diff --git a/tables/donor_chars.tex b/tables/donor_chars.tex
index 0f2211e..fe349f1 100644
--- a/tables/donor_chars.tex
+++ b/tables/donor_chars.tex
@@ -1,18 +1,17 @@
-\begin{tabular}{@{\extracolsep{5pt}} ccccccc}
+\begin{tabular}{@{\extracolsep{5pt}} cccccccc}
   \\[-1.8ex]\hline 
   \hline \\[-1.8ex] 
-ID & Demo & Gender & ABO Type & Age (years) & BMI (\si{\kg\per\m\squared}) & HLA-A2 Present \\
+ID & Demo & Gender & ABO Type  & BMI (\si{\kg\per\m\squared}) & HLA-A2 Present \\
   \hline \\[-1.8ex]
-4 & AA & M & NA & 27 & 21.7 & FALSE \\
-24 & C & M & NA & 22 & 23.9 & FALSE \\
-29 & AA & M & NA & 40 & 20.9 & TRUE \\
-30 & AA & M & NA & 25 & 20.9 & TRUE \\
-309 & C/PI & F & APOS & 22 & 24.9 & FALSE \\
-338 & C & M & OPOS & 23 & 23.4 & TRUE \\
-338 & C & M & OPOS & 24 & 23.4 & TRUE \\
-358 & C & F & OPOS & 52 & 37.1 & TRUE \\
-397 & C & M & OPOS & 53 & 31.2 & FALSE \\
-512 & C & M & OPOS & 21 & 26.5 & FALSE \\
-592 & H & M & APOS & 21 & 31.8 & FALSE \\
+4   & AA   & M & NA   & 21.7 & FALSE \\
+24  & C    & M & NA   & 23.9 & FALSE \\
+29  & AA   & M & NA   & 20.9 & TRUE  \\
+30  & AA   & M & NA   & 20.9 & TRUE  \\
+309 & C/PI & F & APOS & 24.9 & FALSE \\
+338 & C    & M & OPOS & 23.4 & TRUE  \\
+358 & C    & F & OPOS & 37.1 & TRUE  \\
+397 & C    & M & OPOS & 31.2 & FALSE \\
+512 & C    & M & OPOS & 26.5 & FALSE \\
+592 & H    & M & APOS & 31.8 & FALSE \\
   \hline \\[-1.8ex]
 \end{tabular} 
\ No newline at end of file
diff --git a/tables/donor_phenotypes.tex b/tables/donor_phenotypes.tex
index c0a7622..295d538 100644
--- a/tables/donor_phenotypes.tex
+++ b/tables/donor_phenotypes.tex
@@ -1,18 +1,18 @@
-\begin{tabular}{@{\extracolsep{5pt}} ccccccccc}
+\begin{tabular}{@{\extracolsep{5pt}} cccccccccc}
   \\[-1.8ex]\hline 
   \hline \\[-1.8ex] 
-ID & \cd{3} & \cd{4} & \cd{8} & \cd{11c} & \cd{14} & \cd{16} & \cd{19} & \cd{56} \\
+ID & Age (years) & \cd{3} & \cd{4} & \cd{8} & \cd{11c} & \cd{14} & \cd{16} & \cd{19} & \cd{56} \\
   \hline \\[-1.8ex]
-4 & NA & 32.7 & 5.5 & NA & 12.3 & NA & 10.8 & 8.2 \\
-24 & 57.0 & 39.8 & 16.5 & NA & 12.7 & NA & 5.2 & 8.6 \\
-29 & NA & 35.3 & 6.8 & NA & 14.4 & NA & 3.0 & 8.2 \\
-30 & NA & 35.2 & 18.2 & NA & 15.1 & NA & 9.0 & 8.1 \\
-309 & 96.9 & 64.6 & 28.0 & 1.2 & 0.7 & 1.1 & 0.1 & 1.5 \\
-338 & 99.1 & 65.9 & 35.7 & 1.4 & 2.0 & 1.4 & 0.3 & 1.6 \\
-338 & 99.1 & 62.4 & 35.2 & 2.2 & 1.6 & 0.6 & 0.2 & 1.5 \\
-358 & 97.3 & 75.4 & 20.7 & 3.2 & 2.4 & 3.2 & 0.6 & 3.1 \\
-397 & 98.2 & 67.3 & 33.0 & 2.8 & 1.2 & 1.5 & 0.2 & 8.0 \\
-512 & 97.4 & 62.8 & 29.6 & 2.2 & 3.9 & 2.2 & 0.2 & 1.2 \\
-592 & 95.2 & 56.1 & 35.9 & 5.3 & 0.7 & 4.6 & 2.9 & 5.4 \\
+4   & 27 & NA   & 32.7 & 5.5  & NA  & 12.3 & NA  & 10.8 & 8.2 \\
+24  & 22 & 57.0 & 39.8 & 16.5 & NA  & 12.7 & NA  & 5.2  & 8.6 \\
+29  & 40 & NA   & 35.3 & 6.8  & NA  & 14.4 & NA  & 3.0  & 8.2 \\
+30  & 25 & NA   & 35.2 & 18.2 & NA  & 15.1 & NA  & 9.0  & 8.1 \\
+309 & 22 & 96.9 & 64.6 & 28.0 & 1.2 & 0.7  & 1.1 & 0.1  & 1.5 \\
+338 & 23 & 99.1 & 65.9 & 35.7 & 1.4 & 2.0  & 1.4 & 0.3  & 1.6 \\
+338 & 24 & 99.1 & 62.4 & 35.2 & 2.2 & 1.6  & 0.6 & 0.2  & 1.5 \\
+358 & 52 & 97.3 & 75.4 & 20.7 & 3.2 & 2.4  & 3.2 & 0.6  & 3.1 \\
+397 & 53 & 98.2 & 67.3 & 33.0 & 2.8 & 1.2  & 1.5 & 0.2  & 8.0 \\
+512 & 21 & 97.4 & 62.8 & 29.6 & 2.2 & 3.9  & 2.2 & 0.2  & 1.2 \\
+592 & 21 & 95.2 & 56.1 & 35.9 & 5.3 & 0.7  & 4.6 & 2.9  & 5.4 \\
   \hline \\[-1.8ex]
 \end{tabular} 
\ No newline at end of file
diff --git a/tex/thesis.tex b/tex/thesis.tex
index 0d788b7..05c8dd5 100644
--- a/tex/thesis.tex
+++ b/tex/thesis.tex
@@ -4847,7 +4847,7 @@ strongly).
 
 The code used to aggregate all experimental data was written primarily in
 Python, with a subprocess running R in a Docker container to handle the flow
-cytometry data (\cref{fig:meta_overview}). The Postgres database itself was
+cytometry data (\cref{fig:meta_overview}). The PostgreSQL database itself was
 hosted using \gls{aws} using their proprietary Aurora implementation.
 
 \begin{figure*}[ht!]
@@ -4888,17 +4888,17 @@ The code is available here: \url{https://github.gatech.edu/ndwarshuis3/mdma}.
 \chapter{BINDING KINETICS}\label{sec:appendix_binding}
 
 The binding kinetics of \gls{stp} or \glspl{mab} were simulated using a
-receptor:ligand model, where the free-floating species in question was the
+receptor/ligand model, where the free-floating species in question was the
 ligand which bound to receptors attached to the microcarriers. Each microcarrier
 was assumed to be a porous sphere with a fixed number of receptors uniformly
 distributed throughout its interior matrix. The receptor/ligand reaction was
 assumed to be instantaneous (which is reasonable given that these are reactions
 between biotin and \gls{stp} which are extremely strong). From this, we further
-assumed a spherical interface within each microcarrier and aligned at the center
+assumed a spherical interface aligned at the center within each microcarrier 
 wherein all receptors in the interior were unbound and all on the exterior were
 bound. At $\gls{sym:time}=0$ this interface was assumed to start with a radius
 equal to that of the microcarrier, and shrunk down to radius of zero as ligand
-flowed into the porous microcarriers and bound. We assumed the concentration of
+flowed into the porous microcarrier and bound. We assumed the concentration of
 ligand to be zero at the interface and equal to the bulk concentration at the
 exterior surface of the microcarrier. Furthermore, we assumed that the interface
 moved slowly relative to the diffusion of ligand into the microcarriers, and
@@ -4981,21 +4981,21 @@ and \cref{eqn:radial_conc_change} yields \cref{eqn:stp_diffusion_1} and
 \cref{eqn:stp_diffusion_2}.
 
 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 to
 minimize the \inlinecode{SSE} output.
 
 \lstinputlisting{../code/diffusion_stp.m}
 
 The geometric diffusivity from above (the \inlinecode{geometry} variable) was
 used in the below code to obtain the reaction profile for the \gls{mab} binding
-step. The model is the same except for the parameters which were changes to
+step. The model is the same except for the parameters which were changed to
 reflect the \gls{mab} coating process.
 
 \lstinputlisting{../code/diffusion_mab.m}
 
 \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 \glspl{dms} were modeled using the following code:
 
 \lstinputlisting{../code/microcarrier_diffusion_washing.m}