| D007515 |
Islets of Langerhans |
Irregular microscopic structures consisting of cords of endocrine cells that are scattered throughout the PANCREAS among the exocrine acini. Each islet is surrounded by connective tissue fibers and penetrated by a network of capillaries. There are four major cell types. The most abundant beta cells (50-80%) secrete INSULIN. Alpha cells (5-20%) secrete GLUCAGON. PP cells (10-35%) secrete PANCREATIC POLYPEPTIDE. Delta cells (~5%) secrete SOMATOSTATIN. |
Islands of Langerhans,Islet Cells,Nesidioblasts,Pancreas, Endocrine,Pancreatic Islets,Cell, Islet,Cells, Islet,Endocrine Pancreas,Islet Cell,Islet, Pancreatic,Islets, Pancreatic,Langerhans Islands,Langerhans Islets,Nesidioblast,Pancreatic Islet |
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| D008297 |
Male |
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Males |
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| D011237 |
Predictive Value of Tests |
In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. |
Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive |
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| D011446 |
Prospective Studies |
Observation of a population for a sufficient number of persons over a sufficient number of years to generate incidence or mortality rates subsequent to the selection of the study group. |
Prospective Study,Studies, Prospective,Study, Prospective |
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| D012044 |
Regression Analysis |
Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. |
Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions |
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| D002648 |
Child |
A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL. |
Children |
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| D002675 |
Child, Preschool |
A child between the ages of 2 and 5. |
Children, Preschool,Preschool Child,Preschool Children |
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| D003922 |
Diabetes Mellitus, Type 1 |
A subtype of DIABETES MELLITUS that is characterized by INSULIN deficiency. It is manifested by the sudden onset of severe HYPERGLYCEMIA, rapid progression to DIABETIC KETOACIDOSIS, and DEATH unless treated with insulin. The disease may occur at any age, but is most common in childhood or adolescence. |
Diabetes Mellitus, Brittle,Diabetes Mellitus, Insulin-Dependent,Diabetes Mellitus, Juvenile-Onset,Diabetes Mellitus, Ketosis-Prone,Diabetes Mellitus, Sudden-Onset,Diabetes, Autoimmune,IDDM,Autoimmune Diabetes,Diabetes Mellitus, Insulin-Dependent, 1,Diabetes Mellitus, Type I,Insulin-Dependent Diabetes Mellitus 1,Juvenile-Onset Diabetes,Type 1 Diabetes,Type 1 Diabetes Mellitus,Brittle Diabetes Mellitus,Diabetes Mellitus, Insulin Dependent,Diabetes Mellitus, Juvenile Onset,Diabetes Mellitus, Ketosis Prone,Diabetes Mellitus, Sudden Onset,Diabetes, Juvenile-Onset,Diabetes, Type 1,Insulin Dependent Diabetes Mellitus 1,Insulin-Dependent Diabetes Mellitus,Juvenile Onset Diabetes,Juvenile-Onset Diabetes Mellitus,Ketosis-Prone Diabetes Mellitus,Sudden-Onset Diabetes Mellitus |
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| D005260 |
Female |
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Females |
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| D006801 |
Humans |
Members of the species Homo sapiens. |
Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man |
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