Neutrophil-Mediated Nanozyme Delivery System for Acute Kidney Injury Therapy.

Reactive oxygen species (ROS) scavenging of nanozymes toward acute kidney injury (AKI) is a current promising strategy, however, the glomerular filtration barrier (GFB) limits their application for treating kidney related diseases. Here, a neutrophil-mediated delivery system able to hijack neutrophil to transport nanozyme-loaded cRGD-liposomes to inflamed kidney for AKI treatment by cRGD targeting integrin αvß1 is reported. The neutrophil-mediated nanozyme delivery system demonstrated great antioxidant and anti-apoptosis ability in HK-2 and NRK-52E cell lines. Moreover, in ischemia-reperfusion (I/R) induced AKI mice, a single dose of LM@cRGD-LPs 12 h post-ischemia significantly reduces renal function indicators, alleviates renal pathological changes, and inhibits apoptosis of renal tubular cells and the expression of renal tubular injured marker, thus remarkably reducing the damage of AKI. Mechanistically, the treatment of LM@cRGD-LPs markedly inhibits the process of Nrf2 to the nucleus and reduces the expression of the downstream HO-1, achieves a 99.51% increase in renal tissue Nrf2 levels, and an 86.31% decrease in HO-1 levels after LM@cRGD-LPs treatment. In short, the strategy of neutrophil-mediated nanozyme delivery system hold great promise as a potential therapy for AKI or other inflammatory diseases.

A PSMA PET/CT-based risk model for prediction of concordance between targeted biopsy and combined biopsy in detecting prostate cancer.

PURPOSE: This study is to investigate the diagnostic value of 68Ga-PSMA-11 in improving the concordance between mpMRI-TB and combined biopsy (CB) in detecting PCa. METHODS: 115 consecutive men with 68Ga-PSMA-11 PET/CT prior to prostate biopsy were included for analysis. PSMA intensity, quantified as maximum standard uptake value (SUVmax), minimum apparent diffusion coefficient (ADCmin) and other clinical characteristics were evaluated relative to biopsy concordance using univariate and multivariate logistic regression analyses. A prediction model was developed based on the identified parameters, and a dynamic online diagnostic nomogram was constructed, with its discrimination evaluated through the area under the ROC curve (AUC) and consistency assessed using calibration plots. To assess its clinical applicability, a decision curve analysis (DCA) was performed, while internal validation was conducted using bootstrapping methods. RESULTS: Concordance between mpMRI-TB and CB occurred in 76.5% (88/115) of the patients. Multivariate logistic regression analyses performed that SUVmax (OR= 0.952; 95% CI 0.917-0.988; P= 0.010) and ADCmin (OR= 1.006; 95% CI 1.003-1.010; P= 0.001) were independent risk factors for biopsy concordance. The developed model showed a sensitivity, specificity, accuracy and AUC of 0.67, 0.78, 0.81 and 0.78 in the full sample. The calibration curve demonstrated that the nomogram's predicted outcomes closely resembled the ideal curve, indicating consistency between predicted and actual outcomes. Furthermore, the decision curve analysis (DCA) highlighted the clinical net benefit achievable across various risk thresholds. These findings were reinforced by internal validation. CONCLUSIONS: The developed prediction model based on SUVmax and ADCmin showed practical value in guiding the optimization of prostate biopsy pattern. Lower SUVmax and Higher ADCmin values are associated with greater confidence in implementing mono-TB and safely avoiding SB, effectively balancing benefits and risks.