The application of stem cell therapy and brown adipose tissue transplantation in metabolic disorders

The discovery of brown fat in adult humans has led to increased research of the thermogenic function of this tissue in various metabolic diseases. In addition, high levels of brown fat have been correlated with lower body mass index values. Therefore, increasing brown fat mass and/or activity through methods such as the browning of white fat is considered a promising strategy to prevent and treat obesity-associated diseases. Cell-based approaches using mesenchymal stromal cells and brown adipose tissue (BAT) have been utilized to directly increase BAT mass/activity through cell and tissue implantation into animals. In addition, recent studies evaluating the transplantation of human embryonic stem cells and induced pluripotent stem (iPS) cells have shown promising results in terms of positive metabolic function. In this comprehensive review, we provide a summary of the research over the past 10 years with regard to stem cell therapy and brown fat tissue transplantation for the effective treatment of metabolic syndrome. Recent advancements in stem cell methods have allowed for the production of brown adipocytes from human iPS cells, which represent an unlimited source of cellular material with which to study adipocyte development. In addition, this process is expected to be used to further explore drug- and cell-based therapies to treat obesity-related metabolic complications.     

Allometric estimation of metabolic rates in animals

The relationship between body mass (M) and metabolic rate (MR) typically accounts for most (>90%) of the inter-specific variation in MR. As such, when measurement of a species of interest is not possible, its MR can often be predicted using M. However, choosing an appropriate relationship to make such predictions is critical, and the choice is complicated by ongoing debate about the structure of the relationship between M and MR. The present study examines a range of methods including ordinary least squares (OLS), reduced major axis (RMA), and phylogenetically-informed (PI) approaches for estimating log(MR) from log(M), as well as non-linear approaches for estimating the relationship between MR and M without the need for log-transformation. Using data for the basal metabolic rates of mammals, it is shown that RMA regression overestimates the scaling exponent of MR (b, where MR=aM(b)), suggesting that OLS regression is appropriate for these data. PI approaches are preferred over non-PI ones, and the best estimates of log(MR) are obtained by including information on body temperature, climate, habitat, island endemism, and use of torpor in addition to log(M). However, the use of log-transformed data introduces bias into estimates of MR, while the use of non-linear regression underestimates MR for small mammals. This suggests that no single relationship is appropriate for describing the relationship between MR and M for all mammals, and that relationships for more narrow taxonomic groups or body mass ranges should be used when predicting MR from M.     

Proteomic advances in salivary diagnostics

Saliva is identified as functional equivalent to serum, reflecting the physiological state of the body, as well as hormonal, emotional, nutritional and metabolic alterations. The application of mass spectrometry based approaches has allowed a thorough characterization of the saliva proteome and led to the discovery of putative biomarkers. Several salivary biomarkers have been recently explored as potentially useful screening tools in patients diagnosed with metabolic disorders. In this review, we provide an overview of saliva proteomics studies, with a focus on diabetes, and we explore the evidence for the utility of well identified markers for the diagnosis and monitoring of the disease. Emerging approaches in salivary diagnostics that may significantly advance the field of diabetes research are also highlighted.     

A Comparison of Dual-Energy X-Ray Absorptiometry and Somatometrics for Determining Body Fat in Rhesus Macaques

COLMAN, RICKI J., JOHN C. HUDSON, HOWARD S. BARDEN, AND JOSEPH W. KEMNITZ. A comparison of dual-energy X-ray absorptiometry and somatometrics for determining body fat in rhesus macaques. Obes Res. 1999; 7:90–96. Objective : Various approaches have been used to assess fat and fat distribution in nonhuman primates, including measurements of body weight, body dimensions, and estimates derived from these, such as body mass index. Methods such as tritiated water dilution and dual-energy X-ray absorptiometry (DXA) have also been used. The aim of the present study was to evaluate and compare DXA measurements and somatometrics. Research Methods and Procedures : Body composition of 15 adult male rhesus macaques was measured by DXA and somatometrics at four time-points over a 4-year period. Additionally, DXA precision and somatometric variability were analyzed by repeated measurements of the same subjects. Results : DXA estimates of body fat were positively correlated with body weight, body mass index, body circumferences, and abdominal skinfold thicknesses. DXA assessments of soft tissue composition were precise, with coefficients of variation below 3.3% for all compartments analyzed. The majority of the observed variability in somatometrics was explained by subject variance, rather than by inter- or intraobserver variability, or by observer experience level. Discussion : We conclude that noninvasive DXA technology provides precise estimates of nonhuman primate body composition that correlate well with the traditional somatometric measures used in primate studies.     

Disentangling plastic and genetic changes in body mass of Siberian jays

Spatial and temporal phenotypic differentiation in mean body size is of commonplace occurrence, but the underlying causes remain often unclear: both genetic differentiation in response to selection (or drift) and environmentally induced plasticity can create similar phenotypic patterns. Studying changes in body mass in Siberian jays (Perisoreus infaustus) over three decades, we discovered that mean body mass declined drastically (ca. 10%) over the first two decades, but increased markedly thereafter back to almost the initial level. Quantitative genetic analyses revealed that although body mass was heritable (h² = 0.46), the pronounced temporal decrease in body mass was mainly a product of phenotypic plasticity. However, a concomitant and statistically significant decrease in predicted breeding values suggests a genetic component to this change. The subsequent increase in mean body mass was indicated to be entirely due to plasticity. Selection on body mass was estimated to be too weak to fully account for the observed genetic decline in body mass, but bias in selection differential estimates due to environmental covariance between body mass and fitness is possible. Hence, the observed body mass changes appear to be driven mainly by phenotypic plasticity. Although we were not able to identify the ecological driver of the observed plastic changes, the results highlight the utility of quantitative genetic approaches in disentangling genetic and phenotypic changes in natural populations.     

The starvation-predation trade-off predicts trends in body size, muscularity, and adiposity between and within Taxa

The storage of lipids to buffer energy shortage may incur such costs as increased vulnerability to predation, and animals may be more muscular in order to reduce such costs. If muscle and lipid mass interact to determine survival, then both the muscularity and the adiposity of animals will be affected by factors such as predator density and food availability. Here we explore how adiposity and muscularity may depend on such factors. We confirm the expectation that adiposity should decrease with the risk of predation and increase with the frequency of interruptions to the food supply. More surprisingly, the predicted relationships between skeletal size, muscularity, and adiposity qualitatively depended on various factors: for example, adiposity should increase with foraging costs only for small animals and should decrease with total body mass if competition for food is intense. Furthermore, if the locomotive costs of carrying lipids are low, then adiposity should increase with body mass, whereas if such costs are high, then adiposity should decrease with body mass. These predictions are supported by observations of variation between and within species. Our approach demonstrates that broad patterns of body composition can be understood in terms of the fundamental ecological trade-off between starvation and predation.     

Influence of body composition on physical activity validation studies using doubly labeled water.

This study investigated the influence of two approaches (mathematical transformation and statistical procedures), used to account for body composition [body mass or fat-free mass (FFM)], on associations between two measures of physical activity and energy expenditure determined by doubly labeled water (DLW). Complete data for these analyses were available for 136 African American (44.1%) and Hispanic (55.9%) women (mean age 50 +/- 7.3 yr). Total energy expenditure (TEE) by DLW was measured over 14 days. Physical activity energy expenditure (PAEE) was computed as 0.90 x TEE - resting metabolic rate. During week 2, participants wore an accelerometer for 7 consecutive days and completed a 7-day diary. Pearson's product-moment correlations and three statistical procedures (multiple regressions, partial correlations, and allometric scaling) were used to assess the effect of body composition on associations. The methods-comparison analysis was used to study the effect of body composition on agreement. The statistical procedures demonstrated that associations improved when body composition was included in the model. The accelerometer explained a small but meaningful portion of the variance in TEE and PAEE after body mass was accounted for. The methods-comparison analysis confirmed that agreement with DLW was affected by the transformation. Agreement between the diary (transformed with body mass) and TEE reflected the association that exists between body mass and TEE. These results suggest that the accelerometer and diary accounted for a small portion of TEE and PAEE. Most of the variance in DLW-measured energy expenditure was explained by body mass or FFM.     

De novo peptide sequencing and identification with precision mass spectrometry

The recent proliferation of novel mass spectrometers such as Fourier transform, QTOF, and OrbiTrap marks a transition into the era of precision mass spectrometry, providing a 2 orders of magnitude boost to the mass resolution, as compared to low-precision ion-trap detectors. We investigate peptide de novo sequencing by precision mass spectrometry and explore some of the differences when compared to analysis of low-precision data. We demonstrate how the dramatically improved performance of de novo sequencing with precision mass spectrometry paves the way for novel approaches to peptide identification that are based on direct sequence lookups, rather than comparisons of spectra to a database. With the direct sequence lookup, it is not only possible to search a database very efficiently, but also to use the database in novel ways, such as searching for products of alternative splicing or products of fusion proteins in cancer. Our de novo sequencing software is available for download at http://peptide.ucsd.edu/.     

Diurnal patterns of body mass change during stopover in a migrating songbird,the northern wheatear Oenanthe oenanthe

In migrating birds body mass change during stopover is often used to evaluate the quality of a stopover site. Because such body mass changes are difficult to survey in migrating birds various methods were developed to allow the analysis of larger sample sizes. In this article we present patterns of repeated body mass measurements of individual birds and the commonly used method of plotting body mass over time of day of birds being trapped only once. We repeatedly measured body mass of 89 northern wheatears Oenanthe oenanthe, when stopping over at a small island in the North Sea. A balance beneath bowls offering mealworms ad libitum was used to weigh their body mass several times per day. From these repeated body mass measurements we have generated a general model of daily mass gain patterns and nocturnal mass loss. Daily body mass changes followed in general an asymptotic curve progression with highest gain rates in the morning hours. During night birds lost about 5% of the evening body mass irrespectively of local wind force, temperature, night length or precipitation. By plotting first traps by time of day no such pattern in body mass increase was evident. Even in a simulated situation with repeatedly measured birds increasing their body mass, no such body mass increase could be shown when plotting one randomly chosen measurement of each bird per day. This “first‐traps‐by‐time‐of‐day‐method” depends highly on sample size, overall mass increase and the mass variation between individuals and will produce a traceable body mass increase only under certain circumstances.     

Robust analysis with related samples under the presence of population substructure and its application to body mass index

Recent investigations such as a more powerful quasi-likelihoods score test (MQLS) statistic have enabled the efficient association analysis with related samples. Although those approaches are robust against the mis-specified phenotypic distribution and covariance structure, it has been shown that MQLS statistic becomes violated under the presence of the population substructure if the level of population substructure depends on the genomic location. In this report, we propose a new statistical method which combines EIGENSTRAT approach and MQLS-statistic. The proposed method was evaluated with simulation data under various scenarios and we found that proposed method performs better than the traditional methods such as transmission disequilibrium test. The proposed method was applied to genetic association analysis for body mass index with Framingham heart study, and we found that rs1121980 and rs9940128 in the linkage block in FTO gene are associated with the body mass index.     

Evolutionary dynamics of vertebrate body mass range

Change in body mass with time has been considered for many clades, often with reference to Cope's rule, which predicts a tendency to increase in body size. A more general rule, namely increase in the range of body mass with time, is analyzed here for vertebrates. The log range of log vertebrate body mass is shown to increase linearly and highly significantly with the log of duration of clade existence. The resulting regression equations are used to predict the origin age, initial body mass, and subsequent dynamics of body mass range for primate clades such as the New World monkeys (Platyrrhini, 32 million years ago, initial mass of 1.7 kg) and the Anthropoidea (57 million years ago, initial mass of 0.12 kg), tested against the primate fossil record. Using these methods, other major primate clades such as Lemuriformes and Adapoidea are also estimated to have originated in the Tertiary (63 and 64 million years ago, respectively), with only the Plesiadapiformes originating in the Cretaceous (83 million years ago). Similarities of body mass range between primate and other vertebrate sister groups are discussed. Linear relationships of log range and log duration are considered with respect to Brownian processes, with the expected regression coefficients from the latter explored through simulations. The observed data produce regression coefficients that overlap with or are higher than those under Brownian processes. Overall, the analyses suggest the dynamics of vertebrate body mass range in morphologically disparate clades are highly predictable over many tens of million years and that the dynamics of phenotypic characteristics can assist molecular clock and fossil models in dating evolutionary events.     

Why elephant have trunks and giraffe long tongues: how plants shape large herbivore mouth morphology

We investigated whether mass and morphological spatial patterns in plants possibly induced the development of enlarged soft mouth parts in especially megaherbivores. We used power functions and geometric principles to explore allometric relationships of both morphological and foraging characteristics of mammalian herbivores in the South African savannah, covering a body size range of more than three orders magnitude. Our results show that, although intradental mouth volume scaled to a power slightly less than one to body mass, actual bite volume, as measured in the field, scaled to body mass with a factor closer to 1.75. However, when including the volume added to intradental mouth volume by soft mouth parts, such as tongue and lips (or trunks in elephant), mouth volume scaled linearly with actual bite volume and in a similar fashion as actual bite volume to body size. Bite mass and bite leaf mass scaled linearly with body size. We conclude that these scaling relationships indicate that large herbivores use their enlarged soft mouth parts to not only increase bite volume and thereby bite mass, but also select soft plant parts and thereby increase the leaf mass fraction per bite.     

Lack of correlation between body mass and metabolic rate in Drosophila melanogaster

We examined the association between body mass and metabolic rate in Drosophila melanogaster under a variety of conditions. These included comparisons of body mass and metabolic rate in flies from different laboratory lines measured at different ages, over different metabolic sampling periods, and comparisons using wet versus dry mass data. In addition, the relationship between body mass and metabolic rate was determined for flies recently collected from wild populations. In no case was there a significant correlation between body mass and metabolic rate. These results indicate that care must be taken when attempting to account for the effects of body mass on metabolic rate. Expressing such data in mass-specific units may be an inappropriate method of attempting to control for the effects of differences in body mass.     

Exploring macroevolution using modern and fossil data

Macroevolution, encompassing the deep-time patterns of the origins of modern biodiversity, has been discussed in many contexts. Non-Darwinian models such as macromutations have been proposed as a means of bridging seemingly large gaps in knowledge, or as a means to explain the origin of exquisitely adapted body plans. However, such gaps can be spanned by new fossil finds, and complex, integrated organisms can be shown to have evolved piecemeal. For example, the fossil record between dinosaurs and Archaeopteryx has now filled up with astonishing fossil intermediates that show how the unique plexus of avian adaptations emerged step by step over 60 Myr. New numerical approaches to morphometrics and phylogenetic comparative methods allow palaeontologists and biologists to work together on deep-time questions of evolution, to explore how diversity, morphology and function have changed through time. Patterns are more complex than sometimes expected, with frequent decoupling of species diversity and morphological diversity, pointing to the need for some new generalizations about the processes that lie behind such patterns.     

The use of biomarkers for improved retrospective exposure assessment in epidemiological studies: summary of an ECETOC workshop

During a scientific workshop the use of biological monitoring in characterization of retrospective exposure assessment was discussed. The workshop addressed currently available methodology and also novel approaches such as in different fields of ‘omics’. For use in epidemiology requiring retrospective exposure assessment, biomarker levels should not vary too much over time. If variability in exposure over time is large and differences in exposure between individuals are relatively small, this may lead to underestimation of the exposure–response relationship. This means that, for a sound assessment of health risk, biomarkers that reflect cumulative exposure over a long period of time are preferred over biomarkers with short half-lives. Most of the existing biomarkers such as metabolites in body fluids usually have rather short half-lives, typically less than 1–2 days. Some adducts to DNA show somewhat longer half-lives. The current limit to persistence of biomarkers reflecting cumulative exposure over time is from adducts to haemoglobin with a half-life of 4 months. Some specific organic substances may be more persistent due to storage in adipose tissue or metals in kidneys, nails and hair. The metabonomics, proteomics and present gene expression profiling approaches do not provide a perspective to the availability of more persistent biomarkers and most approaches discussed to date show that it is difficult to interpret study outcomes in terms of exposure to a specific xenobiotic factor. Research efforts should focus on improvement and validation of currently available approaches in the field of addition products to DNA and proteins. Promising new developments may be phosphotriester DNA adducts and adducts to more long-lived proteins such as histones.     

Mathematical Model for the Contribution of Individual Organs to Non-Zero Y-Intercepts in Single and Multi-Compartment Linear Models of Whole-Body Energy Expenditure

Mathematical models for the dependence of energy expenditure (EE) on body mass and composition are essential tools in metabolic phenotyping. EE scales over broad ranges of body mass as a non-linear allometric function. When considered within restricted ranges of body mass, however, allometric EE curves exhibit ‘local linearity.’ Indeed, modern EE analysis makes extensive use of linear models. Such models typically involve one or two body mass compartments (e.g., fat free mass and fat mass). Importantly, linear EE models typically involve a non-zero (usually positive) y-intercept term of uncertain origin, a recurring theme in discussions of EE analysis and a source of confounding in traditional ratio-based EE normalization. Emerging linear model approaches quantify whole-body resting EE (REE) in terms of individual organ masses (e.g., liver, kidneys, heart, brain). Proponents of individual organ REE modeling hypothesize that multi-organ linear models may eliminate non-zero y-intercepts. This could have advantages in adjusting REE for body mass and composition. Studies reveal that individual organ REE is an allometric function of total body mass. I exploit first-order Taylor linearization of individual organ REEs to model the manner in which individual organs contribute to whole-body REE and to the non-zero y-intercept in linear REE models. The model predicts that REE analysis at the individual organ-tissue level will not eliminate intercept terms. I demonstrate that the parameters of a linear EE equation can be transformed into the parameters of the underlying ‘latent’ allometric equation. This permits estimates of the allometric scaling of EE in a diverse variety of physiological states that are not represented in the allometric EE literature but are well represented by published linear EE analyses.     

Genetic Influences on Changes in Body Mass Index: A Longitudinal Analysis of Women Twins

AUSTIN, MELISSA A, YECHIEL FRIEDLANDER, BETH NEWMAN, KAREN EDWARDS, ELIZABETH J MAYER-DAVIS, MARY-CLAIRE KING. Genetic influences on changes in body mass index: a longitudinal analysis of women twins. Numerous studies have demonstrated genetic influences on body fat, but there also may be genetic effects on its intraindividual variation over time. This study examined changes in body mass index (BMI) using longitudinal data from two examinations of the Kaiser Permanente Women Twins Study, performed a decade apart. The analysis included 630 women, 185 monozygotic and 130 dizygotic twin pairs, with average ages of 41 years and 51 years at the two examinations, respectively. Age adjusted heritability estimates for the change in BMI over the decade ranged from 0.57 to 0.86 (all ρ≤0.001) using three different statistical analysis approaches, indicating that at least half, and possibly as much as 85%, of the variance in the change in BMI is attributable to genetic influences under a polygenic model. These estimates remained statistically significant after adjusting for environmental factors (ranging from 0.57 to 0.78) and with additional adjustment for BMI at baseline (ranging from 0.41 to 0.79), although dizygotic intraclass correlations were low after these adjustments. Thus, in addition to known environmental and behavioral influences, these results provide evidence for genetic influences on changes in BMI over a decade in women.     

渐变的光周期和温度对布氏田鼠能量代谢和身体成分的影响

为探讨在同时逐渐缩短光照时间和降低温度的过程中,动物能量代谢水平和身体成分的适应性变化, 我们以成年雄性布氏田鼠为对象, 测定了温度为20℃ 和光周期为12L:12D (对照组),以及从温度为20℃ 和长光照条件(16L:8D)逐渐转换到温度为4℃ 和短光照条件(8L:16D)的过程中(实验组), 其体重、静止代谢率和能量摄入的变化, 以及经过8 周驯化后身体器官和组织重量的变化。结果发现:实验组动物的体重增长率低于对照组。在驯化期间, 静止代谢率无组内和组间差异。实验组动物的干物质摄入、能量摄入和消化能等组内差异不明显, 但对照组动物在驯化的第8 周显著降低。实验组动物的能量摄入水平在驯化后显著升高;小肠和胃的干重, 以及小肠和心脏等器官的湿重也都显著高于对照组。结果表明,布氏田鼠能够采取降低体重、增加能量摄入和调整体内某些器官和组织重量的方式来适应变化的环境条件。     

A review on recent developments in mass spectrometry instrumentation and quantitative tools advancing bacterial proteomics

Proteomics has evolved substantially since its early days, some 20 years ago. In this mini-review, we aim to provide an overview of general methodologies and more recent developments in mass spectrometric approaches used for relative and absolute quantitation of proteins. Enhancement of sensitivity of the mass spectrometers as well as improved sample preparation and protein fractionation methods are resulting in a more comprehensive analysis of proteomes. We also document some upcoming trends for quantitative proteomics such as the use of label-free quantification methods. Hopefully, microbiologists will continue to explore proteomics as a tool in their research to understand the adaptation of microorganisms to their ever changing environment. We encourage them to incorporate some of the described new developments in mass spectrometry to facilitate their analyses and improve the general knowledge of the fascinating world of microorganisms.     

Within-family variation in obesity

We use data from the Children of the National Longitudinal Survey of Youth 1979 to document the degree to which childhood obesity varies among siblings. We find considerable differences in body weight between siblings with over half of the siblings differing by more than 20 age-specific percentiles in terms of the body mass index. Even among identical twins, there is an average BMI difference of 12 percentiles. This variation is important for the use of econometric approaches that involve sibling comparisons.