ADD donor characteristics table
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\begin{tabular}{@{\extracolsep{5pt}} ccccccc}
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\\[-1.8ex]\hline
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\hline \\[-1.8ex]
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ID & Demo & Gender & ABO Type & Age (years) & BMI (\si{\kg\per\m\squared}) & HLA-A2 Present \\
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\hline \\[-1.8ex]
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4 & AA & M & NA & 27 & 21.7 & FALSE \\
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24 & C & M & NA & 22 & 23.9 & FALSE \\
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29 & AA & M & NA & 40 & 20.9 & TRUE \\
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30 & AA & M & NA & 25 & 20.9 & TRUE \\
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309 & C/PI & F & APOS & 22 & 24.9 & FALSE \\
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338 & C & M & OPOS & 23 & 23.4 & TRUE \\
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338 & C & M & OPOS & 24 & 23.4 & TRUE \\
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358 & C & F & OPOS & 52 & 37.1 & TRUE \\
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397 & C & M & OPOS & 53 & 31.2 & FALSE \\
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512 & C & M & OPOS & 21 & 26.5 & FALSE \\
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592 & H & M & APOS & 21 & 31.8 & FALSE \\
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\hline \\[-1.8ex]
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\end{tabular}
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\begin{tabular}{@{\extracolsep{5pt}} ccccccccc}
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\\[-1.8ex]\hline
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\hline \\[-1.8ex]
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ID & \cd{3} & \cd{4} & \cd{8} & \cd{11c} & \cd{14} & \cd{16} & \cd{19} & \cd{56} \\
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\hline \\[-1.8ex]
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4 & NA & 32.7 & 5.5 & NA & 12.3 & NA & 10.8 & 8.2 \\
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24 & 57.0 & 39.8 & 16.5 & NA & 12.7 & NA & 5.2 & 8.6 \\
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29 & NA & 35.3 & 6.8 & NA & 14.4 & NA & 3.0 & 8.2 \\
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30 & NA & 35.2 & 18.2 & NA & 15.1 & NA & 9.0 & 8.1 \\
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309 & 96.9 & 64.6 & 28.0 & 1.2 & 0.7 & 1.1 & 0.1 & 1.5 \\
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338 & 99.1 & 65.9 & 35.7 & 1.4 & 2.0 & 1.4 & 0.3 & 1.6 \\
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338 & 99.1 & 62.4 & 35.2 & 2.2 & 1.6 & 0.6 & 0.2 & 1.5 \\
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358 & 97.3 & 75.4 & 20.7 & 3.2 & 2.4 & 3.2 & 0.6 & 3.1 \\
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397 & 98.2 & 67.3 & 33.0 & 2.8 & 1.2 & 1.5 & 0.2 & 8.0 \\
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512 & 97.4 & 62.8 & 29.6 & 2.2 & 3.9 & 2.2 & 0.2 & 1.2 \\
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592 & 95.2 & 56.1 & 35.9 & 5.3 & 0.7 & 4.6 & 2.9 & 5.4 \\
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\hline \\[-1.8ex]
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\end{tabular}
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@ -20,6 +20,7 @@
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\usepackage{setspace}
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\usepackage{setspace}
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\usepackage{listings}
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\usepackage{listings}
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\usepackage{tocloft}
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\usepackage{tocloft}
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\usepackage{rotating}
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\hypersetup{
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\hypersetup{
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colorlinks=true,
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colorlinks=true,
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\newcommand{\amcd}[1]{\antim{\cd{#1}}}
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\newcommand{\amcd}[1]{\antim{\cd{#1}}}
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\newcommand{\pos}[1]{#1+}
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\newcommand{\pos}[1]{#1+}
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\newcommand{\cdp}[1]{\pos{\cd{#1}}}
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\newcommand{\cdp}[1]{\pos{\cd{#1}}}
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\newcommand{\pcd}[1]{\cdp{#1}~\si{\percent}}
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\newcommand{\cdn}[1]{\cd{#1}-}
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\newcommand{\cdn}[1]{\cd{#1}-}
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\newcommand{\ptmem}{\cdp{62L}\pos{CCR7}}
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\newcommand{\ptmem}{\cdp{62L}\pos{CCR7}}
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\newcommand{\ptmemp}{\ptmem{}~\si{\percent}}
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\newcommand{\ptmemp}{\ptmem{}~\si{\percent}}
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@ -2556,13 +2558,13 @@ the treatment parameters themselves.
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In addition to these treatment parameters, we also included covariates to
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In addition to these treatment parameters, we also included covariates to
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improve the precision of our model. Among these were donor parameters including
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improve the precision of our model. Among these were donor parameters including
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age, \gls{bmi}, demographic, and gender, as well as the initial viability and
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age, \gls{bmi}, demographic, and gender, as well as the initial viability and
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CD4/CD8 ratio of the cryopreserved cell lots used in the experiments. We also
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CD4/CD8 ratio of the cryopreserved cell lots used in the experiments
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included the age of key reagents such as IL2, media, and the anti-aggregate
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(\cref{tab:meta_donors}). We also included the age of key reagents such as IL2,
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media used to thaw the T cells prior to activation. Each experiment was
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media, and the anti-aggregate media used to thaw the T cells prior to
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performed by one of three operators, so this was included as a three-level
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activation. Each experiment was performed by one of three operators, so this was
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categorical parameter. Lastly, some of our experiments were sampled
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included as a three-level categorical parameter. Lastly, some of our experiments
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longitudinally, so we included a boolean categorical to represented this
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were sampled longitudinally, so we included a boolean categorical to represented
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modification as removing conditioned media as the cell are expanding could
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this modification as removing conditioned media as the cell are expanding could
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disrupt signaling pathways.
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disrupt signaling pathways.
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\begin{table}[!h] \centering
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\begin{table}[!h] \centering
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@ -4891,6 +4893,26 @@ hosted using \gls{aws} using their proprietary Aurora implementation.
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The code is available here: \url{https://github.gatech.edu/ndwarshuis3/mdma}.
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The code is available here: \url{https://github.gatech.edu/ndwarshuis3/mdma}.
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\chapter{META ANALYSIS DONORS}\label{sec:appendix_donors}
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\begin{table}[!h]
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\caption{Donors used in meta-analysis}
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\begin{subtable}[t]{\textwidth} \centering
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\caption{characteristics}
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\input{../tables/donor_chars.tex}
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\phantomsubcaption\label{tab:meta_donors_chars}
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\end{subtable}
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\bigskip
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\begin{subtable}[t]{\textwidth} \centering
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\caption{phenotype (all in percents)}
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\input{../tables/donor_phenotypes.tex}
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\phantomsubcaption\label{tab:meta_donors_phenotypes}
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\end{subtable}
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\label{tab:meta_donors}
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\end{table}
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\chapter{BINDING KINETICS}\label{sec:appendix_binding}
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\chapter{BINDING KINETICS}\label{sec:appendix_binding}
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\newcommand{\lig}{\textit{ligand}}
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\newcommand{\lig}{\textit{ligand}}
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