Background Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen for both human bloodstream infections and mastitis in cows. However, little attention has been paid to the cross-host transmission of MRSA from cows to high-risk groups in China. Objective To determine the MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang, identify the antibiotic resistance profiles and molecular characteristics of the isolates, and provide scientific evidence for the formulation of targeted infection control strategies. Method A cross-sectional survey combined with laboratory pathogen analysis was conducted. From June to August 2024, large-scale dairy farms in Xinjiang region were selected as study sites. Nasal swabs (n=96) and skin swabs (n=39) were collected from workers, and bovine nasal swab samples (n=109) were collected simultaneously. All samples were subjected to MRSA isolation, cultivation, and identification, followed by antibiotic susceptibility testing to characterize resistance phenotypes. Staphylococcus aureus protein A (Spa) typing was performed to determine strain genotypes and elucidate MRSA colonization rates and molecular epidemiological patterns. Results A total of 35 MRSA strains was successfully isolated from 244 samples. The MRSA colonization rates among dairy farm workers and dairy cows were 20.83% (20/96) and 12.84% (14/109), respectively, with an overall isolation rate of 14.34% (35/244). Among the workers, the nasal colonization rate was 16.67% (16/96), and the skin colonization rate was 12.82% (5/39). One worker exhibited MRSA colonization at multiple body sites. All MRSA strains were resistant to cefoxitin (100%, 35/35). The resistance rates to erythromycin and clindamycin were 42.86% (15/35) and 34.29% (12/35), respectively. Thirteen strains showed a multidrug-resistant phenotype, whereas all strains were susceptible to vancomycin. The MRSA isolates exhibited high genetic diversity, with 13 Spa types identified, among which t441 was the most prevalent (8 strains). Both t441 and t034 types were detected in samples from both the dairy cows and their handlers. These two Spa types also carried and stably inherited specific resistance combinations, including erythromycin–clindamycin–cefoxitin and ciprofloxacin–erythromycin–clindamycin–gentamicin–cefoxitin–tetracycline, and a statistically significant association was also observed between the two resistance profiles and the bacterial types (P < 0.001). In addition, one novel Spa type strain was identified. Conclusion MRSA colonization rates among dairy cows and dairy farm workers in Xinjiang are relatively high, with evidence of multi-site colonization. The isolates exhibit high levels of multidrug resistance and genetic diversity, indicating a potential risk of cross-host transmission.

ObjectiveTo investigate the regulatory effect of overexpressed protein tyrosine phosphatase non-receptor type 2 （Ptpn2） on the inflammatory response of mouse alveolar macrophages （MH-S） induced by SiO₂. MethodsCells with overexpressed Ptpn2 were constructed and induced by SiO₂. The experimental groups were divided into four groups： the negative control group with an empty vector （NC）， the overexpressed Ptpn2 group （P）， the negative control group with an empty vector + SiO₂ induction （NS）， and the overexpressed Ptpn2 + SiO₂ induction group （PS）. Isobaric tags for relative and absolute quantification （iTRAQ） combined with liquid chromatography-tandem mass spectrometry （LC-MS/MS） were used to screen differential proteins， followed by Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） database analyses. Immunofluorescence staining was used to detect the expressions of Tumor necrosis factor （TNF） α， Gasdermin D （GSDMD）， and Transforming growth factor （TGF）-β1. Western blot was used to detect the protein expression levels of PTPN2， Toll-like receptor 4 （TLR4）， tumor necrosis factor-α （TNF-α）， nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3）， and proteins related to the TGF-β1 signaling pathway in the cells of each group. ResultsiTRAQ results identified 144 differential proteins among the four groups. GO analysis showed that in biological processes （BP）， these differential proteins were mainly enriched in IκB kinase/nuclear factor-κB （NF-κB） signaling， cell activation and signal transduction involved in immune responses， and regulation of receptor signaling pathways by signal transducer and activator of transcription （STAT）， etc. KEGG analysis revealed that the differential proteins were mainly enriched in Toll-like receptor signaling pathway， NF-κB signaling pathway， NOD-like receptor signaling pathway， TGF-β signaling pathway， and TNF signaling pathway. The results of immunofluorescence staining showed that compared with the NC group， the expressions of TNF α， GSDMD， and TGF-β1 in the cells of the NS group increased （P < 0.05）； compared to the NS group， the expression of the aforementioned proteins in the PS group decreased in cellular proteins（P < 0.05）. The results of Western blot showed that compared with the NC group， the protein expression levels of PTPN2， p-NF-κB，MyD88，TLR4，NLRP3，GSDMD，Caspase-1，IL-1β， TGF-βR1， TGF-βR，p-Smad2/3 in the NS group were significantly upregulated （P < 0.05）； compared with the NS group， the expression levels of the aforementioned proteins in the PS group were significantly downregulated （P < 0.05）. ConclusionOverexpression of Ptpn2 can inhibit the protein expressions of TLR4-TNF-α signaling， NLRP3 signaling， and TGF-β1 signaling closely related to inflammatory response in SiO₂-mediated MH-S macrophages.

Background Under intensive dairy farming conditions, Enterococcus spp. can be transmitted between animals, farm workers, and the environment via multiple vectors such as feces, soil, water, air, and farming equipment, posing a potential threat to public health. Objective To elucidate the prevalence, distribution, and antimicrobial resistance profiles of Enterococcus faecalis (E. faecalis) and Enterococcus faecium (E. faecium) among farm workers, dairy cattle, and the farm environment in Xinjiang, and to assess the risk of their cross-host transmission. Methods From May 2024 to January 2025, a total of 317 samples were collected from 11 large-scale dairy farms in Xinjiang, China, including feces from farm workers (n=130) and dairy cattle (n=154), and environmental samples (n=33). E. faecalis and E. faecium were isolated and identified, followed by antimicrobial susceptibility testing and multilocus sequence typing (MLST) to analyze their molecular characteristics. Results A total of 183 Enterococcus isolates were obtained (66 E. faecalis and 117 E. faecium isolated). The isolation rates of both species showed statistically significant differences among the three sources (χ²=29.21, P=0.003). Antimicrobial resistance analysis revealed that E. faecalis generally exhibited higher resistance rates across multiple antibiotic classes than E. faecium. High resistance to rifampicin was observed across all sources (50.00%–81.25%), with statistical variation among origins (χ²=8.03, P=0.024). Multidrug-resistant strains accounted for 69.10% of the isolates. Multidrug resistance patterns in E. faecium varied significantly by source (χ²=27.19, P=0.014), and one isolate displayed resistance to eight antibiotic classes. MLST indicated high genetic diversity; E. faecalis was dominated by ST472 and ST227 of which the distrubution was significantly different among sources, while E. faecium primarily clustered into clonal complexes CC94 (centered on ST94) and CC17 (centered on ST22). Conclusion Resistant Enterococcus strains exhibit cross-transmission among farm workers, animals, and the environment. Under the "One Health" framework, standardized farming protocols and prudent antimicrobial use are essential to disrupt the transmission chain of resistant clones and mitigate the spread of antimicrobial resistance at its source.

Background Under intensive dairy farming conditions, Enterococcus spp. can be transmitted between animals, farm workers, and the environment via multiple vectors such as feces, soil, water, air, and farming equipment, posing a potential threat to public health. Objective To elucidate the prevalence, distribution, and antimicrobial resistance profiles of Enterococcus faecalis (E. faecalis) and Enterococcus faecium (E. faecium) among farm workers, dairy cattle, and the farm environment in Xinjiang, and to assess the risk of their cross-host transmission. Methods From May 2024 to January 2025, a total of 317 samples were collected from 11 large-scale dairy farms in Xinjiang, China, including feces from farm workers (n=130) and dairy cattle (n=154), and environmental samples (n=33). E. faecalis and E. faecium were isolated and identified, followed by antimicrobial susceptibility testing and multilocus sequence typing (MLST) to analyze their molecular characteristics. Results A total of 183 Enterococcus isolates were obtained (66 E. faecalis and 117 E. faecium isolated). The isolation rates of both species showed statistically significant differences among the three sources (χ²=29.21, P=0.003). Antimicrobial resistance analysis revealed that E. faecalis generally exhibited higher resistance rates across multiple antibiotic classes than E. faecium. High resistance to rifampicin was observed across all sources (50.00%–81.25%), with statistical variation among origins (χ²=8.03, P=0.024). Multidrug-resistant strains accounted for 69.10% of the isolates. Multidrug resistance patterns in E. faecium varied significantly by source (χ²=27.19, P=0.014), and one isolate displayed resistance to eight antibiotic classes. MLST indicated high genetic diversity; E. faecalis was dominated by ST472 and ST227 of which the distrubution was significantly different among sources, while E. faecium primarily clustered into clonal complexes CC94 (centered on ST94) and CC17 (centered on ST22). Conclusion Resistant Enterococcus strains exhibit cross-transmission among farm workers, animals, and the environment. Under the "One Health" framework, standardized farming protocols and prudent antimicrobial use are essential to disrupt the transmission chain of resistant clones and mitigate the spread of antimicrobial resistance at its source.

Objective:To analyze the predictive role of WT1 expression levels pre-and early post-transplantation on relapse and overall survival(OS)in patients with acute myeloid leukemia(AML)undergoing allogeneic hematopoietic stem cell transplantation(allo-HSCT)during their first complete remission(CR1).Methods:A retrospective analysis was conducted on the clinical data of 107 adult AML patients who underwent allo-HSCT during their CR1 at our center between May 2012 and December 2021.The predictive role of bone marrow WT1 expression levels before transplantation and at 3 and 6 months post-transplantation on relapse and OS was explored in combination with relevant clinical factors.Results:The median follow-up time for the 107 patients was 70(range:11-117)months.Among the patients,15 cases died.Kaplan-Meier survial analysis showed that the 3-year overall survival(OS)rate was 85.0％.20 patients experienced relapse,with a median time to relapse of 8(range:0.5-44)months and a l-year cumulative relapse rate of 13.1％.The overall median value of WT1 before transplantation,3 months after transplantation,and 6 months after transplantation was 0.26％(range:0％-23.64％),with an upper quartile value of 0.74％.No statistically significant differences in WT1 expression levels were observed among the pre-transplantation,3-month post-transplantation,and 6-month post-transplantation time points(P=0.227).Univariate analysis showed that patients with WT1 levels＞0.74％at 3 months post-transplantation had a higher 1-year relapse rate(P=0.029)and lower 3-year OS rate(P＜0.001)compared to patients with WT1 levels ≤0.74％.Other significant factors affecting 1-year relapse included stem cell source(P=0.041)and chronic graft-versus-host disease(cGVHD)(P=0.013).For 3-year OS,additional influencing factors were genetic high risk(P=0.048)and stem cell source(P=0.016).Multivariate analysis revealed that WT1 level＞0.74％at 3 months post-transplantation had a trend to affect 1-year relapse rate(HR=3.309,95％CI:0.958-11.431,P=0.058),while the absence of cGVHD was an independent risk factor for 1-year relapse(HR=3.473,95％CI:0.749-16.100,P=0.037).Only WT1 level＞0.74％at 3 months post-transplantation was an independent risk factor for 3-year OS(HR=6.886,95％CI:2.402-19.738,P＜0.001).Conclusion:High WT1 expression level at 3 months post-transplantation in AML patients undergoing allo-HSCT during CR1 affects the 1-year relapse rate and 3-year OS,and is an independent risk factor affecting 3-year OS.These findings suggest that dynamic monitoring of WT1 expression levels has certain value in prognostic assessment of AML patients who received allo-HSCT during CR1.

Objective To analyze the burden and trend of musculoskeletal diseases(including gout,low back pain,neck pain,osteoarthritis,and rheumatoid arthritis)in China from 1990 to 2021,and to provide reference for formulating and adjusting prevention strategies for musculoskeletal diseases.Methods The Global Burden of Disease(GBD)in 2021 database was used to analyze the status and trend of the incidence and disability-adjusted life years(DALYs)rate of musculoskeletal diseases in China.Annual percentage change(EAPC)was used to comprehensively evaluate the trend of the burden of musculoskeletal diseases from 1990 to 2021.Gender and age-specific incidence and DALYs rate of musculoskeletal diseases were analyzed.Results In 2021,the number of cases of gout,low back pain,neck pain,osteoarthritis,and rheumatoid arthritis in China was 3,079,836,43,374,995,10,292,099,11,652,721,and 247,307,respectively.Among the 5 major musculoskeletal conditions,low back pain had the greatest incidence and DALYs rate.From 1990 to 2021,the age-standardized incidence of gout,osteoarthritis,and rheumatoid arthritis showed an upward trend,that of neck pain remained relatively stable,and that of low back pain showed a downward trend.The age-standardized DALYs rates of gout and osteoarthritis showed an increasing trend,that of neck pain and rheumatoid arthritis remained relatively stable,and that of low back pain showed a decreasing trend.The results of the stratified analysis by gender and age indicated that,the age-standardized incidence rate and age-standardized DALYs rate of gout were higher in men than in women,while the age-standardized incidence rate and age-standardized DALYs rate of low back pain,neck pain,osteoarthritis,and rheumatoid arthritis were higher in women than in men.The age groups with the burden of the five major musculoskeletal diseases were relatively consistent,mainly in the 40-75 years old.Conclusion From 1990 to 2021,the disease burden of gout,osteoarthritis,and rheumatoid arthritis increased significantly in China,while the disease burden of neck pain remained relatively stable,while the disease burden of low back pain showed a certain improvement.In addition,the burden of musculoskeletal diseases in China varies greatly by gender and age.Targeted intervention measures should be implemented as soon as possible based on the stratification results by gender and age,and health education and basic healthcare should be improved to effectively reduce the burden of musculoskeletal diseases.

Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

The risk prediction approach integrating disease and syndrome aligns more precisely with the clinical diagnosis and treatment needs of osteoporosis.Prior research has established a consensus on the model development methodology encompassing"Target outcome selection→ Key information collection→ Data mining and modeling →Model performance evaluation".Building on this foundation,a cohort of osteoporosis patients and syndrome cases with stable follow-up is established.Utilizing artificial intelligence algorithms,critical information in traditional Chinese medicine(TCM)symptoms and syndromes is objectively characterized and quantified alongside imaging data.Employing multi-omics sequencing technology,we seek to identify highly specific microscopic molecular information,analyze potential correlations among various dimensions of information,and develop a multidimensional risk prediction model for osteoporosis with distinctive TCM attributes.This model aims to identify biomarkers with both"disease"and"syndrome"characteristics,thereby advancing the precision diagnosis and treatment system for osteoporosis.

Aim To detect the non-coding RNA(ncRNA)expression profile of neuroglioma cells via whole transcriptome sequencing,establish the ceRNA network and reveal the molecular mechanism of ncRNA participating in the inhibition of neuroglioma cell prolif-eration by melatonin.Methods Neuroglioma cells were intervened with by 0,2,4,6 and 8 mmol·L-1 melatonin for 24,48 and 72 h,and the inhibitory effect of melatonin on cell proliferation was detected via CCK-8;after the intervention of 0 and 4 mmol·L-1 melatonin to U251 cells for 24 h,differentially ex-pressed miRNA(DEmiRNA),lncRNA(DElncRNA)and mRNA(DEmRNA)were detected through whole transcriptome sequencing,along with GO and KEGG enrichment analysis of DEmRNA;the ceRNA network was constructed,and the key gene expression of ceR-NA was verified through qRT-PCR.Results Melato-nin exerts a time-dose-dependent inhibitory effect on the proliferation of neuroglioma cells;a total of 5049 DEmRNA,635 DElncRNA and 146 DEmiRNA in 0 and 4 mmol·L-1 melatonin groups were screened out via whole transcriptome sequencing;DEmRNAs were mainly enriched in cancer-related signaling pathways,such as ferroptosis,mTOR signaling pathway,FoxO signaling pathway and cell cycle;the ceRNA network included 4 lncRNAs,3 miRNAs and 48 mRNAs.As verified through real-time PCR,the expressions of hsa-miR-129-5p,hsa-miR-362-5p,LINC00707 and SLC16A1-AS1 of U251 cells were consistent with the sequencing results,and the gene expression of U87 cells was basically consistent with the sequencing re-sults.Conclusions Melatonin affects cancer-related signaling pathways through the differential expression of ncRNA so as to inhibit the proliferation of U251 cells;the ceRNA network composed of LINC00707,SLC16A1-AS1,hsa-miR-129-5p and hsa-miR-362-5p may take a part in the molecular mechanism of melato-nin in inhibiting neuroglioma cell proliferation.

Objective To investigate the effect of operation mode,thickness,and number of implanted electrode leads on tricuspid regurgitation.Methods This was a single-center retrospective study.Patients who received their first cardiac implantable electronic device at the Second Affiliated Hospital of Harbin Medical University from January 2019 to January 2024 and were followed up within(10±4)months were continuously enrolled.General clinical data,preoperative and outpatient follow-up echocardiography,and other indicators were collected.According to the different operation modes,patients were divided into delivery sheath group,support wire group,and delivery sheath combined support wire group.Under the premise of only one electrode wire crossing the tricuspid valve,according to the different thicknesses of the electrode wire,they were divided into 3830 69 group(4.1 F),5076 58/Solia S60 group(7 F),and 6935M-65cm defibrillator group(9 F).The number of electrode wires was divided into 3830 69 subgroup and 6935M-65cm defibrillator subgroup under the premise of balanced operation mode and electrode material.The changes in tricuspid valve regurgitation were compared in each group.Results A total of 219 patients,aged(65.92±12.04)years,were enrolled.There was no difference in tricuspid valve regurgitation in the 6935M-65cm defibrillator subgroup before implantation(all P＞0.05).In the 3830 69 subgroup,there was a higher proportion of severe regurgitation in the two-electrode group before implantation(P=0.013).In comparison with the change in tricuspid valve regurgitation before electrode wire implantation and during follow-up,the regurgitation of the tricuspid valve in the 6935M-65cm defibrillator subgroup with≥2 electrodes was unexpectedly improved compared to that in the group with one electrode,and the regurgitation of the valve in the group with one electrode was more severe than that in the group with ≥ 2 electrodes implantation(P=0.019).Conclusions The operation mode and thickness of the implanted electrode lead did not cause significant differences in tricuspid valve regurgitation.Single implantation of a 6935M-65cm defibrillator electrode will lead to increased tricuspid regurgitation,and the effect brought by combination with physiological pacing will offset the adverse effects of electrode leads on the valve,providing directional evidence for future implantation strategy selection.