Nonlinear adaptive control of tuberculosis with consideration of the risk of endogenous reactivation and exogenous reinfection

Exploring Hopf-bifurcations and endemic bubbles in a tuberculosis model with behavioral changes and treatment saturation

To manage risks and minimize the transmission of contagious diseases, individuals may reduce their contact with each other and take other precautions as much as possible in their daily lives and workplaces. As a result, the transmission of the infection reduces due to the behavioral changes. These behavioral changes are incorporated into models by introducing saturation in disease incidence. In this article, we propose and analyze a tuberculosis model that incorporates saturated exogenous reinfection and treatment. The stability analysis of the model's steady states is rigorously examined. We observe that the disease-free equilibrium point and the endemic equilibrium point (EEP) are globally asymptotically stable if the basic reproduction number (R0) is less than 1 and greater than 1, respectively, only when exogenous reinfection is not present (p=0) and when treatment is available for all (ω=0). However, even when R0 is less than 1, tuberculosis may persist at a specific level in the presence of exogenous reinfection and treatment saturation, leading to a backward bifurcation in the system. The existence and direction of Hopf-bifurcations are also discussed. Furthermore, we numerically validate our analytical results using different parameter sets. In the numerical examples, we study Hopf-bifurcations for parameters such as β, p, α, and ω. In one example, we observe that increasing β leads to the loss of stability of the unique EEP through a forward Hopf-bifurcation. If β is further increased, the unique EEP restores its stability, and the bifurcation diagram exhibits an interesting structure known as an endemic bubble. The existence of an endemic bubble for the saturation constant ω is also observed.

Nonlinear neural networks adaptive control for a class of fractional-order tuberculosis model

The problem of nonlinear adaptive control for a class of fractional-order tuberculosis (TB) model is studied in this paper. By analyzing the transmission mechanism of TB and the characteristics of fractional calculus, a fractional-order TB dynamical model is established with media coverage and treatment as control variables. With the help of universal approximation principle of radial basis function neural networks and the positive invariant set of established TB model, the expressions of control variables are designed and the stability of error model is analyzed. Thus, the adaptive control method can guarantee that the number of susceptible and infected individuals can be kept close to the corresponding control targets. Finally, the designed control variables are illustrated by numerical examples. The results indicate that the proposed adaptive controllers can effectively control the established TB model and ensure the stability of controlled model, and two control measures can protect more people from tuberculosis infection.

Unique Reciprocal Association Seen Between Latent Tuberculosis Infection and Diabetes Is Due to Immunoendocrine Modulation (DM-LTB-1)

Aim

The prevalence of latent tuberculosis infection (LTBI) among diabetes patients is poorly studied. In the present study, the prevalence of LTBI among pre-diabetes and diabetes patients was studied, along with immunoendocrine biomarkers (n = 804).

Methods

LTBI was screened by Quantiferon TB gold in Normal glucose tolerance [(NGT); n = 170, [Pre-diabetes (PDM; n = 209), Newly diagnosed diabetes (NDM; n = 165) and Known diabetes (KDM; n = 260) subjects. CRP, TNF-α, IL-6, IL-1β, IFN-β, IL-12, IFN-γ, IL-2, insulin, leptin, and adiponectin levels in serum and IFN-γ levels in quantiferon supernatants were quantified by ELISA. The expression of T-bet was quantified using qRT-PCR. Serum TBARS and nitrite levels were quantified by colorimetry.

Results

The LTBI prevalence was 32% in NGT, 23% in PDM, 24% in NDM, and 32% in KDM groups, with an adjusted OR of 0.61 (p < 0.05). Downregulation of CRP, TNF-α, and nitrites and upregulation of adiponectin could be responsible for LTBI mediated protection against insulin resistance (IR), while the high levels of IL-1β, IL-12, and leptin could be responsible for IR mediated anti-TB immunity. The defective antigen-specific IFN-γ response, as seen in the KDM group, could be responsible for the low detection rate of LTBI and high probability of endogenous reactivation.

Conclusion

There appears to be a biphasic relationship between diabetes-latent tuberculosis: At the early stages of diabetes it is reciprocal, while at a late stage it is synergistic, this important phenomenon obviously needs further research.

A structured Markov chain model to investigate the effects of pre-exposure vaccines in tuberculosis control

In this paper, the interest is in a structured Markov chain model to describe the transmission dynamics of tuberculosis (TB) in the setting of small communities of hosts sharing confined spaces, and to explore the potential impact of new pre-exposure vaccines on reducing the number of new TB cases during an outbreak of the disease. The model under consideration incorporates endogenous reactivation of latent tubercle bacilli, exogenous reinfection of latently infected TB hosts, loss of effectiveness of the vaccine protection, and death of hosts due to tubercle bacilli and from causes beyond TB. Various probabilistic measures are defined and analytically studied to describe extreme values and the number of vaccinations during an outbreak, and a random version of the basic reproduction number is used to measure the transmission potential during the initial phase of the epidemic. Our numerical experiments allow us to compare different pre-exposure vaccines versus the level of coverage in terms of these probabilistic measures.

Preclinical Evidence of Nanomedicine Formulation to Target Mycobacterium tuberculosis at Its Bone Marrow Niche

One-third of the world’s population is estimated to be latently infected with Mycobacterium tuberculosis (Mtb). Recently, we found that dormant Mtb hides in bone marrow mesenchymal stem cells (BM-MSCs) post-chemotherapy in mice model and in clinical subjects. It is known that residual Mtb post-chemotherapy may be responsible for increased relapse rates. However, strategies for Mtb clearance post-chemotherapy are lacking. In this study, we engineered and formulated novel bone-homing PEGylated liposome nanoparticles (BTL-NPs) which actively targeted the bone microenvironment leading to Mtb clearance. Targeting of BM-resident Mtb was carried out through bone-homing liposomes tagged with alendronate (Ald). BTL characterization using TEM and DLS showed that the size of bone-homing isoniazid (INH) and rifampicin (RIF) BTLs were 100 ± 16.3 nm and 84 ± 18.4 nm, respectively, with the encapsulation efficiency of 69.5% ± 4.2% and 70.6% ± 4.7%. Further characterization of BTLs, displayed by sustained in vitro release patterns, increased in vivo tissue uptake and enhanced internalization of BTLs in RAW cells and CD271+BM-MSCs. The efficacy of isoniazid (INH)- and rifampicin (RIF)-loaded BTLs were shown using a mice model where the relapse rate of the tuberculosis was decreased significantly in targeted versus non-targeted groups. Our findings suggest that BTLs may play an important role in developing a clinical strategy for the clearance of dormant Mtb post-chemotherapy in BM cells.