As the most familiar type of arthritis and a chronic illness of the joints, Osteoarthritis (OA) affects a great number of people on the global scale. XuanHuSuo powder (XHSP), a conventional herbal formula from China, has been extensively applied in OA treatment. Nonetheless, its pharmacological mechanism has not been completely expounded. In this research, a network pharmacology approach has been chosen to study the pharmacological mechanism of XHSP on OA, and the pharmacology networks were established based on the relationship between four herbs found in XHSP, compound targets, and OA targets. The pathway enrichment analysis revealed that the significant bioprocess networks of XHSP on OA were regulation of inflammation, interleukin-1β (IL-1β) production and nitric oxide (NO) biosynthetic process, response to cytokine or estrogen stimuli, and antiapoptosis. These effects have not been reported previously. The comprehensive network pharmacology approach developed by our research has revealed, for the first time, a connection between four herbs found in XHSP, corresponding compound targets, and OA pathway systems that are conducive to expanding the clinical application of XHSP. The proposed network pharmacology approach could be a promising complementary method by which researchers might better evaluate multitarget or multicomponent drugs on a systematic level.

Background The main goal of this study was to evaluate the prognosis of young patients with oral squamous cell carcinoma (SCC) with a focus on the value of the pretreatment neutrophil-to-lymphocyte ratio (NLR). Materials and methods Young (≤40 years old) patients with oral SCC were retrospectively enrolled, and each young patient was matched with an old (≥60 years old) oral SCC patient. Associations between the NLR and clinicopathological variables were analyzed by the chi-square test, and the Kaplan–Meier method was used to analyze recurrence-free survival (RFS) and disease-specific survival (DSS) rates. Results A total of 103 young patients were enrolled, and compared to the old group, the young group had a significantly lower NLR value ( p =0.012). In the young group, the 5-year RFS and DSS rates were 82% and 85%, respectively. In the old group, the 5-year RFS and DSS rates were 65% and 71%, respectively, and the differences between the groups were significant (both p <0.05). In the young patients with an NLR≤2.56, the 5-year DSS rate was 93%, while in the young patients with an NLR >2.56, the 5-year DSS rate was 76%. This difference was significant ( p =0.020). A further Cox model analysis confirmed that the NLR was an independent prognostic factor for DSS. Conclusion Young patients with oral SCC have a better prognosis than old oral SCC patients, and the NLR is significantly associated with DSS in young patients.

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Si-Wu-Tang (SWT), a traditional Chinese herbal formula, has shown an effect on antibreast cancer. However, the mechanisms and bioactive components of SWT are still unclear. Fortunately, cell type-specific molecular network has provided an effective method. This study integrated the data of formula components, all types of biomolecules in the human body, and nonexpressed protein in breast cancer cells and constructed the breast cancer cell network and the biological network that SWT acted on the breast cancer-related targets by Entity Grammar System (EGS). Biological network showed 59 bioactive components acting on 15 breast cancer-related targets. The antibreast cancer mechanisms were summarized by enrichment analysis: regulation of cell death, response to hormone stimulation, response to organic substance, regulation of phosphorylation of amino acids, regulation of cell proliferation, regulation of signal transmission, and affection of gland development. In addition, we discovered that verbascoside played the role of antibreast cancer by inhibiting cell proliferation, but there was not a report on this effect. The results of CCK8 and western blot were consistent with the antibreast cancer effect of verbascoside based on biological network. Biological network modeling by EGS and network analysis provide an effective way for uncovering the mechanism and identifying the bioactive components of SWT.