Ochratoxins, a common class of mycotoxin in capsicum, and techniques and methods for the determination of mycotoxins in spices have been increasingly developed in recent years. An innovative and eco-friendly method of dispersive liquid–liquid microextraction (DLLME) was demonstrated in this study, based on a synthesized deep eutectic solvent (DES) combined with LC-MS/MS, for the quantification and analysis of two ochratoxins in capsicum. The DES-DLLME method parameters entail selecting the DES type (thymol:decanoic acid, molar ratio 1:1) and DES volume (100 μL). The volume of water (3 mL) and salt concentration (0 g) undergo optimization following a step-by-step approach to achieve optimal target substance extraction efficiency. The matrix effect associated with the direct detection of the target substance in capsicum was significantly reduced in this study by the addition of isotopic internal standards corresponding to the target substance. This facilitated optimal conditions wherein quantitative analysis using LC-MS/MS revealed a linear range of 0.50–250.00 µg/mL, with all two curves calibrated with internal standards showing correlation coefficients (r²) greater than 0.9995. The method’s limits of detection (LODs) and limits of quantification (LOQs) fell in the ranges of 0.14–0.45 μg/kg and 0.45–1.45 μg/kg, respectively. The method’s spiked recoveries ranged from 81.97 to 105.17%, indicating its sensitivity and accuracy. The environmental friendliness of the technique was assessed using two green assessment tools, AGREE and complexGAPI, and the results showed that the technique was more in line with the concept of sustainable development compared to other techniques for detecting ochratoxins in capsicum. Overall, this study provides a new approach for the determination of mycotoxins in a complex food matrix such as capsicum and other spices using DES and also contributes to the application of green analytical chemistry methods in the food industry.

Hawk tea has received increasing attention for its unique flavor and potential health benefits, with antioxidant function being one of its significant bioactivities. However, the metabolic profiles, potential antioxidant components, and action mechanisms of different types of hawk tea are still unclear. In this study, the chemical components of five hawk teas were determined using untargeted metabolomics. Then, the potential antioxidant metabolites and their possible action mechanisms were revealed by integrating network pharmacology and molecular docking. The results showed that the metabolic profiles of various hawk teas differed significantly, but the content of flavonoids was the highest in each group. Network pharmacology analyses suggested that 11 potential antioxidant metabolites—four of which were the same metabolites with high levels in the five types, and seven were differential metabolites—could be involved in several metabolic pathways in vivo. These pathways included the MAPK and PI3K/AKT signaling pathways, which may be closely related to antioxidant activity. Finally, molecular docking revealed potential antioxidant metabolites bound to 25 core antioxidant targets through hydrogen bonding and hydrophobic interactions. Among them, artemisinin, astragalin, isoquercetrin, isoquercitrin, kaempferol-3-glucuronide, and UDP-L-rhamnose exhibited low binding energies to core antioxidant targets such as AKT1, RELA, and MTOR, forming stable conformation. These insights lay the basis for further elucidating the antioxidant mechanism of hawk tea.

The interaction of the dysbiosis of the gut microbiota (GM) with viral infectious disease (VID) has drawn our attention, and a better understanding of the effects of GM on VID might provide potential therapeutic approaches. However, the causal effects between GM and different types of VID remain unclear. We aimed to reveal the causal relationships between GM and VID, including adenovirus, cytomegalovirus, Epstein-Barr virus (EBV), influenza virus subtype H1N1 (H1N1) and herpes simplex virus 1 (HSV-1) infection. The GM and 5 VID types, namely, adenovirus, cytomegalovirus, EBV, H1N1 and HSV-1, were identified from large-scale genome-wide association study summary data. We used Mendelian randomization (MR) to investigate the causal relationships between GM and the 5 types of VID. MR-Egger, weighted median, inverse variance weighted, simple mode and weighted mode were used to examine the causal associations between GM and VID. Inverse variance weighting was used as the main statistical method. Sensitivity analysis was performed via the MR-Egger regression intercept method and Cochran’s Q test. There were 9 positive and 14 negative causal effects between genetic liability in the GM and 5 types of VID. Specifically, the results revealed 6 associated genera in the adenovirus group, 5 associated genera in the cytomegalovirus group, 4 associated genera in the EBV group, 3 associated genera in the H1N1 group and 5 associated genera in the HSV-1 group. The causal relationship between the GM and VIDs provides new ideas and a pretheoretical basis for exploring microbiota transplantation as a strategy for treating VID.

Background: Gastric cancer (GC) ranks among the most prevalent malignancies globally, with persistently high and increasing incidence and mortality rates. The mitochondrial permeability transition (MPT) is pivotal in deciding whether cells perish or persist, and long non-coding RNAs (lncRNAs) function as key regulators shaping cancer progression. In this research, an MPT-associated lncRNA-based prognostic model was developed, and the patterns of immune cell infiltration in GC were explored. Methods: First, lncRNAs associated with MPT were identified, the data of which were from 407 GC patients. Next, a predictive model was developed and rigorously assessed for precision and dependability using various analytical techniques. These included Cox proportional hazards regression, Kaplan - Meier survival estimates, and receiver operating characteristic (ROC) curve evaluation to ensure robust validation. In addition, further studies were conducted, including gene function enrichment analysis, immune infiltration pattern assessment, tumor mutation burden (TMB) analysis, and drug sensitivity evaluation. Finally, PINK1 - AS function was confirmed in GC cell lines through in vitro validation. Results: An efficient predictive model was developed, adeptly categorizing patients into high- and low-risk categories, demonstrating notable disparities in survival outcomes. The model demonstrated independence and efficacy across clinical factors and disease stages. Principal components analysis (PCA) confirmed the effectiveness of risk stratification, and a clinical nomogram was developed for survival prediction. Gene function enrichment analysis revealed the involvement of differentially expressed genes (DEGs) and lncRNAs in immune processes and cancer pathways. Immune infiltration analysis revealed distinct patterns of immune cells between the risk groups. Patients with high risk exhibited elevated TMB levels and poorer survival outcomes. Sensitivity analysis of medications indicated varied drug reactions across the risk categories. In vitro studies have revealed that PINK1-AS facilitates the progression of GC cell lines. Conclusion: The MPT-related lncRNA model holds promises for predicting GC prognosis and optimizing treatment strategies. However, further validation is needed to determine its clinical potential.