Exploration of Compatibility Regularity of Components in Rhei Radix et Rhizoma and Magnoliae Officinalis Cortex by Uniform Design-partial Least Squares Regression Combined with Factor Analysis
CHEN Yin-fang, YU Ri-yue, YE Kang, et al. Exploration of Compatibility Regularity of Components in Rhei Radix et Rhizoma and Magnoliae Officinalis Cortex by Uniform Design-partial Least Squares Regression Combined with Factor Analysis[J]. Chinese journal of experimental traditional medical formulae, 2017, 23(13): 8-12.
CHEN Yin-fang, YU Ri-yue, YE Kang, et al. Exploration of Compatibility Regularity of Components in Rhei Radix et Rhizoma and Magnoliae Officinalis Cortex by Uniform Design-partial Least Squares Regression Combined with Factor Analysis[J]. Chinese journal of experimental traditional medical formulae, 2017, 23(13): 8-12. DOI: 10.13422/j.cnki.syfjx.2017130008.
Objective: To investigate the compatibility regularity of components (emodin
aloe-emodin
magnolol and honokiol) in Rhei Radix et Rhizoma and Magnoliae Officinalis Cortex by uniform design and partial least squares regression combined with factor analysis. Method: SD rats were randomly divided into 8 groups
including sham-operated group
model group and six compatibility groups.The rat model of acute pancreatitis was established by the retrograde injection of 3.5% sodium taurocholate.Abdominal aortic blood was drawn at 6 hour and 24 hour for determination of serum amylase(AMS)
pancreatic lipase(PL)
interleukin-6(IL-6)
IL-10 and tumor necrosis factor-α(TNF-α).The partial least squares regression was adopted to explore the influence law of factors on efficacy index
and factor analysis was used to extract the public factors in indexes. Result: The influence degree of each component on acute pancreatitis was in the order of magnolol>honokiol>emodin>aloe-emodin.Factor analysis extracted two public factors
such as pancreatic injury factors(AMS
IL-6 and TNF-α) and inflammatory factors(PL and IL-10). Conclusion: This method
uniform design-partial least squares regression combined with factor analysis
can effectively clarify the correlation and regularity between many factors and many components
which can provide more suitable effect formulas for clinical symptoms.