PMC:7402624 / 47611-49159 JSON TXT

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LitCovid-PD-FMA-UBERON

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T413","span":{"begin":99,"end":103},"obj":"Body_part"},{"id":"T414","span":{"begin":230,"end":235},"obj":"Body_part"},{"id":"T415","span":{"begin":321,"end":326},"obj":"Body_part"},{"id":"T416","span":{"begin":507,"end":512},"obj":"Body_part"},{"id":"T417","span":{"begin":595,"end":600},"obj":"Body_part"},{"id":"T418","span":{"begin":677,"end":682},"obj":"Body_part"},{"id":"T419","span":{"begin":746,"end":751},"obj":"Body_part"},{"id":"T420","span":{"begin":824,"end":828},"obj":"Body_part"},{"id":"T421","span":{"begin":997,"end":1001},"obj":"Body_part"},{"id":"T422","span":{"begin":1073,"end":1078},"obj":"Body_part"},{"id":"T423","span":{"begin":1116,"end":1118},"obj":"Body_part"},{"id":"T424","span":{"begin":1517,"end":1520},"obj":"Body_part"},{"id":"T425","span":{"begin":1521,"end":1529},"obj":"Body_part"}],"attributes":[{"id":"A413","pred":"fma_id","subj":"T413","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A414","pred":"fma_id","subj":"T414","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A415","pred":"fma_id","subj":"T415","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A416","pred":"fma_id","subj":"T416","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A417","pred":"fma_id","subj":"T417","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A418","pred":"fma_id","subj":"T418","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A419","pred":"fma_id","subj":"T419","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A420","pred":"fma_id","subj":"T420","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A421","pred":"fma_id","subj":"T421","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A422","pred":"fma_id","subj":"T422","obj":"http://purl.org/sig/ont/fma/fma68646"},{"id":"A423","pred":"fma_id","subj":"T423","obj":"http://purl.org/sig/ont/fma/fma84371"},{"id":"A424","pred":"fma_id","subj":"T424","obj":"http://purl.org/sig/ont/fma/fma62873"},{"id":"A425","pred":"fma_id","subj":"T425","obj":"http://purl.org/sig/ont/fma/fma62871"}],"text":"We next took advantage of the FlowSOM clustering in Figs. 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H). For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H). In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H). For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H). In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H). Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H). Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F. The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G)."}

LitCovid-PubTator

LitCovid-PD-MONDO

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T336","span":{"begin":128,"end":136},"obj":"Disease"},{"id":"T337","span":{"begin":1116,"end":1118},"obj":"Disease"}],"attributes":[{"id":"A336","pred":"mondo_id","subj":"T336","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A337","pred":"mondo_id","subj":"T337","obj":"http://purl.obolibrary.org/obo/MONDO_0019035"}],"text":"We next took advantage of the FlowSOM clustering in Figs. 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H). For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H). In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H). For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H). In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H). Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H). Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F. The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G)."}

LitCovid-PD-CLO

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T753","span":{"begin":99,"end":109},"obj":"http://purl.obolibrary.org/obo/CL_0000000"},{"id":"T754","span":{"begin":224,"end":227},"obj":"http://purl.obolibrary.org/obo/CLO_0053438"},{"id":"T755","span":{"begin":228,"end":235},"obj":"http://purl.obolibrary.org/obo/CL_0000084"},{"id":"T756","span":{"begin":253,"end":255},"obj":"http://purl.obolibrary.org/obo/CLO_0053733"},{"id":"T757","span":{"begin":321,"end":326},"obj":"http://purl.obolibrary.org/obo/GO_0005623"},{"id":"T758","span":{"begin":471,"end":480},"obj":"http://purl.obolibrary.org/obo/CLO_0001658"},{"id":"T759","span":{"begin":507,"end":512},"obj":"http://purl.obolibrary.org/obo/GO_0005623"},{"id":"T760","span":{"begin":589,"end":592},"obj":"http://purl.obolibrary.org/obo/CLO_0053438"},{"id":"T761","span":{"begin":593,"end":600},"obj":"http://purl.obolibrary.org/obo/CL_0000084"},{"id":"T762","span":{"begin":671,"end":674},"obj":"http://purl.obolibrary.org/obo/PR_000001004"},{"id":"T763","span":{"begin":675,"end":682},"obj":"http://purl.obolibrary.org/obo/CL_0000084"},{"id":"T764","span":{"begin":715,"end":724},"obj":"http://purl.obolibrary.org/obo/CLO_0001658"},{"id":"T765","span":{"begin":740,"end":743},"obj":"http://purl.obolibrary.org/obo/PR_000001004"},{"id":"T766","span":{"begin":744,"end":751},"obj":"http://purl.obolibrary.org/obo/CL_0000084"},{"id":"T767","span":{"begin":799,"end":800},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T768","span":{"begin":808,"end":817},"obj":"http://purl.obolibrary.org/obo/CLO_0001658"},{"id":"T769","span":{"begin":818,"end":821},"obj":"http://purl.obolibrary.org/obo/PR_000001004"},{"id":"T770","span":{"begin":822,"end":828},"obj":"http://purl.obolibrary.org/obo/CL_0000084"},{"id":"T771","span":{"begin":991,"end":994},"obj":"http://purl.obolibrary.org/obo/PR_000001004"},{"id":"T772","span":{"begin":995,"end":1001},"obj":"http://purl.obolibrary.org/obo/CL_0000084"},{"id":"T773","span":{"begin":1071,"end":1078},"obj":"http://purl.obolibrary.org/obo/CL_0000236"},{"id":"T774","span":{"begin":1419,"end":1421},"obj":"http://purl.obolibrary.org/obo/CLO_0008935"},{"id":"T775","span":{"begin":1423,"end":1424},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"We next took advantage of the FlowSOM clustering in Figs. 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H). For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H). In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H). For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H). In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H). Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H). Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F. The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G)."}

LitCovid-PD-CHEBI

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T322","span":{"begin":307,"end":315},"obj":"Chemical"},{"id":"T323","span":{"begin":496,"end":498},"obj":"Chemical"},{"id":"T324","span":{"begin":558,"end":566},"obj":"Chemical"},{"id":"T325","span":{"begin":1116,"end":1118},"obj":"Chemical"}],"attributes":[{"id":"A322","pred":"chebi_id","subj":"T322","obj":"http://purl.obolibrary.org/obo/CHEBI_35224"},{"id":"A323","pred":"chebi_id","subj":"T323","obj":"http://purl.obolibrary.org/obo/CHEBI_74756"},{"id":"A324","pred":"chebi_id","subj":"T324","obj":"http://purl.obolibrary.org/obo/CHEBI_35224"},{"id":"A325","pred":"chebi_id","subj":"T325","obj":"http://purl.obolibrary.org/obo/CHEBI_53319"},{"id":"A326","pred":"chebi_id","subj":"T325","obj":"http://purl.obolibrary.org/obo/CHEBI_60686"}],"text":"We next took advantage of the FlowSOM clustering in Figs. 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H). For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H). In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H). For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H). In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H). Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H). Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F. The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G)."}

LitCovid-sentences

{"project":"LitCovid-sentences","denotations":[{"id":"T275","span":{"begin":0,"end":57},"obj":"Sentence"},{"id":"T276","span":{"begin":58,"end":209},"obj":"Sentence"},{"id":"T277","span":{"begin":210,"end":428},"obj":"Sentence"},{"id":"T278","span":{"begin":429,"end":666},"obj":"Sentence"},{"id":"T279","span":{"begin":667,"end":934},"obj":"Sentence"},{"id":"T280","span":{"begin":935,"end":1057},"obj":"Sentence"},{"id":"T281","span":{"begin":1058,"end":1261},"obj":"Sentence"},{"id":"T282","span":{"begin":1262,"end":1430},"obj":"Sentence"},{"id":"T283","span":{"begin":1431,"end":1548},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"We next took advantage of the FlowSOM clustering in Figs. 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H). For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H). In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H). For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H). In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H). Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H). Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F. The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G)."}

2_test

{"project":"2_test","denotations":[{"id":"32669297-26485519-135105217","span":{"begin":602,"end":604},"obj":"26485519"}],"text":"We next took advantage of the FlowSOM clustering in Figs. 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H). For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H). In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H). For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H). In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H). Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H). Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F. The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G)."}