In all living organisms, metabolic homeostasis and the immune system are the most fundamental requirements for survival. Recently, obesity has become a global public health issue, which is the cardinal risk factor for metabolic disorder. Many diseases emanating from obesity-induced metabolic dysfunction are responsible for the activated immune system, including innate and adaptive responses. Of note, inflammation is the manifest accountant signal. Deeply studied microRNAs (miRNAs) have participated in many pathways involved in metabolism and immune responses to protect cells from multiple harmful stimulants, and they play an important role in determining the progress through targeting different inflammatory pathways. Thus, immune response and metabolic regulation are highly integrated with miRNAs. Collectively, miRNAs are the new targets for therapy in immune dysfunction.

Excessive lipid deposition is a hallmark of NAFLD. Although much has been learned about the enzymes and metabolites involved in NAFLD, few studies have focused on the role of long noncoding RNAs (lncRNAs) in hepatic lipid accumulation. Here, using in vitro and in vivo models of NAFLD, we found that the lncRNA Gm15622 is highly expressed in the liver of obese mice fed a HFD and in murine liver (AML-12) cells treated with free fatty acids. Investigating the molecular mechanism in the liver-enriched expression of Gm15622 and its effects on lipid accumulation in hepatocytes and on NAFLD pathogenesis, we found that Gm15622 acts as a sponge for the microRNA miR-742-3p. This sponging activity increased the expression of the transcriptional regulator SREBP-1c and promoted lipid accumulation in the liver of the HFD mice and AML-12 cells. Moreover, further results indicated that metformin suppresses Gm15622 and alleviates NAFLD-associated lipid deposition in mice. In conclusion, we have identified an lncRNA Gm15622/miR-742-3p/SREBP-1c regulatory circuit associated with NAFLD in mice, a finding that significantly advances our insight into how lipid metabolism and accumulation are altered in this metabolic disorder. Our results also suggest that Gm15622 may be a potential therapeutic target for managing NAFLD.

Background/Aims: Liver damage is a typical manifestation of nonalcoholic fatty liver disease (NAFLD). It originates from excessive fat accumulation, leading to hepatocyte death, inflammation, and fibrosis. Nonalcoholic steatohepatitis (NASH) is a type of NAFLD with a prevalence of 49% in morbidly obese patients. Pyroptosis plays an important role in the development of NASH; thus, it is important to elucidate the effect of lipid accumulation on pyroptosis. Genipin (GNP), a natural water-soluble cross-linking agent, has hepatoprotective effects and decreases lipid accumulation in the liver; however, the mechanisms underlying these effects are unknown. Methods: In this study, qPCR and Western blot were used to examine pyroptotic gene expression in high-fat diet (HFD) induced obese mice and free fatty acids (FFAs) treated hepatocytes. At the same time, relative lactate dehydrogenase (LDH) release and Hoechst & propidium iodide (PI) staining were done to verify cell death. To explore the molecular mechanism, cell transfection were constructed with siRNA or plasmid to obtain knockdown or overexpression hepatocytes. Results: We found that HFD-fed mice and FFAs-treated hepatocytes had obvious pyroptosis, and addition of GNP reversed liver damage and inhibited pyroptosis both in vitro and in vivo. Besides, UCP2 knockdown cells showed suppressed FFAs-mediated pyroptosis, as determined by decreased pyroptotic gene expression, reduced lactate dehydrogenase (LDH) release, and reduced cell death. Consistent with this, cells transfected with UCP2 had upregulated pyroptotic gene expression, increased LDH release, and increased cell death. Conclusion: GNP reverses HFD-induced liver damage and inhibits UCP2-mediated pyroptosis. Thus, GNP may serve as a potential therapeutic candidate for NAFLD.

The liver is well known as the center of glucose and lipid metabolism in the human body. It also functions as an immune organ. Previous studies have suggested that liver nonparenchymal cells are crucial in the progression of NAFLD. In recent years, NAFLD's threat to human health has been becoming a global issue. And by far, there is no effective treatment for NAFLD. Liver nonparenchymal cells are stimulated by lipid antigens, adipokines, or other factors, and secreted immune factors can alter the expression of key proteins such as SREBP-1c, ChREBP, and PPARγ to regulate lipid metabolism, thus affecting the pathological process of NAFLD. Interestingly, some ncRNAs (including miRNAs and lncRNAs) participate in the pathological process of NAFLD by changing body fat homeostasis. And even some ncRNAs could regulate the activity of HSCs, thereby affecting the progression of inflammation and fibrosis in the course of NAFLD. In conclusion, immunotherapy could be an effective way to treat NAFLD.

This study aimed to discuss the potential roles of isomiRs of miR-27 family in metabolisms associated with disease via analyses of their evolution, expression, and function. miR-27b-3p was relatively highly expressed in liver cancer samples compared to miR-27a-3p and miR-27-5p loci. The diversity of isomiRs in miR-27-3p locus is similar to that of miRNAs among homologous genes. IsomiRs exhibited variable expression across different cancer tissue types, and some of them were abnormally expressed in ob/ob mice. Further experimental validation indicated that the protein expression of metabolism-related proteins, including PEPCK, G6Pase, FAS, and CPT1A, were significantly suppressed when canonical miR-27b was transfected into AML-12 cells. In contrast, the expression of these proteins was only slightly inhibited by isomiR-27b-1 or isomiR-27b-2 after transfection into AML-12 cells. These observations support that isomiRs exhibiting sequence divergence are functional regulatory molecules, and that they may contribute to biological processes via coordinated interactions in regulatory networks.

Drought has become one of the main challenges facing global agricultural production and crop safety. Drought stress will lead to the termination of crop photosynthesis, which will seriously affect the growth and development of crops. We aimed to study a method for identificaton of the drought stress in tomato seedlings using chlorophyll fluorescence imaging. In this study, chlorophyll fluorescence parameters and there corresponding chlorophyll fluorescence images of 4 different drought stress levels were collected. Then three feature optimization algorithms which were Successive Projections Algorithm, Iteratively Retains Informative Variables and Variable Iterative Space Shrinkage Approac were used to choose important parameters. A total of five common parameters were obtained, and the corresponding chlorophyll fluorescence images of the five common parameters were selected. And two types of image features were used to study and analyze drought stress classes: histogram features and texture features. The Pearson correlations of the features were calculated and the high correlated features were input into three models, which were Linear Discriminant Analysis (LDA), Support Vector Machines (SVM) and k-Nearest Neighbor (KNN), to identify drought stress classes. The recognition accuracy rate of LDA, SVM and KNN were 86.8%, 87.1% and 76.5% respectively. Our experiment results showed that the five common fluorescence parameters and there corresponding image features could be used to evaluate the drought stress classes of tomato seedlings, and had a good evaluation effect. This research provideed a new method for monitoring drought stress classes and had considerable prospects for non-destructive diagnosis of plant drought stress. INDEX TERMSChlorophyll fluorescence imaging, drought stress, feature extraction, machine learning, tomato seedlings. YAN LONG received the B.S. degree in electronic and information engineering and the M.S. degree in communication engineering from Shandong University, China, in 2005 and 2008, respectively, and the Ph.D. degree in agricultural electrification and automation from Northwest A&F University, China, in 2015. Since 2018, she has been an Associate Professor with the Mechanical and Electronic Engineering Department, Northwest A&F University. Her research interests include digital agriculture and agricultural information engineering, agricultural electronics, and automation technology. MINJUAN MA received the B.S. degree in electronic information engineering from Northwest A&F University, China, in 2019, where she is currently pursuing the M.S. degree in agricultural electrification and automation. Her research interests include digital agriculture and agricultural information engineering.