Chloroquine inhibits NLRP3 inflammasomes activation and alleviates renal fibrosis in mouse model of hyperuricemic nephropathy with aggravation by a high-fat-diet.

Numerous epidemiological studies have demonstrated that hyperuricemia (HUA) is a risk factor for renal diseases and renal fibrosis. Dietary patterns can influence serum urate levels and hyperuricemic nephropathy (HN). NLRP3 inflammasomes play a crucial role in various inflammatory responses and contribute to HN progression. Chloroquine (CQ) is an anti-inflammatory and disease-modifying anti-rheumatic drug (DMARD) utilized in treating autoimmune diseases such as rheumatoid arthritis and systemic lupus erythematosus. In this study, we examined the effects and underlying mechanisms of CQ in a high-fat-diet (HFD) exacerbated mouse model of HN. C57BL/6 mice were randomized into either a control group or an HN group (induced by adenine/potassium oxonate treatment), followed by a normal diet or HFD, with or without CQ treatment. Our findings revealed that the HN group exhibited elevated serum levels of blood urea nitrogen (BUN) and creatinine compared to the control group. Additionally, the HN + HFD group displayed increased serum levels of uric acid, BUN, and creatinine relative to the control + HFD group. Moreover, the HFD exacerbated renal uric acid crystal deposition and fibrosis in HN mice compared to a normal diet. CQ ameliorated renal dysfunction, as evidenced by reduced serum creatinine levels, renal fibrosis, and renal tubular injury scores, and significantly decreased NLRP3, ASC, caspase-1, and IL-1ß levels in HN mice. These findings suggest that CQ inhibits the activation of NLRP3 inflammasomes and may serve as a potential therapeutic strategy for HN treatment.

Proteomic Perspective of Azole Resistance in Aspergillus fumigatus Biofilm Extracellular Matrix in Response to Itraconazole.

Azole-resistant Aspergillus fumigatus makes a major challenge to the chemotherapy for invasive aspergillosis, whereas cyp51A gene mutation is the most dominant mechanism for azole resistance. Moreover, biofilm contributes to drug resistance for A. fumigatus, and extracellular matrix (ECM) is essential to protect live cells from antifungal drugs. Therefore, we performed a comparative proteomic study on the biofilm ECM of both the wild-type and azole-resistant strains of A. fumigatus under azole pressure. In total, 2377 proteins were identified, of which 480 and 604 proteins with differential expression were obtained from the wild-type and azole-resistant A. fumigatus in exposure to itraconazole respectively (fold change > 2 or < 0.5, P-value < 0.05). We found that a high proportion of regulated proteins were located in cytoplasm, nucleus, and mitochondria. Meanwhile, GO and KEGG analyses revealed that metabolic process and ribosome pathway were significantly enriched. Particularly, differentially expressed proteins in response to azole pressure of both the wild-type and resistant strains were further analyzed. Our results indicated that these changes in biofilm ECM proteins were related to ergosterol synthesis, oxidative stress, efflux pumps, DNA repair, DNA replication, and transcription.

A comparative proteomic study on the biofilm between wild-type and azole-resistant strains of A. fumigatus under drug pressure found that changes in biofilm ECM proteins were related to ergosterol synthesis, oxidative stress, efflux pumps, DNA repair, DNA replication, and transcription.

Risk Factors for Progression of CKD with and without Diabetes.

Objective: We aim to identify independent risk factors to predict CKD progression to end stage renal disease (ESRD) in patients with or without diabetes. Methods: In this retrospective study, we enrolled CKD stage 3-4 patients between January 2013 and December 2018 and followed them until December 2020 or the initiation of dialysis. We used Kaplan-Meier to plot the survival curve. Univariate and multivariable Cox proportional hazards model was used to explore risk factors affecting the progression of CKD. The final model was used to construct nomogram for predicting CKD progression. Calibration plots and concordance index (C-index) were used to evaluate the accuracy and discrimination of the risk model. Results: We enrolled 309 CKD patients, including 80 cases in G3a, 98 cases in G3b, and 131 cases in G4. Among them, 141 patients had diabetes and 168 did not. The mean age of patients at enrolled was 57.86 ± 15.10 years, and 67% were male. The median follow-up time was 25.6 months. There were 81 patients (26.2%) that started dialysis in the total CKD cohort, 52 cases (36.9%) in the CKD with diabetes group, and 29 cases (17.3%) in the CKD without diabetes group. Hypoalbuminemia (HR =2.655, P < 0.001), proteinuria (HR =2.592, P = 0.042), increased LDL (HR =2.494, P < 0.001), diabetes (HR =2.759, P < 0.001), hypertension (HR =3.471, P = 0.037), and CKD stage (HR =2.001, P = 0.046) were risk factors for CKD progression to ESRD in the overall population. For those without diabetes, only hypoalbuminemia (HR =2.938, P = 0.030) was a risk factor for CKD progression to ESRD. For those with diabetes, both hypoalbuminemia (HR =2.758, P = 0.002), the increased level of LDL (HR =3.982, P < 0.001), and CKD stage (HR =3.781, P = 0.001) were risk factors for CKD progression to ESRD. The C-index of the final nomograms was 0.760 (P < 0.001). Conclusions: The results from our risk factor model suggest that CKD disease progression can be predicted and early strategic intervention is necessary for CKD patients to avoid renal function deterioration.