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itis by significantly impairing DSS's ability to induce high expression levels of NF-κB/p65, IL-1β, IL-6, and TNF-α. JQP also reduced the levels of COX-2, CCL2, CXCL2, HIF-1α, MMP3 and MMP9 and regulated the Th17/Treg cell balance in DSS-induced mice.

This study demonstrated that JQP could treat UC by improving the mucosal inflammatory response, repairing the intestinal barrier, and modulating the Th17/Treg immune balance. The results of this study provide new insights into UC treatment and further elucidate the theoretical and practical implications of the pharmaceutical development of TCMs.

This study demonstrated that JQP could treat UC by improving the mucosal inflammatory response, repairing the intestinal barrier, and modulating the Th17/Treg immune balance. The results of this study provide new insights into UC treatment and further elucidate the theoretical and practical implications of the pharmaceutical development of TCMs.

Oncostatin M (OSM) and leukemia inhibitory factor (LIF) are two important pro-inflammatory cytokines of the interleukin-6 (IL-6) family. The two cytokines mediated signaling was recently found to be closely associated with cancer and chronic inflammation, which represent promising therapeutic targets for the treatment of many solid tumors and inflammatory disease. As the most closely related members, cross-reactivity of them may result in undesired activation of off-target cells, leading to toxicity or lack of efficacy of the therapeutic effects. However, the mechanism of the cross-reactivity of OSM and LIF is not well understood.

In this work, protein-protein docking, molecular dynamics (MD) simulations with explicit solvent and post endpoints binding free energy (BFE) analysis were carried out to further understand the structural and energetic principles of interactions between the two cytokines and the shared receptor LIFR.

For the first time, the simulation given a computational model of OSM-LIFR interaction, and provided significant insights into the mechanism of OSM and LIF cross-react with LIFR. The identified common features shared by OSM and LIF bind to LIFR involving 10 "conserved" residues (90% similarity) distributed at the binding site III comprised of AB loop, BC loop and D helix. In addition, 11 shared residues were identified in LIFR contribute 77.85% and 84.63% energies for OSM and LIF binding, which play a critical role in the formation of the two cytokine-receptor complexes. Moreover, the "nonconserved" residues at the same position of cytokines such as Asp41 in OSM and Pro51 in LIF as well as the three residues (Glu338, Asn201 and Glu260) in LIFR were also discovered.

These important information may facilitate the rational design of novel chemical or biological agents with less toxicity and improved efficacy.

These important information may facilitate the rational design of novel chemical or biological agents with less toxicity and improved efficacy.Maternally expressed 3 (MEG3) and RNA binding motif single stranded interacting protein 3 (RBMS3) are abnormally expressed in breast cancer susceptibility genes (BRCA), but the mechanism of the two in breast cancer (BC) is unclear. By performing in vivo and in vitro experiments, we found that MEG3 and RBMS3 were low-expressed, negatively correlated with high-expressed miR-141-3p, were positively correlated with each other in BC. MEG3 targeted miR-141-3p, and miR-141-3p targeted RBMS3. MEG3, which was mainly distributed in BC cytoplasm, could down-regulate miR-141-3p and up-regulate RBMS3, and reverse effect of miR-141-3p on related gene expressions and on promoting cancer development. Overexpressed MEG3 inhibited growth of xenografts, promoted cell apoptosis via regulating apoptosis related factors, and up-regulated RBMS3 expression but down-regulated miR-141-3p. The findings of this study showed that MEG3 inhibited proliferation and promoted apoptosis of BC cells through the miR-141-3p/RBMS3 axis, and MEG3 inhibited growth of xenografts through miR-141-3p.The RGS (regulator of G protein signaling) gene family, which includes negative regulators of G protein-coupled receptors, comprises important drug targets for malignant tumors. It is thus of great significance to explore the value of RGS family genes for diagnostic and prognostic prediction in ovarian cancer. The RNA-seq, immunophenotype, and stem cell index data of pan-cancer, The Cancer Genome Atlas (TCGA) data, and GTEx data of ovarian cancer were downloaded from the UCSC Xena database. In the pan-cancer database, the expression level of RGS1, RGS18, RGS19, and RGS13 was positively correlated with stromal and immune cell scores. Cancer patients with high RGS18 expression were more sensitive to cyclophosphamide and nelarabine, whereas those with high RGS19 expression were more sensitive to cladribine and nelarabine. The relationship between RGS family gene expression and overall survival (OS) and progression-free survival (PFS) of ovarian cancer patients was analyzed using the KM-plotter database, RGS17, RGS16, RGS1, and RGS8 could be used as diagnostic biomarkers of the immune subtype of ovarian cancer, and RGS10 and RGS16 could be used as biomarkers to predict the clinical stage of this disease. Further, Lasso cox analysis identified a five-gene risk score (RGS11, RGS10, RGS13, RGS4, and RGS3). Multivariate COX analysis showed that the risk score was an independent prognostic factor for patients with ovarian cancer. Immunohistochemistry and the HPA protein database confirmed that the five-gene signature is overexpressed in ovarian cancer. GSEA showed that it is mainly involved in the ECM-receptor interaction, TGF-beta signaling pathway, Wnt signaling pathway, and chemokine signaling pathway, which promote the occurrence and development of ovarian cancer. The prediction model of ovarian cancer constructed using RGS family genes is of great significance for clinical decision making and the personalized treatment of patients with ovarian cancer.Triple-negative breast cancer (TNBC) patients often exhibit poor prognosis and breast cancer relapse due to metastasis. This results in secondary tumor generation at distant-unrelated organs that account for the majority of breast cancer-related deaths. selleck chemicals Although breast cancer stem cells (CSCs) have been attributed to metastasis, a mechanistic understanding is essential for developing therapeutic interventions to combat breast cancer relapse. Breast CSCs are generated due to Epithelial-to-mesenchymal transition (EMT), regulated by transcription factors (EMT-TF) that are implicated in tumorigenesis and metastasis. However, the underlying mechanisms mediating these processes remain elusive. In the present study, we have reported that TWIST1, an EMT-TF, exhibits positive transcriptional regulation on PDGFRβ promoter, thus identifying PDGFRβ as one of the downstream targets of EMT regulation in breast CSCs. Breast cancer cells overexpressing PDGFRβ exhibited a significant increase in physiological and molecular properties comparable to that of breast CSCs, while molecular silencing of PDGFRβ in breast CSCs perturbed these phenomena.