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Percoll is a reagent consisting of colloidal silica particles used in cell biology and other laboratory settings. It was first formulated by Pertoft and colleagues, [2] and commercialized by Pharmacia Fine Chemicals. [3] Percoll is used for the isolation of cells, organelles, or viruses by density centrifugation.
Historically a cesium chloride (CsCl) solution was often used, but more commonly used density gradients are sucrose or Percoll.This application requires a solution with high density and yet relatively low viscosity, and CsCl suits it because of its high solubility in water, high density owing to the large mass of Cs, as well as low viscosity and high stability of CsCl solutions.
Differences between differential and density gradient centrifugation [ edit ] The difference between differential and density gradient centrifugation techniques is that the latter method uses solutions of different densities (e.g. sucrose , Ficoll , Percoll ) or gels through which the sample passes.
The curl of the gradient of any continuously twice-differentiable scalar field (i.e., differentiability class) is always the zero vector: =. It can be easily proved by expressing ∇ × ( ∇ φ ) {\displaystyle \nabla \times (\nabla \varphi )} in a Cartesian coordinate system with Schwarz's theorem (also called Clairaut's theorem on equality ...
An electrochemical gradient is a gradient of electrochemical potential, usually for an ion that can move across a membrane. The gradient consists of two parts: The chemical gradient, or difference in solute concentration across a membrane. The electrical gradient, or difference in charge across a membrane.
Temperature gradient gel electrophoresis (TGGE) and denaturing gradient gel electrophoresis (DGGE) are forms of electrophoresis which use either a temperature or chemical gradient to denature the sample as it moves across an acrylamide gel. TGGE and DGGE can be applied to nucleic acids such as DNA and RNA, and (less commonly) proteins.
It is a variant of the biconjugate gradient method (BiCG) and has faster and smoother convergence than the original BiCG as well as other variants such as the conjugate gradient squared method (CGS). It is a Krylov subspace method. Unlike the original BiCG method, it doesn't require multiplication by the transpose of the system matrix.
Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2). In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-semidefinite.