• Journal of Veterinary Science
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• v.22 no.1
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• pp.7.1-7.13
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• 2021

Background: Niemann-Pick disease type C (NPC) is caused by the mutation of NPC genes, which leads to the abnormal accumulation of unesterified cholesterol and glycolipids in lysosomes. This autosomal recessive disease is characterized by liver dysfunction, hepatosplenomegaly, and progressive neurodegeneration. Recently, the application of induced neural stem cells (iNSCs), converted from fibroblasts using specific transcription factors, to repair degenerated lesions has been considered a novel therapy. Objectives: The therapeutic effects on NPC by human iNSCs generated by our research group have not yet been studied in vivo; in this study, we investigate those effects. Methods: We used an NPC mouse model to efficiently evaluate the therapeutic effect of iNSCs, because neurodegeneration progress is rapid in NPC. In addition, application of human iNSCs from NPC patient-derived fibroblasts in an NPC model in vivo can give insight into the clinical usefulness of iNSC treatment. The iNSCs, generated from NPC patientderived fibroblasts using the SOX2 and HMGA2 reprogramming factors, were transplanted by intracerebral injection into NPC mice. Results: Transplantation of iNSCs showed positive results in survival and body weight change in vivo. Additionally, iNSC-treated mice showed improved learning and memory in behavior test results. Furthermore, through magnetic resonance imaging and histopathological assessments, we observed delayed neurodegeneration in NPC mouse brains. Conclusions: iNSCs converted from patient-derived fibroblasts can become another choice of treatment for neurodegenerative diseases such as NPC.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.427-431
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• 2010

Multidimensional scaling (MDS) is a widely used method for dimensionality reduction, of which purpose is to represent high-dimensional data in a low-dimensional space while preserving distances among objects as much as possible. MDS has mainly been applied to data visualization and feature selection. Among various MDS methods, the classical MDS is not readily applicable to data which has large numbers of objects, on normal desktop computers due to its computational complexity. More precisely, it needs to solve eigenpair problems on dissimilarity matrices based on Euclidean distance. Thus, running time and required memory of the classical MDS highly increase as n (the number of objects) grows up, restricting its use in large-scale domains. In this paper, we propose an efficient approximation algorithm for the classical MDS based on divide-and-conquer and CUDA. Through a set of experiments, we show that our approach is highly efficient and effective for analysis and visualization of data consisting of several thousands of objects.

• YAKHAK HOEJI
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• v.51 no.6
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• pp.463-468
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• 2007

Chong Myung Tang is consisted of three medicinal herbs (Acori Graminei Rhizoma, Polygalae Radix and Hoelen cum Radix). It has been used as a medicine for the purpose of learning and memory improvement. In this paper, Chong Myung Tang was screened the biological activities for Alzheimer's disease. The extract (70% ethanol) of Acari Graminei Rhizoma (1 mg/ml) showed that acetylcholinesterase (AChE) and amyloid beta ($A{\beta}$) peptide aggregation inhibitory potency are 43.1% and 76.5%, respectively. The extract of Polygalae Radix showed inhibitory activity against $A{\beta}_{1-42}$ peptide aggregation (51.5%). To predict the drug-likeness, oral absorption ability; blood-brain barrier (BBB) penetraion rate, mutagenecity and carcinogenicity; in silico screening was performed against 16 compounds in the three medicinal herbs. According to the results, all compounds have appropriate chemical structures as medicines. The six compounds in Acori Graminei Rhizoma and the five compounds in Hoelen cum Radix showed excellent oral absorption rate and BBB penetration rate. The four compounds in Polygalae Radix showed excellent oral absorption rate, but their BBB penetration was presented low rate. And, the extract of Hoelen cum Radix didn't show AChE and $A{\beta}_{1-42}$ peptide aggregation inhibitory activities in vitro. Therefore, their activity in brain may be other mechanism. According to all of the results, in silico prediction technology is convenient and effective to determine biological active compounds in medicinal herbs.

• Toxicological Research
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• v.30 no.4
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• pp.267-276
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• 2014

Exposures to lead (Pb) are associated with neurological problems including psychiatric disorders and impaired learning and memory. Pb can be absorbed by iron transporters, which are up-regulated in hereditary hemochromatosis, an iron overload disorder in which increased iron deposition in various parenchymal organs promote metal-induced oxidative damage. While dysfunction in HFE (High Fe) gene is the major cause of hemochromatosis, the transport and toxicity of Pb in Hfe-related hemochromatosis are largely unknown. To elucidate the relationship between HFE gene dysfunction and Pb absorption, H67D knock-in Hfe-mutant and wild-type mice were given drinking water containing Pb 1.6 mg/ml ad libitum for 6 weeks and examined for behavioral phenotypes using the nestlet-shredding and marble-burying tests. Latency to nestlet-shredding in Pb-treated wild-type mice was prolonged compared with non-exposed wild-types (p < 0.001), whereas Pb exposure did not alter shredding latency in Hfe-mutant mice. In the marble-burying test, Hfe-mutant mice showed an increased number of marbles buried compared with wild-type mice (p = 0.002), indicating more repetitive behavior upon Hfe mutation. Importantly, Pb-exposed wild-type mice buried more marbles than non-exposed wild-types, whereas the number of marbles buried by Hfe-mutant mice did not change whether or not exposed to Pb. These results suggest that Hfe mutation could normalize Pb-induced behavioral alteration. To explore the mechanism of repetitive behavior caused by Pb, western blot analysis was conducted for proteins involved in brain dopamine metabolism. The levels of tyrosine hydroxylase and dopamine transporter increased upon Pb exposure in both genotypes, whereas Hfe-mutant mice displayed down-regulation of the dopamine transporter and dopamine D1 receptor with D2 receptor elevated. Taken together, our data support the idea that both Pb exposure and Hfe mutation increase repetitive behavior in mice and further suggest that these behavioral changes could be associated with altered dopaminergic neurotransmission, providing a therapeutic basis for psychiatric disorders caused by Pb toxicity.

• Biomolecules & Therapeutics
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• v.20 no.4
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• pp.357-370
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• 2012

Radiation therapy, the most commonly used for the treatment of brain tumors, has been shown to be of major significance in tumor control and survival rate of brain tumor patients. About 200,000 patients with brain tumor are treated with either partial large field or whole brain radiation every year in the United States. The use of radiation therapy for treatment of brain tumors, however, may lead to devastating functional deficits in brain several months to years after treatment. In particular, whole brain radiation therapy results in a significant reduction in learning and memory in brain tumor patients as long-term consequences of treatment. Although a number of in vitro and in vivo studies have demonstrated the pathogenesis of radiation-mediated brain injury, the cellular and molecular mechanisms by which radiation induces damage to normal tissue in brain remain largely unknown. Therefore, this review focuses on the pathophysiological mechanisms of whole brain radiation-induced cognitive impairment and the identification of novel therapeutic targets. Specifically, we review the current knowledge about the effects of whole brain radiation on pro-oxidative and pro-inflammatory pathways, matrix metalloproteinases (MMPs)/tissue inhibitors of metalloproteinases (TIMPs) system and extracellular matrix (ECM), and physiological angiogenesis in brain. These studies may provide a foundation for defining a new cellular and molecular basis related to the etiology of cognitive impairment that occurs among patients in response to whole brain radiation therapy. It may also lead to new opportunities for therapeutic interventions for brain tumor patients who are undergoing whole brain radiation therapy.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.76-84
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• 2022

In this paper, in order to compose the visual perception cognitive function training content that can be linked with the IPUZZLE image block, an interactive content device that utilizes photos and videos of smartphones. Four areas of visual memory, visual continuity, spatial relationship, and visual discrimination were derived and the content operation, application method, and scenario were written. It was intended to continuously give and induce children's desire to participate in training by designing the content image and developing the existing learning terrain visual and perceptual cognitive function training materials in the form of mobile mini-games. Experiential activities were conducted for general children and their guardians using the developed contents, and the results were found to be significant in terms of concentration, effect, and effect compared to basic puzzle toys. It is expected that this thesis will be a meaningful data for the study of cognitive function improvement activities based on digital toys and contents.

• The Korean Journal of Physiology and Pharmacology
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• v.9 no.5
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• pp.263-268
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• 2005

Striatum has important roles in motor control, habitual learning and memory. It receives glutamatergic inputs from neocortex and thalamus, and dopaminergic inputs from substantia nigra. We examined effects of dopamine (DA) on the corticostriatal synaptic transmission using in vitro extracellular recording technique in rat brain corticostriatal slices. Synaptic responses were elicited by stimulation of cortical glutamatergic inputs on the corpus callosum and recorded in the dorsal striatum. Corticostriatal population spike (PS) amplitudes were decreased ($39.4{\pm}7.9$%) by the application of $100{\mu}M$ DA. We applied receptor subtype specific agonists and antagonists and characterized the modulation of corticostriatal synaptic transmission by different DA receptor subtypes. $D_2$ receptor agonist (quinpirole), antagonist (sulpiride), and $D_1$ receptor antagonist (SKF 83566), but not $D_1$ receptor agonist (SKF 38393), induced significantly the reduction of striatal PS. Pretreatment neither with SKF 83566 nor sulpiride significantly affected corticostriatal synaptic inhibition by DA. However, the inhibition of DA was completely blocked by pretreatment with mixed solution of both SKF 83566 and sulpiride. These results suggest that DA inhibits corticostriatal synaptic transmission through both $D_1$ and $D_2$ receptors in concert with each other.

• CELLMED
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• v.11 no.1
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• pp.2.1-2.8
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• 2021

The clinical condition Amnesia causes difficulty in learning new information and the inability to recall past events. It is primarily concerned with recent memory loss. Majoon-e-Nisyan (MJN) is a polyherbal Unani formulation, present in a semi-solid form. It is widely used potent drug of the Unani System of Medicine (USM) for treating Nisyan (amnesia). In the present study polyherbal Unani formulation, MJN has been studied for its quality control and acute toxicity. Standardization (quality control) of drugs deals with drug identity, drug quality and purity determination. Standardization of MJN had been done as per the Unani pharmacopoeial parameters approved by World Health Organization (WHO) - Pharmacognostical parameters, Physico-chemical parameters, high-performance thin-layer chromatography (HPTLC), microbial load, aflatoxin, and heavy metals. Solvents and chemicals used in the study were of analytical grade and used instrument were calibrated. By conducting an acute oral toxicity study in rats, the safety of MJN was assessed. The limit test method of OECD guideline 425 was followed in the study. Results of standardization and standard operating procedures (SOPs) for preparation of MJN may serve as the standard reference in the future. The data generated in the study for the quality control of MJN proved the quality of formulation and shows that MJN is not toxic in rats following acute dosing up to 2000 mg/kg bw. The data obtained in the paper for MJN may be used as a standard guideline for preparation of the formulation which can save time, cost, and resources for future research endeavours.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1224-1230
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• 2020

Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.