AIM: To investigate the distribution characteristics of pathogens in patients with post-traumatic infectious endophthalmitis(PTIE)and their relationship with serum levels of macrophage inflammatory protein 1α(MIP-1α), heat shock protein 70(HSP70), and soluble triggering receptor expressed on myeloid cells 1(sTREM-1).METHODS:A total of 157 patients with PTIE from the Handan City Eye Hospital(The Third Hospital of Handan)from May 2023 to May 2025 were selected as the study group. They were divided into a good prognosis group and a poor prognosis group based on their uncorrected visual acuity at discharge. Meanwhile, 157 patients with ocular trauma but without endophthalmitis during the same period were selected as control group 1, and 157 healthy volunteers who underwent physical examinations during the same period were selected as control group 2. Aqueous humor and vitreous fluid samples were collected from the study group to detect the distribution of pathogens. The levels of serum MIP-1α, HSP70, and sTREM-1 were measured using the enzyme-linked immunosorbent assay. Multivariate Logistic regression analysis was performed to identify risk factors for poor prognosis. The predictive value of serum MIP-1α, HSP70, and sTREM-1 levels for poor prognosis was evaluated using receiver operating characteristic(ROC)and decision curve analysis(DCA).RESULTS: The general data of the participants in the three groups was comparable. A total of 173 pathogens were detected in the 157 patients with PTIE, with Gram-positive bacteria being the predominant type. The levels of serum MIP-1α and sTREM-1 in the study group were higher than those in control groups 1 and 2, while the level of HSP70 was lower than those in control groups 1 and 2(all P<0.05). There were no significant differences in the levels of serum MIP-1α, HSP70, and sTREM-1 between control groups 1 and 2(all P>0.05). In the poor prognosis group, the time of wound suture was ≥24 h, the wound location was in zones II/III, the type of trauma was rupture, the proportion of rupture injuries, and the levels of serum C-reactive protein, MIP-1α, and sTREM-1 were higher than those in the good prognosis group, while the level of HSP70 was decreased(all P<0.001). Multivariate Logistic regression analysis showed that the time of wound suture, wound location, type of trauma, C-reactive protein, MIP-1α, HSP70, and sTREM-1 were risk factors for poor visual prognosis in patients with PTIE(all P<0.05). The ROC curve results showed that the combined prediction of serum MIP-1α, HSP70, and sTREM-1 for poor visual prognosis in PTIE patients had an AUC value of 0.965, which was significantly higher than that of individual predictions(ZMIP-1α, ZHSP70, ZsTREM-1=3.628, 4.705, 3.930, all P<0.05). Additionally, the DCA curve showed that the combined prediction had a higher net benefit rate than individual predictions in the high-risk threshold range of 0.03-0.97.CONCLUSION:Gram-positive bacteria are the predominant type of pathogenic bacteria in patients with PTIE, with elevated levels of serum MIP-1α and sTREM-1 and decreased levels of HSP70. The combined detection of these three factors has a high predictive efficacy for visual prognosis in patients.

Objectives:To analyze the disease burden and trends of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and provide a basis for disease prevention and management.Methods:Based on the Global Burden of Disease(GBD)2021 data,we compared the age-standardized mortality rate(ASMR)and age-standardized disability-adjusted life year rate(ASDR)of ischemic stroke attributable to major metabolic risk factors(including overweight/obesity,hypertension,elevated low-density lipoprotein cholesterol,low bone density,hyperglycemia,and impaired renal function)in China and globally,and estimated their time trends through estimated annual percentage change(EAPC).We also analyzed the number of deaths,mortality rate,disability adjusted life year(DALY),and DALY rate of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and compared the epidemiological differences among different gender and age groups.Results:From 1990 to 2021,the disease burden of ischemic stroke attributable to major metabolic risk factors in China showed a slight upward trend(1990 to 2005)and then gradually decreased,with a relatively small overall decline.,while the global disease burden showed a decreasing trend.In 2021,the ASMR and ASDR of ischemic stroke attributable to major metabolic risk factors in China were 48.11/100 000 and 898.35/100 000(EAPC[95%CI]were-0.24%[-1.13%to 0.66%]and-0.25%[-1.00%to 0.51%]),respectively,both higher than the global average levels(33.96/100 000 and 651.46/100 000,EAPC[95%CI]were-1.75%[-2.03%to 1.47%]and-1.49%[-1.74%to-1.23%],respectively).Compared with 1990,the actual mortality rate and DALY rate of ischemic stroke attributable to major metabolic risk factors in China increased by 139.60%and 110.53%respectively in 2021.There are gender differences in the disease burden of ischemic stroke attributable to major metabolic risk factors in China,with significantly higher death numbers,mortality rates,DALY,and DALY rates in males compared to females.At the age level,DALY and DALY rates were both higher in individuals aged 15-49,DALY increased but DALY rates decreased in individuals aged 50-69.DALY surged in individuals aged 70 and above,male DALY rates showed increasing trend and female DALY rates showed slightly decreasing trend.Conclusions:The disease burden of ischemic stroke in China is significantly affected by metabolic risk factors.Although prevention and control have achieved certain positive results,the overall disease burden in China is higher than that of the world,and precise intervention strategies need to be developed for different genders and ages in China.

Objective To construct an MRI radiomics model of cerebral damage following carbon monoxide(CO)poisoning.Methods Ninety patients with CO poisoning and 70 healthy controls(HC)were scanned by structural MRI.All patients were randomly divided into training set(n=128)and test set in a ratio of 8∶2.The radiomics features of 9 regions of interest(ROI)were automatically extracted,and each ROI was subjected to 5-fold cross-validation and 9 different types of classifiers to construct a diagnostic model.Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the diagnostic efficacy and clinical value of the model.Results The model based on the radiomics features of the whole brain gray matter(GM)and the left globus pallidus(LGP)had better diagnostic efficacy and clinical application value.The area under the curve(AUC)in the training set and the test set were 0.813,0.815 and 0.806,0.806,respectively.Conclusion The GM-based radiomics model can effectively diagnose cerebral damage following CO poisoning.

This study aims to simultaneously detect three antibiotic resistance genes(blaNDM,mcr-1 and cfr).A triplex fluorescence quantitative PCR method was established.Plasmids,primers and probes were designed and optimized.The method could specifically detect blaNDM,mcr-1 and cfr,but not other antibiotic resistance genes.The R2 of the standard curves of the three antibiotic re-sistance genes were all greater than 0.999,and the coefficients of variation were all lower than 1％.The lowest detection limits of the plasmids were 1 × 102 copies/μL.This method was used to de-tect 800 bacterial samples.The results showed that 32 samples contained mcr-1 gene,40 samples contained blaNDM gene,2 samples contained cfr gene,8 samples contained both mcr-1 and blaNDM genes.There were no samples carrying three antibiotic resistance genes detected.The results indica-ted that the triplex fluorescence quantitative PCR method established in this experiment had the advantages of high sensitivity,specificity and stability.It was suitable for rapid detection of blaNDM,mcr-1 and cfr antibiotic resistance genes in clinical practice.It provided a convenient and quick method basis for the detection of antibiotic resistance genes.

Objective We apply a class imbalance treatment method that can solve the between-class imbalance problem and the within-class imbalance problem of the minority class and the majority class at the same time.And combining it with RF classifier to achieve early recurrence prediction in DLBLC patients,which provided a reference for the treatment of DLBLC patients.Methods Firstly,we apply a class imbalance processing method based on Gaussian mixture model bi-directional clustering resampling to process the data.And compared with ROS,SMOTE,Borderline-1 SMOTE,Borderline-2 SMOTE,GMM oversampling,GMM undersampling,SMOTE+RUS,SMOTE+GMM and GMM+RUS.Afterwards,in order to verify the performance of RF,we use logistic regression and decision tree models as controls.Finally,the evaluation of the model is carried out in terms of discrimination and calibration.Results The RF model with GMM-GMM resampling achieved relatively optimal classification performance(accuracy=0.79,AUC=0.87,sensitivity=0.71,specificity=0.87,G-means=0.79,MSE=0.21).Conclusion GMM-GMM is superior to other traditional resampling methods,and combining it with the RF model for the prediction of early recurrence in DLBCL patients has achieved relatively good classification results,which can well realize the prediction of early recurrence in DLBCL patients.

Objective:To develop a simplified confocal laser endomicroscopy (CLE)-based healing scoring system for assistant diagnosis of deep remission in ulcerative colitis (UC).Methods:CLE images from consecutive UC patients in clinical remission or mild activity and healthy controls undergoing CLE at Peking University First Hospital from January 2017 to December 2019 were retrospectively analyzed. According to the diagnosis of inflammation in intestinal segments in the medical records of UC patients, CLE images were divided into two groups, the involved group (inflamed UC segment) and the control group (segments from healthy individuals and non-inflamed UC segments). CLE features differentiating the groups were identified, and univariable regression analysis was used to obtain indicators related to unhealed histological inflammation (Geboes score>2.0), forming a simplified CLE healing score using the significant indicators, and receiver operator characteristic (ROC) curve was drawn.Results:The study included 53 UC patients and 14 healthy controls, yielding 201 CLE segments (42 healthy, 69 non-inflamed, 90 inflamed). Eight CLE features differed significantly between the involved and the control groups ( P<0.001), including crypt distortion, crypt lumen irregularity, crypt proximity, crypt sparsity, crypt lumen fluorescein leakage, vascular fluorescein leakage, increased vessel diameter, and cellular infiltration. Univariable regression analysis indicated there were 4 indicators related to histological inflammation, including crypt distortion ( P=0.025, OR=3.613, 95% CI:1.174-11.114), crypt lumen irregularity ( P=0.021, OR=4.081, 95% CI: 1.233-13.511), crypt fluorescein leakage ( P=0.011, OR=5.486, 95% CI: 1.468-20.494) and increased vessel diameter ( P=0.002, OR=7.724, 95% CI: 2.062-28.938). These 4 indicators were combined to form a simplified CLE healing score and a ROC curve was plotted with AUC of 0.769 (95% CI:0.654-0.833). The optimal threshold for histological healing was the absence of all four features (score=0), with sensitivity and specificity of 83.1% (59/71) and 42.1% (8/19), respectively. Conclusion:The simplified CLE score demonstrates high sensitivity and correlates positively with histological healing, supporting its utility as an adjunct tool for assessing deep remission in UC.

Objective We apply a class imbalance treatment method that can solve the between-class imbalance problem and the within-class imbalance problem of the minority class and the majority class at the same time.And combining it with RF classifier to achieve early recurrence prediction in DLBLC patients,which provided a reference for the treatment of DLBLC patients.Methods Firstly,we apply a class imbalance processing method based on Gaussian mixture model bi-directional clustering resampling to process the data.And compared with ROS,SMOTE,Borderline-1 SMOTE,Borderline-2 SMOTE,GMM oversampling,GMM undersampling,SMOTE+RUS,SMOTE+GMM and GMM+RUS.Afterwards,in order to verify the performance of RF,we use logistic regression and decision tree models as controls.Finally,the evaluation of the model is carried out in terms of discrimination and calibration.Results The RF model with GMM-GMM resampling achieved relatively optimal classification performance(accuracy=0.79,AUC=0.87,sensitivity=0.71,specificity=0.87,G-means=0.79,MSE=0.21).Conclusion GMM-GMM is superior to other traditional resampling methods,and combining it with the RF model for the prediction of early recurrence in DLBCL patients has achieved relatively good classification results,which can well realize the prediction of early recurrence in DLBCL patients.

Objective:To investigate the clinical efficacy of autologous adipose-derived stem cell gel (SVF-gel) grafting in the treatment of depressed acne scars.Methods:A retrospective analysis was conducted on data collected from 28 patients who underwent SVF-gel grafting treatment for depressed acne scars in the Department of Dermatology, Xijing Hospital, Air Force Medical University from October 2018 to May 2021. There were 17 males and 11 females, aged 17 - 38 (26 ± 4.86) years. As for clinical types, 8 patients were diagnosed with boxcar acne scars, 14 with rolling acne scars, and 6 with acne scars with characteristics of the two types. The clinical acne scar weighted scale (ECCA scale) was used to evaluate the appearance improvement after the treatment, and patients′ subjective satisfaction scores and incidence of adverse reactions were recorded.Results:After the SVF-gel grafting, the facial appearance of patients with depressed acne scars significantly improved, and the ECCA scores significantly decreased 6 months after surgery (before surgery: 52.5 ± 15.8 points; 6 months after surgery: 23.8 ± 10.2 points; t = 11.68, P < 0.001). The subjective satisfaction rate of patients was 82.14% (23/28), the incidence rate of adverse reactions was 17.86% (5/28), and 5 patients experienced mild inflammatory reactions after surgery, including 2 with subcutaneous nodules. The secondary grafting rate was 67.86% (19/28) . Conclusion:The SVF-gel grafting was markedly effective for the treatment of depressed acne scars, which is worthy of clinical promotion and application.

Objectives:To analyze the disease burden and trends of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and provide a basis for disease prevention and management.Methods:Based on the Global Burden of Disease(GBD)2021 data,we compared the age-standardized mortality rate(ASMR)and age-standardized disability-adjusted life year rate(ASDR)of ischemic stroke attributable to major metabolic risk factors(including overweight/obesity,hypertension,elevated low-density lipoprotein cholesterol,low bone density,hyperglycemia,and impaired renal function)in China and globally,and estimated their time trends through estimated annual percentage change(EAPC).We also analyzed the number of deaths,mortality rate,disability adjusted life year(DALY),and DALY rate of ischemic stroke attributable to major metabolic risk factors in China from 1990 to 2021,and compared the epidemiological differences among different gender and age groups.Results:From 1990 to 2021,the disease burden of ischemic stroke attributable to major metabolic risk factors in China showed a slight upward trend(1990 to 2005)and then gradually decreased,with a relatively small overall decline.,while the global disease burden showed a decreasing trend.In 2021,the ASMR and ASDR of ischemic stroke attributable to major metabolic risk factors in China were 48.11/100 000 and 898.35/100 000(EAPC[95%CI]were-0.24%[-1.13%to 0.66%]and-0.25%[-1.00%to 0.51%]),respectively,both higher than the global average levels(33.96/100 000 and 651.46/100 000,EAPC[95%CI]were-1.75%[-2.03%to 1.47%]and-1.49%[-1.74%to-1.23%],respectively).Compared with 1990,the actual mortality rate and DALY rate of ischemic stroke attributable to major metabolic risk factors in China increased by 139.60%and 110.53%respectively in 2021.There are gender differences in the disease burden of ischemic stroke attributable to major metabolic risk factors in China,with significantly higher death numbers,mortality rates,DALY,and DALY rates in males compared to females.At the age level,DALY and DALY rates were both higher in individuals aged 15-49,DALY increased but DALY rates decreased in individuals aged 50-69.DALY surged in individuals aged 70 and above,male DALY rates showed increasing trend and female DALY rates showed slightly decreasing trend.Conclusions:The disease burden of ischemic stroke in China is significantly affected by metabolic risk factors.Although prevention and control have achieved certain positive results,the overall disease burden in China is higher than that of the world,and precise intervention strategies need to be developed for different genders and ages in China.

Objective To construct an MRI radiomics model of cerebral damage following carbon monoxide(CO)poisoning.Methods Ninety patients with CO poisoning and 70 healthy controls(HC)were scanned by structural MRI.All patients were randomly divided into training set(n=128)and test set in a ratio of 8∶2.The radiomics features of 9 regions of interest(ROI)were automatically extracted,and each ROI was subjected to 5-fold cross-validation and 9 different types of classifiers to construct a diagnostic model.Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the diagnostic efficacy and clinical value of the model.Results The model based on the radiomics features of the whole brain gray matter(GM)and the left globus pallidus(LGP)had better diagnostic efficacy and clinical application value.The area under the curve(AUC)in the training set and the test set were 0.813,0.815 and 0.806,0.806,respectively.Conclusion The GM-based radiomics model can effectively diagnose cerebral damage following CO poisoning.