Understanding Negative Feedback Systems: Equations, Dynamics, and Activation

AI Thread Summary
The discussion focuses on the dynamics of negative feedback systems expressed through differential equations, specifically $$\frac{dx}{dt} = \beta - \gamma(x) \cdot x$$. Participants explore the conditions under which the steady state (xST) is determined by the parameters β and γ, particularly in relation to a threshold K. There is confusion regarding the simplification of the equation and the transition from ≤ to < in the context of the steady state conditions. Additionally, there is a request for guidance on determining when feedback is activated and how to solve the equation with an initial condition of x(t=0)=0. Clarification on these points is sought to better understand the system's behavior.
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Homework Statement
A protein X is produced at a constant rate β. Its degradation rate γ is controlled by its own concentration x, meaning that: if x < K then γ(x) = γ[SUB]low[/SUB], otherwise γ = γ[SUB]high[/SUB].
K is the repression threshold.

We have to follow an example given in class, which is very similar, that I attached.
Then answer the following questions:

1. Find the steady-state for different parameters.

2. For the case where feedback is activated in the steady-state, describe the dynamics of the system. Calculate the speedup of the dynamics here compared to the open loop case with the same steady-state?

3. Using the interval method, calculate the dynamics for a delay in the feedback in the extreme case where γ[SUB]low[/SUB] = 0. What is the pulse height as a function of the delay time?

4. Can you suggest a simple synthetic system where degradation based feedback can be studied?
Relevant Equations
See the attached file.
We express such equations by $$\frac{dx}{dt} = \beta - \gamma \cdot x$$, t denotes the time.
In this case, γ depends on x, thus the dynamic equation should probably be:
$$\frac{dx}{dt} = \beta - \gamma(x) \cdot x$$

1. Setting the equation to 0 leads to two different cases:
If x < K: xST = γlow / β
If x ≥ K: xST = γhigh / β

I can also say (like in the example), that it is dependent on β, so:
If β > γlow / k: xST = γlow / β
If β ≤ γhigh / k: xST = γhigh / β

I don't understand why in the example in this step the divided by K drops and why the ≤ becomes a <.

2. Now my biggest concern is, how do I see, in which case the feedback is activated and in which not?
Then I would take this case and try to solve the equation with initial condition x(t=0)=0.
Probably the outcome is very similar to the example.
How would I proceed?

Any help is very appreciated!
 

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No one any suggestions or ideas/thoughts? :)
 
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