| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T251 |
0-66 |
Sentence |
denotes |
There were two challenges with extracting meaning from these data. |
| T252 |
67-193 |
Sentence |
denotes |
First, there was considerable inter-patient heterogeneity for each of these immune features related to disease severity score. |
| T253 |
194-351 |
Sentence |
denotes |
Second, these binary comparisons (e.g., one immune subset versus one clinical feature) vastly underutilized the high dimensional information in this dataset. |
| T254 |
352-474 |
Sentence |
denotes |
Thus, we next visualized major T and B cell subpopulation data as it related to clinical disease severity score (Fig. 6C). |
| T255 |
475-597 |
Sentence |
denotes |
Data were clustered based on immune features and then overlaid with the disease severity score over time for each patient. |
| T256 |
598-719 |
Sentence |
denotes |
This analysis revealed groups of patients with similar composite immune signatures of T and B cell populations (Fig. 6C). |
| T257 |
720-867 |
Sentence |
denotes |
When individual CD8 T cell, CD4 T cell, or B cell populations were examined, a similar concept of patient subgroups emerged (fig. S7, F, G, and H). |
| T258 |
868-1080 |
Sentence |
denotes |
These data suggested the idea of “immunotypes” of COVID-19 patients based on integrated responses of T and B cells, though some individual cell types and/or phenotypes separated patients more clearly than others. |
