Fig 2: Prognostic significance of FGG and LBP estimated by simulated Kaplan-Meier analysis. Both overall survival (OS) and progression-free survival (PFS) were evaluated. The hazard ratio (HR) was utilized to describe the efficiency of prognostic markers and log-rank test was performed to demonstrate their statistical significance (34). (A) Estimated OS of FGG in ovarian cancer. (B) Estimated PFS of FGG in ovarian cancer. (C) Estimated OS of LBP in ovarian cancer. (D) Estimated PFS of LBP in ovarian cancer. FGG, fibrinogen gamma chain; LBP, lipopolysaccharide binding protein.

Fig 3: Receiver operating characteristic (ROC) curve assay of the selected exosomal proteins as diagnostic biomarkers. (A) ROC-AUC of GSN was 0.8309 (0.7343 to 0.9274, P<0.0001). (B) ROC-AUC of FGA was 0.8459 (0.7602 to 0.9317, P<0.0001). (C) ROC-AUC of FGG was 0.7447 (0.6323 to 0.8571, P<0.0001). (D) ROC-AUC of LBP was 0.6588 (0.5381 to 0.7794, P<0.001). GSN, gelsolin; FGA, fibrinogen alpha chain; LBP, lipopolysaccharide binding protein; FGG, fibrinogen gamma chain.

Fig 4: Impact of exercise intervention on specific inflammatory markers. A, TNF a, (B) CRP, and (C) LBP. All values are expressed as model-based means and bars are 95% CI. (§) Log transformation was performed to achieve normal distribution. *P value for time interaction (i.e., the groups (SIT + MICT) behaved similarly for the change in the parameter with a significant difference between them.