Plant natural products have a wide range of pharmacological properties, not only can they be used as plant dietary supplements to meet the nutritional needs of the human body in the accelerated pace of life, but also occupy an important position in the research and development of therapeutic drugs for the treatment of tumors, inflammation and other diseases, and have been widely accepted by the public due to their good safety. However, despite the above advantages of plant natural products, limiting factors such as low solubility, poor stability, lack of targeting, high toxicity and side effects, and unacceptable odor have greatly impeded their conversion to clinical applications. Therefore, the development of new avenues for the application of new natural products has become an urgent problem to be solved at present. In recent years, with the continuous development of research, various strategies have been developed to improve the bioavailability of natural products. Among them, nanocarrier delivery system is one of the most attractive strategies at present. In past studies, a large number of nanomaterials (organic, inorganic, etc.) have been developed to encapsulate plant-derived natural products for their efficient delivery to specific organs and cells. Up to now, nanotechnology has not only been limited to pharmaceutical applications, but is also competing in the fields of nanofood processing technology and nanoemulsions. Among the various nanocarriers, liposomes are the largest nanocarriers with the largest market share at present. Liposomes are bilayer nanovesicles synthesized from amphiphilic substances, which have advantages such as high drug loading capacity and stability. Attractively, the flexible surface of liposomes can be modified with various functional elements. Functionalized modification of liposomes with different functional elements such as antibodies, nucleic acids, peptides, and stimuli-responsive moieties can bring out the excellent drug delivery function of liposomes to a greater extent. For example, the modification of functional elements with targeting function such as nucleic acids and antibodies on the surface of liposomes can deliver natural products to the target location and improve the bioavailability of drugs; the modification of stimulus-responsive groups such as photosensitizers, magnetic nanoparticles, pH-responsive groups, and temperature sensitizers on the surface of liposomes can achieve controlled release of drugs, localized targeting, and synergistic thermotherapy. In addition to the above properties, by using functionalized liposomes to encapsulate natural products with irritating properties can also effectively mask the irritating properties of natural products, improve public acceptance, and increase the possibility of application of irritating natural products. There are various strategies for modifying liposomes with functional elements, and the properties of functionalized liposomes constructed by different construction strategies differ. The commonly used construction strategies for functionalized liposomes include covalent modification and non-covalent modification. These two types of construction strategies have their own advantages and disadvantages. Covalent modification has better stability than non-covalent modification, but its operation is cumbersome. With the above background, this review focuses on the three typical problems faced by plant natural products at present, and summarizes the specific applications of functionalized liposomes in them. In addition, this paper summarizes the construction strategies for building different types of functionalized liposomes. Finally, this paper will also review the opportunities and challenges faced by functionalized liposomes to enter clinical therapy, and explore the opportunities to overcome these problems, with a view to better realizing the precise control of plant nanomedicines, and providing ideas and inspirations for researchers in related fields as well as relevant industrial staff.

As a novel tumor treatment,photodynamic therapy(PDT)has been widely used in clinical treatment of a variety of tumors due to its advantages,such as fewer adverse reactions,precise targeting and repeatability of treatment.Unlike conventional treatments,such as surgery,chemotherapy and radiotherapy,PDT not only eliminates the primary tumor but also effectively inhibits metastatic tumors by activating the body's immune response.However,the PDT-activated immune response is influenced by multiple factors,including the localization and dose of photosensitizer in the cells,light parameters,oxygen concentration in the tumor,and the integrity of immune function.This review summarizes the mechanisms behind the PDT-activated anti-tumor immune response,systematically examines the key influencing factors on the immune effect of PDT,and discusses the future development direction of PDT in cancer treatment.

Objective To investigate disease characteristics and hospitalization costs of children with Mycoplasma Pneumoniae pneumonia(MPP)admitted to Shanghai municipal medical hospitals from 2019 to 2023.Methods Depending on the Shanghai Municipal Hospital Pediatric Alliance,we retrospectively investigated community acquired MPP pediatric patients hospitalized in 22 municipal hospitals with pediatric qualifications(including 4 children's hospitals)in Shanghai from Jan 2019 to Dec 2023.We collected the patients'diagnosis codes,gender,age,length of hospital stay,hospitalization costs,and whether they progressed to severe Mycoplasma pneumoniae pneumonia(SMPP).Results From 2019 to 2023,a total of 29 045 hospitalized children with MPP were treated,with 6 035 cases(20.8%)identified as SMPP in the 22 hospitals.Trend analysis revealed a rising trend with years in the proportion of SMPP patients(χ2trend=365.498,P<0.001).Among the 4 children's hospitals,there were 18 710 cases with MPP,including 4 078 cases(21.8%)of SMPP.The proportion of SMPP patients also showed an increasing trend with years(χ2trend=14.548,P<0.001),and the proportion in 2023(23.0%)was higher than that in previous years with statistical significance.There were statistical differences in the seasonal distribution of MPP cases between different years,with higher proportions in summer and autumn overall.The age distribution of hospitalized MPP children varied among different years,with school-age children accounting for the majority(56.8%)in 2023.There was no difference in the distribution of severe cases between different genders,but there were differences in the proportion of severe cases among different age groups in different years,with a gradual increase in severe cases among children aged 1 to 3 years(χ2trend=191.567,P<0.001).The average length of hospital stay for MPP during the epidemic was higher than that during non-epidemic periods,and there were statistically significant differences in the average length of hospital stay between different years(P<0.001).The individual hospitalization costs during the epidemic were higher than in other years,and there were statistically significant differences in individual hospitalization costs between different years(P<0.001).The total hospitalization costs were still higher in 2019 and 2023.The individual hospitalization costs for SMPP were higher than for non-SMPP cases.Conclusion MPP outbreaks occurred in Shanghai in 2019 and 2023,with the higher proportions in summer and autumn overall.Compared to previous years,the number of hospitalized MPP children in Shanghai was higher in 2023,with a higher proportion of SMPP cases,especially among children under 3 years old.The individual per capita hospitalization expenses for SMPP cases were higher than for non-SMPP cases.

Osteoporosis is an important cause of internal fixation loosening after spinal surgery.Cement-augmented pedicle screw instru-mentation(CAPSI)technique is the most widely used technique in clinical practice to improve the stability of pedicle screw,mainly applied in osteoporosis and revision surgery,which included conventional solid pedicles crews and fenestrated/cannulated pedicle screws technique.CAPSI technique may cause cement leakage and pulmonary embolism,and there is no consensus on its indications or technical points.Therefore,this article reviews the research progress of CAPSI,in order to provide relevant reference for clinical practice.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.

Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5％in all clinical isolates amd 5.7％in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7％(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)％,followed by secretions/pus(16.4±2.3)％and urine(16.0±0.9)％.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9％),and only(7.1±0.8)％of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)％compared to the inpatients in any other departement.Overall,≤ 7.9％of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6％of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7％vs 3.9％).Overall,≤8.1％of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5％of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0％over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.