ADD sr figure and nmr cor figure

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Nathan Dwarshuis 2021-07-29 14:07:43 -04:00
parent 572f10a9e4
commit a3b49d42ed
3 changed files with 21036 additions and 6 deletions

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@ -2309,14 +2309,25 @@ three methods. Lastly, SR and PLSR achieved R2>90\% while other ML methods
exhibited exceedingly variable LOO-R2 (0.3\%,RF-51.5\%,LASSO) for CD8+ TN+TCM
cells.
% FIGURE the CD4/CD8 model results using SR
\begin{figure*}[ht!]
\begingroup
\includegraphics{../figures/sr_omics.png}
\endgroup
\caption[Symbolic Regression Cytokine Dependencies]
{Multi-omics culturing media prediction profiles at day 6 using symbolic
regression.}
\label{fig:sr_omics}
\end{figure*}
The top-performing technique, SR, showed that the median aggregated predictions
for CD4+ and CD8+ TN+TCM cells increases when IL2 concentration, IL15, and IL2R
increase while IL17a decreases in conjunction with other features. These
patterns combined with low values of DMS concentration and GM-CSF uniquely
characterized maximum CD8+ TN+TCM. Meanwhile, higher glycine but lower IL13 in
combination with others showed maximum CD4+ TN+TCM predictions (Fig.2).
combination with others showed maximum CD4+ TN+TCM predictions
(\cref{fig:sr_omics}).
\begin{figure*}[ht!]
\begingroup
@ -2345,6 +2356,30 @@ concentration, were commonly selected in >=5 ML methods (Fig.3a,c). Moreover,
IL13 and IL15 were found predictive in combination with these using SR
(Supp.Table.S4).
\begin{figure*}[ht!]
\begingroup
\includegraphics{../figures/nmr_cors.png}
\phantomsubcaption\label{fig:nmr_cors_lactate}
\phantomsubcaption\label{fig:nmr_cors_formate}
\phantomsubcaption\label{fig:nmr_cors_glucose}
\phantomsubcaption\label{fig:nmr_cors_matrix}
\endgroup
\caption[NMR Day 4 correlations]
{\gls{nmr} features at day 4 are strongly correlated with each other and the
response variables. Highly correlated relationships are shown for
\subcap{fig:nmr_cors_lactate}{lactate},
\subcap{fig:nmr_cors_formate}{formate}, and
\subcap{fig:nmr_cors_glucose}{glucose}. Blue and blue connections indicate
positive and negative correlations respectively. The threshold for
visualizing connections in all cases was 0.8.
\subcap{fig:nmr_cors_matrix}{The correlation matrix for all predictive
features and the total \ptmemh{} response.}
}
\label{fig:nmr_cors}
\end{figure*}
\section{discussion}
% optimization of process features
@ -2384,8 +2419,8 @@ features were observed to slightly improve prediction and dominated the ranking
of important features and variable combinations when modeling together with NMR
media analysis and process parameters (Fig.3b,d).
Predictive cytokine features such as \gls{tnfa}, IL2R, IL4, IL17a, IL13, and IL15 were
biologically assessed in terms of their known functions and activities
Predictive cytokine features such as \gls{tnfa}, IL2R, IL4, IL17a, IL13, and
IL15 were biologically assessed in terms of their known functions and activities
associated with T cells. T helper cells secrete more cytokines than T cytotoxic
cells, as per their main functions, and activated T cells secrete more cytokines
than resting T cells. It is possible that some cytokines simply reflect the
@ -2423,8 +2458,6 @@ ability to induce large numbers of memory T cells by functioning in an
autocrine/paracrine manner and could be explored by blocking either the cytokine
or its receptor.
% FIGURE correlation plots from supplement (as alluded to here)
Moreover, many predictive metabolites found here are consistent with metabolic
activity associated with T cell activation and differentiation, yet it is not
clear how the various combinations of metabolites relate with each other in a