ObjectiveTo investigate the effects of different fermentation methods and times on the fungal flora and chemical composition of Aurantii Fructus， in order to obtain the optimal fermentation conditions and flora structure， and to ensure the stability and controllability of the fermented varieties. MethodsScanning electron microscopy was used to observe and analyze the colony characteristics on the surface of Aurantii Fructus under different fermentation conditions. Internal transcribed spacer 2（ITS2） high-throughput sequencing， combined with fungal community diversity analysis and fungal community structure analysis， were used to obtain the fungal flora microbial categories of Aurantii Fructus under the conditions of traditional pressure-shelf fermentation and non-pressure-shelf natural fermentation for 7， 14， 21 d（numbered Y1-Y3 for the former， and numbered F1-F3 for the latter）， respectively. At the same time， the chemical components in the fermentation process were detected by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， combined with principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and compound retention time， parent ions， characteristic fragment ions and other information， the differential compounds between the different fermentation samples were screened and identified. ResultsThe analysis of fungal community diversity showed that the dominant flora did not change at different fermentation time points in the traditional pressure-shelf fermentation method， while in the non-pressure-shelf natural fermentation method， there was a significant difference with the fermentation process， and at the genus level， the dominant genus of samples Y1， Y2， Y3 and F2 was Aspergillus， while the dominant genera of samples F1 and F3 were both Rhizopus. This indicated that the microbial growth environment provided by the traditional fermentation method was more stable， and the microbial community structure was more stable， which was more conducive to the stable and controllable fermentation process and fermented products. A total of 155 compounds were identified by compositional analysis， including 70 flavonoids， 38 coumarins， 10 alkaloids， 34 organic acids and 3 other compounds. After fermentation， two new components of ribalinine and pranferin were produced. Different fermentation conditions also brought about differences in chemical composition， multivariate statistical analysis obtained 26 differential compounds under two different fermentation methods， mainly including flavonoids， organic acids and coumarins. Comprehensively， the microbial community structure of samples fermented by the traditional pressure-shelf method of Aurantii Fructus for 14 d was stable， the species richness was high and the overall content of differential compounds was high， which was the optimal processing condition. ConclusionCompared with non-pressure-shelf natural fermentation， the traditional method has obvious advantages in terms of the stability of the microbial community structure and the content of chemical compounds， and the optimal condition is 14 days of fermentation. This study is helpful to promote the quality stability and fermentation bioavailability of fermented products of Aurantii Fructus， as well as to provide an experimental basis for the further improvement of the quality control methods of this variety.

ObjectiveTo investigate the effects of different fermentation methods and times on the fungal flora and chemical composition of Aurantii Fructus， in order to obtain the optimal fermentation conditions and flora structure， and to ensure the stability and controllability of the fermented varieties. MethodsScanning electron microscopy was used to observe and analyze the colony characteristics on the surface of Aurantii Fructus under different fermentation conditions. Internal transcribed spacer 2（ITS2） high-throughput sequencing， combined with fungal community diversity analysis and fungal community structure analysis， were used to obtain the fungal flora microbial categories of Aurantii Fructus under the conditions of traditional pressure-shelf fermentation and non-pressure-shelf natural fermentation for 7， 14， 21 d（numbered Y1-Y3 for the former， and numbered F1-F3 for the latter）， respectively. At the same time， the chemical components in the fermentation process were detected by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， combined with principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and compound retention time， parent ions， characteristic fragment ions and other information， the differential compounds between the different fermentation samples were screened and identified. ResultsThe analysis of fungal community diversity showed that the dominant flora did not change at different fermentation time points in the traditional pressure-shelf fermentation method， while in the non-pressure-shelf natural fermentation method， there was a significant difference with the fermentation process， and at the genus level， the dominant genus of samples Y1， Y2， Y3 and F2 was Aspergillus， while the dominant genera of samples F1 and F3 were both Rhizopus. This indicated that the microbial growth environment provided by the traditional fermentation method was more stable， and the microbial community structure was more stable， which was more conducive to the stable and controllable fermentation process and fermented products. A total of 155 compounds were identified by compositional analysis， including 70 flavonoids， 38 coumarins， 10 alkaloids， 34 organic acids and 3 other compounds. After fermentation， two new components of ribalinine and pranferin were produced. Different fermentation conditions also brought about differences in chemical composition， multivariate statistical analysis obtained 26 differential compounds under two different fermentation methods， mainly including flavonoids， organic acids and coumarins. Comprehensively， the microbial community structure of samples fermented by the traditional pressure-shelf method of Aurantii Fructus for 14 d was stable， the species richness was high and the overall content of differential compounds was high， which was the optimal processing condition. ConclusionCompared with non-pressure-shelf natural fermentation， the traditional method has obvious advantages in terms of the stability of the microbial community structure and the content of chemical compounds， and the optimal condition is 14 days of fermentation. This study is helpful to promote the quality stability and fermentation bioavailability of fermented products of Aurantii Fructus， as well as to provide an experimental basis for the further improvement of the quality control methods of this variety.

Aim To explore the therapeutic effect and mechanism of Qingjie Huagong decoction in modulating PI3K/AKT/NF-κB signaling pathway in inflammatory response of acute pancreatitis(AP)mice.Methods Twenty-four mice were randomly divided into Blank group,Model group,Ustekin group,and Qingjie Hua-gong decoction group,with six mice in each group.The AP model was prepared by using rain frogin.Serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α lev-els were detected by ELISA;the pancreatic pathology was detected by HE staining;the expressions of PI3K,AKT,and NF-κB-related proteins and mRNAs were de-tected by immunohistochemistry,Western blot,and RT-qPCR.Results Compared with the blank group,the model group showed obvious pathological damage to the pancreas,with significantly higher serum α-AMS,PN-LP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels(P＜0.01),and significantly higher levels of PI3K,AKT,and NF-κB-related proteins and mRNA expression(P＜0.01).Compared with the model group,both the Qingjie Huagong decoction group and the ustekin group improved the histopathological changes in the pancreas of AP mice,decreased the serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels,and down-reg-ulated the expression levels of pancreatic PI3K,AKT,NF-κB-related proteins and mRNA(P＜0.05 or P＜0.01).Conclusion Qingjie Huagong decoction may inhibit the inflammatory response and protect pancreat-ic tissues by regulating the expression of PI3K/AKT/NF-κB signaling pathway.

With the rapid evolution of medical information technology, internet hospitals had become an integral part of China′s healthcare service system and could play a unique role in multidisciplinary diagnosis and treatment (MDT). In 2023, Nanjing Drum Tower Hospital built a smart service platform for MDT based on its internet hospital under the design concept of " global collaboration, process re-engineering, and smart empowerment", and officially launched in November of the same year. The platform included a five-tier architectur: user interaction, application services, data management, system integration and infrastructure, and embeds functional modules such as consultation management, an AI-assisted engine and a workflow engine. This platform covered Nanjing Drum Tower Hospital Group members, implemented an online-offline integrated, end-to-end workflow (pre-intra-post consultation). It realized the integration and utilization of high-quality medical resources across regions and institutions, and improved the quality and efficiency of MDT. As of December 2024, the platform had covered 30 specialties and completed 75 MDT consultations. The consultation cycle had been shortened from the traditional MDT mode of 14.2 days to 2.4 days, effectively reducing the number of patients traveling to and from the hospital. This platform had expanded the business scope of internet hospitals, improved the utilization rate of medical resources, and could provide references for other public hospitals in China to optimize the MDT service mode.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Aim To explore the therapeutic effect and mechanism of Qingjie Huagong decoction in modulating PI3K/AKT/NF-κB signaling pathway in inflammatory response of acute pancreatitis(AP)mice.Methods Twenty-four mice were randomly divided into Blank group,Model group,Ustekin group,and Qingjie Hua-gong decoction group,with six mice in each group.The AP model was prepared by using rain frogin.Serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α lev-els were detected by ELISA;the pancreatic pathology was detected by HE staining;the expressions of PI3K,AKT,and NF-κB-related proteins and mRNAs were de-tected by immunohistochemistry,Western blot,and RT-qPCR.Results Compared with the blank group,the model group showed obvious pathological damage to the pancreas,with significantly higher serum α-AMS,PN-LP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels(P＜0.01),and significantly higher levels of PI3K,AKT,and NF-κB-related proteins and mRNA expression(P＜0.01).Compared with the model group,both the Qingjie Huagong decoction group and the ustekin group improved the histopathological changes in the pancreas of AP mice,decreased the serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels,and down-reg-ulated the expression levels of pancreatic PI3K,AKT,NF-κB-related proteins and mRNA(P＜0.05 or P＜0.01).Conclusion Qingjie Huagong decoction may inhibit the inflammatory response and protect pancreat-ic tissues by regulating the expression of PI3K/AKT/NF-κB signaling pathway.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.