Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

A mangiferin aglycon derivative J99745 has been identified as a potent xanthine oxidase (XOD) inhibitor by previous study. This study aimed to evaluate the hypouricemic effects of J99745 in experimental hyperuricemia mice, and explore the underlying mechanisms. Mice were orally administered 600 mg/kg xanthine once daily for 7 days and intraperitoneally injected 250 mg/kg oxonic acid on the 7th day to induce hyperuricemia. Meanwhile, J99745 (3, 10, and 30 mg/kg), allopurinol (20 mg/kg) or benzbromarone (20 mg/kg) were orally administered to mice for 7 days. On the 7th day, uric acid and creatinine in serum and urine, blood urea nitrogen (BUN), malondialdehyde (MDA) content and XOD activities in serum and liver were determined. Morphological changes in kidney were observed using hematoxylin and eosin (H&E) staining. Hepatic XOD, renal urate transporter 1 (URAT1), glucose transporter type 9 (GLUT9), organic anion transporter 1 (OAT1) and ATP-binding cassette transporter G2 (ABCG2) were detected by Western blot and real time polymerase chain reaction (PCR). The results showed that J99745 at doses of 10 and 30 mg/kg significantly reduced serum urate, and enhanced fractional excretion of uric acid (FEUA). H&E staining confirmed that J99745 provided greater nephroprotective effects than allopurinol and benzbromarone. Moreover, serum and hepatic XOD activities and renal URAT1 expression declined in J99745-treated hyperuricemia mice. In consistence with the ability to inhibit XOD, J99745 lowered serum MDA content in hyperuricemia mice. Our results suggest that J99745 exerts urate-lowering effect by inhibiting XOD activity and URAT1 expression, thus representing a promising candidate as an anti-hyperuricemia agent.

A double targets of high throughput screening model for xanthine oxidase inhibitors and superoxide anion scavengers was established. In the reaction system of xanthine oxidase, WST-1 works as the probe for the ultra oxygen anion generation, and product uric acid works as xanthine oxidase activity indicator. By using SpectraMax M5 continuous spectrum enzyme sign reflectoscope reflector, the changes of these indicators' concentration were observed and the influence factors of this reaction system to establish the high throughput screening model were studied. And the model is confirmed by positive drugs. In the reaction system, the final volume of reaction system is 50 μL and the concentrations of xanthine oxidase is 4 mU x mL(-1), xanthine 250 μmol x L(-1) and WST-1 100 μmol x L(-1), separately. The Z'-factor of model for xanthine oxidase inhibitors is 0.537 4, S/N is 47.519 9; the Z'-factor of model for superoxide anion scavengers is 0.507 4, S/N is 5.388 9. This model for xanthine oxidase inhibitors and superoxide anion scavengers has more common characteristics of the good stability, the fewer reagent types and quantity, the good repeatability, and so on. And it can be widely applied in high-throughput screening research.