OBJECTIVE To investigate a suspected hospital-acquired infection cluster of Enterococcus faecium(Efm)in a neonatal intensive care unit(NICU)of the First Medical Center of Chinese PLA General Hospital,identify the source of infection and transmission routes,and provide a reference for precise prevention and control of hospital-acquired infections.METHODS Epidemiological investigations and environmental microbiological sam-pling were conducted for two neonates with Efm bloodstream infections in the NICU in Jul.2024 to detect Efm in the ward environment.Whole-genome average nucleotide identity(ANI)and multilocus sequence typing(MLST)were used to analyze the homology,drug resistance,and virulence factors of Efm isolates from patients and envi-ronments.Targeted intervention measures were proposed.RESULTS Two cases of Efm bloodstream infection were detected.A total of 37 environmental specimens were collected,and 2 were cultured Efm(the wipe dispenser o-pening and incubator handle of the patients).The drug susceptibility testing results of 2 environmental specimens were consistent with those of the two patient specimens.Genomic analysis confirmed high homology(ANI＞99.99％)among the four Efm isolates.After implementing a series of measures including centralized isolation,strict hand hygiene,thorough environmental cleaning and disinfection,strict disinfection and management of inva-sive devices,enhanced grouping of medical staff for diagnosis and treatment,the incident was effectively con-trolled.CONCLUSIONS This incident can be determined as cluster of hospital-acquired infection with Enterococcus faecium in the neonatal intensive care unit.The wet wipes are the source or transmission medium of contamina-tion.Inadequate disinfection of items and the environment,and insufficient hand hygiene of medical staff are the main reasons for this infection outbreak.Early identification of abnormal cluster of infection,investigation of the source of infection and transmission routes and timely implementation of targeted measures are the keys for preventing infection outbreaks.

Objective To identify the cuproptosis genes associated with prognosis and immune microenvironment in lung cancer with the use of bioinformatics.Methods The lung cancer dataset used in this study was obtained from the TCGA database.The cuproptosis-related genes(CRGs)were obtained from the previously reported literature.The R software Deseq2 package was used to identify the differentially expressed genes(DEGs)in lung cancer.The intersection of DEGs and CRGs was taken to obtain the differentially expressed CRGs(DE-CRGs).COX analysis and R software rms package were used to identify DE-CRGs associated with the prognosis of lung cancer.Estimate and Cibersort algorithms were applied to identify the correlation of DE-CRGs with the immune microenvironment.Results Compared to the normal tissues,a total of 5,269 DEGs were present in lung cancer tissues in the TCGA database,and there were 11 shared genes between DEGs and CRGs.The 11 DE-CRGs mainly regulated the energy metabolism,carbon metabolism and amino acid metabolism.In the DE-CRGs,LIPT1 was an independent risk factor for lung cancer,and the column chart constructed with the clinical features(age,TNM staging,and residual tumor)predicted the survival of lung cancer patients in a manner similar to their actual outcomes.LIPT1 showed a positive correlation with the infiltration of M1 and M2 type macrophages,activated natural killer cells cells and CD8+T cells,and showed a significant negative correlation with M0 type macrophages,activated mast cells,neutrophils and Treg cells(P<0.05).Conclusion LIPT1 may serve as a prognostic and immune microenvironment-associated cuproptosis gene,which is a novel biomarker for lung cancer therapy.

The superiority of magnetic resonance(MR)images in soft tissue imaging makes them indispensable for medical diagnosis and radiotherapy,but factors such as acquisition cost and contraindications limit their widespread application.In contrast,computed tomography(CT)scanning has the advantages of fast imaging speed and low cost.Herein,this review summarizes the research progress of generative deep learning models in the field of medical CT to MR image synthesis,and especially analyzes the technical characteristics,performance advantages,and challenges of various MR image synthesis methods from clinical scenarios such as spinal lesions,acute ischemic stroke,and tumor segmentation.Furthermore,the application value and future research prospects of medical image synthesis are discussed.

Objective To explore the impact of Metformin(Met)on the balance of type 17 helper T cells(Th17)/regulatory T cells(Treg)in DM rats by regulating the C-C motif chemokine ligand 2(CCL2)-C-C motif chemokine receptor 2(CCR2)axis.Methods A total of 50 SD rats were randomly divided into normal control(NC)group,model(Mod)group,Met(100 mg/kg)group,Met+empty vector(Met+oe-NC)group,and Met+CCL2 overexpression(Met+oe-CCL2)group,with 10 rats in each group.The changes of FBG evaluated in each group,and the pathological changes of pancreatic islet tissue were assessed using hematoxylin-eosin(HE)staining followed by histological scoring.The ratio of Th17/Treg in peripheral blood was detected by flow cytometry.ELISA was used to measure the serum levels of IL-17,TNF-α,TGF-β and IL-10.Immunofluorescence was used to detect the proportion of Th17 and Treg in pancreatic tissue.RT-PCR and Western blot were used to detect the mRNA and protein expression of ROR-γt,forkhead box P3(FOXP3),CCL2 and CCR2 in pancreatic tissue.Results The islet structure was intact and the boundary was clear,and there was no pathological damage in the NC group.In the Mod group,the islet tissue exhibited significant pathological damage,characterized by disrupted architecture,reduced volume,and blurred boundaries with surrounding tissues.Additionally,the cells in the islet displayed marked disorganization and substantial loss.Compared with the Mod group,the pathological damage of the islet tissue was alleviated in the Met and Met+oe-NC group.Compared with the Met group,the pathological damage was aggravated in the Met+oe-CCL2 group.Compared with the NC group,the levels of FBG,Th17/Treg ratio,IL-17,TNF-α,Th17 infiltration rate,ROR-γt,CCL2,and CCR2 mRNA and protein expression were higher(P<0.05),while TGF-β,IL-10,Treg infiltration rate,FOXP3 mRNA and protein expression were lower in the Mod group(P<0.05).Compared with the Mod group,the levels of FBG,Th17/Treg ratio,IL-17,TNF-α,Th17 infiltration rate,ROR-γt,CCL2,and CCR2 mRNA and protein were lower(P<0.05),while TGF-β,IL-10,Treg infiltration rate,FOXP3 mRNA and protein expression were higher in the Met and Met+oe-NC groups(P<0.05).Compared with the Met group,the levels of FBG,Th17/Treg ratio,IL-17,TNF-α,Th17 infiltration rate,ROR-γt,CCL2,and CCR2 mRNA and protein were higher(P<0.05),and TGF-β,IL-10,Treg infiltration rate,FOXP3 mRNA and protein expression were higher in the Met+oe-CCL2 group(P<0.05).Conclusions Metformin can promote Th17/Treg cell balance drift towards Treg direction by inhibiting the activation of CCL2-CCR2 signal axis,thereby preventing the occurrence and development of inflammatory reactions,alleviating pancreatic islet damage,and improving the glucose metabolism in DM rats.

The superiority of magnetic resonance(MR)images in soft tissue imaging makes them indispensable for medical diagnosis and radiotherapy,but factors such as acquisition cost and contraindications limit their widespread application.In contrast,computed tomography(CT)scanning has the advantages of fast imaging speed and low cost.Herein,this review summarizes the research progress of generative deep learning models in the field of medical CT to MR image synthesis,and especially analyzes the technical characteristics,performance advantages,and challenges of various MR image synthesis methods from clinical scenarios such as spinal lesions,acute ischemic stroke,and tumor segmentation.Furthermore,the application value and future research prospects of medical image synthesis are discussed.

Objective To explore the impact of Metformin(Met)on the balance of type 17 helper T cells(Th17)/regulatory T cells(Treg)in DM rats by regulating the C-C motif chemokine ligand 2(CCL2)-C-C motif chemokine receptor 2(CCR2)axis.Methods A total of 50 SD rats were randomly divided into normal control(NC)group,model(Mod)group,Met(100 mg/kg)group,Met+empty vector(Met+oe-NC)group,and Met+CCL2 overexpression(Met+oe-CCL2)group,with 10 rats in each group.The changes of FBG evaluated in each group,and the pathological changes of pancreatic islet tissue were assessed using hematoxylin-eosin(HE)staining followed by histological scoring.The ratio of Th17/Treg in peripheral blood was detected by flow cytometry.ELISA was used to measure the serum levels of IL-17,TNF-α,TGF-β and IL-10.Immunofluorescence was used to detect the proportion of Th17 and Treg in pancreatic tissue.RT-PCR and Western blot were used to detect the mRNA and protein expression of ROR-γt,forkhead box P3(FOXP3),CCL2 and CCR2 in pancreatic tissue.Results The islet structure was intact and the boundary was clear,and there was no pathological damage in the NC group.In the Mod group,the islet tissue exhibited significant pathological damage,characterized by disrupted architecture,reduced volume,and blurred boundaries with surrounding tissues.Additionally,the cells in the islet displayed marked disorganization and substantial loss.Compared with the Mod group,the pathological damage of the islet tissue was alleviated in the Met and Met+oe-NC group.Compared with the Met group,the pathological damage was aggravated in the Met+oe-CCL2 group.Compared with the NC group,the levels of FBG,Th17/Treg ratio,IL-17,TNF-α,Th17 infiltration rate,ROR-γt,CCL2,and CCR2 mRNA and protein expression were higher(P<0.05),while TGF-β,IL-10,Treg infiltration rate,FOXP3 mRNA and protein expression were lower in the Mod group(P<0.05).Compared with the Mod group,the levels of FBG,Th17/Treg ratio,IL-17,TNF-α,Th17 infiltration rate,ROR-γt,CCL2,and CCR2 mRNA and protein were lower(P<0.05),while TGF-β,IL-10,Treg infiltration rate,FOXP3 mRNA and protein expression were higher in the Met and Met+oe-NC groups(P<0.05).Compared with the Met group,the levels of FBG,Th17/Treg ratio,IL-17,TNF-α,Th17 infiltration rate,ROR-γt,CCL2,and CCR2 mRNA and protein were higher(P<0.05),and TGF-β,IL-10,Treg infiltration rate,FOXP3 mRNA and protein expression were higher in the Met+oe-CCL2 group(P<0.05).Conclusions Metformin can promote Th17/Treg cell balance drift towards Treg direction by inhibiting the activation of CCL2-CCR2 signal axis,thereby preventing the occurrence and development of inflammatory reactions,alleviating pancreatic islet damage,and improving the glucose metabolism in DM rats.

OBJECTIVE To investigate a suspected hospital-acquired infection cluster of Enterococcus faecium(Efm)in a neonatal intensive care unit(NICU)of the First Medical Center of Chinese PLA General Hospital,identify the source of infection and transmission routes,and provide a reference for precise prevention and control of hospital-acquired infections.METHODS Epidemiological investigations and environmental microbiological sam-pling were conducted for two neonates with Efm bloodstream infections in the NICU in Jul.2024 to detect Efm in the ward environment.Whole-genome average nucleotide identity(ANI)and multilocus sequence typing(MLST)were used to analyze the homology,drug resistance,and virulence factors of Efm isolates from patients and envi-ronments.Targeted intervention measures were proposed.RESULTS Two cases of Efm bloodstream infection were detected.A total of 37 environmental specimens were collected,and 2 were cultured Efm(the wipe dispenser o-pening and incubator handle of the patients).The drug susceptibility testing results of 2 environmental specimens were consistent with those of the two patient specimens.Genomic analysis confirmed high homology(ANI＞99.99％)among the four Efm isolates.After implementing a series of measures including centralized isolation,strict hand hygiene,thorough environmental cleaning and disinfection,strict disinfection and management of inva-sive devices,enhanced grouping of medical staff for diagnosis and treatment,the incident was effectively con-trolled.CONCLUSIONS This incident can be determined as cluster of hospital-acquired infection with Enterococcus faecium in the neonatal intensive care unit.The wet wipes are the source or transmission medium of contamina-tion.Inadequate disinfection of items and the environment,and insufficient hand hygiene of medical staff are the main reasons for this infection outbreak.Early identification of abnormal cluster of infection,investigation of the source of infection and transmission routes and timely implementation of targeted measures are the keys for preventing infection outbreaks.

Objective To explore the value of biparametric magnetic resonance imaging(bp-MRI)radiomics models in noninvasive prediction of high-risk prostate cancer.Methods A total of 320 patients with pathologically confirmed prostate cancer were retro-spectively selected,and all patients underwent bp-MRI before pathology,including T2WI and diffusion weighted imaging(DWI).Appar-ent diffusion coefficient(ADC)maps were extracted from DWI.All patients were divided into high-risk(Gleason score≥8)and medium-low risk(Gleason score ≤7)groups based on the Gleason score.Using 3D Slicer software,the entire prostate gland was outlined.Python software was used to calculate parameters,and the minimum redundancy maximum correlation and sequence back-ward elimination algorithms were used to extract and select radiomics features and to build a model.Three radiomics(T2 WI,DWI,ADC)models were constructed and verified by logistic regression(LR).The performance of the model was evaluated by area under the curve(AUC)of receiver operating characteristic(ROC)curve,specificity(SP),sensitivity(SE),and accuracy(ACC).An indi-vidual prediction model was established via the clinical data of 224 patients and bp-MRI features,and validated via the data of 96 patients.Results A total of 1 165 radiomics features were extracted.After feature screening,2,4 and 6 radiomics features were screened out to construct T2WI model,DWI model and ADC model for predicting high-risk prostate cancer.All radiomics models had significant predictive performance in identifying medium-low risk and high-risk groups(P＜0.05).The DWI model had the highest predictive value,and the AUC,ACC,SE,and SP in the training group were 0.814,0.756,0.838,and 0.744,respectively.The AUC,ACC,SE,and SP in the verification group were 0.840,0.756,0.848,and 0.784,respectively.Conclusion Radiomics based on bp-MRI can better identify medium-low risk and high-risk prostate cancer before surgery.

OBJECTIVE To evaluate the effectiveness， safety， economy， innovation， suitability and accessibility of recombinant Mycobacterium tuberculosis fusion protein （EC）， and to provide evidence for selecting skin detection methods for tuberculosis infection diagnosis and auxiliary diagnosis of tuberculosis. METHODS The effectiveness and safety of EC compared with purified protein derivative of tuberculin （TB-PPD） were analyzed by the method of systematic review. Cost minimization analysis， cost-effectiveness analysis and cost-utility analysis were used to evaluate the short-term economy of EC compared with TB-PPD， and cost-utility analysis was used to evaluate the long-term economy. The evaluation dimensions of innovation， suitability and accessibility were determined by systematic review and improved Delphi expert consultation， and the comprehensive score of EC and TB-PPD in each dimension were calculated by the weight of each indicator. RESULTS The scores of effectiveness， safety， economy， innovation and suitability of EC were all higher than those of TB-PPD. The affordability scores of the two drugs were consistent， while the availability score of EC was lower than those of TB-PPD. After considering dimensions and index weight， the scores of effectiveness， safety， economy， innovation， suitability， accessibility and the comprehensive score of EC were all higher than those of TB-PPD. CONCLUSIONS Compared with TB-PPD， EC performs better in all dimensions of effectiveness， safety， economy， innovation， suitability and accessibility. However， it is worth noting that EC should further improve its availability in the dimension of accessibility.

OBJECTIVE: To investigate the consistency and diagnostic performance of magnetic resonance imaging (MRI) for detecting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and the validity of deep learning attention mechanisms and clinical features for MVI grade prediction. METHODS: This retrospective study was conducted among 158 patients with HCC treated in Shunde Hospital Affiliated to Southern Medical University between January, 2017 and February, 2020. The imaging data and clinical data of the patients were collected to establish single sequence deep learning models and fusion models based on the EfficientNetB0 and attention modules. The imaging data included conventional MRI sequences (T₁WI, T₂WI, and DWI), enhanced MRI sequences (AP, PP, EP, and HBP) and synthesized MRI sequences (T1mapping-pre and T1mapping-20 min), and the high-risk areas of MVI were visualized using deep learning visualization techniques. RESULTS: The fusion model based on T1mapping-20min sequence and clinical features outperformed other fusion models with an accuracy of 0.8376, a sensitivity of 0.8378, a specificity of 0.8702, and an AUC of 0.8501 for detecting MVI. The deep fusion models were also capable of displaying the high-risk areas of MVI. CONCLUSION The fusion models based on multiple MRI sequences can effectively detect MVI in patients with HCC, demonstrating the validity of deep learning algorithm that combines attention mechanism and clinical features for MVI grade prediction.
Humans ; Carcinoma, Hepatocellular ; Retrospective Studies ; Liver Neoplasms ; Magnetic Resonance Imaging ; Algorithms