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Bunimovich-Mendrazitsky, S.

Publications and source records attributed to Bunimovich-Mendrazitsky, S..

2 recordsLinked to original sources

Generic Approach For Mathematical Model of Multi-Strain Pandemics

Pandemics with multi-strain have become a major concern. We introduce a new model for assessing the connection between multi-strain pandemic and the mortality rate, basic reproduction number, and the maximum of infected individuals. The proposed model provides a general mathematical approach for representing multi-strain pandemics, generalizing for an arbitrary number of strains. We show the proposed model fits well with epidemiological historical data world health over a long period. From a theoretical point of view, we show that the increasing number of strains increases logarithmically the maximum number of infected individuals and the mean mortality rate. Moreover, the mean basic reproduction number is statistically identical to the single, most aggressive strain pandemic for multi-strain pandemics.

bioinformatics↗

Clinically Relevant Mathematical Model for the BCG-based Treatment Of Type 1 Diabetes

This work introduces a model of immunotherapy treatment, namely the Bacillus Calmette-Guerin (BCG) vaccine, of type 1 diabetes (T1D). The model takes into consideration a clinically relevant interaction network between multiple immune cells and compartments. A set of ordinary differential equations (ODEs) is introduced to capture the connectivity between these variables and clinical presentation of the disease. Four subsets of the T1D patients and healthy controls that exhibit normal and high-level glucose consumption are evaluated. The results that obtained for mice, suggest that BCG treatment of the T1D patients that follow healthy eating habits normalizes glucose to levels observed in non-diabetic controls. Furthermore, glucose consumption profoundly influences disease progression. The stable equilibrium state with constant glucose levels is not attainable without repeated BCG treatment. This outcome suggests that immunotherapy may modulate molecular and cellular manifestations of the disease but it does not eliminate T1D. Of note, our data indicate that the BCG immunotherapy treatment may benefit healthy controls on a high-glucose diet. One may speculate the preventive BCG treatment to provide long-term health benefits in this specific cohort. Author summaryWe proposed a clinically relevant mathematical model of Bacillus Calmette-Guerin (BCG) based immunotherapy for type 1 diabetes (T1D) treatment. The model shows that BCG treatment is able to delay the T1D effects and to provide long-term health benefits while it may modulate molecular and cellular manifestations of the disease but it does not eliminate T1D. The main advantage of the proposed model is the ability to personalize the treatment protocol according to the patients metabolism and diet.

bioinformatics↗