Mentha species are well recognized for their medicinal and aromatic properties. The comprehensive metabolite profiles of nine Mentha species have been determined. The extracts of these Mentha species were also screened for antioxidant and free radical scavenging activities. Forty-seven hydrophilic and seventeen lipophilic compounds were identified and quantified from the selected Mentha species. Also, eleven phenolic compounds, riboflavin and eight carotenoids were present, and their composition and content varied among the various Mentha species. The different Mentha species exhibited a range of antioxidant potencies. Horse mint especially exhibited the strongest antioxidant capacities (1,1-diphenyl-2-picryl-hydrazyl (DPPH), hydrogen peroxide, and reducing power assay) among the nine Mentha species. A difference between different samples from the same species was not observed by multivariate analysis. A high correlation between metabolites involved in closely linked biosynthetic pathways has been indicated. The projection to latent structure method, using the partial least squares (PLS) method, was applied to predict antioxidant capacities based on the metabolite profiles of Mentha leaves. According to the PLS analysis, several carotenoid contents, such as E-β-carotene, 9Z-β-carotene, 13Z-β-carotene and lutein, as well as phenolic compounds, showed a positive relationship in reducing the power of Mentha extracts. Horse mint is a good candidate because of its high antioxidant efficacy among the nine Mentha species included in the study.

Peroxisome proliferator-activated receptors (PPARs) are key nuclear receptors and therapeutic targets for the treatment of metabolic diseases through the regulation of insulin resistance, diabetes, and dyslipidemia. Although a few drugs that target PPARs have been approved, more diverse and novel PPAR ligands are necessary to improve the safety and efficacy of available drugs. To expedite the search for new natural agonists of PPARs, we developed a screening assay based on ultrafiltration liquid chromatography-mass spectrometry (LC-MS) that is compatible with complex samples such as dietary foods or botanical extracts. The known PPARα and/or PPARγ ligands resveratrol and rosiglitazone were used as positive controls to validate the developed method. When applied to the screening of an Artemisia argyi extract, eupatilin was identified as a selective PPARα ligand. A PPAR competitive binding assay based on FRET detection also confirmed eupatilin as a selective PPARα agonist exhibiting a binding affinity of 1.18 μM (IC₅₀). Furthermore, eupatilin activation of the transcriptional activity of PPARα was confirmed using a cell-based transactivation assay. Thus, ultrafiltration LC-MS is a suitable assay for the identification of PPAR ligands in complex matrixes such as extracts of dietary foods and botanicals.

Objective: Seronegative rheumatoid arthritis (RA) is defined as RA without circulating autoantibodies such as rheumatoid factor and anti-citrullinated protein antibodies; thus, early diagnosis of seronegative RA can be challenging. Here, we aimed to identify diagnostic biomarkers for seronegative RA by performing lipidomic analyses of sera and urine samples from patients with RA.Methods: We performed untargeted lipidomic analysis of sera and urine samples from 111 RA patients, 45 osteoarthritis (OA) patients, and 25 healthy controls (HC). These samples were divided into a discovery cohort (n = 97) and a validation cohort (n = 84). Serum samples from 20 patients with systemic lupus erythematosus (SLE) were also used for validation.Results: The serum lipidome profile of RA was distinguishable from that of OA and HC. We identified a panel of ten serum lipids and three urine lipids in the discovery cohort that showed the most significant differences. These were deemed potential lipid biomarker candidates for RA. The serum lipid panel was tested using a validation cohort; the results revealed an accuracy of 79%, a sensitivity of 71%, and a specificity of 86%. Both seropositive and seronegative RA patients were differentiated from patients with OA, SLE, and HC. Three urinary lipids showing differential expression between RA from HC were identified with an accuracy of 84%, but they failed to differentiate RA from OA. There were five lipid pathways that differed between seronegative and seropositive RA.Conclusion: Here, we identified a panel of ten serum lipids as potential biomarkers that can differentiate RA from OA and SLE, regardless of seropositivity. In addition, three urinary lipids had diagnostic utility for differentiating RA from HC.