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Multicomponent analysis for alkaline phosphatase isoenzyme determination by multiple linear regression

C R Tillyer1, S Rakhorst, C M Colley

  • 1Department of Chemical Pathology, Royal Marsden Hospital, London, UK.

Clinical Chemistry
|May 1, 1994
PubMed
Summary
This summary is machine-generated.

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This study introduces a multicomponent analysis using inhibitors to determine alkaline phosphatase (EC 3.1.3.1) isoenzymes. The optimal method combines levamisole, phenylalanine, and heat inhibition for accurate bone, hepatic, intestinal, and placental isoenzyme prediction.

Area of Science:

  • Biochemistry
  • Enzymology

Background:

  • Alkaline phosphatase (EC 3.1.3.1) isoenzymes play crucial roles in various physiological processes.
  • Accurate determination of these isoenzymes is essential for diagnosing certain diseases.

Purpose of the Study:

  • To develop and validate a multicomponent analysis method for quantifying alkaline phosphatase isoenzymes in serum.
  • To identify an optimal set of inhibitors and conditions for precise isoenzyme determination.

Main Methods:

  • Utilized multiple linear regression analysis to determine inhibition coefficients.
  • Compared enzyme activities in the presence of inhibitors with electrophoretically determined isoenzyme activities.
  • Evaluated various combinations of inhibitors (levamisole, phenylalanine) and heat treatments (56°C, 65°C).

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Main Results:

  • The optimal predictive system included levamisole, phenylalanine, and dual-temperature heat inhibition.
  • This system effectively determined bone, hepatic, intestinal, and placental isoenzymes.
  • Treating hepatic isoenzyme as separate liver and macromolecular fractions worsened prediction accuracy.

Conclusions:

  • Multicomponent analysis with specific inhibitors offers a viable method for alkaline phosphatase isoenzyme determination.
  • The chosen inhibitor set and heat conditions provide reliable quantification.
  • Inaccuracies in electrophoretic methods may impact the precision of isoenzyme prediction.