diff --git a/tex/thesis.tex b/tex/thesis.tex
index 84b8c65..5e558a6 100644
--- a/tex/thesis.tex
+++ b/tex/thesis.tex
@@ -2084,7 +2084,7 @@ Flow cytometry was performed analogously to \cref{sec:flow_cytometry}.
 Cytokines were quantified via Luminex as described in
 \cref{sec:luminex_analysis}.
 
-% TODO paraphrase this entire section since I didn't do it
+% TODO add a footnote saying I didn't do this
 \subsection{NMR metabolomics}
 
 Prior to analysis, samples were centrifuged at \SI{2990}{\gforce} for
@@ -2108,8 +2108,8 @@ One-dimensional spectra were manually phased and baseline corrected in TopSpin.
 Two-dimensional spectra were processed in NMRpipe37. One dimensional spectra
 were referenced, water/end regions removed, and normalized with the PQN
 algorithm38 using an in-house MATLAB (The MathWorks, Inc.) toolbox.
-% (https://github.com/artedison/Edison_Lab_Shared_Metabolomics_UGA).
 
+% TODO add the supplemental figure alluded to here?
 To reduce the total number of spectral features from approximately 250 peaks and
 enrich for those that would be most useful for statistical modeling, a
 variance-based feature selection was performed within MATLAB. For each digitized
@@ -2130,14 +2130,15 @@ spectral data supporting the match as previously described11. Annotated
 metabolites were matched to previously selected features used for statistical
 analysis.
 
-Using the list of annotated metabolites obtained above, an approximation of a
-representative experimental spectrum was generated using the GISSMO mixture
-simulation tool.39,40 With the simulated mixture of compounds, generated at 600
-MHz to match the experimental data, a new simulation was generated at 80 MHz to
-match the field strength of commercially available benchtop NMR spectrometers.
-The GISSMO tool allows visualization of signals contributed from each individual
-compound as well as the mixture, which allows annotation of features in the
-mixture belonging to specific compounds.
+% I'm pretty sure this isn't relevant
+% Using the list of annotated metabolites obtained above, an approximation of a
+% representative experimental spectrum was generated using the GISSMO mixture
+% simulation tool.39,40 With the simulated mixture of compounds, generated at 600
+% MHz to match the experimental data, a new simulation was generated at 80 MHz to
+% match the field strength of commercially available benchtop NMR spectrometers.
+% The GISSMO tool allows visualization of signals contributed from each individual
+% compound as well as the mixture, which allows annotation of features in the
+% mixture belonging to specific compounds.
 
 Several low abundance features selected for analysis did not have database
 matches and were not annotated. Statistical total correlation spectroscopy41
@@ -3216,7 +3217,6 @@ advantage via \gls{il15} signaling.
 % cell density in the DMS cultures would lead to more of these trans interactions,
 % and therefore upregulate the IL15 pathway and lead to more memory T cells.
 
-
 \chapter{aim 3}\label{aim3}
 
 \section{introduction}
@@ -3488,6 +3488,27 @@ other groups in regard to the final tumor burden.
   \label{fig:mouse_timecourse_ivis}
 \end{figure*}
 
+% RESULT this figure
+% DISCUSSION this figure
+
+\begin{figure*}[ht!]
+  \begingroup
+
+  \includegraphics{../figures/mouse_summary.png}
+  \phantomsubcaption\label{fig:mouse_summary_1}
+  \phantomsubcaption\label{fig:mouse_summary_2}
+
+  \endgroup
+  \caption[Mouse Summary]
+  {Summary of cells injected into mice during for
+    \subcap{fig:mouse_summary_1}{the first mouse experiment} and 
+    \subcap{fig:mouse_summary_2}{the second mouse experiment}. The y axis
+    maximum is set to the maximum number of cells injected between both
+    experiments (\num{1.25e6}).
+  }
+  \label{fig:mouse_summary}
+\end{figure*}
+
 \section{discussion}
 
 % TABLE make a summary table showing the results from both experiments; this is