Taking the log of an exponential function and finding the slope

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SUMMARY

The discussion focuses on solving a differential equation related to the population dynamics of uninfected T cells, infected T cells, and viruses, specifically analyzing the logarithmic behavior of the virus population function V(t). The key equations include the differential equations for T(t), I(t), and V(t), with the assumption that the infection rate constant β is set to 0. The main conclusion is that the slope of the log graph of V(t) should approach -μ, the negative reciprocal of the average lifespan of infected CD4+ T cells, but a discrepancy arises due to the presence of a ln(10) factor when using base 10 logarithms instead of natural logarithms.

PREREQUISITES
  • Understanding of differential equations, particularly first-order linear differential equations.
  • Familiarity with population dynamics in biological systems.
  • Knowledge of logarithmic functions and their derivatives.
  • Basic concepts of virology, specifically the behavior of T cells and viruses in the human body.
NEXT STEPS
  • Review the derivation of solutions for first-order linear differential equations.
  • Study the properties of logarithmic functions and their applications in biological modeling.
  • Explore the implications of using different logarithmic bases in mathematical modeling.
  • Investigate the dynamics of viral infections and the role of CD4+ T cells in the immune response.
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Students and researchers in mathematics, biology, and virology, particularly those involved in modeling infectious diseases and analyzing population dynamics through differential equations.

cryora
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This is part of a differential equations group project problem where I solve a set of differential equations to obtain the solution to a function. The part that I am stuck at involves taking the log of an exponential function, though there may be a mistake on the book's part, but I'm not sure.

Homework Statement


Argue from your formula for V(t), that the graph of V(t) on a log scale (i.e., the graph of log V) over an extended period of time (say, several weeks) will tend toward a graph of a straight line whose slope is either -γ (the negative reciperocol of the average lifespan of a free virus) or -μ (the negative reciprocol of the average lifespan of an infected CD4+ T cell), according to whether γ or μ is smaller.

Homework Equations


\frac{d}{dt}T(t) = λ - δT(t) - βV(t)T(t)
\frac{d}{dt}I(t) = βV(t)T(t) - μI(t)
\frac{d}{dt}V(t) = NμI(t) - γV(t)
T represents population of uninfected T cells in units of cells.
I represents population of infected T cells in units of cells.
V represents population of virus in units of virions.
λ is the rate of T cell production by the human body per day in units of 1/days
δ is the rate constant of T cells naturally dying off per day in units of 1/days
μ is the rate constant of Infected T cells dying off (bursting) per day resulting in the spread of virus in units of 1/days
γ is the rate constant of virus decaying per day in units of 1/days
N is the number of virus per cell in units of virions/cell
β is the infection rate constant in units of 1/(days*virions)

The problem states to set β = 0, assuming there is a drug that completely removes infection of T cells, allowing me to solve by 1st order linear differential equation methods to get V(t):
V(t) = \frac{NμI_0}{γ-μ}e^{-μt} + (V_0 - \frac{NμI_0}{γ-μ})e^{-γt}
with initial conditions
V(0) = V_0 \text{ and } I(0) = I_0

The Attempt at a Solution


Taking the log of V(t) and then taking the derivative, I get:
\frac{d}{dt}log[V(t)] = \frac{d}{dt}\frac{ln[V(t)]}{ln(10)} = \frac{1}{ln(10)V(t)}\frac{d}{dt}V(t)
and
\frac{d}{dt}V(t) = \frac{-Nμ^2I_0}{γ-μ}e^{-μt} - γ(V_0 - \frac{NμI_0}{γ-μ})e^{-γt}

Assuming μ is smaller than γ, the term containing e^{-γt} should go to 0 when t is large, leaving us with:
\frac{d}{dt}log[V(t)] = \frac{V'(t)}{ln(10)V(t)} = \frac{\frac{-Nμ^2I_0}{γ-μ}e^{-μt}}{ln(10)\frac{NμI_0}{γ-μ}e^{-μt}} = \frac{-μ}{ln(10)} \text{for large t}

The problem is the factor of \frac{1}{ln(10)} causing the slope of the log graph to be inconsistent with what the problem statement claims it should be: -μ.
 
Last edited:
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When doing calculus, "log" means "natural logarithm".
 
pasmith said:
When doing calculus, "log" means "natural logarithm".

While that would get rid of the 1/ln10 factor, I doubt I could make that assumption in this case because for one this book does use ln notation, and there are graphs for this problem that depicts virus amount in a log base 10 scale (where it goes from 1 to 10 to 100 to... 10^n... every major gridline). The problem even states to determine μ based on the slope of those graphs.
 

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