Analysis of influencing factors on quality of life in patients with chronic kidney disease undergoing maintenance haemodialysis.

Objective: To investigate and analyse the quality of life (QoL) of patients with chronic kidney disease (CKD) undergoing maintenance haemodialysis (MHD), explore influencing factors and provide a basis for formulating corresponding intervention measures. Methods: A cross-sectional study was conducted on 190 patients with CKD undergoing MHD in hospital between March 2021 and March 2022. A general information questionnaire and the Kidney Disease Quality of Life Short Form were used to collect data. The QoL scores of patients with CKD undergoing MHD were calculated and compared by t-test and analysis of variance. Pearson correlation analysis was used to analyse the correlation between QoL scores and related factors. Stepwise multiple linear regression analysis was used to screen the influencing factors of QoL. Results: The total score of QoL of patients with CKD undergoing MHD was 59.32 ± 11.67, and the scores of physical component summary, mental component summary and kidney disease component summary were 50.21 ± 9.32, 48.76 ± 10.81 and 66.34 ± 12.76, respectively. The QoL scores of patients with CKD undergoing MHD were significantly different in age, education level, marital status, employment status, monthly income, dialysis frequency, dialysis duration and complications (p < 0.05). The QoL scores were positively correlated with education level, monthly income and dialysis frequency, and negatively correlated with age, dialysis duration and blood phosphorus level (p < 0.05). Stepwise multiple linear regression analysis showed that age, education level, employment status, dialysis frequency, dialysis duration and blood phosphorus level were the main influencing factors of QoL (p < 0.05). Conclusion: The QoL of patients with CKD undergoing MHD is low, and it is affected by multiple factors. We suggest that healthcare workers should pay attention to the physical and mental health of patients with CKD undergoing MHD, provide individualised and comprehensive nursing interventions and improve their QoL.

A pilot study on identifying gene signatures as markers for predicting patient response to antiseizure medications.

The majority of the biomarkers were associated with the diagnosis of epilepsy and few of them can be applied to predict the response to antiseizure medications (ASMs). In this study, we identified 26 significantly up-regulated genes and 32 down-regulated genes by comparing the gene expression profiles of patients with epilepsy that responded to valproate with those without applying any ASM. The results of gene set enrichment analysis indicated that the ferroptosis pathway was significantly impacted (p = 0.0087) in patients who responded to valproate. Interestingly, the gene NCOA4 in this pathway exhibited significantly different expression levels between the two groups, indicating that NCOA4 could serve as a potential biomarker to better understand the mechanism of valproate resistance. In addition, six up-regulated genes SF3A2, HMGN2, PABPN1, SSBP3, EFTUD2, and CREB3L2 as well as six down-regulated genes ZFP36L1, ACRC, SUB1, CALM2, TLK1, and STX2 also showed significantly different expression patterns between the two groups. Moreover, based on the gene expression profiles of the patients with the treatment of valproate, carbamazepine, and phenytoin, we proposed a strategy for predicting the response to the ASMs by using the Connectivity Map scoring method. Our findings could be helpful for better understanding the mechanisms of drug resistance of ASMs and improving the clinical treatment of epilepsy.

Synergistic Phototherapy-Molecular Targeted Therapy Combined with Tumor Exosome Nanoparticles for Oral Squamous Cell Carcinoma Treatment.

Oral squamous cell carcinoma (OSCC) contributes to more than 90% of all oral malignancies, yet the performance of traditional treatments is impeded by limited therapeutic effects and substantial side effects. In this work, we report a combinational treatment strategy based on tumor exosome-based nanoparticles co-formulating a photosensitizer (Indocyanine green) and a tyrosine kinase inhibitor (Gefitinib) (IG@EXOs) for boosting antitumor efficiency against OSCC through synergistic phototherapy-molecular targeted therapy. The IG@EXOs generate distinct photothermal/photodynamic effects through enhanced photothermal conversion efficiency and ROS generation, respectively. In vivo, the IG@EXOs efficiently accumulate in the tumor and penetrate deeply to the center of the tumor due to passive and homologous targeting. The phototherapy effects of IG@EXOs not only directly induce potent cancer cell damage but also promote the release and cytoplasmic translocation of Gefitinib for achieving significant inhibition of cell proliferation and tumor angiogenesis, eventually resulting in efficient tumor ablation and lymphatic metastasis inhibition through the synergistic phototherapy-molecular targeted therapy. We envision that the encouraging performances of IG@EXOs against cancer pave a new avenue for their future application in clinical OSCC treatment.

Structure-Activity Relationship (SAR) Model for Predicting Teratogenic Risk of Antiseizure Medications in Pregnancy by Using Support Vector Machine.

Teratogenicity is one of the main concerns in clinical medications of pregnant women. Prescription of antiseizure medications (ASMs) in women with epilepsy during pregnancy may cause teratogenic effects on the fetus. Although large scale epilepsy pregnancy registries played an important role in evaluating the teratogenic risk of ASMs, for most ASMs, especially the newly approved ones, the potential teratogenic risk cannot be effectively assessed due to the lack of evidence. In this study, the analyses are performed on any medication, with a focus on ASMs. We curated a list containing the drugs with potential teratogenicity based on the US Food and Drug Administration (FDA)-approved drug labeling, and established a support vector machine (SVM) model for detecting drugs with high teratogenic risk. The model was validated by using the post-marketing surveillance data from US FDA Spontaneous Adverse Events Reporting System (FAERS) and applied to the prediction of potential teratogenic risk of ASMs. Our results showed that our proposed model outperformed the state-of-art approaches, including logistic regression (LR), random forest (RF) and extreme gradient boosting (XGBoost), when detecting the high teratogenic risk of drugs (MCC and recall rate were 0.312 and 0.851, respectively). Among 196 drugs with teratogenic potential reported by FAERS, 136 (69.4%) drugs were correctly predicted. For the eight commonly used ASMs, 4 of them were predicted as high teratogenic risk drugs, including topiramate, phenobarbital, valproate and phenytoin (predicted probabilities of teratogenic risk were 0.69, 0.60 0.59, and 0.56, respectively), which were consistent with the statement in FDA-approved drug labeling and the high reported prevalence of teratogenicity in epilepsy pregnancy registries. In addition, the structural alerts in ASMs that related to the genotoxic carcinogenicity and mutagenicity, idiosyncratic adverse reaction, potential electrophilic agents and endocrine disruption were identified and discussed. Our findings can be a good complementary for the teratogenic risk assessment in drug development and facilitate the determination of pharmacological therapies during pregnancy.

Degradation prognosis for proton exchange membrane fuel cell based on hybrid transfer learning and intercell differences.

Proton exchange membrane fuel cell (PEMFC) has been widely used in diverse applications. However, degradation and durability problem is one of the biggest barriers to take PEMFCs into extensive commercial use. Prognostics and health management is an effective solution to this problem. In this study, we focus on its core technology prognostics and propose an individual difference conscious prediction method for PEMFC using a hybrid transfer learning approach to get higher accuracy. Firstly, a time-scale self-optimization local weighted regression method is designed to adaptively smooth the raw data to prominent the performance degradation trend. Then, to obtain a more similar curve to the predicted fuel cell as the training data of the prediction model, a transferability measurement method using cosine-distance selects the most similar historical test data. Furtherly, it is utilized to generate a more similar curve by a data transfer method combining a deep learning model named stacked autoencoder and a hybrid transfer learning strategy. Two types of transfer learning approaches are fused to maximally mine available information from historical data and previous models to help improve the similarity of the generated curve. In this process, the common degradation information of all cells and individual information of the predicted cells are considered to improve generation quality. Finally, a prediction model using stacked Long-short Term Memory(LSTM) having a significant advantage in modeling series relation is trained by the generated samples cut with variable width sliding windows and estimates remaining useful life(RUL) the target fuel cell. Experimental validation data are employed to verify the effectiveness of the proposed algorithm. Satisfying results are also obtained by accuracy comparison under different smoothing scales, numbers of transferable samples, and prediction methods.

Correction: A proteomic study of Shengmai injection's mechanism on preventing cardiac ischemia-reperfusion injury via energy metabolism modulation.

Correction for 'A proteomic study of Shengmai injection's mechanism on preventing cardiac ischemia-reperfusion injury via energy metabolism modulation' by Shuyu Zhan et al., Mol. BioSyst., 2015, 11, 540-548.

Qingnaoyizhi decoction suppresses the formation of glial fibrillary acidic protein-positive cells in cultured neural stem cells by inhibiting the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway.

OBJECTIVE: Inactivation of the Janus kinase 2 in treated NSCs. Furthermore, QNYZD may play a direct role in suppressing the formation of GFAP-positive cells and enhancing neuronal differentiation by inhibiting JAK2/STAT3 activation. Overall, these results provide insights into the possible mechanism underlying QNYZD-mediated neurogenesis. (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling axis plays a crucial role in determining the fate of neural stem cells (NSCs). Qingnaoyizhi decoction (QNYZD) has been used for the treatment of vascular dementia and has shown to improve synaptic remodeling. The aim of this study was to evaluate the effect of cerebrospinal fluid (CSF) containing QNYZD (CSF-QNYZD) on the differentiation of cultured NSCs and the involvement of the JAK2/STAT3 pathway. METHODS: The protein expression levels of glial fibrillary acidic protein (GFAP), tubulin, drosophila mothers against decapentaplegic protein (SMAD-1), STAT3, and phosphorylated-STAT3 were detected by western immunoblot analysis in the groups: control, CSF, JAK/STAT inhibitor (AG490), CSF-QNYZD, and CSF-XDZ (CSF-Xidezhen). The differentiation of NSCs was determined by immunofluorescence staining. The proliferation of NSCs was measured using the Cell Counting Kit-8 proliferation assay. RESULTS: Compared with the control group, CSF-QNYZD and AG490 significantly increased the number and expression of tubulin-positive cells, reduced the number and expression of GFAP-positive cells, and down-regulated the expression of p-STAT3. However, CSF-QNYZD also decreased the expression of SMAD-1 and STAT3. CONCLUSION: Enhanced neuronal differentiation may be associated with the down-regulation of glial differentiation instead of promoting proliferation in treated NSCs. Furthermore, QNYZD may play a direct role in suppressing the formation of GFAP-positive cells and enhancing neuronal differentiation by inhibiting JAK2/STAT3 activation. Overall, these results provide insights into the possible mechanism underlying QNYZD-mediated neurogenesis.

Traditional Chinese medicine's intervention in endothelial nitric oxide synthase activation and nitric oxide synthesis in cardiovascular system.

Cardiovascular disease (CVD) is one of the most dangerous diseases which has become a major cause of human death. Many researches evidenced that nitric oxide (NO)/endothelial nitric oxide synthase (eNOS) system plays a significant role in the occurrence and development of CVD. NO, an important signaling molecule, closely associated with the regulation of vasodilatation, blood rheology, blood clotting and other physiological and pathological processes. The synthesis of NO in the endothelial cells primarily depends on the eNOS activity, thus the exploration of the mechanisms and effects of the eNOS activation on NO production is of great significance. Recently, studies on the effects of traditional Chinese medicine (TCM) and its extracts on eNOS activation and NO synthesis have gradually attracted more and more attentions. In this paper, we reviewed the mechanisms of NO synthesis and eNOS activation in the vascular endothelial cells (VECs) and intervention of TCM, so as to provide reference and train of thought to the intensive study of NO/eNOS system and the research and development of new drug for the treatment of CVD.

Effective dose of the combination of salvianolic acids and tanshinones against inflammatory injury in human umbilical vein endothelial cells injured by thrombin.

OBJECTIVE: To investigate the pharmacological effective doses of Chinese Danshen components, (salvianolic acids and tanshinones) combinations on vascular endothelia cells against inflammatory injury. METHODS: Thrombin (50 U/mL) was incubated in human umbilical vein endothelia cells (HUVECs) with 50 and 100 µg/L (1:0, 0:1, 3:1, 2:1, 1:1, and 1:2) salvianolic acids and tanshinones or without the components of Danshen extract. Cell viability was confirmed in (4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium (MTT) assay and cell death was confirmed in lactate dehydrogenase (LDH) released into the cell culture supernatant. RESULTS: Six hours treatment of HUVECs with 50 or 100 µg/L salvianolic acids and tanshinones combinations at ratios 1:0, 0:1, 3:1, 2:1, 1:1, and 1:2 significantly (P<0.05 or P<0.01) improved cell proliferation in vitro compared with model group when assayed in MTT, whereas 100 µg/L groups displayed trend toward upshift in potency compared with 50 µg/L groups (2:1, 1:1, and 1:2), respectively, in addition to inhibition of cell death confirmed in reduced LDH released into the culture medium. CONCLUSIONS: These findings provided some useful information for safe and effective use of Danshen preparations in clinical practice. We made observations regarding the protective effect of Danshen components combinations in vascular endothelial against inflammatory injury caused by thrombin activation of endothelial cell.

Simultaneous determination of 2 aconitum alkaloids and 12 ginsenosides in Shenfu injection by ultraperformance liquid chromatography coupled with a photodiode array detector with few markers to determine multicomponents.

A method with few markers to determine multicomponents was established and validated to evaluate the quality of Shenfu injection by ultraperformance liquid chromatography coupled with a photodiode array detector. The separations were performed on an ACQUITY UPLC BEH C18 (2.1 × 50 mm2, 1.7 µm) column. Methanol and 0.1% formic acid aqueous solution were used as the mobile phase. The flow rate was 0.3 mL/min. 2 aconitum alkaloids and 12 ginsenosides could be perfectly separated within 15 minutes. Ginsenoside Rg1 and benzoylmesaconine, the easily available active components, were employed as the maker components to calculate the relative correction factors of other components in Shenfu injection, Panax ginseng and Aconitum carmichaeli. The external standard method was also established to validate the feasibility of the method with few markers to determine multicomponents. Parameter p and the principal component analysis method were employed to investigate the disparities among batches for the effective quality control of Shenfu injection. The results demonstrated that the ultraperformance liquid chromatography coupled with a photodiode array detector method with few markers to determine multicomponents could be used as a powerful tool for the quality evaluation of traditional Chinese medicines and their preparations.

A proteomic study of Shengmai injection's mechanism on preventing cardiac ischemia-reperfusion injury via energy metabolism modulation.

Energy metabolism modulation plays an important role in protecting the heart from ischemia-reperfusion (IR) injury. Shengmai injection (SMI) is a Chinese medicine, which is widely used in China to treat ischemic heart diseases with speculated functions of modulating energy metabolism. To uncover the molecular mechanisms underlying the cardioprotective activity of SMI via the modulation of energy metabolism, a proteomic analysis was performed on ischemia-reperfusion (IR) injured hearts of rats in this study. Two-dimensional gel electrophoresis (2-DE) was used to measure the protein expression profiles of heart tissues. Differentially expressed proteins among groups were identified using matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS/MS). Western blot analysis was used to validate differentially expressed proteins. Proteomic data revealed 14 major differentially expressed proteins that are related to the energy metabolism. It was found that the glucose oxidation, TCA cycle and ATP synthesis related proteins were consistently up-regulated in SMI treated rats, which is beneficial to aerobic respiration and ATP generation. In contrast, two proteins catalyzing fatty acid ß-oxidation were down-regulated, implying the inhibition of this pathway to avoid high oxygen consumption. It is thus concluded that one of the major mechanisms of SMI protection against IR injury was modulation of the myocardial energy metabolism to improve cardiac efficiency through multiple metabolic pathways including stimulating glucose metabolism and inhibiting fatty acid metabolism. It provided potential protein targets for the therapeutic strategy through modulation of the myocardial energy metabolism.

[Network analysis of ethanol precipitation process for Schisandrae chinensis fructus].

A set of central composite design experiments were designed by using four factors which were ethanol amount, ethanol concentration, refrigeration temperature and refrigeration time. The relation between these factors with the target variables of the retention rate of schizandrol A, the soluble solids content, the removal rate of fructose and the removal rate of glucose were analyzed with Bayesian networks, and ethanol amount and ethanol concentration were found as the critical process parameters. Then a network model was built with 2 inputs and 4 outputs using back propagation artificial neural networks which was optimized by genetic algorithms. The R2 and MSE from the training set were 0.983 8 and 0.001 1. The R2 and MSE from the test set were 0.975 9 and 0.001 8. The results showed that network analysis method could be used for modeling of Schisandrae Chinensis Fructus ethanol precipitation process and identify critical operating parameters.

[Reliability theory based on quality risk network analysis for Chinese medicine injection].

A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality.

[Data integration, data mining and visualization analysis of traditional Chinese medicine manufacturing process].

Huge amount of data becomes available from the pharmaceutical manufacturing process with wide application of in- dustrial automatic control technology in traditional Chinese medicine (TCM) industry. The industrial big data thus provides golden op- portunities to better understand the manufacturing process and improve the process performance. Therefore it is important to implement data integration and management systems in TCM plants to easily collect, integrate, store, analyze, communicate and visulize the data with high efficiency. It could break the data island and discover useful information and knowledge to improve the manufacturing process performance. The key supporting technologies for TCM manufacturing and industrial big data management were introduced in this paper, with a specific focus on data mining and visualization technologies. Using historic data collected from a manufacturing plant of Shengmai injection of SZYY group, we illustrated the usefulness and discussed future prospects of data mining and visualization technologies.

[Multi-objective optimization of extraction process for red ginseng based upon extraction efficiency and cost control].

It is the objective of this study to optimize the extraction process of red ginseng to minimize the unit cost of extracting effective ingredients. The relation between the target variables of total quantity of ginsenosides and first extraction time, first extraction solution amount, second extraction time, second extract solution amount were studied with Box-Behnken experimental design method. At the same we also considered the cost of extraction solution and energy usage. The objective function was set as unit cost of target (total quantity of ginsenosides or its purity) for the multi-objective optimization of extraction process. As a result, the optimal process parameters were found as first extraction time (108.7 min), first extraction solution amount folds (12), second extraction time (30 min), second extraction solution amount folds (8) to minimize the unit cost. It indicated that this approach could potentially be used to optimize industrial extraction process for manufacturing Chinese medicine.

[Dynamic predictive modeling of extraction process for red ginseng using near-infrared spectroscopy].

It is the objective of this study to develop dynamic predictive model for the extraction process of red Ginseng using NIR spectroscopy. NIR spectroscopy was collected online and PLSR models were developed for total quantity of ginsenosides. The performance of NIR prediction model achieved R, RMSEC, RMSEP of 0.996 09, 0.018 9, 0.016 8, respectively. A first order dynamic mass transfer model was combined with NIR prediction of the quality indicator to predict the trajectory of the extraction process based upon the initial 3 or 4 data points. The results showed good agreement with actual measurements indicating reasonable accuracy of the predictive model. It could potentially be used for advanced predictive control of the extraction process.

A metabonomic study of cardioprotection of ginsenosides, schizandrin, and ophiopogonin D against acute myocardial infarction in rats.

BACKGROUND: Metabonomics is a useful tool for studying mechanisms of drug treatment using systematic metabolite profiles. Ginsenosides Rg1 and Rb1, ophiopogonin D, and schizandrin are the main bioactive components of a traditional Chinese formula (Sheng-Mai San) widely used for the treatment of coronary heart disease. It remains unknown the effect of individual bioactive component and how the multi-components in combination affect the treating acute myocardial infarction (AMI). METHODS: Rats were divided into 7 groups and dosed consecutively for 7 days with mono and combined-therapy administrations. Serum samples were analyzed by proton nuclear magnetic resonance (1H NMR) spectroscopy. Partial least squares discriminate analysis (PLS-DA) was employed to distinguish the metabolic profile of rats in different groups and identify potential biomarkers. RESULTS: Score plots of PLS-DA exhibited that combined-therapy groups were significantly different from AMI group, whereas no differences were observed for mono-therapy groups. We found that AMI caused comprehensive metabolic changes involving stimulation of glycolysis, suppression of fatty acid oxidation, together with disturbed metabolism of arachidonic acid, linoleate, leukotriene, glycerophospholipid, phosphatidylinositol phosphate, and some amino acids. ß-hydroxybutyrate, cholines and glucose were regulated by mono-therapy of schizandrin and ginsenosides respectively. Besides these metabolites, combined-therapy ameliorated more of the AMI-induced metabolic changes including glycerol, and O-acetyl glycoprotein. A remarkable reduction of lactate suggested the therapeutic effect of combined-therapy through improving myocardial energy metabolism. CONCLUSIONS: This study provided novel metabonomic insights on the mechanism of synergistic cardioprotection of combined-therapy with ginsenosides, schizandrin, and ophiopogonin D, and demonstrated the potential of discovering new drugs by combining bioactive components from traditional Chinese formula.

[Strategies and key technologies for risk control and management in quality of Chinese medicine injections based on integrated pharmacology].

This paper focuses on the quality risk control and management of Chinese medicine (CM) injections. The most important technological requirements are analyzed, and a strategy for integrated pharmacology to study CM mechanism is proposed. A key technology system for quality risk control and management was further constructed. The strategy and technology system was finally applied to Shengmai injection for quality risk control and management.

Effects of Shenfu injection and its main components on the contraction of isolated rat thoracic aortic rings.

BACKGROUND AND PURPOSE: Shenfu injection (SFI), derived from the ancient traditional Chinese medicine (Red Radix Ginseng and Radix Aconitum Carmichaeli), has been widely used in the clinical for the treatment of cardiovascular diseases for more than 20 years. The present study aims to investigate the effects of SFI and its main components on the contraction of isolated rat thoracic aorta rings and the potential mechanisms of this action. METHODOLOGY/PRINCIPAL FINDINGS: The isolated rat thoracic aorta rings were initially treated with different concentrations of SFI, Hongshen injection (HSI, mainly containing ginsenoside) or Fupian injection (FPI, mainly containing aconite total alkaloids) separately. The control group was added an equal volume Krebs-Henseleit (K-H) solution. All three injections exhibited no obviously effects on the basal tension of the rings in the resting state. However, in the isolated thoracic aorta rings with intact endothelium, when the rings were first induced by 60 mM potassium chloride (KCl) or 1 µM norepinephrine (NE) to the maximal contraction and then treated with above injections, SFI and HSI significantly inhibited the vasoconstriction induced by KCl or NE. In addition, FPI has a tendency to inhibit KCl-induced vasoconstriction and facilitate NE-induced vasoconstriction, but no significant difference. None of them showed obvious effect on the endothelium denuded vessels. Moreover, this procedure was repeated after pre-incubation of nitric oxide synthase (NOS) inhibitor N(G)-nitro- L-arginine methyl ester (L-NAME), which suppressed the vasorelaxation effect of SFI and HSI. CONCLUSIONS AND IMPLICATIONS: These results demonstrate that both SFI and HSI caused an apparent thoracic aorta relaxation by endothelium-dependent manner, which was associated with eNOS system, while FPI had no detectable vasodilator effect. This suggested that the ginsenoside from red Radix Ginseng may be the main active ingredient of SFI's vasodilator effect.

Characterization of in vivo antioxidant constituents and dual-standard quality assessment of Danhong injection.

Antioxidants and oxidative stress play a critical role in cardiovascular diseases. Danhong injection (DHI) is a well prescribed cardiovascular medication in China, but its detailed chemical basis and mechanisms of action remain unknown. To prove the antioxidant activity of DHI, its free radical scavenging capacity (RSC) was assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) spectrophotometric assay. The 50% radical scavenging activity value was 1:129.2 mL/mL, against 0.95 mM DPPH. To further identify the antioxidant compounds, modified thin-layer chromatography combined with DPPH bioautography assay was used. Compared with vitamin C, 11 of 16 available compounds displayed strong antioxidant activity, which were also detected in rat serum after intravenous administration of DHI by ultra-performance liquid chromatography-tandem mass spectrometry, except for hydroxysafflor yellow A. Therefore, 10 antioxidants remaining in the blood as key markers, and six other compounds as general markers, were employed to perform the quality control of DHI by ultra-performance liquid chromatography-ultraviolet detection after systematic methodological validation. The analytical results indicate a high correlation (r = 0.9) between the total content of those antioxidants remaining in blood and RSC of DHI among 10 batches. Further, the antioxidant profiling and chemical marker quantification as dual-standard quality assessment was successfully applied to evaluate Danshen and safflower injections.