• The Korean Journal of Physiology and Pharmacology
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• 제25권2호
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• pp.147-157
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• 2021

Coronary microembolization (CME) is associated with cardiomyocyte apoptosis and cardiac dysfunction. Puerarin confers protection against multiple cardiovascular diseases, but its effects and specific mechanisms on CME are not fully known. Hence, our study investigated whether puerarin pretreatment could alleviate cardiomyocyte apoptosis and improve cardiac function following CME. The molecular mechanism associated was also explored. A total of 48 Sprague-Dawley rats were randomly divided into CME, CME + Puerarin (CME + Pue), sham, and sham + Puerarin (sham + Pue) groups (with 12 rats per group). A CME model was established in CME and CME + Pue groups by injecting 42 ㎛ microspheres into the left ventricle of rats. Rats in the CME + Pue and sham + Pue groups were intraperitoneally injected with puerarin at 120 mg/kg daily for 7 days before operation. Cardiac function, myocardial histopathology, and cardiomyocyte apoptosis index were determined via cardiac ultrasound, hematoxylin-eosin (H&E) and hematoxylin-basic fuchsin-picric acid (HBFP) stainings, and TdT-mediated dUTP nick-end labeling (TUNEL) staining, respectively. Western blotting was used to measure protein expression related to the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/glycogen synthase kinase-3β (GSK-3β) pathway. We found that, puerarin significantly ameliorated cardiac dysfunction after CME, attenuated myocardial infarct size, and reduced myocardial apoptotic index. Besides, puerarin inhibited cardiomyocyte apoptosis, as revealed by decreased Bax and cleaved caspase-3, and up-regulated Bcl-2 and PI3K/Akt/GSK-3β pathway related proteins. Collectively, puerarin can inhibit cardiomyocyte apoptosis and thus attenuate myocardial injury caused by CME. Mechanistically, these effects may be achieved through activation of the PI3K/Akt/GSK-3β pathway.

• Journal of Multimedia Information System
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• 제3권3호
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• pp.97-102
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• 2016

Deep learning enables machines to have perception and can potentially outperform humans in the medical field. It can save a lot of time and reduce human error by detecting certain patterns from medical images without being trained. The main goal of this paper is to build the optimal model for breast mass classification by applying various methods that influence the performance of Convolutional Neural Network (CNN). Google's newly developed software library Tensorflow was used to build CNN and the mammogram dataset used in this study was obtained from 340 breast cancer cases. The best classification performance we achieved was an accuracy of 0.887, sensitivity of 0.903, and specificity of 0.869 for normal tissue versus malignant mass classification with augmented data, more convolutional filters, and ADAM optimizer. A limitation of this method, however, was that it only considered malignant masses which are relatively easier to classify than benign masses. Therefore, further studies are required in order to properly classify any given data for medical uses.

• BMB Reports
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• 제56권6호
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• pp.353-358
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• 2023

In the present study, to determine the efficacy of oral supplementation of ginseng berry extracts in augmenting exercise performance and exercise-associated metabolism, male mice were given orally 200 and 400 mg/kg of body weight (BW) of GBC for nine weeks. Although there are no differences in pre-exercise blood lactate levels among (1) the control group that received neither exercise nor GBC, (2) the group that performed only twice-weekly endurance exercise, and (3) and (4) the groups that combined twice-weekly endurance exercise with either 200 or 400 mg/kg GBC, statistically significant reductions in post-exercise blood lactate levels were observed in the groups that combined twice-weekly endurance exercise with oral administration of either 200 or 400 mg/kg GBC. Histological analysis showed no muscle hypertrophy, but transcriptome analysis revealed changes in gene sets related to lactate metabolism and mitochondrial function. GBC intake increased nicotinamide adenine dinucleotide levels in the gastrocnemius, possibly enhancing the mitochondrial electron transport system and lactate metabolism. Further molecular mechanisms are needed to confirm this hypothesis.

• Parasites, Hosts and Diseases
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• 제59권2호
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• pp.113-119
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• 2021

The computer vision diagnostic approach currently generates several malaria diagnostic tools. It enhances the accessible and straightforward diagnostics that necessary for clinics and health centers in malaria-endemic areas. A new computer malaria diagnostics tool called the malaria scanner was used to investigate living malaria parasites with easy sample preparation, fast and user-friendly. The cultured Plasmodium parasites were used to confirm the sensitivity of this technique then compared to fluorescence-activated cell sorting (FACS) analysis and light microscopic examination. The measured percentage of parasitemia by the malaria scanner revealed higher precision than microscopy and was similar to FACS. The coefficients of variation of this technique were 1.2-6.7% for Plasmodium knowlesi and 0.3-4.8% for P. falciparum. It allowed determining parasitemia levels of 0.1% or higher, with coefficient of variation smaller than 10%. In terms of the precision range of parasitemia, both high and low ranges showed similar precision results. Pearson's correlation test was used to evaluate the correlation data coming from all methods. A strong correlation of measured parasitemia (r²=0.99, P<0.05) was observed between each method. The parasitemia analysis using this new diagnostic tool needs technical improvement, particularly in the differentiation of malaria species.

• Annals of Geriatric Medicine and Research
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• 제22권4호
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• pp.157-158
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• 2018

• IMMUNE NETWORK
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• 제20권1호
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• pp.4.1-4.17
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• 2020

Tregs have a role in immunological tolerance and immune homeostasis by suppressing immune reactions, and its therapeutic potential is critical in autoimmune diseases and cancers. There have been multiple studies conducted on Tregs because of their roles in immune suppression and therapeutic potential. In tumor immunity, Tregs can promote the development and progression of tumors by preventing effective anti-tumor immune responses in tumor-bearing hosts. High infiltration of Tregs into tumor tissue results in poor survival in various types of cancer patients. Identifying factors specifically expressed in Tregs that affect the maintenance of stability and function of Tregs is important for understanding cancer pathogenesis and identifying therapeutic targets. Thus, manipulation of Tregs is a promising anticancer strategy, but finding markers for Treg-specific depletion and controlling these cells require fine-tuning and further research. Here, we discuss the role of Tregs in cancer and the development of Treg-targeted therapies to promote cancer immunotherapy.

• 환경생물
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• 제35권4호
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• pp.427-436
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• 2017

두 개의 딸기 온실 (농약살포포장, 천적방사포장)에서 점박이응애(Tetranychus urticae Koch)의 고정 정확도 수준에서 표본조사법 (Fixed-precision sampling plan)을 개발하였다. 표본추출은 조사구역당 3개엽으로 이루어진 복엽 1줄기를 기준으로 하여 3줄기를 채취하였다. 각 복엽은 Relative net precision (RNP) 값을 비교하기 위해 3개의 서로 다른 단위(1엽, 2엽, 3엽)로 나뉘어졌다. RNP 값 결과 1엽 단위가 다른 단위들보다 정확도와 효율적인 면에서 우수했다. 공간분포 분석은 Taylor's power law (TPL)를 이용하였으며, 각 딸기 온실별로 계산된 TPL 계수의 동질성검정에는 공분산분석(ANCOVA)을 이용하였으며, 분석결과 차이를 보이지 않았다. 표본추출 정시선을 구하기 위한 TPL 계수는 농약살포포장과 천적방사포장의 딸기 1엽 단위에서 점박이응애 밀도 자료를 합한 뒤 재계산하여 사용하였다. 그리고 점박이응애 발생밀도수준을 3마리와 10마리로 설정하여 방제의사를 결정하였다. 분석에 사용하지 않은 독립된 자료를 이용하여 개발된 표본추출법의 유효성을 Resampling Validation for sampling plan (RVSP)으로 확인한 결과 적합한 정확도를 보였다.

• Journal of Korean Neurosurgical Society
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• 제66권1호
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• pp.53-62
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• 2023

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.

• Journal of Gastric Cancer
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• 제19권3호
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• pp.235-253
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• 2019

Gastric cancer (GC) is one of the deadliest malignancies in the world. Currently, clinical treatment decisions are mostly made based on the extent of the tumor and its anatomy, such as tumor-node-metastasis staging. Recent advances in genome-wide molecular technology have enabled delineation of the molecular characteristics of GC. Based on this, efforts have been made to classify GC into molecular subtypes with distinct prognosis and therapeutic response. Simplified algorithms based on protein and RNA expressions have been proposed to reproduce the GC classification in the clinical field. Furthermore, a recent study established a single patient classifier (SPC) predicting the prognosis and chemotherapy response of resectable GC patients based on a 4-gene real-time polymerase chain reaction assay. GC patient stratification according to SPC will enable personalized therapeutic strategies in adjuvant settings. At the same time, patient-derived xenografts and patient-derived organoids are now emerging as novel preclinical models for the treatment of GC. These models recapitulate the complex features of the primary tumor, which is expected to facilitate both drug development and clinical therapeutic decision making. An integrated approach applying molecular patient stratification and patient-derived models in the clinical realm is considered a turning point in precision medicine in GC.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.704-708
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• 2004

The RMD(Rehabilitation Medicine Device) with CJM(Compound Joint Motion) is the lower limb unit muscular strengthening promotion rehabilitation medicine device for patients of joint orthopedic operation or the deficient elder of ability to walk, the handicapped. Since the products for the rehabilitation medicine device have limited to the simplicity linear motion, those do not give efficient the lower unit muscular strengthening effects. This device which was under the development gives to exercise of hip joint and knee joint with user's selection at once, get out of the simplicity linear motion. Also it will be contributed to a field of rehabilitation medicine and a mobility aid technology of the deficient elders of ability to walk, the handicapped.