Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Objective To evaluate the effects of low-dose intrathecal morphine(ITM)combined with liposomal bupivacaine adductor canal block(LB-ACB)on postoperative analgesia and opioid-sparing efficacy in patients undergoing total knee arthroplasty(TKA).Methods In this randomized,double-blind,controlled trial,80 TKA patients were allocated to either an intervention group(ITM 0.1 mg+LB-ACB,n=40)or a control group(intrathecal saline+LB-ACB,n=40).Primary outcomes included resting/movement visual analog scale(VAS)scores at 6,12,24,48,and 72 hours postoperatively,48-hour morphine consumption,time to first rescue analgesia,and incidence of complications.Results(1)The intervention group showed significantly lower resting and movement VAS scores at 6,12,24,and 48 hours postoperatively compared with controls(all P<0.05),except at 72 hours(P>0.05).(2)The intervention group had a significant reduction in 48-hour morphine consumption(4.58±1.0 mg vs.9.34±4.8 mg,P=0.027),a significantly lower rescue analgesia rate(15.0%vs.47.5%,P=0.002),and a significantly prolonged time to first rescue analgesia(48.8±7.5 h vs.14.5±5.5 h,P<0.001).(3)The intervention group demonstrated a significant decrease in the incidence of nausea(from 15.0%to 35.0%,P=0.039)and vomiting(from 10.0%to 27.5%,P=0.045),but no significant differences were observed in the incidences of pruritus,urinary retention,or motor block(all P>0.05).Conclusion Low-dose ITM(0.1 mg)combined with LB-ACB significantly enhances early postoperative analgesia,reduces opioid consumption,and decreases nausea/vomiting risk,without increasing the risks of other complications.This regimen aligns with enhanced recovery after surgery(ERAS)principles.

Objective:To analyze the impact of the universal coverage,integration and DRG/DIP payment method reform of Basic Medical Insurance(BMI)on the equity of the health service utilization and resource allocation.Methods:The 1998-2022 panel data on health service utilization and resources were collected for China.Health equity is measured using the Concentration Index(CI)and Theil index,and the impact of BMI reform on health equity is analyzed by BP neural network and ITSA.Results:Universal coverage,integration,and DRG/DIP payment reform of BMI had a positive effect on the number of health workers,beds,and admissions(P＜0.001),and inhibited the growth of per capita hospitalization costs(P＜0.05).The CI for the number of health workers and beds declined by 0.004 and 0.003 per year after universal coverage of BMI;and both still declined by 0.002 per year with a 5-year lag(P＜0.05).The CI for the hospital admissions fell by 0.014 immediately after the DRG/DIP payment reform and by 0.012 per year thereafter(P＜0.001).Conclusion:BMI reforms not only can contribute to improve the health service utilization and resources,but also it can also improve health equity.In addition,it has a lagged effect on improving health equity.

Randomized controlled trials have long been regarded as the gold standard for evaluating vaccine efficacy. However, conducting randomized controlled trials to assess vaccines in real-world settings is often impractical due to limitations in research resources and ethical considerations. In recent years, the emulated target trial has emerged as a novel methodological framework that applies the design principles of randomized trials to observational studies. By using observational data to emulate the randomization and treatment assignment of a clinical trial, this approach enables the evaluation of vaccine effectiveness in the real world. The application of emulated target trials enhances the quality and applicability of real-world evidence. This article explains the fundamental principles, design elements, advantages, and limitations of using emulated target trials to evaluate vaccine effectiveness, providing methodological guidance for conducting such studies in China.

Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Randomized controlled trials have long been regarded as the gold standard for evaluating vaccine efficacy. However, conducting randomized controlled trials to assess vaccines in real-world settings is often impractical due to limitations in research resources and ethical considerations. In recent years, the emulated target trial has emerged as a novel methodological framework that applies the design principles of randomized trials to observational studies. By using observational data to emulate the randomization and treatment assignment of a clinical trial, this approach enables the evaluation of vaccine effectiveness in the real world. The application of emulated target trials enhances the quality and applicability of real-world evidence. This article explains the fundamental principles, design elements, advantages, and limitations of using emulated target trials to evaluate vaccine effectiveness, providing methodological guidance for conducting such studies in China.

Objective:To analyze the impact of the universal coverage,integration and DRG/DIP payment method reform of Basic Medical Insurance(BMI)on the equity of the health service utilization and resource allocation.Methods:The 1998-2022 panel data on health service utilization and resources were collected for China.Health equity is measured using the Concentration Index(CI)and Theil index,and the impact of BMI reform on health equity is analyzed by BP neural network and ITSA.Results:Universal coverage,integration,and DRG/DIP payment reform of BMI had a positive effect on the number of health workers,beds,and admissions(P＜0.001),and inhibited the growth of per capita hospitalization costs(P＜0.05).The CI for the number of health workers and beds declined by 0.004 and 0.003 per year after universal coverage of BMI;and both still declined by 0.002 per year with a 5-year lag(P＜0.05).The CI for the hospital admissions fell by 0.014 immediately after the DRG/DIP payment reform and by 0.012 per year thereafter(P＜0.001).Conclusion:BMI reforms not only can contribute to improve the health service utilization and resources,but also it can also improve health equity.In addition,it has a lagged effect on improving health equity.

Objective To evaluate the effects of low-dose intrathecal morphine(ITM)combined with liposomal bupivacaine adductor canal block(LB-ACB)on postoperative analgesia and opioid-sparing efficacy in patients undergoing total knee arthroplasty(TKA).Methods In this randomized,double-blind,controlled trial,80 TKA patients were allocated to either an intervention group(ITM 0.1 mg+LB-ACB,n=40)or a control group(intrathecal saline+LB-ACB,n=40).Primary outcomes included resting/movement visual analog scale(VAS)scores at 6,12,24,48,and 72 hours postoperatively,48-hour morphine consumption,time to first rescue analgesia,and incidence of complications.Results(1)The intervention group showed significantly lower resting and movement VAS scores at 6,12,24,and 48 hours postoperatively compared with controls(all P<0.05),except at 72 hours(P>0.05).(2)The intervention group had a significant reduction in 48-hour morphine consumption(4.58±1.0 mg vs.9.34±4.8 mg,P=0.027),a significantly lower rescue analgesia rate(15.0%vs.47.5%,P=0.002),and a significantly prolonged time to first rescue analgesia(48.8±7.5 h vs.14.5±5.5 h,P<0.001).(3)The intervention group demonstrated a significant decrease in the incidence of nausea(from 15.0%to 35.0%,P=0.039)and vomiting(from 10.0%to 27.5%,P=0.045),but no significant differences were observed in the incidences of pruritus,urinary retention,or motor block(all P>0.05).Conclusion Low-dose ITM(0.1 mg)combined with LB-ACB significantly enhances early postoperative analgesia,reduces opioid consumption,and decreases nausea/vomiting risk,without increasing the risks of other complications.This regimen aligns with enhanced recovery after surgery(ERAS)principles.

Objective To explore the mechanism by which She-Ti-Zhi-Qiu decoction alleviates allergic rhinitis (AR) through gut microbiota-mediated regulation of T helper cell 17(Th17)/regulatory T cells(Treg) balance and related cytokines. Methods Twenty-eight female SD rats were randomly divided into four groups: the Control group, Model group, STZQ group, and Probiotics group. Except for the Control group, all other groups were sensitized with ovalbumin (OVA) to establish AR models. The Control and Model groups received intragastric administration of normal saline, while the STZQ group was administered She-Ti-Zhi-Qiu Decoction, and Probiotics group received probiotics. After two weeks of continuous intragastric administration, nasal mucosa, serum, peripheral blood, and colon contents were collected. The inflammation of nasal mucosal tissue was assessed via HE staining. 16S rDNA sequencing was used to detect and analyze the structure and content of bacteria in colon contents. Flow cytometry was used to detect the relative proportions of Treg and Th17 cells in peripheral blood. ELISA was used to measure the levels of Th17- and Treg-related cytokines in serum. Results Compared with the Control group, the Model group showed an inflammatory response in nasal mucosal tissue, along with increased IL-17A and IL-17E levels and decreased IL-10 levels. The percentage of Th17 cells in peripheral blood increased, while the percentage of Treg cells decreased. Beneficial bacteria in the intestine were decreased, while pathogenic bacteria were increased. Compared with the Model group, the STZQ group showed lower serum IL-17A and IL-17E levels and higher IL-10 levels. The percentage of Th17 in peripheral blood decreased, while the percentage of Treg increased. There was an increase in beneficial bacteria in the intestine and a decrease in pathogenic bacteria. The changes in the microbiota were correlated with IL-17A, IL-17E, and IL-10 levels. Conclusion She-Ti-Zhi-Qiu decoction can ameliorate the inflammation of AR by regulating gut microbiota and Th17/Treg immune balance.
Animals ; T-Lymphocytes, Regulatory/drug effects* ; Th17 Cells/drug effects* ; Gastrointestinal Microbiome/drug effects* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/therapeutic use* ; Female ; Rhinitis, Allergic/microbiology* ; Rats ; Cytokines