Atherosclerosis (AS) is a leading cause of cardiovascular diseases (CVDs) and it results in a high rate of death worldwide, with an increased prevalence with age despite advances in lifestyle management and drug therapy. Atherosclerosis is a chronic progressive inflammatory process, and it mainly presents with lipid accumulation, foam cell proliferation, inflammatory response, atherosclerotic plaque formation and rupture, thrombosis, and vascular calcification. Therefore, there is a great need for reliable therapeutic drugs or remedies to cure or alleviate atherosclerosis and reduce the societal burden. Ginsenosides are natural steroid glycosides and triterpene saponins obtained mainly from the plant ginseng. Several recent studies have reported that ginsenosides have a variety of pharmacological activities against several diseases including inflammation, cancer and cardiovascular diseases. This review focuses on describing the different pharmacological functions and underlying mechanisms of various active ginsenosides (Rb1,-Rd, -F, -Rg1, -Rg2, and -Rg3, and compound K) for atherosclerosis, which could provide useful insights for developing novel and effective anti-cardiovascular drugs.

As a newly-identified protein post-translational modification, malonylation is involved in a variety of biological functions. Recognizing malonylation sites in substrates represents an initial but crucial step in elucidating the molecular mechanisms underlying protein malonylation. In this study, we constructed a deep learning (DL) network classifier based on long short-term memory (LSTM) with word embedding (LSTMWE) for the prediction of mammalian malonylation sites. LSTMWE performs better than traditional classifiers developed with common pre-defined feature encodings or a DL classifier based on LSTM with a one-hot vector. The performance of LSTMWE is sensitive to the size of the training set, but this limitation can be overcome by integration with a traditional machine learning (ML) classifier. Accordingly, an integrated approach called LEMP was developed, which includes LSTMWE and the random forest classifier with a novel encoding of enhanced amino acid content. LEMP performs not only better than the individual classifiers but also superior to the currently-available malonylation predictors. Additionally, it demonstrates a promising performance with a low false positive rate, which is highly useful in the prediction application. Overall, LEMP is a useful tool for easily identifying malonylation sites with high confidence. LEMP is available at http://www.bioinfogo.org/lemp.

Gut microbiota plays an important role in the high-fat diet (HFD)-induced obesity and related metabolic syndrome (MetS). Our previous study has demonstrated that unsaturated alginate oligosaccharides (UAOS) degraded by alginate lyase possess significant anti-obesity effects in HFD-fed mice. Herein, we further established that UAOS could significantly ameliorate obesity-related metabolic abnormalities, including hyperlipidemia, insulin resistance and low-grade inflammation. Particularly, the beneficial effect of UAOS on these metabolic abnormalities could be significantly reversed by antibiotic supplementation. Subsequently, the microbiological analysis has revealed that UAOS treatment can modulate the overall composition of the gut microbiota, which is highly associated with metabolic parameters. UAOS supplementation can partially reverse the gut dysbiosis induced by HFD-diet or antibiotics. Specifically, UAOS treatment selectively increased the relative abundance of beneficial intestinal bacteria (e.g. Lactobacillus and Akkermansia genus) and decreased the abundance of inflammogenic bacteria (e.g. Bacteroides and Parabacteroides). These results suggest that UAOS can attenuate the HFD-induced obesity and related abnormalities through modulating gut microbiota, indicating that UAOS can act as potent prebiotic agents in treating obesity and related metabolic diseases.

In this study, the two enzymatic low molecular weight chitosan oligosaccharides (LMW-COSs), LMW-COS-H and LMW-COS-L, were prepared with average MWs of 879.6 Da and 360.9 Da, respectively. Compared to LMW-COS-L, the LMW-COS-H was more effective in improving high-fat diet (HFD)-induced metabolic abnormalities, such as obesity, hyperlipidemia, low-grade inflammation and insulin resistance. The subsequent analysis of gut microbiota showed that the supplement of LMW-COSs caused overall structural and genus/species-specific changes in the gut microbiota, which were significantly correlated with the metabolic parameters. Specifically, both of the LMW-COSs significantly decreased the relative abundance of inflammatory bacteria such as Erysipelatoclostridium and Alistipes, whereas that of the beneficial intestinal bacteria (such as Akkermansia and Gammaproteobacteria) increased significantly. This study suggested that there were potential prebiotic functions of LMW-COSs in HFD fed mice, which regulated the dysfunctional gut microbiota, alleviated low-grade inflammation and maintained the intestinal epithelial barrier.

Obesity and its related complications have become one of the leading problems affecting human health. However, current anti-obesity treatments are limited by high cost and numerous adverse effects. In this study, we investigated the use of a non-toxic green food additive, known as unsaturated alginate oligosaccharides (UAOS) from the enzymatic degradation of Laminaria japonicais, which showed effective anti-obesity effects in a high-fat diet (HFD) mouse model. Compared with acid hydrolyzed saturated alginate oligosaccharides (SAOS), UAOS significantly reduced body weight, serum lipid, including triacylglycerol (TG), total cholesterol (TC) and free fatty acids (FFA), liver weight, liver TG and TC, serum alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels, adipose mass, reactive oxygen species (ROS) formation, and accumulation induced in HFD mice. Moreover, the structural differences in β-d-mannuronate (M) and its C5 epimer α-l-guluronate (G) did not cause significant functional differences. Meanwhile, UAOS significantly increased both AMP-activated protein kinase α (AMPKα) and acetyl-CoA carboxylase (ACC) phosphorylation in adipocytes, which indicated that UAOS had an anti-obesity effect mainly through AMPK signaling. Our results indicate that UAOS has the potential for further development as an adjuvant treatment for many metabolic diseases such as fatty liver, hypertriglyceridemia, and possibly diabetes.