Objective To analyze the prevalence of dengue fever in Guangzhou based on circuit-qi theory.Methods Data on dengue fever cases in Guangzhou from January 21,2012,to January 19,2024 were collected.And then the incidence of dengue fever was analyzed under the circuit-qi conditions of dominant qi,guest qi,celestial qi,joining of guest qi with dominant qi,and dissimilation of circuit and qi.Results Higher incidence of dengue fever in Guangzhou was presented under the circuit-qi conditions of the fifth qi of the dominant qi in each year,shaoyang minister fire of the guest qi,shaoyin monarch fire of the celestial qi,guest qi restricting dominant qi in the joining of guest qi with dominant qi,shaoyang minister fire(guest qi)joining with yangming dry-metal(dominant qi)in the pattern of guest qi restricting dominant qi.The outbreak of dengue fever under the circuit-qi conditions of dissimilation of circuit and qi showed no statistically significant difference.Conclusion Over the 12-year period from 2012 to 2024,the prevalence of dengue fever in Guangzhou exhibited a 4-5-year cyclical pattern,often with consecutive outbreaks over two years.The prevalence of dengue fever in Guangzhou is associated with the factors of dampness and heat in the theory of five circuits and six qi,while has less relation with dissimilation of circuit and qi.

BackgroundCompared with absenteeism， health-related productivity loss has a long-lasting negative effect， and poses a greater harm and loss. The health-related productivity loss is mediated by self-efficacy， and perceived social support has been shown to have an impact on health-related productivity loss， whereas the interaction mechanism among the three remains unclear. ObjectiveTo investigate the status of perceived social support， occupational coping self-efficacy and health-related productivity loss among ICU nurses， and to test the mediation role of perceived social support in the relationship between occupational coping self-efficacy and health-related productivity loss. MethodsFrom September to November， 2021， purposive sampling technique was adopted to select 468 ICU nurses in 8 tertiary hospitals in Sichuan Province. Subjects were assessed using self-made general information questionnaire， Perceived Social Support Scale （PSSS）， Occupational Coping Self Efficacy Scale for Nurses （OCSE-N） and Stanford Presenteeism Scale-6 （SPS-6）. Pearson correlation analysis was used to examine the correlation among variables. Amos 24.0 was utilized to test the mediation role of perceived social support in the relationship between occupational coping self-efficacy and health-related productivity loss. ResultsA total of 415 ICU nurses completed the valid questionnaire survey. ICU nurses scored （63.13±11.62） on PSSS， （22.24±6.15） on OCSE-N， and （16.83±4.24） on SPS-6. Health-related productivity loss was detected in 279 ICU nurses （67.23%）. Correlation analysis denoted that PSSS total score was positively correlated with OCSE-N total score （r=0.348， P<0.05）， and negatively correlated with SPS-6 total score （r=-0.274， P<0.05）. OCSE-N total score was negatively correlated with SPS-6 total score （r=-0.421， P<0.05）. The direct effect value of occupational coping self-efficacy on health-related productivity loss was -0.401， and perceived social support showed a mediation role in the relationship between occupational coping self-efficacy and health-related productivity loss （the indirect effect value was -0.052， accounting for 11.48% of the total effect）. ConclusionThe occupational coping self-efficacy of ICU nurses may affect the health-related productivity loss through the action path of perceived social support.［Funded by Scientific Research Project of Sichuan Provincial Health Commission （number， 19PJ042）］

Objective To explore the relationship between androgen level and adverse pregnancy outcome of pregnant women at advanced maternal age.Methods A total of 192 pregnant women who were admitted to Changzhou Maternal and Child Health Care Hospital for delivery from May to October 2022 were selected as the study objects.According to guidelines for diagnosis and treatment of hypertensive disorder complicating pregnancy and maternal age,the study objects were divided into simple pregnant women at advanced maternal age group,pregnant women at advanced maternal age complicated with hypertensive disorder complicating pregnancy,healthy control group and age-appropriate pregnant women complicated with hypertensive disorder complicating pregnancy group.Serum levels of five androgens[total testosterone(TT),sex hormone binding globulin(SHBG),free testosterone index(FTI),dehydroepiandrosterone sulfate(DHEAS)and androstendi-one(A2)]in each group were detected by chemiluminescence method.Results Compared with the healthy control group,TT,A2,FTI were significantly increased and SHBG was significantly decreased in the age-ap-propriate pregnant women complicated with hypertensive disorder complicating pregnancy group,the level of DHEAS was decreased in the simple pregnant women at advanced maternal age group,and the differences were statistically significant(P＜0.05).Pearson correlation analysis showed that TT was negatively correla-ted with age(P＜0.05),positively correlated with systolic blood pressure,diastolic blood pressure and body mass index(P＜0.05),and had no correlation with offspring sex and offspring weight(P＞0.05).Multivari-ate Logistic regression analysis showed that TT and body mass index were independent risk factors for hyper-tensive disorder complicating pregnancy in pregnant women(P＜0.05).Conclusion The level of androgen in pregnant women at advanced maternal age is related to the occurrence of hypertensive disorder complicating pregnancy.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

Objective:To investigate the cognitive functions of temporal lobe epilepsy (TLE) patients with bilateral asynchronous interictal discharges.Methods:A total of 162 TLE patients who were treated at Zhongshan Hospital, Fudan University, from June 2021 to December 2023 were collected. According to the interictal scalp electroencephalogram, TLE patients were classified to the TLE with bilateral temporal asynchronous interictal epileptiform discharges ( n=51) and TLE with unilateral temporal epileptiform discharges ( n=111). Unilateral TLE patients were divided into TLE with right ( n=48) and left ( n=63) temporal epileptiform discharges. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Digital Span (DS), Verbal Fluency Test (VFT), the third part of Color Word Test (CWT-C), Trail Making Test-B (TMT-B), Symbol Digit Modalities Test (SDMT), Auditory Verbal Learning Test (AVLT), Rey-Osterrieth Complex Figure (ROCF), and Similarity Comprehension Test were performed for the participants. The differences of cognitive functions between patients with bilateral and unilateral temporal discharges were compared. Univariate and multivariate Logistic regression models were used to analyze the risk factors for patients with bilateral temporal asynchronous discharges. Spearman analysis was used to explore the correlation between cognitive function and clinical indicators. Results:In the group of TLE patients with bilateral asynchronous discharges compared to those with unilateral discharges, the completion time of CWT-C [67 (55, 103) s vs 59 (50, 71) s, Z=-2.904, P=0.004], TMT-B [159 (108, 219) s vs 129 (95, 180) s, Z=-2.361, P=0.018] was longer. Additionally, TLE patients with bilateral asynchronous discharges got lower scores of MMSE [28 (26, 29) vs 29 (28, 30), Z=3.098, P=0.002], MoCA [23 (19, 28) vs 27 (23, 28), Z=3.175, P=0.001], AVLT1+2+3 [16.843±6.482 vs 19.162±5.526, t=-2.347, P=0.020], AVLT6 [6 (3, 10) vs 8 (5, 10), Z=3.275, P=0.001], ROCF2 [15 (8, 22) vs 20 (12, 25), Z=2.870, P=0.004], ROCF3 [14 (8, 22) vs 20 (11, 25), Z=2.634, P=0.008], and Similarity Test [13 (8, 18) vs 16 (12, 20), Z=2.387, P=0.017] as well as lower VFT-vegetable and fruit count [15 (13, 19) vs 18 (15, 21), Z=2.402, P=0.016] and SDMT completion count [41 (30, 53) vs 51 (40, 60), Z=3.089, P=0.002]. The multivariate Logistic regression analysis showed that the decrease in AVLT6 scores ( OR=1.546, 95% CI 1.150-2.078, P=0.004) and longer TMT-B time ( OR=1.013, 95% CI 1.001-1.025, P=0.035) were independent risk factors for TLE patients with bilateral asynchronous discharges. Conclusions:Compared to the patients with TLE characterized by unilateral temporal lobe discharges, those with asynchronous discharges in bilateral temporal lobes show statistically significant declines in all domains of cognitive functions, including executive function, memory, and language abilities. Decreased cue recall ability in language memory and prolonged trail-making test in executive function are independent cognitive impairment risk factors for bilateral temporal asynchronous discharges.

The effect of Radix isatidis polysaccharide(IRPS)on TLR3/TRIF innate immune path-way and type Ⅰ interferon secretion in 3D4/21/CD163 cells infected by porcine reproductive and re-spiratory syndrome virus(PRRSV)was tested by Western blot and ELISA;moreover,the effect of IRPS on the immunosuppression infected by PRRSV was further verified with the TLR3 agonist poly(I∶C).The results showed that the protein levels of TLR3,TRIF,IRF3,IRF7 and type Ⅰ in-terferon secretion were significantly decreased at 18,24 h of PRRSV infection,while IRPS signifi-cantly inhibited this process;poly(I∶C)alleviated the protein levels of TRIF,IRF3 and IRF7 as well as the phosphorylation levels of IRF3 and IRF7 infected by PRRSV;at the same time,IRPS is synergistic with poly(I∶C).The results indicate that IRPS is able to alleviate immunosuppression caused by PRRSV infection via the TLR3/TRIF pathway.

BACKGROUND: China bears the biggest atrial fibrillation (AF) burden in the world. However, little is known about the incidence and predictors of AF. This study aimed to investigate the current incidence of AF and its electrocardiographic (ECG) predictors in general community individuals aged over 60 years in China. METHODS: This was a prospective cohort study, recruiting subjects who were aged over 60 years and underwent annual health checkups from April to July 2015 in four community health centers in Songjiang District, Shanghai, China. The subjects were then followed up from 2015 to 2019 annually. Data on sociodemographic characteristics, medical history, and the resting 12-lead ECG were collected. Kaplan-Meier curve was used for showing the trends in AF incidence and calculating the predictors of AF. Associations of ECG abnormalities and AF incidence were examined using Cox proportional hazard models. RESULTS: This study recruited 18,738 subjects, and 351 (1.87%) developed AF. The overall incidence rate of AF was 5.2/1000 person-years during an observation period of 67,704 person-years. Multivariable Cox regression analysis indicated age (hazard ratio [HR], 1.07; 95% confidence interval [CI]: 1.06-1.09; P < 0.001), male (HR, 1.30; 95% CI: 1.05-1.62; P = 0.018), a history of hypertension (HR, 1.55; 95% CI: 1.23-1.95; P < 0.001), a history of cardiac diseases (HR, 3.23; 95% CI: 2.34-4.45; P < 0.001), atrial premature complex (APC) (HR, 2.82; 95% CI: 2.17-3.68; P < 0.001), atrial flutter (HR, 18.68; 95% CI: 7.37-47.31; P < 0.001), junctional premature complex (JPC) (HR, 3.57; 95% CI: 1.59-8.02; P = 0.002), junctional rhythm (HR, 18.24; 95% CI: 5.83-57.07; P < 0.001), ventricular premature complex (VPC) (HR, 1.76; 95% CI: 1.13-2.75, P = 0.012), short PR interval (HR, 5.49; 95% CI: 1.36-22.19; P = 0.017), right atrial enlargement (HR, 6.22; 95% CI: 1.54-25.14; P = 0.010), and pacing rhythm (HR, 3.99; 95% CI: 1.57-10.14; P = 0.004) were independently associated with the incidence of AF. CONCLUSIONS The present incidence of AF was 5.2/1000 person-years in the studied population aged over 60 years in China. Among various ECG abnormalities, only APC, atrial flutter, JPC, junctional rhythm, short PR interval, VPC, right atrial enlargement, and pacing rhythm were independently associated with AF incidence.
Humans ; Male ; Middle Aged ; Aged ; Atrial Fibrillation/epidemiology* ; Prospective Studies ; Incidence ; Atrial Flutter/complications* ; Risk Factors ; China/epidemiology* ; Electrocardiography

Objective To analyze the process of intercomparison of national personal dose monitoring, evaluate the ability of personal dose monitoring, and ensure the accuracy and reliability of monitoring results in our laboratory. Methods In accordance with the intercomparison protocol for 2019—2021, an energy-discriminant thermoluminescence dosimeter was used for measurement at different doses. The uncertainty of measurement was evaluated and compared with the reference value. Results H_p(10) was measured for intercomparison in 2019—2021. In 2019, the single group performance difference was −0.02 to 0.02 and the comprehensive performance was 0.02. These values were 0.02-0.10 and 0.05 in 2020, and −0.02 to 0.02 and 0.01 in 2021. The intercomparison results were rated as excellent in the three consecutive years. Conclusion The personal dose monitoring system in our laboratory was in good condition, and the monitoring results were accurate and reliable. Improving the knowledge of personnel and cultivating a serious working attitude are important for intercomparison and personal dose monitoring.

Objective:To establish and preliminarily validate a nomogram model for predicting the risk of retinal vein occlusion (RVO).Methods:A retrospective clinical study. A total of 162 patients with RVO (RVO group) diagnosed by ophthalmology examination in The Second Affiliated Hospital of Xi'an Jiaotong University from January 2017 to April 2022 and 162 patients with age-related cataract (nRVO group) were selected as the modeling set. A total of 45 patients with branch RVO, 45 patients with central RVO and 45 patients with age-related cataract admitted to Xi'an Fourth Hospital from January 2022 to February 2023 were used as the validation set. There was no significant difference in gender composition ratio ( χ2=2.433) and age ( Z=1.006) between RVO group and nRVO group ( P=0.120, 0.320). Age, gender, blood routine (white blood cell count, hemoglobin concentration, platelet count, neutrophil count, monocyte count, lymphocyte count, erythrocyte volume, mean platelet volume, platelet volume distribution width), and four items of thrombin (prothrombin time, activated partial thrombin time, fibrinogen, and thrombin time) were collected in detail ), uric acid, blood lipids (total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, lipoprotein a), hypertension, diabetes mellitus, coronary heart disease, and cerebral infarction. Neutrophil/lymphocyte ratio and platelet/lymphocyte ratio were calculated. The single logistic regression was used to analyze the clinical parameters of the two groups of patients in the modeling set, and the stepwise regression method was used to screen the variables, and the column graph for predicting the risk of RVO was constructed. The Bootstrap method was used to repeated sample 1 000 times for internal and external verification. The H-L goodness-of-fit test and receiver operating characteristic (ROC) curve were used to evaluate the calibration and discrimination of the nomogram model. Results:After univariate logistic regression and stepwise regression analysis, high density lipoprotein, neutrophil count and hypertension were included in the final prediction model to construct the nomogram. The χ2 values of the H-L goodness-of-fit test of the modeling set and the validation set were 0.711 and 4.230, respectively, and the P values were 0.701 and 0.121, respectively, indicating that the nomogram model had good prediction accuracy. The area under the ROC curve of the nomogram model for predicting the occurrence of post-stroke depression in the modeling set and the verification set was 0.741 [95% confidence interval ( CI) 0.688-0.795] and 0.741 (95% CI 0.646-0.836), suggesting that the nomogram model had a good discrimination. Conclusions:Low high density lipoprotein level, high neutrophil count and hypertension are independent risk factors for RVO. The nomogram model established based on the above risk factors can effectively assess and quantify the risk of post-stroke depression in patients with cerebral infarction.