Beneficial Effects of Fructooligosaccharides Esterified with Lauric Acid in a Metabolic Syndrome Model Induced by a High-Fat and High-Carbohydrate Diet in Wistar Rats

Lauric acid attenuates hepato-metabolic complications and molecular alterations in high-fat diet-induced nonalcoholic fatty liver disease in rats

Nonalcoholic fatty liver disease (NAFLD) has emerged as a major chronic liver illness characterized by increase of lipid content in the liver. This study investigated the role of lauric acid to treat NAFLD in male adult Sprague Dawley rats. In this study, to induce NAFLD in the rats, a high-fat diet (HFD) was administered for eight consecutive weeks. Lauric acid groups received lauric acid (250 and 500 mg/kg; orally), concurrently with HFD for eight consecutive weeks. Lauric acid could ameliorate the serum levels of TG, TC, ALT, AST, blood glucose, and insulin. Moreover, lauric acid significantly elevated the levels of SOD, GSH, catalase, and IL-10. Additionally, it lowered the hepatic levels of MDA, ROS, MPO, 4-HNE, interleukin (IL)-1β, and tumor necrosis factor (TNF-α). Furthermore, lauric acid significantly up-regulated the hepatic expression of IRS1, AMPK, PI3K, and SIRT1 genes. In parallel, lauric acid could improve the histopathological picture of the liver and reduce the liver apoptosis via decreasing the expression of annexin V (Anx V). Finally, our data proposed that lauric acid could be an effective candidate for the NAFLD treatment.

GC-MS Analysis of Persicaria bistorta: Uncovering the Molecular Basis of Its Traditional Medicinal Use

Persicaria bistorta is a perennial herb used traditionally in treating various ailments, including diarrhea, abdominal pain, and bleeding. In this study, we used gas chromatography-mass spectrometry (GC-MS) analysis to identify the chemical composition of Persicaria bistorta. The GC-MS analysis revealed the presence of several compounds, including flavonoids, tannins, saponins, and alkaloids. Among those, the most important from medicinal points of view are ethyl oleate (3%), cyclotetradecane (4.74%), dodecanoic acid (4.69%), hexadecanoic acid (5.61%), tetradecane (5.25%), cis-13-octadecenoic acid (10.91%), and bis(2-ethylhexyl) phthalate (32%). The GC-MS analysis of ethanolic fraction of Persicaria bistorta involved in antibacterial activity showed about 18 compounds. Among those, the most important from a medicinal and nutritional point of view are bis(2-ethylhexyl) phthalate (42.20%), 6-octadecenoic acid methyl ester, (Z)- (10.37%), ethyl oleate (6.84%), hexadecanoic acid methyl ester (6.67%), and methyl ester and oleic acid (5.27%). Reported biological antibacterial activity has shown that the main compound determined in both extracts was bis(2-ethylhexyl) phthalate, which has higher peak area percentage in ethanolic extract than in ethyl acetate fraction. Some oily compounds important for health because of their cis-conformation were also revealed in the given study like ethyl oleate and oleic acid. Overall, results suggest that Persicaria bistorta may have therapeutic potential and warrant further investigation. Further research is needed to confirm the efficacy and safety of Persicaria bistorta as a natural medicine and determine its active compounds' mechanisms of action.

Microbiome and metabolome dysbiosis analysis in impaired glucose tolerance for the prediction of progression to diabetes mellitus

Gut microbiota and circulating metabolite dysbiosis predate important pathological changes in glucose metabolic disorders; however, comprehensive studies on impaired glucose tolerance (IGT), a diabetes mellitus (DM) precursor, are lacking. Here, we perform metagenomic sequencing and metabolomics on 47 pairs of individuals with IGT and newly diagnosed DM and 46 controls with normal glucose tolerance (NGT); patients with IGT are followed up after 4 years for progression to DM. Analysis of baseline data reveals significant differences in gut microbiota and serum metabolites among the IGT, DM, and NGT groups. In addition, 13 types of gut microbiota and 17 types of circulating metabolites showed significant differences at baseline before IGT progressed to DM, including higher levels of Eggerthella unclassified, Coprobacillus unclassified, Clostridium ramosum, L-valine, L-norleucine, and L-isoleucine, and lower levels of Eubacterium eligens, Bacteroides faecis, Lachnospiraceae bacterium 3_1_46FAA, Alistipes senegalensis, Megaspaera elsdenii, Clostridium perfringens, α-linolenic acid, 10E,12Z-octadecadienoic acid, and dodecanoic acid. A random forest model based on differential intestinal microbiota and circulating metabolites can predict the progression from IGT to DM (AUC = 0.87). These results suggest that microbiome and metabolome dysbiosis occur in individuals with IGT and have important predictive values and potential for intervention in preventing IGT from progressing to DM.