Hypoxia-inducible factor (HIF) is an important transcriptional factor,which plays crucial role in response to hypoxia.HIF is highly expressed in many human cancers,and it is closely related to tumor angiogenesis.HIF promotes tumor growth,invasion and metastasis via up-regulating vascular endothelial growth factor gene and starting associated angiogenesis.With the in-depth study of HIF regulation of tumor angiogenesis mechanism,HIF is expected to become an important target for anti-angiogenesis therapy.

In order to better control the quality of Flos Puerariae(FP),qualitative and quantitative analyses were initially performed by using chemical fingerprint and chemometrics methods in this study.First,the fingerprint of FP was developed by HPLC and the chemical markers were screened out by similarity analysis(SA),hierarchical clustering analysis(HCA),principal components analysis(PCA),and orthogonal partial least squares discriminant analysis(OPLS-DA).Next,the chemical constituents in FP were profiled and identified by HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry(HPLC-FT-ICR MS).Then,the characteristic constituents in FP were quantitatively analyzed by HPLC.As a result,31 common peaks were assigned in the fingerprint and 6 of them were considered as qualitative markers.A total of 35 chemical constituents were detected by HPLC-FT-ICR MS and 16 of them were unambiguously identified by comparing retention time,UV absorption wavelength,accurate mass,and MS/MS data with those of reference standards.Subsequently,the contents of glycitin,genistin,tectoridin,glycitein,genistein,and tectorigenin in 13 batches of FP were detected,ranging from 0.4438 to 11.06 mg/g,0.955 to 1.726 mg/g,9.81 to 57.22 mg/g,3.349 to 41.60 mg/g,0.3576 to 0.989 mg/g,and 2.126 to 9.99 mg/g,respectively.In conclusion,fingerprint analysis in combination with chemometrics methods could discover chemical markers for improving the quality control standard of FP.It is expected that the strategy applied in this study will be valuable for further quality control of other traditional Chinese medicines.

Objective:To systematically review the predictive model for de novo stress urinary incontinence (de novo SUI) after pelvic organ prolapse (POP) surgery, with the aim of providing reference for preventing the occurrence of de novo SUI.Methods:Literature on the prediction model of de novo SUI after POP surgery was electronically retrieved in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, WanFang, and VIP. The search period was from the establishment of the database to December 31, 2023, and the language was limited to Chinese and English. Two researchers independently screened literature, extracted data, and used the prediction model risk of bias assessment tool (PROBAST) to evaluate the quality of the models.Results:A total of 13 articles were included, including 13 de novo SUI risk prediction models. One literature was a prospective study, one literature was a secondary analysis of data, and the rest were retrospective studies. The area under the receiver operating characteristic curve in nine models ranged from 0.595 to 0.842, and the C-index of three models ranged from 0.710 to 0.738. Five models were not validated or only internally validated after construction. Six models were validated in one external population. The predictive performance of one model was validated in six external populations. The overall applicability of the 13 prediction models was good, but there was a certain risk of bias in all of them. Conclusions:There is a significant difference in the predictive performance of the de novo SUI risk prediction model after POP surgery, and the number is relatively small, indicating that it is still in the development stage. Future research should continuously optimize existing models and conduct external validation, and construct predictive models suitable for postoperative de novo SUI in POP patients in China.