Breast cancer detection by Michaelis-Menten constants via linear programming

David Blokh, Elena Afrimzon, Ilia Stambler, Eden Korech, Yana Shafran, Naomi Zurgil, Mordechai Deutsch

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The Michaelis-Menten constants (Km and Vmax) operated by linear programming, were employed for detection of breast cancer. The rate of enzymatic hydrolysis of fluorescein diacetate (FDA) in living peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, was assessed by measuring the fluorescence intensity (FI) in individual cells under incubation with either the mitogen phytohemagglutinin (PHA) or with tumor tissue, as compared to control. The suggested model diagnoses three conditions: (1) the subject is diseased, (2) the diagnosis is uncertain, and (3) the subject is not diseased. Out of 50 subjects tested, 44 were diagnosed correctly, in 5 cases the diagnosis was not certain, and 1 subject was diagnosed incorrectly.

Original languageEnglish
Pages (from-to)210-213
Number of pages4
JournalComputer Methods and Programs in Biomedicine
Volume85
Issue number3
DOIs
StatePublished - Mar 2007

Bibliographical note

Funding Information:
This research was supported by the Komen Foundation and by the Horowitz Foundation.

Funding

This research was supported by the Komen Foundation and by the Horowitz Foundation.

FundersFunder number
Komen Foundation
Horowitz Foundation for Social Policy

    Keywords

    • Breast cancer (BC)
    • Linear programming
    • Michaelis-Menten constants (K and V)
    • Peripheral blood mononuclear cells (PBMC)

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