• Parasites, Hosts and Diseases
• /
• v.49 no.4
• /
• pp.349-356
• /
• 2011

The existence of symbiotic relationships between Acanthamoeba and a variety of bacteria is well-documented. However, the ability of Acanthamoeba interacting with host bacterial pathogens has gained particular attention. Here, to understand the interactions of Escherichia coli K1 and E. coli K5 strains with Acanthamoeba castellanii trophozoites and cysts, association assay, invasion assay, survival assay, and the measurement of bacterial numbers from cysts were performed, and nonpathogenic E. coli K12 was also applied. The association ratio of E. coli K1 with A. castellanii was 4.3 cfu per amoeba for 1 hr but E. coli K5 with A. castellanii was 1 cfu per amoeba for 1 hr. By invasion and survival assays, E. coli K5 was recovered less than E. coli K1 but still alive inside A. castellanii. E. coli K1 and K5 survived and multiplied intracellularly in A. castellanii. The survival assay was performed under a favourable condition for 22 hr and 43 hr with the encystment of A. castellanii. Under the favourable condition for the transformation of trophozoites into cysts, E. coli K5 multiplied significantly. Moreover, the pathogenic potential of E. coli K1 from A. castellanii cysts exhibited no changes as compared with E. coli K1 from A. castellanii trophozoites. E. coli K5 was multiplied in A. castellanii trophozoites and survived in A. castellanii cysts. Therefore, this study suggests that E. coli K5 can use A. castellanii as a reservoir host or a vector for the bacterial transmission.

• Fire Science and Engineering
• /
• v.30 no.6
• /
• pp.92-98
• /
• 2016

This study evaluated thermal image real-time estimation and fire alarm using by a CCD camera, which has been a seamless feature-point analysis method, according to the angle and position and image fusion by a vector coordinate point set-up of equal shape. The system has higher accuracy, fixing data value of temperature sensing and fire image of 0~255, and sensor output-value of 0~5,000. The operation time of a flame specimen within 500 m, 1000 m, and 1500 m from the test report specimen took 7 s, 26 s, and 62 s, respectively, and image creation was proven. A diagnosis of fire accident was designated to 3 steps: Caution/Alarm/Fire. Therefore, a series of process and the transmission of SNS were identified. A light bulb and fluorescent bulb were also tested for a false alarm test, but no false alarm occurred. The possibility that an unwanted alarm will be reduced was verified through a forecast of the fire progress or real-time estimation of a thermal image by the change in the image of a time-based flame and an analysis of the diffusion velocity.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.28 no.3
• /
• pp.496-503
• /
• 2001

Maxilla overgrowth who diagnosis with skeletal Class II division 1 have transverse and also sagittal problem. If maxillary growth vector is direction to anterior inferior, mandible is rotation to clockwise pattern and it disturbance it's anterior growth. At this time, treatment goal is restrict of maxillary growth to accomplish ideal intermaxillary relation and one of treatment choice is the application of extraoral force. This report is 3 case treated by activator and headgear combination therapy, who diagnosed with skeletal Class II div. 1 malocclusion.

• Genomics & Informatics
• /
• v.4 no.4
• /
• pp.161-166
• /
• 2006

The establishment of DNA microarray technology has enabled high-throughput analysis and molecular profiling of various types of cancers. By using the gene expression data from microarray analysis we are able to investigate diagnostic applications at the molecular level. The most important step in the application of microarray technology to cancer diagnostics is the selection of specific markers from gene expression profiles. In order to select markers of Immortalization and transformation we used c-myc and $H-ras^{V12}$ oncogene-transfected NIH3T3 cells as our model system. We have identified 8751 differentially expressed genes in the immortalization/transformation model by multivariate permutation F-test (95% confidence, FDR<0.01). Using the support vector machine algorithm, we selected 13 discriminative genes which could be used to predict immortalization and transformation with perfect accuracy. We assayed $H-ras^{V12}$-transfected 'transformed' cells to validate our immortalization/transformation dassification system. The selected molecular markers generated valuable additional information for tumor diagnosis, prognosis and therapy development.

• Korean Journal of Veterinary Research
• /
• v.40 no.1
• /
• pp.86-93
• /
• 2000

Paratuberculosis (Johne's disease), a chronic enteritis produced by Mycobacterium paratuberculosis, affects a large proportion of ruminants in all continents and causes important economic losses. The identification of well-characterized and species-specific components of M paratuberculosis would provide the means to improve the specificity and sensitivity of immunodiagnostic assays for Johne's disease. The aims of this study were to express the recombinant C-terminal of 34kDa protein (rC34P) of M paratuberculosis in E coli and to investigate the effectiveness of this protein in detecting antibodies to the native protein in sera from paratuberculosis infected cattle. The C-terminal of the gene encoding the 34kDa protein was amplified by polymerase chain reaction from the chromosomal DNA of M paratuberculosis (ATCC 19698) and cloned into vector pGEX-4T-2. Then, cloned plasmid was transformed into E coli DH5${\alpha}$ and the rC34P was overexpressed. The rC34P was purified by affinity chromatography and gel filtration. The rC34P was examined antigenicity by Western blot. The rC34P was reactive with culture positive bovine serum and hyperimmune rabbit anti-M paratuberculosis serum but was not reactive with culture negative bovine serum and tuberculin positive bovine serum in Western blot. In conclusion, the rC34P produced in this study is expected as a useful candidate for antigen in serological diagnosis of Johne's disease.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.10
• /
• pp.2163-2170
• /
• 2009

We present an automated, energy minimized-based method for Lung parenchyma segmenting Chest Computed Tomography(CT) datasets. Deformable model is used for energy minimized segmentation. Quantitative knowledge including expected volume, shape of Chest CT provides more feature constrain to diagnosis or surgery operation planning. Segmentation subdivides an lung image into its consistent regions or objects. Depends on energy-minimizing, the level detail image of subdivision is carried. Segmentation should stop when the objects or region of interest in an application have been detected. The deformable model that has attracted the most attention to date is popularly known as snakes. Snakes or deformable contour models represent a special case of the general multidimensional deformable model theory. This is used extensively in computer vision and image processing applications, particularly to locate object boundaries, in the mean time a new type of external force for deformable models, called gradient vector flow(GVF) was introduced by Xu. Our proposed algorithm of deformable model is new external energy of GVF for exact segmentation. In this paper, Clinical material for experiments shows better results of proposal algorithm in Lung parenchyma segmentation on Chest CT.

• Journal of Biomedical Engineering Research
• /
• v.40 no.2
• /
• pp.62-67
• /
• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Biomedical Science Letters
• /
• v.25 no.1
• /
• pp.99-106
• /
• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• Parasites, Hosts and Diseases
• /
• v.56 no.6
• /
• pp.559-565
• /
• 2018

The identification and characterization of pathogenic and zoonotic tick-borne diseases like granulocytic anaplasmosis are essential for developing effective control programs. The differential diagnosis of pathogenic Anaplasma phagocytophilum and non-pathogenic A. phagocytophilum-like Anaplasma spp. is important for implementing effective treatment from control programs. The objective of the present study was to investigate the prevalence of Anaplasma spp. in horses in Korea by nucleotide sequencing and restriction enzyme fragment length polymorphism assay. Of the 627 horses included in the study, only 1 (0.2%) was infected with A. phagocytophilum. Co-infection with A. phagocytophilumlike Anaplasma spp. was not detected in the study. The 16S rRNA sequence of A. phagocytophilum was similar (99.5-100%) to A. phagocytophilum 16S rRNA isolated from horses in other countries. PCR adapted to amplify A. phagocytophilum groEL and msp2 genes failed to generate amplicons, suggesting genetic diversity in these genes. This study is the first molecular detection of A. phagocytophilum in horses in Korea. Human granulocytic anaplasmosis and animal infection of A. phagocytophilum have been reported in Korea recently. Because of vector tick distribution, global warming, and the increase of the horse industry, horses should be considered as a potential reservoir for A. phagocytophilum, and cross infectivity should be evaluated even though a low prevalence of infection was detected in this study. Furthermore, continuous surveillance and effective control measures for A. phagocytophilum should be established to prevent disease distribution and possible transmission to humans.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.7
• /
• pp.1088-1097
• /
• 2021

Vibration data of mechanical equipment inevitably have noise. This noise adversely af ects the maintenance of mechanical equipment. Accordingly, the performance of a learning model depends on how effectively the noise of the data is removed. In this study, the noise of the data was removed using the Denoising Auto Encoder (DAE) technique which does not include the characteristic extraction process in preprocessing time series data. In addition, the performance was compared with that of the Wavelet Transform, which is widely used for machine signal processing. The performance comparison was conducted by calculating the failure detection rate. For a more accurate comparison, a classification performance evaluation criterion, the F-1 Score, was calculated. Failure data were detected using the One-Class SVM technique. The performance comparison, revealed that the DAE technique performed better than the Wavelet Transform technique in terms of failure diagnosis and error rate.