scholarly journals In vivo measurement of total body lipid content of common carp (<i>Cyprinus carpio</i> L.) by electrical conductivity

2003 ◽  
Vol 46 (4) ◽  
pp. 397-402 ◽  
Author(s):  
C. Hancz ◽  
G. Milisits ◽  
P. Horn
Keyword(s):  
Electrical Conductivity ◽  
Lean Body Mass ◽  
Body Mass ◽  
Common Carp ◽  
Lipid Content ◽  
Live Weight ◽  
Fat Content ◽  
Whole Body ◽  
Body Lipid ◽  
Total Body

Abstract. non-destructive method to predict the total lipid content and the lean body mass (LBM) was evaluated by measuring the total body electrical conductivity (TOBEC) with common carp. This technique is based on the principle that body fat and fat-free mass differ in electric properties which can be measured in a low-frequency electromagnetic field. Experimental fish with average body weight of 1225 ± 298 g originated from a commercial stock. Fish were slaughtered immediately after the measurements and homogenized samples were taken from the grinded whole-body. The fat content of the homogenates was analysed using Soxhlet extraction after hydrochloric acid digestion. The weight of lean body mass (LBM) was calculated as the difference between the live weight and the weight of fat determined. The TOBEC method provided very precise estimation of lean body mass (R2 = 0.99). Total body lipid content (in gram) can also be predicted from the E value and live weight with adequate accuracy (R2 = 0.66) in the size range of 706–1989 g in common carp. The predictibility of the crude fat content (in %) was moderate (R2 = 0.37) in the present investigation. It could not be increased significantly by including other body measurements as standard lenght, height and circumference. Fat content of table-sized, sexually matured common carp can be estimated at a precision level that may be adequate only if high selection pressure has to be applied in a breeding program.

LEAN BODY MASS AND FAT IN OBESE CHILDREN

PEDIATRICS ◽  
1964 ◽  
Vol 34 (3) ◽  
pp. 308-314
Author(s):  
Gilbert B. Forbes
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Scintillation Counter ◽  
Bone Age ◽  
Abdominal Circumference ◽  
Whole Body ◽  
Average Height ◽  
Obese Children ◽  
Normal Children ◽  
Total Body

Measurements of total body potassium in obese children were made in the whole body scintillation counter, and from this value lean body mass was calculated, and then fat by difference. A series of normal children was available for comparison. There was a good correlation between total body fat and relative body weight, abdominal circumference, and buttocks circumference, and a fair correlation with triceps skin-fold thickness. Although the series is a small one, it suggests that there are two types of obesity in childhood. The first is characterized by increased LBM in addition to fat, by a tendency to tallness and advanced bone age, and to have been overweight since infancy. The second group shows no increase in LBM; these subjects tend to have a normal bone age, to be of average height, and the majority have become obese during the childhood years.

Estimation of the body chemical composition of live cattle varying widely in fat content

1981 ◽  
Vol 96 (1) ◽  
pp. 213-220 ◽  
Author(s):  
D. A. Little ◽  
R. W. McLean
Keyword(s):  
Body Weight ◽  
Body Fat ◽  
Total Body Water ◽  
Live Weight ◽  
Fat Content ◽  
Body Water ◽  
Whole Body ◽  
Gut Contents ◽  
Accurate Estimation ◽  
Total Body

SUMMARYFollowing the measurement of tritiated water (TOH) spaces, 31 cattle were slaughtered and chemically analysed in this study. They included several breeds, both females and castrate males, and were of varied nutritional history. Their body-fat content ranged from 4 to 21% of fasted live weight.Total body water (including the water in the gut contents) was reliably estimated from TOH space, measured after allowing an overnight 16 h waterless fast for TOH equilibration. Following this regime, residual D.M. in the gut contents amounted to 1·75% of fasted live weight. The relationships of body fat to body weight, and body fat to body water when both were expressed as percentages of body weight, were too variable to be used in any predictive fashion. Equations were derived, using fasted live weight, allowing the accurate estimation in vivo of the quantities of the chemical components in the whole body (i.e. total body minus D.M. in gut contents).It was demonstrated that the sum of total body water and total body fat constituted virtually 80% of total body tissues, and that total body protein closely approximated 80% of the fat-free dry matter, in cattle varying widely in body condition. These relationships constitute the physiological basis of the equations presented.Comparable principles appear to apply to sheep, and a range of other mammalian species.

The relative proportions of fat, muscle and bone in the normal human forearm as determined by computed tomography

1984 ◽  
Vol 66 (6) ◽  
pp. 683-689 ◽  
Author(s):  
R. J. Maughan ◽  
J. S. Watson ◽  
J. Weir
Keyword(s):  
Computed Tomography ◽  
Lean Body Mass ◽  
Body Mass ◽  
Fat Content ◽  
Whole Body ◽  
Water Displacement ◽  
Cross Sectional ◽  
Human Forearm ◽  
Normal Human ◽  
Male Subjects

1. Computed tomography has been used to establish the proportions of fat, muscle and bone present in the normal human forearm. 2. Subjects were healthy young volunteers, eight males and eight females. A series of six cross-sectional scans at right angles to the long axis of the forearm was obtained, the scans being made at equidistant intervals between the olecranon process and the ulnar styloid. 3. The volumes occupied by fat, muscle and bone were calculated for the complete forearm. Total forearm volume calculated by this method agreed closely with that measured by water displacement. 4. For the male subjects, forearm composition was 72.1 ± 4.4% muscle (mean ± SD), 15.0 ± 5.3% fat and 12.9 ± 1.2% bone. Female forearms had less muscle (P<0.001) and more fat (P<0.001) than those of the male subjects: 58.5 ± 4.0% muscle, 29.3 ± 5.0% fat and 12.3 ± 1.4% bone. 5. Forearm muscle volume was significantly correlated (r= 0.75; P<0.05) with lean body mass in the male subjects; the range of values for lean body mass in the female subjects was too small to permit calculation of the equivalent relationship. 6. Forearm fat content, as a percentage of total volume, was proportional to whole body fat content as estimated from skinfold thickness (males, r = 0.84; P< 0.01; females, r = 0.77; P< 0.05).

scholarly journals A comparison of thermoregulatory responses to exercise between mass-matched groups with large differences in body fat

2016 ◽  
Vol 120 (6) ◽  
pp. 615-623 ◽  
Author(s):  
Sheila Dervis ◽  
Geoff B. Coombs ◽  
Georgia K. Chaseling ◽  
Davide Filingeri ◽  
Jovana Smoljanic ◽  
...  
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Sweat Rate ◽  
Whole Body ◽  
Total Body Mass ◽  
Percentage Body Fat ◽  
Thermoregulatory Responses ◽  
Local Sweat Rate ◽  
Total Body

We sought to determine 1) the influence of adiposity on thermoregulatory responses independently of the confounding biophysical factors of body mass and metabolic heat production (Hprod); and 2) whether differences in adiposity should be accounted for by prescribing an exercise intensity eliciting a fixed Hprod per kilogram of lean body mass (LBM). Nine low (LO-BF) and nine high (HI-BF) body fat males matched in pairs for total body mass (TBM; LO-BF: 88.7 ± 8.4 kg, HI-BF: 90.1 ± 7.9 kg; P = 0.72), but with distinctly different percentage body fat (%BF; LO-BF: 10.8 ± 3.6%; HI-BF: 32.0 ± 5.6%; P < 0.001), cycled for 60 min at 28.1 ± 0.2°C, 26 ± 8% relative humidity (RH), at a target Hprod of 1) 550 W (FHP trial) and 2) 7.5 W/kg LBM (LBM trial). Changes in rectal temperature (ΔTre) and local sweat rate (LSR) were measured continuously while whole body sweat loss (WBSL) and net heat loss (Hloss) were estimated over 60 min. In the FHP trial, ΔTre (LO-BF: 0.66 ± 0.21°C, HI-BF: 0.87 ± 0.18°C; P = 0.02) was greater in HI-BF, whereas mean LSR (LO-BF 0.52 ± 0.19, HI-BF 0.43 ± 0.15 mg·cm−2·min−1; P = 0.19), WBSL (LO-BF 586 ± 82 ml, HI-BF 559 ± 75 ml; P = 0.47) and Hloss (LO-BF 1,867 ± 208 kJ, HI-BF 1,826 ± 224 kJ; P = 0.69) were all similar. In the LBM trial, ΔTre (LO-BF 0.82 ± 0.18°C, HI-BF 0.54 ± 0.19°C; P < 0.001), mean LSR (LO-BF 0.59 ± 0.20, HI-BF 0.38 ± 0.12 mg·cm−2·min−1; P = 0.04), WBSL (LO-BF 580 ± 106 ml, HI-BF 381 ± 68 ml; P < 0.001), and Hloss (LO-BF 1,884 ± 277 kJ, HI-BF 1,341 ± 184 kJ; P < 0.001) were all greater at end-exercise in LO-BF. In conclusion, high %BF individuals demonstrate a greater ΔTre independently of differences in mass and Hprod, possibly due to a lower mean specific heat capacity or impaired sudomotor control. However, thermoregulatory responses of groups with different adiposity levels should not be compared using a fixed Hprod in watts per kilogram lean body mass.

Hyperhydration: thermoregulatory effects during compensable exercise-heat stress

1997 ◽  
Vol 83 (3) ◽  
pp. 860-866 ◽  
Author(s):  
William A. Latzka ◽  
Michael N. Sawka ◽  
Scott J. Montain ◽  
Gary S. Skrinar ◽  
Roger A. Fielding ◽  
...  
Keyword(s):  
Heat Stress ◽  
Heat Loss ◽  
Lean Body Mass ◽  
Body Mass ◽  
Core Temperature ◽  
Whole Body ◽  
Threshold Temperature ◽  
Evaporative Heat Loss ◽  
Sweating Rate ◽  
Total Body

Latzka, William A., Michael N. Sawka, Scott J. Montain, Gary S. Skrinar, Roger A. Fielding, Ralph P. Matott, and Kent B. Pandolf.Hyperhydration: thermoregulatory effects during compensable exercise-heat stress. J. Appl. Physiol. 83(3): 860–866, 1997.—This study examined the effects of hyperhydration on thermoregulatory responses during compensable exercise-heat stress. The general approach was to determine whether 1-h preexercise hyperhydration [29.1 ml/kg lean body mass; with or without glycerol (1.2 g/kg lean body mass)] would improve sweating responses and reduce core temperature during exercise. During these experiments, the evaporative heat loss required (Ereq = 293 W/m2) to maintain steady-state core temperature was less than the maximal capacity (Emax = 462 W/m2) of the climate for evaporative heat loss (Ereq/Emax= 63%). Eight heat-acclimated men completed five trials: euhydration, glycerol hyperhydration, and water hyperhydration both with and without rehydration (replace sweat loss during exercise). During exercise in the heat (35°C, 45% relative humidity), there was no difference between hyperhydration methods for increasing total body water (∼1.5 liters). Compared with euhydration, hyperhydration did not alter core temperature, skin temperature, whole body sweating rate, local sweating rate, sweating threshold temperature, sweating sensitivity, or heart rate responses. Similarly, no difference was found between water and glycerol hyperhydration for these physiological responses. These data demonstrate that hyperhydration provides no thermoregulatory advantage over the maintenance of euhydration during compensable exercise-heat stress.

Total-body electrical conductivity (TOBEC): relationship to estimates of muscle mass, fat-free weight, and lean body mass

1989 ◽  
Vol 49 (4) ◽  
pp. 593-598 ◽  
Author(s):  
C A Horswill ◽  
R Geeseman ◽  
R A Boileau ◽  
B T Williams ◽  
D K Layman ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Lean Body Mass ◽  
Muscle Mass ◽  
Body Mass ◽  
Free Weight ◽  
Total Body

Comparison in man of total body electrical conductivity and lean body mass derived from body density: Validation of a new body composition method

Metabolism ◽  
1983 ◽  
Vol 32 (5) ◽  
pp. 524-527 ◽  
Author(s):  
Elio Presta ◽  
Karen R. Segal ◽  
Bernard Gutin ◽  
Gail G. Harrison ◽  
Theodore B. Van Itallie
Keyword(s):  
Electrical Conductivity ◽  
Body Composition ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Density ◽  
Composition Method ◽  
Total Body

scholarly journals A method for evaluation of patient-specific lean body mass from limited-coverage CT images and its application in PERCIST: comparison with predictive equation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jingjie Shang ◽  
Zhiqiang Tan ◽  
Yong Cheng ◽  
Yongjin Tang ◽  
Bin Guo ◽  
...  
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Whole Body ◽  
Patient Specific ◽  
Predictive Equation ◽  
Reference Standard ◽  
Pet Ct ◽  
Before And After ◽  
Percist 1.0 ◽  
Limited Coverage

Abstract Background Standardized uptake value (SUV) normalized by lean body mass ([LBM] SUL) is recommended as metric by PERCIST 1.0. The James predictive equation (PE) is a frequently used formula for LBM estimation, but may cause substantial error for an individual. The purpose of this study was to introduce a novel and reliable method for estimating LBM by limited-coverage (LC) CT images from PET/CT examinations and test its validity, then to analyse whether SUV normalised by LC-based LBM could change the PERCIST 1.0 response classifications, based on LBM estimated by the James PE. Methods First, 199 patients who received whole-body PET/CT examinations were retrospectively retrieved. A patient-specific LBM equation was developed based on the relationship between LC fat volumes (FVLC) and whole-body fat mass (FMWB). This equation was cross-validated with an independent sample of 97 patients who also received whole-body PET/CT examinations. Its results were compared with the measurement of LBM from whole-body CT (reference standard) and the results of the James PE. Then, 241 patients with solid tumours who underwent PET/CT examinations before and after treatment were retrospectively retrieved. The treatment responses were evaluated according to the PE-based and LC-based PERCIST 1.0. Concordance between them was assessed using Cohen’s κ coefficient and Wilcoxon’s signed-ranks test. The impact of differing LBM algorithms on PERCIST 1.0 classification was evaluated. Results The FVLC were significantly correlated with the FMWB (r=0.977). Furthermore, the results of LBM measurement evaluated with LC images were much closer to the reference standard than those obtained by the James PE. The PE-based and LC-based PERCIST 1.0 classifications were discordant in 27 patients (11.2%; κ = 0.823, P=0.837). These discordant patients’ percentage changes of peak SUL (SULpeak) were all in the interval above or below 10% from the threshold (±30%), accounting for 43.5% (27/62) of total patients in this region. The degree of variability is related to changes in LBM before and after treatment. Conclusions LBM algorithm-dependent variability in PERCIST 1.0 classification is a notable issue. SUV normalised by LC-based LBM could change PERCIST 1.0 response classifications based on LBM estimated by the James PE, especially for patients with a percentage variation of SULpeak close to the threshold.

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