Hong, Bok Sil;Baek, Suji;Kim, Myoung-Ryu;Park, Sun Mi;Kim, Bom Sahn;Kim, Jisu;Lee, Kang Pa
Korean Journal of Exercise Nutrition
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v.25
no.4
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pp.38-44
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2021
[Purpose] Exercise can prevent conditions such as atrophy and degenerative brain diseases. However, owing to individual differences in athletic ability, exercise supplements can be used to improve a person's exercise capacity. Schisandra chinensis (SC) is a natural product with various physiologically active effects. In this study, we analyzed SC using a pharmacological network and determined whether it could be used as an exercise supplement. [Methods] The active compounds of SC and target genes were identified using the Traditional Chinese Medicine Database and Analysis Platform (TCMSP). The active compound and target genes were selected based on pharmacokinetic (PK) conditions (oral bioavailability (OB) ≥ 30%, Caco-2 permeability (Caco-2) ≥ -0.4, and drug-likeness (DL) ≥ 0.18). Gene ontology (GO) was analyzed using the Cytoscape software. [Results] Eight active compounds were identified according to the PK conditions. Twenty-one target genes were identified after excluding duplicates in the eight active compounds. The top 10 GOs were analyzed using GO-biological process analysis. GO was subsequently divided into three representative categories: postsynaptic neurotransmitter receptor activity (53.85%), an intracellular steroid hormone receptor signaling pathway (36.46%), and endopeptidase activity (10%). SC is related to immune function. [Conclusion] According to the GO analysis, SC plays a role in immunity and inflammation, promotes liver metabolism, improves fatigue, and regulates the function of steroid receptors. Therefore, we suggest SC as an exercise supplement with nutritional and anti-fatigue benefits.
Neuromorphic technology is proposed to complement the shortcomings of existing artificial intelligence technology by mimicking the human brain structure and computational process with hardware. NA-IDE has also been proposed for developing neuromorphic hardware-based IoT applications. To implement an SNN model in NA-IDE, commonly used input data must be transformed for use in the SNN model. In this paper, we implemented a neural coding method encoder component that converts image data into a spike train signal and uses it as an SNN input. The decoder component is implemented to convert the output back to image data when the SNN model generates a spike train signal. If the decoder component uses the same parameters as the encoding process, it can generate static data similar to the original data. It can be used in fields such as image-to-image and speech-to-speech to transform and regenerate input data using the proposed encoder and decoder.
Intraventricular hemorrhage (IVH) is a serious concern for preterm infants and can predispose such infants to brain injury and poor neurodevelopmental outcomes. IVH is particularly common in preterm infants. Although advances in obstetric management and neonatal care have led to a lower mortality rate for preterm infants with IVH, the IVH-related morbidity rate in this population remains high. Therefore, the present review investigated the pathophysiology of IVH and the evidence related to interventions for prevention. The analysis of the pathophysiology of IVH was conducted with a focus on the factors associated with cerebral hemodynamics, vulnerabilities in the structure of cerebral vessels, and host or genetic predisposing factors. The findings presented in the literature indicate that fluctuations in cerebral blood flow, the presence of hemodynamic significant patent ductus arteriosus, arterial carbon dioxide tension, and impaired cerebral venous drainage; a vulnerable or fragile capillary network; and a genetic variant associated with a mechanism underlying IVH development may lead to preterm infants developing IVH. Therefore, strategies focused on antenatal management, such as routine corticosteroid administration and magnesium sulfate use; perinatal management, such as maternal transfer to a specialized center; and postnatal management, including pharmacological agent administration and circulatory management involving prevention of extreme blood pressure, hemodynamic significant patent ductus arteriosus management, and optimization of cardiac function, can lower the likelihood of IVH development in preterm infants. Incorporating neuroprotective care bundles into routine care for such infants may also reduce the likelihood of IVH development. The findings regarding the pathogenesis of IVH further indicate that cerebrovascular status and systemic hemodynamic changes must be analyzed and monitored in preterm infants and that individualized management strategies must be developed with consideration of the risk factors for and physiological status of each preterm infant.
Objective : Deep learning is a machine learning approach based on artificial neural network training, and object detection algorithm using deep learning is used as the most powerful tool in image analysis. We analyzed and evaluated the diagnostic performance of a deep learning algorithm to identify skull fractures in plain radiographic images and investigated its clinical applicability. Methods : A total of 2026 plain radiographic images of the skull (fracture, 991; normal, 1035) were obtained from 741 patients. The RetinaNet architecture was used as a deep learning model. Precision, recall, and average precision were measured to evaluate the deep learning algorithm's diagnostic performance. Results : In ResNet-152, the average precision for intersection over union (IOU) 0.1, 0.3, and 0.5, were 0.7240, 0.6698, and 0.3687, respectively. When the intersection over union (IOU) and confidence threshold were 0.1, the precision was 0.7292, and the recall was 0.7650. When the IOU threshold was 0.1, and the confidence threshold was 0.6, the true and false rates were 82.9% and 17.1%, respectively. There were significant differences in the true/false and false-positive/false-negative ratios between the anterior-posterior, towne, and both lateral views (p=0.032 and p=0.003). Objects detected in false positives had vascular grooves and suture lines. In false negatives, the detection performance of the diastatic fractures, fractures crossing the suture line, and fractures around the vascular grooves and orbit was poor. Conclusion : The object detection algorithm applied with deep learning is expected to be a valuable tool in diagnosing skull fractures.
Proceedings of the Korean Society of Computer Information Conference
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2021.07a
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pp.305-307
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2021
Alzheimer's Disease (AD) is a cognitive disorder characterized by memory impairment that can be assessed at early stages based on administering clinical tests. However, the AD pathophysiological mechanism is still poorly understood due to the difficulty of distinguishing different levels of AD severity, even using a variety of brain modalities. Therefore, in this study, we present a hybrid EEG-fNIRS modalities to compensate for each other's weaknesses with the help of Machine Learning (ML) techniques for classifying four subject groups, including healthy controls (HC) and three distinguishable groups of AD levels. A concurrent EEF-fNIRS setup was used to record the data from 41 subjects during Oddball and 1-back tasks. We employed both a traditional neural network (NN) and a CNN-LSTM hybrid model for fNIRS and EEG, respectively. The final prediction was then obtained by using majority voting of those models. Classification results indicated that the hybrid EEG-fNIRS feature set achieved a higher accuracy (71.4%) by combining their complementary properties, compared to using EEG (67.9%) or fNIRS alone (68.9%). These findings demonstrate the potential of an EEG-fNIRS hybridization technique coupled with ML-based approaches for further AD studies.
Acute necrotizing encephalopathy (ANE) is a rare but deadly complication with an unclear pathogenesis. We aimed to elucidate the immune characteristics of H1N1 influenza virus-associated ANE (IANE) and provide a potential therapeutic approach for IANE. Seven pediatric cases from a concentrated outbreak of H1N1 influenza were included in this study. The patients' CD4+ T cells from peripheral blood decreased sharply in number but highly expressed Eomesodermin (Eomes), CD69 and PD-1, companied with extremely high levels of IL-6, IL-8 in the cerebrospinal fluid and plasma. Patient 2, who showed high fever and seizures and was admitted to the hospital very early in the disease course, received intravenous tocilizumab and subsequently showed a reduction in temperature and a stable conscious state 24 h later. In conclusion, a proinflammatory cytokine storm associated with activated CD4+ T cells may cause severe brain pathology in IANE. Tocilizumab may be helpful in treating IANE.
Sun Murray Han;Hye Young Na;Onju Ham;Wanho Choi;Moah Sohn;Seul Hye Ryu;Hyunju In;Ki-Chul Hwang;Chae Gyu Park
IMMUNE NETWORK
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v.16
no.1
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pp.61-74
/
2016
Dendritic cells (DCs) are professional antigen-presenting cells that sample their environment and present antigens to naïve T lymphocytes for the subsequent antigen-specific immune responses. DCs exist in a range of distinct subpopulations including plasmacytoid DCs (pDCs) and classical DCs (cDCs), with the latter consisting of the cDC1 and cDC2 lineages. Although the roles of DC-specific transcription factors across the DC subsets have become understood, the posttranscriptional mechanisms that regulate DC development are yet to be elucidated. MicroRNAs (miRNAs) are pivotal posttranscriptional regulators of gene expression in a myriad of biological processes, but their contribution to the immune system is just beginning to surface. In this study, our in-house probe collection was screened to identify miRNAs possibly involved in DC development and function by targeting the transcripts of relevant mouse transcription factors. Examination of DC subsets from the culture of mouse bone marrow with Flt3 ligand identified high expression of miR-124 which was able to target the transcript of TCF4, a transcription factor critical for the development and homeostasis of pDCs. Further expression profiling of mouse DC subsets isolated from in vitro culture as well as via ex vivo purification demonstrated that miR-124 was outstandingly expressed in CD24+ cDC1 cells compared to in pDCs and CD172α+ cDC2 cells. These results imply that miR-124 is likely involved in the processes of DC subset development by posttranscriptional regulation of a transcription factor(s).
The advent of digital media has facilitated easy access for adolescents to environments conducive to the purchase of narcotics. In particular, there's an increasing trend in the purchase and consumption of narcotics mediated through Social Network Services (SNS) and messenger services. Adolescents, sensitive to such environments, are at risk of experiencing neurological and mental health issues due to narcotic addiction, increasing their exposure to criminal activities, hence necessitating national-level management and support. Consequently, the quest for sustainable treatment methods for adolescents exposed to narcotics emerges as a critical challenge. In the context of high relapse rates in narcotic addiction, the necessity for cost-effective and user-friendly treatment programs is emphasized. This study conducts a literature review aimed at utilizing digital platforms to create an environment where adolescents can voluntarily participate, focusing on the development of therapeutic content through art. Specifically, it reviews societal perceptions and treatment statuses of adolescent drug addiction, analyzes the impact of narcotic addiction on adolescent brain activity and cognitive function degradation, and explores approaches for developing digital therapeutics to promote the rehabilitation of the addicted brain through analysis of precedential case studies. Moreover, the study investigates the benefits that the integration of digital therapeutic approaches and art therapy can provide in the treatment process and proposes the possibility of enhancing therapeutic effects through various treatment programs such as drama therapy, music therapy, and art therapy. The application of art therapy methods is anticipated to offer positive effects in terms of tool expansion, diversification of expression, data acquisition, and motivation. Through such approaches, an enhancement in the effectiveness of treatments for adolescent narcotic addiction is anticipated. Overall, this study undertakes foundational research for the development of digital therapeutics and related applications, offering economically viable and sustainable treatment options in consideration of the societal context of adolescent narcotic addiction.
Su Min Ha;Hak Hee Kim;Eunhee Kang;Bo Kyoung Seo;Nami Choi;Tae Hee Kim;You Jin Ku;Jong Chul Ye
Journal of the Korean Society of Radiology
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v.83
no.2
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pp.344-359
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2022
Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.
Objectives: Pinelliae Rhizoma has traditionally been used as an anti-depressant in oriental medicine. This study is to investigate the effect of Pinelliae Rhizoma extract (PRe) on psychological stress in genome wild expression of mice. Methods: After giving physical stress to mice, PRe was orally administered with 100 mg/kg/day for five days. After extracting whole brain tissue from the mice, their genome changes were observed by micorarray analysis method. The genome changes were analyzed by IMAGENE 4.0, TREEVIEW, FatiGo algorithems, BOND database, cytoscape program, etc. Results: 1. PRe administered group were remained at normal level; 60% of increase was shown in expressed genes by physical stress, and 65% of decrease was shown in expressed genes by psychological stress. 2. Genes with increased expression in control group that remained at a normal state in PRe administered group were involved with the gene of a cellular metabolic process on biological process, protein binding on molecular function, and cell part on cell composition. The pathway was found to be cytokin-cytokin receptor interaction. 3. Genes with decreased expression in control group that remained at a normal state in PRe administered group were involved with the gene of a cellular metabolic process on biologiacl detail and coupled ATPaes activity on molecular function. This gene related path was Ubiquintin mediated proteolysis etc. 4. Core node genes analyzed by protein interaction network were Vinculin, Cell sdivision cycle 42 homolog (S. cerevisiae) etc. They played an important role in maintaining cytoskeleton and controlling cell cycle. Conclusions: Several genes were up-regulated and down-regulated in response to psychological stress. The expression of most of the genes that were altered in response to psychological stress was restored to normal levels in PRe treated mice. When the interaction network information was analyzed, the recovery of the core node genes in PRe treated mice indicates that this final set of genes may be the effective target of PRe.
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