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 Chinese and English publications pertaining to Oncomelania hupensis control from 2005 to 2024, so as to decipher the research status and hotspots of O. hupensis control. Methods Chinese and English publications pertaining to O. hupensis control from 2005 to 2024 were retrieved in the Web of Science Core Collection Database and China National Knowledge Infrastructure. The annual number of publications was analyzed from 2005 to 2024, and the author and institution cooperation networks were mapped using the software CiteSpace 6.3.1. Keywords were extracted from publications to map the co-occurrence, burst and timeline of keywords to identify the research hotspots of O. hupensis control. Results A total of 158 English publications and 771 Chinese publications were included for bibliometric analyses. The overall output of English publications was relatively small from 2005 to 2024, the annual average publication was 7.90 publications. Parasites & Vectors was the most productive journal by the number of publications (21 publications). The three most productive authors included Li Shizhu (24 publications), Zhou Xiaonong (13 publications), and Yang Kun (12 publications), and the three most productive institutions included Chinese Center for Disease Control and Prevention (49 publications), the WHO (27 publications), and Fudan University (25 publications). The annual average number of Chinese publications was high from 2005 to 2015 (57.73 publications), and reduced to 15.11 publications during the period from 2016 to 2024, with Chinese Journal of Schistosomiasis Control as the most productive journal (241 publications). The three most productive authors included Wang Wanxian (18 publications), Sun Qixiang (16 publications), and Dai Jianrong (16 publications), and the three most productive institutions included Jiangsu Institute of Parasitic Diseases (55 publications), Chinese Center for Disease Control and Prevention (47 publications), and Hubei Uni-versity (38 publications). Among the 158 English publications, molluscicidal effect, climate change, geographic information, biological control, machine learning were current research hotspots, and the Yangtze River and elimination were emerging research hotspots. Among the 771 Chinese publications, molluscicidal effect, niclosamide, comprehensive management, molluscicide, effectiveness evaluation, marshland, and endophyte were current research hotspots, and the future research hotspots shifted to molluscicidal effect and pyriclobenzuron. Conclusions Limited attention is paid to the research on O. hupensis control across the world. The Yangtze River, elimination, molluscicidal effect, and pyriclobenzuron may be future research hotspots. High attention is recommended to be paid to the research on O. hupensis control, and development of diverse approaches for O. hupensis control is of urgent needs. We should continue to attach importance to the control research of O. hupensis and strengthen the exploration of diverse snail extermination and control methods.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chronic liver disease worldwide, affecting approximately 32%-38% of the adult population and posing a growing public health burden. MASLD represents a continuous disease spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), progressive hepatic fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC). The pathological core of MASLD lies in disruption of hepatic lipid metabolic homeostasis, characterized by an imbalance among de novo lipogenesis, fatty acid β-oxidation, and very-low-density lipoprotein (VLDL)-mediated lipid export. This metabolic disequilibrium subsequently drives inflammatory injury and fibrotic progression. Among the multiple regulatory pathways involved, thyroid hormone (TH) signaling has emerged as a central regulator of hepatic metabolic homeostasis. The liver is a major peripheral target organ of TH action, where TH predominantly exerts its metabolic effects through thyroid hormone receptor β (TRβ). Large-scale epidemiological studies and meta-analyses have demonstrated that hypothyroidism is significantly associated with increased MASLD prevalence, more severe histological injury, and advanced hepatic fibrosis, suggesting that dysregulation of TH signaling may participate throughout the entire MASLD disease spectrum. At the molecular level, TH regulates hepatic lipid metabolism by coordinating suppression of lipogenesis, enhancement of mitochondrial fatty acid oxidation, and promotion of VLDL assembly and secretion through integrated genomic actions of the T3-TRβ axis and non-genomic signaling pathways. Across different stages of MASLD, TH signaling exerts stage-dependent protective effects. In the steatosis stage, TH improves metabolic flexibility by modulating insulin sensitivity, glucose metabolism, and lipid droplet clearance, thereby alleviating early lipotoxic stress. During progression to MASH, TH attenuates inflammatory amplification by improving mitochondrial homeostasis, suppressing activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and modulating the gut-liver axis microenvironment. In advanced stages, TH signaling influences hepatic stellate cell activation and extracellular matrix deposition, partly through interaction with the transforming growth factor-β (TGF-β)/SMAD pathway, while alterations in intrahepatic TH availability, mediated by dynamic changes in iodothyronine deiodinase 1 (DIO1), contribute to fibrosis progression and hepatocellular dedifferentiation. In hepatocellular carcinoma, coordinated downregulation of TRβ and DIO1 establishes a tumor-associated hypothyroid state that promotes metabolic reprogramming and tumor progression. The clinical relevance of TH signaling in MASLD has been underscored by the recent approval of Resmetirom, a liver-targeted TRβ‑selective agonist, for the treatment of non-cirrhotic MASH with moderate-to-severe fibrosis (F2-F3). This approval represents a landmark transition from mechanistic understanding to metabolism-centered precision therapy in MASLD. Clinical trials have demonstrated that Resmetirom not only improves key histological endpoints, including MASH resolution and fibrosis regression, but also favorably modulates atherogenic lipid profiles, highlighting the therapeutic potential of selectively targeting hepatic TH pathways. This review systematically summarizes the multidimensional regulatory roles of TH across the MASLD disease spectrum and discusses emerging diagnostic and therapeutic implications of TH-based interventions, aiming to inform future mechanistic research and optimize clinical management strategies.

ObjectiveTo explore the relationship between negative life events and depression severity in adolescent patients with depressive disorder， as well as the chain mediating role of insomnia symptoms and quality of life. Methods374 outpatient patients and hospitalized patients with adolescent depressive disorders were enrolled. The Adolescent Life Event Scale （ASLEC）， the Insomnia Severity Index （ISI）， the World Health Organization Quality of Life Questionnaire Short Form （WHOQOL-BREF）， and the Center for Epidemiology Depression Scale （CES-D） were used to evaluate the negative life event situation， insomnia symptoms， quality of life level and depression severity of the subjects， respectively. In addition， the PROCESS 4.0 macroprogram was used to analyze the chain mediating effect of insomnia symptoms and quality of life between negative life events and depression severity in patients with adolescent depressive disorder. ResultsThe results of correlation analysis showed that there was a significant correlation between negative life events and insomnia symptoms， quality of life， and depression severity （all P<0.05）. In addition， the results of chain mediation showed that negative life events had a significant direct effect on depression severity， with an effect size of 0.12 （P<0.001）. Insomnia symptoms and quality of life played a mediating role in the relationship between negative life events and depression severity in patients with adolescent depressive disorders， with indirect effect sizes of 0.062 （95%CI： 0.040-0.087） and 0.091 （95%CI： 0.059-0.123）， respectively. It could also play a chain mediation role， and the effect size was 0.039 （95%CI： 0.024-0.057）. ConclusionNegative life events experienced by patients with adolescent depressive disorder not only directly affect the severity of depressive symptoms， but may also indirectly exacerbate depression through insomnia symptoms and quality of life.

Objective To detect the isocenter of a medical linear accelerator using an optical surface monitoring system (OSMS) combined with a self-made 3D-printed phantom, and compare with the conventional front pointer measurement method. Methods A phantom that could be fixed to the front pointer of the accelerator was fabricated using 3D printing technology. The front pointer method and OSMS were used to detect the rotation isocenter deviations of the accelerator. During the experiments, the collimator, gantry, and couch linear displacement readings were recorded at different angles. We also recorded the measurement time of different surveyors. Results Compared to the front pointer measurement method, the OSMS method showed lower standard deviations. The reductions in standard deviations showed statistical significance in the Lat direction for the collimator rotation isocenter as well as in the Lat and Vrt directions for the gantry rotation isocenter. The mean deviation of Mag values for the collimator rotation isocenter using the OSMS method was 0.50 mm, which was larger than the 0.42 mm using the front pointer method. However, the standard deviation was 0.06 using the OSMS method, which was smaller than the 0.18 using the front pointer method. The mean deviation and standard deviation of Sag values for the gantry rotation isocenter using the OSMS method were 1.03 mm and 0.12, respectively, which were both larger than 0.47 mm and 0.06 using the front pointer method. For the couch rotation isocenter, the mean deviation and standard deviation using the OSMS method were 0.32 mm and 0.04, respectively, which were both smaller than the 0.55 mm and 0.20 using the front pointer method. All surveyors spent less time in isocenter measurements using the OSMS method compared to the front pointer method. Conclusion Compared with the front pointer method, the OSMS method significantly reduces the standard deviation among surveyors, effectively reduces the influence of the angle deviation of the accelerator on the measurement results, reduces detection time, improves detection efficiency, and provides a powerful practical basis for the application of OSMS in detecting the mechanical accuracy of the linear accelerator.

Objective To detect the isocenter of a medical linear accelerator using an optical surface monitoring system (OSMS) combined with a self-made 3D-printed phantom, and compare with the conventional front pointer measurement method. Methods A phantom that could be fixed to the front pointer of the accelerator was fabricated using 3D printing technology. The front pointer method and OSMS were used to detect the rotation isocenter deviations of the accelerator. During the experiments, the collimator, gantry, and couch linear displacement readings were recorded at different angles. We also recorded the measurement time of different surveyors. Results Compared to the front pointer measurement method, the OSMS method showed lower standard deviations. The reductions in standard deviations showed statistical significance in the Lat direction for the collimator rotation isocenter as well as in the Lat and Vrt directions for the gantry rotation isocenter. The mean deviation of Mag values for the collimator rotation isocenter using the OSMS method was 0.50 mm, which was larger than the 0.42 mm using the front pointer method. However, the standard deviation was 0.06 using the OSMS method, which was smaller than the 0.18 using the front pointer method. The mean deviation and standard deviation of Sag values for the gantry rotation isocenter using the OSMS method were 1.03 mm and 0.12, respectively, which were both larger than 0.47 mm and 0.06 using the front pointer method. For the couch rotation isocenter, the mean deviation and standard deviation using the OSMS method were 0.32 mm and 0.04, respectively, which were both smaller than the 0.55 mm and 0.20 using the front pointer method. All surveyors spent less time in isocenter measurements using the OSMS method compared to the front pointer method. Conclusion Compared with the front pointer method, the OSMS method significantly reduces the standard deviation among surveyors, effectively reduces the influence of the angle deviation of the accelerator on the measurement results, reduces detection time, improves detection efficiency, and provides a powerful practical basis for the application of OSMS in detecting the mechanical accuracy of the linear accelerator.

Objective To detect the isocenter of a medical linear accelerator using an optical surface monitoring system (OSMS) combined with a self-made 3D-printed phantom, and compare with the conventional front pointer measurement method. Methods A phantom that could be fixed to the front pointer of the accelerator was fabricated using 3D printing technology. The front pointer method and OSMS were used to detect the rotation isocenter deviations of the accelerator. During the experiments, the collimator, gantry, and couch linear displacement readings were recorded at different angles. We also recorded the measurement time of different surveyors. Results Compared to the front pointer measurement method, the OSMS method showed lower standard deviations. The reductions in standard deviations showed statistical significance in the Lat direction for the collimator rotation isocenter as well as in the Lat and Vrt directions for the gantry rotation isocenter. The mean deviation of Mag values for the collimator rotation isocenter using the OSMS method was 0.50 mm, which was larger than the 0.42 mm using the front pointer method. However, the standard deviation was 0.06 using the OSMS method, which was smaller than the 0.18 using the front pointer method. The mean deviation and standard deviation of Sag values for the gantry rotation isocenter using the OSMS method were 1.03 mm and 0.12, respectively, which were both larger than 0.47 mm and 0.06 using the front pointer method. For the couch rotation isocenter, the mean deviation and standard deviation using the OSMS method were 0.32 mm and 0.04, respectively, which were both smaller than the 0.55 mm and 0.20 using the front pointer method. All surveyors spent less time in isocenter measurements using the OSMS method compared to the front pointer method. Conclusion Compared with the front pointer method, the OSMS method significantly reduces the standard deviation among surveyors, effectively reduces the influence of the angle deviation of the accelerator on the measurement results, reduces detection time, improves detection efficiency, and provides a powerful practical basis for the application of OSMS in detecting the mechanical accuracy of the linear accelerator.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

ObjectiveMicrotube associated protein-2 （MAP-2）， alpha-tubulin （α-tubulin）， and synaptophysin （SYP） are important proteins in neuronal signal communication. This paper observed the effects of modified Zhigancao Tang on the expression of serum α-Synuclein （α-Syn） and its oligomers， MAP-2， α-tubulin， and SYP of patients with liver and kidney deficiency of Parkinson's disease （PD）， analyzed their correlation， and evaluated the therapeutic effect of modified Zhigancao Tang in patients with liver and kidney deficiency of PD based on α-Syn transmission pathway mediated by neuronal communication in vivo. MethodsA total of 60 patients with PD who met the inclusion criteria were randomly divided into a treatment group （30 cases） and a control group （30 cases）. Both groups were treated on the basis of PD medicine， and the treatment group was treated with modified Zhigancao Tang. Both groups were treated for 12 weeks. The changes in UPDRS score， TCM syndrome score， and expression of serum α-Syn and its oligomers， MAP-2， α-tubulin， and SYP were observed before and after 12 weeks of treatment in each group. The correlation between the above-mentioned serum biological indexes and the levels of serum α-Syn and its oligomers was analyzed. ResultsAfter treatment， the TCM syndrome score， UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ score of the treatment group were significantly decreased （P<0.05， P<0.01）. The UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ scores in the treatment group were significantly decreased compared with those in the control group after treatment （P<0.05）. After treatment， the total effective rate of the control group was 63.3% （19/30）， and that of the treatment group was 86.7% （26/30）. The clinical effect of the observation group was better than the control group （Z=-2.03， P<0.05）. The total effective rate of the observation group was better than that of the control group， and the difference was statistically significant （χ²=5.136， P<0.05）. After treatment， the oligomer level of serum α-Syn and MAP-2 level in the treatment group were significantly decreased （P<0.05， P<0.01）. The levels of serum α-Syn and its oligomers， as well as α-tubulin in the treatment group， were significantly decreased compared with those in the control group after treatment （P<0.05， P<0.01）. Serum α-Syn was correlated with serum MAP-2 and α-Syn oligomer in patients with PD （P<0.05， P<0.01） but not correlated with serum SYP . Serum α-Syn oligomers of patients with PD were correlated with serum MAP-2 and α-tubulin （P<0.05， P<0.01） but not correlated with serum SYP level. Serum SYP of patients with PD was correlated with serum MAP-2 （P<0.05）. ConclusionModified Zhigancao Tang has a therapeutic effect on patients with liver and kidney deficiency of PD by inhibiting the production of α-Syn oligomers and intervening α-Syn microtubule transport pathway in vivo.