Fig 1: DC parameters are differentially associated to inflammatory markers in mild and severe acute SARS-CoV-2 infected patients. Heatmap graphs representing correlations between the percentages of DC subpopulations and the percentages of DCs expressing activation and homing markers with inflammatory marker levels including CRP, D-dimer, LDH, TNF-a, IL-6, IL-8, IL1-ß, MIP1-a, MIP1-ß, IFN-?, CD25, IP-10, and neutrophil numbers, in mild (A) and severe (B) SARS-CoV-2 infected patients. Blue color represents positive correlations and red color shows negative correlations. The intensity of the color indicates the R coefficient. The most relevant data are highlighted with black squares. *p < 0.05; **p < 0.01; ***p < 0.001. Spearman test was used for nonparametric correlations
Fig 2: ROC curves of IP-10, MCP-1, d-dimer and combined indicators in blood tests of COVID-19 patients
Fig 3: Dynamic changes of coagulation and thrombosis-related indicators in the two outcomes after the critical illness turned into severe and the critically ill patients eventually died. A.1, A.2 Dynamic changes of IP-10: when the critical illness turned into severe, the IP-10 level in most patients increased at first and then decreased along the 20–30 days of the disease. When the critical illness turned into death, the IP-10 level in most patients decreased at first and then increased in approximately 20–30 days of disease progression. B.1, B.2 Dynamic changes of MCP-1: when the critical illness turned into severe, the MCP-1 level gradually decreased in most patients. When the critical illness turned to death, the MCP-1 level gradually increased in most patients. C.1, C.2 Dynamic changes of MIP1α: when the critical illness turned into severe, the MIP1α level gradually decreased in most patients. When the critical illness turned into death, the MIP1α level gradually increased in most patients
Fig 4: IP-10 and TNF-α aggravate BBB damage caused by CV-A16 infection. (A) WB was conducted to evaluate the expression of junctional complexes in brain tissues. (B) IHC analysis of brain tissues was performed to determine the expression of junctional complexes.
Fig 5: CV-A16 infection up-regulates NF-κB-mediated IP-10 production. (A) The mRNA expression of IP-10 was measured via qRT-PCR. (B) The protein expression of IP-10 was detected by WB. (C) The release concentration of IP-10 was determined by ELISA. (D) NF-κB protein expression was examined with WB in NF-κB-knockdown or NF-κB-overexpressing treated cells. (E) The protein expression of IP-10 was assessed using WB in NF-κB-knockdown or NF-κB-overexpressing treated cells. (F) The concentration of IP-10 released from NF-κB-knockdown or NF-κB-overexpressing cells was monitored via ELISA. (G) The fluorescence signals of NF-κB were visualized by confocal immunofluorescence microscopy. (H) WB analysis of TLR3-TRIF-TRAF3-TBK1-NF-κB and RIG-I/MDA5-MAVS-TRAFS-TBK1-NF-κB signaling molecules in CV-A16-infected cells.
Supplier Page from Abcam for Human IP-10 ELISA Kit