Objective:To explore the differences between the Phoenix sepsis scoring system including Phoenix sepsis score (PSS) and Phoenix-8 organ dysfunction score (hereinafter referred to as Phoenix-8) and the commonly used pediatric sepsis scores in evaluating clinical characteristics and prognostic analysis of pediatric patients with severe sepsis diagnosed under traditional standards, namely the diagnostic criteria from the 2005 International Pediatric Sepsis Consensus Conference.Methods:This study was a retrospective observational study. From December 2020 to March 2023, 202 pediatric patients with severe sepsis meeting the inclusion criteria were admitted to the Children's Hospital of Nanjing Medical University. Based on the sepsis diagnostic criteria outlined in the International Consensus Criteria for Pediatric Sepsis and Septic Shock (2024), the pediatric patients were categorized into a sepsis group and a non-sepsis group. Sepsis group was further subdivided into a death subgroup and a survival subgroup based on the outcomes. The age, hospitalization costs, disease outcome indicators (e.g., mortality rate and incidence of septic shock), major organ (e.g., heart, liver, lungs, and kidneys) damage and their correlations, as well as PSS, Phoenix-8 and commonly used pediatric sepsis scores (e.g., pediatric sequential organ failure assessment (pSOFA), pediatric risk of mortality score Ⅲ (PRISM Ⅲ), pediatric logistic organ dysfunction-2 score (PELOD-2), pediatric multiple organ dysfunction score (P-MODS), pediatric critical illness score (PCIS), and pediatric early warning score (PEWS)) were collected and compared. Receiver operating characteristic (ROC) curve and precision-recall curve were plotted to evaluate the predictive ability of PSS, Phoenix-8, and commonly used pediatric sepsis scores for mortality risk in pediatric patients with severe sepsis under traditional standards. Predictive performance was quantified using the area under the ROC curve (AUROC). Univariate logistic regression analysis was employed to quantify the odds ratios of PSS and Phoenix-8 for predicting mortality risk. Patients with severe sepsis under traditional standards were further stratified into subgroups based on complications and comorbidities, including central nervous system (CNS) diseases, multiple infections, cardiovascular system diseases, shock, and malignancies. The Hosmer-Lemeshow goodness-of-fit test was used to assess calibration of PSS and Phoenix-8, and the DeLong test was used to compare whether there were statistically significant differences in the AUROC of PSS and Phoenix-8 for predicting mortality risk among different subgroups of pediatric patients. Results:Compared with those in non-sepsis group, pediatric patients in sepsis group were significantly older ( Z=-2.92, P<0.05) with higher incidences of septic shock and mortality, hospitalization costs, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, PSS, and Phoenix-8 (with χ2 values of 21.28 and 13.64, respectively, Z values of -1.99, -5.33, -5.10, -8.55, -6.91, -10.98, and -9.93, respectively, P<0.05), and lower PCIS ( Z=-3.34, P<0.05). Compared with those in survival subgroup, hospitalization costs, PSS, Phoenix-8, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, and P-MODS of pediatric patients in death subgroup was significantly higher (with Z values of -2.50, -3.50, -2.47, -5.11, -3.84, -2.94, -3.61, and -3.04, respectively, P<0.05). Compared with those in survival subgroup, the incidences of lung damage and liver damage of pediatric patients in death subgroup were also significantly higher (with χ2 values of 6.20 and 10.94, respectively, P<0.05), and 64.7% (97/150) of patients exhibited two or more concurrent organ damage. For predicting mortality risk in pediatric patients with severe sepsis under traditional standards, the AUROC values for PRISM Ⅲ, PCIS, PEWS, pSOFA, PELOD-2, P-MODS, PSS, and Phoenix-8 were approximately 0.70, with optimal cutoff values of 17.5, 91.0, 5.5, 4.5, 2.5, 4.5, 3.5, and 4.5, respectively; PELOD-2 demonstrated the highest sensitivity (0.83); while PRISM Ⅲ, PSS, and Phoenix-8 showed high specificity (>0.80). Univariate logistic regression analysis showed that for every 1-point increase in the PSS within 24 hours of pediatric intensive care unit admission, the relative risk of mortality increased by 63.7% (with odds ratio of 1.64, 95% confidence interval of 1.34-1.99, P<0.05). Similarly, for every 1-point increase in the Phoenix-8, the relative risk of mortality increased by 37.5% (with odds ratio of 1.38, 95% confidence interval of 1.18-1.60, P<0.05). The AUROC values (around 0.80) of PSS and Phoenix-8 for predicting mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases were relatively high. In contrast, the AUROC values (0.60-0.80) for predicting mortality risk in pediatric patients with severe sepsis combined with shock or malignant tumors were moderate. All models passed the Hosmer-Lemeshow goodness-of-fit test ( P>0.05). The DeLong test indicated no statistically significant differences in predictive ability between PSS and Phoenix-8 across subgroups of pediatric patients ( P>0.05). Conclusions:PSS and Phoenix-8 exhibited higher specificity than most of the commonly used pediatric sepsis scores in predicting mortality risk under traditional standards. Both scores performed much better in predicting the mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases.

Objective To observe the value of improved marching cubes(MC)algorithm based on Monte Carlo sampling and multi-feature analysis for reconstructing head and abdominal CT images.Methods Totally 69 head axial CT images from one patient with glioma and 108 abdominal axial CT images from another patient with liver cancer were retrospectively enrolled,while 98 head axial CT images of males in visible human project dataset were included.Monte Carlo sampling and multi-feature analysis were introduced into MC algorithm.Monte Carlo sampling was used to simulate the uncertainty of voxel values and estimate the probability of voxels belonging to the isosurface,and dynamic thresholds were generated through combining gradient,curvature,local variance and distance term features of voxels.Then head and abdominal CT images were reconstructed with improved MC algorithm,which were compared with those reconstructed with traditional MC and probabilistic MC(PMC)algorithms.Results Compared with traditional MC and PMC algorithms,improved MC algorithm had lower mean square error,higher signal-to-noise ratio,peak signal-to-noise ratio and computation time for reconstructing head and abdominal CT images without significant difference of Dice similarity coefficient nor recall rate,which could keep the structural loss rate and morphological change rate at low level.Conclusion Improved MC algorithm based on Monte Carlo sampling and multi-feature analysis could significantly improve the robustness and edge accuracy for reconstructing head and abdominal CT images,but the computational efficiency and preservation of head structural details still needed to be optimized.

Objective:The components of Rubus parvifolius L. were analyzed based on UPLC-MS/MS technology and combined with network pharmacology analysis to explore the mechanism of action of Rubi Parvifolii Radix in treating inflammation, cough, fever, influenza and sore throat. Method:The chemical constituents of Rubi Parvifolii Radix were identified according to the information of mass spectrometry. The network pharmacology was used to analyze the corresponding targets and related pathways of its chemical components, and the "component-target-pathway" interaction diagram was drawn. PyMOL 2.5.7 software wasused to perform molecular docking between active components and key targets.Results:Twenty chemical components were identified by UPLC-MS/MS, and 15 components were screened out by network pharmacology, which can be used as quality markers of Rubi Parvifolii Radix, namely Azelaic acid, Procyanidol B3, Caprolactam, Bis (2-ethylhexyl) adipate, Cryptochlorogenic acid, 3-O-Feruloylquinic, Ellagic acid, Aurantiamide acetate, 2 α,3 β,19 α,23-Tetrahydroxyurs-12-en-28-oic acid, L-Epicatechin, (E)-3-Indoleacrylic acid, Euscaphic acid, Suberic acid, Diisononyl phthalate and Prodelphinidin T4. Molecular docking showed that 5 compounds compared with the reference substance could bind to the target proteins of disease well. Conclusions:The 15 active ingredients in Rubi Parvifolii Radix, including Caprolactam and (E)-3-Indoleacrylic acid, may play a therapeutic role in treating colds, high fever, sore throat, and inflammation by acting on targets such as AKT1 and TNF. This provides a certain reference for the clinical application of Rubi Parvifolii Radix.

Objective:To establish a mass spectrometry method for the determination of characteristic peptides of Galli Gigerii Endothelium Corneum that can identify the authenticity of Galli Gigerii Endothelium Corneum as well as its preparations; To evaluate their quality.Methods:Ultra performance chromatography-electrospray tandem mass spectrometry (UPLC-MS/MS) with the mode of multiple reaction monitoring quantification (MRM) was employed to monitor the ion pairs of m/z 379.21(charge: +2)→571.36, m/z 379.21(charge: +2)→385.26, m/z 785.41(charge: +2)→941.51 and m/z 785.41(charge: +2)→245.08, in order to detect the Galli Gigerii Endothelium Corneum crude drug and its preparations. Results:Chicken specific peptide I and chicken specific peptide Ⅱ could be detected in the 18 batches of Galli Gigerii Endothelium Corneum from different regions, their corresponding extractions and 4 batches of prescription preparations, while the chicken specific peptides were not detected in the 8 batches of endothelium corneums from ducks, geese and pigeons.Conclusions:The method established in this study can effectively supplement the deficiencies in standards of Galli Gigerii Endothelium Corneum and its decoction pieces, improve the quality control standard, and provide a reference for the safety and effectiveness of Galli Gigerii Endothelium Corneum in clinical medication.

Objective To observe the value of improved marching cubes(MC)algorithm based on Monte Carlo sampling and multi-feature analysis for reconstructing head and abdominal CT images.Methods Totally 69 head axial CT images from one patient with glioma and 108 abdominal axial CT images from another patient with liver cancer were retrospectively enrolled,while 98 head axial CT images of males in visible human project dataset were included.Monte Carlo sampling and multi-feature analysis were introduced into MC algorithm.Monte Carlo sampling was used to simulate the uncertainty of voxel values and estimate the probability of voxels belonging to the isosurface,and dynamic thresholds were generated through combining gradient,curvature,local variance and distance term features of voxels.Then head and abdominal CT images were reconstructed with improved MC algorithm,which were compared with those reconstructed with traditional MC and probabilistic MC(PMC)algorithms.Results Compared with traditional MC and PMC algorithms,improved MC algorithm had lower mean square error,higher signal-to-noise ratio,peak signal-to-noise ratio and computation time for reconstructing head and abdominal CT images without significant difference of Dice similarity coefficient nor recall rate,which could keep the structural loss rate and morphological change rate at low level.Conclusion Improved MC algorithm based on Monte Carlo sampling and multi-feature analysis could significantly improve the robustness and edge accuracy for reconstructing head and abdominal CT images,but the computational efficiency and preservation of head structural details still needed to be optimized.

Objective:To explore the differences between the Phoenix sepsis scoring system including Phoenix sepsis score (PSS) and Phoenix-8 organ dysfunction score (hereinafter referred to as Phoenix-8) and the commonly used pediatric sepsis scores in evaluating clinical characteristics and prognostic analysis of pediatric patients with severe sepsis diagnosed under traditional standards, namely the diagnostic criteria from the 2005 International Pediatric Sepsis Consensus Conference.Methods:This study was a retrospective observational study. From December 2020 to March 2023, 202 pediatric patients with severe sepsis meeting the inclusion criteria were admitted to the Children's Hospital of Nanjing Medical University. Based on the sepsis diagnostic criteria outlined in the International Consensus Criteria for Pediatric Sepsis and Septic Shock (2024), the pediatric patients were categorized into a sepsis group and a non-sepsis group. Sepsis group was further subdivided into a death subgroup and a survival subgroup based on the outcomes. The age, hospitalization costs, disease outcome indicators (e.g., mortality rate and incidence of septic shock), major organ (e.g., heart, liver, lungs, and kidneys) damage and their correlations, as well as PSS, Phoenix-8 and commonly used pediatric sepsis scores (e.g., pediatric sequential organ failure assessment (pSOFA), pediatric risk of mortality score Ⅲ (PRISM Ⅲ), pediatric logistic organ dysfunction-2 score (PELOD-2), pediatric multiple organ dysfunction score (P-MODS), pediatric critical illness score (PCIS), and pediatric early warning score (PEWS)) were collected and compared. Receiver operating characteristic (ROC) curve and precision-recall curve were plotted to evaluate the predictive ability of PSS, Phoenix-8, and commonly used pediatric sepsis scores for mortality risk in pediatric patients with severe sepsis under traditional standards. Predictive performance was quantified using the area under the ROC curve (AUROC). Univariate logistic regression analysis was employed to quantify the odds ratios of PSS and Phoenix-8 for predicting mortality risk. Patients with severe sepsis under traditional standards were further stratified into subgroups based on complications and comorbidities, including central nervous system (CNS) diseases, multiple infections, cardiovascular system diseases, shock, and malignancies. The Hosmer-Lemeshow goodness-of-fit test was used to assess calibration of PSS and Phoenix-8, and the DeLong test was used to compare whether there were statistically significant differences in the AUROC of PSS and Phoenix-8 for predicting mortality risk among different subgroups of pediatric patients. Results:Compared with those in non-sepsis group, pediatric patients in sepsis group were significantly older ( Z=-2.92, P<0.05) with higher incidences of septic shock and mortality, hospitalization costs, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, PSS, and Phoenix-8 (with χ2 values of 21.28 and 13.64, respectively, Z values of -1.99, -5.33, -5.10, -8.55, -6.91, -10.98, and -9.93, respectively, P<0.05), and lower PCIS ( Z=-3.34, P<0.05). Compared with those in survival subgroup, hospitalization costs, PSS, Phoenix-8, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, and P-MODS of pediatric patients in death subgroup was significantly higher (with Z values of -2.50, -3.50, -2.47, -5.11, -3.84, -2.94, -3.61, and -3.04, respectively, P<0.05). Compared with those in survival subgroup, the incidences of lung damage and liver damage of pediatric patients in death subgroup were also significantly higher (with χ2 values of 6.20 and 10.94, respectively, P<0.05), and 64.7% (97/150) of patients exhibited two or more concurrent organ damage. For predicting mortality risk in pediatric patients with severe sepsis under traditional standards, the AUROC values for PRISM Ⅲ, PCIS, PEWS, pSOFA, PELOD-2, P-MODS, PSS, and Phoenix-8 were approximately 0.70, with optimal cutoff values of 17.5, 91.0, 5.5, 4.5, 2.5, 4.5, 3.5, and 4.5, respectively; PELOD-2 demonstrated the highest sensitivity (0.83); while PRISM Ⅲ, PSS, and Phoenix-8 showed high specificity (>0.80). Univariate logistic regression analysis showed that for every 1-point increase in the PSS within 24 hours of pediatric intensive care unit admission, the relative risk of mortality increased by 63.7% (with odds ratio of 1.64, 95% confidence interval of 1.34-1.99, P<0.05). Similarly, for every 1-point increase in the Phoenix-8, the relative risk of mortality increased by 37.5% (with odds ratio of 1.38, 95% confidence interval of 1.18-1.60, P<0.05). The AUROC values (around 0.80) of PSS and Phoenix-8 for predicting mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases were relatively high. In contrast, the AUROC values (0.60-0.80) for predicting mortality risk in pediatric patients with severe sepsis combined with shock or malignant tumors were moderate. All models passed the Hosmer-Lemeshow goodness-of-fit test ( P>0.05). The DeLong test indicated no statistically significant differences in predictive ability between PSS and Phoenix-8 across subgroups of pediatric patients ( P>0.05). Conclusions:PSS and Phoenix-8 exhibited higher specificity than most of the commonly used pediatric sepsis scores in predicting mortality risk under traditional standards. Both scores performed much better in predicting the mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases.

Objective:To establish HPLC fingerprints of Aristolochia contorta and honey-processed Aristolochia contorta; To analyze the changes of chemical components before and after honey processing with multivariate statistics; To provide a reference for the study on the toxicity reduction of Aristolochia contorta.Methods:The fingerprints of 11 batches of Aristolochia contorta and honey-processed Aristolochia contorta were established through HPLC. Clustering analysis (HCA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and independent sample t-test were used to compare the changes of chemical components of Aristolochia contorta before and after honey processing.Results:The results showed that there were 14 common peaks in the fingerprints of Aristolochia contorta and Aristolochia contorta. 7 common peaks were identified. Both HCA and PCA could clearly distinguish the samples of Aristolochia contorta before and after honey processing. OPLS-DA found and screened 7 differential markers, and the order of difference significance was peak 3 > peak 7 (7-hydroxy aristolochic acid A) > peak 5 (aristolochic acid C)> peak 8 (aristolochic acid D) > peak 6 > peak 2 (Magnolia alkaloid) > peak 14 (aristolochic acid Ⅰ). After honey processing, the content of chemical components represented by peaks 2, 3, 5, 6, 7, 8 and 14 decreased ( P<0.05). Conclusion:This method is simple and specific, which can be used for the fingerprint analysis of Aristolochia contorta and honey-processed Aristolochia contorta, and can effectively distinguish Aristolochia contorta and honey-processed Aristolochia contorta, and provide a reference for the processing research of toxicity reduction of Aristolochia contorta honey processing.

The establishment of a traceability system for the entire industry chain of Chinese medicinal materials can enhance regional brand building,raise the quality awareness of medicinal material producers,standardize the production processes of Chinese medicinal materials,and ensure the production of high-quality medicinal materials.Sichuan Province has successfully implemented a provincial-level Traditional Chinese Medicine(TCM)tracing system that is interconnected across provinces,cities,and counties.This system enables the complete tracking of the entire supply chain,starting from seed and seedling cultivation,through planting and breeding,harvesting and processing,and finally to the production and distribution of decoction pieces in trade and medical institutions.This research provides a comprehensive overview of the progress made in establishing the Chinese herbal medicine traceability system in Sichuan Province.It analyzes the existing challenges faced by participating enterprises,such as the hierarchy of involvement,information integrity,and the overall impact of the system.Moreover,the paper presents valuable insights and suggestions for the further development of the Chinese herbal medicine traceability system in Sichuan Province.These recommendations focus on enhancing the traceability scope,improving service capabilities,promoting data sharing,and establishing standardized norms and guidelines.

Objective:To establish the fingerprints of Microctis Folium by ultra high performance liquid chromatography (UPLC); To determine the contents of three flavonoids in the Microctis Folium; To evaluate the quality difference of Microctis Folium from different producing areas. Methods:The fingerprints were performed on Agilent ZORBAX SB C18 column (2.1 mm×150 mm,1.8 μm). The mobile phase was acetonitrile - 0.1 % acetic acid solution with gradient elution at a flow rate of 0.30 ml/min. The column temperature was 30 ℃ and the detection wavelength was 315 nm. The common fingerprint peaks were identified by UPLC-mass spectrometry, and the identification results were confirmed by comparison of reference materials. Waters Cortecs T3 C18 chromatographic column (2.1 mm × 100 mm,1.6 μm) was used for content determination. The mobile phase was methanol-0.1 % formic acid solution with gradient elution at a flow rate of 0.35 ml/min. The column temperature was 30 ℃ and the detection wavelength was 339 nm. The contents of vitexin, isovitexin and narcissoside in 15 batches of Microctis Folium from different habitats were determine. Results:There were 11 common peaks in the fingerprint of Microctis Folium. Identified by mass spectrometry and confirmed by reference substance,10 chemical components were identified, including caffeic acid, p-hydroxycinnamic acid, ferulic acid, vitexin, isovitexin, kaempferol-3-O-rutoside, astragaloside, narcissoside, isorhamnetin-3-O-glucoside and linden glycoside. The similarity between the fingerprints of 15 batches of Microctis Folium and the control fingerprint was greater than 0.95, indicating that the overall similarity of the fingerprints of Microctis Folium from different producing areas was high. The total contents of three active components were 3.23-5.64 mg/g in Yangjiang City, Guangdong, 3.60-5.78 mg/g in Zhanjiang City, Guangdong, 4.68-5.73 mg/g in Yulin City, Guangxi and 3.87-5.21 mg/g in Wuzhishan City, Hainan . There was no significant difference in the content of three active components in different producing areas. Conclusion:The fingerprints and the determination method established in the study are stable and feasible, which can be used for the quality evaluation of Microctis Folium.

Objective:This study aims to analyze the efficacy and safety of anlotinib in the real world for patients with unresectable or metastatic bone and soft-tissue sarcomas(STSs). Methods:Clinical data of 124 patients with unresectable or metastatic bone and STSs treated with anlotinib in the First Affiliated Hospital of Zhengzhou University from January 2018 to December 2020 were retrospectively analyzed.Information on age,sex,performance status,lines of anlotinib,surgical history,reduction of anlotinib,adverse reaction,metastatic site,tumor location,pathological subtypes and combination chemotherapy was collected and analyzed.The objective response rate(ORR)and disease control rate(DCR)was analyzed for short-term efficacy.Kaplan-Meier method was performed for survival analysis,and the evaluation indexes were median progression-free survival(mPFS)and median overall survival(mOS). Results:The main pathological subtypes of 124 patients were Synovial sarcoma(SS),Leiomyosarcoma(LMS),liposarcoma(LPS).The median age was 48.5 years(9-83 years).The ORR and DCR of anlotinib used in first-line therapy were 26.8％and 82.1％,but in second-line therapy and beyond,the ORR and DCR only were 5.9％and 64.7％.There were improvement in mPFS and mOS with anlotinib in first-line therapy compared to second-line therapy and beyond(mPFS:22.0 months vs 7.0 months,P=0.001;mOS:51.0 months vs 32.0 months,P=0.035).Adverse reactions of anlotinib were well tolerated,and the main grades of adverse reactions were grade Ⅰ and Ⅱ.No new anlotinib-related adverse reactions were identified. Conclusion:Anlotinib has shown a definite effect in the treatment of unresectable or metastatic bone and STSs.The adverse events of anlotinib are minor and well tolerated,and the efficacy of first-line treatment is better.