Background: Xiaochaihu capsules are a widely used traditional Chinese patent medicine. The extraction process, a critical step in their production, necessitates online monitoring to determine the levels of key indicators, thereby informing subsequent processing stages. Objective: The objective of this study was to establish online quantitative models for 6 key indicators (solid content, liquiritin, baicalin, wogonoside, glycyrrhizic acid, and saikosaponin B ) during the extraction process of Xiaochaihu capsules. This approach aims to provide a technical foundation for enhanced process control and to serve as a methodological reference for the application of multisource information fusion in monitoring the extraction of multi-herb traditional Chinese medicine formulations. Methods: Online quantitative models were developed based on multiple sensors, ultraviolet-visible spectroscopy (UV-Vis), and near-infrared spectroscopy (NIR) to monitor 6 indicators during the extraction process of Xiaochaihu capsules. Different preprocessing methods for spectroscopic data were optimized, and data fusion strategies were integrated to improve the predictive performance of the online quantitative models. Results: The optimal modeling strategies for the 6 indicators were as follows: for solid content, a second-order polynomial model was established using the measurement results from 2 sensors (pH and conductivity), with a predictive coefficient of determination (R ) of 0.9821. For baicalin, the optimal model was developed using UV-Vis spectra pretreated with the first derivative (1stD), achieving a predictive R of 0.9841. For wogonoside, modeling was also conducted after 1stD preprocessing of the UV-Vis spectra, yielding a predictive R of 0.9929. For liquiritin, a high-level fusion strategy combining UV-based feature extraction via the random frog (RF) algorithm and NIR-based feature extraction via competitive adaptive reweighted sampling (CARS) was used, achieving an R of 0.9406 in the validation set. For glycyrrhizic acid, the optimal approach involved a combination of UV-CARS feature extraction and NIR-RF feature extraction, coupled with high-level data fusion, resulting in an R of 0.9859 in the validation set. For saikosaponin B , the optimal scheme utilized UV-RF feature extraction combined with NIR-CARS feature extraction and high-level fusion (R = 0.7702 in the validation set). Conclusion: The integration of process analytical technologies and data fusion strategies enabled the successful establishment of online quantitative models for 6 indicators during the extraction process of Xiaochaihu capsules. Overall, the established online quantitative models effectively captured and reflected the dynamic changes of these indicators throughout the extraction process.

The antidepressant activity and molecular mechanisms of Yueju Wan volatile oil were investigated. The Yueju Wan volatile oil was extracted by using supercritical CO_2. Gas chromatography-mass spectrometry(GC-MS) combined with network pharmacology identified 28 chemical constituents in Yueju Wan volatile oil, primarily terpenes and lactones. A total of 123 overlapping targets were associated with depression, including core targets of interleukin-1β(IL-1β), signal transducer and activator of transcription 3(STAT3), and caspase-3(CASP3). These targets were mainly involved in the prolactin, advanced glycation end products/receptor(AGE/RAGE), and phosphoinositide 3-kinase/protein kinase B(PI3K/Akt) signaling pathways. A reserpine-induced depression mouse model was established to evaluate the therapeutic effects and mechanisms of Yueju Wan volatile oil. The effects of Yueju Wan volatile oil on depression-like behavior in mice were evaluated by analyzing body mass, body temperature index, tail suspension immobility time, forced swimming immobility time, and sucrose preference. Hematoxylin-eosin(HE) staining revealed neuronal protection of Yueju Wan volatile oil in the brain of mice. Enzyme-linked immunosorbent assay(ELISA) and Western blot were employed to detect the protein expression of AGEs, IL-1β, phosphorylated PI3K(p-PI3K), Akt, phosphorylated Akt(p-Akt), nuclear factor κB(NF-κB), and brain-derived neurotrophic factor(BDNF). Behavioral evaluation showed that Yueju Wan volatile oil could effectively control the decline of body mass and body temperature of depressed mice, reduce tail suspension and swimming immobility time, and enhance their preference for sucrose. Histopathological examination showed that Yueju Wan volatile oil could alleviate the neuronal damage in CA1 and dentate gyrus(DG) of the hippocampus of mice. ELISA and Western blot results showed that Yueju Wan volatile oil could significantly increase the protein expression levels of PI3K, Akt, and BDNF and significantly decrease the protein expression levels of AGEs, IL-1β, p-PI3K, p-Akt, and NF-κB in the hippocampus of mice. Furthermore, the p-PI3K/PI3K and p-Akt/Akt ratios were significantly decreased at medium and high doses. These findings suggest that the aromatherapy of Yueju Wan volatile oil can significantly improve reserpine-induced depression-like behavior in mice, which may be related to reducing the expression of neuronal membrane protein AGEs, reducing the phosphorylation levels of PI3K and Akt, inhibiting NF-κB entry into the nucleus, and alleviating the release of pro-inflammatory factors and nerve injury.
Animals ; Antidepressive Agents/chemistry* ; Mice ; Proto-Oncogene Proteins c-akt/immunology* ; Phosphatidylinositol 3-Kinases/immunology* ; Oils, Volatile/chemistry* ; Male ; Drugs, Chinese Herbal/chemistry* ; Signal Transduction/drug effects* ; Depression/metabolism* ; Glycation End Products, Advanced/immunology* ; Humans

The extraction process of traditional Chinese medicine(TCM) is an important part in the production and processing of TCM products. The modeling of this process is of great significance for achieving intelligent production. This paper summarizes the modeling methods for the extraction process of TCM, which mainly include mechanism modeling, empirical formula modeling, data-driven modeling, and mixed modeling. Among them, mechanism modeling and data-driven modeling are widely used. Furthermore, this paper suggests that the future research on the modeling of the extraction process of TCM can be carried out from the following five aspects: in-depth research and development of the extraction process of TCM compound prescriptions, complete description of the whole extraction process of TCM, development of methods for accurate determination of the properties of TCM decoction pieces before extraction, development of adaptive self-optimization technology for models, and construction of models based on a new generation of artificial intelligence methods.
Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/methods* ; Models, Theoretical ; Artificial Intelligence ; Humans

OBJECTIVE: To explore clinical efficacy of membrane-induced technique combined with gastrocnemius muscle flap transposition in treating traumatic osteomyelitis of the upper tibia. METHODS: A retrospective analysis was conducted on 7 patients with traumatic osteomyelitis of the upper tibia who were treated with membrane-induced technique combined with gastrocnemius muscle flap transposition from January 2022 to December 2023. Among them, there were 4 males and 3 females; aged from 29 to 57 years old; 4 patients were treated after open fracture, 2 patients were treated after closed fracture, and 1 patient was treated after scalding; the courses of disease ranges from 2 weeks to 8 years; sinus tracts were present in all patients, and the lesion range of the tibia ranged from 5 to 9 cm. The results of deep tissue bacterial culture showed that 2 patients were negative, 3 patients were staphylococcus aureus, 1 patient was methicillin-resistant staphylococcus aureus, and 1 patient was pseudomonas aeruginosa and 1 patient was klebsiella pneumoniae. After debridement, the range of bone defect ranged from 8 to 12 cm, and the cortical defect accounted for approximately 30% of the circumference. The area of soft tissue defect ranged from 8.0 cm×2.0 cm to 10.0 cm×6.0 cm. At the first stage, vancomycin-loaded/meropenem/gentamicin-loaded bone cement was implanted. The gastrocnemius muscle flap was repositioned to cover the wound surface and free skin grafting was performed. After an interval of 7 to 10 weeks, the stageⅡsurgery was performed to remove bone cement. Autologous iliac bone mixed with vancomycin/gentamicin and calcium sulfate artificial bone was transplanted, and the wound was sutured. One patient retained the original internal plants, one patient removed the internal plants and replaced them with steel plate external fixation, one patient replaced the internal plants and added steel plate external fixation, and three patients were simply fixed with steel plate external fixation. One year after operation, the recovery of knee joint and ankle joint functions was evaluated by using Hospital for Special Surgery (HSS) knee joint score and Kofoed ankle joint function score respectively. RESULTS: All patients had their wounds closed simultaneously with bone cement implantation and healed well. All patients were followed up for 12 to 17 months after operation, and satisfactory bone healing was achieved at 6 months after stageⅡsurgery. Twelve months after operation, all patients had good bone healing without obvious limping was observed when walking. At 12 months after operation HSS knee joint score ranged from 93 to 100 points, and Kofoed ankle function score ranged from 96 to 100 points. CONCLUSION For traumatic osteomyelitis of the upper tibia, a staged treatment plan combining membrane-induced technique and gastrocnemius flap transposition on the basis of thorough debridement could safely cover the wound surface, effectively control bone infection and achieve satisfactory bone healing, without adverse effects on limb function.
Humans ; Male ; Female ; Middle Aged ; Osteomyelitis/surgery* ; Adult ; Surgical Flaps ; Retrospective Studies ; Tibia/injuries* ; Muscle, Skeletal/surgery*

Objective To analyze the changes of intestinal microbiota in patients with nonalcoholic fatty liver disease(NAFLD)and healthy controls so as to explore the relationship between intestinal microbiota and NAFLD.Methods A total of 353 samples from the National Center for Biotechnology Information were included,including 110 healthy controls and 243 NAFLD patients(127 NASH and 116 NAFLD).Macrogenome sequencing data were extracted to obtain data on intergroup flora diversity changes and analyze the potential correlation between alterations in gut microbes and NAFLD.Results Alpha diversity analysis showed no significant differences in Invsimpson index(P=0.57)or Simpson index(P=0.57)between NAFLD patients and healthy controls,while there was a trend of decreasing Shannon index(P=0.084),but with no significant difference.β-diversity analysis showed significant differences between the two groups(P=0.002).Species composition analysis showed that at the genus level,NAFLD patients and healthy controls had the same species types,with Bacteroidetes and Firmicutes being the dominant phyla in both groups.However,compared to Control group,NAFLD group had significantly lower Firmicutes,Synergistetes,and Candidatus_Melainabacteria.At the species level,there were significant differences between NAFLD group and Control group for 10 bacterial species,including Bacteroides_uniformis and Faecalbacterium_prausnitzil.Intergroup difference analysis showed that Phocaeicola dorei,Parabacteroides_distasonis,Bilophila_wadsworthia,and Dysosmobacter_welbionis were significantly enriched in NAFLD patients(LDA score＞2.0,P＜0.05),while Prevotella_stercorea,Faecalibacterium prausnitzii,and others were negatively associated with NAFLD.A disease detection model was constructed based on metagenomic data,and 26 intestinal microorganisms related to NAFLD were selected,including Pyramidobacter piscolens and Citrobacter freundii,etc.The diagnostic accuracy of NAFLD was judged by ROC curve discriminant model,and the AUC of the ROC curve was 0.743 8,indicating that the model has a certain accuracy in diagnosing NAFLD.Conclusion This study revealed differences in gut microbial diversity between NAFLD patients and healthy controls and identified key bacterial groups associated with NAFLD.In addition,the disease detection model constructed based on metagenomic data provides a new method and idea for the diagnosis of NAFLD,which is conducive to further study of the disease and the early diagnosis and treatment of clinical patients.

In the past 50 years,Jiashan County had leveraged the platform of Zhejiang University and relied on its independent cancer prevention and treatment institute to vigorously carry out co-lorectal cancer prevention and control work,which made remarkable results and becoming a na-tional model for county-level cancer prevention and control.The paper summarized the develop-ment history of Jiashan Institute of Cancer Prevention and Treatment,the process of colorectal cancer prevention and treatment,the establishment and main results of tumor registry and three-level cancer prevention system,and looked forward to the future cancer prevention and control work in Jiashan County.

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.

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.