Triglyceride and lipoprotein (a) are markers of coronary artery disease severity among postmenopausal women.

OBJECTIVE: After menopause, some women manifest coronary artery disease (CAD) with highly variable angiographic severity. For these women, postmenopausal appearing of some CAD risk factors may have differently influenced the CAD risk and severity. In this study, we attempt to unravel differences in the frequency or intensity of CAD risk factors among postmenopausal women with different angiographic severity. METHODS: We studied 182 postmenopausal women (64+/-6 years) who underwent coronary angiography to investigate thoracic pain. Subjects with no detectable coronary lesions at angiography were recruited to the non-obstructive group and patients with CAD were grouped in one-vessel or multi-vessel groups. We compared clinical variables as the body mass index (BMI), age at menopause, age, hypertension, diabetes and cigarette smoking, and lipid measurements as plasma levels of total cholesterol, triglyceride, low-density lipoprotein cholesterol, very low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, apolipoprotein (apo) A1, apo B and lipoprotein(a) (Lp(a)). RESULTS: Comparing to the non-obstructive group, Lp(a) was twofold higher in the one-vessel group and threefold higher in the multi-vessel group and triglycerides were 34% higher in the one-vessel group and 50% higher in the multi-vessel group. No further difference was found among the three groups. After multivariate logistic regression analysis, triglyceride (odds ratio: 1.01; P=0.0013) and Lp(a) (odds ratio: 1.006; P<0.0001) were independently indicative of the presence of obstructive CAD. CONCLUSIONS: We found that both Lp(a) and triglycerides constitute useful markers of CAD severity among postmenopausal women.

DMP3: a dynamic multilayer perceptron construction algorithm.

This paper presents DMP3 (Dynamic Multilayer Perceptron 3), a multilayer perceptron (MLP) constructive training method that constructs MLPs by incrementally adding network elements of varying complexity to the network. DMP3 differs from other MLP construction techniques in several important ways, and the motivation for these differences are given. Information gain rather than error minimization is used to guide the growth of the network, which increases the utility of newly added network elements and decreases the likelihood that a premature dead end in the growth of the network will occur. The generalization performance of DMP3 is compared with that of several other well-known machine learning and neural network learning algorithms on nine real world data sets. Simulation results show that DMP3 performs better (on average) than any of the other algorithms on the data sets tested. The main reasons for this result are discussed in detail.

LIA: a location-independent transformation for ASOCS adaptive algorithm 2.

Most Artificial Neural Networks (ANNs) have a fixed topology during learning, and often suffer from a number of short-comings as a result. ANNs that use dynamic topologies have shown the ability to overcome many of these problems. Adaptive Self-Organizing Concurrent Systems (ASOCS) are a class of learning models with inherently dynamic topologies. This paper introduces Location-Independent Transformations (LITs) as a general strategy for implementing learning models that use dynamic topologies efficiently in parallel hardware. An LIT creates a set of location-independent nodes, where each node computes its part of the network output independent of other nodes, using local information. This type of transformation allows efficient support for adding and deleting nodes dynamically during learning. In particular, this paper presents the Location-Independent ASOCS (LIA) model as an LIT for ASOCS Adaptive Algorithm 2. The description of LIA gives formal definitions for LIA algorithms. Because LIA implements basic ASOCS mechanisms, these definitions provide a formal description of basic ASOCS mechanisms in general, in addition to LIA.

Progesterone increases glomerular filtration rate, urinary kallikrein excretion and uric acid clearance in normal women.

In pregnancy there is a rise in glomerular filtration rate (GFR), plasma aldosterone levels, uric acid clearance and urinary kallikrein excretion. In toxemia all the above parameters tend to decrease. Progesterone has a diuretic effect which is usually related to aldosterone antagonism. We administered progesterone to normal women and observed that GFR, uric acid clearance and kallikrein excretion increased significantly, GFR from 103.0 +/- 13.7 ml/min to 118.0 +/- 18.0 ml/min (P less than 0.01), uric acid clearance from 9.0 +/- 3.6 ml/min to 14.3 +/- 4.0 ml/min (P less than 0.01), and urinary kallikrein excretion from 165 +/- 156 mU to 432 +/- 220 mU (P less than 0.01). Natriuresis and potassium excretion also increased from 15.9 +/- 6.4 mEq to 33.4 +/- 10.9 mEq (P less than 0.01) and from 7.6 +/- 2.7 mEq to 14.0 +/- 5.4 mEq, (P less than 0.01), respectively, suggesting that in this situation aldosterone antagonism is not relevant to explain the diuretic effects of progesterone.