Blokh D and Stambler I., 2014. Estimation of Heterogeneity in Diagnostic Parameters of Age-related Diseases. Aging and Disease, 5, 218-225. 

The heterogeneity of parameters is a ubiquitous biological phenomenon, with critical implications for biological systems functioning in normal and diseased states. We developed a method to estimate the level of objects set heterogeneity with reference to particular parameters and applied it to type II diabetes and heart disease, as examples of age-related systemic dysfunctions. The Friedman test was used to establish the existence of heterogeneity. The Newman-Keuls multiple comparison method was used to determine clusters. The normalized Shannon entropy was used to provide the quantitative evaluation of heterogeneity. There was obtained an estimate for the heterogeneity of the diagnostic parameters in healthy subjects, as well as in heart disease and type II diabetes patients, which was strongly related to their age. With aging, as with the diseases, the level of heterogeneity (entropy) was reduced, indicating a formal analogy between these phenomena. The similarity of the patterns in aging and disease suggested a kind of “early aging” of the diseased subjects, or alternatively a “disease-like” aging process, with reference to these particular parameters. The proposed method and its validation on the chronic age-related disease samples may support a way toward a formal mathematical relation between aging and chronic diseases and a formal definition of aging and disease, as determined by particular heterogeneity (entropy) changes.

Blokh D and Stambler I., 2015. Information theoretical analysis of aging as a risk factor for heart disease. Aging and Disease, 6, 196-207.

We estimate the weight of various risk factors in heart disease, and the particular weight of age as a risk factor, individually and combined with other factors. To establish the weights we use the information theoretical measure of normalized mutual information that permits determining both individual and combined correlation of diagnostic parameters with the disease status. The present information theoretical methodology takes into account the non-linear correlations between the diagnostic parameters, as well as their non-linear changes with age. Thus it may be better suited to analyze complex biological aging systems than statistical measures that only estimate linear relations. We show that individual parameters, including age, often show little correlation with heart disease. Yet in combination, the correlation improves dramatically. For diagnostic parameters specific for heart disease the increase in the correlative capacity thanks to the combination of diagnostic parameters, is less pronounced than for the less specific parameters. Age shows the highest influence on the presence of disease among the non-specific parameters and the combination of age with other diagnostic parameters substantially improves the correlation with the disease status. Hence age is considered as a primary “metamarker” of aging-related heart disease, whose addition can improve diagnostic capabilities. In the future, this methodology may contribute to the development of a system of biomarkers for the assessment of biological/physiological age, its influence on disease status, and its modifications by therapeutic interventions.

Blokh D and Stambler I, 2015. Applying information theory analysis for the solution of biomedical data processing problems. American Journal of Bioinformatics, 3 (1), 17-29.  

The use of information-theoretical methods can be highly valuable for the solution of biomedical data processing problems. Some of the problems that can be solved by those methods include: The assessment of the influence of diagnostic parameters, biomarkers and risk factors, on the emergence of disease; the discretization of diagnostic parameters; the analysis of a combined influence of a group of parameters; the partition of a group of diagnostic parameters according to the amount of diagnostic information contained in those parameters; the analysis of the parameters' heterogeneity or variability and more. To illustrate the solution of those problems, we use a data base on diabetes patients. There are grounds to believe that an increasing application of information-theoretical methodologies in biomedical research will lead to significant practical dividends for diagnosis and therapy.

Blokh D and Stambler I, 2016. The application of information theory for the research of aging and aging-related diseases. Progress in Neurobiology, doi:10.1016/j.pneurobio.2016.03.005,

This article reviews the application of information-theoretical analysis, employing measures of entropy and mutual information, for the study of aging and aging-related diseases. The research of aging and aging-related diseases is particularly suitable for the application of information theory methods, as aging processes and related diseases are multi-parametric, with continuous parameters coexisting alongside discrete parameters, and with the relations between the parameters being as a rule non-linear. Information theory provides unique analytical capabilities for the solution of such problems, with unique advantages over common linear biostatistics. Among the age-related diseases, information theory has been used in the study of neurodegenerative diseases (particularly using EEG time series for diagnosis and prediction), cancer (particularly for establishing individual and combined cancer biomarkers), diabetes (mainly utilizing mutual information to characterize the diseased and aging states), and heart disease (mainly for the analysis of heart rate variability). Few works have employed information theory for the analysis of general aging processes and frailty, as underlying determinants and possible early preclinical diagnostic measures for aging-related diseases. Generally, the use of information-theoretical analysis permits not only establishing the (non-linear) correlations between diagnostic or therapeutic parameters of interest, but may also provide a theoretical insight into the nature of aging and related diseases by establishing the measures of variability, adaptation, regulation or homeostasis, within a system of interest. It may be hoped that the increased use of such measures in research may considerably increase diagnostic and therapeutic capabilities and the fundamental theoretical mathematical understanding of aging and disease.

Blokh D, Afrimzon E, Stambler I, Korech E, Shafran Y, Zurgil N, Deutsch M, 2006. Breast cancer detection by Michaelis-Menten constants via linear programming. Computer Methods and Programs in Biomedicine, 85, 210-213.

The Michaelis-Menten constants (K(m) and V(max)) 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.

Blokh D, Stambler I,  Afrimzon E, Shafran Y, Korech E, Sandbank J, Orda R, Zurgil N, Deutsch M., 2007. The information-theory analysis of Michaelis–Menten constants for detection of breast cancer. Cancer Detection and Prevention, 31, 489-498.

BACKGROUND: The Michaelis-Menten constants (K(m) and V(max)) operated by the Information Theory were employed for detection of breast cancer.
METHODS: The rate of enzymatic hydrolysis of fluorescein diacetate (FDA) in live 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 data were processed by the Information Theory to determine the parameters and test conditions, which can best discriminate between the different groups. The normalized mutual information (uncertainty coefficients) was used as the measure of correlation/discrimination.
RESULTS: An estimated general correlation was established between the K(m)/V(max) parameters and the examined patterns in the different bioassays. The information-theoretical analysis revealed the relative diagnostic value of each parameter.
CONCLUSION: It was found that K(m) and V(max) as individual parameters show relatively low correlations with the presence or absence of disease, yet in combination often provide a good diagnostic measure. Based on the relative diagnostic values of each parameter, a diagnostic decision making rule was constructed. The diagnostic rule provided correct diagnosis for 37 out of 40 subjects.

Blokh D, Zurgil N, Stambler I, Afrimzon E, Shafran Y, Korech E, Sandbank J, Deutsch M., 2008. An information-theoretical model for breast cancer detection. Methods of Information in Medicine, 47, 322-327.

OBJECTIVES: Formal diagnostic modeling is an important line of modern biological and medical research. The construction of a formal diagnosticmodel consists of two stages: first, the estimation of correlation between model parameters and the disease under consideration; and second, the construction of a diagnostic decision rule using these correlation estimates. A serious drawback of current diagnostic models is the absence of a unified mathematical methodological approach to implementing these two stages. The absence of a unified approach makes the theoretical/biomedical substantiation of diagnostic rules difficult and reduces the efficacy of actual diagnostic model application.
METHODS: The present study constructs a formal model for breast cancer detection. The diagnostic model is based on information theory. Normalized mutual information is chosen as the measure of relevance between parameters and the patterns studied. The "nearest neighbor" rule is utilized for diagnosis, while the distance between elements is the weighted Hamming distance. The model concomitantly employs cellular fluorescence polarization as the quantitative input parameter and cell receptor expression as qualitative parameters.
RESULTS: Twenty-four healthy individuals and 34 patients (not including the subjects analyzed for the model construction) were tested by themodel. Twenty-three healthy subjects and 34 patients were correctly diagnosed.
CONCLUSIONS: The proposed diagnostic model is an open one, i.e. it can accommodate new additional parameters, which may increase its effectiveness.

Blokh D, Stambler I, Afrimzon E, Platkov M, Shafran Y, Korech E, Sandbank J, Zurgil N, Deutsch M., 2009. Comparative analysis of cell parameter groups for breast cancer detection. Computer Methods and Programs in Biomedicine, 94, 239-249.

We present a method for the comparative analysis of parameter groups according to their correlation to disease. The theoretical basis of the proposed method is Information Theory and Nonparametric Statistics. Normalized mutual information is used as the measure of correlation between parameters, and statistical conclusions are based on ranking. The fluorescence polarization (FP) parameter is considered as the principal diagnostic characteristic. The FP was measured in fluorescein diacetate (FDA)-stained individual peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, under different stimulation conditions: by tumor tissue, the mitogen phytohemagglutinin (PHA) or without the stimulants. The FP parameters were grouped according to their correlation with breast cancer. It was established that the greatest difference between cells of BC patients and healthy subjects is found in the PHA test (parameter P1).

Blokh D, 2013. Information-Theory Analysis of Cell Characteristics in Breast Cancer Patients. International Journal on Bioinformatics & Biosciences (IJBB), 3 (1).

A problem of selecting a subset of parameters containing a maximum amount of information on all parameters of a given set is considered. The proposed method of selection is based on the informationtheory analysis and rank statistics. The uncertainty coefficient (normalized mutual information) is used as a measure of information about one parameter contained in another parameter. The most informative characteristics are selected from the set of cytological characteristics of breast cancer patients.

Stambler I, 2015. Stop Aging Disease! ICAD 2014. Aging and Disease, 6 (2), 76-94

On November 1–2, 2014, there took place in Beijing, China, the first International Conference on Aging and Disease (ICAD 2014) of the International Society on Aging and Disease (ISOAD). The conference participants presented a wide and exciting front of work dedicated to amelioration of aging-related conditions, ranging from regenerative medicine through developing geroprotective substances, elucidating a wide range of mechanisms of aging and aging-related diseases, from energy metabolism through genetics and immunomodulation to systems biology. The conference further emphasized the need to intensify and support research on aging and aging-related diseases to provide solutions for the urgent health challenges of the aging society.

Jin K, Simpkins JW, Ji X, Leis M and Stambler I. 2015. The Critical Need to Promote Research of Aging and Aging-related Diseases to Improve Health and Longevity of the Elderly Population. Aging and Disease, 6(1), 1-5

Due to the aging of the global population and the derivative increase in aging-related non-communicable diseases and their economic burden, there is an urgent need to promote research on aging and aging-related diseases as a way to improve healthy and productive longevity for the elderly population. To accomplish this goal, we advocate the following policies: 1) Increasing funding for research and development specifically directed to ameliorate degenerative aging processes and to extend healthy and productive lifespan for the population; 2) Providing a set of incentives for commercial, academic, public and governmental organizations to foster engagement in such research and development; and 3) Establishing and expanding coordination and consultation structures, programs and institutions involved in aging-related research, development and education in academia, industry, public policy agencies and at governmental and supra-governmental levels.