Effects of Long-acting Injectable 3-Monthly Paliperidone Palmitate on the Clinical and Social Performance of Patients with Schizophrenia

Jihoon Oh(Jihoon Oh),Jihye Oh(Jihye Oh),Dong Wook Kim(Dong Wook Kim),HyunChul Youn(HyunChul Youn),Sae-Hoon Kim(Sae-Hoon Kim),Soo In Kim(Soo In Kim),In Won Chung(In Won Chung),Kuan Shu Wang(Kuan Shu Wa 대한정신약물학회 2023 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.21 No.1

Objective: To investigate the effects of long-acting injectable 3-monthly paliperidone palmitate on the clinical and social functioning of patients with schizophrenia. Methods: This study enrolled patients with schizophrenia receiving long-acting injectable 1-monthly paliperidone palmitate for at least 4 months and who subsequently received 3-monthly paliperidone palmitate. Accordingly, 418 patients were followed up for 24 weeks. Their clinical symptoms and social functioning were measured using the Clinical Global Impression-Severity of Illness and Personal and Social Performance scales. Results: The Personal and Social Performance total score was significantly higher after 3-monthly paliperidone palmitate treatment than at baseline (baseline vs. week 24: 54.3 ± 18.0 vs. 61.0 ± 14.5 [mean ± standard deviation]; p < 0.001; Wilcoxon signed-rank test); the proportion of patients in the mildly ill group (scores 71−100) also increased significantly (baseline vs. week 24: 16.5% vs. 20.6%; p < 0.001; McNemar-Bowker test). The mean Clinical Global Impression-Severity of Illness score decreased significantly (baseline vs. week 24: 3.7 ± 1.0 vs. 3.4 ± 0.9; p < 0.001; Wilcoxon signed-rank test), as did the proportion of patients in the severely ill group (baseline vs. week 24: 4.1% vs. 2.1%; p < 0.001; McNemar-Bowker test). Conclusion: Continuous 3-monthly paliperidone palmitate treatment significantly enhances the personal and social performance of patients with schizophrenia and reduces the proportion of those with severe illness. These findings suggest that long-acting injectable antipsychotic administration at intervals longer than 1 month might improve the social functioning of and promote return to activities of daily living in patients with schizophrenia.

Effect of Home-based Self-administered Transcranial Direct Stimulation in Patients with Mild to Moderate Major Depressive Disorder: A Single-arm, Multicentral Trial

Jihoon Oh(Jihoon Oh),Sekye Jeon(Sekye Jeon),Tae Hyon Ha(Tae Hyon Ha),Woojae Myung(Woojae Myung),Seung-Hwan Lee(Seung-Hwan Lee),Young-Hoon Ko(Young-Hoon Ko),Do Hoon Kim(Do Hoon Kim),Hwa-Young Lee(Hwa-Y 대한정신약물학회 2023 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.21 No.2

Objective: Although the effects and safety of transcranial direct current stimulation (tDCS) treatment in depressive patients are largely investigated, whether the self-administration of tDCS treatment at patient’s home is comparable to clinic-based treatment is still unknown. Methods: In this single-arm, multi-center clinical trial, 61 patients with mild to moderate major depressive disorder were enrolled. tDCS treatment was delivered at the patient’s home once a day, 5 to 7 times a week for 6 weeks, and each session lasted for 30 minutes. The primary outcome was a total Beck-Depression Inventory-II score, and no concurrent antidepressants were used. Results: The remission rates in both Full-Analysis (FA) (n = 61) and Per-Protocol (PP) (n = 43) groups were statistically significant (FA: 57.4% [0.44−0.70], PP: 62.8% [0.47−0.77]; percent [95% confidence interval]). The degree of depression- related symptoms was also significantly improved in 2, 4, and 6 weeks after the treatment when compared with baseline. There was no significant association between treatment compliance and remission rate in both FA and PP groups. Conclusion: These results suggest that acute treatment of patient-administered tDCS might be effective in improving the subjective feeling of depressive symptoms in mild to moderate major depressive disorder patients.

Auditory imagery modulates frequency-specific areas in the human auditory cortex.

Oh, Jihoon,Kwon, Jae Hyung,Yang, Po Song,Jeong, Jaeseung Published by the MIT Press with the Cognitive Neur 2013 Journal of cognitive neuroscience Vol.25 No.2

<P>Neural responses in early sensory areas are influenced by top-down processing. In the visual system, early visual areas have been shown to actively participate in top-down processing based on their topographical properties. Although it has been suggested that the auditory cortex is involved in top-down control, functional evidence of topographic modulation is still lacking. Here, we show that mental auditory imagery for familiar melodies induces significant activation in the frequency-responsive areas of the primary auditory cortex (PAC). This activation is related to the characteristics of the imagery: when subjects were asked to imagine high-frequency melodies, we observed increased activation in the high- versus low-frequency response area; when the subjects were asked to imagine low-frequency melodies, the opposite was observed. Furthermore, we found that A1 is more closely related to the observed frequency-related modulation than R in tonotopic subfields of the PAC. Our findings suggest that top-down processing in the auditory cortex relies on a mechanism similar to that used in the perception of external auditory stimuli, which is comparable to early visual systems.</P>

Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm

Oh, Jihoon,Yun, Kyongsik,Maoz, Uri,Kim, Tae-Suk,Chae, Jeong-Ho Elsevier 2019 Journal of affective disorders Vol.257 No.-

<P><B>Abstract</B></P> <P><B>Background</B></P> <P>As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depression has remained challenging. Deep-learning algorithms can be applied to assess the factors leading up to prevalence and clinical manifestations of depression.</P> <P><B>Methods</B></P> <P>Customized deep-neural-network and machine-learning classifiers were assessed using survey data from 19,725 participants from the NHANES database (from 1999 through 2014) and 4949 from the South Korea NHANES (K-NHANES) database in 2014.</P> <P><B>Results</B></P> <P>A deep-learning algorithm showed area under the receiver operating characteristic curve (AUCs) of 0.91 and 0.89 for detecting depression in NHANES and K-NHANES, respectively. The deep-learning algorithm trained with serial datasets (NHANES, from 1999 to 2012), predicted the prevalence of depression in the following two years of data (NHANES, 2013 and 2014) with an AUC of 0.92. Machine learning classifiers trained with NHANES could further predict depression in K-NHANES. There, logistic regression had the highest performance (AUC, 0.77) followed by deep learning algorithm (AUC, 0.74).</P> <P><B>Conclusions</B></P> <P>Deep neural-networks managed to identify depression well from other health and demographic factors in both the NHANES and K-NHANES datasets. The deep-learning algorithm was also able to predict depression relatively well on new data set—cross temporally and cross nationally. Further research can delineate the clinical implications of machine learning and deep learning in detecting disease prevalence and progress as well as other risk factors for depression and other mental illnesses.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Estimating epidemiological contributors to depression and predicting the prevalence of depression are still challenging. </LI> <LI> We aimed to estimate factors affecting depression in National Health and Nutrition Examination Survey (NHANES) datasets using deep learning and machine learning algorithms. </LI> <LI> Deep-learning achieved a high performance for identifying depression on the NHANES datasets of both the United States and South Korea. </LI> <LI> Trained deep-learning and machine learning algorithms are useful for estimating the prevalence of depression. </LI> </UL> </P>

Effect of Self-administered Transcranial Direct Stimulation in Patients with Major Depressive Disorder: A Randomized, Single-blinded Clinical Trial

Jihoon Oh,Kuk-In Jang,Sekye Jeon,Jeong-Ho Chae 대한정신약물학회 2022 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.20 No.1

Objective: In numerous studies that have addressed transcranial direct current stimulation (tDCS) devices, participants visit the hospital regularly and undergo stimulation directed by health professionals. This method has the advantage of being able to deliver accurate stimuli in a controlled environment, but it does not adopt the merits of tDCS portability and applicability. Thus, it may be necessary to investigate how self-administered tDCS treatment at home affects depression- related symptoms. Methods: In this randomized, single-blinded clinical trial, 58 patients with major depressive disorder were assigned to active and sham tDCS stimulation groups, and treatment responses were evaluated biweekly over six weeks. Both active and sham tDCS treatment group were treated with escitalopram. All participants were instructed the protocol and usage of at-home tDCS device, and self-administered tDCS treatment at their home. Results: The beck-depression inventory score decreased significantly as treatment progressed, and the degree of symptom improvement was significantly higher in the active group than in the sham tDCS group. There were no significant differences between the two groups in other indices, including the Hamilton Depression Scale. Conclusion: These results suggest that patient-administered tDCS treatment might be effective in improving subjective symptoms of depression.

Decreased Health-Seeking Behaviors in People With Depressive Symptoms: The Korea National Health and Nutrition Examination Survey 2014, 2016, and 2018

Oh Jihye,Hong Hyungsook,Oh Jihoon,Kim Tae-Suk 대한신경정신의학회 2022 PSYCHIATRY INVESTIGATION Vol.19 No.2

Objective The purpose of this study was to investigate the effects of depressive symptoms on health-seeking behaviors using the large epidemiological study data of the Korea National Health and Nutrition Examination (KNHANES).Methods Data from the Korea National Health and Nutrition Examination Survey (KNHANES), which is a large-scale national survey, were used in this study. The Patient Health Questionnaire-9 (PHQ-9) was used to assess the depressive state of the participants. Specialized self-reported questionnaires that included questions about health-seeking behaviors were also performed. To examine the relationships between depression and health-seeking behaviors, complex sample logistic regression models with control for covariates were used.Results There was a significant association between decreased health-seeking behaviors and depressive symptoms in adults (odds ratio [OR]: 3.11, 95% confidence interval [CI]: 2.44–3.96). The association was found to be especially strong in males (OR: 2.63, 95% CI: 1.69–4.10) versus in females (OR: 2.49, 95% CI: 1.90–3.27). With regard to age group, younger adults (19–44 years of age) showed the highest OR (OR: 3.07, 95% CI: 2.12–4.45).Conclusion Our findings support the idea that there is a significant association between health-seeking behaviors and depressive symptoms in the Korean population. These results suggest that individuals with decreased health-seeking behaviors could be evaluated for depressive symptoms.

Speech-To-Text와 화면 전환 인식을 활용한 비대면 교육 / 회의 플랫폼에 대한 연구

오지훈(Jihoon Oh),김건오(Guno Kim),누비아 파스칼(Nnubia Pascal Nnamdi),손윤식(Yunsik Son) 한국정보과학회 2021 한국정보과학회 학술발표논문집 Vol.2021 No.12

소리쟁이 뿌리의 유효성분에 대한 연구

오지훈(Jihoon Oh),이문순(Moon-Soon Lee) 한국약용작물학회 2012 한국약용작물학회 학술대회논문집 Vol.2012 No.1

Hair Separation and Detection in Mutant Drosophila Hair Images

Jihoon Kwak,Chun-Taek Oh,Sung-Jun Han,Myungjoo Kang 한국산업응용수학회 2010 한국산업응용수학회 학술대회 논문집 Vol.5 No.1

To test the genotoxicity of drug candidates in the process of drug discovery, The Drosophila wing somatic mutation and recombination test (SMART)[3][1] is used, which analyzes the development frequency of mutant hairs of Drosophila. Because the current mutant hair counting method is totally manual work, in which humans search and count the mutant hairs by their eyes through the microscope, its speed and accuracy is limited. Our goal is to culture the mutant Drosophila using possibly genotoxic chemicals, to take the image of Drosophila wing hair, and to develop an automated system that counts mutant hairs and tells the genotoxicity of the chemicals. In this work, we explain the image acquisition method using multi-focused image stack, hair separation method into upper and lower hair, and hair detection method using template matching.

Development of HIL simulator for the sensitivity analysis of factors influencing ESC performance

Jihoon Roh,Kangwon Lee,Jongil Lee,Seungkyu Oh,Hyoungsoo Kim,Jinhee Jang 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

The performance of ESC system is greatly influenced by vehicle design factor and tire performance. Butmany car maker develop the vehicle can have variability to meet the variety consumer requirement of several countries.ESC system also should be developed with considering the chassis configuration of vehicle and being satisfied therequirement. So, robust control algorithm and value-added-function regarding market requirements are required. The more variant vehicle has, the more complex validation test in vehicle level become. Test for the evaluation of ESCperformance in real vehicle is time consuming and required much cost. Therefore, many evaluation processes isreplaced by laboratory test such as hardware in the loop simulation. HILS (Hardware in the loop simulation) is thecomputer simulation include real hardware control unit in simulation loop. It is useful tool to test and validate these controllers in phase of development. This paper described the outline of HIL simulation for ESC performance evaluation and the process of HIL simulator development is explained, then interface model is introduced between real time platform and hardware system. Finally, automated system application for the change of factor influencing ESC performance is presented.