Numerical resolution of CCD-curves.
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Biomedical subjects
Publications and source records attributed to S Wold.
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Some analytical functions were tested for goodness of fit to standard curves in radio-immunoassays of insulin (Hales & Randle, 1963). Letting a, b and c be parameters, and y the radioactivity measured at an insulin concentration of x, excellent fit was obtained with the function 1/(y+c)=ax+b. This function was associated with a smaller variance around y and a greater number of sign changes for the residuals (calculated radioactivity minus observed radioactivity) than any of the following: 1/y=ax(c)+b; y=ae(bx)+c; y=a+bx+cx(2)+dx(3). The mean number of sign changes of the residuals in 50 separate assays of mouse insulin was within the 95% confidence interval expected for a correct model. The function that was found to be applicable to assays of mouse, human and ox insulins should be useful in routines for computer processing of insulin assay data and may also prove applicable to other radio-immunoassays.
The effects of thioridazine and thiothixene were studied by a double-blind technique on 40 schizophrenic patients. The doses were adjusted for optimal clinical and therapeutic effects and side effects were rated after three and eight weeks of treatment. No statistically significant differences were observed between the two drugs or between either of the two drugs and the previous medication. Plasma levels were estimated by a fluorometric technique after three and eight weeks of treatment. No correlation was found between plasma levels and clinical effects for either thioridazine or thiothixene. Plasma levels of both drugs were clearly correlated to dosage after three weeks of treatment. After eight weeks this correlation persisted for thioridazine but not for thiothixene. By that time plasma levels of thiothixene had decreased to about 30 per cent of the initial value, indicating strong enzyme induction.
Statistical experimental design provides an efficient approach for selecting the building blocks to span the structural space and increase the information content in a combinatorial library. A set of renin-inhibitors, hexapeptoids, is used to illustrate the approach. Multivariate quantitative structure-activity relationships (MQSARs) were developed relating renin inhibition to the peptoid sequences variation, parametrized by the z-scales. By using the information from the models, the number of building block sets could be reduced from six to three. Using a statistical molecular design (SMD) reduces the number of compounds from more than 100,000 down to 90. A second SMD was used for comparison, based on less prior knowledge. This gave a reduction from over 2 billion to 120 compounds.
When X and Y are multivariate, the two-block partial least squares (PLS) method is often used. In this paper, we outline an extension addressing a special case of the three-block (X/Y/Z) problem, where Z sits "under" Y. We have called this approach three-block bi-focal PLS (3BIF-PLS). It views the X/Y relationship as the dominant problem, and seeks to use the additional information in Z in order to improve the interpretation of the Y-part of the X/Y association. Two data sets are used to illustrate 3BIF-PLS. Example I relates to single point mutants of haloalkane dehalogenase from Sphingomonas paucimobilis UT26 and their ability to transform halogenated hydrocarbons, some of which are found as organic pollutants in soil. Example II deals with soil remediation capability of bacteria. Whole bacterial communities are monitored over time using "DNA-fingerprinting" technology to see how pollution affects population composition. Since the data sets are large, hierarchical multivariate modelling is invoked to compress data prior to 3BIF-PLS analysis. It is concluded that the 3BIF-PLS approach works well. The paper contains a discussion of pros and cons of the method, and hints at further developmental opportunities.