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Sodium Thymolphthalein Monophosphate: A New Acid Phosphatase Substrate with Greater Specificity for the Prostatic Enzyme in Serum

Roy, A V, Brower, Mary E, Hayden, Jean E·1971·Clinical Chemistry

Abstract

We describe the use of sodium thymolphthalein monophosphate as a substrate for measuring acid phosphatase activity in serum. Thymolphthalein is liberated in the reaction and is conveniently measured by increasing the pH of the medium, which produces a color and also stops the hydrolysis. Optimal conditions for enzymatic activity were defined for use in the final assay system. Purified acid phosphatase isoenzymes from various human tissues and sera from patients with nonprostatic diseases most likely to affect serum acid phosphatase activity were used to show that the new method is more specific for the prostatic enzyme than other commonly used procedures for acid phosphatase. Other advantages include simplicity, good sensitivity over a wide range of activity, high precision, zero-order kinetics to about 200 times the upper limit of normal, easy standardization by a pure standard, and reagent stability.

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Metadata

Authors
Roy, A. V., Brower, M. E., & Hayden, J. E.
Venue
Clinical Chemistry
Published
1971-11-01
Volume
17
Issue
11
Pages
1093-1102
ISSN
  • 0009-9147 (ISSN-L)
  • 1530-8561
OpenAlex
W1899295031
Cited by
210
References
0
FWCI
1.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Sodium Thymolphthalein Monophosphate: A New Acid Phosphatase Substrate with Greater Specificity for the Prostatic Enzyme in Serum. https://app.cochat.ai/papers/10.1093/clinchem/17.11.1093
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Roy, A. V., Brower, M. E., & Hayden, J. E. (1971). Sodium Thymolphthalein Monophosphate: A New Acid Phosphatase Substrate with Greater Specificity for the Prostatic Enzyme in Serum. Clinical Chemistry. https://doi.org/10.1093/clinchem/17.11.1093

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.