Sleep disorders commonly exist and are the earliest clinical symptoms in Alzheimer's disease (AD). At present, the molecular mechanism of AD caused by sleep disorders is not clear. Recent studies have found that sleep disorders can promote the accumulation of beta amyloid (Aβ) in the brain to form amyloid plaques with toxic effects. The increased Aβ inhibits the synaptic transmission pathway and induces abnormal phosphorylation of tau protein, which eventually leads to synaptic dysfunction. In addition, the inflammatory and stress response induced by Aβ are also associated with AD. Therefore, the improvement of sleep disorders may be a new pathway for the treatment of AD, in which light therapy is proved to be particularly effective. This article reviewes the latest progresses in the influences of sleep disorders in pathogenesis and treatment of AD in recent years.

OBJECTIVE To establish HPLC fingerprint of Portulaca oleracea， establish quantitative analysis of multi- components by single-marker （QAMS） method for the content determination of caffeic acid， ferulic acid， genistin and quercetin， and provide reference for quality control of the medicine. METHODS The determination was performed on Eclipse XDB-C18 column with mobile phase consisted of methanol-0.2% phosphoric acid solution （gradient elution） at the flow rate of 1.0 mL/min. The column temperature was 25 °C， and detection wavelength was set at 360 nm. The sample size was 10 μL. HPLC fingerprint of P. oleracea was established according to the above chromatographic conditions. Cluster analysis （CA） and principal component analysis （PCA） were performed for 15 batches of specimens. Using caffeic acid as internal standard， relative correction factors of other three components were calculated by QAMS， and then the component content was calculated on the basis of relative correction factors， which was compared with the external standard method. RESULTS HPLC fingerprints of 15 batches of P. oleracea were calibrated with a total of 17 common peaks， and 4 components （caffeic acid， ferulic acid， genistin， quercetin） were identified； the similarities of 15 batches of samples were greater than 0.890. The results of CA showed that S1-S10 were clustered into one category， and S11-S15 were clustered into one category. The results of PCA revealed that the accumulative contribution rate of the two main components was 92.502%， and the classification results were basically consistent with CA. The linear range of caffeic acid， ferulic acid， genistin and quercetin were 0.003 1-0.157 1， 0.003 6-0.181 7， 0.008 5-0.425 6，0.000 4-0.021 8 mg/mL （R2≥0.999 7）； the results of precision， repeatability， stability （24 h） and recovery tests all complied with the requirements of Chinese Pharmacopoeia. The relative correction factors of ferulic acid， genistin and quercetin calculated by QAMS were 1.534， 5.302 and 0.174； there was no significant difference in the contents of components measured between this method and the external standard method. CONCLUSIONS The established HPLC fingerprint combined with QAMS can be used for the quality control of multiple index components in P. oleracea. The origin has a certain influence on the quality of P. oleracea， and the quality of P. oleracea produced in Sichuan is better than that produced in Anhui and Hebei.