Estimation of visceral fat in 9- to 13-year-old girls using dual-energy X-ray absorptiometry (DXA) and anthropometry.

OBJECTIVES: Accumulation of visceral fat (VF) in children increases the risk of cardiovascular disease and type 2 diabetes, and measurement of VF in children using computed tomography and magnetic resonance imaging (MRI) is expensive. Dual-energy X-ray absorptiometry (DXA) may provide a low-cost alternative. This study aims to determine if DXA VF estimates can accurately estimate VF in young girls, determine if adding anthropometry would improve the estimate and determine if other DXA fat measures, with and without anthropometry, could be used to estimate VF in young girls. METHODS: Visceral fat was measured at lumbar intervertebral sites (L1-L2, L2-L3, L3-L4 and L4-L5) using 3.0T MRI on 32 young girls (mean age 11.3 ± 1.3 years). VF was estimated using the GE CoreScan application. Measurement of DXA android and total body fat was performed. Weight, height and waist circumference (WC) measurements were also obtained. RESULTS: Waist circumference and body mass index were both strongly correlated with MRI, although WC was the best anthropometric covariate. Per cent fat (%fat) variables had the strongest correlation and did best in regression models. DXA %VF (GE CoreScan) and DXA android %fat and total body %fat accounted for 65% to 74% of the variation in MRI VF. CONCLUSION: Waist circumference predicted MRI VF almost as well as DXA estimates in this population, and a combination of WC and DXA fat improves the predictability of VF. DXA VF estimate was improved by the addition of WC; however, DXA android %fat with WC was better at predicting MRI VF.

Dual energy X-ray absorptiometry spine scans to determine abdominal fat in postmenopausal women.

Body composition may be a better predictor of chronic disease risk than body mass index (BMI) in older populations. OBJECTIVES: We sought to validate spine fat fraction (%) from dual energy X-ray absorptiometry (DXA) spine scans as a proxy for total abdominal fat. METHODS: Total body DXA scan abdominal fat regions of interest (ROI) that have been previously validated by magnetic resonance imaging were assessed among healthy, postmenopausal women who also had antero-posterior spine scans (n = 103). ROIs were (1) lumbar vertebrae L2-L4 and (2) L2-Iliac Crest (L2-IC), manually selected by two independent raters, and (3) trunk, auto-selected by DXA software. Intra-class correlation coefficients evaluated intra and inter-rater reliability on a random subset (N = 25). Linear regression models, validated by bootstrapping, assessed the relationship between spine fat fraction (%) and total abdominal fat (%) ROIs. RESULTS: Mean age, BMI, and total body fat were 66.1 ± 4.8 y, 25.8 ± 3.8 kg/m2 and 40.0 ± 6.6%, respectively. There were no significant differences within or between raters. Linear regression models adjusted for several participant and scan characteristics were equivalent to using only BMI and spine fat fraction. The model predicted L2-L4 (Adj. R2 : 0.83) and L2-IC (Adj. R2 : 0.84) abdominal fat (%) well; the adjusted R2 for trunk fat (%) was 0.78. Model validation demonstrated minimal over-fitting (Adj. R2 : 0.82, 0.83, and 0.77 for L2-L4, L2-IC, and trunk fat, respectively). CONCLUSIONS: The strong correlation between spine fat fraction and DXA abdominal fat measures make it suitable for further development in postmenopausal chronic disease risk prediction models. Am. J. Hum. Biol. 28:918-926, 2016. © 2016Wiley Periodicals, Inc.

High genetic risk individuals benefit less from resistance exercise intervention.

OBJECTIVES: Genetic factors have an important role in body mass index (BMI) variation, and also likely have a role in the weight loss and body composition response to physical activity/exercise. With the recent identification of BMI-associated genetic variants, it is possible to investigate the interaction of these genetic factors with exercise on body composition outcomes. METHODS: In a block-randomized clinical trial of resistance exercise among women (n=148), we examined whether the putative effect of exercise on weight and dual-energy x-ray absorptiometry-derived body composition measurements differs according to genetic risk for obesity. Approximately one-half of the sample was randomized to an intervention consisting of a supervised, intensive, resistance exercise program, lasting 1 year. Genetic risk for obesity was defined as a genetic risk score (GRS) comprised of 21 single-nucleotide polymorphisms (SNPs) known to be associated with BMI variation. We examined the interaction of exercise intervention and the GRS on anthropometric and body composition measurements after 1 year of the exercise intervention. RESULTS: We found statistically significant interactions for body weight (P=0.01), body fat (P=0.01), body fat % (P=0.02) and abdominal fat (P=0.02), whereby the putative effect of exercise is greater among those with a lower level of genetic risk for obesity. No single SNP appears to be a major driver of these interactions. CONCLUSIONS: The weight-loss response to resistance exercise, including changes in body composition, differs according to an individual's genetic risk for obesity.

Muscle density predicts changes in bone density and strength: a prospective study in girls.

OBJECTIVE: We sought to determine whether muscle density, an index of skeletal muscle fat content, was predictive of 2-year changes in weight-bearing bone parameters in young girls. METHODS: Two-year prospective data from 248 girls, aged 8-13 years at baseline. Peripheral quantitative computed tomography was used to measure changes in bone strength indices (bone strength index [BSI, mg(2)/mm(4)] and strength-strain index [SSIp, mm(3)]) and volumetric bone mineral density [vBMD, mg/cm(3)] at distal metaphyseal and diaphyseal regions of the femur and tibia, as well as calf and thigh muscle density (mg/cm(3)), and muscle cross-sectional area (MCSA, mm(2)), indices of skeletal muscle fat content and muscle force production, respectively. RESULTS: After controlling for potential confounders, greater gains in femur BSI (44%, P<0.002), total femur vBMD (114%, P<0.04) and femur trabecular vBMD (306%, P<0.002) occurred in girls in the lowest versus the highest groups of baseline thigh muscle density. Greater gains in tibial BSI (25%, P<0.03) and trabecular vBMD (190%, P<0.002) were also observed in the lowest versus the highest baseline calf muscle density groups. CONCLUSION: Baseline muscle density is a significant predictor of changes in bone density and bone strength in young girls during a period of rapid skeletal development.

Associations of physical activity duration, frequency, and load with volumetric BMD, geometry, and bone strength in young girls.

SUMMARY: More efficacious physical activity (PA) prescriptions for optimal bone development are needed. This study showed that PA duration, frequency, and load were all independently associated with bone parameters in young girls. Increased PA duration, frequency, and load are all important osteogenic stimuli that should be incorporated into future PA interventions. INTRODUCTION: This study evaluated the associations of physical activity (PA) duration, frequency, load, and their interaction (total PA score = duration × frequency × load) with volumetric bone mineral density, geometry, and indices of bone strength in young girls. METHODS: Four hundred sixty-five girls (aged 8-13 years) completed a past year physical activity questionnaire (PYPAQ) which inquires about the frequency (days per week) and duration (average minutes per session) of leisure-time PA and sports. Load (peak strain score) values were assigned to each activity based on ground reaction forces. Peripheral quantitative computed tomography was used to assess bone parameters at metaphyseal and diaphyseal sites of the femur and tibia of the non-dominant leg. RESULTS: Correlations across all skeletal sites between PA duration, frequency, load and periosteal circumference (PC), bone strength index (BSI), and strength-strain index (SSI) were significant (p ≤ 0.05), although low (0.10-0.17). A 2.7-3.7% greater PC across all skeletal sites was associated with a high compared to a low PYPAQ score. Also, a high PYPAQ score was associated with greater BSI (6.5-8.7%) at metaphyseal sites and SSI (7.5-8.1%) at diaphyseal sites of the femur and tibia. The effect of a low PYPAQ score on bone geometric parameters and strength was greater than a high PYPAQ score. CONCLUSIONS: PA duration, frequency, and load were all associated with bone geometry and strength, although their independent influences were modest and site specific. Low levels of PA may compromise bone development whereas high levels have only a small benefit over more average levels.

Changes in soft tissue composition are the primary predictors of 4-year bone mineral density changes in postmenopausal women.

UNLABELLED: Changes in body weight influence bone mineral density, but the role of body composition is not clear in postmenopausal women. Body weight and soft tissue composition predicted bone changes independent of calcium supplementation and exercise frequency, indicating that soft tissue composition should be measured in clinical trials. INTRODUCTION: The purpose of this study was to examine the relationship between changes in body weight and composition and changes in 4-year bone mineral density (BMD) after accounting for age, 4-year exercise frequency (EX), and 4-year calcium supplement intake (CA) in postmenopausal women with and without hormone therapy (HT). METHODS: Postmenopausal women (aged 40-65 years) either using HT (for 1-3.9 years) or not using HT (for > or =1 year) were recruited to the study. EX and CA was monitored throughout the study and 167 women completed 4 years. BMD and soft tissue composition measurements were made using dual-energy X-ray absorptiometry. Regression was used to predict 4-year BMD changes from EX, CA, age, baseline and 4-year changes in body weight and composition. HT users (n = 115, 55.3 +/- 4.3 years) and non-users (n = 52, 57.5 +/- 4.7 years) were analyzed separately. RESULTS: The models predicting regional BMD changes that included soft tissue composition changes explained the most variation compared with those with body weight or EX and CA alone. Larger amounts of variation in BMD changes were explained in the no HT group. CONCLUSION: Body composition changes are important positive predictors of BMD changes independent of EX and CA supplementation, but their contribution varies according to bone site and with HT use.

Basal metabolic rate of Brazilians living in the Southwestern United States.

Estimation of energy requirements relies on adequate values of basal metabolic rate (BMR). Prediction equations recommended for international use have been shown to overestimate BMR in populations living in the tropics. We have previously shown the inadequacy of these equations in samples of Brazilians living in tropical and temperate regions of the country. We sought to investigate whether BMR could adequately be estimated by prediction equations in a sample of Brazilians living in a different setting: the Sonoran desert of the Southwestern USA. BMR was measured under standard conditions in 33 subjects (14 men). Mean bias (estimated-measured) varied from 404.4 to 708.6 kJ day(-1) in women and 566.8 to 1122.8 kJ day(-1) in men, representing 8.5-15 and 8.9-17.6% overestimation, respectively, using the Schofield equations. Bland and Altman analyses showed large, relevant limits of agreement. The results using the recommended equations for the American population (IOM, 2005) were only 2% different from the Schofield equations. The Harris and Benedict equations yielded higher overestimations (15.0 and 16.8% for women and men, respectively) and the Henry and Rees equations also overestimated BMR (8.5 and 8.9%) even though they were developed for populations from the tropics, although to a lesser degree. It is concluded that the equations currently recommended for international use are not appropriate for Brazilians living in the Southwestern USA.

Validation of bioelectrical impedance analysis (BIA) for estimation of body composition in Black, White and Hispanic adolescent girls.

AIM: Equations for estimating % fat mass (%BF) and fat-free mass (FFM) from bioelectrical impedance analysis (BIA) that work in adolescent girls from different racial/ethnic backgrounds are not available. We investigated whether race/ethnicity influences estimation of body composition in adolescent girls. PRINCIPAL PROCEDURES: Prediction equations were developed for estimating FFM and %BF from BIA in 166 girls, 10-15 years old, consisting of 51 Black (B), 45 non-Black Hispanic (H), 55 non-Hispanic White (W) and 15 mixed (M) race/ethnicity girls, using dual energy x-ray absorptiometry (DXA) as the criterion method. FINDINGS: Black girls had similar %BF compared to other groups, yet were heavier per unit of height according to body mass index (BMI: kg.m(-2)) due to significantly greater FFM. BIA resistance index, age, weight and race/ethnicity were all significant predictors of FFM (R(2) = 0.92, SEE = 1.81 kg). Standardized regression coefficients showed resistance index (0.63) and weight (0.34) were the most important predictors of FFM. Errors in %BF (~2%) and FFM (~1.0 kg) were greater when race/ethnicity was not included in the equation, particularly in Black girls. We conclude the BIA-composition relationship in adolescent girls is influenced by race, and consequently have developed new BIA equations for adolescent girls for predicting FFM and %BF.

A review of psychosocial pre-treatment predictors of weight control.

Prompted by the large heterogeneity of individual results in obesity treatment, many studies have attempted to predict weight outcomes from information collected from participants before they start the programme. Identifying significant predictors of weight loss outcomes is central to improving treatments for obesity, as it could help professionals focus efforts on those most likely to benefit, suggest supplementary or alternative treatments for those less likely to succeed, and help in matching individuals to different treatments. To date, however, research efforts have resulted in weak predictive models with limited practical usefulness. The two primary goals of this article are to review the best individual-level psychosocial pre-treatment predictors of short- and long-term (1 year or more) weight loss and to identify research needs and propose directions for further work in this area. Results from original studies published since 1995 show that few previous weight loss attempts and an autonomous, self-motivated cognitive style are the best prospective predictors of successful weight management. In the more obese samples, higher initial body mass index (BMI) may also be correlated with larger absolute weight losses. Several variables, including binge eating, eating disinhibition and restraint, and depression/mood clearly do not predict treatment outcomes, when assessed before treatment. Importantly, for a considerable number of psychosocial constructs (e.g. eating self-efficacy, body image, self-esteem, outcome expectancies, weight-specific quality of life and several variables related to exercise), evidence is suggestive but inconsistent or too scant for an informed conclusion to be drawn. Results are discussed in the context of past and present conceptual and methodological limitations, and several future research directions are described.

Pretreatment predictors of attrition and successful weight management in women.

OBJECTIVE: This study analyzed baseline behavioral and psychosocial differences between successful and nonsuccessful participants in a behavioral weight management program. Success was defined by commonly used health-related criteria (5% weight loss). Noncompletion was also used as a marker of a failed attempt at weight control. SUBJECTS: A total of 158 healthy overweight and obese women (age, 48.0+/-4.5 y; BMI, 31.0+/-3.8 kg/m(2); body fat, 44.5+/-5.3%). INTERVENTION: Subjects participated in a 16-week lifestyle weight loss program consisting of group-based behavior therapy to improve diet and increase physical activity, and were followed for 1 y after treatment. METHODS: At baseline, all women completed a comprehensive behavioral and psychosocial battery assessing dieting/weight history, dietary intake and eating behaviors, exercise, self-efficacy, outcome evaluations, body image, and other variables considered relevant for weight management. Participants who maintained a weight loss of 5% or more at 16 months (or 10% or more of initial fat mass) were classified as successful. Nonsuccessful participants were those who dropped out and completers who had not lost weight at follow-up. RESULTS: Of all participants, 30% (n=47) did not complete initial treatment and/or missed follow-up assessments (noncompleters). Noncompletion was independently associated with more previous weight loss attempts, poorer quality of life, more stringent weight outcome evaluations, and lower reported carbohydrate intake at baseline. In logistic regression, completion status was predicted correctly in 84% of all cases (chi(2)=45.5, P<0.001), using baseline information only. Additional predictors of attrition were initial weight, exercise minutes, fiber intake, binge eating, psychological health, and body image. A large variation in weight loss/maintenance results was observed (range: 37.2 kg for 16-month weight change). Independent baseline predictors of success at 16 months were more moderate weight outcome evaluations, lower level of previous dieting, higher exercise self-efficacy, and smaller waist-to-hip ratio. Success status at follow-up was predicted correctly in 74% of all starting cases (chi(2)=33.6, P<0.001). CONCLUSION: Psychosocial and behavioral variables (eg, dieting history, dietary intake, outcome evaluations, exercise self-efficacy, and quality of life) may be useful as pretreatment predictors of success level and/or attrition in previously overweight and mildly obese women who volunteer for behavioral weight control programs. These factors can be used in developing readiness profiles for weight management, a potentially important tool to address the issue of low success/completion rates in the current management of obesity.

Effects of exercise training on bone remodeling, insulin-like growth factors, and bone mineral density in postmenopausal women with and without hormone replacement therapy.

The purpose of this study was to determine the effects of 12 months of weight bearing and resistance exercise on bone mineral density (BMD) and bone remodeling (bone formation and bone resorption) in 2 groups of postmenopausal women either with or without hormone replacement therapy (HRT). Secondary aims were to characterize the changes in insulin-like growth factors-1 and -2 (IGF-1 and -2) and IGF binding protein 3 (IGFBP3) in response to exercise training. Women who were 3-10 years postmenopausal (aged 40-65 years) were included in the study. Women in the HRT and no HRT groups were randomized into the exercise intervention, resulting in four groups: (1) women not taking HRT, not exercising; (2) those taking HRT, not exercising; (3) those exercising, not taking HRT; and (4) women exercising, taking HRT. The number of subjects per group after 1 year was 27, 21, 25, and 17, respectively. HRT increased BMD at most sites whereas the combination of exercise and HRT produced increases in BMD greater than either treatment alone. Exercise training alone resulted in modest site-specific increases in BMD. Bone remodeling was suppressed in the groups taking HRT regardless of exercise status. The bone remodeling response to exercise training in women not taking HRT was not significantly different from those not exercising. However, the direction of change suggests an elevation in bone remodeling in response to exercise training, a phenomenon usually associated with bone loss. No training-induced differences in IGF-1, IGF-2, IGF-l:IGF-2 (IGF-1 : IGF-2), and IGFBP3 were detected.

Total and regional fat and serum cardiovascular disease risk factors in lean and obese children and adolescents.

OBJECTIVE: This study was conducted to evaluate the association of total and central adiposity with serum cardiovascular disease (CVD) risk factors in lean and obese Portuguese children and adolescents. RESEARCH METHODS AND PROCEDURES: A total of 87 girls (13.2 +/- 1.6 years old, 29.9 +/- 6.4% body fat [mean +/- SD]) and 72 boys (13.2 +/- 1.6 years old, 20.8 +/- 9.9% body fat) volunteered for the study. Whole-body composition and fat distribution, from DXA and anthropometry, and serum lipids, lipoproteins, and apolipoproteins were evaluated. RESULTS: The sum of three trunk skinfolds (STS) was highly correlated with total trunk fat mass measured by DXA (p < 0.001). Body mass index, DXA-measured percentage of body fat, trunk fat mass, STS, and the waist-to-height ratio were generally found to be associated with triacylglycerol, the ratio of total cholesterol (TC) to high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), and apolipoprotein B levels, (significant age-adjusted r between 0.16 and 0.27, p < 0.05). Body mass index, STS, and the waist circumference were also associated with HDL-C (p < 0.05), whereas no body composition variable significantly correlated with TC or apolipoproteins A-I. The STS was significantly correlated with HDL-C (p < 0.01), TC/HDL-C (p < 0.05), and apolipoproteins A-I (p < 0.05) independently of whole-body fatness. Obese subjects (n = 73) had higher TC, LDL-C, TC/HDL-C, and apolipoprotein B than did non-obese subjects (n = 86), and significant associations between central adiposity and some lipid variables (triacylglycerol and HDL-C) were found in obese children and adolescents that were not present in leaner individuals. DISCUSSION: DXA- and anthropometry-based whole-body and central fat measures are associated with serum CVD risk factors in Portuguese boys and girls. Obese children and adolescents have a poorer lipid profile than do their leaner counterparts. Trunk skinfolds, which are easy to obtain even in large samples, predict CVD risk factors to the same extent as DXA-based variables, in some cases, independently of total fatness.

E. coli Rep oligomers are required to initiate DNA unwinding in vitro.

E. coli Rep protein is a 3' to 5' SF1 superfamily DNA helicase which is monomeric in the absence of DNA, but can dimerize upon binding either single-stranded or duplex DNA. A variety of biochemical studies have led to proposals that Rep dimerization is important for its helicase activity; however, recent structural studies of Bacillus stearothermophilus PcrA have led to suggestions that SF1 helicases, such as E. coli Rep and E. coli UvrD, function as monomeric helicases. We have examined the question of whether Rep oligomerization is important for its DNA helicase activity using pre-steady state stopped-flow and chemical quenched-flow kinetic studies of Rep-catalyzed DNA unwinding. The results from four independent experiments demonstrate that Rep oligomerization is required for initiation of DNA helicase activity in vitro. No DNA unwinding is observed when only a Rep monomer is bound to the DNA substrate, even when fluorescent DNA substrates are used that can detect partial unwinding of the first few base-pairs at the ss-ds-DNA junction. In fact, under these conditions, ATP hydrolysis causes dissociation of the Rep monomer from the DNA, rather than DNA unwinding. These studies demonstrate that wild-type Rep monomers are unable to initiate DNA unwinding in vitro, and that oligomerization is required.

Body composition profiles of elite American heptathletes.

This study characterized body composition profiles of elite American heptathletes and cross-validated skinfold (SKF) and bioelectrical impedance analysis (BIA) field method equations for estimation of percent body fat (%Fat) using dual energy x-ray absorptiometry (DXA) as the criterion. Weight, height, fat mass (FM), fat-free mass (FFM), bone mineral density (BMD), and %Fat were measured in 19 heptathletes using standard measurement protocols for DXA, SKFs and BIA. The ages, heights, and weights were respectively 25.5 +/- 3.5 years, 175.0 +/- 6.6 cm, 67.3 +/- 7.1 kg. DXA estimates of mean +/- SD values for body composition variables were 57.2 +/- 6.1 kg FFM, 10.1 +/- 2.6 kg FM, 114 +/- 7% BMD for age/racial reference group, and 15 +/- 3.0 %Fat. Ranges of bias values for %Fat (DXA minus SKF or BIA) were, respectively, -0.5 to 1.6% and -5.5 to -1.2%. Ranges for standard errors of estimate and total errors were, respectively, SKF 2.4-2.5%, 2.4 - 2.8% and BIA 3.0%, 5.0-6.5%. Regression analyses of the field methods on DXA were significant (p < .05) for all SKF equations but not BIA equations. This study demonstrates that elite American heptathletes are lean, have high levels of BMD, and that SKF equations provide more accurate estimates of %Fat relative to DXA than estimates from BIA equations.

Subcutaneous central fat is associated with cardiovascular risk factors in men independently of total fatness and fitness.

The purpose of this study was to analyze the single and independent associations of whole body composition and fat distribution with cardiovascular disease (CVD) risk factors and fitness in middle-aged men. Sixty-two healthy Caucasian men (37.6 +/- 2.9 yr, 81.8 +/- 11.3 kg, 171.5 +/- 4.9 cm) participated in the study. Dual-energy x-ray absorptiometry (DXA) was used to assess total and regional body composition. The triceps, biceps, midthigh, calf, subscapular, chest, abdominal and suprailiac skinfolds, and the waist, hip and midthigh circumferences, and sagittal diameter were estimated. Cardiovascular fitness was estimated with a submaximal test. Bivariate and partial correlation analysis were used to study the association of total body percent fat (%fat), DXA trunk fat and trunk skinfolds (sum of subscapular, chest, abdominal, and suprailiac) and fitness with insulin, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), TC/HDL-C, low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoprotein AI (apo AI), apolipoprotein B (apo B), lipoprotein(a) [Lp(a)], and diastolic and systolic blood pressure. All anthropometric and DXA body composition variables were significantly correlated with TC/HDL-C (from .26 to .50, P < .05). Similar relationships were found for insulin, HDL-C, and systolic blood pressure (r from .26 to .47, P < .05). Cardiovascular fitness was significantly (P < .05) associated with insulin (r = -.36), HDL-C (r = .27), TC/HDL (r = -.27), and with systolic blood pressure (r = -.37). After controlling for trunk skinfolds, none of the anthropometric and DXA body composition variables were correlated with any of the CVD risk factors. Similarly, when controlling for trunk skinfolds, cardiovascular fitness was not related to any of the metabolic variables. After adjusting for %fat, DXA trunk fat, and cardiovascular fitness, trunk skinfolds remained significantly (P < .05) related to insulin (r = .35), HDL-C (r = -.40), TC/HDL-C (r = .43), and apo AI (r = -.39). In conclusion, this study suggests that subcutaneous truncal fat, as estimated by skinfolds, is an independent predictor of CVD risk factors, and that the association between cardiovascular fitness and these risk factors may be mediated by the levels of abdominal subcutaneous fat in Caucasian middle-aged men.

Large contributions of coupled protonation equilibria to the observed enthalpy and heat capacity changes for ssDNA binding to Escherichia coli SSB protein.

Many macromolecular interactions, including protein-nucleic acid interactions, are accompanied by a substantial negative heat capacity change, the molecular origins of which have generated substantial interest. We have shown previously that temperature-dependent unstacking of the bases within oligo(dA) upon binding to the Escherichia coli SSB tetramer dominates the binding enthalpy, DeltaH(obs), and accounts for as much as a half of the observed heat capacity change, DeltaC(p). However, there is still a substantial DeltaC(p) associated with SSB binding to ssDNA, such as oligo(dT), that does not undergo substantial base stacking. In an attempt to determine the origins of this heat capacity change, we have examined by isothermal titration calorimetry (ITC) the equilibrium binding of dT(pT)(34) to SSB over a broad pH range (pH 5. 0-10.0) at 0.02 M, 0.2 M NaCl and 1 M NaCl (25 degrees C), and as a function of temperature at pH 8.1. A net protonation of the SSB protein occurs upon dT(pT)(34) binding over this entire pH range, with contributions from at least three sets of protonation sites (pK(a1) = 5.9-6.6, pK(a2) = 8.2-8.4, and pK(a3) = 10.2-10.3) and these protonation equilibria contribute substantially to the observed DeltaH and DeltaC(p) for the SSB-dT(pT)(34) interaction. The contribution of this coupled protonation ( approximately -260 to -320 cal mol(-1) K(-1)) accounts for as much as half of the total DeltaC(p). The values of the "intrinsic" DeltaC(p,0) range from -210 +/- 33 cal mol(-1) degrees K(-1) to -237 +/- 36 cal mol(-1)K(-1), independent of [NaCl]. These results indicate that the coupling of a temperature-dependent protonation equilibria to a macromolecular interaction can result in a large negative DeltaC(p), and this finding needs to be considered in interpretations of the molecular origins of heat capacity changes associated with ligand-macromolecular interactions, as well as protein folding.

Structure of the DNA binding domain of E. coli SSB bound to ssDNA.

The structure of the homotetrameric DNA binding domain of the single stranded DNA binding protein from Escherichia coli (Eco SSB) bound to two 35-mer single stranded DNAs was determined to a resolution of 2.8 A. This structure describes the vast network of interactions that results in the extensive wrapping of single stranded DNA around the SSB tetramer and suggests a structural basis for its various binding modes.

Comparison of methods for assessing body-composition changes over 1 y in postmenopausal women.

BACKGROUND: Advances in dual-energy X-ray absorptiometry (DXA) software algorithms have improved the accuracy of this method for body-composition measurement. OBJECTIVE: Our objective was to compare the utility of DXA, underwater weighing (UWW), and a multicomponent model (MC) for assessing changes in body composition. DESIGN: : Previously sedentary women aged 40-66 y were randomly assigned to exercise training (ET; n = 36) and no exercise training (NT; n = 40). ET subjects exercised 3 d/wk; NT subjects remained sedentary. Changes in body mass, fat mass, and fat-free mass over 1 y were assessed by the 3 methods. RESULTS: Correlations among methods were significant and large (0.73-0.97). Body weight did not change significantly in either group. In the ET group, fat-free mass increased significantly as assessed by DXA (0.7 +/- 1.0 kg) but changes assessed by MC and UWW were not significant. Changes in fat mass and percentage body fat in the ET group were not significant. SDs for changes in fat mass and percentage body fat, respectively, from DXA were 2.5 kg and 2.7%; for MC, 5.5 kg and 7.1%; and for UWW, 4.4 kg and 5.8%. In the NT group, changes in fat-free mass, fat mass, and percentage body fat were significant (P

Estimation of body fat from anthropometry and bioelectrical impedance in Native American children.

OBJECTIVE: Obesity, as measured by body mass index, is highly prevalent in Native American children, yet there are no valid equations to estimate total body fatness for this population. This study was designed to develop equations to estimate percentage body fat from anthropometry and bioelectrical impedance as a critical part of Pathways, a multi-site study of primary prevention of obesity in Native American children. DESIGN: Percentage fat was estimated from deuterium oxide dilution in 98 Native American children (Pima/Maricopa, Tohono O'odham and White Mountain Apache tribes) between 8 and 11 y of age. The mean fat content (38.4%+/-8. 1%) was calculated assuming the water content of the fat-free body was 76%. Initial independent variables were height, weight, waist circumference, six skinfolds and whole-body resistance and reactance from bioelectrical impedance (BIA). RESULTS: Using all-possible-subsets regressions with the Mallows C (p) criterion, and with age and sex included in each regression model, waist circumference, calf and biceps skinfolds contributed least to the multiple regression analysis. The combination of weight, two skinfolds (any two out of the four best: triceps, suprailiac, subscapular and abdomen) and bioelectrical impedance variables provided excellent predictability. Equations without BIA variables yielded r2 almost as high as those with BIA variables. The recommended equation predicts percentage fat with a root mean square error=3.2% fat and an adjusted r2=0.840. CONCLUSION: The combination of anthropometry and BIA variables can be used to estimate total body fat in field studies of Native American children. The derived equation yields considerably higher percentage fat values than other skinfold equations in children.