Objective: Osteoporosis has become the biggest cause of non-fatal health issue. Currently, the limitations of traditional anti-osteoporosis drugs such as long-term ill-effects and drug resistance, have raised concerns toward complementary and alternative therapies, particularly herbal medicines and their natural active compounds. Thus, this study aimed to provide an integrative analysis of active chemicals, drug targets and interacting pathways of the herbs for osteoporosis treatment. Methods: Here, we introduced a systematic pharmacology model, combining the absorption, distribution, metabolism, and excretion (ADME) screening model, drug targeting and network pharmacology, to probe into the therapeutic mechanisms of herbs in osteoporosis. Results: We obtained 86 natural compounds with favorable pharmacokinetic profiles and their 58 targets from seven osteoporosis-related herbs. Network analysis revealed that they probably synergistically work through multiple mechanisms, such as suppressing inflammatory response, maintaining bone metabolism or improving organism immunity, to benefit patients with osteoporosis. Furthermore, experimental results showed that all the five compounds (calycosin, asperosaponin VI, hederagenin, betulinic acid and luteolin) enhanced osteoblast proliferation and differentiation in vitro, which corroborated the validity of this system pharmacology approach. Notably, gentisin and aureusidin among the identified compounds were first predicted to be associated with osteoporosis. Conclusion: Herbs and their natural compounds, being characterized as the classical combination therapies, might be engaged in multiple mechanisms to coordinately improve the osteoporosis symptoms. This work may contribute to offer novel strategies and clues for the therapy and drug discovery of osteoporosis and other complex diseases.

Objective To evaluate the correlation of the positron emission tomography/magnetic resonance imaging (PET/MR) parameters with the pathological differentiation of head and neck squamous cell carcinoma(HNSCC) and the diagnostic efficiencies of PET/MR parameters. Methods Patients with clinical suspicion of HNSCC were included and underwent PET/MR scan. HNSCC was pathologically confirmed in all these patients. The PET/MR examination included PET and MR sequences of diffusion-weighted imaging (DWI) and T2-and T1-weighted imaging. The multiple parameters of PET/MR included the mean values of apparent diffusion coefficient(ADC) and the maximum and mean values of standardized uptake value (SUV and SUV) were measured and estimated. The correlations of all the parameters and distribution between the different tumor differentiation groups were analyzed. Logistic regression was utilized to build the model as the PET/MR combined parameter for predicting the differentiation by multiple parameters of PET/MR. The receiver operating characteristic curve was calculated for each parameter and the combination. Results Totally 23 patients were included in this study:9 patients (9 males and 0 female) had well-differentiated tumor,with an average age of (61.0±6.8)years;14 cases had moderately-differentiated (n=10) or poorly-differentiated tumors (n=4),with an average age of (62.0±9.1) years. All the patients were males. There was statistical correlation between SUV and SUV (P<0.001);however,ADC showed no statistical correlation with SUV and with SUV (P=0.42,P=0.13). ADC and SUV showed significant difference between well-differentiated group and moderately-poorly-differentiated group (P=0.005,P=0.007). Compared with the individual parameters,the combination of PET/MR parameters with SUV and ADC had higher efficacy in predicting tumor differentiation,with an area under curve of 0.84. Conclusions The distributions of ADC,SUV and SUV differ among HNSCC with different pathological differentiation. Compared with the individual parameters,the combination of the PET/MR parameters has higher efficiency in predicting tumor differentiation.