Objective To analyze chemical constituents of compound Maxing Shigan decoction by ultra-high perfor-mance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS). Methods The separation was performed on a UPLC BEH C₁₈ column (2.1 mm×100 mm, 2.5 µm)，with a gradient elution applying 0.1% aqueous formic acid solution and 0.1% formic acid acetonitrile as a mobile phase. The column temperature was 40 °C. The flow rate was 0.4 ml/min and the analysis time was 15 min. Mass spectrometry (MS) data were collected in both positive and negative ESI ion modes. Results Through UPLC-QTOF/MS analysis and reference validation, a total of 59 chemical components in Maxing Shigan decoction were identified. Conclusion An ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) method was established to identify the chemical components of Maxing Shigan decoction. This method is simple, efficient, sensitive and accurate, and provides a basis for the elucidation of the pharmacodynamic material basis and mechanism of Maxing Shigan decoction. It can provide data reference for the optimization of the compatibility of traditional Chinese medicine in the treatment of COVID-19.

BACKGROUND:Based on the principle of vertical tooth movement,a personalized orthodontic appliance is created through digital design combined with 3D printing,so that the personalized orthodontic appliance forms a support system with the individual incisors.With the help of the absolute support of the micro-implant,the single tooth is precisely controlled in a three-dimensional direction.OBJECTIVE:To design personalized orthodontic appliances with 11,12,21,and 22 intrusion and extrusion based on biomechanical principles,and analyze the safety of the personalized orthodontic appliances in terms of their movement effect on the teeth by means of the three-dimensional finite element method.METHODS:Three-dimensional finite element models of alveolar bone-periodontium-maxillary incisors-personalized cantilever micro-implant-connecting plates-personalized brackets in the maxillary anterior region(teeth numbers 11,12,21,and 22)were established using Mimics,Geomagic Wrap,SolidWorks,and Ansys Workbench software,respectively.Personalized orthodontic appliances with low pressure movement and extended movement were set up at each tooth position.The stress level of each component of the personalized orthodontic appliances was analyzed,and the tooth displacement and periodontal stress distribution were calculated under loading of 300 g tensile or thrust force.RESULTS AND CONCLUSION:(1)The maximum equivalent force on the personalized intrusion mobile orthodontic appliance was 162.90 MPa,and the maximum equivalent force on the personalized extrusion mobile orthodontic appliance was 239.57 MPa.The maximum equivalent stress on both devices was located in the vertical portion of the personalized bracket loading attachment.The equivalent stresses on each part of the personalized orthodontic appliance were all within the yield strength,and they had good safety.(2)The initial displacement of the teeth under the action of the personalized orthodontic appliances showed a tendency towards overall intrusion or extrusion,with the displacement in the vertical direction far exceeding that in the horizontal and sagittal directions.The equivalent stress peak appeared at the root tip or neck of the periodontal membrane,and the equivalent stress concentration area appeared in the periodontal membrane of the root apical region.(3)The results show that the personalized orthodontic appliance allows 11,12,21,and 22 to approximate either intrusion movement or extrusion movement,initially confirming the effectiveness of the personalized vertical movement orthodontic appliance.

Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.

BACKGROUND:Based on the principle of vertical tooth movement,a personalized orthodontic appliance is created through digital design combined with 3D printing,so that the personalized orthodontic appliance forms a support system with the individual incisors.With the help of the absolute support of the micro-implant,the single tooth is precisely controlled in a three-dimensional direction.OBJECTIVE:To design personalized orthodontic appliances with 11,12,21,and 22 intrusion and extrusion based on biomechanical principles,and analyze the safety of the personalized orthodontic appliances in terms of their movement effect on the teeth by means of the three-dimensional finite element method.METHODS:Three-dimensional finite element models of alveolar bone-periodontium-maxillary incisors-personalized cantilever micro-implant-connecting plates-personalized brackets in the maxillary anterior region(teeth numbers 11,12,21,and 22)were established using Mimics,Geomagic Wrap,SolidWorks,and Ansys Workbench software,respectively.Personalized orthodontic appliances with low pressure movement and extended movement were set up at each tooth position.The stress level of each component of the personalized orthodontic appliances was analyzed,and the tooth displacement and periodontal stress distribution were calculated under loading of 300 g tensile or thrust force.RESULTS AND CONCLUSION:(1)The maximum equivalent force on the personalized intrusion mobile orthodontic appliance was 162.90 MPa,and the maximum equivalent force on the personalized extrusion mobile orthodontic appliance was 239.57 MPa.The maximum equivalent stress on both devices was located in the vertical portion of the personalized bracket loading attachment.The equivalent stresses on each part of the personalized orthodontic appliance were all within the yield strength,and they had good safety.(2)The initial displacement of the teeth under the action of the personalized orthodontic appliances showed a tendency towards overall intrusion or extrusion,with the displacement in the vertical direction far exceeding that in the horizontal and sagittal directions.The equivalent stress peak appeared at the root tip or neck of the periodontal membrane,and the equivalent stress concentration area appeared in the periodontal membrane of the root apical region.(3)The results show that the personalized orthodontic appliance allows 11,12,21,and 22 to approximate either intrusion movement or extrusion movement,initially confirming the effectiveness of the personalized vertical movement orthodontic appliance.

Objective:To construct a general deep learning dose prediction model applicable to radiotherapy for head and neck tumors, establish design methods for artificial intelligence (AI)-assisted radiotherapy plan and evaluate the accuracy of prediction.Methods:Radiotherapy plans of 818 patients who received radiotherapy for head and neck cancers from January 2018 to June 2021 in Cancer Hospital of Chinese Academy of Medical Sciences were enrolled. Patients involved 17 types of common head and neck cancers, and the prescribed dose covered 5 kinds of dose gradients ranging from 54 Gy to 73.92 Gy. And 1-2 cases per each cancer type (31 cases in total) were randomly selected as the validation set, and the remaining 787 cases were used as the training set to build a deep learning head and neck radiotherapy generalized dose prediction model. Then based on the dose prediction results of this model, a program was written to automatically generate inverse optimization condition scripts, which were sent back to the treatment planning system to achieve AI-assisted radiotherapy plan design. Among the patients who received radiotherapy in our hospital from June 2021 to January 2022, 1 patient for each disease type (17 cases in total) was selected to evaluate the AI-assisted plan design program and evaluate its clinical feasibility using paired t-test. Results:Dose prediction model accuracy evaluation revealed that in the 31-case validation set, there was no statistical difference in the evaluation metrics of clinical concern for organs at risks, except for the D 1 cm3 prediction for spinal cord planning risk volume, which was statistically different compared with the clinical reference plan. The AI-assisted plan design program had higher plan quality metric scores (37.88±6.42) than manual plans (35.00±7.63) in 17 test cases ( t=-1.00, P=0.166). The number of manual adjustments to the inverse optimization conditions was reduced from (5.47±2.97) times to (2.76±1.00) times for the AI-assisted plan compared to the manual-only plan ( t=4.12, P<0.001). And the number of outlined dose shaping structures was reduced from 7.35±3.98 to 3.12±1.18 ( t=5.61, P<0.001). Conclusions:The unified universal model of dose prediction established for different head and neck cancers has high accuracy in dose prediction for all types of head and neck tumor plans. The AI-assisted planning method established in this pattern can reduce the clinical workload of physicists and improve the efficiency of their work.

Objective To utilize bioinformatic approaches to elucidate the correlation between secreted phosphoprotein 1(SPP1)and immune infiltration in various malignancies,elucidating the mechanism of gene function in cancer-immune cell interplay.Methods Cancer samples were derived from the Cancer Genome Atlas(TCGA)and Genotype-tissue Expression(GTEx)database,examining SPP1 expression difference between tumors and normal tissues using Gene Expression Profiling Interactive Analysis(GEPIA2),and its correlation with different immune cells in extracellular matrix via TIMER2 Database.SPP1's association with interacting molecules was scrutinized on the STRING website,followed by assessment of its distinct functional state across various cancers from Cancer Single-cell State Atlas Database(Cancer SEA).Results In 32 tumor types,SPP1 mRNA is significantly elevated in 23 types of cancers and correlates heavily with fibroblast,integrin family,and CD44.Furthermore,the SPP1 gene exhibits profound specificity in tumor functions such as vascular invasion,metastasis,DNA damage,and repair.Conclusion Specific expression of SPP1 in tumors signifies a significant correlation with tumor immune cells in the extracellular matrix,promoting tumor progression and invasion.This suggests that targeted monitoring of SPP1 could serve as a prospective cancer diagnostics/therapeutics biomarker.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To explore the effect of auto-segmentation based on deep learning(DL)and Atlas during online adaptive MRI-guided radiotherapy.Methods Totally 15 prostate cancer patients undergoing MRI-guided online adaptive radiotherapy at some hospital from January 2020 to September 2021 were selected and divided into a training set(12 cases)and a test set(3 cases)by random sampling method.With the training set data the models of clinical target volume(CTV)and organs at risk(OAR)by DL and Atlas segmentation were established,and with the test set data the two segmentation models were modified and the modification lengths were recorded.DL and Atlas segmentation methods were compared on segmentation efficiency and accuracy in terms of Dice similarity coefficient(DSC),Hausdorff distance(HD)and mean distance to agreement(MDA).A joint auto-segmentation scheme based on combined DL and Atlas was constructed with considerations on the advantages and characteristics of the two methods,which was compared with the schemes respectively based on DL or Atlas from the aspect of the time consumed for segmentation.Results Accuracy comparison showed Atlas segmentation model behaved better significantly than DL model for CTV(P＜0.05),while obviously worse than the latter for DSC and MDA in bladder and rectum(P＜0.05).The doctor took 9.4 min in average for CTV and OAR modification based on DL model and 12 min in average for Atlas-model-based modification.The joint auto-segmentation scheme only needed 8 min in average for CTV and OAR modification,which gained advantages over the schemes based on DL or Atlas.Conclusion The auto-segmentation based on combined DL and Atlas during online adaptive MRI-guided radiotherapy behaves well in low time consumption,high accuracy and efficiency.[Chinese Medical Equipment Journal,2024,45(6):59-64]

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0％ were gram-positive and 71.0％ were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6％,81.9％ and 78.5％,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9％ of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4％ of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1％ in the isolates from children and and 95.9％ in the isolates from adults.The resistance rate to carbapenems was lower than 15.0％ for most Enterobacterales species except for Klebsiella,22.5％ and 23.6％ of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6％ to 10.0％.The resistance rate to imipenem and meropenem was 21.9％ and 17.4％ for Pseudomonas aeruginosa,respectively,and 67.5％ and 68.1％ for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0％ were gram-positive and 71.0％ were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6％,81.9％ and 78.5％,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9％ of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4％ of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1％ in the isolates from children and and 95.9％ in the isolates from adults.The resistance rate to carbapenems was lower than 15.0％ for most Enterobacterales species except for Klebsiella,22.5％ and 23.6％ of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6％ to 10.0％.The resistance rate to imipenem and meropenem was 21.9％ and 17.4％ for Pseudomonas aeruginosa,respectively,and 67.5％ and 68.1％ for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.