ENH integrate new appendices

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Nathan Dwarshuis 2021-08-03 19:05:34 -04:00
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1 changed files with 24 additions and 17 deletions

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@ -1558,16 +1558,15 @@ quantified for \gls{stp} protein using the \gls{bca} assay.
% TODO defend why the microcarriers were saturated with stp % TODO defend why the microcarriers were saturated with stp
The effective diffusivity of the microcarriers was determined using a The effective diffusivity of the microcarriers was determined using a
pseudo-steady-state model. Each microcarrier was assumed to be a porous sphere pseudo-steady-state model. Each microcarrier was assumed to be a porous sphere
with a fixed number of `\gls{stp} binding sites' equal to the maximum number of with a fixed number of `\gls{stp} binding sites' equal to the number of
\gls{stp} molecules that could binding to the surface per area (eg, we assumed \gls{stp} molecules experimentally determined to bind to the microcarriers.
the surface was fully covered by \gls{stp}). Because the reaction rate between Because the reaction rate between biotin and \gls{stp} was so fast, we assumed
biotin and \gls{stp} was so fast, we assumed that the interface of free biotin that the interface of free biotin shrunk as a function of \gls{stp} bound until
shrunk as a function of \gls{stp} bound until the center of the microcarriers the center of the microcarriers was reached. We also assumed that the pores in
was reached. We also assumed that the pores in the microcarriers were large the microcarriers were large enough that the interactions between the \gls{stp}
enough that the interactions between the \gls{stp} and surfaces would be small, and surfaces would be small, thus the apparent diffusivity could be represented
thus the apparent diffusivity could be represented as a fraction of the as a fraction of the diffusion coefficient of \gls{stp} in water. This model was
diffusion coefficient of \gls{stp} in water. This model was given by given by \cref{eqn:stp_diffision_1,eqn:stp_diffision_2}:
\cref{eqn:stp_diffision_1,eqn:stp_diffision_2}:
% TODO actually derive these equations, eg state the initial conditions and % TODO actually derive these equations, eg state the initial conditions and
% governing equation % governing equation
@ -1598,15 +1597,23 @@ diffusion coefficient of \gls{stp} in water. This model was given by
The diffusion rate of \gls{stp} was assumed to be The diffusion rate of \gls{stp} was assumed to be
\SI{6.2e-7}{\cm\squared\per\second}\cite{Kamholz2001}. Since all but $\beta$ was \SI{6.2e-7}{\cm\squared\per\second}\cite{Kamholz2001}. Since all but $\beta$ was
known, the experimental data was fit using these equations using known, the experimental data was fit using these equations using
\inlinecode{ode45} in MATLAB and least squares as the fitting error. These equations were then used analogously to describe the reaction profile of \inlinecode{ode45} in MATLAB and least squares as the fitting error. These
equations were then used analogously to describe the reaction profile of
\glspl{mab} assuming a diffusion rate of \glspl{mab} assuming a diffusion rate of
\SI{4.8e-7}{\cm\squared\per\second}\cite{Sherwood1992}. These same coefficients \SI{4.8e-7}{\cm\squared\per\second}\cite{Sherwood1992}.
These same coefficients
were used in determining the kinetics of the washing steps, and were used in determining the kinetics of the washing steps, and
\SI{5.0e-6}{\cm\squared\per\second}\cite{Niether2020} was used as the diffusion \SI{5.0e-6}{\cm\squared\per\second}\cite{Niether2020} was used as the diffusion
coefficient for free biotin (which should be the only species left in solution coefficient for free biotin (which should be the only species left in solution
after all the \gls{snb} has hydrolyzed). All diffusion coefficients were taken after all the \gls{snb} has hydrolyzed).
to be valid at \gls{rt} and in \gls{di} water, which is a safe assumption given
that our reaction medium was 1X \gls{pbs}. All diffusion coefficients were taken to be valid at \gls{rt} and in \gls{di}
water, which is a safe assumption given that our reaction medium was 1X
\gls{pbs}.
See \cref{sec:appendix_binding} and \cref{sec:appendix_washing} for the MATLAB
code (and output in the case of the washing steps) used.
% METHOD add the equation governing the washing steps % METHOD add the equation governing the washing steps
@ -4471,7 +4478,7 @@ hosted using \gls{aws} using their proprietary Aurora implementation.
The code is available here: \url{https://github.gatech.edu/ndwarshuis3/mdma}. The code is available here: \url{https://github.gatech.edu/ndwarshuis3/mdma}.
\chapter{binding kinetics code} \chapter{binding kinetics code}\label{sec:appendix_binding}
The \gls{stp} binding kinetic profile was fit and calculated using the following The \gls{stp} binding kinetic profile was fit and calculated using the following
MATLAB code. Note that the \inlinecode{geometry} parameter was varied so as to MATLAB code. Note that the \inlinecode{geometry} parameter was varied so as to
@ -4486,7 +4493,7 @@ reflect the \gls{mab} coating process.
\lstinputlisting{../code/diffusion_mab.m} \lstinputlisting{../code/diffusion_mab.m}
\chapter{washing kinetics code} \chapter{washing kinetics code}\label{sec:appendix_washing}
The wash steps for the \gls{dms} were modeled using the following code: The wash steps for the \gls{dms} were modeled using the following code: