During orthodontic treatment, clinical monitoring of patients is a crucial factor in determining treatment success. It aids in timely problem detection and resolution, ensuring adherence to the intended treatment plan. In recent years, digital technology has increasingly permeated orthodontic clinical diagnosis and treatment, facilitating clinical decision-making, treatment planning, and follow-up monitoring. This review summarizes recent advancements in digital technology for monitoring orthodontic tooth movement, related complications, and appliance-wearing compliance. It aims to provide insights for researchers and clinicians to enhance the application of digital technology in orthodontics, improve treatment outcomes, and optimize patient experience. The digitization of diagnostic data and the visualization of dental models make chair-side follow-up monitoring more convenient, accurate, and efficient. At the same time, the emergence of remote monitoring technology allows orthodontists to promptly identify oral health issues in patients and take corresponding measures. Furthermore, the multimodal data fusion method offers valuable insights into the monitoring of the root-alveolar relationship. Artificial intelligence technology has made initial strides in automating the identification of orthodontic tooth movement, associated complications, and patient compliance evaluation. Sensors are effective tools for monitoring patient adherence and providing data-driven support for clinical decision-making. The application of digital technology in orthodontic monitoring holds great promise. However, challenges like technical bottlenecks, ethical considerations, and patient acceptance remain.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

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.

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 investigate the clinical characteristics of preoperative intestinal symptoms in patients with bowel endometriosis and to compare the effects of shaving versus segmental bowel resection on postoperative intestinal function.Methods A total of 105 patients diagnosed with bowel endometriosis and treated by the same surgical team at the Obstetrics and Gynecology Hospital,Fudan University between Aug 1,2013 and Dec 30,2017 were prospectively enrolled in this study.Clinical data were collected via outpatient visits and telephone follow-ups at four time points:preoperative(T0)and postoperative(T1:Nov 2018;T2:Nov 2020;T3:Apr 2024).The primary outcome was bowel symptoms and gastrointestinal function scores;secondary outcome was pain scores.A generalized estimating equation(GEE)model was used to analyze the interaction effect of surgical approach and follow-up time on outcomes.Results Ultimately,a total of 89 patients were included(15.24%loss to follow-up),among whom 79 patients(88.76%)underwent shaving excision.Preoperatively,46 patients(51.68%)presented with bowel symptoms,primarily anus bulge(21 cases,46.65%)and diarrhea(15 cases,32.61%)during menstruation.Postoperatively,there was a significant increase in constipation rates(T1:71.43%;T2:50.00%;T3:72.00%).Both surgical groups exhibited significant improvements in dysmenorrhea,gastrointestinal discomfort scores as well as gastrointestinal quality of life index(P<0.000 5).However,the segmental resection group had significantly higher scores for low anterior resection syndrome,constipation compared with the shaving excision group(P=0.02 and P=0.05).Conclusion Approximately half of the patients with bowel endometriosis exhibit typical bowel symptoms preoperatively,such as anus bulge and diarrhea.Both shaving excision and segmental resection effectively alleviate pain;however,shaving excision demonstrates an advantage regarding preservation of bowel function,whereas segmental resection may elevate risks associated with postoperative constipation or altered defecation patterns due to structural changes.The selection of surgical approach should carefully balance lesion removal and functional preservation,moreover,be sure that potential risks are thoroughly informed to patients prior to surgery.

The major components of Olaflur raw material were characterized using ultra performance liquid chromatography-quadrupole time-of-flight-mass spectrometry(UPLC-Q-TOF/MS).The results revealed that cetyl amine fluoride(C16-AmF),octadecene amine fluoride(C18:1-AmF),and octadecyl amine fluoride(Olaflur)were the main components.The contents of C16-AmF,C18:1-AmF,and Olaflur in oral care products were determined via ultra performance liquid chromatography-charged aerosol detector coupled with solid-phase extraction(SPE-UPLC-CAD).The oral care sample was dispersed evenly with a 50%ethanol aqueous solution,and then vortexed with ethanol.The supernatant was collected by centrifugation,concentrated to near dryness,and redissolved with ultrapure water.The re-dissolved sample was loaded onto a Poly-Sery HLB Pro SPE column for purification and elution.The acetonitrile eluate was collected and concentrated to 1.0 mL.Finally,a prepared test solution was separated on a Thermo Acclaim Surfactant Plus chromatographic column(2.1 mm×150 mm,3 μm).Acetonitrile and 100 mmol/L acetic acid-ammonium acetate aqueous solution(pH=4.8)were used as the mobile phases for gradient elution.The flow rate was 0.3 mL/min and cloumn temperature was maintained at 40℃.The sample was detected using a charged aerosol detector,and quantified using an external standard method.The experimental results indicated that the three organic fluorinated amines showed good linear relationship in their respective concentration ranges.The correlation coefficients(r)were greater than 0.99.The limit of detection(LOD)and the limit of quantification(LOQ)of C16-AmF were 2.0 and 8.0 μg/mL,respectively.The LOD and LOQ of C18:1-AmF were 2.0 and 8.0 μg/mL,respectively.The LOD and LOQ of Olaflur were 3.0 μg/mL and 10.0 μg/mL,respectively.The spiked recoveries of the three organic fluorinated amines were 84.3%-104.2%,with relative standard deviations(RSDs)of 4.93%-5.82%.The 28 batches of commercial oral care samples were detected by this method and the results indicated that three organic fluorinated amines were detected in 18 samples and the total content were 22.2-11477.8 μg/g.This method had high sensitivity and good reproducibility.It was suitable for verifying the authenticity of the claims of oral care products promoted with Olaflur as the main efficacy ingredient and selling point,and provided a valuable reference for establishing and improving the standard analytical method for Olaflur.

AIM To establish the preparation process and quality standard for Zhenggu Pills.METHODS With decoction time,decoction frequency and water addition as influencing factors,comprehensive score for extract yield and transfer rates of epicatechin and naringin as an evaluation index,the decoction process was optimized by orthogonal test.With sugarless paste relative density,medicinal powder fineness,sugarless paste-corn starch ratio,drying temperature and drying time as influencing factors,soft material traits,pill formability,moisture and disintegration time limit as evaluation indices,the formability process was optimized by single factor test.TLC was adopted in the qualitative identification of Dipsaci Radix,salt-processed Psoraleae Fructus,cooked Rhei Radix et Rhizoma and Notoginseng Radix et Rhizoma.HPLC was used for the content determination of paeoniflorin and naringin.RESULTS The optimal decoction process was determined to be 0.5 h for decoction time,two times for decoction frequency,and 10 times for water addition,the comprehensive score was 0.93.The optimal formability process was determined to be 1.21-1.22 for sugarless paste relative density,80 mesh for medicinal powder fineness,1∶0.17-1∶0.18 for sugarless paste-corn starch ratio,70 ℃ for drying temperature,and 24 h for drying time,good soft material traits and pill formability were observable,and moisture and disintegration time limit accored with 2020 edition of Chinese Pharmacopoeia requirements.The TLC spots were clear without negative interference.Two constituents showed good linear relationships within 61.30-490.41 μg/mL(r=0.999 8)and 3.27-26.18 μg/mL(r=0.999 8),whose average recoveries were 100.15％and 98.15％with the RSDs of 0.55％and 2.30％,respectively.CONCLUSION This stable,reliable and specific method can be used for the production and quality evaluation of Zhenggu Pills.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.