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 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.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

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.

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 explore the feasibility and advantages of applying visualized thermosensitive color-changing bolus in postmastectomy radiotherapy (PMRT) for breast cancer.Methods:Forty patients with breast cancer treated with PMRT in the Second Affiliated Hospital of Soochow University from June 2023 to June 2024 were prospectively selected. They were randomly divided into test and control groups (also referred to as groups A and B, respectively), with 20 patients in each group. Group A, underwent two CT scans: the first scan without bolus (image A1) and the second scan with visualized thermosensitive color-changing bolus (image A2). They were treated with visualized thermosensitive color-changing bolus. Group B also underwent two CT scans: the first scan without bolus (image B1) and the second scan with conventional commercial bolus (image B2), and then were treated with conventional commercial bolus. In the radiotherapy planning, images A1 and A2 were designed as A1-Plan and A2-Plan, and A3-Plan was created by transferring the A1-Plan onto image A2. Images B1 and B2 were designed as B1-Plan and B2-Plan, and B3-Plan was created by transferring the B1-Plan onto image B2. The radiation fields and target optimization functions were identical. The dosimetric differences and skin toxicity reactions between different plans were compared.Results:In Group A, A1-Plan and A2-Plan manifested no statistically significant differences ( P > 0.05) in the doses to organs at risk (OARs), including the ipsilateral lung ( V5 Gy, V10 Gy, V20 Gy), heart ( Dmean), contralateral breast ( Dmean), and skin ( Dmax and Dmean), target homogeneity index (HI), conformity index (CI), prescription dose volume ( V50 Gy), depth of maximum dose ( Dmax), and monitor unit (MU). In Group B, B3-Plan compared to B1-Plan showed reduced V50 Gy (89.9% vs. 95%), HI (0.153 vs. 0.136), and CI (0.817 vs. 0.810), while the two plans displayed no statistically significant differences in doses to OARs. In contrast, A3-Plan and B3-Plan exhibited statistically significant differences ( t = 2.78, 2.29, -0.47, 0.51, 3.13, P < 0.05) in V50 Gy (94.05% vs. 89.90%), Dmax (5 665.4 cGy vs. 5 632.7 cGy), HI (0.148 vs. 0.163), CI (0.83 vs. 0.82), and skin Dmean (5 153.6 cGy vs. 5 048.2 cGy). Compared to the conventional commercial bolus of the same thickness, the visualized thermosensitive color-changing bolus yielded a significantly reduced air cavity volume (3 833 mm 3vs. 21 498 mm 3,t = -9.65, P < 0.05). Both groups experienced only grade I skin toxicity reactions. Conclusions:Compared to the conventional commercial bolus of the same thickness, the visualized thermosensitive color-changing bolus shows a more effective dosimetric distribution in terms of target coverage, HI, and CI, a higher fit to the skin, highly visualized air cavity, and higher positional repeatability in fractionated radiotherapy, demonstrating high practicality and safety.

Immunotherapy has emerged as a revolutionary approach to treat immune-related diseases. Dendritic cells (DCs) play a pivotal role in orchestrating immune responses, making them an attractive target for immunotherapeutic interventions. Modulation of gene expression in DCs using genome editing techniques, such as the CRISPR-Cas system, is important for regulating DC functions. However, the precise delivery of CRISPR-based therapies to DCs has posed a significant challenge. While lipid nanoparticles (LNPs) have been extensively studied for gene editing in tumor cells, their potential application in DCs has remained relatively unexplored. This study investigates the important role of cholesterol in regulating the efficiency of BAMEA-O16B lipid-assisted nanoparticles (BLANs) as carriers of CRISPR/Cas9 for gene editing in DCs. Remarkably, BLANs with low cholesterol density exhibit exceptional mRNA uptake, improved endosomal escape, and efficient single-guide RNA release capabilities. Administration of BLAN_mCas9/gPD-L1 results in substantial PD-L1 gene knockout in conventional dendritic cells (cDCs), accompanied by heightened cDC1 activation, T cell stimulation, and significant suppression of tumor growth. The study underscores the pivotal role of cholesterol density within LNPs, revealing potent influence on gene editing efficacy within DCs. This strategy holds immense promise for the field of cancer immunotherapy, offering a novel avenue for treating immune-related diseases.