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 prepare the recombinant Echinococcus granulosus Polo-like kinase 2 (rEgPLK2) protein and evaluate its immunoprotective efficacy against cystic echinococcosis, so as to provide insights into research and development of novel vaccines against echinococcosis. Methods The Polo-like kinase (PLK) protein sequences were retrieved from 12 species in the NCBI protein database, including E. granulosus and E. multilocularis. Multiple sequence alignment was performed using the Clustal Omega program, and structural visualization and homology analysis were conducted using the ESPript 3.2 program. The recombinant plasmid pET-30a-EgPLK2 was transformed into BL21(DE3) competent cells. Protein expression was induced with isopropyl-β-D-thiogalactoside (IPTG), and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) was performed to characterize the expression and molecular weight of the rEgPLK2 protein. The purified rEgPLK2 protein was thoroughly emulsified with Freund’s complete adjuvant at a 1 : 1 volume ratio. Two New Zealand white rabbits were immunized with multipoint subcutaneous injection on the back at a dose of 300 μg per rabbit for primary immunization. For booster immunizations, the protein was emulsified with Freund’s incomplete adjuvant at a 1 : 1 volume ratio and administered on days 14, 28, and 42 after the primary immunization at a dose of 150 μg per rabbit. Serum was sampled from the rabbit ear vein on day 7 after the final immunization to yield anti-rEgPLK2 polyclonal antibodies. Antibody titer was determined by indirect enzyme-linked immunosorbent assay (ELISA), and antibody specificity was verified by Western blotting. The tissue localization of the EgPLK2 protein was detected in E. granulosus protoscoleces and adult worms using immunofluorescence assay (IFA). Eighteen 6- to 8-week-old female SPF-grade BALB/c mice were randomly divided into three groups, including the blank control group, rEgPLK2-ISA immunization group, and PBS-ISA adjuvant control group, of 6 mice each group. Mice in the rEgPLK2-ISA immunization group and PBSISA group received three primary immunizations via intramuscular injection, and animals in the rEgPLK2-ISA immunization group was inoculated with immunogens prepared by emulsifying rEgPLK2 protein with ISA 201 adjuvant at a 1 : 1 volume ratio (6 μg per mouse), while mice in the PBS-ISA adjuvant control group received an equal volume of PBS emulsified with ISA adjuvant at a 1 : 1 volume ratio. A fourth booster immunization was administered via intraperitoneal injection. Mice in the rEgPLK2-ISA immunization group received a booster immunization with 8 μg of rEgPLK2 protein per mouse, and animals in the PBS-ISA group received an equal volume of PBS, with immunizations given at 2-week intervals. Mice in the blank control group were given no treatment, and housed under standard conditions. Tail vein blood was collected from all mice 7 days after the final immunization, and levels of specific anti-rEgPLK2 IgG antibody and its subclasses (IgG1, IgG2a, IgG2b, IgG3) were measured by indirect ELISA. E. granulosus infection was modelled in mice through injection with 1 000 E. granulosus protoscoleces via intrahepatic portal vein in the rEgPLK2-ISA immunization group and PBS-ISA adjuvant control group 2 weeks after the last immunization. All mice were sacrificed and dissected. The number of cysts was counted in mouse livers, and the cyst reduction rate was calculated. Liver tissues were processed for paraffin sectioning and stained with hematoxylin and eosin (HE), and histopathological changes were examined under a light microscope. Results Sequence analysis revealed that EgPLK2 shared a high amino acid sequence homology with E. multilocularis PLK2 (EmPLK2) and contained the typical domains of the Polo-like kinase family, including the serine/threonine protein kinase catalytic domain (STKc) and Polo-box. The IPTG-induced rEgPLK2 protein was mainly expressed in the form of inclusion bodies, and the purified rEgPLK2 protein showed a relative molecular mass of approximately 70 kDa. The prepared rabbit anti-rEgPLK2 polyclonal antibody had a titer of 1 : 256 000, and Western blotting assay showed that this anti-body specifically recognized the rEgPLK2 protein with a relative molecular mass of approximately 70 kDa. Immunofluorescence assay showed that the EgPLK2 protein was localized in the excretory bladder and rostellum of E. granulosus protoscoleces, as well as the tegument, suckers, and inter-proglottid junctions of adult worms. Immunoprotective assay showed that the serum levels of specific anti-rEgPLK2 IgG, IgG1, IgG2a, and IgG2b antibodies were 2.92 ± 0.49, 0.33 ± 0.10, 0.31 (0.36), and 3.12 (1.73) in mice in the rEgPLK2-ISA immunization group, which were all significantly higher than those in the PBS-ISA adjuvant control group (0.14 ± 0.04, 0.07 ± 0.01, 0.12 ± 0.04, and 0.11 ± 0.04, respectively) (t = 19.28 and 8.46, Z = 3.75 and 4.15; all P values < 0.001); however, there was no significant difference in the serum anti-IgG3 antibody level between the rEgPLK2-ISA immunization group and the PBS-ISA adjuvant control group [0.07 (0.01) vs. 0.073 (0.07); Z = 0.69, P > 0.05)]. In the mouse model of E. granulosus infections, the area of hepatic lesions was reduced and the inflammatory infiltration was alleviated in the rEgPLK2-ISA immunization group than in the PBS-ISA adjuvant control group, and the number of hepatic cysts was higher in the PBS-ISA adjuvant control group than in the rEgPLK2-ISA immunization group [8.00 (2.00) vs. 1.00 (0.75); Z = −2.93, P < 0.01], with a cyst reduction rate of 80.40%. Indirect ELISA assay measured higher serum levels of specific anti-rEgPLK2 IgG (3.28 ± 0.48 vs. 0.11 ± 0.04; t = 15.86, P < 0.01), IgG1 (0.29 ± 0.02 vs. 0.09 ± 0.01; t = 15.67, P < 0.01), IgG2a [3.71 (1.09) vs. 0.08 (0.03); Z = 2.88, P < 0.01], and IgG2b antibodies [3.34 (1.01) vs. 0.08 (0.03); Z = 2.88, P < 0.01] in the rEgPLK2-ISA immunization group than in the PBS-ISA adjuvant control group, and there was no significant difference in the serum level of the specific anti-rEgPLK2 IgG3 antibody between the rEgPLK2-ISA immunization group and the PBS-ISA adjuvant control group (0.07 ± 0.01 vs. 0.07 ± 0.01; t = 1.29, P > 0.05). Conclusions The prokaryotic expression system has been successfully constructed for the EgPLK2 gene and the anti-rEgPLK2 polyclonal antibody has been obtained. The rEgPLK2 protein exhibits a high immunogenicity, and is effective to protect against E. granulosus infection, and inhibits cyst development, which is a promising candidate vaccine target against cystic echinococcosis.

ObjectiveBased on non-targeted metabolomics， to analyze the regulation of endogenous differential metabolites in serum of type 2 diabetes mellitus（T2DM） rats by Fuling Yunhua granules， and to clarify the metabolic pathways through which this granules exerted its effect on improving T2DM. MethodSeventy SD rats， half male and half female， were randomly divided into the control group， model group， and high， medium， low dose groups of Fuling Yunhua granules（20.70， 10.35， 5.18 g·kg^-1 in raw drug amount） and the positive drug group（pioglitazone hydrochloride tablets， 8.1 mg·kg^-1）. Except for the control group， other groups were fed with high-sugar and high-fat diet combined with intraperitoneal injection of streptozotocin（STZ） to establish a T2DM rat model. After successful modeling， the treatment groups were administered the corresponding drugs by gavage， and the control group and model group were treated with an equal volume of saline by gavage， once/d， for 28 d. Fasting blood glucose（FBG） and glycosylated hemoglobin A1c（GHbA1c） levels were measured in all groups of rats during the administration period， and hematoxylin-eosin（HE） staining was used to observe the pathomorphological changes in the pancreatic tissues of rats at the end of the administration period. The endogenous metabolite levels in rat serum were detected by ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-LTQ-Orbitrap MS）， and the data were processed using principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. Differential metabolites were identified by the Human Metabolome Database（HMDB） and the Kyoto Encyclopedia of Genes and Genomes（KEGG）， and screened for differential metabolites with variable importance in the projection（VIP） value>1， P<0.05， and fold change（FC）<0.6 or FC>1. And the metabolic pathway enrichment analysis of the screened differential metabolites was performed by MetaboAnalyst 5.0， then the screened differential metabolites were diagnosed and evaluated by the receiver operating characteristic（ROC） curves. ResultCompared with the control group， the FBG level of rats in the model group increased significantly（P<0.01）， the GHbA1c content tended to increase， but the difference was not statistically significant， and the pancreatic tissue of rats was obviously damaged， the number of pancreatic islets decreased， and the pancreatic β-cells were obviously reduced， atrophied and enlarged. Compared with the model group， the FBG levels of rats in the high dose group of Fuling Yunhua granules and the positive drug group were significantly reduced after 2 weeks of administration（P<0.05， P<0.01）， the GHbA1c content of rats in the high dose group of Fuling Yunhua granules was significantly reduced（P<0.05）， and the pancreatic tissue lesions of rats in the different dose groups of Fuling Yunhua granules were reduced. The results of non-targeted metabolomics showed that 46 differential metabolites were significantly changed in the model group compared with the blank group. Pathway enrichment analysis found that T2DM mainly affected biological processes including biosynthesis of primary bile acid， D-amino acid metabolism， steroid hormone biosynthesis， and glycerophospholipid metabolism in rats. Compared with the model group， the levels of 8 differential metabolites in the high dose group of Fuling Yunhua granules were significantly adjusted， and the pathway enrichment analysis found that D-amino acid metabolism， retinol metabolism， glycine， serine and threonine metabolism， tryptophan metabolism and other metabolic pathways were mainly involved. ROC curves further analysis revealed that the four characteristic differential markers of 11-cis-retinol， D-piperidinic acid， D-serine， and p-cresol sulfate had high diagnostic value for the treatment of T2DM with Fuling Yunhua granules. ConclusionFuling Yunhua granules can improve the symptoms of T2DM rats by regulating the amino acid metabolic and retinol metabolic pathways through the modulation of endogenous differential metabolites.