Renoprotective activity of Ribes diacanthum pall (RDP) against inflammation in cisplatin-stimulated mice model and human renal tubular epithelial cells

Investigation of pulmonary toxicity evaluation on mice exposed to polystyrene nanoplastics: The potential protective role of the antioxidant N-acetylcysteine

Accumulating evidences show that the hazardous substance atmospheric nanoplastics increase the respiratory risk of individuals, but the inside toxicity mechanisms to lung tissue remain unclear. This study aims at investigating the potential mechanisms of inhaled cationic polystyrene nanoplastics (amine-polystyrene nanoplastics, APS-NPs)-induced pulmonary toxicity on mice. In vivo, the mice intratracheal administrated with APS-NPs suspension (5 mg/kg) were found inflammatory infiltrates in lung tissues through histopathology analysis. Furthermore, transcriptome analysis demonstrated that 1821 differentially expressed mRNA between APS group and control group were dominantly associated with 288 known KEGG pathways, indicating that APS-NPs might cause early inflammatory responses in lung tissue by activating the NLRP3/capase-1/IL-1β signaling pathway. Moreover, in vitro results also showed that NLRP3 inflammasome could be activated to induce pyroptosis in MLE-12 cells after exposure to APS-NPs. And, MH-S cells after exposure to APS-NPs exhibited increased Irg1 proteins, leading to the increasing generation of ROS and inflammatory factors (e.g., tnf-α, il-6, il-1β). In conclusion, these results revealed that Irg1/NF-κB/NLRP3/Caspase-1 signaling pathway was activated significantly after exposing to APS-NPs, leading to pulmonary toxicity on mice. Intriguingly, prior administration of the clinical antioxidant N-acetylcysteine (NAC) could serve as a possible candidate for the prevention and treatment of pulmonary toxicity induced by APS-NPs. The study contributes to a better understanding of the potential risks of environmental nanoplastics to humans and its improvement measure.

Combining multiple acquisition modes and computational data annotation for structural characterization in traditional Chinese medicine: Miao Nationality medicine Qijiao Shengbai Capsule as a case study

Qijiao Shengbai Capsule (QSC) is a reputable Miao Nationality medicine used for treating leukopenia, but its chemical composition has not yet been elucidated. We herein present a strategy, by integrating multiple data acquisition, computational data annotation and processing methods to visualize and identify the complicated constituents in QSC based on ultra-high-performance liquid chromatography coupled with traveling wave ion mobility quadrupole time-of-flight mass spectrometry (UPLC-TWIMS-QTOF-MS). The multiple data acquisition modes, including data-independent mass spectrometryEnergy (MSE), data-independent high-definition mass spectrometryEnergy (HDMSE), and fast data-dependent acquisition (fast-DDA), in both positive and negative ion modes, were conducted on a Waters-SYNAPT G2-Si mass spectrometer with an ESI source. An in-house library built by the UNIFI platform could efficiently process the peak annotation of known compounds, whilst different structural types were clustered in the molecular networks for the analogous classification and structural annotation of the unknown ones. Neutral loss, diagnostic ions, feature fragmentation behaviors, and community curation of mass spectrometry data of known compounds helped exploit those similar neighboring nodes of unknown compounds. Moreover, by combination of the predicted CCS values from CCS platform with the experimental CCS values from HDMSE, as well as diagnostic fragment ions, isomer compounds were annotated. By integrating reference compound comparison, a total of 202 constituents, including 94 flavonoids, 12 saponins, 30 phthalides, 38 organic acids, 3 amino acids, 7 alkaloids and 18 others, were unambiguously characterized or tentatively identified in QSC. Among them, 5 potential new compounds were detected and 12 pairs of isomers were comprehensively distinguished. Conclusively, the established multiple acquisition modes, computational data processing and analysis strategy proved to be useful for the in-depth structural identification of QSC.