A MODEL OF THE OPTIMAL IMMUNOTHERAPY OF PSORIASIS BY INTRODUCING IL-10 AND IL-22 INHIBITORS

Reappraisal of psoriasis pathogenesis: the role of TEAD4 expression in keratinocytes

BACKGROUND

Psoriasis is an immune-mediated inflammatory skin disorder with a multifaceted pathogenesis. Immune dysregulation and immune cell dysfunction are among the mechanisms involved. TEA domain family member 4 (TEAD4) is suggested to play a role in psoriasis development. TEAD4 expression in keratinocytes may have a chemotactic effect and could disturb the function of FOXP3-positive T lymphocytes. This study aimed to evaluate the expressions of TEAD4 and FOXP3 in lesional, nonlesional psoriatic, and healthy skin and assess the clinical impact of their expression.

METHODS

This case-control study included 32 cases with psoriasis vulgaris and 32 control groups. Hematoxylin and eosin-stained slides were examined to evaluate the histopathological findings. Moreover, other sections were immunohistochemically stained with FOXP3 and TEAD4.

RESULTS

FOXP3 was expressed in inflammatory cells in 56.5, 37.5, and 12.5% of lesional, nonlesional, and healthy skin, whereas it was entirely negative in the keratinocytes. TEAD4 was expressed in keratinocytes in 93.7 and 46.9% of lesional and nonlesional skin, while negative in healthy skin. Significant differences were observed between their lesional, nonlesional, and healthy skin expressions. Furthermore, FOXP3 expression in lesional skin was significantly associated with early onset (P = 0.016), low PASI score (P = 0.002), mild psoriasis (P = 0.007), and axial affection (P = 0.022), while TEAD4 expression was associated with progressive course (P = 0.032), high PASI score (P = 0.002), severe psoriasis (P = 0.001), severe inflammation (P = 0.001), and progressive course (P = 0.017).

CONCLUSION

TEAD4 expression was higher in lesional than nonlesional skin and absent in healthy skin, suggesting a role in psoriasis development. TEAD4 expression was also associated with severe and progressive psoriasis. This may be mediated by the downregulation of FOXP3 and dysfunction of Treg cells. TEAD4 could serve as a promising therapeutic target in psoriasis.

Modeling of psoriasis by considering drug influence: A mathematical approach with memory trace

Psoriasis is an immune-mediated genetic disease, characterized by its manifestation on the skin, the joints, or both. In this paper, our primary aim is to increase awareness about the intricate nature of this multifaceted condition, highlight the potential of therapeutic approaches, and examine the factors affecting the future course of psoriasis. This paper introduces a mathematical model for psoriasis, formulated by fractional order differential equations (FODE) with Caputo sense. The model also includes the drug effect of immune-boosting drugs on psoriasis. It has been shown that the solution of the proposed system exists and is unique, and its positivity and boundedness have been proven. Additionally, the local stability and global stability of the co-existing equilibrium point have been investigated. Numerical solutions have been conducted using the Adams Bashforth PECE method to analyze the influence of fractional order derivatives (FODs) and distinct parameters on population dynamics. The graphics have been acquired using the L1 scheme, incorporating a memory trace (MT) mechanism capable of comprehensively capturing and amalgamating historical system dynamics to visualize the memory trace in detail. One of the results deduced from this paper is that the MT disappears when α equals 1. Upon decreasing the fractional order α from 1, the MT experiences a non-linear augmentation starting from zero. This observed MT emphasizes the distinction between derivatives of fractional and integer orders. Within the proposed model, our findings suggest that introducing the immune booster drug efficiently controls psoriasis. Furthermore, when appropriate clinical patient data are available, the proposed results can be used for a specific psoriasis patient. Our study suggests that treatment with the drug may be a new insight into psoriasis treatment and may be proposed as a treatment policy for future clinical trials.

Stability analysis of within-host SARS-CoV-2/HIV coinfection model

The world has been suffering from the coronavirus disease 2019 (COVID-19) since late 2019. COVID-19 is caused by a virus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The human immunodeficiency virus (HIV) coinfection with SARS-CoV-2 has been reported in many patients around the world. This has raised the alarm for the importance of understanding the dynamics of coinfection and its impact on the lives of patients. As in other pandemics, mathematical modeling is one of the important tools that can help medical and experimental studies of COVID-19. In this paper, we develop a within-host SARS-CoV-2/HIV coinfection model. The model consists of six ordinary differential equations. It depicts the interactions between uninfected epithelial cells, infected epithelial cells, free SARS-CoV-2 particles, uninfected CD4+ T cells, infected CD4+ T cells, and free HIV particles. We confirm that the solutions of the developed model are biologically acceptable by proving their nonnegativity and boundedness. We compute all possible steady states and derive their positivity conditions. We choose suitable Lyapunov functions to prove the global asymptotic stability of all steady states. We run some numerical simulations to enhance the global stability results. Based on our model, weak CD4+ T cell immune response or low CD4+ T cell counts in SARS-CoV-2/HIV coinfected patient increase the concentrations of infected epithelial cells and SARS-CoV-2 viral load. This causes the coinfected patient to suffer from severe SARS-CoV-2 infection. This result agrees with many studies which showed that HIV patients are at greater risk of suffering from severe COVID-19 when infected. More studies are needed to understand the nature of SARS-CoV-2/HIV coinfection and the role of different immune responses during infection.

Mathematical analysis of a SIPC age-structured model of cervical cancer

Human Papillomavirus (HPV), which is the main causal factor of cervical cancer, infects normal cervical cells on the specific cell's age interval, i.e., between the G₁ to S phase of cell cycle. Hence, the spread of the viruses in cervical tissue not only depends on the time, but also the cell age. By this fact, we introduce a new model that shows the spread of HPV infections on the cervical tissue by considering the age of cells and the time. The model is a four dimensional system of the first order partial differential equations with time and age independent variables, where the cells population is divided into four sub-populations, i.e., susceptible cells, infected cells by HPV, precancerous cells, and cancer cells. There are two types of the steady state solution of the system, i.e., disease-free and cancerous steady state solutions, where the stability is determined by using Fatou's lemma and solving some integral equations. In this case, we use a non-standard method to calculate the basic reproduction number of the system. Lastly, we use numerical simulations to show the dynamics of the age-structured system.