Mathematical modeling of septic shock: an innovative tool for assessing therapeutic hypotheses

Abstract

Septic shock is provoked by hyper-activation of the pro-inflammatory response after infection and the patient requires anti-inflammatory treatment. However, the immune system develops a compensatory mechanism where the resulting feedback leads to an anti-inflammatory response after the initial state, which is referred to as immunodeficiency. Therefore, the initial therapeutic treatment with anti-inflammatory intervention has failed for almost 20 years and it has been changed in the last 10 years based on modulation of the inflammatory response. Using in silico methods, it is possible to develop a new approach based on physiopathology for treating septic shock. According to our new mathematical model, we can consider the dysfunctional immune system in a patient with septic shock and modify two parameters at different times to determine a possible treatment, and bearing out the single nucleoid polymorphism (SNP) may predominate the further deterioration of sepsis. The result represents the initial anti-inflammatory treatment with interleukin-10 activation and an increased risk of mortality over time for the septic shock patient, excluding the early stages. However, a hypothetical treatment based on interleukin-10 inhibition can change the patient's immune stage and provide a new therapy according to our results, and show that the frequency of pro-inflammatory related gene SNP can be the possibility of increase sepsis risk. In conclusion, our proposed in silico method can explore therapeutic strategies and predict their associated efficacy and important factors, with the ultimate objective of improving treatments to reduce mortality.

Circulating microRNAs in oncogenic viral infections: potential diagnostic biomarkers

“…It is a contagious disease having genes associated with complicate biological processes, so closely linked with constant infection of high-risk human papilloma virus (HPV) [61]. Chromosomal mutation and alteration of single nucleotide polymorphisms; these were the key factors to cause the malignant alteration of cervical epithelial [62].…”

Dynamical modeling of pro- and anti-inflammatory cytokines in the early stage of septic shock

“…Numerous models are used to simulate the immune system for better understanding, [14,16,17,19,22,24,26,27]. The authors have different modeling approaches, but, currently, the principal limitation is the availability and complexity of experimental data for validation.…”

“…Some models are used as the foundation for simulations for testing therapy strategies [21,23,26,[28][29][30].…”

Predicting the neuro‐cardio‐haemodynamic outcomes of sepsis and its pharmacological interventions: Get to the future through numerical equations

“…In recent years, several mathematical models operating on the system level have been developed to better understand the cellular determinants of sepsis and to predict the effects of pharmacological agents (McDaniel et al 2019;Yamanaka et al 2019;Zhao et al 2019). The model by Yamanaka et al (2019) focused on elucidating the impact of inflammation on cardiovascular dynamics during sepsis, incorporating the core elements of blood pressure (BP), such as stroke volume and vessel properties (i.e.…”

“…Interestingly, the inflammation model in BioGears was optimised using murine data employed for human predictions, which is problematic because murine inflammatory pathways are different from those found in humans (Dobreva et al 2021). Next, Zhao et al (2019) developed a mathematical model of septic shock, integrating a previously published endotoxin-induced human inflammation model with epigenetic regulatory loops. They employed the model to investigate the effects of interleukin (IL)-10 modulation during septic shock and subsequently compared the results with clinical data and experimental data obtained in mice.…”