Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

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.

Objective: To analyze the adverse treatment outcome status and spatio temporal characteristics of pulmonary tuberculosis cases among students in Qinghai Province, providing a reference basis for pulmonary tuberculosis prevention and control in schools. Methods: The data of student pulmonary tuberculosis cases during 2013-2023 in Qinghai Province were obtained through the "National Tuberculosis Management Information System", and the treatment outcome was retrospectively analyzed. The Joinpoint model was applied to analyze the adverse outcome rate trend. Global and local spatial autocorrelation analysis, and spatiotemporal scan cluster analysis were conducted on the adverse outcome rate of pulmonary tuberculosis among students in Qinghai Province. Results: During 2013-2023, 488 cases of adverse outcomes were reported among 6 155 students with pulmonary tuberculosis in Qinghai Province, with an adverse outcome rate of 7.93%. The reporting adverse outcome rate of pulmonary tuberculosis among students showed a downward trend from 2013 to 2023 (APC=-16.20, t =-3.89, P <0.05). The results of spatial autocorrelation showed that the adverse outcome rate of pulmonary tuberculosis was Moran s I >0 among students in Qinghai Province. Among them, there was a spatially positive correlation in the adverse outcome rate of pulmonary tuberculosis among students in 2020, 2021 and 2022(all Z >1.96, all P <0.05). The results of clustering and outlier analysis in local spatial autocorrelation showed that the areas with high high aggregation were mainly concentrated in Yushu Prefecture(Zhiduo County, Zaduo County, Nangqian County, Yushu City), Huangnan Prefecture (Zeku County, Henan County) and Hainan Prefecture (Tongde County). The low low concentration areas were distributed in Haidong City, Xining City, Haibei Prefecture (Gangcha County, Qilian County), Haixi Prefecture (Tianjun County, Ulan County), Hainan Prefecture (Gonghe County, Guide County) and Huangnan Prefecture (Tongren City, Jianzha County). The spatio temporal scanning showed that a total of two possible aggregation areas had been detected. Among them, the first level aggregation area composed of 10 counties and districts in Yushu Prefecture and Guoluo Prefecture of Qinghai Province, and the cluster radius was 658.09 km, the RR was 10.58 , and the LLR was 305.91; the second level aggregation area was composed of 16 counties and districts in Hainan Prefecture, Haixi Prefecture, Huangnan Prefecture and Guoluo Prefecture, and the cluster radius was 407.02 km, the RR was 9.83, and the LLR was 152.48 (both P <0.05). Conclusions The reporting rates of adverse treatment outcome of pulmonary tuberculosis cases among students in Qinghai Province remain relatively high and unevenly distribute throughout the province. Supervision should be strengthened to improve cases compliance,and to reduce student pulmonary tuberculosis adverse treatment outcomes incidence.

Objective: To explore the distribution of traditional Chinese medicine (TCM) syndromes in patients with interstitial lung disease (ILD) and its influencing factors. Methods: This cross-sectional study included 385 patients with ILD admitted to the First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine) from January 2018 to June 2022. Data on sex, age, body mass index, smoking history, respiratory rate, hospitalization time, treatment cost, whether velcro rales can be heard, comorbidities with rheumatic immune diseases, TCM four examination information, and clinical examination results, including CT imaging, D-dimer level, and lung function-related indicators, were collected. The distribution pattern of TCM syndromes in patients with ILD and the association between TCM syndromes and clinical indicators were analyzed using the cluster analysis and binary Logistic regression analysis. Results: Among the 385 patients with ILD, sticky phlegm (59.74%) and shortness of breath (56.10%) were common symptoms, while greasy tongue coating (55.32%), red tongue (52.73%), and slippery and rapid pulse (25.71%) were common tongue and pulse manifestations. The patients were divided into five syndromes using cluster analysis: syndrome of phlegm-heat stagnation in the lung (36.62%), syndrome of turbid phlegm obstructing lung (29.35%), syndrome of deficiency of both qi and yin (12.99%), syndrome of qi deficiency of lung and kidney (11.95%), and syndrome of phlegm and blood stasis obstructing lung (9.09%). The D-dimer level was lower in patients with syndrome of phlegm-heat stagnation in the lung, syndrome of turbid phlegm obstructing lung, syndrome of deficiency of both qi and yin, and syndrome of qi deficiency of lung and kidney than in those with syndrome of phlegm and blood stasis obstructing lung (P<0.05). The percentage of predicted forced vital capacity (FVC%pred) of patients with syndrome of phlegm-heat stagnation in the lung, syndrome of turbid phlegm obstructing lung, syndrome of deficiency of both qi and yin, and syndrome of phlegm and blood stasis obstructing lung was higher than in those with syndrome of qi deficiency of lung and kidney (P<0.05). Among patients aged 60 and above, those with syndrome of phlegm-heat stagnation in the lung, syndrome of phlegm and blood stasis obstructing lung, and syndrome of deficiency of both qi and yin containing dual pathogenic syndrome elements were more likely to experience moderate to severe pulmonary diffusion impairment than those with syndrome of turbid phlegm obstructing lung and syndrome of qi deficiency of lung and kidney containing single pathogenic syndrome elements (P<0.05). The Logistic regression showed that the FVC%pred was an influential factor for syndrome of qi deficiency of lung and kidney, and the area under the receiver operating characteristic (ROC) curve (AUC) between FVC%pred and the formation of syndrome of qi deficiency of lung and kidney was 0.676 (95%CI: 0.598-0.755), P=0.002. The sensitivity was 0.431, the specificity was 0.966, and the best threshold on the ROC curve of 0.397 was 79.1%. The D-dimer level was an influential factor in the formation of syndrome of phlegm and blood stasis obstructing lung. The AUC between D-dimer level and the formation of syndrome of phlegm and blood stasis obstructing lung was 0.729 (95%CI: 0.655-0.802), P<0.001. The sensitivity was 0.914, the specificity was 0.523, and the best threshold on the ROC curve of 0.437 was 0.675 mg/L. Conclusion syndrome of phlegm-heat stagnation in the lung and syndrome of turbid phlegm obstructing lung are common among patients with ILD. Complex pathological syndromes are more likely to exacerbate pulmonary diffusion dysfunction. The FVC%pred can assist in differentiating syndrome of qi deficiency of lung and kidney, whereas the D-dimer level can assist in differentiating syndrome of phlegm and blood stasis obstructing lung.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

Parkinson's disease(PD) is a neurodegenerative disorder characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra and the accumulation of Lewy bodies. While conventional drugs like levodopa can improve early symptoms, their efficacy diminishes over time, and they may cause severe side effects. Traditional Chinese medicine(TCM), with its multi-target therapeutic approach, has shown unique advantages in PD treatment, particularly in slowing disease progression and improving clinical symptoms. The nuclear factor erythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1) signaling pathway plays a critical role in cellular antioxidation, anti-inflammation, and cellular repair mechanisms, which are crucial for neuroprotection against PD. Studies indicate that TCM regulates the Nrf2/HO-1 pathway to enhance neuronal antioxidative capacity, inhibit neuroinflammation, promote dopaminergic neuron repair and survival, and slow pathological progression. This review explores the neuroprotective role of the Nrf2/HO-1 pathway in PD patients, including alleviating oxidative stress, suppressing neuroinflammation, promoting neuronal repair, and regulating iron metabolism and autophagy. It also discusses the mechanisms by which TCM active ingredients(flavonoids, alkaloids, terpenes, saponins, polyphenols, etc.), single herbs(Cistanche deserticola, Uraria crinite, and Melissa officinalis, etc.), and formulas(Bushen Jianpi Decoction, Didang Decoction, and Gancao Yangyin Decoction, etc.) modulate the Nrf2/HO-1 pathway in PD treatment, providing a theoretical basis for the clinical application and new drug development of TCM in PD prevention and treatment.
Humans ; Parkinson Disease/genetics* ; NF-E2-Related Factor 2/genetics* ; Signal Transduction/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Heme Oxygenase-1/genetics* ; Medicine, Chinese Traditional

This study compared the differences in intestinal absorption characteristics of eleven active components in Rubus multibracteatus(RM) extract(protocatechuic acid, tiliroside, scutellarin, luteoloside, astragalin, epicatechin, catechin, xanthotoxin, p-coumaric acid, caffeic acid, and apigenin-7-O-glucuronide) between normal rats and inflammatory pain model rats using the in-vitro everted intestinal sac model. The RM extract was administered at absorption concentrations of 25.0, 50.0, and 100.0 mg·mL~(-1). The contents of the eleven components in intestinal absorption solution samples were quantified by ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS), and their cumulative absorption(Q) and absorption rate constant(K_a) were calculated to evaluate the absorption characteristics of these components in normal rats and inflammatory pain model rats. The results show that except for catechin, epicatechin, and caffeic acid, the cumulative absorption-time curves of the other eight components(protocatechuic acid, tiliroside, scutellarin, luteoloside, astragalin, xanthotoxin, p-coumaric acid, and apigenin-7-O-glucuronide) exhibit an upward trend without saturation, with correlation coefficients(R~2) all > 0.9, indicating linear absorption. However, the overall absorption of all components is not dose-dependent with increasing concentration, suggesting that their absorption mechanisms are not solely passive diffusion. In both normal and model rats, the jejunum shows the highest absorption for all components except xanthotoxin. The overall absorption of seven components(excluding protocatechuic acid, caffeic acid, apigenin-7-O-glucuronide, and luteoloside) in normal rats is better than that in model rats across all intestinal segments. These findings indicate that the pathological state of inflammatory pain alters the intestinal absorption of RM extract, and its mechanism needs further investigation.
Animals ; Rats ; Intestinal Absorption/drug effects* ; Male ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/metabolism* ; Disease Models, Animal ; Pain/metabolism* ; Intestines/drug effects* ; Intestinal Mucosa/metabolism*