Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

Objective To analyze the application value of multimodal CT imaging parameters in the differentiation of TOAST classification for cerebral infarction.Methods According to the TOAST classification,the selected 103 patients with cerebral infarction were categorized into large-artery atherosclerosis(LAA)group,cardioembolic(CE)group,small-artery occlusion(SAO)group,other determined etiologies(SOD)group,and undetermined etiologies(SUE)group.All patients underwent non-contrast CT scanning and CT angiography.Cerebral angiography was adopted as the gold standard.Results For the LAA,CE,SAO,SOD,and SUE groups,the diagnostic performance of multimodal CT imaging was as followed:true positive rates were 73.17%,45.45%,75.00%,40.00%,and 72.00%;sensitivities were 90.10%,85.71%,92.30%,85.71%,and 90.00%;specificities were 75.00%,75.00%,66.67%,66.67%,and 80.00%;miss rates were 9.09%,28.57%,7.69%,14.28%,and 10.00%;misdiagnosis rates were 25.00%,25.00%,33.33%,33.33%,and 20.00%;positive predictive rates were 93.75%,83.33%,92.31%,85.71%,and 94.74%;and negative predictive rates were 66.67%,60.00%,66.67%,66.67%,and 66.67%,respectively.Kappa test results showed that the multimodal CT imaging findings were highly consistent with the gold standard(Kappa>0.75,P<0.05).Conclusion Multimodal CT imaging technology can effectively assist in the differentiation of TOAST classification for cerebral infarction,thereby improving the accuracy of clinical diagnosis.

Objective:To investigate the correlation between serum calcium binding protein S100A9 levels and lung function in patients with idiopathic pulmonary fibrosis (IPF).Method:A retrospective case-control study was conducted. Forty patients diagnosed with IPF in respiratory department from January 4, 2023, to January 30, 2024 were selected as the IPF group,with a mean age of (65.3±8.4) years old, including 29 males and 11 females. while 50 healthy volunteers receiving health examinations in our physical examination center were enrolled in this study, including 38 males and 12 females, with a mean age of (64.1±6.3) years. The levels of biochemical parameters were assayed with biochemical analyzer. S100A9 levels were determined by Enzyme linked immunosorbent assay. The lung function test results of all participants were recorded. SPSS 19.0 statistical software was used to compare the differences of biomarkers levels between the two groups , Using parameter testing (independent sample t-test) to compare the differences in serum S100A9 levels and lung function between the two groups, the enumeration data were treated with the chi-square test. Pearson correlation analysis was used to evaluate the correlation between S100A9 and lung function, the influencing factors of IPF were analyzed by using multivariate logistic regression model, and receiver operating characteristic (ROC) curve analysis was used to assess the value of Calprotectin S100A9 in predicting IPF. Results:The serum S100A9 levels in the IPF group were significantly higher than those in the healthy control group [(132.47±21.46) pg/ml,(44.75±8.84) pg/ml, t=3.544, P<0.05], forced expiratory volume in one second(FEV1,1.38±0.19) L, forced vital capacity (FVC, 2.38±0.59) L, FEV1/FVC (57.98±6.13), the maximum spontaneous ventilation (MVV, 57.48±7.66) L/min was lower than that of the control group [(3.24±0.65) L, (3.65±0.67) L, (88.77±7.97), (86.34±7.23) L/min, t=3.486,3.393,2.771,3.462, P<0.05]. Serum S100A9 was negatively correlated with FEV1, FVC, FEV1/FVC, and MVV ( r=-0.537,-0.458,-0.489,-0.511, P<0.05), S100A9 was positively correlated with S100A9 in bronchoalveolar lavage fluid and high-resolution CT fibrosis score ( r=0.632, r=0.517, P<0.05).The area under the curve (AUC) of S100A9 for predicting IPF was 0.691. Conclusion:The level of calcium binding protein S100A9 was significantly increased in IPF patients, and was closely related to decreased lung ventilation function and the occurrence of IPF, which might serve as a marker for evaluating pulmonary fibrosis.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective:To analyze the surveillance results of brucellosis in Shanxi Province, to gain a understanding of the epidemic characteristics and changing trend of brucellosis in Shanxi Province, and to provide scientific basis for formulating prevention and control strategies and measures for brucellosis.Methods:The surveillance data of brucellosis in Shanxi Province from Infectious Disease Reporting Information Management System of China Disease Prevention and Control Information System, and the active surveillance results of 5 national brucellosis surveillance sites from 2018 to 2023 were collected for descriptive analysis.Results:From 2018 to 2023, a total of 24 041 cases of human brucellosis were reported in Shanxi Province, with the number of cases increased from 2 800 in 2018 to 5 131 in 2023. The annual reported incidence was 11.22/100 000, ranging from 7.56/100 000 to 14.74/100 000, showing an overall upward trend (χ 2trend = 1 377.43, P < 0.001). The epidemic had affected all counties (cities and districts) in the province, mainly concentrated in Linfen City, Jinzhong City, Datong City, and Shuozhou City, with a total of 13 489 cases of human brucellosis reported, accounting for 56.11%. The population distribution was mainly composed of individuals aged 40 - 69 (17 682 cases), males (18 513 cases), farmers (20 295 cases), and household and unemployed individuals (1 017 cases). The onset of the disease showed obvious seasonality, with the peak time from March to August, accounting for 66.39% (15 961/24 041). A total of 14 130 occupational individuals were investigated at the surveillance sites, and 11 141 underwent serological tests, with a positive rate of 5.25% (585/11 141), including 299 new cases. The positive rate of serological tests was relatively high in Qinyuan County, at 8.51% (241/2 832). Etiological culture was conducted on 338 human blood samples, and 43 strains of Brucella were isolated, with a detection rate of 12.72%. All strains were Brucella melitensis, including 42 strains of Brucella melitensis biovar 3. Conclusions:The overall trend of human brucellosis epidemic in Shanxi Province from 2018 to 2023 is on the rise, and it is still at a high level. It is suggested to continue strengthening monitoring, study the epidemic situation in a timely manner, take comprehensive prevention and control measures, and effectively control the spread of brucellosis.

Excessive fat accumulation,viral infections and sustained inflammatory responses caused by non-alcoholic and alcoholic factors can contribute to liver inflammation,fibrosis and carcinogenesis,promoting the development of chronic liver disease.Gaining an in-depth understanding of the etiologic factors and underlying mechanisms that lead to chronic liver disease can help identify potential therapeutic targets for targeted therapy.Lactate,as an important substance in hepatic metabolism,has been found to be involved in the process of chronic liver disease through various pathways,and this review will provide a useful reference for the prevention and treatment of chronic liver disease.

Objective:To investigate the correlation between serum calcium binding protein S100A9 levels and lung function in patients with idiopathic pulmonary fibrosis (IPF).Method:A retrospective case-control study was conducted. Forty patients diagnosed with IPF in respiratory department from January 4, 2023, to January 30, 2024 were selected as the IPF group,with a mean age of (65.3±8.4) years old, including 29 males and 11 females. while 50 healthy volunteers receiving health examinations in our physical examination center were enrolled in this study, including 38 males and 12 females, with a mean age of (64.1±6.3) years. The levels of biochemical parameters were assayed with biochemical analyzer. S100A9 levels were determined by Enzyme linked immunosorbent assay. The lung function test results of all participants were recorded. SPSS 19.0 statistical software was used to compare the differences of biomarkers levels between the two groups , Using parameter testing (independent sample t-test) to compare the differences in serum S100A9 levels and lung function between the two groups, the enumeration data were treated with the chi-square test. Pearson correlation analysis was used to evaluate the correlation between S100A9 and lung function, the influencing factors of IPF were analyzed by using multivariate logistic regression model, and receiver operating characteristic (ROC) curve analysis was used to assess the value of Calprotectin S100A9 in predicting IPF. Results:The serum S100A9 levels in the IPF group were significantly higher than those in the healthy control group [(132.47±21.46) pg/ml,(44.75±8.84) pg/ml, t=3.544, P<0.05], forced expiratory volume in one second(FEV1,1.38±0.19) L, forced vital capacity (FVC, 2.38±0.59) L, FEV1/FVC (57.98±6.13), the maximum spontaneous ventilation (MVV, 57.48±7.66) L/min was lower than that of the control group [(3.24±0.65) L, (3.65±0.67) L, (88.77±7.97), (86.34±7.23) L/min, t=3.486,3.393,2.771,3.462, P<0.05]. Serum S100A9 was negatively correlated with FEV1, FVC, FEV1/FVC, and MVV ( r=-0.537,-0.458,-0.489,-0.511, P<0.05), S100A9 was positively correlated with S100A9 in bronchoalveolar lavage fluid and high-resolution CT fibrosis score ( r=0.632, r=0.517, P<0.05).The area under the curve (AUC) of S100A9 for predicting IPF was 0.691. Conclusion:The level of calcium binding protein S100A9 was significantly increased in IPF patients, and was closely related to decreased lung ventilation function and the occurrence of IPF, which might serve as a marker for evaluating pulmonary fibrosis.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective To analyze the application value of multimodal CT imaging parameters in the differentiation of TOAST classification for cerebral infarction.Methods According to the TOAST classification,the selected 103 patients with cerebral infarction were categorized into large-artery atherosclerosis(LAA)group,cardioembolic(CE)group,small-artery occlusion(SAO)group,other determined etiologies(SOD)group,and undetermined etiologies(SUE)group.All patients underwent non-contrast CT scanning and CT angiography.Cerebral angiography was adopted as the gold standard.Results For the LAA,CE,SAO,SOD,and SUE groups,the diagnostic performance of multimodal CT imaging was as followed:true positive rates were 73.17%,45.45%,75.00%,40.00%,and 72.00%;sensitivities were 90.10%,85.71%,92.30%,85.71%,and 90.00%;specificities were 75.00%,75.00%,66.67%,66.67%,and 80.00%;miss rates were 9.09%,28.57%,7.69%,14.28%,and 10.00%;misdiagnosis rates were 25.00%,25.00%,33.33%,33.33%,and 20.00%;positive predictive rates were 93.75%,83.33%,92.31%,85.71%,and 94.74%;and negative predictive rates were 66.67%,60.00%,66.67%,66.67%,and 66.67%,respectively.Kappa test results showed that the multimodal CT imaging findings were highly consistent with the gold standard(Kappa>0.75,P<0.05).Conclusion Multimodal CT imaging technology can effectively assist in the differentiation of TOAST classification for cerebral infarction,thereby improving the accuracy of clinical diagnosis.

Excessive fat accumulation,viral infections and sustained inflammatory responses caused by non-alcoholic and alcoholic factors can contribute to liver inflammation,fibrosis and carcinogenesis,promoting the development of chronic liver disease.Gaining an in-depth understanding of the etiologic factors and underlying mechanisms that lead to chronic liver disease can help identify potential therapeutic targets for targeted therapy.Lactate,as an important substance in hepatic metabolism,has been found to be involved in the process of chronic liver disease through various pathways,and this review will provide a useful reference for the prevention and treatment of chronic liver disease.