AdipocyteAdipocytes, also known as lipocytes and fat cells, are the cells that primarily compose adipose tissue, specialized in storing energy as fat. Adipocytes are derived from mesenchymal stem cells which give rise to adipocytes through adipogenesis. In cell culture, adipocyte progenitors can also form osteoblasts, myocytes and other cell types. There are two types of adipose tissue, white adipose tissue (WAT) and brown adipose tissue (BAT), which are also known as white and brown fat, respectively, and comprise two types of fat cells.
Stratified samplingIn statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when subpopulations within an overall population vary, it could be advantageous to sample each subpopulation (stratum) independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should define a partition of the population.
Sample spaceIn probability theory, the sample space (also called sample description space, possibility space, or outcome space) of an experiment or random trial is the set of all possible outcomes or results of that experiment. A sample space is usually denoted using set notation, and the possible ordered outcomes, or sample points, are listed as elements in the set. It is common to refer to a sample space by the labels S, Ω, or U (for "universal set"). The elements of a sample space may be numbers, words, letters, or symbols.
Brown adipose tissueBrown adipose tissue (BAT) or brown fat makes up the adipose organ together with white adipose tissue (or white fat). Brown adipose tissue is found in almost all mammals. Classification of brown fat refers to two distinct cell populations with similar functions. The first shares a common embryological origin with muscle cells, found in larger "classic" deposits. The second develops from white adipocytes that are stimulated by the sympathetic nervous system.
Chronic liver diseaseChronic liver disease in the clinical context is a disease process of the liver that involves a process of progressive destruction and regeneration of the liver parenchyma leading to fibrosis and cirrhosis. "Chronic liver disease" refers to disease of the liver which lasts over a period of six months. It consists of a wide range of liver pathologies which include inflammation (chronic hepatitis), liver cirrhosis, and hepatocellular carcinoma. The entire spectrum need not be experienced.
Fatty liver diseaseFatty liver disease (FLD), also known as hepatic steatosis, is a condition where excess fat builds up in the liver. Often there are no or few symptoms. Occasionally there may be tiredness or pain in the upper right side of the abdomen. Complications may include cirrhosis, liver cancer, and esophageal varices. There are two types of fatty liver disease: non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease. NAFLD is made up of simple fatty liver and non-alcoholic steatohepatitis (NASH).
Sample mean and covarianceThe sample mean (sample average) or empirical mean (empirical average), and the sample covariance or empirical covariance are statistics computed from a sample of data on one or more random variables. The sample mean is the average value (or mean value) of a sample of numbers taken from a larger population of numbers, where "population" indicates not number of people but the entirety of relevant data, whether collected or not. A sample of 40 companies' sales from the Fortune 500 might be used for convenience instead of looking at the population, all 500 companies' sales.
Sample size determinationSample size determination is the act of choosing the number of observations or replicates to include in a statistical sample. The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power.
SimulationA simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Often, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games.
Bone marrow adipose tissueBone marrow adipose tissue (BMAT), sometimes referred to as marrow adipose tissue (MAT), is a type of fat deposit in bone marrow. It increases in states of low bone density -osteoporosis, anorexia nervosa/ caloric restriction, skeletal unweighting such as that which occurs in space travel, and anti-diabetes therapies. BMAT decreases in anaemia, leukaemia, and hypertensive heart failure; in response to hormones such as oestrogen, leptin, and growth hormone; with exercise-induced weight loss or bariatric surgery; in response to chronic cold exposure; and in response to pharmacological agents such as bisphosphonates, teriparatide, and metformin.
Sampling (signal processing)In signal processing, sampling is the reduction of a continuous-time signal to a discrete-time signal. A common example is the conversion of a sound wave to a sequence of "samples". A sample is a value of the signal at a point in time and/or space; this definition differs from the term's usage in statistics, which refers to a set of such values. A sampler is a subsystem or operation that extracts samples from a continuous signal. A theoretical ideal sampler produces samples equivalent to the instantaneous value of the continuous signal at the desired points.
Observational errorObservational error (or measurement error) is the difference between a measured value of a quantity and its true value. In statistics, an error is not necessarily a "mistake". Variability is an inherent part of the results of measurements and of the measurement process. Measurement errors can be divided into two components: random and systematic. Random errors are errors in measurement that lead to measurable values being inconsistent when repeated measurements of a constant attribute or quantity are taken.
