The zebrafish model has attracted much attention due to its strong reproductive ability, short research cycle, and ease of maintenance. It has always been an important vertebrate model system, often used to carry out human disease research. Its motor behavior features have the advantages of being simpler, more intuitive, and quantifiable. In recent years, it has received widespread attention in the study of traditional Chinese medicine(TCM)for the treatment of sleep disorders, neurodegenerative diseases, fatigue, epilepsy, and other diseases. This paper reviews the characteristics of zebrafish motor behavior and its applications in the pharmacodynamic verification and mechanism research of TCM extracts, active ingredients, and TCM compounds, as well as in active ingredient screening and safety evaluation. The paper also analyzes its advantages and disadvantages, with the aim of improving the breadth and depth of zebrafish and its motor behavior applications in the field of TCM research.
Zebrafish/physiology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Disease Models, Animal ; Drug Evaluation, Preclinical/methods* ; Animals ; Sleep Wake Disorders/physiopathology* ; Epilepsy/physiopathology* ; Neurodegenerative Diseases/physiopathology* ; Fatigue/physiopathology* ; Behavior, Animal/physiology* ; Motor Activity/physiology*

Kidney-Yang deficiency syndrome is a common geriatric disease that underlies chronic conditions such as diabetic nephropathy, chronic kidney disease, and osteoporosis. As age progresses, the kidney-Yang deficiency syndrome showcases increasingly pronounced manifestations, emerging as a key factor in the comorbidities experienced by elderly patients and affecting their quality of life and overall health status. Traditional Chinese medicine(TCM) has been extensively utilized in the treatment of kidney-Yang deficiency syndrome, with Epimedii Folium, Cinnamomi Cortex, and Lycii Fructus widely used in clinical settings. Despite the complexity of the molecular mechanisms involved in treating kidney-Yang deficiency syndrome, the potential therapeutic value of TCM remains compelling. Delving into the mechanisms of TCM treatment of kidney-Yang deficiency syndrome by regulating the neuro-endocrine-immune system can provide a scientific basis for targeted treatments of this syndrome and lay a foundation for the modernization of TCM. The pathophysiology of kidney-Yang deficiency syndrome involves multiple systems, including the interaction of the neuro-endocrine-immune system, the decline in renal function, the intensification of oxidative stress responses, and energy metabolism disorders. Understanding these mechanisms and their interrelationships can help untangle the etiology of kidney-Yang deficiency syndrome, aiding clinicians in making more precise diagnoses and treatments. Furthermore, the research on the specific applications of TCM in research on these pathological mechanisms can enhance the international recognition and status of TCM, enabling it to exert a greater global influence.
Humans ; Yang Deficiency/physiopathology* ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Kidney Diseases/physiopathology* ; Neurosecretory Systems/physiopathology* ; Animals ; Kidney/physiopathology* ; Endocrine System/physiopathology* ; Immune System/physiopathology*

OBJECTIVE: To investigate the therapeutic efficacy of cinnamaldehyde (CA) on systemic Candida albicans infection in mice and to provide supportive data for the development of novel antifungal drugs. METHODS: Ninety BALB/c mice were randomly divided into 3 groups according to a random number table: CA treatment group, fluconazole (positive control) group, and Tween saline (negative control) group, with 30 mice in each group. Initially, all groups of mice received consecutive intraperitoneal injections of cyclophosphamide at 200 mg/kg for 2 days, followed by intraperitoneal injection of 0.25 mL C. albicans fungal suspension (concentration of 1.0 × 10⁷ CFU/mL) on the 4th day, to establish an immunosuppressed systemic Candida albicans infection animal model. Subsequently, the mice were orally administered CA, fluconazole and Tween saline, at 240, 240 mg/kg and 0.25 mL/kg respectively for 14 days. After a 48-h discontinuation of treatment, the liver, small intestine, and kidney tissues of mice were collected for fungal direct microscopic examination, culture, and histopathological examination. Additionally, renal tissues from each group of mice were collected for (1,3)- β -D-glucan detection. The survival status of mice in all groups was monitored for 14 days of drug administration. RESULTS: The CA group exhibited a fungal clearance rate of C. albicans above 86.7% (26/30), significantly higher than the fluconazole group (60.0%, 18/30, P<0.01) and the Tween saline group (30.0%, 9/30, P<0.01). Furthermore, histopathological examination in the CA group revealed the disappearance of inflammatory cells and near-normal restoration of tissue structure. The (1,3)-β-D-glucan detection value in the CA group (860.55 ± 126.73 pg/mL) was significantly lower than that in the fluconazole group (1985.13 ± 203.56 pg/mL, P<0.01) and the Tween saline group (5910.20 ± 320.56 pg/mL, P<0.01). The mouse survival rate reached 90.0% (27/30), higher than the fluconazole group (60.0%, 18/30) and the Tween saline group (30.0%, 9/30), with a significant difference between the two groups (both P<0.01). CONCLUSIONS CA treatment exhibited significant therapeutic efficacy in mice with systemic C. albicans infection. Therefore, CA holds potential as a novel antifungal agent for targeted treatment of C. albicans infection.
Animals ; Acrolein/pharmacology* ; Candida albicans/physiology* ; Mice, Inbred BALB C ; Candidiasis/pathology* ; Antifungal Agents/therapeutic use* ; Mice ; Fluconazole/therapeutic use* ; Kidney/drug effects* ; Female

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Based on transcriptome sequencing technology, the mouse model of prediabetes treated with Huangjing Qianshi Decoction was sequenced to explore the possible mechanism of treating prediabetes. First of all, transcriptome sequencing was performed on the normal BKS-DB mouse group, the prediabetic model group, and the Huangjing Qianshi Decoction treatment group(treatment group) to obtain differentially expressed genes in the skeletal muscle samples of mice. The serum biochemical indexes were detected in each group to screen out the core genes of Huangjing Qianshi Decoction in prediabetes. Gene Ontology(GO) database and Kyoto Encyclopedia of Genes and Genomes(KEGG) database were used to conduct signaling pathway enrichment analysis of differentially expressed genes, and real-time quantitative polymerase chain reaction(RT-qPCR) was used to verify them. The results showed that the levels of fasting blood glucose(FBG), fasting insulin(FINS), insulin resistance index(HOMA-IR), total cholesterol(TC), triglycerides(TG), and low-density lipoprotein cholesterol(LDL-C) in the mouse model were significantly decreased after treatment with Huangjing Qianshi Decoction. In the results of differential gene screening, there were 1 666 differentially expressed genes in the model group as compared with the normal group, and there were 971 differentially expressed genes in the treatment group as compared with the model group. Among them, interleukin-6(IL-6) and NR3C2 genes, which were closely related to the regulation of insulin resis-tance function, were significantly up-regulated between the model group and the normal group, and vascular endothelial growth factor A(VEGFA) genes were significantly down-regulated between the model group and the normal group. However, the expression results of IL-6, NR3C2, and VEGFA genes were adverse between the treatment group and the model group. GO functional enrichment analysis found that the biological process annotation mainly focused on cell synthesis, cycle, and metabolism; cell component annotation mainly focused on organelles and internal components; and molecular function annotation mainly focused on binding molecular functions. KEGG pathway enrichment analysis found that it involved the protein tyrosine kinase 6(PTK6) pathway, CD28-dependent phosphoinositide 3-kinase/protein kinase B(PI3K/AKT) pathway, p53 pathway, etc. Therefore, Huangjing Qianshi Decoction can improve the state of prediabetes, and the mechanism may be related to cell cycle and apoptosis, PI3K/AKT pathway, p53 pathway, and other biological pathways regulated by IL-6, NR3C2, and VEGFA.
Animals ; Mice ; Proto-Oncogene Proteins c-akt ; Phosphatidylinositol 3-Kinases ; Prediabetic State ; Vascular Endothelial Growth Factor A ; Interleukin-6 ; Transcriptome ; Tumor Suppressor Protein p53 ; Insulin ; Cholesterol

Yiyi Fuzi Baijiang Powder(YFBP), originating from Synopsis of the Golden Chamber, is a classic prescription composed of Coicis Semen, Aconiti Lateralis Radix Praeparata, and Patriniae Herba for the treatment of abscesses and pus discharge. This article presented a systematic analysis of the clinical application of YFBP, including the indicated diseases, the number of cases, efficacy, dosage, administration methods, and compatibility with other drugs. The analysis reveals that YFBP has a wide range of clinical applications. It is commonly used, often with modifications or in combination with western medicine, for diseases in the fields of gastroente-rology, gynecology, urology, dermatology, and others. And most of the Traditional Chinese Medicine(TCM) evidence involved in these diseases are damp-heat evudence. The prescription shows rich variations in clinical administration methods, and most of which are the treatment of aqueous decoction of it. The therapeutic effect is also significant, and the total effective rate of clinical treatment is re-latively high. Additionally, this article summarized the pharmacological research on YFBP and found that it possessed various pharmacological effects, including anti-inflammatory, antioxidant, anticancer, and immune-modulating properties. Finally, correlation analysis was conducted on the main diseases, TCM types, prescription doses, pharmacological effects and action targets of YFBP, which to show the relationship between these five aspects in a visual form, reflecting the relationship between its clinical application and modern pharmacological effects. These findings provide a reference basis for further development and research on YFBP.
Powders ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Diterpenes ; Aconitum