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.

[Objective]To investigate and explore the characteristics and influencing factors of glucose metabolism in children with β-thalassemia major(β-TM)after allogeneic hematopoietic stem cell transplantation(allo-HSCT).[Methods]The follow-up data of 41 patients with β-TM who underwent HSCT at Hematopoietic Stem Cell Transplantation Department of Children's Medical Center of Sun Yat-sen Memorial Hospital,Sun Yat-sen University were retrospectively analyzed.Their glucose metabolism characteristics were evaluated through laboratory tests and the related influencing factors were analyzed.[Results]In the study,41.46％(17/41)of patients developed abnormal glucose homeostasis after HSCT.Among them,82.35％(14/17)characterized by insulin resistance,but no cases of diabetes mellitus were found.The results of insulin releasing test and oral glucose tolerance test(OGTT)showed that 45.00％(9/20)of patients had abnormal insulin releasing curve and 40.0％(8/20)had delayed serum glucose peak.The average age of HSCT in abnormal glucose homeostasis group was significantly older than that in the normal glucose homeostasis group[(8.8±3.9)years old vs(6.0±3.1)years old,P=0.015].[Conclusions]Patients with β-TM after HSCT may develop abnormal glucose homeostasis,consists largely of insulin resistance.The elder age of HSCT(≥7 years old)is a risk factor for abnormal glucose homeostasis in β-TM patients after HSCT.It is recommended to regularly monitor glucose metabolism indicators in β-TM children after HSCT,especially in elderly transplant recipients.

Objective To establish a laser diffraction method for determining globule size distribution in medium and long chain fat emulsion injection(C8～24Ve).Methods The Mastersizer 3000 laser particle size analyzer and Hydro EV wet sampling device were used,with water as the dispersion medium.Critical parameters,including refractive index,absorption coefficient,obscuration,measurement duration,stirring speed,and sonication parameters,were systematically optimized.Comparative evaluations were conducted across different computational models(Mie vs.Fraunhofer theories)and instrument platforms.Results The optimized optical parameters for particle size distribution analysis of medium and long chain fat emulsion injection(C8～24Ve)were determined as follows:absorption rate 0.001,refractive index 1.52,measurement duration 10 s,stirring speed 1 200 r·min-1,with no sonication applied.Under these conditions,the method demonstrated satisfactory precision,repeatability,and robustness.Conclusions This method demonstrates operational simplicity,high accuracy,and excellent reproducibility,making it suitable for particle size distribution analysis of medium and long chain fat emulsion injection(C8～24Ve).The established protocol provides a valuable reference for the development of particle size determination methods for emulsion formulations.

Objective:To explore the capability of deep learning image reconstruction (DLIR) compared to adaptive statistical iterative reconstruction (ASiR-V) in improving the image quality and myocardial edge sharpness of dynamic stress myocardial CT perfusion imaging (CTP).Methods:Thirty subjects who underwent dynamic stress myocardial CTP at Guangdong Provincial People′s Hospital from September 2023 to February 2024 were recruited. Image data of all enrolled patients were reconstructed using ASiR-V 50%, ASiR-V 80%, medium-intensity DLIR(DLIR-M), and high-intensity DLIR(DLIR-H), respectively. Regions of interest were selected in the left ventricular cavity, interventricular septum, and left ventricular lateral wall for measurement of CT values and standard deviations (SD), and calculation of signal to noise ratio (SNR) and contrast to noise ratio (CNR). Matlab was utilized to obtain the differences (d) and slopes (s) of CT value changes at four left ventricular myocardial edges for objective edge sharpness evaluation. Two radiologists subjectively scored the images for noise, natural appearance, and edge sharpness. In case of disagreement between the two radiologists, a third senior radiologist′s score was decisive. Left ventricular myocardial blood flow (MBF) of ASiR-V and DLIR images with lower SD, higher SNR and CNR were calculated, respectively. When the normal distribution was satisfied, the independent sample t test was used for comparison between two groups, and the random block design ANOVA was used for comparison between multiple groups. And analysis was conducted using Friedman test for non-normally distributed data, and Bonferroni correction for pairwise comparisons. Results:There were statistically significant differences in SD, SNR, and CNR among the four images in the interventricular septum and left ventricular lateral wall (all P<0.05), with ASiR-V 80% and DLIR-H demonstrating the lowest SD, highest SNR and CNR, and the subjective image noise score. Statistically significant differences were observed in d and s for the four left ventricular myocardial edges (all P<0.05), with DLIR-M and DLIR-H exhibiting the best objective edge sharpness [5 (5, 5)], and ASiR-V 80% the worst [3.5 (3, 4)]. In the subjective scores for natural appearance, DLIR-M and DLIR-H received the highest scores [5 (5, 5)], while ASiR-V 80% received the lowest scores [3 (3, 4)], with statistically significant differences (all P<0.05). There was no statistically significant difference in MBF values calculated from ASiR-V 80% and DLIR-H images (all P>0.05). Conclusions:The SD value, SNR and CNR of dynamic stress myocardial CTP images reconstructed by DLIR-H are equivalent to ASiR-V 80%, and using DLIR-H can improve the edge sharpness of left ventricular myocardium without affecting the calculation of MBF.

Mitochondrial transcription factor B1(TFB1M)is mainly involved in mitochondrial DNA transcription and related to the development of hepatocellular carcinoma and breast cancer.However,its role in colon cancer is unclear.In this study,the expression level of TFB1M in colon cancer and its prognosis were analyzed based on TCGA and other databases and IHC assays.Differentially expressed genes(DEGs)were screened and subjected to the analysis of functional enrichment,mutation analysis,immune cell infiltration,and drug sensitivity analysis.CCK-8 and flow cytometry were used to detect the effects of overexpression of TFB1M on the viability,apoptosis and cell cycle distribution of colon cancer cells.Our results showed that the expression level of TFB1M was significantly up-regulated in colon canc-er,and its expression level was correlated with the N stage and TNM stage(P＜0.05).The prognosis of colorectal cancer patients in the high TFB1M expression group was worse.Functional enrichment results showed that TFB1M was related to leukocyte-mediated immunity,immunoglobulin production and other signaling pathways.Mutation results showed that high-frequency mutated genes,such as ZFHX4,RYR2,PIK3CA and FAT4,had significantly higher mutation frequencies in the TFB1M high-expression group(all P＜0.05).In addition,the expression level of TFB1M was significantly higher in the PIK3CA and FAT4 mutation groups(all P＜0.05).Immune infiltration results showed that the percentage of CD4+memory activated T cells was increased in the TFB1M high expression group,while the percentage of Treg cells was reduced.The drug sensitivity results showed that patients in the TFB1M high expression group might be more sensitive to Tozasertib,cytarabine,vincristine,etc.,while patients in the TFB1M low expression group might be more sensitive to Dasatinib,JQ1,ERK_2440,etc.The results of cellular experiments showed that over-expression of TFB1M enhanced viability,reduced apoptosis and increased the percentage of S-phase and G2/M-phase cells in colon cancer cells.Altogether,the results indicated that TFB1M might play a key role in the growth of colon cancer cells by regulating immune cell infiltration and function.

Objective:To analyze serum inflammatory factors associated with antihistamine resistance in patients with chronic spontaneous urticaria (CSU) .Methods:A total of 88 CSU patients were enrolled from Guangzhou Dermatology Hospital from January 2022 to December 2024. All patients received antihistamine treatment according to the "Guideline for diagnosis and treatment of urticaria in China (2022) " . Based on the 7-day urticaria activity score (UAS7) after 4-week treatment, these patients were divided into an antihistamine-sensitive group and an antihistamine-resistant group. Serum levels of inflammatory factors at the initial visit were analyzed using the Olink-targeted proteomics technology. Specific biomarkers associated with antihistamine resistance were identified, and Spearman correlation analysis was carried out to analyze correlations among differentially expressed proteins. A logistic regression model was constructed based on the Olink proteomics data, and the predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis. Measurement data were expressed as mean ± standard deviation or median (lower quartile, upper quartile) .Results:The 88 CSU patients aged 12 to 81 (38.78 ± 13.89) years, with the disease duration being 18 (7.00, 60.00) months. There were 32 patients in the antihistamine-sensitive group and 56 in the antihistamine-resistant group. No significant differences were found between the two groups in terms of age, disease duration, gender, or history of allergic diseases (all P > 0.05) . After 4 weeks of antihistamine treatment, the UAS7 score was significantly higher in the antihistamine-resistant group (25.00 [15.25, 31.00] points) than in the antihistamine-sensitive group (0.50 [0.00, 4.00] points; Z = -7.08, P < 0.001) . The Olink-targeted proteomics identified 5 differentially expressed proteins between the two groups: compared with the antihistamine-sensitive group, the antihistamine-resistant group showed > 2-fold higher expression of fibroblast growth factor 19 (FGF19) , interleukin-15 receptor subunit alpha (IL-15RA) , eotaxin (CCL11) , and monocyte chemoattractant protein-1 (MCP-1) ; in contrast, the expression of sulfotransferase 1A1 (ST1A1) in the antihistamine-sensitive group was 2.54 times that in the antihistamine-resistant group. Among the differentially expressed proteins, MCP-1 showed the highest specificity (1.00) for predicting antihistamine resistance, followed by CCL11 (0.97) . Correlation analysis revealed a significant positive correlation between MCP-1 and CCL11, and a significant negative correlation between IL-15RA and ST1A1. ROC curve analysis showed that MCP-1 and CCL11 had area under the curve values of 0.603 and 0.630, respectively, in predicting antihistamine resistance. Conclusion:MCP-1 and CCL11 may be potential biomarkers for predicting antihistamine resistance in CSU patients.

Objective:To analyze serum inflammatory factors associated with antihistamine resistance in patients with chronic spontaneous urticaria (CSU) .Methods:A total of 88 CSU patients were enrolled from Guangzhou Dermatology Hospital from January 2022 to December 2024. All patients received antihistamine treatment according to the "Guideline for diagnosis and treatment of urticaria in China (2022) " . Based on the 7-day urticaria activity score (UAS7) after 4-week treatment, these patients were divided into an antihistamine-sensitive group and an antihistamine-resistant group. Serum levels of inflammatory factors at the initial visit were analyzed using the Olink-targeted proteomics technology. Specific biomarkers associated with antihistamine resistance were identified, and Spearman correlation analysis was carried out to analyze correlations among differentially expressed proteins. A logistic regression model was constructed based on the Olink proteomics data, and the predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis. Measurement data were expressed as mean ± standard deviation or median (lower quartile, upper quartile) .Results:The 88 CSU patients aged 12 to 81 (38.78 ± 13.89) years, with the disease duration being 18 (7.00, 60.00) months. There were 32 patients in the antihistamine-sensitive group and 56 in the antihistamine-resistant group. No significant differences were found between the two groups in terms of age, disease duration, gender, or history of allergic diseases (all P > 0.05) . After 4 weeks of antihistamine treatment, the UAS7 score was significantly higher in the antihistamine-resistant group (25.00 [15.25, 31.00] points) than in the antihistamine-sensitive group (0.50 [0.00, 4.00] points; Z = -7.08, P < 0.001) . The Olink-targeted proteomics identified 5 differentially expressed proteins between the two groups: compared with the antihistamine-sensitive group, the antihistamine-resistant group showed > 2-fold higher expression of fibroblast growth factor 19 (FGF19) , interleukin-15 receptor subunit alpha (IL-15RA) , eotaxin (CCL11) , and monocyte chemoattractant protein-1 (MCP-1) ; in contrast, the expression of sulfotransferase 1A1 (ST1A1) in the antihistamine-sensitive group was 2.54 times that in the antihistamine-resistant group. Among the differentially expressed proteins, MCP-1 showed the highest specificity (1.00) for predicting antihistamine resistance, followed by CCL11 (0.97) . Correlation analysis revealed a significant positive correlation between MCP-1 and CCL11, and a significant negative correlation between IL-15RA and ST1A1. ROC curve analysis showed that MCP-1 and CCL11 had area under the curve values of 0.603 and 0.630, respectively, in predicting antihistamine resistance. Conclusion:MCP-1 and CCL11 may be potential biomarkers for predicting antihistamine resistance in CSU patients.

BACKGROUND:The repair process of myocardial injury involves complex cellular and molecular mechanisms,especially mitochondrial calcium homeostasis,macrophage autophagy and pyroptosis pathways.Traditional Chinese medicine(TCM)has shown significant clinical efficacy in improving myocardial injury,but its mechanism of action needs to be thoroughly investigated. OBJECTIVE:To investigate the role of mitochondrial calcium homeostasis-mediated macrophage autophagy and pyroptosis pathways in myocardial injury,and to summarize the progress of TCM in this field. METHODS:A computerized search was performed for relevant literature from the database inception to March 2024 in the Web of Science,PubMed and CNKI.The search terms were"mitochondrial calcium homeostasis,macrophage autophagy,macrophage pyroptosis,traditional Chinese medicine,myocardial injury,myocardial injury reperfusion"in Chinese and English.Through literature review,we analyzed the relationship between mitochondrial calcium homeostasis and macrophage autophagy and pyroptosis,explored the mechanism of their roles in myocardial injury,and summarized the pathways of multi-targeted,multi-pathway effects of TCM. RESULTS AND CONCLUSION:The maintenance of mitochondrial calcium homeostasis has been found to be closely related to the normal function of cardiomyocytes.Macrophages can participate in the repair process of myocardial injury through autophagy and pyroptosis pathways.Autophagy contributes to cell clearance and regulation of inflammatory response,while pyroptosis affects myocardial repair by releasing inflammatory factors.TCM regulates mitochondrial calcium homeostasis and macrophage function through multiple mechanisms.For example,astragalosid regulates calcium homeostasis by lowering mitochondrial membrane potential and inhibiting cytochrome C,and epimedium glycoside plays a role in reducing β-amyloid deposition.In addition,herbal compounds and single drugs promote myocardial repair by activating or inhibiting specific signaling pathways,such as PI3K/AKT and nuclear factor-κB signaling pathways.Future studies should focus on the interactions between mitochondrial calcium homeostasis,autophagy and pyroptosis pathways,as well as how TCM can exert therapeutic effects through these pathways to provide new strategies and drugs for the treatment of myocardial injury.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

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.