Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: This study investigated the factors influencing smartphone overdependence in university students using an ecological model and descriptive research. Methods: Data were collected from 482 students at 13 universities in the six regions in South Korea from October 20, 2020, to March 25, 2021. Data analysis involved descriptive statistics, the chi-square test, the independent samples t-test, analysis of variance, and hierarchical multiple regression. Results: The significant ecological factors influencing smartphone overdependence included self-awareness of smartphone overdependence (β=.33, p<.001), autonomy (β=–.25, p<.001), average daily smartphone usage time (β=.18, p<.001), gender (β=.15, p=.001), college year (β=.15, p=.020), forming relationships with others as a motivation for smartphone use (β=–.15, p=.008), friend support (β=.14, p=.006), and age (β=–.12, p=.047). The model explained 34.9% of the variance. Conclusion The study emphasized the role of personal and interpersonal factors, in smartphone overdependence among university students. Tailored intervention strategies are necessary to address smartphone overdependence, considering the unique characteristics of students’ environments. A significant aspect of this study is that it provides an explanation of the multidimensional factors contributing to smartphone overdependence among university students, including intrapersonal, interpersonal, and environmental influences.

Purpose: This study investigated the factors influencing smartphone overdependence in university students using an ecological model and descriptive research. Methods: Data were collected from 482 students at 13 universities in the six regions in South Korea from October 20, 2020, to March 25, 2021. Data analysis involved descriptive statistics, the chi-square test, the independent samples t-test, analysis of variance, and hierarchical multiple regression. Results: The significant ecological factors influencing smartphone overdependence included self-awareness of smartphone overdependence (β=.33, p<.001), autonomy (β=–.25, p<.001), average daily smartphone usage time (β=.18, p<.001), gender (β=.15, p=.001), college year (β=.15, p=.020), forming relationships with others as a motivation for smartphone use (β=–.15, p=.008), friend support (β=.14, p=.006), and age (β=–.12, p=.047). The model explained 34.9% of the variance. Conclusion The study emphasized the role of personal and interpersonal factors, in smartphone overdependence among university students. Tailored intervention strategies are necessary to address smartphone overdependence, considering the unique characteristics of students’ environments. A significant aspect of this study is that it provides an explanation of the multidimensional factors contributing to smartphone overdependence among university students, including intrapersonal, interpersonal, and environmental influences.

Purpose: This study investigated the factors influencing smartphone overdependence in university students using an ecological model and descriptive research. Methods: Data were collected from 482 students at 13 universities in the six regions in South Korea from October 20, 2020, to March 25, 2021. Data analysis involved descriptive statistics, the chi-square test, the independent samples t-test, analysis of variance, and hierarchical multiple regression. Results: The significant ecological factors influencing smartphone overdependence included self-awareness of smartphone overdependence (β=.33, p<.001), autonomy (β=–.25, p<.001), average daily smartphone usage time (β=.18, p<.001), gender (β=.15, p=.001), college year (β=.15, p=.020), forming relationships with others as a motivation for smartphone use (β=–.15, p=.008), friend support (β=.14, p=.006), and age (β=–.12, p=.047). The model explained 34.9% of the variance. Conclusion The study emphasized the role of personal and interpersonal factors, in smartphone overdependence among university students. Tailored intervention strategies are necessary to address smartphone overdependence, considering the unique characteristics of students’ environments. A significant aspect of this study is that it provides an explanation of the multidimensional factors contributing to smartphone overdependence among university students, including intrapersonal, interpersonal, and environmental influences.

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: This study investigated the factors influencing smartphone overdependence in university students using an ecological model and descriptive research. Methods: Data were collected from 482 students at 13 universities in the six regions in South Korea from October 20, 2020, to March 25, 2021. Data analysis involved descriptive statistics, the chi-square test, the independent samples t-test, analysis of variance, and hierarchical multiple regression. Results: The significant ecological factors influencing smartphone overdependence included self-awareness of smartphone overdependence (β=.33, p<.001), autonomy (β=–.25, p<.001), average daily smartphone usage time (β=.18, p<.001), gender (β=.15, p=.001), college year (β=.15, p=.020), forming relationships with others as a motivation for smartphone use (β=–.15, p=.008), friend support (β=.14, p=.006), and age (β=–.12, p=.047). The model explained 34.9% of the variance. Conclusion The study emphasized the role of personal and interpersonal factors, in smartphone overdependence among university students. Tailored intervention strategies are necessary to address smartphone overdependence, considering the unique characteristics of students’ environments. A significant aspect of this study is that it provides an explanation of the multidimensional factors contributing to smartphone overdependence among university students, including intrapersonal, interpersonal, and environmental influences.

Purpose: To investigate the outcomes of brolucizumab reinjection after intraocular inflammation (IOI) development. Methods: This retrospective study analyzed patients with brolucizumab injections from April 2021 to January 2024. Patients who developed IOI after brolucizumab were included and categorized into subgroups depending on reinjection, discontinuation, and further IOI development. Results: A total of 472 eyes of 432 patients received brolucizumab injections. Thirty-eight cases developed IOI at least once, and 25 continued brolucizumab. Sixteen cases had no more IOI events, and nine experienced a second or more IOI events. Among the nine cases, three maintained brolucizumab injections despite IOI recurrence. The incidence of IOI was 8.1% based on the number of eyes (38 of 472 eyes) and 2.0% based on the number of brolucizumab injections (50 of 2,468 injections). The incidence of occlusive retinal vasculitis was 0.2% (1 of 472 eyes). The recurrence rate was 23.7% (9 of 38 eyes). The average number of injections between the first brolucizumab injection and the injection date on which IOI first developed was 2.15 times in the no-reinjection group, 3.44 times in the no-IOI-recurrence group, and 2.0 times in the second-IOI-episode group. Time to IOI occurrence in cases with first IOI episode was 18.60 ± 16.73 days, with 15 cases developing IOI within 1 week. Conclusions This study elucidates the real-world incidence of brolucizumab associated IOIs, with a description of information related to reinjections after the IOI episodes. A comprehensive understanding of brolucizumab reinjection is essential for its optimal utilization.

Purpose: The aim of this study was to investigate the efficacy of ethanol extracts of Cornus alba (ECA) against benign prostatic hyperplasia (BPH) in vitro and in vivo. Materials and Methods: The prostate stromal cells (WPMY-1) and epithelial cells (RWPE-1) were used to examine the action mechanism of ECA in BPH in vitro. ECA efficacy was evaluated in vivo using a testosterone propionate (TP)-induced BPH rat model. Results: Treatment with ECA inhibited the proliferation of prostate cells by inducing G1-phase cell cycle arrest through the regulation of positive and negative proteins. Treatment of prostate cells with ECA resulted in alterations in the mitogen-activated protein kinases and protein kinase B signaling pathways. The transcriptional binding activity of the NF-κB motif was suppressed in both ECA-treated prostate cells. In addition, treatment with ECA altered the level of BPH-associated axis markers (5α-reductase, fibroblast growth factor-2, androgen receptor, epidermal growth factor, Bcl-2, and Bax) in both cell lines. Finally, the administration of ECA attenuated the enlargement of prostatic tissues in the TP-induced BPH rat model, accompanied by histology, immunoblot, and serum dihydrotestosterone levels. Conclusions These results demonstrated that ECA exerted beneficial effects on BPH both in vitro and in vivo and might provide valuable information in the development of preventive or therapeutic agents for improving BPH.