MODEL

Team UFLORIDA In Silico Model

Results

Using our model, we were able to produce 6 immune cases that we believe are biologically relevant.

• Healthy person with no pathogen insult
• Healthy person with moderate pathogen insult
• Person who undergoes sepsis early-death
• Person who experiences two infections
• Person who undergoes aseptic death
• Person who undergoes aseptic death recovery

Healthy person with no pathogen insult

This case is quite significant because it demonstrates that our model can accurately mimic what happens when a healthy person isn't affected by any diseases. We've simulated this scenario, and it's clear from a few key features in our graphs.

Firstly, we've chosen initial values that make sense, with no pathogens entering the system. We start with a basic hematopoietic stem and progenitor cells (HSPC) population and a steady level of leukocytes. As we run the simulation, you'll notice that none of the levels change, except for the pro and anti-inflammatory cytokines. This happens because the system isn't entirely accurate at the beginning; it needs some time to "build" its immune system. But once it's done, the system reaches homeostasis.

Another interesting thing you'll see is that none of the stable leukocytes change into pro or anti-inflammatory types. This is because there's no infection to make them act differently. This is important because it shows that our system can reach a stable state in the basic case where there are no pathogens involved.

Healthy person with moderate pathogen insult

We undertook the modeling of this specific case to create a scenario where an individual transitions from a state of health to sickness and eventually returns to the homeostatic equilibrium characteristic of a pathogen-free healthy person. It is instrumental that our model achieves this.

To commence, the initial parameter selection is of biological relevance to the scenario under consideration. We prescribe specific quantities of HSPCs, pro-inflammatory and anti-inflammatory cytokines, and stable leukocytes. In the initial phase, a obvious decrease is observed in the stable leukocyte population as the immune system is invoked, prompting differentiation into either activated or immunosuppressive leukocyte subsets. The HSPC population experiences an immediate decline as these cells undergo differentiation into distinct leukocyte populations. However, this decrease is transient and is followed by a resurgence upon successful pathogen removal. Moreover, all other nodes in the model gradually revert to homeostasis once the infection has been killed.

The pathogen graph serves as a tangible indicator of infection resolution, demonstrating an initial surge as the pathogen proliferates, followed by a decline after the immune system's activation. These graphical representations collectively underscore our model's robustness in perturbation response to pathogen insult, facilitating a return to homeostasis, akin to the recuperation process witnessed when a healthy individual temporarily becomes sick and subsequently becomes healthy again.

Person who undergoes sepsis early-death

In the context of sepsis, this affliction manifests in two primary forms: "sepsis early-death" and "chronic sepsis." For this investigation, our focus is on the former, which seeks to replicate a scenario in which an individual encounters a pathogenic insult that results in their immune system being unable to restore homeostasis. We commence our exploration with a selection of initial values that align with the biological dynamics of this scenario.

Specifically, we establish the HSPC and stable leukocyte levels at values akin to those observed in our homeostasis model. However, a significant difference occurs after the initial activation of our immune model, where we introduce a substantial pathogenic insult. It's noteworthy that this insult leads to the apparent defeat of the immune system, as evident in the graph exhibiting a standard logistic growth curve reaching its carrying capacity. While this progression may not precisely mirror a clinical case, it serves as a demonstrative construct to illustrate the point at which the pathogen overpowers the host.

The trajectory of the HSPC graph holds particular significance, as it initially declines, only to persistently diminish until it reaches zero. This occurrence is pivotal since HSPCs are indispensable for the derivation of other immune cell types within the system. Consequently, their extinction precipitates a cascade of immune cell depletion. Concurrently, all other graphical representations depict a declining trend over time.

This particular case emulation is vital as it underscores our model's capacity to not only reproduce stable states but also simulate the intricacies of sepsis, offering a comprehensive platform for analysis.

Person who experiences two infections

This case holds notable significance as it is an effort to model a form of chronic sepsis. We initiate the scenario with initial values from our healthy person case. However, at time intervals t_50 and t_150, we introduce an increase in the pathogen level. The first infection can be observed as an initial challenge met by the immune system, evidenced by the initial decline followed by a subsequent rebound in HSPCs and stable leukocytes, coupled with an initial surge and subsequent decline in both cytokine types and activated leukocytes.

This case is significant, as it shows how our model responds when exposed to an initial infection, successfully overcoming it. However, should a subsequent, more potent infection inflict the system before the system has fully recovered, it demonstrates an inability to regain homeostasis, offering valuable insights into the dynamics of chronic sepsis.

This case holds significant biological relevance by mirroring real-life scenarios, it suggests that the critical level of infection (the level of pathogenic insult needed to lead to septic death) is lowered with successive infections within a short period of time. It shows the significance of secondary infections in ICU settings, raising the possibility that administering an artificial boost of HSPCs following the initial infection could potentially lower mortality rates. Furthermore, the graphical evidence reaffirms the credibility of our model's capacity to simulate a functional immune system, as this state emerges without any specialized parameter adjustments.

(This is achieved by setting t_50 = 870 and t_150 = 1307)

Person who undergoes aseptic death

This case has been studied due to its capacity to mirror a situation in which an individual manages to kill an infection, yet succumbs to the immune dysregulation triggered by the very infection they overcame. Our initial parameters were selected to cause the healthy person case, but then subsequently compromised by an increase in the pathogen level. In this unique scenario, the dynamics of pro and anti-inflammatory cytokines play a pivotal role, rendering the immune system unable to effectively combat the infection and facilitate recovery. The graphical representations accompanying this case give evidence to this claim. The pathogen graph demonstrates that the pathogen has indeed been killed, yet the other graphs show the immune system's failure. This depiction holds significant biological relevance to sepsis, contributing to a comprehensive representation of the multifaceted dynamics that our model has captured, enhancing our understanding of this condition and its diverse manifestations.

Person who undergoes aseptic death recovery

This case was undertaken as a test scenario, driven by the thought of whether we could take a trajectory leading to aseptic death and implement a treatment strategy that would facilitate recovery. The results of our investigation are evident in the graphical depictions. To simulate a clinical intervention, we devised a method of elevating the HSPC level each time it dipped below a predetermined threshold. This artificial HSPC boost emulates a scenario where a patient, under medical care, receives a controlled infusion of HSPC's as a treatment for their illness. Starting with the initial values known to cause in aseptic death, our model exhibits oscillatory behavior before ultimately driving the pathogen levels to zero and stabilizing the other variables. The significance of this case extends beyond its testing function. It shows how our model is versatile, not only for replicating biologically relevant scenarios but also for assessing diverse treatment options and generating hypotheses grounded in the observed outcomes. In essence, our model emerges as a predictive tool capable of projecting potential outcomes for a range of treatment strategies.

(This is achieved by setting the HSPC level to increase by 1000 when it goes below 4000) (Meant to simulate someone who is artificially given HSPC's as a treatment option)