No apparent progress in bioelectrical impedance accuracy: validation against metabolic risk and DXA

Bioelectrical impedance (BIA) is quick, easy, and safe when quantifying fat and lean tissue. New BIA models (Tanita BC-418 MA, abbreviated BIA(8)) can perform segmental body composition analysis, e.g., estimate %trunkal fatness (%TF). It is not known, however, whether new BIA models can detect metabolic risk factors (MRFs) better than older models (Tanita TBF-300, abbreviated BIA(4)). We therefore tested the correlation between MRF and percentage whole-body fat (%BF) from BIA(4) and BIA(8) and compared these with the correlation between MRF and dual-energy X-ray absorptiometry (DXA, used as gold standard), BMI and waist circumference (WC). The sample consisted of 136 abdominally obese (WC >or= 88 cm), middle-aged (30-60 years) women. MRF included fasting blood glucose and insulin; high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides; high sensitive C-reactive protein, plasminogen activator inhibitor-1 (PAI-1), and fibrinogen; and alanine transaminase (ALT) liver enzyme. We found that similar to DXA, but in contrast to BMI, neither %BF BIA(4) nor %BF BIA(8) correlated with blood lipids or ALT. In the segmental analysis of %TF, BIA(8) only correlated with inflammatory markers, but not insulin, blood lipids, or ALT liver enzyme (in contrast to WC and %TF DXA). %TF DXA was associated with homeostatic model assessment insulin resistance (HOMA-IR) independently of WC (P = 0.03), whereas %TF BIA(8) was not (P = 0.53). Receiver-operating characteristic (ROC) curves confirmed that %TF BIA(8) did not differ from chance in the detection of insulin resistance (P = 0.26). BIA estimates of fatness were, at best, weakly correlated with obesity-related risk factors in abdominally obese women, even the new eight-electrode model. Our data support the continued use of WC and BMI.     

生物分子相互作用分析技术应用实例（三）——药物筛选和鉴定

美国Schering-Plough公司利用BIA技术成功地进行了药物筛选.他们选用抑制法从大量合成和天然小分子物文库中筛选细胞因子拮抗物.     

The role of proteomics in toxicology: identification of biomarkers of toxicity by protein expression analysis

Proteomics, i.e. the high throughput separation, display and identification of proteins, has the potential to be a powerful tool in drug development. It could increase the predictability of early drug development and identify non-invasive biomarkers of toxicity or efficacy. This review provides an introduction to modern proteomics, with particular reference to applications in toxicology. A literature search was carried out to identify studies in two broad classes: screening/predictive toxicology, and mechanistic toxicology. The strengths and limitations of current methods and the likely impact of techniques in drug development are also considered. Proteomics can increase the speed and sensitivity of toxicological screening by identifying protein markers of toxicity. Proteomics studies have already provided insights into the mechanisms of action of a wide range of substances, from metals to peroxisome proliferators. Current limitations involving speed of throughput are being overcome by increasing automation and the development of new techniques. The isotope-coded affinity tag (ICAT) method appears particularly promising. The application of proteomics to drug development has given rise to the new field of pharmacoproteomics. New associations between proteins and toxicopathological effects are constantly being identified, and major progress is on the horizon as we move into the post-genomic era.     

The role of proteomics in toxicology: identification of biomarkers of toxicity by protein expression analysis

Proteomics, i.e. the high throughput separation, display and identification of proteins, has the potential to be a powerful tool in drug development. It could increase the predictability of early drug development and identify non-invasive biomarkers of toxicity or efficacy. This review provides an introduction to modern proteomics, with particular reference to applications in toxicology. A literature search was carried out to identify studies in two broad classes: screening/predictive toxicology, and mechanistic toxicology. The strengths and limitations of current methods and the likely impact of techniques in drug development are also considered. Proteomics can increase the speed and sensitivity of toxicological screening by identifying protein markers of toxicity. Proteomics studies have already provided insights into the mechanisms of action of a wide range of substances, from metals to peroxisome proliferators. Current limitations involving speed of throughput are being overcome by increasing automation and the development of new techniques. The isotope-coded affinity tag (ICAT) method appears particularly promising. The application of proteomics to drug development has given rise to the new field of pharmacoproteomics. New associations between proteins and toxicopathological effects are constantly being identified, and major progress is on the horizon as we move into the post-genomic era.     

Noninvasive estimation of body composition in small mammals: a comparison of conductive and morphometric techniques

Body fat stores may serve as an index of condition in mammals. Thus, techniques that measure fat content accurately are important for assessing the ecological correlates of condition in mammal populations. We compared the ability of two conductive techniques, bioelectrical impedance analysis (BIA) and total body electrical conductivity (TOBEC), to predict body composition with that of morphometric methods in three small mammal species: red squirrels (n=13), snowshoe hares (n=30), and yellow-bellied marmots (n=4). Animals were livetrapped in northern Idaho; BIA (all subjects) and TOBEC (squirrels only) measurements were taken following chemical immobilization in the field, and morphometric measurements were taken postmortem. Information provided by BIA and TOBEC failed to improve upon the predictive power of morphometric equations for total body water (TBW) and lean body mass (LBM) in squirrels and hares, which do not store substantial amounts of fat (<5% body mass comprised of fat). Although the same pattern held with respect to LBM in marmots, which accumulate substantial amounts of body fat (>10% body mass), a BIA-based model proved best at estimating TBW, suggesting that the usefulness of conductive techniques may be a function of fat deposition. However, regardless of the technique used to predict body composition, estimates of body fat furnished by our equations failed to approximate actual fat levels accurately in all three test species, probably because these techniques only provide indirect estimates of fat content. These results highlight the limitations inherent in contemporary methods of animal fat estimation and underscore the need for the development of direct and accurate measures of body fat in mammals.     

Estimation of skeletal muscle mass by bioelectrical impedance analysis.

The purpose of this study was to develop and cross-validate predictive equations for estimating skeletal muscle (SM) mass using bioelectrical impedance analysis (BIA). Whole body SM mass, determined by magnetic resonance imaging, was compared with BIA measurements in a multiethnic sample of 388 men and women, aged 18-86 yr, at two different laboratories. Within each laboratory, equations for predicting SM mass from BIA measurements were derived using the data of the Caucasian subjects. These equations were then applied to the Caucasian subjects from the other laboratory to cross-validate the BIA method. Because the equations cross-validated (i.e., were not different), the data from both laboratories were pooled to generate the final regression equation SM mass (kg) = [(Ht²/ R x 0.401) + (gender x 3.825) + (age x -0. 071)] + 5.102 where Ht is height in centimeters; R is BIA resistance in ohms; for gender, men = 1 and women = 0; and age is in years. The r(2) and SE of estimate of the regression equation were 0.86 and 2.7 kg (9%), respectively. The Caucasian-derived equation was applicable to Hispanics and African-Americans, but it underestimated SM mass in Asians. These results suggest that the BIA equation provides valid estimates of SM mass in healthy adults varying in age and adiposity.     

Detection of mutations in PCR products from clinical samples by surface plasmon resonance

Two different strategies for scanning and screening of mutations in polymerase chain reaction (PCR) products by hybridization analysis are described, employing real-time biospecific interaction analysis (BIA) for detection. Real-time BIA was used to detect differences in hybridization responses between PCR products and different 17-mer oligonucleotide probes. For the analysis using a biosensor instrument, two different experimental formats were investigated based on immobilization of either biotinylated PCR products or oligonucleotide probes onto a sensor chip. Applied on the human tumour suppressor p53 gene, differences in hybridization levels for full-match and mismatch situations employing both formats allowed the detection of point mutations in exon 6 PCR products, derived from a breast tumour biopsy sample. In addition, a mutant sample sequence could be detected in a 50/50 background of wild type exon 6 sequence. The suitability of the different formats for obtaining a regenerable system and a high throughput of samples is discussed. © 1997 John Wiley & Sons, Ltd.     

Reliability and validity of body composition measures in female athletes.

The purpose of this investigation was to determine the reliability and validity of bioelectrical impedance (BIA) and near-infrared interactance (NIR) for estimating body composition in female athletes. Dual-energy X-ray absorptiometry was used as the criterion measure for fat-free mass (FFM). Studies were performed in 132 athletes [age = 20.4 +/- 1.5 (SD) yr]. Intraclass reliabilities (repeat and single trial) were 0.987-0.997 for BIA (resistance and reactance) and 0.957-0.980 for NIR (optical densities). Validity of BIA and NIR was assessed by double cross-validation. Because correlations were high (r = 0.969-0.983) and prediction errors low, a single equation was developed by using all 132 subjects for both BIA and NIR. Also, an equation was developed for all subjects by using height and weight only. Results from dual-energy X-ray absorptiometry analysis showed FFM = 49.5 +/- 6.0 kg, which corresponded to %body fat (%BF) of 20.4 +/- 3.1%. BIA predicted FFM at 49.4 +/- 5.9 kg (r = 0.981, SEE = 1.1), and NIR prediction was 49. 5 +/- 5.8 kg (r = 0.975, SEE = 1.2). Height and weight alone predicted FFM at 49.4 +/- 5.7 kg (r = 0.961, SEE = 1.6). When converted to %BF, prediction errors were approximately 1.8% for BIA and NIR and 2.9% for height and weight. Results showed BIA and NIR to be extremely reliable and valid techniques for estimating body composition in college-age female athletes.     

Use of bioelectrical impedance to assess body composition changes at high altitude.

This study determined the feasibility of using bioelectrical impedance analysis (BIA) to assess body composition alterations associated with body weight (BW) loss at high altitude. The BIA method was also evaluated relative to anthropometric assessments. Height, BW, BIA, skinfold (SF, 6 sites), and circumference (CIR, 5 sites) measurements were obtained from 16 males (23-35 yr) before, during, and after 16 days of residence at 3,700-4,300 m. Hydrostatic weighings (HW) were performed pre- and postaltitude. Results of 13 previously derived prediction equations using various combinations of height, BW, age, BIA, SF, or CIR measurements as independent variables to predict fat-free mass (FFM), fat mass (FM), and percent body fat (%Fat) were compared with HW. Mean BW decreased from 84.74 to 78.84 kg (P less than 0.01). As determined by HW, FFM decreased by 2.44 kg (P less than 0.01), FM by 3.46 kg (P less than 0.01), and %Fat by 3.02% (P less than 0.01). The BIA and SF methods overestimated the loss in FFM and underestimated the losses in FM and %Fat (P less than 0.01). Only the equations utilizing the CIR measurements did not differ from HW values for changes in FFM, FM, and %Fat. It was concluded that the BIA and SF methods were not acceptable for assessing body composition changes at altitude.     

The influence of posture change on measurements of relative body fat in the bioimpedance analysis method

The purpose of this study was to clarify the influence of posture change on relative body fat in the bioelectrical impedance analysis (BIA) method. The subjects were 30 Japanese healthy young adult males (age: 19.8 +/- 1.4 years, height: 172.3 +/- 5.8 cm, weight: 67.1 +/- 8.2 kg). We used devices with different body segment inductions, between the hand and foot (H-F BIA) and between hands (H-H BIA), and set four measurement conditions differing in posture (supine or sitting), during rest and measurement. The reliabilities of %BF in the H-H and H-F BIA methods were very high (r = 0.995, 0.966), and the relationship in %BF between the UW method and each BIA method was mid-range (r = 0.767, 0.709). Although there were no differences in %BF among different measurement postures in the H-F BIA method, %BF in the H-H BIA method increased significantly when the posture was changed just before measurement. This indicated that it is necessary to pay attention to the posture change just before measurement in the H-H BIA method.     

Advances in surface plasmon resonance biomolecular interaction analysis mass spectrometry (BIA/MS)

Ongoing, worldwide efforts in genomic and protein sequencing, and the ability to readily access corresponding sequence databases, have emphatically driven the development of high‐performance bioanalytical instrumentation capable of characterizing proteins and protein–ligand interactions with great accuracy, speed and sensitivity. Two such analytical techniques have arisen over the past decade to play key roles in the characterization of proteins: surface plasmon resonance biomolecular interaction analysis (SPR‐BIA) and matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF). SPR‐BIA is used in the real‐time investigation of biomolecular recognition events, and is thereby capable of providing details on the association and dissociation kinetics involved in the interaction, information ultimately leading to the determination of dissociation constants involved in the event. MALDI‐TOF is used in the structural characterization, identification and sensitive detection of biomolecules. Although the two techniques have found many independent uses in bioanalytical chemistry, the combination of the two, to form biomolecular interaction analysis mass spectrometry (BIA/MS), enables a technique of analytical capabilities greater than those of the component parts. Reviewed here are issues of concern critical to maintaining high‐levels of performance throughout the multiplexed analysis, as well as examples illustrating the potential analytical capabilities of BIA/MS. Copyright © 1999 John Wiley & Sons, Ltd.     

Effect of physical training on body composition in Moscow adolescents

The influence of physical activity on body mass components has been studied using a sample of Moscow children. 195 girls and 259 boys of Russian ethnicity from 12 to 17 years old were investigated cross-sectionally in 2005 in different Moscow schools. According to the level of physical activity they were divided into three groups: 1-those who did not take part in regular physical exercise (44 boys and 50 girls); 2-those who took part in special sports programs in general education schools (82 boys and 82 girls); 3-students of special sports schools with a high sports ranking (133 boys and 63 girls). The program included anthropometric measurements, evaluation of sexual maturation indices, somatotypes, and "functional" traits (diastolic and systolic blood pressure, pulse rate, hand grip, etc). For the study of body composition, bioelectrical impedance analysis (BIA) was used. The estimates of body mass components were also calculated using the anthropometric measurements. For the fat component, the estimates obtained by BIA and the anthropometric methods were highly correlated: r=0.85-0.88. Age changes of BIA measurements and body components were analysed. With multiple regression analysis it was shown that BIA measurements are dependent on a great number of morphological and functional traits, with the most informative sets of traits being selected. The degree of physical activity has a strong effect on body components: the contents of fat-free mass (FFM) and total body water (TBW) significantly increase, and the fat mass (FM) in girls decreases.     

MrHAMER yields highly accurate single molecule viral sequences enabling analysis of intra-host evolution

Technical challenges remain in the sequencing of RNA viruses due to their high intra-host diversity. This bottleneck is particularly pronounced when interrogating long-range co-evolved genetic interactions given the read-length limitations of next-generation sequencing platforms. This has hampered the direct observation of these genetic interactions that code for protein-protein interfaces with relevance in both drug and vaccine development. Here we overcome these technical limitations by developing a nanopore-based long-range viral sequencing pipeline that yields accurate single molecule sequences of circulating virions from clinical samples. We demonstrate its utility in observing the evolution of individual HIV Gag-Pol genomes in response to antiviral pressure. Our pipeline, called Multi-read Hairpin Mediated Error-correction Reaction (MrHAMER), yields >1000s of viral genomes per sample at 99.9% accuracy, maintains the original proportion of sequenced virions present in a complex mixture, and allows the detection of rare viral genomes with their associated mutations present at <1% frequency. This method facilitates scalable investigation of genetic correlates of resistance to both antiviral therapy and immune pressure and enables the identification of novel host-viral and viral-viral interfaces that can be modulated for therapeutic benefit.     

Percentage of Body Fat Assessment Using Bioelectrical Impedance Analysis and Dual-Energy X-ray Absorptiometry in a Weight Loss Program for Obese or Overweight Chinese Adults

The current study aimed to compare the estimates of body fat percentage (%BF) by performing bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA) in a sample of obese or overweight Chinese adults who participated in a weight-loss randomized control trial stratified by gender to determine whether or not BIA is a valid measurement tool. Among 189 adults [73 males, 116 females; age  = 41 to 74 years; mean body mass index (BMI)  = 27.3 kg/m²], assessments of %BF at the baseline and six months from the baseline were conducted by performing BIA and DXA. Bland-Altman analyses and multiple regression analyses were used to assess the relationships between %BF_BIA and %BF_DXA. Compared with DXA, BIA underestimated %BF [in males: 4.6, –2.4 to 11.7 (mean biases, 95% limit of agreement) at the baseline, 1.4, –7.4 to 10.2 at the endpoint, and 3.2, –4.8 to 11.3 in changes; in females: 5.1, –2.4 to 12.7; 2.2, –6.1 to 10.4; and 3.0, –4.8 to 10.7, respectively]. For males and females, %BFDXA proved to be a significant predictor of the difference between DXA and BIA at the baseline, the endpoint, and in changes when BMI and age were considered (in males: p<0.01 and R ²  = 23.1%, 24.1%, 20.7%, respectively; for females: p<0.001 and R ²  = 40.4%, 48.8%, 25.4%, respectively). The current study suggests that BIA provides a relatively accurate prediction of %BF in individuals with normal weight, overweight, or obesity after the end of weight-loss program, but less accurate prediction of %BF in obese individuals at baseline or weight change during the weight-loss intervention program.     

Estimating Body Composition in Adolescent Sprint Athletes: Comparison of Different Methods in a 3 Years Longitudinal Design

A recommended field method to assess body composition in adolescent sprint athletes is currently lacking. Existing methods developed for non-athletic adolescents were not longitudinally validated and do not take maturation status into account. This longitudinal study compared two field methods, i.e., a Bio Impedance Analysis (BIA) and a skinfold based equation, with underwater densitometry to track body fat percentage relative to years from age at peak height velocity in adolescent sprint athletes. In this study, adolescent sprint athletes (34 girls, 35 boys) were measured every 6 months during 3 years (age at start = 14.8 ± 1.5yrs in girls and 14.7 ± 1.9yrs in boys). Body fat percentage was estimated in 3 different ways: 1) using BIA with the TANITA TBF 410; 2) using a skinfold based equation; 3) using underwater densitometry which was considered as the reference method. Height for age since birth was used to estimate age at peak height velocity. Cross-sectional analyses were performed using repeated measures ANOVA and Pearson correlations between measurement methods at each occasion. Data were analyzed longitudinally using a multilevel cross-classified model with the PROC Mixed procedure. In boys, compared to underwater densitometry, the skinfold based formula revealed comparable values for body fatness during the study period whereas BIA showed a different pattern leading to an overestimation of body fatness starting from 4 years after age at peak height velocity. In girls, both the skinfold based formula and BIA overestimated body fatness across the whole range of years from peak height velocity. The skinfold based method appears to give an acceptable estimation of body composition during growth as compared to underwater densitometry in male adolescent sprinters. In girls, caution is warranted when interpreting estimations of body fatness by both BIA and a skinfold based formula since both methods tend to give an overestimation.     

The novel anticonvulsant BIA 2-093 inhibits transmitter release during opening of voltage-gated sodium channels: a comparison with carbamazepine and oxcarbazepine

(S)-(-)-10-acetoxy-10,11-dihydro-5H-dibenz/b,f/azepine-5-carboxamide (BIA 2-093) is endowed with high anticonvulsant activity and shares with carbamazepine (CBZ) and oxcarbazepine (OXC) the capability to inhibit voltage-gated sodium channels (VGSC). The present study was aimed to compare the effects of BIA 2-093, CBZ and OXC on the release of glutamate, aspartate, gamma-aminobutyric acid (GABA) and dopamine from striatal slices induced by the VGSC opener veratrine. The release of glutamate, aspartate, GABA and aspartate by veratrine from rat striatal slices was a concentration and time dependent process. All the three dibenzazepine carboxamide derivatives, BIA 2-093, CBZ and OXC inhibited in a concentration dependent manner (from 30 to 300 microM) the veratrine-induced release of glutamate, aspartate, GABA and dopamine. CBZ, OXC and BIA 2-093 were endowed with similar potencies in inhibiting veratrine-induced transmitter release. It is concluded that BIA 2-093, CBZ and OXC inhibit veratrine-induced transmitter release, which is in agreement with their capability to block VGSC. This property may be of importance for the anticonvulsant effects of BIA 2-093.     

Estimation of human body composition by electrical impedance methods: a comparative study

This study 1) further validated the relationship between total body electrical conductivity (TOBEC) and densitometrically determined lean body mass (LBMd) and 2) compared with existing body composition techniques (densitometry, total body water, total body potassium, and anthropometry) two new electrical methods for the estimation of LBM: TOBEC, a uniform current induction method, and bioelectrical impedance analysis (BIA), a localized current injection method. In a sample of 75 male and female subjects ranging from 4.9 to 54.9% body fat the correlation between LBMd and LBM predicted from TOBEC by use of a previously developed regression equation was extremely strong (r = 0.962), thus confirming the validity of the TOBEC method. LBM predicted from BIA by use of prediction equations provided with the instrument also correlated with LBMd (r = 0.912) but overestimated LBM compared with LBMd in obese subjects. However, no such systematic error was apparent when new prediction equations derived from this heterogeneous sample of subjects were applied. Thus the TOBEC and BIA methods, which are based on the differing electrical properties of lean tissue and fat and which are convenient, rapid, and safe, correlate well with more cumbersome human body composition techniques.     

The Escherichia coli K-12 SOS chromotest agar spot test for simple, rapid detection of genotoxic agents

The Escherichia coli K-12 SOS chromotest is a colorimetric (beta-galactosidase induction) system for detecting genotoxic chemicals as agents which induce filamentation in response to DNA damage. The chromotest was modified from a liquid suspension assay to a simple, convenient agar spot test, which was performed in the manner of a related colorimetric prophage induction assay (BIA). Chromotest agar dishes yielded optimal results after 16-18 h incubation, presumably because of the agar growth characteristics of tester strain PQ37. Of 44 tested chemicals, nitro aromatics, cytotoxic/antitumor agents, polycyclic hydrocarbons and aflatoxins showed good activity. Alkylating agents such as MNNG and MMS were active only at high concentrations. Compounds active in both the chromotest and BIA were active at 10-100-fold lower concentrations in the chromotest. The chromotest appeared to be less effective than the Salmonella Ames mutagenicity test in the detection of diverse classes of chemical carcinogens. The chromotest may be a useful alternative to the BIA in the study of particular classes of genotoxic compounds.