Untargeted metabonomic analysis of non-alcoholic fatty liver disease with iron overload in rats via UPLC/MS.

BACKGROUND/AIMS: In recent years, many metabolites specific to nonalcoholic fatty liver disease (NAFLD) have been identified thanks to the application of metabolomics techniques. This study aimed to investigate the candidate targets and potential molecular pathways involved in NAFLD in the presence of iron overload. METHODS: Male Sprague Dawley rats were fed with control or high-fat diet with or without excess iron. After 8, 16, 20 weeks of treatment, urine samples of rats were collected for metabolomics analysis using ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). Blood and liver samples were also collected. RESULTS: High-fat, high-iron diet resulted in increased triglyceride accumulation and increased oxidative damage. A total of 13 metabolites and four potential pathways were identified. Compared to the control group, the intensities of adenine, cAMP, hippuric acid, kynurenic acid, xanthurenic acid, uric acid, and citric acid were significantly lower (p < 0.05) and the concentration of other metabolites was significantly higher in the high-fat diet group. In the high-fat, high-iron group, the differences in the intensities of the above metabolites were amplified. CONCLUSION: Our findings suggest that NAFLD rats have impaired antioxidant system and liver function, lipid disorders, abnormal energy, and glucose metabolism, and that iron overload may further exacerbate these disorders.

An Anti-Jamming Method against Interrupted Sampling Repeater Jamming Based on Compressed Sensing.

Interrupted sampling repeater jamming (ISRJ) is an attracted coherent jamming method to inverse synthetic aperture radar (ISAR) in the past decades. By means of different jamming parameters settings, realistic dense false targets can be formed around the true target. This paper proposed an adaptive anti-jamming method against ISRJ by adjusting the number of measurements based on compressed sensing (CS). The jamming signal is energy concentrated and segmented sparse in the frequency domain. The measurements number of the reconstructed target signal and the jamming signal is different. According to the restricted isometry property (RIP) condition of CS theory, signal reconstructing performance depends on the number of measurements that varies with the sparsity of the vector. Thus, the jamming signal is suppressed, and the true target signal is retained by altering the measurements number of echo signals. Besides, the two-dimensional (2D) anti-jamming method is derived in detail. The anti-jamming effect is analyzed with different signal-to-noise ratios (SNR), sampling rates, and jam-to-signal ratios (JSR). Simulations prove the effectiveness of the proposed anti-jamming method.