Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0018799 (heart disease)
 34,133 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Plasma lipoprotein cholesterol and triglyceride levels were measured in 24 obese not-insulin dependent Pima Indian diabetics and 9 obese nondiabetic controls before and after 1-8 months on a 500 calorie diet. The diabetics were divided into 3 groups--severe, recent onset (n = 10), severe long-term (n = 6), and borderline (n = 8). The diet regimen resulted in weight loss and improved glucose tolerance in all of the diabetics, and insulin secretion increased in the 2 groups of severe diabetics. After the period of weight loss, total plasma cholesterol had declined greater than 20%, and LDL cholesterol decreased 25% in all diabetic groups and in the controls. In all diabetic groups, HDL cholesterol did not decline; therefore the ratio of HDL/LDL cholesterol after diet therapy was significantly increased. In the controls HDL cholesterol declined with weight loss, and the distribution of HDL/LDL cholesterol remained constant. Plasma and VLDL triglyceride levels decreased in all groups in those with initial triglyceride levels greater than 150 mg/dl. The results indicate that weight loss in not-insulin dependent diabetics not only improves glucose tolerance, but also lowerss plasma lipids and reverses the dyslipoproteinemia often associated with this disorder. This may influence the risk of arteriosclerotic heart disease in these individuals.
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PMID:Changes in plasma lipoproteins accompanying diet therapy in obese diabetics. 22 83

As part of an ongoing epidemiologic study, the death rate and causes of death during 1975 through 1984 were determined in Pima Indians who resided in the Gila River Indian Community (GRIC) in 1965 and later. Death certificates were available for 677 of the 681 deaths. In 78% of the deaths, the underlying cause recorded on the death certificate agreed with the cause determined after review of all available relevant records. The age- and sex-adjusted average annual death rate for the GRIC population (1639/100,000) was 1.9 times (95% CI 1.7-2.0) the 1980 rate for the U.S. all races (878/100,000). In Pima males, whose death rate was substantially higher than that of Pima females, the age-adjusted death rate was 2.3 times that in U.S. males, all races. Moreover among males 25-34 years of age, the Pima death rate was 6.6 times that for the U.S. all races. Diseases of the heart and malignant neoplasms caused 59% of U.S. deaths in 1980, but only 19% of GRIC deaths. By contrast, the age- and sex-adjusted mortality rate in the GRIC Pima was 5.9 times the rate of the U.S. all races for accidents, 6.5 times for cirrhosis, 7.4 times for homicide, 4.3 times for suicide, and 11.9 times for diabetes. Tuberculosis and coccidioidomycosis were important causes of death in the Pima, for whom infectious diseases was the tenth leading cause of death. The findings indicate that programs to improve the adverse mortality experience of the GRIC population should emphasize factors related to fatal accidents, alcoholic cirrhosis, homicide, suicide, diabetes mellitus, and infectious diseases. Young Pimas, especially the males, should be the primary focus of such preventive efforts. These findings and recommendations probably apply to many Native American populations.
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PMID:Adverse mortality experience of a southwestern American Indian community: overall death rates and underlying causes of death in Pima Indians. 224 58

Pima Indians have a high prevalence of hyperinsulinemia, obesity, and diabetes, but they have low plasma cholesterol levels, reduced low density lipoprotein synthesis, and little arteriosclerotic heart disease. To investigate lipoprotein metabolism further in this group, very low density lipoprotein (VLDL) metabolism was studied, using [3H]glycerol as an endogenous precursor of triglyceride (TG) synthesis, in 15 obese Pima nondiabetic males and compared to that of 10 obese and 13 normal weight, normolipidemic, nondiabetic Caucasian males. The resultant kinetic data were analyzed using a multicompartmental model which includes two pathways for VLDL-TG synthesis and a process of stepwise delipidation for VLDL catabolism. As compared to obese Caucasians, the obese Pimas had a lower rate of VLDL-TG synthesis, and a lower proportion of slow pathway for synthesis. The fractional catabolic rate in the Pimas was higher than in either Caucasian group, a larger proportion of VLDL-TG was delipidized at each step, and particle residence time was shorter. When the relation between VLDL-TG metabolism and plasma insulin was examined, plasma insulin levels in the Pima were not correlated with VLDL-TG synthetic rates, catabolic rates, or plasma pools. On the other hand VLDL-TG synthetic rates were correlated with plasma free fatty acid levels. Thus, in this population with low plasma lipids and reduced arteriosclerotic heart disease, VLDL-TG synthesis is low, VLDL-TG catabolism is accelerated, and VLDL pools appear to be insensitive to the influence of body weight and hyperinsulinemia.
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PMID:Studied of very low density lipoprotein triglyceride metabolism in an obese population with low plasma lipids: lack of influence of body weight or plasma insulin. 700 43

For complex database prediction problems such as medical diagnosis, the ARTMAP-IC neural network adds distributed prediction and category instance counting to the basic fuzzy ARTMAP system. For the ARTMAP match tracking algorithm, which controls search following a predictive error, a new version facilitates prediction with sparse or inconsistent data. Compared to the original match tracking algorithm (MT+), the new algorithm (MT-) better approximates the real-time network differential equations and further compresses memory without loss of performance. Simulations examine predictive accuracy on four medical databases: Pima Indian diabetes, breast cancer, heart disease, and gall bladder removal. ARTMAP-IC results are equal to or better than those of logistic regression, K nearest neighbour (KNN), the ADAP preceptron, multisurface pattern separation, CLASSIT, instance-based (IBL), and C4. ARTMAP dynamics are fast, stable, and scalable. A voting strategy improves prediction by training the system several times on different orderings of an input set. Voting, instance counting, and distributed representations combine to form confidence estimates for competing predictions.
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PMID:ARTMAP-IC and medical diagnosis: Instance counting and inconsistent cases. 1266 41

The conventional aetiological model of obesity and diabetes proposes a genetic predisposition and a precipitation by an unhealthy adult lifestyle. This hypothesis was challenged by David Barker who proposed that the intrauterine environment influences the risk of non-communicable diseases (NCDs). The original idea was based on fetal undernutrition because lower birth weight was associated with a higher risk of diabetes and heart disease. However, soon it was clear that the association was U shaped, and that the increased risk in large babies was driven by maternal obesity and diabetes. A number of human and animal studies have refined our ideas of 'fetal programming', which is now thought to be related to acquired chemical changes in DNA (methylation), histones (acetylation and other) and the role of non-coding miRNAs. Maternal nutritional disturbances are the major programming stimulus, in addition to a deranged metabolism, infections, maternal stress, extreme atmospheric temperature, etc. The first demonstration of a link between fetal 'starvation' and future ill-health was in the Dutch Hunger Winter studies. In the prospective Pune Maternal Nutrition Study, we found that small and thin Indian babies were more adipose compared to larger English babies, and their higher risk of future diabetes was reflected in higher insulin and leptin and lower adiponectin concentrations in the cord blood. This phenotype was partly related to a deranged 1-carbon metabolism due to an imbalance in vitamin B12 (low) and folate (high) nutrition, which was also related to insulin resistance in the offspring. Maternal obesity and diabetes have made an increasing contribution to childhood obesity and diabetes at a young age. This was prominently shown in Pima Indians but is now obvious in all other populations. The best window of opportunity to prevent fetal programming of NCDs is in the periconceptional period. This is the period when gametogenesis, fertilisation, implantation, embryogenesis and placentation occur. Improving the nutrition and the health of young girls could make a substantial contribution to reducing the rapidly rising epidemic of NCDs in the world. This is referred to as 'primordial' prevention.
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PMID:Transmission of obesity-adiposity and related disorders from the mother to the baby. 2505 1

Accurate medical disease diagnosis is considered to be an important classification problem. The main goal of the classification process is to determine the class to which a certain pattern belongs. In this article, a new classification technique based on a combination of The Teaching Learning-Based Optimization (TLBO) algorithm and Fuzzy Wavelet Neural Network (FWNN) with Functional Link Neural Network (FLNN) is proposed. In addition, the TLBO algorithm is utilized for training the new hybrid Functional Fuzzy Wavelet Neural Network (FFWNN) and optimizing the learning parameters, which are weights, dilation and translation. To evaluate the performance of the proposed method, five standard medical datasets were used: Breast Cancer, Heart Disease, Hepatitis, Pima-Indian diabetes and Appendicitis. The efficiency of the proposed method is evaluated using 5-fold cross-validation and 10-fold cross-validation in terms of mean square error (MSE), classification accuracy, running time, sensitivity, specificity and kappa. The experimental results show that the efficiency of the proposed method for the medical classification problems is 98.309%, 91.1%, 91.39%, 88.67% and 93.51% for the Breast Cancer, Heart Disease, Hepatitis, Pima-Indian diabetes and Appendicitis datasets, respectively, in terms of accuracy after 30 runs for each dataset with low computational complexity. In addition, it has been observed that the proposed method has efficient performance compared with the performance of other methods found in the related previous studies.
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PMID:Utilizing hybrid functional fuzzy wavelet neural networks with a teaching learning-based optimization algorithm for medical disease diagnosis. 3135 92