Body fat distribution of overweight females with a history of weight cycling.

Weight cycling may cause a redistribution of body fat to the upper body fat compartments. We investigated the distribution of subcutaneous adipose tissue (SAT) in 30 overweight women with a history of weight-cycling and age-matched controls (167 normal weight and 97 overweight subjects). Measurements of SAT were performed using an optical device, the Lipometer. The SAT topography describes the thicknesses of SAT layers at 15 anatomically well-defined body sites from neck to calf. The overweight women with a history of weight cycling had significantly thicker SAT layers on the upper body compared to the overweight controls, but even thinner SAT layers on their legs than the normal weight women. An android fat pattern was attributed to overweight females and, even more pronounced, to the weight cyclers. The majority of normal weight women showed a gynoid fat pattern. Using stepwise discriminant analysis, 89.0% of all weight cyclers and overweight controls could be classified correctly into the two groups. These findings show the importance of normal weight maintenance as a health-promoting factor.

Android subcutaneous adipose tissue topography in lean and obese women suffering from PCOS: comparison with type 2 diabetic women.

The new optical device, the lipometer, enables the noninvasive, quick, safe, and precise determination of the thickness of subcutaneous adipose tissue (SAT) layers at any given site of the human body. Fifteen anatomically well-defined body sites from neck to calf describe a SAT topography (SAT-Top) like an individual "fingerprint" of a subject. This SAT-Top was examined in 16 women with polycystic ovary syndrome (PCOS) and compared to the body fat distribution of 87 age-matched healthy controls and 20 type-2 diabetic women. SAT-Top differences of these three groups were described and, to render the possibility of visual comparison, the 15-dimensional body fat information was condensed to a two-dimensional factor plot by factor analysis. All PCOS patients had an android body fat distribution with significantly thinner SAT layers on the legs as compared to healthy controls. Moreover, a hierarchical cluster analysis resulted in two distinctly different groups of PCOS women, a lean (PCOSL) and an obese (PCOSO) cluster: compared to healthy women, lean PCOS patients had significantly lower total SAT development, even though height, weight, and body mass index did not deviate significantly. Especially on the legs, their SAT layers were significantly lowered, indicating a more "apple-like" fat distribution type. Obese PCOS women showed a SAT-Top pattern very similar to that of women with type-2 diabetes, although the mean age difference between these groups was more than 30 years. Compared to healthy controls, the SAT-Top of these obese PCOS patients was strongly shifted into the android direction, appearing as "super-apples" with a significantly increased upper trunk obesity to 237.8% and a significantly decreased leg SAT development to 79.8%.

Relationships between bioelectric impedance and subcutaneous adipose tissue thickness measured by LIPOMETER and skinfold calipers in children.

The aim of this study was to compare the relationships between bioelectrical impedance and thicknesses of adipose tissue measured by traditional skinfold caliper (double thickness) or a LIPOMETER device (single non-compressed thickness) in 9- to 12-year-old boys ( n=52) and girls ( n=44). In total, nine skinfolds (triceps, subscapular, biceps, iliac crest, supraspinale, abdominal, front thigh, medial calf, mid-axilla) were measured. Measurement for the thickness of subcutaneous adipose tissue layers (SAT-layers) by LIPOMETER were performed at 15 body sites (neck, triceps, biceps, upper back, front chest, lateral chest, upper abdomen, lower abdomen, lower back, hip, front thigh, lateral thigh, rear thigh, inner thigh, calf). Body bioelectrical impedance was measured with a multiple-frequency impedance device Multiscan-5000 (Bodystat, UK). Impedance at 50 kHz highly correlated with body mass ( r=-0.47 in boys, r=-0.46 in girls, r=-0.47 in total group). The relationship with body height was significant only in girls ( r=-0.42). Skinfold thicknesses measured by caliper did not correlate significantly with body impedance at 50 kHz. SAT-layers measured by LIPOMETER at triceps, front thigh, lateral thigh and rear thigh sites in boys and at the lateral thigh site in girls correlated significantly with body impedance measured at 50 kHz. Stepwise multiple regression analysis indicated that the iliac crest and front thigh skinfold thicknesses measured by caliper characterized only 5.7-12.0% of the impedance at 50 kHz in the total group ( n=96). From the measured 15 SAT-layers, the most significant was the lateral thigh layer which characterized 20.0%, 11.9% and 13.6% of the impedance at 50 kHz in boys, girls and the total group, respectively. It was concluded that the influence of subcutaneous adipose tissue on body impedance is relatively low in children. However, SAT-layers have a slightly higher influence on body impedance than skinfold thicknesses measured by caliper. The sum of skinfolds or SAT-layers did not correlate significantly with body impedance in any group.

Subcutaneous adipose tissue pattern in lean and obese women with polycystic ovary syndrome.

The new optical device, Lipometer, permits the noninvasive, quick, safe, and precise measurement of the thickness of subcutaneous adipose tissue (SAT) layers at any given site of the human body. Fifteen anatomically well-defined body sites from neck to calf describe the SAT topography (SAT-Top) like an individual "fingerprint." SAT-Top was examined in 33 women with polycystic ovary syndrome (PCOS), in 87 age-matched healthy controls and in 20 Type-II diabetic women. SAT-Top differences of these three groups were described, and, based on a hierarchical cluster analysis, two distinctly different groups of PCOS women, a lean (PCOS(L)) and an obese (PCOS(O)) cluster, were found. For visual comparison of the different types of body fat distribution, the 15-dimensional body fat information was condensed to a two-dimensional factor plot by factor analysis. For comparison of the PCOS like body fat distribution with the "healthy" fat pattern, the (previously published) SAT-Top results of 590 healthy women and men (20-70 years old) and 162 healthy girls and boys (7-11 years old) were added to the factor plot. PCOS(O) women showed a SAT-Top pattern very similar to that of women with Type-II diabetes, even though the diabetic women were on average 30 years older. Compared with their healthy controls, SAT-Top of these PCOS(O) patients was strongly skewed into the android direction, providing significantly decreased leg SAT development and significantly higher upper body obesity. Compared with healthy women, PCOS(L) patients had significantly lower total SAT development (even though height, weight, and body mass index did not deviate significantly), showing a slightly lowered amount of body fat in the upper region and a highly significant leg SAT reduction. This type of fat pattern is the same as found in girls and boys before developing their sex specific body fat distribution. We conclude that women with PCOS develop an android SAT-Top, but compared in more detail, we found two typical types of body fat distribution: the "childlike" SAT pattern in lean PCOS patients, and the "diabetic" body fat distribution in obese PCOS women.

Relationship between subcutaneous fatness and leptin in male athletes.

PURPOSE: Circulating leptin is low in trained subjects and closely related to body fat content. However, data are scarce as to whether differences exist in the relationship between different estimates of adiposity, metabolic parameters, and leptin in endurance- and resistance-trained male athletes. We investigated this relationship with special emphasis on subcutaneous fatness and its distribution. METHODS: 20 endurance (ET) and 17 resistance (RT) athletes recruited from different kind of sports were studied. Fat-free mass (FFM) was estimated by means of impedance and fat mass (FM) was calculated. Subcutaneous fat (SAT) and its distribution was measured by means of the optical device Lipometer at 15 body sites (SAT-layers; from 1-neck to 15-calf) on the right side of the body. Fifteen SAT-layers were summed to calculate SAT. Blood samples were obtained for determination for leptin, insulin, and glucose. Insulin resistance was calculated through the fasting insulin resistance index (FIRI; [insulin x glucose/25]). RESULTS: RT-athletes had a greater body mass and body fat content than ET-athletes, but no differences were found for leptin and metabolic parameters. In all athletes, estimates of adiposity were correlated to leptin. However, in ET-athletes FM (P < 0.05), FFM (P < 0.05), and SAT (P < 0.001) but not metabolic parameters were correlated to leptin. In RT-athletes, SAT (P < 0.0001), metabolic parameters (all P < 0.05), but not FM and FFM were in significant relationship with leptin. Stepwise regression revealed SAT as the main determinant for the variation in leptin in all athletes (adj. R(2 )= 0.52, P < 0.0001). CONCLUSION: The results suggest that estimates of adiposity and metabolic parameters are associated with leptin in a sport-specific manner. Whereas leptin might be regulated by overall subcutaneous fatness in athletes, our study does not imply a main influence of fat patterning on leptin in this group of trained subjects.

Effects of weight loss on leptin, sex hormones, and measures of adiposity in obese children.

Adipose tissue influences steroid conversion by paracrine and autocrine mechanisms. Leptin is secreted by adipocytes and influenced by sex hormones and adiposity. Short-term weight loss in the treatment of childhood obesity reduces leptin and adipose tissue. We therefore asked, Do alterations in sex hormones occur owing to weight loss? and can these alterations be explained by changes in fat mass or sc fat and are alterations in sex hormones directly related to the fall in leptin? Twenty obese boys and 40 obese girls were studied before and after 3 wk of low-calorie diet and physical activity. The weight loss program significantly lowered fat mass, abdominal fat distribution, sc fat (all p < 0.0001), leptin, insulin, and estradiol (all p < 0.0001) but not testosterone. Changes in leptin were related to changes in body mass and to changes in fat mass in boys. In girls, changes in leptin were related to changes in sc fatness and also to changes in insulin. In boys, the reduction in sc fat was positively correlated to changes in testosterone (r = 0.54; p < 0.01) and inversely related to the fall in estradiol (r = -0.41; p < 0.05). In girls, changes in testosterone (r = 0.33; p < 0.05) and in estradiol (r = 0.40; p < 0.01) were related to changes in insulin. Stepwise regression showed that initial leptin was the best determinant for the fall in leptin (adjusted R2 = 0.87; p < 0.0001). The results show that alterations in sex hormones are related to changes in certain fat depots in boys whereas in girls changes in insulin might participate in changes in sex hormones. A greater fall in leptin owing to short-term weight loss is not associated with greater alterations in sex hormones and initial leptin is the best determinant to explain the variability in changes in leptin. The possibility of sex differences in changes in sex hormones secondary to the reduction in fatness warrants further study.

Subcutaneous adipose tissue layers as a stable correlate of leptin in response to short term energy restriction in obese girls.

AIMS: We studied the relationship of subcutaneous adipose tissue layers (SAT-layers) measured at 15 specified body sites with leptin before and after a weight loss program for three weeks. SUBJECTS AND METHODS: In 70 obese girls, SAT-layers were measured by means of the optical device, lipometer. Fat mass (FM) was estimated by means of bioelectrical impedance. RESULTS: At the beginning of the study, all estimates of adiposity, insulin, and SAT-layers from the upper body (from 1-neck to 6-lateral chest) were correlated to leptin at a P-value of<0.0001. Percentage FM together with SAT-layer 4-upper back and insulin explained 75% of the variation in leptin (P<0.0001). After three weeks, estimates of adiposity and leptin were reduced (all P<0.0001). Most SAT-layers were reduced, but SAT-layers 8-lower abdomen and 9-lower back were significantly increased. Changes in leptin were best explained by initial leptin, but percentage change (Delta) in insulin, Delta SAT-layer 1-neck, and Delta SAT-layer 3-biceps contributed to the Delta leptin (adj. r(2)=0.47, P<0.0001). In the weight-reduced state, circulating leptin was best explained by three SAT-layers and insulin (adj. r(2)=0.67, P<0.0001). DISCUSSION: The results suggest that Delta changes in leptin are attributable to changes in the endocrine state and subcutaneous fat, and SAT-layers may serve as a stable correlate of leptin in the weight-reduced state.

Interrelationship between estimates of adiposity and body fat distribution with metabolic and hemostatic parameters in obese children.

Adiposity in childhood is often associated with metabolic abnormalities and accompanied by a dysregulation of the coagulation and fibrinolytic systems. We studied the interrelationship of metabolic and hemostatic parameters and explored their relationship with measures of adiposity and fat distribution in obese children. In 34 obese boys (mean age, 11.7 years) and 57 obese girls (12.1 years), blood samples were determined for insulin, glucose, triglycerides, fibrinogen, plasminogen activator inhibitor-1 (PAI-1), and tissue-type plasminogen activator-antigen (tPA-Ag). Body composition was assessed by means of impedance. Waist (Wc) and hip circumference were measured. The thickness of subcutaneous adipose tissue-layers (SAT-layers) was measured at 15 different body sites (from 1-neck to 15-calf) by means of the optical device, Lipometer. Overall subcutaneous fatness (SAT) was calculated and SAT-distribution was estimated by means of factor analysis. Significant correlations were found between different measures of adiposity and Wc with metabolic parameters. Fibrinogen was mainly associated with upper body subcutaneous fatness (factor 1) in boys. In girls, hemostatic parameters were associated with nearly all measures of adiposity and also with factor 1 and SAT. Regression analysis showed that factor 1 together with PAI-1 (both P <.0001) contribute to fibrinogen (adjusted [adj], R(2) =.30). PAI-1 together with trigylcerides (both P <.0001) and age (P <.04) were main determinants for tPA-Ag (adj, R(2) =.41). tPA-Ag (P <.0001) together with glucose (P <.001, negative slope), fibrinogen (P <.001, negative slope), and percentage fat mass (%FM) (P <.01) contributed to PAI-1 (adj, R(2) =.54). These results favor the concept of an interrelationship between metabolic and hemostatic parameters resulting from increased adiposity, perhaps influenced by pubertal development of children. Although upper body subcutaneous fatness was found to be a main correlate of metabolic and hemostatic parameters, it remains to be investigated whether this type of subcutaneous fat distribution is involved in the expression of metabolic and hemostatic risk factors and participates in the dysregulation of the hemostatic system in the state of childhood obesity.

Orthogonal factor coefficient development of subcutaneous adipose tissue topography (SAT-Top) in girls and boys.

The new optical device Lipometer allows noninvasive, quick, and safe determination of the thickness of subcutaneous adipose tissue (SAT) layers (in mm) at any site of the human body. The specification of 15 evenly distributed body sites enables the precise measurement of subcutaneous body fat distribution, so-called subcutaneous adipose tissue topography (SAT-Top). SAT-Top was measured in 980 children aged 7-19 years. In this paper we describe the degree to which SAT-Top body sites are intercorrelated. We consider whether a meaningful reduction of data is possible using factor analysis, which factors can be extracted, and how SAT-Top data of children can be added to a factor value plot, depicting the essential results of age-dependent subcutaneous fat development. SAT layers situated on the same body area provide correlation coefficients up to +r = 0.91. Two factors are extracted: factor 1, containing all upper body sites (from neck to hip); and factor 2, consisting of all leg body sites. When all 980 children are divided into three age groups in a factor value plot, the first age group (7-11 years) shows almost equal SAT-Top development in boys and girls. Afterwards, for the consecutive age groups 2 (11-15 years) and 3 (15-19 years), the age-dependent subcutaneous fat development of boys and girls progresses into nearly orthogonal directions.

Artificial neural networks compared to factor analysis for low-dimensional classification of high-dimensional body fat topography data of healthy and diabetic subjects.

Subcutaneous adipose tissue thickness was measured in 590 healthy subjects at 15 specific body sites by means of the new optical device, lipometer, providing a high-dimensional and partly highly intercorrelated set of data, which had been analyzed by factor analysis previously. N-2-N back-propagation neural networks are able to perform low-dimensional display of high-dimensional data as a special application. We report about the performance of such a 15-2-15 network and compare its results with the output of factor analysis. As test data for verification, measurement values on women with proven diabetes mellitus type II (NIDDM) are used. Surprisingly our 15-2-15 neural network is able to reproduce the classification pattern resulting from factor analysis very precisely. After extracting the network weights the classification of new subjects is even more simple with the neural network as compared with factor analysis. In addition, the network weights are able to cluster highly correlated body sites nicely to different groups, corresponding to different regions of the human body. Thus, the analysis of these weights provides additional information about the structure of the data. Therefore, N-2-N networks seem to be a good alternative method for analyzing high-dimensional data with strong intercorrelation.

Differences of subcutaneous adipose tissue topography in type-2 diabetic (NIDDM) women and healthy controls.

Women suffering from type-2 diabetes mellitus (non-insulin-dependent diabetes mellitus [NIDDM]) have more total body fat and upper body obesity compared with healthy controls. However, the standard measurement methods have disadvantages such as radiological burden, lack of precision, or high time consumption. A new optical device, the Lipometer, enables the noninvasive, quick, and save determination of the thickness of subcutaneous adipose tissue layers at any given site of the human body. The specification of 15 evenly distributed body sites allows the precise measurement of subcutaneous body fat distribution, so-called subcutaneous adipose tissue topography (SAT-Top). SAT-Tops of 20 women with clinically proven NIDDM and 122 healthy controls matched by age group were measured. In this paper, we describe the precise SAT-Top differences of these two groups and present the multidimensional SAT-Top information condensed in a two-dimensional factor plot and in a response plot of an artificial neural network. NIDDM women provide significantly lower leg SAT-Top and significantly higher upper trunk SAT-Top development ("apple"-type) compared with their healthy controls.

Artificial neural networks as a method to improve the precision of subcutaneous adipose tissue thickness measurements by means of the optical device LIPOMETER.

The LIPOMETER is an optical device for measuring the thickness of a subcutaneous adipose tissue layer. It illuminates the interesting layer, measures the backscattered light signals and from these, it computes absolute values of subcutaneous adipose tissue layer thickness (in mm). Previously, these light pattern values were fitted by nonlinear regression analysis to absolute values provided by computed tomography. Nonlinear regression analysis might provide slight limitations for our problem: a selected curve type cannot be changed afterwards during the application of the measurement device. Artificial neural networks yield a more flexible approach to this fitting problem and might be able to refine the fitting results. In the present paper we compare nonlinear regression analysis with the behaviour of different architectures of multilayer feed forward neural networks trained by error back propagation. Specifically, we are interested whether neural networks are able to yield a better fit of the LIPOMETER light patterns to absolute subcutaneous adipose tissue layer thicknesses than the nonlinear regression techniques. Different architectures of these networks are able to surpass the best result of regression analysis in training and test, providing higher correlation coefficients, regression lines with absolute values obtained from computed tomography closer to the line of identity, decreased sums of absolute and squared deviations, and higher measurement agreement.

The relationship between different subcutaneous adipose tissue layers, fat mass and leptin in obese children and adolescents.

We studied the relationships of subcutaneous adipose tissue layers (SAT-layers), body fat mass (FM) and waist-to-hip ratio (WHR) with leptin in obese children and adolescents. Twenty-nine obese children and adolescents (12 boys: age: 11.3 +/- 3.7 yr; body mass index [BMI]: 28.5 +/- 4) and 17 girls (age: 12.2 +/- 2.2 yr; BMI: 29.8 +/- 4.7) (mean +/- SD) were studied. FM was estimated by bioelectrical impedance. SAT-layers were determined at 15 different body sites from 1-neck to 15-calf by the Lipometer optical device. Leptin and insulin were determined by RIA. Maturity was associated with a greater thickness of certain SAT-layers from the upper body and with a lower thickness of SAT-layers from the abdominal region and lower extremities. Significant correlations were found for all estimates of adiposity and leptin (all p<0.001). Waist and hip circumferences were not correlated to leptin after adjustment for FM. SAT-layers from the upper body were significantly and positively correlated to leptin. Multiple regression analysis revealed FM as a main contributor to the variation in leptin (R2=0.53, p<0.0001). FM together with SAT-layers 5-front chest and 13-rear thigh explained 72% of the variation in leptin (p<0.0001). In a body fat distribution model, hip circumference together with SAT-layers 4-upper back and 2-triceps explained 75% of the variation in leptin (p< 0.0001). The results suggest that SAT-layers and their topography are main determinants for leptin in obese children and adolescents. Maturity in obese children is associated with higher values of upper body SAT-layers and lower values of abdominal and lower extremities SAT-layers. Whether leptin is under the control of certain subcutaneous adipose tissue depots from the upper body remains to be elucidated by longitudinal studies.

Quantifying the 'appleness' or 'pearness' of the human body by subcutaneous adipose tissue distribution.

To quantify subcutaneous adipose tissue topography (SAT-Top) describing individual SAT distribution for a subject or even a group we measured subcutaneous adipose tissue thickness at 15 specified body sites of 303 healthy women aged 20-69 yrs and 20 women with proven non-insulin-dependent diabetes mellitus (NIDDM) by the optical device 'LIPOMETER'. The type of upper-body- and lower-body-fat pattern, (apples or pears), was determined by factor analysis of the data. Upper body sites were highly loaded in factor 1, whereas factor 2 included highly loaded body sites from the lower extremities. For an individual, factor 1 scores > factor 2 scores, was described as an 'apple'-type, while factor 2 > factor 1 was described as a 'pear'-type. We found about 80% 'pears' and 20% 'apples' in 20-29 year olds and 20% 'pears' and 80% 'apples' in 60-69 year old women. Women with NIDDM tended to be 'super-apples'. SAT-Top provides a useful differentiation between apples and pears and we recommend this approach as a screening method.

Artificial neural networks in laboratory medicine and medical outcome prediction.

Since the early nineties the number of scientific papers reporting on artificial neural network (ANN) applications in medicine has been quickly increasing. In the present paper, we describe in some detail the architecture of network types used most frequently in ANN applications in the broad field of laboratory medicine and clinical chemistry, present a technique-structured review about the recent ANN applications in the field, and give information about the improvements of available ANN software packages. ANN applications are divided into two main classes: supervised and unsupervised methods. Most of the described supervised applications belong to the fields of medical diagnosis (n = 7) and outcome prediction (n = 9). Laboratory and clinical data are presented to multilayer feed-forward ANNs which are trained by the back propagation algorithm. Results are often better than those of traditional techniques such as linear discriminant analysis, classification and regression trees (CART), Cox regression analysis, logistic regression, clinical judgement or expert systems. Unsupervised ANN applications provide the ability of reducing the dimensionality of a dataset. Low-dimensional plots can be generated and visually understood and compared. Results are very similar to that of cluster analysis and factor analysis. The ability of Kohonen's self-organizing maps to generate 2D maps of molecule surface properties was successfully applied in drug design.

The determination of three subcutaneous adipose tissue compartments in non-insulin-dependent diabetes mellitus women with artificial neural networks and factor analysis.

The optical device LIPOMETER allows for non-invasive, quick, precise and safe determination of subcutaneous fat distribution, so-called subcutaneous adipose tissue topography (SAT-Top). In this paper, we show how the high-dimensional SAT-Top information of women with type-2 diabetes mellitus (non-insulin-dependent diabetes mellitus (NIDDM)) and a healthy control group can be analysed and represented in low-dimensional plots by applying factor analysis and special artificial neural networks. Three top-down sorted subcutaneous adipose tissue compartments are determined (upper trunk, lower trunk, legs). NIDDM women provide significantly higher upper trunk obesity and significantly lower leg obesity ('apple' type), as compared with their healthy control group. Further, we show that the results of the applied networks are very similar to the results of factor analysis.

NADH stimulates endogenous dopamine biosynthesis by enhancing the recycling of tetrahydrobiopterin in rat phaeochromocytoma cells.

Treatment of Parkinson patients with L-DOPA (3,4-dihydroxy-L-phenylalanine) leads to endproduct inhibition of tyrosine hydroxylase, the key enzyme in dopamine biosynthesis and the enzyme needing tetrahydrobiopterin and iron as cofactors. To overcome this problem an alternative treatment was investigated which attempted to stimulate endogenous dopamine biosynthesis. Incubation of rat PC 12 cells with NADH (beta-nicotinamide adeninedinucleotide) leads to increased dopamine production. We investigated the possibility that this increase of dopamine biosynthesis was due to stimulation of quinonoid dihydropteridine reductase, the enzyme which recycles the inactive dihydrobiopterin to the active tetrahydrobiopterin. The experiments showed that whereas NADH is able to increase dopamine production in PC 12 cells (rat phaeochromocytoma cells, clone PC 12) up to three-fold, no influence is exerted by NADH on pteridine metabolism; neither are tetrahydrobiopterin concentrations nor the de novo-biosynthesis of pteridines from guanosine triphosphate altered by NADH. Further no influence of NADH on protein de novo synthesis of quinonoid dihydropteridine reductase was observed. However, NADH was able to directly increase the catalytic activity of this enzyme. Our results suggest that the stimulation of dopamine biosynthesis by NADH is due to more rapid regeneration of quinonoid dihydrobiopterin to tetrahydrobiopterin.

Neural networks as a tool for compact representation of ab initio molecular potential energy surfaces.

Ab initio quantum chemical calculations of molecular properties such as, e.g., torsional potential energies, require massive computational effort even for moderately sized molecules, if basis sets with a reasonable quality are employed. Using ab initio data on conformational properties of the cofactor (6R,1'R,2'S)-5,6,7,8-tetrahydrobiopterin, we demonstrate that error backpropagation networks can be established that efficiently approximate complicated functional relationships such as torsional potential energy surfaces of a flexible molecule. Our pilot simulations suggest that properly trained neural networks might provide an extremely compact storage medium for quantum chemically obtained information. Moreover, they are outstandingly comfortable tools when it comes to making use of the stored information. One possible application is demonstrated, namely, computation of relaxed torsional energy surfaces.

"Lipometer": determining the thickness of a subcutaneous fatty layer.

The "Lipometer" is a new computerized optical measuring system for determining the thickness of a subcutaneous fatty layer. It offers a non-invasive, quick, precise and safe way measuring a fat layer.