4-(Benzo[c][1,2,5]thiadiazol-4-ylethynyl)benzoic acid (BTEBA) as a promising electron acceptor has been used in the highly efficient organic dye-sensitized solar cells (DSCs) recently. Because of its strong electron-deficient character, BTEBA could bring forth a remarkable decline in the energy level of the lowest unoccupied molecular orbital (LUMO) and further reduce the energy gap of dye molecules significantly. In this contribution, two metal-free organic dyes WEF1 and WEF2 were synthesized by simply combining BTEBA with two slightly tailored electron-releasing moieties: 4-hexylphenyl substituted indaceno[1,2-b:5,6-b']dithiophene (IDT) and cyclopenta[1,2-b:5,4-b']dithiophene[2',1':4,5]thieno[2,3-d]thiophene (CPDTDT), which were screened rationally from an electron-donor pool via computational simulation. With respect to those of WEF1, WEF2-sensitized solar cells demonstrate a far better short-circuit photocurrent density (JSC) and open-circuit photovoltage (VOC), resulting in a ∼50% improved power conversion efficiency of 10.0% under irradiance of 100 mW cm(-2) AM1.5G sunlight. We resorted to theoretical calculations, electrical measurements, steady-state, and time-resolved spectroscopic methods to shed light on the fatal influences of elaborately modulating electron donors on light absorption, interfacial energetics, and multichannel charge-transfer dynamics.
Purpose To identify the characteristics of retinal image in women with recurrent spontaneous abortion (RSA). Methods A case-control study was conducted in the Shenzhen Maternity & Child Healthcare Hospital. Eighty women who were diagnosed RSA were recruited. Those women who were age matched with the RSA group and experienced a successful birth history were chosen as the control group. Retinal images were collected and characteristics were analysed. Multivariable logistic model was built to identify the characteristics of retinal image. Results Compared to the control group, the patients with RSA had higher CRAE (P = 0.02), Vasym(P < 0.0001) and Aasym(P = 0.002), larger Aangle(P = 0.035), BCA(P < 0.0001) and more obvious Nicking(P = 0.001) and occlusion( P = 0.001) in the retinal artery, but lower AVR(P = 0.314) in retinal characteristics. The area under the ROC curve of the multivariable logistic regression was 0.8541 (95% C.I. 0.796–0.912). Conclusions Compared to the Normal pregnancy women, those with RSA had special retinal characteristics, which might provide useful information for RSA identification.
Purpose To establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI. Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048). Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI.
Purpose To establish a prediction model for premature ovarian insufficiency (POI) identification.Methods A total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models. Results Compared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P=0.006), central retinal vein equivalent (CRVE) (P=0.001), index of venules asymmetry (Vasym) (P=0.000); larger bifurcation angles of arterioles (Aangle) (P=0.001), bifurcation coefficient of venule (BCV) (P=0.001) and more obvious arteriovenous nipping (Nipping) (P=0.005), but lower arteriole-to-venule ratio (AVR) (P=0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49–9.79e-15, P=0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34–.0000, P=5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10–.0698, P=0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob> chi-square = 0.6048).Conclusion This study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI.
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