Investigating whether DHC accelerates palatal wound healing and to elucidate the role of the p38 mitogen-activated protein kinase (MAPK)/CCL2 signaling axis in DHC-mediated regulation of macrophage chemotaxis demonstrated that DHC accelerated palatal wound healing 1.6-fold in mice.
Yingyi Chen, Zhao-Nan Liu, Yijia Wang et al.· Biomedicines· 0 citations
Inter-patient heterogeneity complicates predicting treatment response in ovarian cancer (OC). We developed OMICS-FUSE, an early-fusion multi-omics predictive model integrating proteomic, transcriptomic, and methylomic data from OC patients, evaluated across five machine learning algorithms with SHapley Additive exPlanations (SHAP) and experimental validation. The early-fusion Random Forest model achieved excellent predictive accuracy (AUC = 0.939, accuracy = 0.896, F1 = 0.939), with performance comparable to or surpassing that of the best-performing single-omics models. Nevertheless, the multi-omics framework yielded superior balance across accuracy and F1 score. SHAP analysis identified key determinants of treatment response, including CLEC2A, MYH4, and methylation of SYT12_1, with functional enrichment implicating immune regulation, metabolic pathways, and drug resistance signaling. Experimental validation confirmed six hub genes (CASP8, AQP8, CAV1, FN1, CREB1, KDR), exhibiting expression patterns associated with drug resistance, immune regulation, and prognosis. This multi-omics machine learning model enables robust, interpretable prediction, uncovering molecular signatures for therapeutic stratification and precision oncology in OC.
Jie Chen, Tianshi Mao, Yu Yang et al.· npj Digital Medicine· 0 citations