Team:UCAS-China/Model TM

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  • Model for the Design
  • Dynamic of Hp Infection
  • Dynamic of Hp-SHEEP-Human System
  • Model for Therapy Method
  • Estimation for Individuality in Stable States
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Model for Therapy Method

Merely knowing about what happens in our stomach is not enough, designing a therapy and making SHEEP really an advanced and practical treatment is our final goal. In this part we study the medicine’s influence on Hp and design a dose regimen for SHEEP therapy.

Part 1. Traditional Treatment

To take medicine into consideration, we assume that the total medicine concentration can be represent by \(f(t)\) with equivalent effect. In other words, we use \(f(t)\) to represent the medicine concentration and modify the master equation. This means medicine in stomach get into mucus continuously by diffusion.

The simulation is run with different initial conditions. The main findings are listed here.

(a) P-state has strong drug resistance. It results from the fact that in p-state, Hp governs the system and has the ability of rapid reproduction.

(b) The biofilm makes Hp much more resistant against medicine. When sensing medicine, Hp’s biofilm increases and “stores” Hp in it. if patients stop taking medicine too soon (like stop right after symptoms disappear), Hp would quickly return to p-state.

(c) Total elimination of Hp takes about 400 days.

(d) The average drug concertation is 19 P.

Notice that when Hp is not at p-state, there is no need to keep such a high level of drug concentration. An easy improve of the treatment could be introduced—for the first week the dose regimen does not change. Then reduce the dose to about 10% of initial amount. Simulation shows that that would be enough to prevent Hp from returning to stable states. This improvement could significantly reduce the drug concentration in stomach, but cannot accelerate the therapy process.

Part 2. SHEEP Therapy

As mentioned in the last part, traditional treatment takes a long time. However, since SHEEP does not aim to eliminate Hp, the duration of therapy could be significantly shortened.

One possible dose regimen is given here. Take the improved traditional treatment for the first 45 days; stop taking medicine on the 45th day and take a unit dose of SHEEP. The process is easy, but it is already enough to establish the h-state. Meanwhile, the duration of therapy is only 11% of traditional ones.

Part 3. Family Evolutionary Tree

This well-prepared project was accidentally aborted by COVID-19.

Initially, we had planned to convene some patients who were related and infected by H. pylori. Subsequently, samples collected via our capsule robots from patients will be sent to genetic laboratory where we sequence and analyze the whole genome of H. pylori from individuals. With the assistance from several software, namely Phylip as well as MEGA, we are able to build a family evolutionary tree, which demonstrates the infectious process among family members and brings to light the mechanism and dynamics of mutation as well as selection.

That is the most meaningful part: after parsing the family evolutional tree via computational biological method, precision medicine for each individual comes into reality. In addition, a multidimensional insight into H. pylori’s mutation and selection makes it possible to adjust SHEEP, our strategy for treatment, for the purpose of declaring selective pressure of drug-resistance

Apart from that, patients’ permission as well as comprehension are of great importance. We are doomed to prudentially preserve each patients’ data and private information in order to protect their privacy and dignity.

Part 4. Machine Evolution Guiding SHEEP

Our superiority and prospect:

From our perspective, the best optimal strategy is balanced treatment rather than a fierce one. Lactobacillus acidophilus, which is a modified bacterium, with the gene of human antimicrobial peptides called LL-37 attached, has a competitive relationship with H. pylori. Besides, L. acidophilus has an ability to colonize in stomach for several generations. If we introduce our modified bacterium to patients, a homeostasis among human - H. pylori - L. acidophilus will be established. So that H. pylori will be controlled at a low level, avoiding the risk of severe gastric disease as well as maintaining a healthy and sound balance.

Apart from that, we have planed to put machine evolution into use. Evolutional logic, namely mutation and selection, will be defined as function and struct in program. Unlike artificial intelligence and machine learning, machine evolution is a brand-new horizon to simulate organism, in other words, is a way to create Digital Twin for our patients. If we make our prospect into reality, there is no deny that our balanced therapeutic prescription obtains a powerful assistance, and furthermore, individual medical treatment is doomed to be progressive and dynamic rather than stationary.

Here is our little program trying machine evolution~