OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

Objective: To evaluate repeated testing on blood screening platforms in confirmation of non-discriminatory reactive (NDR) samples in nucleic acid testing (NAT). Methods: A total of 102 HBsAg-negative/NAT NDR samples were collected from voluntary blood donors at Dalian Blood Center between January 2021 and December 2023. Repeated testing was performed using two NAT platforms (Cobas s201 and Panther). For the first round of repeated testing, all samples were tested 12 times on each system; for the second round, the samples which were non-reactive or only reactive once in the first round were tested an additional 8 times. Anti-HBc and anti-HBs was detected using electrochemiluminescence assay (ECA). Meanwhile, blood donors were followed up. Results: The proportion of anti-HBc+ in 102 NDR samples was 88.2%. Forty-one samples (40.2%, 41/102) and 7 samples were confirmed HBV DNA+ in first-round and second-round repeated testing, respectively. The cumulative confirmation rate of HBV DNA+ was 47.1% (48/102) after repeated testing. Extra five blood donors detected HBV DNA+ in follow-up were identified as anti-HBc+ occult hepatitis B virus infection (OBI), while no window period infection was observed. Ultimately, there were 53 HBV infected donors confirmed, 46 HBV infection-unconfirmed, and 3 HBV uninfected. No significant difference was observed between the confirmation rate of the first-round testing and the cumulative confirmation rate after the second-round testing (P>0.05). The proportion of anti-HBc+ donors was quite high in both HBV infection-confirmed (98.1%) and unconfirmed group (82.6%), and donors with seronegative and anti-HBs-only occupied a high proportion in the latter (P<0.05). Conclusion: Numerous repeated testing of NDR samples using NAT platforms cannot achieve complete confirmation of HBV infection. Supplementary anti-HBc testing can minimize potential OBI risk among NDR donors, and is low-cost and efficient.

Objective: To investigate whether Tuina alleviates fibrotic symptoms in myofascial trigger points (MTrPs) by regulating transforming growth factor (TGF)-β1/Smad3 signaling pathway, thereby deactivating these points. Methods: This study comprised two experimental phases. In phase 1, 27 specific pathogen-free (SPF) grade female Sprague-Dawley (SD) rats were randomized into three groups: control 1, model 1, and Tuina 1 groups. Model 1 and Tuina 1 groups underwent an 8-week MTrPs modeling protocol involving blunt impact and eccentric exercise. After successful modeling, rats in Tuina 1 group received manual pressing on nodules or cord-like taut bands on the medial aspect of the left hindlimb. Pain sensitivity and tissue stiffness were evaluated via pressure pain threshold (PPT) and soft tissue tension (STT). Muscle histopathology and fibrosis were observed using hematoxylin and eosin (HE) and Masson staining. Inflammatory factors in muscle were measured by enzyme-linked immunosorbent assay (ELISA), while immunofluorescence (IF) and Western blot (WB) were used to detect the expression levels of α-smooth muscle actin (α-SMA), collagen Ⅲ, and TGF-β1. In phase 2, 45 SPF female SD rats were randomized into five groups: control 2, model 2, Tuina 2, TGF-β1 inhibitor (TI), and Tuina + TGF-β1 agonist (Tuina + TA) groups. All groups except control 2 underwent standardized MTrPs modeling. Rats in Tuina 2 group received consistent pressing manipulation. TI group received intraperitoneal injections of oxymatrine, while Tuina + TA group received intraperitoneal injections of SRI-011381 hydrochloride followed by the same pressing protocol as Tuina 2 group. WB was used to detect the expression of collagen I, collagen III, TGF-β1, and phosphorylated-Smad3 (p-Smad3)/Smad3. Results: In phase 1, Tuina significantly improved PPT and STT in MTrPs of rats (P < 0.01), reversed pathological damages including disorganized muscle fiber arrangement, abnormal myocyte morphology, and exacerbated fibrosis. In addition, in MTrPs of rats in model 1 group, expression levels of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and fibrosis markers (α-SMA, collagen I, and collagen III) were upregulated, and all exhibited a significant downward trend after Tuina intervention (P < 0.05 or P < 0.01). This indicates that the therapeutic effects of Tuina are directly associated with reduced local inflammation and fibrosis in MTrPs. In phase 2, compared with model 2 group, rats in TI and Tuina 2 groups had decreased expression levels of TGF-β1 and p-Smad3/Smad3 in MTrPs, alongside reduced levels of inflammatory factors (IL-1β, IL-6, NF-κB, and TNF-α) and fibrosis markers (α-SMA, collagen I, and collagen III) (P < 0.05 or P < 0.01). When co-administered with TGF-β1 agonist, the therapeutic effects of Tuina were significantly attenuated, with rebounded TGF-β1 expression and p-Smad3/Smad3 in local MTrPs, and fibrosis and inflammatory responses were re-exacerbated (P < 0.05 or P < 0.01). Conclusion Tuina can effectively reduce inflammatory responses and fibrosis in MTrPs tissue, and its mechanism is closely related to the inhibition of the TGF-β1/Smad3 signaling pathway, which plays a critical role in Tuina-mediated regulation of MTrPs fibrosis.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Objective: To address systemic challenges in the blood system, such as supply-demand imbalance, inefficient allocation, and inappropriate clinical use, while bridging gaps in current theories regarding the integration of social mobilization, institutional practice, and policy coordination. It sought to construct a system dynamics model spanning from macro to micro levels to analyze the blood management system holistically. Methods: Key variables were identified by a systematic literature search in both Chinese and English databases. An improved Delphi method was then employed to conduct expert consultations across different fields, leading to the selection and determination of core variable sets for each sub-model. Furthermore, by defining their logical relationships, a system dynamics model was constructed to systematically analyze the operation mechanism of the blood management system. Results: Four core sub-models were developed: 1) A macro "Dynamic Balance" model quantifying regional supply-demand equilibrium and inventory control; 2) a mobilization "Three-Layer Funnel" model analyzing how socio-cultural factors, service channels, and policy incentives influence donation behavior; 3) an institutional "Dual-Cycle Regulation" model revealing hospital blood usage is driven by both disease burden (demand cycle) and management practices (regulation cycle); and 4) an individual "Three-Layer Filter" model standardizing clinical transfusion decisions based on necessity, risk-benefit, and context. These were integrated into a "Multi-Layer Linkage and Feedback" model, elucidating bidirectional interactions among five levels: policy environment, regional supply, blood station mobilization, hospital application, and clinical decision-making. Conclusion: This study constructed a system dynamics model for blood management. By defining key variables and their logical relationships, it systematically analyzes the system′s operational mechanism. The integrated framework connects multiple levels—regional supply, voluntary donation, hospital blood use, and clinical decision-making—revealing their intrinsic linkages. Future efforts should employ systems thinking to synergistically enhance supply-side mobilization, demand-side management, systemic regulation, and decision standardization to build a safe, efficient, and sustainable blood security system.

OBJECTIVE To establish a quality control method for Jinbei oral liquid based on multi-wavelength switching high performance liquid chromatography （HPLC） fingerprint， chemical pattern recognition and multi-index content determination. METHODS A total of 15 batches of Jinbei oral liquid were used as test samples. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （ Version 2012 ） was adopted to establish multi-wavelength switching HPLC fingerprints， followed by chromatographic peak identification and similarity evaluation. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were applied to conduct chemical pattern recognition on the 15 batches of samples. The multi-wavelength switching HPLC method was used to simultaneously determine the contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianoli c acid B and wogonoside in samples. RESULTS A total of 25 common peaks were calibrated in the fingerprints of 15 batches of Jinbei oral liquid， among which 7 common peaks were unambiguously identified. The similarity of all samples was higher than 0.960. Chemical pattern recognition results showed that samples S1-S8 were clustered into group 1， and samples S9-S15 were clustered into group 2. Baicalin， wogonoside， neochlorogenic acid， chlorogenic acid and salvianolic acid B were identified as the differential quality markers. The average contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianolic acid B and wogonoside in 15 batches of Jinbei oral liquid were 0.213 7， 0.085 3， 0.104 9， 0.287 3， 0.420 1， 0.062 1， 0.176 0 mg/mL， respectively. CONCLUSIONS The established quality control method for Jinbei oral liquid combining multi-wavelength switching HPLC fingerprint， chemical pattern recognition and multi-index content determination is stable and reliable， which can provide a reference for the formulation of quality standards of this preparation.

OBJECTIVE To establish a quality control method for Jinbei oral liquid based on multi-wavelength switching high performance liquid chromatography （HPLC） fingerprint， chemical pattern recognition and multi-index content determination. METHODS A total of 15 batches of Jinbei oral liquid were used as test samples. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （ Version 2012 ） was adopted to establish multi-wavelength switching HPLC fingerprints， followed by chromatographic peak identification and similarity evaluation. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were applied to conduct chemical pattern recognition on the 15 batches of samples. The multi-wavelength switching HPLC method was used to simultaneously determine the contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianoli c acid B and wogonoside in samples. RESULTS A total of 25 common peaks were calibrated in the fingerprints of 15 batches of Jinbei oral liquid， among which 7 common peaks were unambiguously identified. The similarity of all samples was higher than 0.960. Chemical pattern recognition results showed that samples S1-S8 were clustered into group 1， and samples S9-S15 were clustered into group 2. Baicalin， wogonoside， neochlorogenic acid， chlorogenic acid and salvianolic acid B were identified as the differential quality markers. The average contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianolic acid B and wogonoside in 15 batches of Jinbei oral liquid were 0.213 7， 0.085 3， 0.104 9， 0.287 3， 0.420 1， 0.062 1， 0.176 0 mg/mL， respectively. CONCLUSIONS The established quality control method for Jinbei oral liquid combining multi-wavelength switching HPLC fingerprint， chemical pattern recognition and multi-index content determination is stable and reliable， which can provide a reference for the formulation of quality standards of this preparation.