Objective To develop and evaluate an aptamer based biosensor (aptasensor) for rapid colorimetric detection of enteropathogenic Escherichia coli (EPEC). Method The aptasensor was fabricated by modifying the truncated LPS-binding aptamer on the surface of nanoscale polydiacetylene vesicles using peptide bonding between the carboxyl group of the vesicle and the amine group of the aptamer. Molecular recognition between EPEC and aptamer at the interface of the vesicle led to blue-red transition of polydiacetylene which was readily visible to the naked eyes and could be quantified by colorimetric responses (CR). Transmission electron microscopy (TEM) was used to confirm the specific interactions between EPEC and polydiacetylene vesicles. Result Truncated aptamer showed the similar LPS-binding activity. The aptasensor could detect the target bacteria in a range of 105-108 colony-forming units (CFU)/ml within less than 30 minutes and its specificity was 100% for detection of EPEC O111. The sensor reproducibiliry obtained at 106 CFU/ml was 6. 08% R. S. D. The results of TEM confirmed that the specific interactions between EPEC and polydiacetylene vesicles. Conclusion A new aptasensor was developed successfully for rapid colorimetric detection of EPEC.

Objective:To observe the efficacy of conbercept in the treatment of different types of diabetic macular edema (DME).Methods:A retrospective clinical study. From March 2019 to March 2021, 136 eyes of 136 patients with DME diagnosed in Department of Ophthalmology of Xi'an No.3 Hospital were included in the study. Among them, there were 65 males and 71 females; the average age was 56.65±8.65 years. All patients underwent best corrected visual acuity (BCVA), optical coherence tomography (OCT) examination, and glycosylated hemoglobin level (HbA1c) examination. Early Treatment Diabetic Retinopathy Study visual acuity chart was used for BCVA examination, which was converted into the logarithmic minimum angle of resolution (logMAR) visual acuity during statistics. An OCT instrument was used to measure the central retinal thickness (CRT) of the macula. According to the characteristics of OCT, DME was divided into diffuse retinal thickening (DRT) type, cystoid macular edema (CME) type, serous retinal detachment (SRD) type, mixed type, and grouped accordingly, respectively, about 30, 38, 33, 35 eyes. There was no significant difference in age ( F=1.189), sex ratio ( χ2=1.331), and HbA1c level ( F=3.164) of the four groups of patients ( P>0.05). All eyes were treated with intravitreal injection of 10 mg/ml conbercept 0.05 ml (including conbercept 0.5 mg) once a month for 3 consecutive times, and then treated as needed after evaluation. BCVA and OCT examinations were performed 1, 3, and 6 months after treatment with the same equipment and methods as before treatment. The changes of BCVA and CRT before and after treatment were compared and observed. For measurement data subject to normal distribution, one-way analysis of variance was performed for comparison between groups; χ2 test was performed for comparison of count data. Results:Before treatment, the logMAR BCVA of the eyes in the DRT group, CME group, SRD group, and mixed group were 0.68±0.11, 0.69±0.15, 0.71±0.12, 0.73±0.14, and CRT was 631.4±50.7, 640.6±55.7, 652.3±63.4, 660.4±61.8 μm. Compared with before treatment, 1, 3, 6 months after treatment, DRT group (BCVA: t=8.139, 11.552, 11.672; CRT: t=16.163, 21.653, 25.855), CME group (BCVA: t=8.923, 9.995, 13.842; CRT: t=16.163, 21.653, 25.855), SRD type group (BCVA: t=5.171, 7.315, 6.051; CRT: t=9.099, 13.731, 21.306), mixed type group (BCVA: t=5.072, 6.939, 7.142; CRT: t=6.920, 15.352, 17.538) The BCVA of the affected eyes was significantly increased, and the CRT was significantly decreased, and the difference was statistically significant ( P<0.05). At 6 months after treatment, the differences in logMAR BCVA and CRT of the 4 groups of eyes were statistically significant ( χ2=58.478, 64.228; P<0.05). The average number of injections in the eyes of the DRT group, CME group, SRD group, and mixed group were 3.37±1.35, 3.68±1.38, 4.18±1.40, 4.13±1.50 times, respectively. Compared with the average number of injections in the eye, the difference was statistically significant ( χ2=9.139, P=0.028). Conclusions:Conbercept can effectively reduce CRT and increase BCVA in eyes with different types of DME. Compared with SRD type and mixed type, DRT and CME type eye are more effective in improving vision, CRT reduction degree is greater, and the number of injections is less.

Objective To determine the correlation between obstructive sleep apnea syndrome (OSAS)and nonarteritic ischemic optic neuropathy (NAION).Methods It was a perspective study.A total of 41 consecutive patients with NAION (NAION group) and 41 age-and sex-matched physical examination subjects (control group) in Xi'an No.3 Hospital from December 2016 to December 2018 were enrolled in this study.The apnea hypopnea index (AHI,the number of sleep apneas per hour) was monitored using a polysomnography for patients in NAION group and control group.At the same time,the blood oxygen saturation was continuously recorded.The OSAS can be diagnosed if the AHI value was ≥ 5.OSAS severity was graded as mild:5≤AHI＜ 15;moderate:15≤AHI＜30;severe:AHI ≥30.The grading of OSAS severity between two groups was compared by Fisher's exact test.The AHI and minimum blood oxygen saturation were compared between NAION group and control group using the Mann-Whitney U test.Spearman correlation analysis was performed on the correlation between OSAS and NAION.Results Among the patients in the NAION group,31 patients (75.61％) were diagnosed with OSAS.Among them,6 patients (14.63％) were mild,9 patients (21.95％) were moderate,and 16 patients (39.03％) were severe.In the control group,19 patients (46.34％) were diagnosed with OSAS.Among them,10 patients (24.39％) were mild,5 patients (12.20％) were moderate,and 4 patients (9.75％) were severe.The difference of OSAS patients of mild,moderate and severe between two groups were statistically significant (Z=0.235,0.245,0.312;P=0.012,0.014,0.032).The average AHI of patients in the NAION group was 20.25 ± 7.74,and the mean minimum oxygen saturation at night was (87.38± 5.53)％.The average AHI of the control group was 18.67 ± 11.67,and the mean minimum oxygen saturation at night was (85.06+4.25)％.The differences of the mean AHI and mean minimum oxygen saturation between two groups were statistically significant (Z=1.124,2.317,P=0.003,0.020).There was a positive correlation between OSAS and NAION (Spearman correlation coefficient=0.229,P=0.030).Conclusion There is a positive correlation between OSAS and NAION.

Objective:To observe the correlation between obstructive sleep apnea syndrome (OSAS) and central serous chorioretinopathy (CSC).Methods:From October 2016 to December 2018, 50 cases of CSC patients (CSC group) and 50 healthy people (control group) matched by age and sex who were diagnosed in the ophthalmological examination of Xi’an No.3 Hospital were included in the study. According to the course of the disease, CSC was divided into acute phase and chronic phase, with 20 and 30 cases respectively. The average age ( Z=1.125) and body mass index (BMI) ( Z=0.937) of the two groups were compared, and the difference was not statistically significant ( P>0.05); the age of patients with different courses of CSC ( Z=1.525) and gender composition ratio ( χ2=0.397) and BMI ( Z=1.781) were compared, the difference was not statistically significant ( P>0.05). The Berlin questionnaire was used to assess the OSAS risk of subjects in the CSC group and the control group; polysomnography was used to monitor the apnea-hypopnea index (AHI) and minimum blood oxygen saturation (MOS) during night sleep. OSAS diagnostic criteria: typical sleep snoring, daytime sleepiness, AHI (times/h) value ≥ 5. The severity of OSAS was classified as mild OSAS: 5≤AHI<15; moderate OSAS: 15≤AHI <30; severe OSAS: AHI≥30. Non-normally distributed measurement data were compared by rank sum test; count data were compared by χ2 test. Spearman correlation analysis was performed on the correlation between OSAS and CSC. Results:The AHI data in the CSC group and the control group were 17.46±3.18 and 15.72±4.48 times/h, respectively; the MOS were (83.48±4.68)% and (87.40±3.82)%, respectively; those diagnosed with OSAS were respectively 36 (72.00%, 36/50) and 13 (26.00%, 13/50) cases. AHI ( Z=0.312), MOS ( Z=0.145), and OSAS incidence ( χ2=21.17) were compared between the two groups of subjects, and the differences were statistically significant ( P=0.028, 0.001,<0.001). The AHI of acute and chronic CSC patients were 15.95±3.02 and 18.47±2.92 times/h; the MOS were (86.10±11.07)% and (81.73±4.58)%, respectively. There were statistically significant differences in AHI ( Z=0.134) and MOS ( Z=0.112) in patients with different course of disease ( P=0.005, 0.001). The results of Spearman correlation analysis showed that OSAS and CSC were positively correlated ( r=0.312, P=0.031). Conclusion:OSAS may be a risk factor for the onset of CSC.

Community-acquired pneumonia (CAP) is a common respiratory infectious disease.The etiologic diagnosis of CAP remains an uneasy task.Early etiologic diagnosis is critical for proper treatment and might improve the prognosis.So,it is important to identify pathogens causing CAP in early time and accurate way with sensitive and effective method.This paper summarizes the recent progress in the research of the detection assay for CAP.

【Objective】 To establish a blood transfusion outcome prediction model for comprehensivel evaluation of coagulation function of patients with upper gastrointestinal bleeding by thrombelastogram (TEG) and blood coagulation indicators. 【Methods】 The data of 101 patients with upper gastrointestinal hemorrhage, admitted to the Department of Gastroenterology of Zhejiang Provincial People′s Hospital and its Chun′an Branch from June 2018 to June 2021, were collected through Tongshuo blood transfusion management system and His system. Those patients were divided into blood transfusion group (n=56) and non-transfusion group (n=45), and into cirrhosis group (n=74) and non-cirrhosis group (n=27), and 40 patients, with non-upper gastrointestinal bleeding, were enrolled as the control. The results of TEG indicators (R, K, α, MA), coagulation function (PT, INR, APTT, TT, Fib), blood routine (Hb, Plt, WBC, NEUT%) and biochemical detection(Alb, SCr, ALT, AST, GGT) before transfusion were compared between groups and the correlation between TEG indicators and traditional coagulation parameters was analyzed. Single-factor and multi-factor analysis were used to screen blood transfusion-related factors to establish a predictive model. 【Results】 The comparisons of paremeters between transfusion and non-transfusion group were as follows, K (min), α (°), and MA (mm) was 3.86±3.12 vs 2.50±1.47, 54.00±14.08 vs 61.05±10.88, and 51.12±13.37 vs 58.26±11.08, respectively (P<0.01); PT (s) and Fib (g) was 16.36±7.45 vs 13.44±1.50 and 1.59±0.87 vs 2.35±1.09 (P<0.01); NEUT% and Hb (g/L) was 0.75 ±0.13 vs 0.66±0.15 and 68.04±14.49 vs 100.73±22.92 (P<0.01); Alb (g/L) and SCr (nmol/L) was 29.73±6.08 vs 33.73±7.19 and 99.50±53.55 vs 76.25±19.28 (P<0.01). Correlation analysis showed that APTT was positively correlated with R and K values, and negatively correlated with α and MA. Fib was negatively correlated with K values, and positively correlated with α and MA. Plt was negatively correlated with K values, and positively correlated with α and MA (P<0.01). Eight pre-transfusion indicators as K, MA, PT, Fib, NEUT%, Hb, Alb, and SCr were subjected to Logistic regression to establish a blood transfusion prediction model. The optimal ROC curve of blood transfusion threshold (blood transfusion predictive value of patients), sensitivity, specificity and AUC were 0.448, 92.9%, 88.9%, and 0.969, respectively. 【Conclusion】 The establishment of Logistic regression model by integrating detection indicators of TEG, coagulation function, blood routine and biochemistry in patients with upper gastrointestinal bleeding have showed significant correlation with blood transfusion prediction, and good clinical practicability.