Modeling the transmission phenomena of water-borne disease with non-singular and non-local kernel

Computational techniques to monitoring fractional order type-1 diabetes mellitus model for feedback design of artificial pancreas

BACKGROUND AND OBJECTIVES

In this paper, we developed a significant class of control issues regulated by nonlinear fractal order systems with input and output signals, our goal is to design a direct transcription method with impulsive instant order. Recent advances in the artificial pancreas system provide an emerging treatment option for type 1 diabetes. The performance of the blood glucose regulation directly relies on the accuracy of the glucose-insulin modeling. This work leads to the monitoring and assessment of comprehensive type-1 diabetes mellitus for controller design of artificial panaceas for the precision of the glucose-insulin glucagon in finite time with Caputo fractional approach for three primary subsystems.

METHODS

For the proposed model, we admire the qualitative analysis with equilibrium points lying in the feasible region. Model satisfied the biological feasibility with the Lipschitz criteria and linear growth is examined, considering positive solutions, boundedness and uniqueness at equilibrium points with Leray-Schauder results under time scale ideas. Within each subsystem, the virtual control input laws are derived by the application of input to state theorems and Ulam Hyers Rassias.

RESULTS

Chaotic Relation of Glucose insulin glucagon compartmental in the feasible region and stable in finite time interval monitoring is derived through simulations that are stable and bounded in the feasible regions. Additionally, as blood glucose is the only measurable state variable, the unscented power-law kernel estimator appropriately takes into account the significant problem of estimating inaccessible state variables that are bound to significant values for the glucose-insulin system. The comparative results on the simulated patients suggest that the suggested controller strategy performs remarkably better than the compared methods.

CONCLUSION

In the model under investigation, parametric uncertainties are identified since the glucose, insulin, and glucagon system's parameters are accurately measured numerically at different fractional order values. In terms of algorithm resilience and Caputo tracking in the presence of glucagon and insulin intake disturbance to maintain the glucose level. A comprehensive analysis of numerous difficult test issues is conducted in order to offer a thorough justification of the planned strategy to control the type 1 diabetes mellitus with designed the artificial pancreas.

Structural basis for substrate recognition by a S-adenosylhomocysteine hydrolase Lpg2021 from Legionella pneumophila

S-Adenosyl-l-homocysteine hydrolase (SAHH) is a crucial enzyme that governs S-adenosyl methionine (SAM)-dependent methylation reactions within cells and regulates the intracellular concentration of SAH. Legionella pneumophila, the causative pathogen of Legionnaires' disease, encodes Lpg2021, which is the first identified dimeric SAHH in bacteria and is a promising target for drug development. Here, we report the structure of Lpg2021 in its ligand-free state and in complexes with adenine (ADE), adenosine (ADO), and 3-Deazaneplanocin A (DZNep). X-ray crystallography, isothermal titration calorimetry (ITC), and molecular docking were used to elucidate the binding mechanisms of Lpg2021 to its substrates and inhibitors. Virtual screening was performed to identify potential Lpg2021 inhibitors. This study contributes a novel perspective to the understanding of SAHH evolution and establishes a structural framework for designing specific inhibitors targeting pathogenic Legionella pneumophila SAHH.

Fractional view analysis of sexual transmitted human papilloma virus infection for public health

The infection of human papilloma virus (HPV) poses a global public health challenge, particularly in regions with limited access to health care and preventive measures, contributing to health disparities and increased disease burden. In this research work, we present a new model to explore the transmission dynamics of HPV infection, incorporating the impact of vaccination through the Atangana-Baleanu derivative. We establish the positivity and uniqueness of the solution for the proposed model HPV infection. The threshold parameter is determined through the next-generation matrix method, symbolized by [Formula: see text]. Moreover, we investigate the local asymptotic stability of the infection-free steady-state of the system. The existence of the solutions of the recommended model is determined through fixed-point theory. A numerical scheme is presented to visualize the dynamical behavior of the system with variation of input factors. We have shown the impact of input parameters on the dynamics of the system through numerical simulations. The findings of our investigation delineated the principal parameters exerting significant influence for the control and prevention of HPV infection.