Cimifugin suppresses type 2 airway inflammation by binding to SPR and regulating its protein expression in a non-enzymatic manner.

BACKGROUND: Cimifugin is one of the main bioactive components of Yu-Ping-Feng-San, a well-known traditional Chinese medicine, which can effectively relieve Allergic asthma (AA) and atopic dermatitis and reduce recurrence in clinic. However, the underlying mechanism of cimifugin on AA is still unknown. PURPOSE: In the present study, we aimed to investigate the effect and mechanism of cimifugin on AA. STUDY DESIGN: In vivo and in vitro experimental studies were performed. METHODS: The effect of cimifugin on AA was demonstrated in vivo and in vitro. Sepiapterin reductase (SPR) was predicted as the most potent target of cimifugin in treating AA by reverse docking. Molecular docking and microscale thermophoresis (MST) were used to analyze the direct binding between cimifugin and SPR. Overexpression and interference of SPR were performed to verify whether targeting SPR is a key step of cimifugin in the treatment of AA. QM385, an inhibitor of SPR, was administrated in vivo and in vitro to evaluate the role of SPR in AA. Further, HPLC and cell-free direct hSPR enzyme activity assay were performed to research whether cimifugin regulated SPR by influencing the enzyme activity. Simultaneously, the inhibitors of protein degradation were used in vitro to explore the mechanism of cimifugin on SPR. RESULTS: We found cimifugin effectively alleviated AA by reducing airway hyperresponsiveness, inhibiting type 2 cytokines-mediated airway inflammation, and restoring the expression of epithelial barrier proteins. Molecular docking predicted the direct binding ability of cimifugin to SPR, which was further verified by MST. Notably, the therapeutic effect of cimifugin on AA was dampened with SPR interfering, in contrast, the phenotypic features of AA were significantly alleviated with QM385 application both in vivo and in vitro. Interestingly, cimifugin showed no effect on the enzyme activity of SPR, as the level of its substrate sepiapterin was not affected with cimifugin treatment by cell-free enzyme activity assay. Furthermore, we found cimifugin could reduce SPR protein expression without affecting its mRNA expression probably through autophagosome pathway. CONCLUSIONS: To our knowledge, we're reporting for the first time that cimifugin can suppresses type 2 airway inflammation to alleviate AA by directly binding to SPR and regulating its protein expression in a non-enzymatic manner.

A microfluidic demonstration of "cluster-sprout-infiltrating" mode for hypoxic mesenchymal stem cell guided cancer cell migration.

Mesenchymal stem cells (MSCs) play a critical role in tumor metastasis. However, the dynamic process of MSCs-mediated cancer cell invasion remains inconclusive. In breast cancer mouse models, we observed that MSCs promoted lung metastasis. We constructed a microfluidic-based 3D co-culture device to monitor MSCs-mediated cancer cell invasion in a nutrient-deficient hypoxic microenvironment. On biomimetic microfluidic devices, MSCs guided cancer cell migration in a "cluster-sprout-infiltrating" mode. Importantly, hypoxic conditions significantly promoted MSCs migration at the infiltration stage, leading to accelerated breast cancer cell invasion. Moreover, hypoxia related LncRNA analysis showed that H19 was dramatically upregulated in response to hypoxic conditions. Conversely, H19 depletion impaired MSCs-directed breast cancer cell invasion. Mechanistically, H19 functions as a competitive endogenous RNA (ceRNA) which sequesters miRNA let-7 to release its target matrix metalloproteinase-1 (MMP1). Intriguingly, aspirin dramatically suppressed H19 and MMP1 expression and blocked MSCs infiltration under hypoxic conditions, resulting in alleviated breast cancer cell invasion. These findings point to the metastatic promoting role of MSCs in tumor stroma and suggest that MSCs might be a therapeutic target for metastatic breast cancer.

Multi-wavelength fusion column fingerprint technology combined with chemometric analysis to evaluate the overall quality of the Gardenia jasminoides root.

Chromatographic fingerprinting provides effective technical means for quality evaluation of traditional Chinese medicine. In this work, a novel multi-wavelength fusion column fingerprint was obtained by intelligent selection of chromatographic peaks from different wavelengths, which displayed the maximum peak area information under the optimal wavelength at the same retention time. Here, the Gardenia jasminoides root was selected as a sample. The multi-wavelength fusion column fingerprint graph of the Gardenia jasminoides root was constructed from five wavelengths (203 nm, 210 nm, 238 nm, 250 nm and 330 nm). The peak capacity, peak resolution, the number of common peaks and similarity were used to evaluate the performance. The 19 batches of Gardenia jasminoides root were classified into three categories with clear distinction between origin categories based on the multi-wavelength fusion column fingerprint combined with chemometrics, including hierarchical cluster analysis and principal component analysis. Nine markers of variation that led to differences between batches were screened by orthogonal partial least squares discriminant analysis. This study demonstrated that the classification model based on the multi-wavelength fusion column fingerprint was better than that on a single-wavelength, and the fusion fingerprint was suitable for the identification and quality control of traditional Chinese medicine with more comprehensive chemical composition information and more accurate prediction ability.

Research Progress of Gliomas in Machine Learning.

In the field of gliomas research, the broad availability of genetic and image information originated by computer technologies and the booming of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied as possible approaches to speed up the data mining processes. In this article, we reviewed the present situation and future orientations of machine learning application in gliomas within the context of workflows to integrate analysis for precision cancer care. Publicly available tools or algorithms for key machine learning technologies in the literature mining for glioma clinical research were reviewed and compared. Further, the existing solutions of machine learning methods and their limitations in glioma prediction and diagnostics, such as overfitting and class imbalanced, were critically analyzed.

Epigenome-Wide Tobacco-Related Methylation Signature Identification and Their Multilevel Regulatory Network Inference for Lung Adenocarcinoma.

Tobacco exposure is one of the major risks for the initiation and progress of lung cancer. The exact corresponding mechanisms, however, are mainly unknown. Recently, a growing body of evidence has been collected supporting the involvement of DNA methylation in the regulation of gene expression in cancer cells. The identification of tobacco-related signature methylation probes and the analysis of their regulatory networks at different molecular levels may be of a great help for understanding tobacco-related tumorigenesis. Three independent lung adenocarcinoma (LUAD) datasets were used to train and validate the tobacco exposure pattern classification model. A deep selecting method was proposed and used to identify methylation signature probes from hundreds of thousands of the whole epigenome probes. Then, BIMC (biweight midcorrelation coefficient) algorithm, SRC (Spearman's rank correlation) analysis, and shortest path tracing method were explored to identify associated genes at gene regulation level and protein-protein interaction level, respectively. Afterwards, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and GO (Gene Ontology) enrichment analysis were used to analyze their molecular functions and associated pathways. 105 probes were identified as tobacco-related DNA methylation signatures. They belong to 95 genes which are involved in hsa04512, hsa04151, and other important pathways. At gene regulation level, 33 genes are uncovered to be highly related to signature probes by both BIMC and SRC methods. Among them, FARSB and other eight genes were uncovered as Hub genes in the gene regulatory network. Meanwhile, the PPI network about these 33 genes showed that MAGOH, FYN, and other five genes were the most connected core genes among them. These analysis results may provide clues for a clear biological interpretation in the molecular mechanism of tumorigenesis. Moreover, the identified signature probes may serve as potential drug targets for the precision medicine of LUAD.

From dangerous branches to urban banyan: Facilitating aerial root growth of Ficus rubiginosa.

Large urban trees have many benefits. However, falling branches pose a serious hazard to both people and infrastructure. In several tree species, aerial roots grow down from branches to the ground. These roots are capable of thickening to support the branches, lessening the risk of tree failure. Unfortunately, in urban environments most aerial roots die before reaching the ground. Here, we report a new method for encouraging aerial roots to reach the ground, developed by the second-year botany class at UNSW Sydney. Our class tested three experimental treatments on aerial roots of Ficus rubiginosa Desf. ex Vent. (Port Jackson Fig)-PVC pipes filled with sphagnum moss, PVC pipes filled with potting mix, and PVC pipes filled with sphagnum moss and topped with funnels to catch extra rainwater. All three treatments significantly improved aerial root growth, with 26 of the 30 (87%) treatment roots reaching the ground after one year compared to 0 of the 10 control roots. Our method was successful for roots up to 3 m above the ground, suggesting the potential growth rate of aerial roots is substantial when conditions are favourable. Our novel approach is an attractive and cost-effective alternative to slings and other artificial supports. This project is an example of using undergraduate practical classes to teach science while simultaneously addressing important real-world problems.