Body mass index (BMI) and parameters of bone formation and resorption in postmenopausal women.

OBJECTIVES: Aim of this study was to evaluate increased body mass index (BMI) as an anthropometric factor, predisposing to lower rates of bone turnover or changes in bone balance after menopause. MATERIAL AND METHODS: For this purpose, we calculated BMI, and measured spinal (BMD(SP)) and femoral bone mineral density (BMD(FN)) and biochemical markers of bone formation (serum osteocalcin (S-OC), serum procollagen type I C propeptide (S-PICP), serum bone-specific alkaline phosphatase (S-B-ALP)) and resorption (urine N- and C-terminal cross-linking telopeptide of type I collagen (U-NTX-I and U-CTX-I), pyridinoline (U-PYD) and deoxypyridinoline (U-DPD)) in 130 healthy postmenopausal women, aged 46-85 years. Bone balance indices were calculated by subtracting z-scores of resorption markers from z-scores of formation markers, to evaluate bone balance. RESULTS: S-PICP ( r = -0.297, P = 0.002), S-OC ( r = -0.173, P = 0.05) and bone balance indices (zPICP-zDPD) and (zPICP-zPYD) were negatively correlated with BMI (r = -0.25, P = 0.01 and r = -0.25, P = 0.01 and r = -0.21, P = 0.037) and with BMD(SP) (r = -0.196, P = 0.032 and r = -0.275 and P = 0.022). Women were grouped according to their BMI, in normals (BMI < 25 kg/m2), overweight (BMI = 25-30 kg/m2, and obese (BMI > 30 kg/m2). Overweight and obese women had approximately 30% lower levels of S-PICP compared to normals (68.11 +/- 24.85 and 66.41 ng/ml versus 97.47 +/- 23.36 ng/ml, respectively; P = 0.0001). zPICP-zDPD, zPICP-zCTX-I and zPICP-zPYD were significantly declined in obese women compared to normals (P = 0.0072, 0.02 and 0.0028). CONCLUSIONS: We conclude that in postmenopausal women, BMI is inversely associated with levels of collagen I formation marker, serum PICP. In obesity formation of collagen I was reduced, in favor of degradation, but since this finding is not followed by simultaneous decrease in bone mineral density, it seems that increased body weight may have different effects on mature estrogen-deficient bone and extraskeletal tissues containing collagen I.

Diagnostic and neural analysis of skin cancer (DANAOS). A multicentre study for collection and computer-aided analysis of data from pigmented skin lesions using digital dermoscopy.

BACKGROUND: Early detection of melanomas by means of diverse screening campaigns is an important step towards a reduction in mortality. Computer-aided analysis of digital images obtained by dermoscopy has been reported to be an accurate, practical and time-saving tool for the evaluation of pigmented skin lesions (PSLs). A prototype for the computer-aided diagnosis of PSLs using artificial neural networks (NNs) has recently been developed: diagnostic and neural analysis of skin cancer (DANAOS). OBJECTIVES: To demonstrate the accuracy of PSL diagnosis by the DANAOS expert system, a multicentre study on a diverse multinational population was conducted. METHODS: A calibrated camera system was developed and used to collect images of PSLs in a multicentre study in 13 dermatology centres in nine European countries. The dataset was used to train an NN expert system for the computer-aided diagnosis of melanoma. We analysed different aspects of the data collection and its influence on the performance of the expert system. The NN expert system was trained with a dataset of 2218 dermoscopic images of PSLs. RESULTS: The resulting expert system showed a performance similar to that of dermatologists as published in the literature. The performance depended on the size and quality of the database and its selection. CONCLUSIONS: The need for a large database, the usefulness of multicentre data collection, as well as the benefit of a representative collection of cases from clinical practice, were demonstrated in this trial. Images that were difficult to classify using the NN expert system were not identical to those found difficult to classify by clinicians. We suggest therefore that the combination of clinician and computer may potentially increase the accuracy of PSL diagnosis. This may result in improved detection of melanoma and a reduction in unnecessary excisions.