No abstract available.
Breast Neoplasms* ; Breast* ; Cell Proliferation* ; MCF-7 Cells ; Polyamines

No abstract available.
Fatigue Syndrome, Chronic* ; Fibromyalgia

This is a case report of a cystic hygroma with polycystic kidney in a fetus which was suspected by ultrasonography and was confirmed by autopsy. Recently, we have experienced this case in 25-year old woman repeatedly and we report that with a brief review of relevant literature.
Adult ; Autopsy ; Female ; Fetus ; Humans ; Lymphangioma, Cystic* ; Polycystic Kidney Diseases* ; Ultrasonography

No abstract available.
Arthritis, Rheumatoid* ; Humans

No abstract available.
Tenosynovitis*

PURPOSE: This study was conducted to determine the factors affecting the prevention of needle stick injury. METHODS: Data collection was conducted during the period July 15-31, 2013 by a self-administered questionnaire involving 220 nurses working in 7 hospitals. The data was analyzed by SPSS v18 and AMOS v18. RESULTS: Actions by nurses to prevent needle stick injury were directly and indirectly influenced by perceived benefits, attitude toward the behavior, perceived behavioral control, and intention underlying the behavior. Specially, perceived behavioral control is verified to have not only direct influence but also indirect influence on the performance of preventive action through the intention underlying the behavior. Also, perceived benefits indirectly influence the intention toward the behavior and performance of preventive action through attitude toward the behavior and perceived behavioral control. The predictor variables in this model are 52% explicable in terms of intention of prevention action against needle stick injury, and 66% explicable in terms of performance of preventive action. CONCLUSION: To ensure high performance of preventive action against needle stick injury, constructing not only the solution that inspires the intention toward behavior but also a system that can positively solve and improve obstructive factors in behavioral performance is of primary importance.
Data Collection ; Intention ; Needles* ; Surveys and Questionnaires

OBJECTIVES: Sleep disorders cause changes of autonomic nervous system (ANS) which affect cardiovascular system. Primary insomnia (PI) makes acceleration of sympathetic nervous system (SNS) tone by sleep deficiency and arousal. Obstructive sleep apnea syndrome (OSAS) sets off SNS by frequent arousals and hypoxemias during sleep. We aimed to compare the changes of heart rate variability (HRV) indices induced by insomnia or sleep apnea to analyze for ANS how much to be affected by PI or OSAS. METHODS: Total 315 subjects carried out nocturnal polysomnography (NPSG) were categorized into 4 groups - PI, mild, moderate and severe OSAS. Severity of OSAS was determined by apnea-hypopnea index (AHI). Then we selected 110 subjects considering age, sex and valance of each group's size [Group 1 : PI (mean age=41.50+/-13.16 yrs, AHI <5, n=20), Group 2 : mild OSAS (mean age=43.67+/-12.11 yrs, AHI 5-15, n=30), Group 3 : moderate OSAS (mean age 44.93+/-12.38 yrs, AHI 16-30, n=30), Group 4 : severe OSAS (mean age=45.87+/-12.44 yrs, AHI >30, n=30)]. Comparison of HRV indices among the four groups was performed with ANCOVA (adjusted for age and body mass index) and Sidak post-hoc test. RESULTS: We found statistically significant differences in HRV indices between severe OSAS group and the other groups (PI, mild OSAS and moderate OSAS). And there were no significant differences in HRV indices among PI, mild and moderate OSAS group. In HRV indices of PI and severe OSAS group showing the most prominent difference in the group comparisons, average RR interval were 991.1+/-27.1 and 875.8+/-22.0 ms (p=0.016), standard deviation of NN interval (SDNN) was 85.4+/-6.6 and 112.8+/-5.4 ms (p=0.022), SDNN index was 57.5+/-5.2 and 87.6+/-4.2 (p<0.001), total power was 11,893.5+/-1,359.9 and 18,097.0+/-1,107.2 ms2 (p=0.008), very low frequency (VLF) was 7,534.8+/-1,120.1 and 11,883.8+/-912.0 ms2 (p=0.035), low frequency (LF) was 2,724.2+/-327.8 and 4,351.6+/-266.9 ms2 (p=0.003). CONCLUSIONS: VLF and LF which were correlated with SNS tone showed more increased differences between severe OSAS group and PI group than other group comparisons. We could suggest that severe OSAS group was more influential to increased SNS activity than PI group.
Acceleration ; Anoxia ; Arousal ; Autonomic Nervous System ; Cardiovascular System ; Heart ; Heart Rate ; Polysomnography ; Sleep Apnea Syndromes ; Sleep Apnea, Obstructive ; Sleep Wake Disorders ; Sleep Initiation and Maintenance Disorders ; Sympathetic Nervous System

Objective: This study investigates the reciprocal, longitudinal relationship between smartphone dependence and externalizing behavior problems in children. Methods: A total of 379 school-aged children (7–12 years old) were assessed using the Smartphone Overdependency Observer Scale and the Korean Version of the Child Behavior Checklist for Ages 6–18 at four six-month intervals from June 2021 to June 2022. Among them, 338 children completed at least two assessments. An autoregressive cross-lagged model was employed to examine the bidirectional relationships and temporal stability between smartphone overdependence and externalizing behavior problems while controlling for gender, age, and baseline internalizing behavior problems. Results: Both variables demonstrated significant autoregressive effects, indicating stability over time. Cross-lagged analysis revealed that higher smartphone dependence predicted increased externalizing behavior problems in subsequent periods while externalizing behavior problems did not predict future smartphone dependence. Conclusion Smartphone dependence appears to contribute to externalizing behavior problems in children, highlighting the critical need for early interventions that promote healthy digital habits to mitigate behavioral challenges.

Objective: This study investigates the reciprocal, longitudinal relationship between smartphone dependence and externalizing behavior problems in children. Methods: A total of 379 school-aged children (7–12 years old) were assessed using the Smartphone Overdependency Observer Scale and the Korean Version of the Child Behavior Checklist for Ages 6–18 at four six-month intervals from June 2021 to June 2022. Among them, 338 children completed at least two assessments. An autoregressive cross-lagged model was employed to examine the bidirectional relationships and temporal stability between smartphone overdependence and externalizing behavior problems while controlling for gender, age, and baseline internalizing behavior problems. Results: Both variables demonstrated significant autoregressive effects, indicating stability over time. Cross-lagged analysis revealed that higher smartphone dependence predicted increased externalizing behavior problems in subsequent periods while externalizing behavior problems did not predict future smartphone dependence. Conclusion Smartphone dependence appears to contribute to externalizing behavior problems in children, highlighting the critical need for early interventions that promote healthy digital habits to mitigate behavioral challenges.

Objective: This study investigates the reciprocal, longitudinal relationship between smartphone dependence and externalizing behavior problems in children. Methods: A total of 379 school-aged children (7–12 years old) were assessed using the Smartphone Overdependency Observer Scale and the Korean Version of the Child Behavior Checklist for Ages 6–18 at four six-month intervals from June 2021 to June 2022. Among them, 338 children completed at least two assessments. An autoregressive cross-lagged model was employed to examine the bidirectional relationships and temporal stability between smartphone overdependence and externalizing behavior problems while controlling for gender, age, and baseline internalizing behavior problems. Results: Both variables demonstrated significant autoregressive effects, indicating stability over time. Cross-lagged analysis revealed that higher smartphone dependence predicted increased externalizing behavior problems in subsequent periods while externalizing behavior problems did not predict future smartphone dependence. Conclusion Smartphone dependence appears to contribute to externalizing behavior problems in children, highlighting the critical need for early interventions that promote healthy digital habits to mitigate behavioral challenges.