. Body composition was estimated using dual energy X-ray absorptiometry. RESULTS: TFM decreased significantly in all groups (-4.6 ± 1.9 kg; -3.8 ± 2.6 kg, and -4.7 ± 3.0 kg in AT, RT, and AT+RT groups respectively; P < 0.001). The relative contribution of FM into each segment changed significantly: TrFM represented 46.6% ± 5.8% of TFM at baseline and reduced to 43.1% ± 5.5% (P < 0.001); LLFM was 39.7% ± 5.8% vs. 41.6% ± 5.7% (P < 0.01); ULFM was 11.3% ± 1.3% vs. 12.2% ± 1.4% (P < 0.01). CONCLUSION: Training type did not influence changes of TFM and RFM. Fat mobilization came predominantly from Tr in all training protocols. These findings suggest that overweight and obese women can reduce TFM and RFM, independently of training type.

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OBJECTIVES: A lipidomic approach was employed in a clinically well-defined cohort of healthy obese women to explore blood lipidome phenotype ascribed to body fat deposition, with emphasis on epicardial adipose tissue (EAT). METHODS: The present investigation delivered a lipidomics signature of epicardial adiposity under healthy clinical conditions using a cohort of 40 obese females (age: 25-45 years, BMI: 28-40 kg/m(2) ) not showing any metabolic disease traits. Lipidomics analysis of blood plasma was employed in combination with in vivo quantitation of mediastinal fat depots by computerized tomography. RESULTS: All cardiac fat depots correlated to indicators of hepatic dysfunctions (ALAT and ASAT), which describe physiological connections between hepatic and cardiac steatosis. Plasma lipidomics encompassed overall levels of lipid classes, fatty acid profiles, and individual lipid species. EAT and visceral fat associated with diacylglycerols (DAG), triglycerides, and distinct phospholipid and sphingolipid species. A pattern of DAG and phosphoglycerols was specific to EAT. CONCLUSIONS: Human blood plasma lipidomics appears to be a promising clinical and potentially diagnostic readout for patient stratification and monitoring. Association of blood lipidomics signature to regio-specific mediastinal and visceral adiposity under healthy clinical conditions may help provide more biological insights into obese patient stratification for cardiovascular disease risks.