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The chromatography technique was first invented in 1901 by Michael S. Tswett, a Russian botanist, to separate plant pigments using organic solvents. Further, in 1941, Archer John Porter Martin and R. L. M. Synge modified the technique by packing silica gel into a column. A mixture of amino acids was then separated on the packed column using chloroform and water mixture as the mobile phase. This was the first report on column chromatography. At present, column chromatography is a widely used...
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The stability and compatibility of column material with samples are crucial for efficient purification in chromatographic techniques. Various operating parameters such as pH, temperature, or solvent affect the packing of the column material, thereby determining the purification efficiency. The choice of column material also plays an essential role in deciding the operating parameters and can be modified based on the proteins that need to be purified.
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Cochran's Q Test is a nonparametric statistical test used to determine if there are potential differences in the outcomes of three or more related groups on a binary (yes/no) or dichotomous outcome. It is essentially an extension of the McNemar Test, which is limited to two related samples - Cochran's Q test can handle three or more related samples, making it more versatile in scenarios where subjects are measured under multiple conditions. The test statistic follows a Chi-Square...
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Designing columns to withstand eccentric loads is a critical aspect of structural engineering, ensuring structures can support off-center loads without failure. This design process must account for the additional normal stresses introduced by eccentric loading, which can significantly influence a column's stress distribution and overall stability. An eccentric load applied to a column induces normal stresses that can be conceptualized as a combination of stresses due to an equivalent...
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The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
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Cochrane column

Taryn Young1, Charles S Wiysonge1, Anel Schoonees2

  • 1Centre for Evidence-based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa. E-mail: charlesw@sun.ac.za. Website: www.sun.ac.za/cebhc.

International Journal of Epidemiology
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No abstract available in PubMed .

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