Objective To construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

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.

This paper summarizes the progress of theoretical research and practice of One Health in China,and discusses the paradigm of One Health governance to improve the prevention and control of infectious diseases in China and the world,and provide an example for the improvement of the public health system.In particular,China has long history to apply the concept of One Health in the national schistosomiasis control programmes and patriotic health campaigns,which were not only focusing on human health,but also emphasizing the sustainable development of animal health and ecological environment.At the same time,the application of tools such as system dynamics model,eDNA technology,One Health economic assessment and global One Health index(GOHI)in the field of disease control and environmental health provides technical support for the concept of One Health.Despite the challenges of practical application of these tools,the One Health concept will play a greater role in providing sustainable solutions for human-animal-environmental health by strengthening interdisciplinary collaboration,improving standardization protocols and promoting inter-national cooperation.

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.

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.

This paper summarizes the progress of theoretical research and practice of One Health in China,and discusses the paradigm of One Health governance to improve the prevention and control of infectious diseases in China and the world,and provide an example for the improvement of the public health system.In particular,China has long history to apply the concept of One Health in the national schistosomiasis control programmes and patriotic health campaigns,which were not only focusing on human health,but also emphasizing the sustainable development of animal health and ecological environment.At the same time,the application of tools such as system dynamics model,eDNA technology,One Health economic assessment and global One Health index(GOHI)in the field of disease control and environmental health provides technical support for the concept of One Health.Despite the challenges of practical application of these tools,the One Health concept will play a greater role in providing sustainable solutions for human-animal-environmental health by strengthening interdisciplinary collaboration,improving standardization protocols and promoting inter-national cooperation.

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.

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

OBJECTIVE: To investigate the effect of Yinlai Decoction (YD) on the microstructure of colon, and activity of D-lactic acid (DLA) and diamine oxidase (DAO) in serum of pneumonia mice model fed with high-calorie and high-protein diet (HCD). METHODS: Sixty male Kunming mice were randomly divided into 6 groups by the random number table method: normal control, pneumonia, HCD, HCD with pneumonia (HCD-P), YD (229.2 mg/mL), and dexamethasone (15.63 mg/mL) groups, with 10 in each group. HCD mice were fed with 52% milk solution by gavage. Pneumonia mice was modeled with lipopolysaccharide inhalation and was fed by gavage with either the corresponding therapeutic drugs or saline water, twice daily, for 3 days. After hematoxylin-eosin staining, the changes in the colon structure were observed under light microscopy and transmission electron microscope, respectively. Enzyme-linked immunosorbent assay was used to detect the protein levels of DLA and DAO in the serum of mice. RESULTS: The colonic mucosal structure and ultrastructure of mice in the normal control group were clear and intact. The colonic mucosal goblet cells in the pneumonia group tended to increase, and the size of the microvilli varied. In the HCD-P group, the mucosal goblet cells showed a marked increase in size with increased secretory activity. Loose mucosal epithelial connections were also observed, as shown by widened intercellular gaps with short sparse microvilli. These pathological changes of intestinal mucosa were significantly reduced in mouse models with YD treatment, while there was no significant improvement after dexamethasone treatment. The serum DLA level was significantly higher in the pneumonia, HCD, and HCD-P groups as compared with the normal control group (P<0.05). Serum DLA was significantly lower in the YD group than HCD-P group (P<0.05). Moreover, serum DLA level significantly increased in the dexamethasone group as compared with the YD group (P<0.01). There was no statistical significance in the serum level of DAO among groups (P>0.05). CONCLUSIONS YD can protect function of intestinal mucosa by improving the tissue morphology of intestinal mucosa and maintaining integrity of cell connections and microvilli structure, thereby reducing permeability of intestinal mucosa to regulate the serum levels of DLA in mice.
Mice ; Male ; Animals ; Lactic Acid/pharmacology* ; Intestinal Mucosa ; Colon/pathology* ; Dexamethasone/pharmacology* ; Diet, High-Protein ; Pneumonia/pathology*