Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

This study was aimed at understanding the prevalence and influencing factors of food-borne parasitic diseases in ethnic minority areas of Guizhou Province,to provide a scientific basis for the development of appropriate intervention measures based on the human-animal-environment One Health concept.In 2023,the infection status of the human population,reservoir hosts,intermediate hosts,food-borne parasitic diseases,and related social and environmental factors were investigated in Congjiang County in Qidongnan Miao and Dong Autonomous Prefecture;Luodian County in Qiannan Buyi and Miao Autonomous Prefecture;and Ceheng County in Qianxinan Buyi and Miao Autonomous Prefecture.At least 1 000 individuals were sampled from each county,along with at least 50 insect-protected host samples from each location.Food-borne parasite infections were detected with the modified Kato thick smear method.A questionnaire survey was administered to the population.Detection of food-borne parasitic metacercariae was performed in intermediate host fish through the flaking and digestion method,and in crabs through the pounding and sedimentation method.The chi-square test was used to compare rates,and logistic regression was applied for multivariate analysis.A total of 3 023 questionnaires and fecal samples were collected.Males accounted for 47.50%,females accounted for 52.50%,and members of ethnic minorities accounted for 96.06%.A total of 186 food-borne parasitic infections were identified,and the infection rate was 6.15%.Five insect species were detected,which showed an infection rate of 5.39%.The infection rate of Clonorchis sinensis was 0.33%,that of Taenia was 0.40%,that of Heteroceles was 0.17%,that of Acanthus was 0.17%,and that of Echinostoma was 0.03%.Human infections with Echinostomus colloides and Echinostomia transferoris had not previously been reported in China.Single-factor analysis revealed statistically significant differences in food-borne parasite infections according to various factors,including the consumption of untreated water,raw fish and shrimp,raw pig blood,raw cow gastric juice,and raw pork and beef,as well as raw pig and cow viscera(P<0.05).Multivariate analysis indicated that the risk factors for food-borne parasite infections among residents in minority areas of Guizhou Province included the consumption of raw pig blood(OR=2.841,95%CI:1.809-4.463),raw cow gastric juice(OR=2.122,95%CI:1.297-3.469),and raw fish and shrimp(OR=1.779,95%CI:1.049-3.018).A total of 173 fecal samples of the reservoir host were examined,which showed a rate of food-borne parasite infection of 5.2%.A total of 510 intermediate host fish were examined,which showed a 4.51%positivity rate of encysted metacercaria of Clonorchis sinensis.The crab,pig,and beef samples were not positive.In conclusion,food-borne parasitic infections were prevalent in ethnic minority regions of Guizhou Province,and consumption of raw food were influencing factors.A focus on populations with raw food consumption habits,including raw pig blood,cow gastric juice,fish and shrimp,is essential.Concurrently,monitoring of animal hosts must be strengthened to perform key interventions according to the One Health concept.

Objective:To develop a popular science educational product aimed at enhancing home-based self-management among peritoneal dialysis (PD) patients.Methods:A preliminary framework for popular science content on home-based self-management for PD patients was constructed based on an evidence summary. Through refinement of the evidence and expert panel discussions, the final educational content was determined and used to produce a popular science video. From June 18 to June 30, 2024, the video was disseminated through both online and offline channels. A questionnaire survey was used to assess the quality of the popular science educational product.Results:The final content framework consisted of four key areas: volume management, nutrition management, exercise management, and management of common problems. A popular science video with a total duration of 5 minutes and 52 seconds was developed. A total of 158 PD patients rated the quality of the popular science educational product with an average score of (83.03±2.01) .Conclusions:The development method of the popular science educational product is scientifically sound, and the content is suitable for dissemination. It provides a practical reference for improving health literacy and self-management ability among home-based PD patients.

Nano/microplastics(NMPs),due to their environmental persistence and resistance to degradation,have emerged as a major contributor to global pollution.NMPs are capable of adsorbing various hazardous chemicals and heavy metals,thereby posing threats to aquatic ecosystem health,which may ultimately cause potential risks to human health.Conventional analytical methods suffered from limited resolution,insufficient chemical information,or destruction of sample,invalidating these assays for on-site detection of NMPs.Surface-enhanced Raman scattering(SERS)offers distinct advantages such as high sensitivity,superior specificity,rich fingerprint information,and non-destructive analysis,thus facilitating the on-site analysis of NMPs in complex matrices.This review summarized recent advances in SERS substrates for detection of NMPs,discussed the construction and applications of SERS-based multimodal detection strategies,and introduced the research progress of SERS detection of NMPs in food safety,environmental pollution,and bioanalysis.Moreover,the main challenges and future directions of SERS-based NMP detection were outlined.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

OBJECTIVE: Several epidemiological observational studies have related particulate matter (PM) exposure to Inflammatory bowel disease (IBD), but many confounding factors make it difficult to draw causal links from observational studies. The objective of this study was to explore the causal association between PM _2.5 exposure, its absorbance, and IBD. METHODS: We assessed the association of PM _2.5 and PM _2.5 absorbance with the two primary forms of IBD (Crohn's disease [CD] and ulcerative colitis [UC]) using Mendelian randomization (MR) to explore the causal relationship. We conducted two-sample MR analyses with aggregated data from the UK Biobank genome-wide association study. Single-nucleotide polymorphisms linked with PM _2.5 concentrations or their absorbance were used as instrumental variables (IVs). We used inverse variance weighting (IVW) as the primary analytical approach and four other standard methods as supplementary analyses for quality control. RESULTS: The results of MR demonstrated that PM _2.5 had an adverse influence on UC risk (odds ratio [ OR] = 1.010; 95% confidence interval [ CI] = 1.001-1.019, P = 0.020). Meanwhile, the results of IVW showed that PM _2.5 absorbance was also causally associated with UC ( OR = 1.012; 95% CI = 1.004-1.019, P = 0.002). We observed no causal relationship between PM _2.5, PM _2.5 absorbance, and CD. The results of sensitivity analysis indicated the absence of heterogeneity or pleiotropy, ensuring the reliability of MR results. CONCLUSION Based on two-sample MR analyses, there are potential positive causal relationships between PM _2.5, PM _2.5 absorbance, and UC.
Humans ; Mendelian Randomization Analysis ; Particulate Matter/analysis* ; Polymorphism, Single Nucleotide ; Inflammatory Bowel Diseases/genetics* ; Air Pollutants/analysis* ; Crohn Disease/genetics* ; Colitis, Ulcerative/genetics* ; Genome-Wide Association Study ; Risk Factors ; Environmental Exposure

Nodal marginal zone B-cell lymphoma(NMZL),the least common subtype of marginal zone lymphoma,represents a low-grade malignancy arising from the marginal zone of lymph node follicles,composed of small B-cells with an inert non-Hodgkin lymphoma nature.It accounts for 1.5% to 1.8% of all non-Hodgkin lymphomas and 10% of all marginal zone lymphomas.The low incidence and lack of typical clinical and pathological features pose a challenge to the diagnosis and clinical management of NMZL.In this article,we reported the diagnosis and treatment of a case of NMZL located in the parapharyngeal space of the left neck and reviewed the relevant literature from both domestic and international sources.We summarized the clinical manifestations,histopathological features,immunohistochemical characteristics,imaging features,diagnosis and treatment modalities,and prognosis of NMZL.
Humans ; Lymphoma, B-Cell, Marginal Zone/pathology* ; Lymph Nodes/pathology* ; Neck/pathology* ; Male

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.