Objective: Maumgyeol Basic service is a mental health evaluation and grade scoring software using the 2 channels EEG and photoplethysmogram (PPG). This service is supposed to assess potential at-risk groups with mental illness more easily, rapidly, and reliably. This study aimed to evaluate the clinical implication of the Maumgyeol Basic service. Methods: One hundred one healthy controls and 103 patients with a psychiatric disorder were recruited. Psychological evaluation (Mental Health Screening for Depressive Disorders [MHS-D], Mental Health Screening for Anxiety Disorders [MHS-A], cognitive stress response scale [CSRS], 12-item General Health Questionnaire [GHQ-12], Clinical Global Impression [CGI]) and digit symbol substitution test (DSST) were applied to all participants. Maumgyeol brain health score and Maumgyeol mind health score were calculated from 2 channel frontal EEG and PPG, respectively. Results: Participants were divided into three groups: Maumgyeol Risky, Maumgyeol Good, and Maumgyeol Usual. The Maumgyeol mind health scores, but not brain health scores, were significantly lower in the patients group compared to healthy controls. Maumgyeol Risky group showed significantly lower psychological and cognitive ability evaluation scores than Maumgyeol Usual and Good groups. Maumgyel brain health score showed significant correlations with CSRS and DSST. Maumgyeol mind health score showed significant correlations with CGI and DSST. About 20.6% of individuals were classified as the No Insight group, who had mental health problems but were unaware of their illnesses. Conclusion This study suggests that the Maumgyeol Basic service can provide important clinical information about mental health and be used as a meaningful digital mental healthcare monitoring solution to prevent symptom aggravation.

Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine the lesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reported based on artificial intelligence for computer-aided diagnosis. Recently, deep learning–based approaches have been applied to many possible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recent deep learning–based approaches for clinical applications, we present the current status and future direction of artificial intelligence for capsule endoscopy.
Artificial Intelligence* ; Capsule Endoscopy* ; Classification ; Diagnosis ; Endoscopy ; Specialization

Dyslipidemia is a major cause of cardiovascular diseases which represent a leading cause of death in humans. Diverse immune cells are known to be involved in the pathogenesis of cardiovascular diseases such as atherosclerosis. Conversely, dyslipidemia is known to be tightly associated with immune disorders in humans, as evidenced by a higher incidence of atherosclerosis in patients with autoimmune diseases including psoriasis, rheumatoid arthritis, and systemic lupus erythematosus. Given that the dyslipidemia-related autoimmune diseases are caused by autoreactive T cells and B cells, dyslipidemia seems to directly or indirectly regulate the adaptive immunity. Indeed, accumulating evidence has unveiled that proatherogenic factors can impact the differentiation and function of CD4+ T cells, CD8+ T cells, and B cells. This review discusses an updated overview on the regulation of adaptive immunity by dyslipidemia and proposes a potential therapeutic strategy for immune disorders by targeting lipid metabolism.

Dyslipidemia is a major cause of cardiovascular diseases which represent a leading cause of death in humans. Diverse immune cells are known to be involved in the pathogenesis of cardiovascular diseases such as atherosclerosis. Conversely, dyslipidemia is known to be tightly associated with immune disorders in humans, as evidenced by a higher incidence of atherosclerosis in patients with autoimmune diseases including psoriasis, rheumatoid arthritis, and systemic lupus erythematosus. Given that the dyslipidemia-related autoimmune diseases are caused by autoreactive T cells and B cells, dyslipidemia seems to directly or indirectly regulate the adaptive immunity. Indeed, accumulating evidence has unveiled that proatherogenic factors can impact the differentiation and function of CD4+ T cells, CD8+ T cells, and B cells. This review discusses an updated overview on the regulation of adaptive immunity by dyslipidemia and proposes a potential therapeutic strategy for immune disorders by targeting lipid metabolism.

Ataxia is presented by various etiologies, including acquired, genetic and degenerative disorders. Although hereditary ataxia is suspected when typical symptom of ataxia with concurrent is identified, it is sometimes difficult to diagnose hereditary ataxia without genetic test. Clinically, next generation sequencing technology has been developed and widely used for diagnosis of hereditary disease. Hereby, we experienced cases of genetically confirmed OPA1 mutation, which are presented with various clinical manifestations including ataxic gait and decreased visual acuity.

This retrospective case series of prospective data aims to describe the transaxillary approach for the treatment of upper thoracic spine pathology. Various surgical techniques and approaches have been reported across the literature to address upper thoracic spine pathology, including the cervicothoracic approach, anterior transsternal approach, posterolateral approach, supraclavicular approach, and lateral parascapular approaches. These techniques are invasive. A minimally invasive, less morbid, and direct access approach to the pathology of the upper thoracic spine has not been reported in the literature. Patients with pathology affecting the first thoracic vertebra up to the sixth thoracic vertebra were classified into the upper thoracic spine group. Patients with pathology below the sixth thoracic vertebra were excluded. Patients not having a minimum follow-up of 12 months were also excluded. The study analyzed 18 patients. The mean preoperative modified Japanese Orthopedic Association score was 7.2±1.44, which improved to 10.16±1.2 (p<0.05). The majority (14/18) of the patients had an excellent outcome. Three patients had good outcomes, and one patient had a fair outcome. Five cases of intraoperative dural leak were recorded, and one patient had postoperative neurological deficit. The transaxillary approach is a safe, viable, muscle-sparing, and minimally invasive approach for ventral pathologies of the upper thoracic spine.

Objective: The development of individual subtypes based on biomarkers offers a cost-effective and timely avenue to comprehending individual differences pertaining to mental health, independent from individuals’ subjective insights. Incorporating 2-channel electroencephalography (EEG) and photoplethysmogram (PPG), we sought to establish a subtype classification system with clinical relevance. Methods: One hundred healthy participants and 99 patients with psychiatric disorders were recruited. Classification thresholds were determined using the EEG and PPG data from 2,278 individuals without mental disorders, serving to classify subtypes in our sample of 199 participants. Multivariate analysis of variance was applied to examine psychological distinctions among these subtypes. K-means clustering was employed to verify the classification system. Results: The distribution of subtypes differed between healthy participants and those with psychiatric disorders. Cognitive abilities were contingent upon brain subtypes, while mind subtypes exhibited significant differences in symptom severity, overall health, and cognitive stress. K-means clustering revealed that the results of our theory-based classification and data-driven classification are comparable. The synergistic assessment of both brain and mind subtypes was also explored. Conclusion Our subtype classification system offers a concise means to access individuals’ mental health. The utilization of EEG and PPG signals for subtype classification offers potential for the future of digital mental healthcare.

Capsule endoscopy (CE) is a preferred diagnostic method for analyzing small bowel diseases. However, capsule endoscopes capture a sparse number of images because of their mechanical limitations. Post-procedural management using computational methods can enhance image quality. Additional information, including depth, can be obtained by using recently developed computer vision techniques. It is possible to measure the size of lesions and track the trajectory of capsule endoscopes using the computer vision technology, without requiring additional equipment. Moreover, the computational analysis of CE images can help detect lesions more accurately within a shorter time. Newly introduced deep leaning-based methods have shown more remarkable results over traditional computerized approaches. A large-scale standard dataset should be prepared to develop an optimal algorithms for improving the diagnostic yield of CE. The close collaboration between information technology and medical professionals is needed.
Capsule Endoscopes ; Capsule Endoscopy ; Cooperative Behavior ; Dataset ; Methods