AIM To study the chemical constituents from the branches and leaves of Michelia yunnanensis Franch.ex Finet & Gagnep.and their anti-inflammatory activities.METHODS The methanol extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Twenty compounds were isolated and identified as dihydrodehydrodiconifenyl alcohol(1),8-hydroxypinoresinol(2),lariciresinol(3),isolariciresinol(4),(7S,8R)-4-hydroxy-3,3',5'-trimethoxy-8',9'-dinor-8,4'-oxyneoligna-7,9-diol-7'-aldehyde(5),thero-2,3-bis-(4-hydroxy-3-methoxypheyl)-3-methoxy-propanol(6),evofolin B(7),(E)-p-coumaryl alcohol γ-O-methyl ether(8),ω-hydroxypropioguaiacone(9),sinapaldehyde(10),isoscopoletin(11),6-hydroxy-5,7-dimethoxycoumarin(12),2α,3α-dihydroxy-2-methylbutyrolactone(13),6-hydroxy-3(1-hydroxy-1-methylethyl)-6-methyl-2-cyclohexen-1-one(14),benzofuran-2-carboxaldehyde(15),3,4-dihydroxy-5-methoxybenzaldehyde(16),3,5-dimethoxy-4-hydroxybenzaldehyde(17),3,4-dihydroxybenzaldehyde(18),3,4-dihydroxybenzoic methyl ester(19),vanillic acid(20).The inhibition rate of compound 1 on NO was 45.39％±0.32％.CONCLUSION Compounds 1-16,18-20 are first isolated from this plant.Compound 1 has anti-inflammatory activity.

Objective:To analyze the predictive factors associated with late-onset sepsis(LOS) in very low birth weight infants,and to develop a risk prediction score scale applicable to these infants three days postnatal.This will provide valuable insights for early diagnosis and timely intervention.Methods:Very low birth weight infants admitted to the Children's Hospital of Fudan University from January 1,2022,to June 30,2024,were selected as research subjects.These infants were categorized into two groups:the LOS group and the non-LOS group,based on whether they developed LOS.LASSO regression analysis,alongside univariate and multivariate regression analyses,was employed to identify predictive factors for LOS in this population.A Logistic model was constructed using the optimal combination of predictive variables,and a risk assessment scale was subsequently developed.The prediction performance of the model was evaluated using the Hosmer-Lemeshow chi-square test and the receiver operating characteristic curve.Results:A total of 444 cases of very low birth weight infants were included,of which 185 had LOS and 259 did not.After screening the variables,seven independent factors were included into the model:birth weight,gestational age,tracheal intubation,abnormal skin color,abdominal distension,elevated C-reactive protein levels,and right hand perfusion index.A predictive scoring scale was developed based on the regression coefficients of each variable,with corresponding risk scores assigned as follows:1,4,3,2,1,1,and 2; a score of ≥3.5 indicated high-risk groups.The Hosmer-Lemeshow test results demonstrated that χ2 = 7.602( P = 0.473).The area under the receiver operating characteristic curve was 0.792 ( P<0.001),with a sensitivity of 73.5% and specificity of 71.0%. Conclusion:The risk score scale developed in this study exhibits significant predictive capability,providing valuable insights for clinical medical personnel to assess the risk of LOS in very low birth weight infants during the early postnatal period.

AIM To study the chemical constituents from the branches and leaves of Michelia yunnanensis Franch.ex Finet & Gagnep.and their anti-inflammatory activities.METHODS The methanol extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Twenty compounds were isolated and identified as dihydrodehydrodiconifenyl alcohol(1),8-hydroxypinoresinol(2),lariciresinol(3),isolariciresinol(4),(7S,8R)-4-hydroxy-3,3',5'-trimethoxy-8',9'-dinor-8,4'-oxyneoligna-7,9-diol-7'-aldehyde(5),thero-2,3-bis-(4-hydroxy-3-methoxypheyl)-3-methoxy-propanol(6),evofolin B(7),(E)-p-coumaryl alcohol γ-O-methyl ether(8),ω-hydroxypropioguaiacone(9),sinapaldehyde(10),isoscopoletin(11),6-hydroxy-5,7-dimethoxycoumarin(12),2α,3α-dihydroxy-2-methylbutyrolactone(13),6-hydroxy-3(1-hydroxy-1-methylethyl)-6-methyl-2-cyclohexen-1-one(14),benzofuran-2-carboxaldehyde(15),3,4-dihydroxy-5-methoxybenzaldehyde(16),3,5-dimethoxy-4-hydroxybenzaldehyde(17),3,4-dihydroxybenzaldehyde(18),3,4-dihydroxybenzoic methyl ester(19),vanillic acid(20).The inhibition rate of compound 1 on NO was 45.39％±0.32％.CONCLUSION Compounds 1-16,18-20 are first isolated from this plant.Compound 1 has anti-inflammatory activity.

Objective:Based on the background of high-quality development,we analyze the operational efficiency of traditional Chinese medicine(TCM)hospitals in China's Yangtze River Economic Belt in 2021 and explore the impact of external environmental factors on operational efficiency,so as to provide a reference for promoting the high-quality development of TCM hospitals in the Yangtze River Economic Belt.Methods:The three-stage DEA model was used to analyze the operational efficiency of TCM hospitals in 11 provinces and cities in the Yangtze River Economic Zone in China in 2021.Results:After three-stage DEA analysis,the values of comprehensive efficiency,pure technical efficiency and scale efficiency of TCM hospitals in China's Yangtze River Economic Belt are 0.976,0.986 and 0.990,respectively.5 provinces and cities,Shanghai,Jiangsu,Hunan,Chongqing and Guizhou,are efficient before and after the adjustment,and the comprehensive efficiency of Zhejiang,Anhui,Hubei,Jiangxi,Sichuan and Yunnan have increased compared with that before the adjustment.Ranking of the average value of the comprehensive efficiency of TCM hospitals operation in the three major city clusters of the Yangtze River Economic Belt after adjustment:Chengdu-Chongqing city cluster(0.998)>city cluster in the Yangtze River Delta(0.964)>city cluster in the middle reaches of the Yangtze River(0.962).Conclusion:The operational efficiency of TCM hospitals in the Yangtze River Economic Zone has been underestimated,and the comprehensive efficiency is mainly affected by scale efficiency;there are differences in the operational efficiency of TCM hospitals in the three major urban agglomerations,and balanced development is needed between regions;the operational efficiency of TCM hospitals is affected by the external environment,and it is necessary to improve the external environment;it is necessary to strengthen the construction of digital and informatization of TCM,and to pay attention to the role of talents in TCM,so as to promote the high-quality development of TCM hospitals.

Objective:To analyze the predictive factors associated with late-onset sepsis(LOS) in very low birth weight infants,and to develop a risk prediction score scale applicable to these infants three days postnatal.This will provide valuable insights for early diagnosis and timely intervention.Methods:Very low birth weight infants admitted to the Children's Hospital of Fudan University from January 1,2022,to June 30,2024,were selected as research subjects.These infants were categorized into two groups:the LOS group and the non-LOS group,based on whether they developed LOS.LASSO regression analysis,alongside univariate and multivariate regression analyses,was employed to identify predictive factors for LOS in this population.A Logistic model was constructed using the optimal combination of predictive variables,and a risk assessment scale was subsequently developed.The prediction performance of the model was evaluated using the Hosmer-Lemeshow chi-square test and the receiver operating characteristic curve.Results:A total of 444 cases of very low birth weight infants were included,of which 185 had LOS and 259 did not.After screening the variables,seven independent factors were included into the model:birth weight,gestational age,tracheal intubation,abnormal skin color,abdominal distension,elevated C-reactive protein levels,and right hand perfusion index.A predictive scoring scale was developed based on the regression coefficients of each variable,with corresponding risk scores assigned as follows:1,4,3,2,1,1,and 2; a score of ≥3.5 indicated high-risk groups.The Hosmer-Lemeshow test results demonstrated that χ2 = 7.602( P = 0.473).The area under the receiver operating characteristic curve was 0.792 ( P<0.001),with a sensitivity of 73.5% and specificity of 71.0%. Conclusion:The risk score scale developed in this study exhibits significant predictive capability,providing valuable insights for clinical medical personnel to assess the risk of LOS in very low birth weight infants during the early postnatal period.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Aim To study the protective effect of the silibinin derivative Sil-1 on acute myocardial ischemia in SD rats and its mechanism of action.Methods Af-ter 18 hours of oxygen-glucose deprivation and treat-ment of H9c2 cells,the protective effect of Sil-1 on rat cardiomyocytes was examined.SD rats were treated 30 minutes before surgery,followed by 24 h ligation of the left anterior descending coronary artery.The cardiopro-tective effects of Sil-1 and its mechanisms for improving myocardial ischemic injury were investigated using pro-teomics technology.Results In vitro,compared with the control group,the activity of H9c2 cells in the mod-el group showed reduced cell viability,increased dead cells,elevated ROS and higher levels of LDH and in-flammatory cytokines TNF-α,IL-1β and IL-6 in the culture medium.Sil-1 could improve the above condi-tions to different degrees.In vivo,compared with the control group,rats in the model group showed signifi-cantly higher T waves on electrocardiogram,significant ischemic areas in the heart section,disorganized ar-rangement of cardiomyocytes,increased inflammatory factor infiltration and elevated CK,CK-MB,LDH and inflammatory factors TNF-α,IL-6 and IL-1β.Besides,NF-κB phosphorylation levels in myocardial tissue in-creased.Sil-1 improved the above conditions to varying degrees.The results of proteomics showed that 90 pro-teins were found between the control vs model group and the Sil-1 vs model group,and KEGG enrichment a-nalysis showed that MAPK,chemokines,VEGF and other signaling pathways were abundant.Western blot results showed that Sil-1 blocked the phosphorylation of ERK,JNK and p38 MAPK.Conclusions Sil-1 inhib-its the MAPK pathway by blocking the phosphorylation of JNK,ERK,and p38 MAPK,and achieves a protec-tive effect on rats with acute myocardial infarction.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.