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.

BACKGROUND: Arsenic trioxide (ATO) is indicated as a broad-spectrum medicine for a variety of diseases, including cancer and cardiac disease. While the role of ATO in hepatic ischemia/reperfusion injury (HIRI) has not been reported. Thus, the purpose of this study was to identify the effects of ATO on HIRI. METHODS: In the present study, we established a 70% hepatic warm I/R injury and partial hepatectomy (30% resection) animal models in vivo and hepatocytes anoxia/reoxygenation (A/R) models in vitro with ATO pretreatment and further assessed liver function by histopathologic changes, enzyme-linked immunosorbent assay, cell counting kit-8, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay. Small interfering RNA (siRNA) for extracellular signal-regulated kinase (ERK) 1/2 was transfected to evaluate the role of ERK1/2 pathway during HIRI, followed by ATO pretreatment. The dynamic process of autophagic flux and numbers of autophagosomes were detected by green fluorescent protein-monomeric red fluorescent protein-LC3 (GFP-mRFP-LC3) staining and transmission electron microscopy. RESULTS: A low dose of ATO (0.75 μmol/L in vitro and 1 mg/kg in vivo ) significantly reduced tissue necrosis, inflammatory infiltration, and hepatocyte apoptosis during the process of hepatic I/R. Meanwhile, ATO obviously promoted the ability of cell proliferation and liver regeneration. Mechanistically, in vitro  studies have shown that nontoxic concentrations of ATO can activate both ERK and phosphoinositide 3-kinase-serine/threonine kinase (PI3K-AKT) pathways and further induce autophagy. The hepatoprotective mechanism of ATO, at least in part, relies on the effects of ATO on the activation of autophagy, which is ERK-dependent. CONCLUSION Low, non-toxic doses of ATO can activate ERK/PI3K-AKT pathways and induce ERK-dependent autophagy in hepatocytes, protecting liver against I/R injury and accelerating hepatocyte regeneration after partial hepatectomy.
Animals ; Arsenic Trioxide ; Autophagy/physiology* ; Reperfusion Injury/prevention & control* ; Mice ; Male ; Proto-Oncogene Proteins c-akt/physiology* ; Arsenicals/therapeutic use* ; Oxides/therapeutic use* ; Liver/metabolism* ; Extracellular Signal-Regulated MAP Kinases/metabolism* ; Mice, Inbred C57BL

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.

OBJECTIVE To establish the specific chromatogram of Qianghuo Shengshi Tang(QHSS) reference sample, clarify the key quality attributes of QHSS, providing reference for the quality evaluation of QHSS reference sample. METHODS The SilGreen C18 column(4.6 mm×250 mm, 5 μm) was used. The mobile phase consisted acetonitrile and 0.2% formic acid aqueous solution. The detection wavelength was 328 nm. Established an HPLC characteristic spectrum analysis method for the reference sample of QHSS. A variety of chromatographic columns and different instruments were applied to investigate the adaptability of the system. HPLC-LTQ-Orbitrap MS was used to identify the specific peaks of the QHSS reference samples in positive ion mode. RESULTS There were 14 peaks in the specific chromatogram, which belonged to Notopterygii Rhizoma Et Radix, Angelicae Pubescentis Radix, Ligustici Rhizoma Et Radix, Chuanxiong Rhizome, Viticis Fructus, respectively. Ferulic acid(peak 3) was reference peak. A total of 22 compounds were identified by mass spectrometry, including coumarin and flavonoids. CONCLUSION The established specific chromatogram method of QHSS is simple, stable and reproducible. The material basis of QHSS reference sample is basically determined, providing a reference for the development and quality control of QHSS.

Objective:To construct an system of optimization and evaluation parameters for the archive management of medical equipment in hospital,and to optimize and improve the quality and effect of the management for the archive of medical equipment of hospital.Methods:The problems existing in the management of the archives of medical equipment in hospitals were analyzed,and the targeted measures were formulated on the basis of the optimization of management mode,the innovation of management process of the archives,the improvement of management system of archives and continuous improvement of the quality of management personnel of equipment archives.The indicator system of optimization and evaluation of the management of medical equipment archives of hospital was constructed from 6 secondary indicators included management mechanism and system construction,personnel training and capacity building,quality of archive management,efficiency of archives review,satisfaction survey of service object,and innovation ability,as well as 18 tertiary indicators under the secondary indicators.The scores of the secondary and tertiary indicators of the evaluation of indicator system between before and after the measures of indicator system of optimization and evaluation of archive management of medical equipment of Peking University School and Hospital of Stomatology were implemented were compared.Results:Before each measure that was formulated by the indicator system of optimization and evaluation of the archive management of medical equipment of hospital was implemented,the comprehensive evaluation score of archive management of medical equipment of hospital was 3.65 points.The comprehensive evaluation score was 4.9 points after the each measure was implemented.After the indicator system was implemented,the median scores of secondary and tertiary indicators were respectively 0.63(0.40-1.50)points and 0.25(0.13-0.50)points,which were all significantly higher than those before they were implemented,and the differences were all statistically significant(Z=-2.23,-3.22,P<0.05).Conclusion:The indicator system of optimization and evaluation of archive management of medical equipment of hospital can improve the quality and effect of archive management of medical equipment of hospital,and provide a basis and guarantee for the whole life cycle management of medical equipment such as procurement decision-making,quality control management,maintenance management,and scrap disposal of medical equipment of hospital.

Objective To investigate the effect of thalidomide combined with infliximab (IFX) in treatment of refractory inflammatory bowel disease (IBD) and its effects on insulin-like growth factor-1 (IGF-1) and transforming growth factor-β1 (TGF-β1). Methods A total of 120 patients with refractory IBD were randomly divided into experimental group and control group, with 60 cases in each group. The two groups were given conventional treatment (mesalazine), the control group was given IFX, and the experimental group was given IFX combined with thalidomide, continuous treatment for two months. The efficacy, intestinal flora disturbance rate, adverse reactions, Crohn's disease activity index (CDAI), Lewis score, serum IGF-1, TGF-β1 levels and nutritional status indexes[albumin (ALB), transferrin (Tf)]before and after treatment for 1 month and 2 months of the two groups were compared. Results The total effective rate of the experimental group was significantly higher than that of the control group (P < 0.05). After one month and two months of treatment, CDAI and Lewis scores of the experimental group were significantly lower than those of the control group (P < 0.05); the serum levels of IGF-1, TGF-β1 as well as ALB and Tf in the experimental group were significantly higher than those in the control group (P < 0.05). The improvement of intestinal flora disturbance rate in the experimental group was significantly better than that in the control group (P < 0.05). There was no significant difference in the incidence of oral and nasal mucosa dryness, throat discomfort, nausea and vomiting between two groups (P>0.05). Conclusion In the treatment of refractory IBD patients, thalidomide combined with IFX can regulate serum IGF-1 and TGF-β1 levels, effectively relieve clinical manifestations, inhibit inflammatory activities, and improve nutritional status and intestinal flora disorders of patients, and it has high safety.

ObjectiveTo establish the specific chromatogram and thin layer chromatography（TLC） of Qingxin Lianziyin（QXLZY） benchmark samples， in order to clarify the key quality attributes and provide a reference for the quality evaluation of QXLZY. MethodHigh performance liquid chromatography（HPLC） specific chromatogram of QXLZY benchmark samples was developed by using a YMC Hydrosphere C₁₈ column（4.6 mm×250 mm， 5 μm） with the mobile phase of acetonitrile（A）-0.2% formic acid aqueous solution（B） for gradient elution（0-10 min， 5%-20%A； 10-20 min， 20%A； 20-25 min， 20%-24%A； 25-40 min， 24%-30%A； 40-55 min， 30%-50%A； 55-65 min， 50%-100%A； 65-75 min， 100%A； 75-75.1 min， 100%-5%A； 75.1-90 min， 5%A）， and the detection wavelength was 360 nm. Ultra-high performance liquid chromatography-linear ion trap/orbitrap mass spectrometry（UHPLC-LTQ-Orbitrap MS） with electrospray ionization（ESI） was used to identify the components of QXLZY benchmark samples by accurate relative molecular weight and multilevel MS fragment ion information， the detection conditions were positive and negative ion modes and data dependency scanning mode. TLC identification methods for Ophiopogonis Radix， Lycii Cortex， Nelumbinis Semen， Poria， Astragali Radix and Ginseng Radix et Rhizoma in QXLZY were established. ResultA total of 15 characteristic peaks were identified from Glycyrrhizae Radix et Rhizoma， Plantaginis Semen and Scutellariae Radix， and the relative standard deviations of the retention times of 15 characteristic peaks in 15 batches of QXLZY benchmark samples were≤3% with peak 8（baicalin） as the reference peak. A total of 100 compounds， including flavonoids， organic acids， saponins， amino acids and others， were identified in the benchmark samples by UHPLC-LTQ-Orbitrap MS. The established TLC had good separation and was suitable for the identification of Ophiopogonis Radix， Lycii Cortex， Nelumbinis Semen， Poria， Astragali Radix and Ginseng Radix et Rhizoma in QXLZY. ConclusionThe material basis of QXLZY benchmark samples is basically determined by MS designation and source attribution. The established specific chromatogram and TLC of QXLZY are simple， stable and reproducible， which can provide a reference for the development and quality control of QXLZY.

ObjectiveTo establish the specific chromatogram and thin layer chromatography（TLC） identification method of Kaixinsan（KXS） samples， in order to clarify the key quality attributes and provide reference for the quality evaluation of KXS. MethodHigh performance liquid chromatography（HPLC） specific chromatogram of KXS was developed with YMC Hydrosphere C₁₈ column（4.6 mm×250 mm， 5 μm）， the mobile phase was acetonitrile（A）-0.2% formic acid aqueous solution（B） for gradient elution（0-15 min， 2%-20%A； 15-25 min， 20%-25%A； 25-30 min， 25%-30%A； 30-45 min， 30%-31%A； 45-50 min， 31%-44%A； 50-65 min， 44%-45%A； 65-73 min， 45%-75%A； 73-95 min， 75%-100%A； 95-105 min， 100%A； 105-105.1 min， 100%-2%A； 105.1-120 min， 2%A）， the detection wavelength was 320 nm. Ultra high performance liquid chromatography-linear ion trap-electrostatic field orbitrap mass spectrometry（UHPLC-LTQ-Orbitrap MS） was used to identify the chemical components of KXS with electrospray ionization（ESI）， negative ion mode and scanning range of m/z 50-2 000. TLC identification methods for Poria and Ginseng Radix et Rhizoma in KXS were established. ResultThere were 11 common peaks in the specific chromatogram of KXS， attributed to Polygalae Radix， Poria and Acori Tatarinowii Rhizoma. Taking peak 9（α-asarone） as the reference peak， the relative standard deviations of the retention times of 15 batches of KXS samples were<0.2%. A total of 34 compounds were identified by UHPLC-LTQ-Orbitrap MS， including terpenoids， phenylpropanoids， oligosaccharides and ketones. The established TLC had good separation and was rapid， reliable， simple， feasible， suitable for the identification of Poria and Ginseng Radix et Rhizoma in KXS. ConclusionThe specific chromatogram and TLC of KXS are stable and reproducible. The material basis of KXS is basically clarified by MS， which can provide a reference for the development and quality control of KXS.

ObjectiveAlmond， which is bitter in taste， contains traces of toxic substances. For the sake of the safety of prescriptions containing this medicinal material， the processing method of "soaking in boiling water" was selected. Moreover， through literature research and network pharmacology， the characteristic index of this medicinal material was determined. On this basis， a method was established for the determination of amygdalin in Qingfei Paidu Granules （QFPD） and the transfer rate of it in the processing of this prescription was monitored， aiming at improving the quality control system of QFPD. MethodThe high performance liquid chromatography conditions are as follows： YMC Triart C₁₈ column （4.6 mm × 150 mm， 5 µm）， mobile phase of methanol-water with flow of 1.0 mL·min^-1， column temperature of 35 ℃， and detection wavelength of 210 nm. ResultThe linear curve fitted well and the average recovery of amygdalin was 97.74% with RSD of 4.3%. The transfer rates of amygdalin from the medicinal material to the extract， from extract to concentrate， and from concentrate to granules were investigated with this method. The result showed that the average transfer rate from the medicinal material to the granules was （60±3.91）%. The comparison of transfer rate between the processes suggesting that the extraction of the medicinal material might be the key part influencing the prescription preparation. ConclusionThe method is simple， sensitive， reproducible， stable， and accurate， and the index is reasonable. Thus， the method can be used for the quality control of QFPD and determination of transfer rate of components in the preparation of QFPD. This study further improves the quality control standard of almond in QFPD， which can serve as a reference for the clinical application of QFPD.