Comparative Analysis of Pharmacodynamics in the C3HeB/FeJ Mouse Tuberculosis Model for DprE1 inhibitors TBA-7371, PBTZ169 and OPC-167832

Multiple drug discovery initiatives for tuberculosis are currently ongoing to identify and develop new potent drugs with novel targets in order to shorten treatment duration. One of the drug classes with a new mode of action are DprE1 inhibitors targeting an essential process in cell wall synthesis of Mycobacterium tuberculosis . In this investigation, three DprE1 inhibitors currently in clinical trials, TBA-7371, PBTZ169 and OPC-167832, were evaluated side-by-side as single agents in the C3HeB/FeJ mouse model presenting with caseous necrotic pulmonary lesions upon tuberculosis infection. The goal was to confirm the efficacy of the DprE1 inhibitors in a mouse tuberculosis model with advanced pulmonary pathology, and perform comprehensive analysis of plasma, lung and lesion-centric drug levels to establish pharmacokinetic-pharmacodynamic (PK-PD) parameters predicting efficacy at the site of infection. Results showed significant efficacy for all three DprE1 inhibitors in the C3HeB/FeJ mouse model after two months of treatment. Superior efficacy was observed for OPC-167832 even at low dose levels, which can be attributed to its low MIC, favorable distribution and sustained retention above the MIC throughout the dosing interval in caseous necrotic lesions where the majority of bacteria reside in C3HeB/FeJ mice. These results support further progression of the three drug candidates through clinical development for tuberculosis treatment.

Exploring the Stochastic Host-Pathogen Tuberculosis Model with Adaptive Immune Response

In this literature, we probe a stochastic host-pathogen tuberculosis model with the adaptive immune response of four states of epidemiological classification: Mycobacterium tuberculosis, uninfected macrophages, infected macrophages, and immune response CD4+ T cells. This model is pertinent to the latent stage of tuberculosis infection and active tuberculosis-infected individuals. The stochastic host-pathogen tuberculosis model in pathology is constituted based on the environmental influence on the Mycobacterium tuberculosis and macrophage population, elucidated by stochastic perturbations, and it is proportional to each state. We evince the existence and a unique global positive solution of a stochastic tuberculosis model. We attain sufficient conditions for the extinction of the tubercle bacillus. Moreover, we acquire the existence of the stationary distribution of the positive solutions by the Lyapunov function method. Eventually, numerical simulations validate analytical findings and the dynamics of the stochastic TB model.

Application of optimal control to tuberculosis model with parameter estimations: Bayesian approach

In this paper, one-strain tuberculosis (TB) model with two control mechanisms, education campaigns and chemoprophylaxis of TB-infected patients, was studied to determine their effects on the reduction of latent and active TB cases. In the case of analysis, boundedness and positivity of the model solutions were carried out to determine the biological feasibility of the study. Besides, the calibration of the parameters by utilizing the identifiability technique through the Markov chain Monte Carlo (MCMC) was thoroughly analysed. The optimum conditions for controlling TB were derived from the Pontryagin Maximum Principle. The numerical simulations were carried out using the forward-back sweep method with the help of the Runge-Kutta fourth-order numerical schemes. Simulation results showed that the education campaigns strategy is more effective in reducing TB infections than the chemoprophylaxis of TB-infected individuals. The combination of the two control strategies reduces a significant number of infections than when each strategy is used on its own. To minimize the transmission of TB from the community, we recommend the education campaigns strategy be a focal point and treatment of latent TB to be paired with the treatment of active TB cases. Keywords: Tuberculosis, Education campaigns, Chemoprophylaxis, MCMC

A Within-host Tuberculosis Model Using Optimal Control

In this paper, we studied a mathematical model of tuberculosis with vaccination for the treatment of tuberculosis. We considered an in-host tuberculosis model that described the interaction between Macrophages and Mycobacterium tuberculosis and investigated the effect of vaccination treatments on uninfected macrophages. Optimal control is applied to show the optimal vaccination and effective strategies to control the disease. The optimal control formula is obtained using the Hamiltonian function and Pontryagin's maximum principle. Finally, we perform numerical simulations to support the analytical results. The results suggest that control or vaccination is required if the maximal transmission of infection rate at which macrophages became infected is large. In this paper, we studied a mathematical model of tuberculosis with vaccination for the treatment of tuberculosis.We considered an in-host tuberculosis model that described the interaction between macrophages Macrophages and Mycobacterium tuberculosis and investigated the effect of vaccination treatments on uninfected macrophages. Optimal controlis applied to show the optimal vaccination and effective strategies to control the disease. The optimal control formula isobtained using the Hamiltonian function and Pontryagin's maximum principle. Finally, we perform numerical simulations to support the analytical results.The results suggest thatcontrol or vaccination is required if the maximal transmission of infection rate at which macrophages became infected is large.

Blockade of translationally controlled tumor protein attenuated the aggressiveness of fibroblast-like synoviocytes and ameliorated collagen-induced arthritis

Histamine releasing factor/translationally controlled tumor protein (HRF/TCTP) stimulates cancer progression and allergic responses, but the role of HRF/TCTP in rheumatoid arthritis (RA) remains undefined. In this study, we explored the pathogenic significance of HRF/TCTP and evaluated the therapeutic effects of HRF/TCTP blockade in RA. HRF/TCTP transgenic (TG) and knockdown (KD) mice with collagen-induced arthritis (CIA) were used to determine the experimental phenotypes of RA. HRF/TCTP levels in the sera of RA patients were measured and compared to those from patients with osteoarthritis (OA), ankylosing spondylitis, Behçet’s disease, and healthy controls. HRF/TCTP expression was also assessed in the synovium and fibroblast-like synoviocytes (FLSs) obtained from RA or OA patients. Finally, we assessed the effects of HRF/TCTP and dimerized HRF/TCTP-binding peptide-2 (dTBP2), an HRF/TCTP inhibitor, in RA-FLSs and CIA mice. Our clinical, radiological, histological, and biochemical analyses indicate that inflammatory responses and joint destruction were increased in HRF/TCTP TG mice and decreased in KD mice compared to wild-type littermates. HRF/TCTP levels in the sera, synovial fluid, synovium, and FLSs were higher in patients with RA than in control groups. Serum levels of HRF/TCTP correlated well with RA disease activity. The tumor-like aggressiveness of RA-FLSs was exacerbated by HRF/TCTP stimulation and ameliorated by dTBP2 treatment. dTBP2 exerted protective and therapeutic effects in CIA mice and had no detrimental effects in a murine tuberculosis model. Our results indicate that HRF/TCTP is a novel biomarker and therapeutic target for the diagnosis and treatment of RA.