Understanding South Korean women workers' career transition experiences: using the career decision tree model.

Introduction: Relatively little research has explored non-Western women workers and their career transitions within their unique cultural contexts. Thus, more context-sensitive approaches to women's career trajectories are needed. Methods: Based on Bian and Wang's Career Decision Tree Model (2019) as a conceptual framework, the reasons for South Korean women workers' career transitions and influencing factors were explored using a qualitative approach with in-depth interviews with 35 South Korean women workers at various career stages. Results and Discussion: Their main motive of career transitions was difficulty maintaining their physical and mental health, which stemmed from their demanding work life. A typical issue, the burden of child rearing and family responsibilities, was also reported, but it was not the primary reason for their career transitions. Instead, the women workers often mentioned these responsibilities along with other reasons. Other reasons were unresolved career interests and expectations associated with their lack of career goals and preparation prior to joining the labor market. These factors led to significant changes in women's values and priorities along their career path, which finally triggered a decision to make a career transition. South Korean socio-cultural characteristics embedded in the South Korean women's personal and organizational lives provide insights on how to interpret the findings. Although on the surface some of our findings appeared to confirm previous studies on women's career transitions in Western-based literature, noteworthy differences were discovered when delving deeper into women's career transitions in the South Korean context.

Interrupting Effect of Social Distancing on Ischemic Heart Disease, Asthma, Stroke, and Suicide Attempt Patients by PM2.5 Exposure.

PURPOSE: This study aimed to examine the interrupting effect of social distancing (SD) on emergency department (ED) patients with ischemic heart disease (IHD), stroke, asthma, and suicide attempts by PM2.5 exposure in eight Korean megacities from 2017 to 2020. MATERIALS AND METHODS: The study used National Emergency Department Information System and AirKorea data. A total of 469014 patients visited EDs from 2017 to 2020. Interrupted time series analysis was employed to examine changes in the level and slope of the time series, relative risk, and confidence intervals (CIs) by PM2.5 exposure. The SD level was added to the sensitivity analysis. RESULTS: The interrupted time series analysis demonstrated a significant increase in the ratio of relative risk (RRR) of IHD patients in Seoul (RRR=1.004, 95% CI: 1.001, 1.006) and Busan (RRR=1.007, 95% CI: 1.002, 1.012) post-SD. Regarding stroke, only patients in Seoul exhibited a significant decrease post-SD (RRR=0.995, 95% CI: 0.991, 0.999). No significant changes were observed for asthma in any of the cities. In the case of suicide attempts, Ulsan demonstrated substantial pre-SD (RR=0.827, 95% CI: 0.732, 0.935) and post-SD (RRR=1.200, 95% CI: 1.057, 1.362) differences. CONCLUSION: While the interrupting effect of SD was not as pronounced as anticipated, this study did validate the effectiveness of SD in modifying health behaviors and minimizing avoidable visits to EDs in addition to curtailing the occurrence of infectious diseases.

Clinical validation of enhanced CT imaging for distal radius fractures through conditional Generative Adversarial Networks (cGAN).

BACKGROUND/PURPOSE: Distal radius fractures (DRFs) account for approximately 18% of fractures in patients 65 years and older. While plain radiographs are standard, the value of high-resolution computed tomography (CT) for detailed imaging crucial for diagnosis, prognosis, and intervention planning, and increasingly recognized. High-definition 3D reconstructions from CT scans are vital for applications like 3D printing in orthopedics and for the utility of mobile C-arm CT in orthopedic diagnostics. However, concerns over radiation exposure and suboptimal image resolution from some devices necessitate the exploration of advanced computational techniques for refining CT imaging without compromising safety. Therefore, this study aims to utilize conditional Generative Adversarial Networks (cGAN) to improve the resolution of 3 mm CT images (CT enhancement). METHODS: Following institutional review board approval, 3 mm-1 mm paired CT data from 11 patients with DRFs were collected. cGAN was used to improve the resolution of 3 mm CT images to match that of 1 mm images (CT enhancement). Two distinct methods were employed for training and generating CT images. In Method 1, a 3 mm CT raw image was used as input with the aim of generating a 1 mm CT raw image. Method 2 was designed to emphasize the difference value between the 3 mm and 1 mm images; using a 3 mm CT raw image as input, it produced the difference in image values between the 3 mm and 1 mm CT scans. Both quantitative metrics, such as peak signal-to-noise ratio (PSNR), mean squared error (MSE), and structural similarity index (SSIM), and qualitative assessments by two orthopedic surgeons were used to evaluate image quality by assessing the grade (1~4, which low number means high quality of resolution). RESULTS: Quantitative evaluations showed that our proposed techniques, particularly emphasizing the difference value in Method 2, consistently outperformed traditional approaches in achieving higher image resolution. In qualitative evaluation by two clinicians, images from method 2 showed better quality of images (grade: method 1, 2.7; method 2, 2.2). And more choice was found in method 2 for similar image with 1 mm slice image (15 vs 7, p = 201). CONCLUSION: In our study utilizing cGAN for enhancing CT imaging resolution, the authors found that the method, which focuses on the difference value between 3 mm and 1 mm images (Method 2), consistently outperformed.

Attenuation of phytofungal pathogenicity of Ascomycota by autophagy modulators.

Autophagy in eukaryotes functions to maintain homeostasis by degradation and recycling of long-lived and unwanted cellular materials. Autophagy plays important roles in pathogenicity of various fungal pathogens, suggesting that autophagy is a novel target for development of antifungal compounds. Here, we describe bioluminescence resonance energy transfer (BRET)-based high-throughput screening (HTS) strategy to identify compounds that inhibit fungal ATG4 cysteine protease-mediated cleavage of ATG8 that is critical for autophagosome formation. We identified ebselen (EB) and its analogs ebselen oxide (EO) and 2-(4-methylphenyl)-1,2-benzisothiazol-3(2H)-one (PT) as inhibitors of fungal pathogens Botrytis cinerea and Magnaporthe oryzae ATG4-mediated ATG8 processing. The EB and its analogs inhibit spore germination, hyphal development, and appressorium formation in Ascomycota pathogens, B. cinerea, M. oryzae, Sclerotinia sclerotiorum and Monilinia fructicola. Treatment with EB and its analogs significantly reduced fungal pathogenicity. Our findings provide molecular insights to develop the next generation of antifungal compounds by targeting autophagy in important fungal pathogens.