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Journal of Chinese Pharmaceutical Sciences ›› 2022, Vol. 31 ›› Issue (6): 452-460.DOI: 10.5246/jcps.2022.06.039

• Original articles • Previous Articles     Next Articles

The antioxidant activity and total phenolic and total flavonoid contents of Pyracantha fortuneana fruit can be improved by solid-state fermentation with Rhizopus oryzae and Penicillium commune

Jianwei Dong*(), Xuejiao Li*(), Chen Yang, Yanqing Zhang, Huifang Zhou, Yali Li   

  1. College of Chemistry and Environmental Science, Qujing Normal University, Qujing 655011, China
  • Received:2022-01-03 Revised:2022-02-18 Accepted:2022-03-07 Online:2022-06-30 Published:2022-06-30
  • Contact: Jianwei Dong, Xuejiao Li

Abstract:

Cancer metastasis is a process with multi-step complexity and apparent randomness. In this study, we aimed to establish a stochastic mathematical model to describe the random process of cancer metastasis and predict the drug effect of QAP14 on metastasis in a mouse model. The data of lung metastases on the 22nd day after cancer cell implantation with or without the treatment of QAP14, a new chemical compound, were collected in 4T1 breast cancer BALB/c mice. Based on the exponential growth of the primary tumor and metastatic loci, a joint distribution model of metastasis size and number was developed. Disease progression of metastasis and preclinical efficacy of QAP14 were modeled. Parameters M and m representing maximum and minimum of metastasis volume were 3.24 and 0.0184 mm3, respectively. The metastasis growth rate γ and metastasis promotion time ρ were estimated and fixed to be 0.0216 d–1 and 7.8 d, respectively. The efficacy of QAP14 acted on metastasis promotion time and metastasis growth rate constant in an exponential term, and the effect parameter Effectρ and Effectγ were 16.6 and 0.327 g/mg, respectively. In the present study, we comprehensively characterized the random process of lung metastasis and efficacy of QAP14 in 4T1 breast cancer mice, which might provide a useful reference for the establishment of a clinical population model of cancer metastasis.

Key words: Stochastic population model, PD model, 4T1, Lung metastasis, Breast cancer

Supporting: