INTRODUCTION: Antimicrobial resistance (AMR) poses a critical global health threat, with millions of deaths attributed to it annually. Antibiotic stewardship to combat AMR is the responsibility of all healthcare professionals. Despite evidence suggesting that it is unnecessary, dentists routinely prescribe prophylactic antibiotics following third molar (3M) surgeries. METHOD: This mixed-methods study examined the behavioural barriers influencing antibiotic prescribing practices within the Division of Oral and Maxillofacial Surgery at the National University Centre for Oral Health Singapore. This study used the capability, opportunity and motivation for behavioural change or COM-B framework to implement interventions targeting the behavioural barriers. RESULTS: Pre- and post-intervention data over 6 months showed a significant reduction in antibiotic prescriptions from 84.45% to 20.89%, following the implementation of COM-B strategies (P<0.001). Qualitative feedback from focus group discussions highlighted a positive shift in clinicians' attitudes towards antibiotic reduction, acknowledging the minimal infection risk associated with non-prescribing practices. Notably, complication rates remained stable throughout the study period, indicating no adverse effects from reduced antibiotic usage. CONCLUSION These findings demonstrated that the COM-B model can be successfully applied to modify deeply ingrained prescription habits, and underscored the effectiveness of a structured behavioural change intervention in enhancing compliance with antibiotic stewardship guidelines. The study advocates continuation of initiatives to sustain this positive trend and mitigate AMR in clinical practice.
Humans ; Molar, Third/surgery* ; Anti-Bacterial Agents/therapeutic use* ; Singapore ; Antimicrobial Stewardship/methods* ; Practice Patterns, Dentists'/statistics & numerical data* ; Antibiotic Prophylaxis ; Female ; Attitude of Health Personnel ; Male ; Tooth Extraction ; Adult ; Focus Groups ; Practice Patterns, Physicians'

Objective To investigate the improvement effects of homogeneous fecal microbiota transplantation(FMT)on chemotherapy-induced diarrhea(CID)in mice.Methods Fifteen C57BL/6N mice were divided into control group,CID model group and CID+FMT group according to the random number distribution and remainder grouping method,with 5 mice per group.Control group received no intervention,and their feces were used to prepare fecal bacteria suspension.CID model group was injected intraperitoneally with fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,followed by gavage with 0.1 ml of saline on alternate days.CID+FMT group was given 0.1 ml fecal bacteria suspension gavage on alternate days for one week,followed by intraperitoneal injection of fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,with the experiment ending on the 14th day.During the experiment,the mice's food intake and body weight were recorded.At the end of the experiment,the mice were euthanized with deep carbon dioxide anesthesia,and the mice colonic specimens from cecum to anus were collected for hematoxylin and eosin(HE)staining and histopathological examination.Fecal samples were collected for 16S rRNA gene sequencing.Shannon index,Simpson index and Chao1 algorithm were used to analyze the α-diversity species of the intestinal flora in each group of mice.Similarity analysis(Anosim)was used to perform non-parametric on the inter-group differences of intestinal flora among the mice.Linear discriminate analysis size effect(LEfSe)and nonmetric multidimensional scaling(NMDS)were employed to analyze the intestinal dominant flora and the similarity classification relationships in each group of mice.Results The colonic specimen's length from cecum to anus in CID model group was significantly shorter than that in control group(P<0.05),while there was no significant difference between CID+FMT group and CID model group(P>0.05).The weight of mice in CID model group decreased by 42.04%,while control group mice gained 10.24%,with a significant difference between the two groups(P<0.05).The weight of mice in CID+FMT group decreased by 8.12%,which was significantly improved compared to CID model group(P<0.05).HE staining results revealed the intestinal mucosal structure in CID model group was severely damaged,with atrophy and deformation,accompanied by inflammatory cell infiltration,and the pathological score was higher than that of control group(P<0.05).Compared with CID model group,the intestinal mucosal integrity and crypt cells in the CID+FMT group were improved,with less damage,and the pathological score was lower than that of CID model group,but the difference was not statistically significant(P>0.05).The α-diversity analysis showed that there were significant differences in the Shannon,Simpson and Chao1 indices among the three groups(P<0.05).ANOSIM and NMDS analysis revealed that the intestinal flora in CID+FMT group was closer to the normal intestinal flora compared to CID model group.LEfSe analysis showed that the intestinal flora in CID model group was enriched in famliy_Bacteroidaceae,and the intestinal flora in CID+FMT group was similar to that of control group,with an enrichenment of familiy_Enterobacteriaceae.Conclusion Homogeneous FMT can improve the abundance of intestinal flora in CID mice,making it more similar to normal intestinal flora,thereby protecting intestinal mucosa,reducing damage and alleviating the severity of CID.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.

Objective To explore the clinical and genetic characteristics of children with holocarboxylase synthetase(HLCS)deficiency.Methods A retrospective analysis was conducted on the clinical data of 3 children with HLCS deficiency who were admitted to Children's Hospital Affiliated to Zhengzhou University from December 2014 to January 2024.Relevant literature indexed in CNKI,Wanfang Data,PubMed and other databases was reviewed to summarize the clinical characteristics and HLCS gene mutations of children with HLCS deficiency.Results All 3 children were male,with onset age of 4-6 months.The main clinical manifestations included shortness of breath,vomiting,diarrhea,and poor mental state,and partial cases were complicated by growth retardation and neurological symptoms.Laboratory tests showed metabolic acidosis in all cases,blood amino acid and acylcarnitine profiles as well as urinary organic acid analysis suggested multiple carboxylase deficiency.Genetic testing revealed compound heterozygous mutation in the HLCS gene of all 3 children,among which the c.1892delT(p.L631X)mutation was previously unreported.According to the guidelines of the American College of Medical Genetics and Genomics(ACMG),the c.1892delT(p.L631X)mutation was rated as pathogenic mutation(PVS1+PM2_supporting+PM3).Biotin supplementation was effective in all cases.Literature review included 27 English literatures and 29 Chinese literatures,reporting a total of 133 children with HLCS deficiency caused by HLCS gene mutation.Common clinical manifestations included metabolic acidosis,skin lesions,vomiting,feeding difficulties,dyspnea,diarrhea,and neurological symptoms,etc.Conclusions Blood amino acid and acylcarnitine profiles,urine organic acid analysis,and gene testing are helpful for the diagnosis of HLCS deficiency.Timely biotin supplementation leads to a good prognosis.The mutation of HLCS gene is considered as the genetic etiology of HLCS deficiency in 3 children,among which the c.1892delT(p.L631X)mutation is a newly discovered mutation.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

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 develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

This study established a droplet digital PCR(ddPCR)EvaGreen assay and probe methods for Schistosoma japonicum detection,and evaluated their application in detecting early infections in the S.japonicum host oncomelania and mice.Primers and corresponding probes for both ddPCR methods were designed and synthesized,and plasmids containing target sequences were constructed.The sensitivity of the two methods was tested through detection of the corresponding plasmids,and infectious and mixed oncomelania genomic DNA.Their specificity was evaluated by the detection of genomic DNA of negative oncomelania,Schistosoma mansoni,Clonorchis sinensis,Spirometra mansoni,and S.japonicum(as a positive control).The ddPCR probe method was evaluated by detection of early infection of oncomelania exposed tomiracidium with various ratios and incubation times,and the early migration and distribution of cercaria or schistosomula in mouse hosts infected with 200 cercaria via abdominal skin contact.According to standard curves constructed through the detection of plasmid serial dilutions,the regression equation for the EvaGreen assay was y=-0.839 9x+7.050 9,with a correlation coefficient R2=0.988 1,and the regression equation for the probe method was y=-1.047 5x+7.255 1,with a correlation coefficient R2=0.999 8.The lowest limit of plasmid detection with the probe method was between 38.94 cp/μL and 194.74 cp/μL.Both methods successfully detected positive reactions in the genomic DNA samples of infectious oncomelania at concentrations above 0.002 ng/μL and in the genomic DNA of each group of oncomelania mixtures.No significant differences between probe methods were observed in the detection values in the control group and the genomic DNA of negative oncomelania,S.mansoni,C.sinensis,and S.mansoni.However,the detection value of genomic DNA of negative oncomelania(291 ng/μL)with the EvaGreen assay was(20.3±4.39)cp/μL,a value significantly higher than the(1.5±0.1)cp/μL observed in the control group.For detection of early infection in oncomelania,the probe method detected Schistosoma japonicum DNA after 30 s incubation at room temperature with a≥5∶1 ratio of miracidium to oncomelania;the detection value peaked after a short time(5 min),and the peak value showed a fold increase similar to the increase in the miracidium to oncomelania ratio.Detection of early stage infection in mice with the probe method revealed that the schistosomula entered the lungs on day 2 and the liver on day 4,and continually migrated within the organs with abundant blood supply(spleen,kidney,and brain)in the first 9 days;moreover,a tendency toward ectopic parasitism was observed in the heart and pancreas on day 9,and a constantly negative control level was observed in the testes.The ddPCR probe method was more accurate and specific than the EvaGreen assay in the detection of plasmids,and infectious and mixed oncomelania,and the latter showed non-specific reactions in negative oncomelania detection.In a practical application,the probe method was demonstrated to be sensitive,to effectively reflect the early infection of oncomelania,and to reveal schistosomula migration and distribution in multiple organs of infected mice.

Objective To carry out cervical cancer VMAT radiotherapy planning respectively with the single-criteria optimization(SCO)and multi-criteria optimization(MCO)modes of Raystation 4.7 planning system,and to provide references for selecting optimization mode clinically by comparing and analyzing the dosimetric parameters such as target dose distribution,exposure dose to organ at risk(OAR),monitor unit and beam-on time.Methods Ten cervical cancer patients who attended some hospital from February to December 2022 were retrospectively selected,and some VMAT plans were designed for them with the SCO mode of Raystation 4.7 planning system and then enrolled into a SCO group;other VMAT plans were redesigned with the MCO mode under the premise the setup conditions such as machine model and shot field angle were unchanged,and divided into a MCO group.The two groups were compared in terms of maximum dose(D2%),minimum dose(D98%),homogeneity index(HI)and conformity index(CI)of the planning target volume(PTV),beam-on time,monitor unit and exposure doses to OARs including bladder V50 Gy,V40 Gy and V30 Gy,rectum V50 Gy,V40 Gy and V30 Gy,small intestine V50 Gy,V40 Gy and V30 Gy and left and right femur V50 Gy,V40 Gy and V30 Gy.SPSS 22.0 software was used for statistical analysis.Results Both the two groups met clinical requirements.There were no significant differences between the two groups in D98%,CI,small intestine V50 Gy and left and right femur V40 Gy(P>0.05).The MCO group had the values of HI,D2%,V50 Gy,V40 Gy and V30 Gy,rectum V50 Gy,V40 Gy and V30 Gy,small intestine V40 Gy and V30 Gy and left and right femur V30 Gy lower than those of the SCO group,with the differences being statistically significant(P<0.05).The SCO group had less monitor units and shorter beam-on time when compared with the MCO group,with the differences being statistically siginificant(P<0.05).Conclusion When compared with the SCO mode-based VMAT plans,the MCO mode-based VMAT plans significantly decrease the exposure doses and volume to rectum,bladder and small intestine and raise the PTV homogeneity,while lower the treatment efficiency to some extent by increased monitor units and prolonged beam-on time.[Chinese Medical Equipment Journal,2025,46(9):39-44]

Background: Aristolochic acid II (AAII), a major nephrotoxic and carcinogenic component of aristolochic acids (AAs), has been less studied compared with its well-characterized analog, aristolochic acid I (AAI). Although AAs are known to induce carcinogenesis via DNA adduct formation, the toxicity mechanisms, environmental prevalence, and long-term health impacts of AAII remain poorly understood. Objective: This study aimed to systematically evaluate AAII’s acute and chronic toxicity, carcinogenic mechanisms, and environmental exposure patterns using integrated murine models and phytochemical analyses to clarify its toxicological profile and associated health risks. Methods: C57BL/6J mice were used in the following experiments: (1) determination of AAII content in 3 commonly used Aristolochia medicinal materials via liquid chromatography-mass spectrometry/mass spectrometry; (2) acute toxicity testing with single doses of 10, 20, or 40 mg/kg; and (3) chronic exposure with 1 or 10 mg/kg administered every other day for 24 weeks, followed by 21 to 40 weeks of postexposure monitoring. Histopathological examination, whole-exome sequencing, biochemical assays, and micronucleus tests were performed to assess multi-organ damage, tumorigenesis, genomic mutation signatures, and direct clastogenicity. Phytochemical analyses were used to evaluate environmental distribution. Results: (1) A single 40 mg/kg dose of AAII induced dose-dependent renal tubular degeneration without hepatotoxicity; (2) the 10 mg/kg group showed significant mortality (20%), tumor incidence (33.3%, primarily forestomach and bladder transitional cell carcinomas), persistent renal interstitial fibrosis, and subclinical hepatic injury. Chronic exposure to 1 mg/kg still induced 13.3% mortality and 15.5% tumor incidence over a 64-week period; (3) whole-exome sequencing revealed a predominance of C>T mutations and pathway enrichment in chemical carcinogenesis and cytochrome P450-mediated metabolism, indicating reactive metabolite-driven mechanisms distinct from classical AA-DNA adducts; and (4) no histopathological changes were observed in nontarget organs (brain, heart, and testes), and micronucleus assays confirmed the absence of direct clastogenicity. Conclusion: This study highlights the delayed carcinogenic risks of low-dose chronic AAII exposure and emphasizes the need to update regulatory frameworks to ensure the safe use of aristolochiaceae-containing herbal products.