Methyl 6-O-cinnamoyl-α-d-glucopyranoside Ameliorates Acute Liver Injury by Inhibiting Oxidative Stress Through the Activation of Nrf2 Signaling Pathway

Integrated application of selenium and silica reduce arsenic accumulation and enhance the level of metabolites in rice grains

In this study, rice plants were co-exposed to selenium (Se) and silica (Si) under arsenic (As) stress to evaluate As accumulation in rice grains, associated cancer risk, and its impact on the types and numbers of grain metabolites. A total of 58 metabolites were identified, of which, 19 belong to sugars, and drastically altered during different treatments. Arsenic exposure significantly reduced monosaccharides, i.e., D-glucose (83%) >D-galactose (60%) >D-fructose (57%) >D-ribose (29%) but increased that monosaccharide units which have antioxidant properties (i.e. α-D-glucopyranoside and melibiose). However, the levels of D-galactose, fructose, and ribose were significantly increased during co-supplementation of selenite (SeIV) and Si under As stress. Other groups of rice grain metabolites, like sugar alcohols, organic acids, polyphenols, carboxylic acids, fatty acids, and phytosterols, were also significantly altered by As exposure and increased in grains of SeIV and Si supplemented rice compared to alone As exposure. In brief, rice growing in As-affected areas may have a low level of different metabolites. However, supplementation by selenite (SeIV) with Si not only increased metabolites and amylose/amylopectin ratio but also reduced ∼90% of As accumulation in grains. Thus, the use of SeIV with Si might be advantageous for the locals to provide a healthy diet of rice and limit As-induced cancer risk up to 10-fold.

Mitochondria-derived H2O2 triggers liver regeneration via FoxO3a signaling pathway after partial hepatectomy in mice

Reactive oxygen species (ROS) can induce oxidative injury and are generally regarded as toxic byproducts, although they are increasingly recognized for their signaling functions. Increased ROS often accompanies liver regeneration (LR) after liver injuries, however, their role in LR and the underlying mechanism remains unclear. Here, by employing a mouse LR model of partial hepatectomy (PHx), we found that PHx induced rapid increases of mitochondrial hydrogen peroxide (H2O2) and intracellular H2O2 at an early stage, using a mitochondria-specific probe. Scavenging mitochondrial H2O2 in mice with liver-specific overexpression of mitochondria-targeted catalase (mCAT) decreased intracellular H2O2 and compromised LR, while NADPH oxidases (NOXs) inhibition did not affect intracellular H2O2 or LR, indicating that mitochondria-derived H2O2 played an essential role in LR after PHx. Furthermore, pharmacological activation of FoxO3a impaired the H2O2-triggered LR, while liver-specific knockdown of FoxO3a by CRISPR-Cas9 technology almost abolished the inhibition of LR by overexpression of mCAT, demonstrating that FoxO3a signaling pathway mediated mitochondria-derived H2O2 triggered LR after PHx. Our findings uncover the beneficial roles of mitochondrial H2O2 and the redox-regulated underlying mechanisms during LR, which shed light on potential therapeutic interventions for LR-related liver injury. Importantly, these findings also indicate that improper antioxidative intervention might impair LR and delay the recovery of LR-related diseases in clinics.

Mechanism of hydroxysafflor yellow A on acute liver injury based on transcriptomics

Objective: To investigate how Hydroxysafflor yellow A (HSYA) effects acute liver injury (ALI) and what transcriptional regulatory mechanisms it may employ.

Methods: Rats were randomly divided into five groups (n = 10): Control, Model, HSYA-L, HSYA-M, and HSYA-H. In the control and model groups, rats were intraperitoneally injected with equivalent normal saline, while in the HSYA groups, they were also injected with different amounts of HSYA (10, 20, and 40 mg/kg/day) once daily for eight consecutive days. One hour following the last injection, the control group was injected into the abdominal cavity with 0.1 ml/100 g of peanut oil, and the other four groups got the same amount of a peanut oil solution containing 50% CCl4. Liver indexes were detected in rats after dissection, and hematoxylin and eosin (HE) dyeing was utilized to determine HSYA’s impact on the liver of model rats. In addition, with RNA-Sequencing (RNA-Seq) technology and quantitative real-time PCR (qRT-PCR), differentially expressed genes (DEGs) were discovered and validated. Furthermore, we detected the contents of anti-superoxide anion (anti-O2−) and hydrogen peroxide (H2O2), and verified three inflammatory genes (Icam1, Bcl2a1, and Ptgs2) in the NF-kB pathway by qRT-PCR.

Results: Relative to the control and HSYA groups, in the model group, we found 1111 DEGs that were up-/down-regulated, six of these genes were verified by qRT-PCR, including Tymp, Fabp7, Serpina3c, Gpnmb, Il1r1, and Creld2, indicated that these genes were obviously involved in the regulation of HSYA in ALI model. Membrane rafts, membrane microdomains, inflammatory response, regulation of cytokine production, monooxygenase activity, and iron ion binding were significantly enriched in GO analysis. KEGG analysis revealed that DEGs were primarily enriched for PPAR, retinol metabolism, NF-kB signaling pathways, etc. Last but not least, compared with the control group, the anti-O2− content was substantially decreased, the H2O2 content and inflammatory genes (Icam1, Bcl2a1, and Ptgs2) levels were considerably elevated in the model group. Compared with the model group, the anti-O2− content was substantially increased, the H2O2 content and inflammatory genes (Icam1, Bcl2a1, and Ptgs2) levels were substantially decreased in the HSYA group (p < 0.05).

Conclusion: HSYA could improve liver function, inhibit oxidative stress and inflammation, and improve the degree of liver tissue damage. The RNA-Seq results further verified that HSYA has the typical characteristics of numerous targets and multiple pathway. Protecting the liver from damage by regulating the expression of Tymp, Fabp7, Serpina3c, Gpnmb, Il1r1, Creld2, and the PPAR, retinol metabolism, NF-kappa B signaling pathways.