ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to investigate the role of NDC80 kinetochore complex component （NUF2） and magnesium homeostasis in ovarian cancer cell apoptosis， as well as the regulatory mechanism of gypenoside L （Gyp-L） on NUF2 and magnesium homeostasis. MethodsOvarian cancer OVCAR3 cells were divided into a blank control group， a low-concentration Gyp-L group （50 µmol·L^-1）， a high-concentration Gyp-L group （100 µmol·L^-1）， and a cisplatin （15 µmol·L^-1） group. The migration， proliferation， and apoptosis capabilities of OVCAR3 cells were evaluated through cell scratch assays， clonal experiments， and terminal-deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling assay （TUNEL） staining. Differentially expressed genes of ovarian cancer were screened by using the Gene Expression Omnibus （GEO） database. The interaction relationships of differentially expressed genes and proteins were analyzed via the Search Tool for Recurring Instances of Neighbouring Genes （STRING） database. The prognostic survival analysis was performed by using the Tumor Immune Estimation Resource （TIMER） database， and the differential expression levels of genes were validated with the Gene Expression Profiling Interactive Analysis （GEPIA） database. The mRNA expression levels of NUF2， magnesium homeostasis-related indicators， such as magnesium transporter 1 （MAGT1）， non-imprinted in Prader-Willi/Angelman syndrome 1 （NIPA1）， NIPA-like domain containing 1 （NIPAL1）， as well as apoptosis-related indicators B cell lymphoma-2 （Bcl-2） and Bcl-2-associated X protein （Bax） in OVCAR3 cells， were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. The protein expression levels of NUF2， MAGT1， NIPA1， NIPAL1， Bcl-2， and Bax in OVCAR3 cells were quantitatively analyzed by ProteinSimple WES. A model of overexpression of NUF2 was constructed， and Gyp-L intervention was performed. The molecular mechanism by which Gyp-L induces ovarian cancer cell apoptosis by regulating NUF2 and influencing magnesium homeostasis was quantitatively analyzed and detected through cell cloning， TUNEL staining， Real-time PCR， and ProteinSimple WES. Finally， the Mg²⁺ content and protein synthesis efficiency were detected by immunofluorescence. ResultsGyp-L significantly inhibited the migration and proliferation capabilities of OVCAR3 cells and promoted their apoptosis （P<0.05）. Overexpression of NUF2 markedly increased the expression levels of MAGT1， NIPA1， NIPAL1， and Bcl-2， while reducing the expression level of Bax （P<0.05）. It also significantly elevated intracellular Mg²⁺ content and protein synthesis efficiency and simultaneously inhibited apoptosis （P<0.05）. Gyp-L could reverse the magnesium homeostasis imbalance and apoptosis inhibition caused by the overexpression of NUF2， downregulating the expression levels of NUF2， MAGT1， NIPA1， NIPAL1， and Bcl-2 （P<0.05）， while upregulating the expression level of Bax （P<0.05）. ConclusionGyp-L can inhibit the occurrence of ovarian cancer， and its mechanism may involve inhibiting the expression of NUF2 to maintain magnesium homeostasis and inducing apoptosis of ovarian cancer cells.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Kounis syndrome is an acute coronary syndrome triggered by an allergic reaction, which is clinically rare and frequently subject to misdiagnosis or missed diagnosis. This article presents a case report of a 70-year-old male patient who developed a rash, pruritus, and chest pain following colon polyp resection. Coronary angiography revealed occlusion of the left anterior descending artery, and blood flow was restored after stent implantation. However, the patient experienced recurrent symptoms accompanied by loss of consciousness. Drug skin tests confirmed positive reactions to chlorhexidine and fondaparinux sodium, leading to a diagnosis of type Ⅱ Kounis syndrome. By avoiding allergenic drugs and combining antihistamines with symptomatic treatment to correct myocardial ischemia, the patient′s clinical symptoms significantly improved, and he eventually recovered and was discharged from the hospital. This case underscores the importance of maintaining vigilance for this syndrome in patients with allergies accompanied by chest pain and promptly identifying and avoiding allergens.

Objective: To establish an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method based on solid-phase extraction column purification for simultaneous determination of cyromazine and melamine in poultry eggs and meat. Methods: Eggs, quail eggs, and chicken were collected from markets. After homogenization, the sample was extracted with 0.5% formic acid in acetonitrile, subjected to solid-phase extraction using an MCX cartridge, and eluted with 5% ammonia in methanol. The eluate was collected, evaporated to near dryness under nitrogen, and reconstituted in a 10% aqueous methanol solution. Separated using TSK gel Amide-80 column (2.0 mm×150 mm, 5 μm), cyromazine and melamine were simultaneously detected in positive ion multiple reaction monitoring mode via tandem mass spectrometry, with quantification achieved by isotope dilution internal standard methods. Efficiency was enhanced and matrix interference minimized by optimizing conditions such as sample extraction, solid-phase extraction cartridge selection, and instrumental parameters. Calibration curves were constructed, and detection limits, quantification limits, spiked recoveries, and relative standard deviations for (RSD) of cyromazine and melamine were calculated. Results: After method optimization, matrix effects for cyromazine and melamine ranged from 0.97 to 1.04, indicating no significant matrix suppression or enhancement. Both cyromazine and melamine exhibited excellent linearity within the concentration range of 1.0-200.0 ng/mL, with correlation coefficients ≥0.999 5. The limits of detection were 0.3 μg/kg for cyromazine and 0.5 μg/kg for melamine, the quantification limits were 1.0 and 1.5 μg/kg, respectively. At spiked levels of 1.0, 20.0, and 150.0 μg/kg, the average recoveries ranged from 78.6% to 103.1%, with RSD between 3.5% and 6.3%. Among 95 samples tested, cyromazine was detected in 6 samples and melamine in 5 samples; neither cyromazine nor melamine was detected in chicken samples. Conclusion The UPLC-MS/MS method established in this study enables simultaneous detection and accurate quantification of cyromazine and melamine in poultry eggs and meat.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

To explore the variation laws of volatile oil during the extraction process of Artemisiae Argyi Folium and its impact on the quality of the medicinal solution, as well as to achieve precise control of the extraction process, this study employed headspace solid phase microextraction gas chromatography-mass spectrometry(HS-SPME-GC-MS) in combination with multiple light scattering techniques to conduct a comprehensive analysis, identification, and characterization of the changes in volatile components and the physical properties of the medicinal solution during the extraction process. A total of 82 volatile compounds were identified using the HS-SPME-GC-MS technique, including 21 alcohols, 15 alkenes, 14 ketones, 9 acids, 6 aldehydes, 5 phenols, 3 esters, and 9 other types of compounds. At different extraction time points(15, 30, 45, and 60 min), 71, 72, 64, and 44 compounds were identified in the medicinal solution, respectively. It was observed that the content of volatile components gradually decreased with the extension of extraction time. Through multivariate statistical analysis, four compounds with significant differences during different extraction time intervals were identified, namely 1,8-cineole, terpinen-4-ol, 3-octanone, and camphor. RESULTS:: from multiple light scattering techniques indicated that at 15 minutes of extraction, the transmittance of the medicinal solution was the lowest(25%), the particle size was the largest(0.325-0.350 nm), and the stability index(turbiscan stability index, TSI) was the highest(0-2.5). With the extension of extraction time, the light transmittance of the medicinal solution improved, stability was enhanced, and the particle size decreased. These laws of physicochemical property changes provide important basis for the control of Artemisiae Argyi Folium extraction process. In addition, the changes in the bioactivity of Artemisiae Argyi Folium extracts during the extraction process were investigated through mouse writhing tests and antimicrobial assays. The results indicated that the analgesic and antimicrobial effects of the medicinal solution were strongest at the 15-minute extracting point. In summary, the findings of this study demonstrate that the content of volatile oil in Artemisiae Argyi Folium extracts gradually decreases with the extension of extraction time, and the variation in volatile oil content directly influences the physicochemical properties and pharmacological efficacy of the medicinal solution. This discovery provides important scientific reference for the optimization of Artemisiae Argyi Folium extraction processes and the development and application of process analytical technologies.
Oils, Volatile/pharmacology* ; Artemisia/chemistry* ; Gas Chromatography-Mass Spectrometry ; Drugs, Chinese Herbal/pharmacology* ; Chlorogenic Acid/pharmacology* ; Solid Phase Microextraction ; Quality Control

OBJECTIVE: Baicalein has been reported to have wide therapeutic effects that act through its anti-inflammatory activity. This study examines the effect and mechanism of baicalein on sepsis-induced cardiomyopathy (SIC). METHODS: A thorough screening of a small library of natural products, comprising 100 diverse compounds, was conducted to identify the most effective drug against lipopolysaccharide (LPS)-treated H9C2 cardiomyocytes. The core target proteins and their associated signaling pathways involved in baicalein's efficacy against LPS-induced myocardial injury were predicted by network pharmacology. RESULTS: Baicalein was identified as the most potent protective agent in LPS-exposed H9C2 cardiomyocytes. It exhibited a dose-dependent inhibitory effect on cell injury and inflammation. In the LPS-induced septic mouse model, baicalein demonstrated a significant capacity to mitigate LPS-triggered myocardial deficits, inflammatory responses, and ferroptosis. Network pharmacological analysis and experimental confirmation suggested that hypoxia-inducible factor 1 subunit α (HIF1-α) is likely to be the crucial factor in mediating the impact of baicalein against LPS-induced myocardial ferroptosis and injury. By combining microRNA (miRNA) screening in LPS-treated myocardium with miRNA prediction targeting HIF1-α, we found that miR-299b-5p may serve as a regulator of HIF1-α. The reduction in miR-299b-5p levels in LPS-treated myocardium, compared to the control group, was reversed by baicalein treatment. The reverse transcription quantitative polymerase chain reaction, Western blotting, and dual-luciferase reporter gene analyses together identified HIF1-α as the target of miR-299b-5p in cardiomyocytes. CONCLUSION Baicalein mitigates SIC at the miRNA level, suggesting the therapeutic potential of it in treating SIC through the regulation of miR-299b-5p/HIF1-α/ferroptosis pathway. Please cite this article as: Zhou WY, Du JK, Liu HH, Deng L, Ma K, Xiao J, Zhang S, Wang CN. Baicalein attenuates lipopolysaccharide-induced myocardial injury by inhibiting ferroptosis via miR-299b-5p/HIF1-α pathway. J Integr Med. 2025; 23(5):560-575.
Flavanones/pharmacology* ; Animals ; MicroRNAs/genetics* ; Lipopolysaccharides ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Ferroptosis/drug effects* ; Mice ; Myocytes, Cardiac/metabolism* ; Signal Transduction/drug effects* ; Rats ; Male ; Mice, Inbred C57BL ; Cardiomyopathies/etiology* ; Cell Line ; Sepsis/complications*