Objective: To compare the clinical characteristics, support system, and personality traits of cannabis and stimulant users in South Korea. Methods: This study was based on electronic medical records. Among a total of 152 subjects who suspected of drug use and who underwent six types of urine-based drug screening tests at the National Center for Mental Health, 104 people who underwent both an interview with a psychiatrist and a psychological test were selected and classified according to the type of substance used. Psychological and personality characteristics were examined through the National Center for Mental Health psychological test battery for addiction. The differences in characteristics between cannabis (n=60) and stimulant (n=18) users were analyzed by an independent t-test for parametric data and chi-square test or Fisher’s exact test for nonparametric data, and analysis of covariance for psychological tests. Results: The average age of cannabis users was lower than that of stimulant users and they were more often single. Substance cravings were higher in stimulant users, who more often had a psychiatric history than cannabis users. Moreover, stimulant users had higher clinical scale scores for depression and anxiety. Among the Minnesota Multiphasic Personality Inventory-II clinical scale scores, there was a significant difference in social introversion scores between groups. Conclusion We found differences in demographic, psychological, and personality characteristics between cannabis and stimulant users in South Korea. Considering the recent increase in illegal drug use in South Korea, further follow-up and policy research on drug users are needed.

Here we describe characterization of chicken neuronal Per-Arnt-Sim domain 3 (NPAS3) gene during embryogenesis including examinations of expression pattern and function of the gene. RTPCR assay showed that the primary tissue of expression for this gene is the central nervous system (CNS) while RNA in situ hybridization assay confirmed that NPAS3 was expressed in the ventricular zone of developing neural tube as early as Hamburger-Hamilton (HH) stage 20. Ectopic over-expression of the gene in ovo in the developing chicken neural tube by electroporation had little effect on stem cell population, overall neurogenesis, and motor neuron differentiation. We discuss the implications of our observation.
Central Nervous System ; Chickens ; Electroporation ; Embryonic Development ; Female ; In Situ Hybridization ; Motor Neurons ; Neural Tube ; Neurogenesis ; Neurons ; Pregnancy ; RNA ; Stem Cells

PURPOSE: Although previous studies on the screw-home movement (SHM) for autopsy specimen and walking of living persons conducted, the possibility of acquiring SHM based on inertial measurement units received little attention. This study aimed to investigate the possibility of measuring SHM for the non-weighted bearing using a micro-electro-mechanical system-based wearable motion capture system (MEMSS). METHODS: MEMSS and camera-based motion analysis systems were used to obtain kinematic data of the knee joint. The knee joint moved from the flexion position to a fully extended position and then back to the start point. The coefficient of multiple correlation and the difference in the range of motion were used to assess the waveform similarity in the movement measured by two measurement systems. RESULTS: The waveform similarity in the sagittal plane was excellent and the in the transverse plane was good. Significant differences were found in the sagittal plane between the two systems (p<0.05). However, there was no significant difference in the transverse plane between the two systems (p>0.05). CONCLUSION The SHM during the passive motion without muscle contraction in the non-weighted bearing appeared in the entire range. We thought that the MEMSS could be easily applied to the acquisition of biomechanical data on the knee related to physical therapy.

Objective: Insomnia is associated with elevated high-frequency electroencephalogram power in the waking state. Although affective symptoms (e.g., depression and anxiety) are commonly comorbid with insomnia, few reports distinguished objective sleep disturbance from affective symptoms. In this study, we investigated whether daytime electroencephalographic activity explains insomnia, even after controlling for the effects of affective symptoms. Methods: A total of 107 participants were divided into the insomnia disorder (n = 58) and healthy control (n = 49) groups using the Mini-International Neuropsychiatric Interview and diagnostic criteria for insomnia disorder. The participants underwent daytime resting-state electroencephalography sessions (64 channels, eye-closed). Results: The insomnia group showed higher levels of anxiety, depression, and insomnia than the healthy group, as well as increased beta [t(105) = −2.56, p = 0.012] and gamma [t(105) = −2.44, p = 0.016] spectra. Among all participants, insomnia symptoms positively correlated with the intensity of beta (r = 0.28, p ＜ 0.01) and gamma (r = 0.25, p ＜ 0.05) spectra. Through hierarchical multiple regression, the beta power showed the additional ability to predict insomnia symptoms beyond the effect of anxiety (ΔR2 = 0.041, p = 0.018). Conclusion Our results showed a significant relationship between beta electroencephalographic activity and insomnia symptoms, after adjusting for other clinical correlates, and serve as further evidence for the hyperarousal theory of insomnia. Moreover, resting-state quantitative electroencephalography may be a supplementary tool to assess insomnia.

Purpose: This study aimed to determine which interventions are effective in increasing hamstring flexibility due to changes in the range of motion (ROM) and pennation angle (PA) when foam rolling (FR) and proprioceptive neuromuscular facilitation (PNF) stretching were performed. Methods: A total of 24 healthy participants who agreed to participate in the study were randomly chosen. The participants were divided into three groups of eight people: Control, FR, and PNF stretching groups. The hip flexion angle (ROM) and PA of the hamstrings were measured before and after the experiment. The Wilcoxon signed-rank test was used to analyze the ROM and PA for each group by comparing the before and after results. The Kruskal-Wallis test and the Mann-Whitney U test were used to analyze the increase in hamstring flexibility between the groups. Results: A statistically significant difference was observed in the ROM and PA within all groups, and only the ROM was significant in the comparison between the three groups. In the comparison between the control and other two groups, a significant difference was noted in both the ROM and PA in the FR group and only the ROM in the PNF stretching group (p < 0.05). In the comparison between the FR and PNF stretching groups, no significant difference was observed (p > 0.05). Conclusion These findings FR and PNF stretching increased the ROM; however, no change in PA was observed. Therefore, FR and PNF stretching were considered effective interventions in immediately increasing hamstring flexibility.

Purpose: This study investigated the immediate biomechanical effects of unilateral mastication for 10 minutes on the temporomandibular joint (TMJ) with 21 healthy adult participants. Methods: The gum group chewed gum on the right side for 10 minutes, and the control group rested for 10 minutes. Biomechanical data were obtained using a three-dimensional infrared camera before and after intervention. An independent t-test assessed the variation of kinematic data to identify differences between before and after intervention. Results: Among biomechanical variables, the gum group’s length of the left forehead middle region and the temporomandibular joint angle decreased compared to the control group (p<0.05). Conclusion Caution with unilateral masticatory activity is recommended, as unilateral mastication causes biomechanical changes due to excessive load on the soft tissues of the contralateral TMJ.

Objective: The abuse of prescription drugs and over-the-counter medicines has been a major issue addressed as a serious public health problem worldwide. This study explored factors contributing to substance abuse in Korea by examining the status of substance abuse among Korean adults and evaluating their knowledge, attitudes, and intentions toward substance abuse. Methods: Data were collected online from a sample of participants 19 years old or older from May 20 to June 1, 2020 (n=1,020). The survey consisted of questions on demographics, perceptions of drug risk, motives for drug use, and attitudes toward drug addiction treatment. Principal component and multiple logistic regression analyses were used to explore the factors contributing to the perception of drug abuse. Results: In the multivariate regression analysis, overconfidence in handling drug usage, acceptance of addictive substances, and affirmation of public support for drug abuse were associated with opioid abuse (Nagelkerke R2=0.486), and additionally affirmation of legal cannabis usage and motivation to use diet pills were associated with diet pill abuse (Nagelkerke R2=0.569). Conclusion The findings of this study suggest that the actual situation of substance abuse among Korean adults increases awareness of and attitudes toward drug use related to substance abuse.

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Various barriers hinder the successful application and widespread adoption of AI in radiology, such as limited annotated data, data privacy and security, data heterogeneity, imbalanced data, model interpretability, overfitting, and integration with clinical workflows. In this review, some of the various possible solutions to these challenges are presented and discussed; these include training with longitudinal and multimodal datasets, dense training with multitask learning and multimodal learning, self-supervised contrastive learning, various image modifications and syntheses using generative models, explainable AI, causal learning, federated learning with large data models, and digital twins.