The high level of reactive oxygen species (ROS) in the rheumatoid arthritis (RA) microenvironment (RAM) and its persistent inflammatory nature can promote damage to joints, bones, and the synovium. Targeting strategies that integrate effective RAM regulation with imaging-based monitoring could lead to improvements in the diagnosis and treatment of RA. Here, we report the combined use of small interfering RNAs (siRNAs T/I ) and Prussian blue nanoparticles (PBNPs) to silence the expression of proinflammatory cytokines TNF-α/IL-6 and scavenge the ROS associated with RAM. To enhance the in vitro and in vivo biological stability, biocompatibility, and targeting capability of the siRNAs T/I and PBNPs, macrophage membrane vesicles were used to prepare biomimetic nanoparticles, M@P-siRNAs T/I . The resulting constructs were found to suppress tumor necrosis factor-α/interleukin-6 expression and overcome the hypoxic nature of RAM, thus alleviating RA-induced joint damage in a mouse model. The M@P-siRNAs T/I of this study could be monitored via near-infrared photoacoustic (PA) imaging. Moreover, multispectral PA imaging without the need for labeling permitted the real-time evaluation of M@P-siRNAs T/I as a putative RA treatment. Clinical microcomputed tomography and histological analysis confirmed the effectiveness of the treatment. We thus suggest that macrophage-biomimetic M@P-siRNAs T/I and their analogs assisted by PA imaging could provide a new strategy for RA diagnosis, treatment, and monitoring.

To study the potential risk factors including cerebral microbleeds (CMB) of hemorrhagic transformation (HT) after acute ischemic stroke. We included 348 consecutive patients with acute infarction who were hospitalized in two centers from June 2009 to December 2010. Acute ischemic infarctions were subdivided into atherosclerotic, cardioemblic, lacunar, and undetermined infarction groups. The related risk factors were recruited for analysis. All patients underwent gradient-echo T2-weighted imaging (GRE) to detect CMB and HT. Logistic regression analysis was used to analyze relationships, with HT as response variable and potential risk factors as explanatory variables. Multivariate logistic regression analysis demonstrated that predictor factors of HT were cardioembolic infarction (OR 24.956, 95 % CI 2.734-227.801, P = 0.004), infarction of undetermined causes (OR 19.381, 95 % CI 1.834-205.104, P = 0.014), and scores of NIHSS (OR 1.187, 95 % CI 1.109-1.292, P < 0.001), diabetes mellitus (OR 4.973, 95 % CI 2.004-12.338, P = 0.001). Whereas, the level of low-density lipoprotein was the protective factor (OR 0.654, 95 % CI 0.430-0.996, P = 0.048).The prevalence of CMB was 45.98 % (160/348) with no statistically difference among different subtypes. Thirty-five out of 348 (10.06 %) patients with ischemic stroke developed HT with a statistical difference among different subtypes of ischemia (χ (2) = 42.140, P < 0.001). The distributions of HI and PH among subgroups were variable with significant differences (χ (2) = 17.536, P = 0.001; χ (2) = 12.028, P = 0.007). PH frequency of cardioembolism was the highest (4/28, 14.29 %), and symptomatic ICH was also highest (7.14 %). The CMBs do not significantly correlate with HT. Knowledge of the risk factors associated with HT after ACI, especially HT following thrombolyitc therapy may provide insight into the mechanisms underlying the development of HT, helps to develop treatment strategy that reduces the risk of PH and implicates for the design of future acute ischemic stroke trials.

No abstract