Background Infective endocarditis (IE) continues to be associated with great challenges. Embolic events (EE) are frequent and life‐threatening complications in IE patients. It remains challenging to predict and assess the embolic risk in individual patients with IE accurately. Hypothesis Accurate prediction of embolization is critical in the early identification and treatment of risky and potentially embolic lesions in patients with IE. Methods We searched the PubMed, Web of Science, and Google Scholar databases using a range of related search terms, and reviewed the literatures about the pathogenesis and embolic predictors of IE. Results The development of IE and its complications is widely accepted as the result of complex interactions between microorganisms, valve endothelium, and host immune responses. The predictive value of echocardiographic characteristics is the most powerful for EE. In addition, both easily obtained blood biomarkers such as C‐reactive protein, mean platelet volume, neutrophil‐to‐lymphocyte ratio, anti‐β2‐glycoprotein I antibodies, D‐Dimer, troponin I, matrix metalloproteinases, and several microbiological or clinical characteristics might be promising as potential predictors of EE. Conclusion Our review provides a synthesis of current knowledge regarding the pathogenesis and predictors of embolism in IE along with a review of potentially emerging biomarkers.

Abdominal aortic aneurysms (AAAs) elicit massive inflammatory leukocyte recruitment to the aorta. CD4+ T cells, which include regulatory T cells (Tregs) and conventional T cells (Tconvs), are involved in the progression of AAA. Tregs have been reported to limit AAA formation. However, the function and phenotype of the Tconvs found in AAAs remain poorly understood. We characterized aortic Tconvs by bulk RNA sequencing and discovered that Tconvs in aortic aneurysm highly expressed Cxcr6 and Csf2. Herein, we determined that the CXCR6/CXCL16 signaling axis controlled the recruitment of Tconvs to aortic aneurysms. Deficiency of granulocyte‐macrophage colony‐stimulating factor (GM‐CSF), encoded by Csf2, markedly inhibited AAA formation and led to a decrease of inflammatory monocytes, due to a reduction of CCL2 expression. Conversely, the exogenous administration of GM‐CSF exacerbated inflammatory monocyte infiltration by upregulating CCL2 expression, resulting in worsened AAA formation. Mechanistically, GM‐CSF upregulated the expression of interferon regulatory factor 5 to promote M1‐like macrophage differentiation in aortic aneurysms. Importantly, we also demonstrated that the GM‐CSF produced by Tconvs enhanced the polarization of M1‐like macrophages and exacerbated AAA formation. Our findings revealed that GM‐CSF, which was predominantly derived from Tconvs in aortic aneurysms, played a pathogenic role in the progression of AAAs and may represent a potential target for AAA treatment.

Infective endocarditis (IE) is a life-threatening disease with embolisms occurring in 20%-50% of cases. We aimed to evaluate the value of the systemic immune-inflammation index (SII) in predicting embolic events (EEs) in patients with infective endocarditis.A total of 186 patients diagnosed with definite IE, who admitted to the Union Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology, were retrospectively identified from November 2011 to March 2019.The median (interquartile) age of the patients was 46 (32-57) years. Viridans group streptococci were the most common microorganism identified from blood culture (24.7%). The most frequent complication was heart failure (64.2%), followed by EEs (30.2%). Patients complicated with EEs presented a significantly higher SII than those without EEs (1605.38 versus 1039.61, P = 0.001). SII had an area under the curve (AUC) value for EEs of 0.661 (95% CI: 0.575-0.747, P = 0.001), which predicted the presence of EEs with a sensitivity of 42.6% and specificity of 86.3%. Multivariate logistic regression analysis revealed that SII (OR = 6.925; 95% CI: 1.035-46.318, P = 0.046) was an independent predictor of EEs in IE patients.We demonstrated that a high level of SII is associated with a higher likelihood of EEs. The SII may be a promising predictor for EEs in patients with IE.