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